ph.d. thesis at imperial college london

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The Influence of Psychological Intervention upon

Psycho-Neuro-Endocrino-Immune Network

A thesis submitted for the award of

Doctor of Philosophy (Ph.D.)

Imperial College, Faculty of Medicine, London

Akira NAITO M.D.

August 2006

Imperial College London

Faculty of Medicine

Division of Neuroscience and Mental Health

Charing Cross Campus

St. Dunstan’s Road, London W6 8RP

and

Department of Immunology

Chelsea and Westminster Campus

369 Fulham Road, London SW10 9NH

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This thesis is dedicated to my father:

Nagayoshi NAITO

1940 - 2006

My role model and mentor

who taught me the importance of being myself

and passed away at the end of my Ph.D. course.

I thank him for his truthfulness, warm understanding and spiritual support.

Cyclamen

(31 January 2006)

The last piece of work in his private life with my mother, Masako

Psychological intervention and psycho-neuro-endocrino-immune network. Akira NAITO

Ph.D. at University of London - 3 - Imperial College London

Abstract

A growing body of evidence suggests that there are cross regulatory influences between

the psychological, neurological, endocrinological and immunological systems. This has led to

the proposal of a psycho-neuro-endocrino-immune network, in which a change in one part has

consequential influences upon other parts of the network. Thus psychological stress can also

affect physical well-being through the network.

This thesis is based on the hypothesis that the detrimental effects of stress upon the

network can be alleviated by psychological intervention. The aim of this project is to examine

whether learning and practising stress-management skills improves psychological and physical

well-being.

An in vivo study using university students confirmed that examination stress provokes

anxiety and increases stress, and that stress perception was associated with NK-cell function.

Immune alterations were observed in vitro when NK-cells and lymphocytes were exposed to

stress hormones. Another in vivo study using HIV-infected patients not receiving anti-retroviral

treatments confirmed that there is a steady decline in CD4 T-lymphocyte counts, and that this

decline was associated with declines in quality-of-life scores.

The psychological interventions used in the project, self-hypnosis and Johrei, aimed to

provide alternative perspectives of, and unique self-help coping strategies for, stressful life

events. These, particularly Johrei, were shown to alleviate or even to reverse the effects of stress

upon the immune system, including a decrease in NK-cells in university students and the

decline of CD4 T-lymphocytes in HIV-infected patients. Neither intervention affected stress

perception significantly, although Johrei appeared to improve the quality-of-life scores.

These findings support the a priori hypothesis that psychological intervention may

counteract the detrimental effects of stress on health and promote well-being, and suggest this

via meaning-focused coping. These warrant the need for further research to explore the inter-

dependent relationships amongst the integrated psycho-neuro-endocrino-immune network, and

the influence of Johrei upon the network.



Contents Page Abstract 3

List of Figures 6

List of Tables 9

List of Text boxes 14

Abbreviations 15

Acknowledgements 16

Chapter I Introduction

Contents of chapter I 18

1.1 Project overview 19

1.2 Theoretical framework 22

1.3 Approach taken 49

Chapter II Materials and Methods

Contents of chapter II 51

2.1 Participants with regard to outcomes and measurement time points 53

2.2 Psychological intervention 60

2.3 Self-report questionnaires 63

2.4 Materials and methods in vitro 65

2.5 Statistical analyses 77

Chapter III Results

Contents of chapter III 79

3.1 The influence of psychological intervention upon stress-related changes

in university students facing academic examinations 83

3.2 The influence of psychological intervention upon perceived stress and

quality-of-life and various immunological disease-associated

parameters in HIV-infected individuals 102

3.3 In vitro investigation into the effect of exposure to stress hormones

upon Natural Killer cells 128

3.4 In vitro investigation into the effect of exposure to stress hormones

upon T-lymphocytes 151



Chapter IV Discussion

Contents of chapter IV 171

4.1 The influence of psychological intervention upon sustained stress and

stress-associated changes in university students facing exams and in

patients with HIV-infection 173

4.2 Stress hormone associated changes in vitro in immune cells as an

exemplar of the psycho-neuro-endocrino-immune network interaction 191

4.3 Conclusion 198

4.4 Future directions 199

References 200

Appendices

A-1. Ethics approval, information sheet and consent form 214

A-2. Psychological training intervention protocols 226

i. Self hypnosis training 227

ii. Johrei training 253

A-3. Questionnaires 286

� Stress perception (STAI , IES and PSS) 287

� Quality of Life and sleep quality (LoC, MCS and PSQI) 290

A-4. Standard operating procedures (SOPs) for laboratory methods 296

� [3H]-thymidine incorporation using whole blood for proliferation assay 296

� Flowcytometry analysis of proliferation response in whole blood assay protocol

298

� NK cell cytotoxic activity assay by flow cytometry 300

A-5. Papers 304

i. Peer reviewed publications 304

ii. Presentation and workshop given 305

iii. Supervisor for research students 307

A-6. Additional results 308

A-7. Research proposal for post-doctorial project 316



List of Figures

Figure 1: A typical Natural Killer cell

Figure 2: Schema of the neuro-endocrino-immune interaction

Figure 3: Numbers of students recruited and remaining in the study at the Exam and Non-exam

assessment time points. The number of drop-out students is also indicated.

Figure 4: Timing of the Exam and Non-exam assessment time points with respect to recruitment for

individual students in the Cohorts A and B

Figure 5: Timing of training, follow-ups and data-collection sessions (Baseline and Exams assessment

points) and numbers of students at the sessions

Figure 6: Timing of the measurement collection time points (Recruitment and After 4 months) and the

one-month blocks (Baseline, Term one to Term four) for clinical routine blood collections

Figure 7: Timing of the two measurement points (Recruitment and Post-intervention) with regard to the

period of training and practice of the psychological interventions

Figure 8: Time-points (Training time point and the Terms according to the Training). Intervals between

the doted-lines represent one term (one month)

Figure 9: Comparison format with regard to the Training time point (Pre-intervention vs. Post-

intervention). Intervals between dot-lines represent one term (one month) as in Figure 8

Figure 10: FSC vs. SSC dot plot

Figure 11: Individual cortisol levels in the tissue culture medium and in plasma from 34 volunteers

Figure 12: K562 cell growth at starting cell concentrations of 1.5x104, 1.5x105 and 1.0x106 cells per mL

Figure 13: Acquision settings of a flow cytometry method measuring the levels of NK cytotoxic activity

Figure 14: Acquision settings of the flow cytometer in the NCR analyses

Figure 15: Acquision settings of the flow cytometer in the Annexin V- PI analysis

Figure 16: Mean (95% C.I.) PSS scores at the Non-exam and Exam time points

Figure 17: Mean (95% C.I.) State anxiety scores in the STAI at the Non-exam and Exam time points

Figure 18: Mean (95% C.I.) NK-cell percentages in male and female students

Figure 19: Mean (95% C.I.) NKCA (% killing) in the Not-stressed and Stressed subgroups

Figure 20: Mean (95% C.I.) NKCA levels (% killing) in the Not-stressed and Stressed male students

Figure 21: Mean (95% C.I.) per-NK-cell cytotoxic activity (calculated as a ratio: NK cytotoxic activity

(NKCA) / NK-cell percentage (NKC%)) in the Not-stressed and Stressed subgroups

Figure 22: Mean (95% C.I.) per-NK-cell cytotoxic activity (calculated as a ratio: NKCA / NK-cell

percentage) in the Not-stressed and Stressed male students

Figure 23: Mean (95% C.I.) CD4 T-cell levels (%) of male and female students

Figure 24: Mean (95% C.I.) State anxiety scores in the STAI of the three groups at baseline and the

Exam time point

Figure 25: Mean (95% C.I.) levels of NK-cells of the three groups at baseline and the Exam time point

Figure 26: The individual levels of NK-cell percentages in the three groups at baseline and the Exam

time point



Figure 27: Mean (95% C.I.) levels of CD4 T-cells of the three groups at baseline and the Exam time

point

Figure 28: The individual levels of CD4 T-cell percentages in the three groups at baseline and the Exam

time point

Figure 29: Mean (95% C.I.) levels of CD8 T-cells of the three groups at baseline and the Exam time

point

Figure 30: The individual levels of CD8 T-cell percentages in the three groups at baseline and the Exam

time point

Figure 31: Mean (95% C.I.) PSS levels of the Not-stressed and Stressed subgroups at recruitment and

four months later

Figure 32: Mean (95% C.I.) levels of the State anxiety scores in the STAI of the Not-stressed and Stress

subgroups at recruitment and four months later

Figure 33: Mean (95% C.I.) levels of the IES in the Not-stressed and Stress subgroups at recruitment and

four months later

Figure 34: Mean (95% C.I.) levels of the LoC in the Not-stressed and Stressed subgroups at recruitment

and four months later

Figure 35: Mean (95% C.I.) levels of the MSC in the Not-stressed and Stressed subgroups at recruitment


Figure 36: Mean (95% C.I.) levels of the PSQI in the Stress and Not-stressed subgroups at recruitment


Figure 37: Mean (95% C.I.) CD4 gradients (cells per �l per month) in the Increased control (decreased

scores of the LoC) and Decreased control (increased scores of the LoC) subgroups

Figure 38: Mean (95% C.I.) CD4 gradients (cells per �l per month) in the Improved psychological

functioning (Improved QoL: increased scores of the MCS) and Decreased psychological

functioning (Decreased QoL: decreased scores of the MCS) subgroups

Figure 39: Mean (95% C.I.) CD4 gradients (cells per �l per month) in the Improved sleep quality

(decreased scores of the PSQI) and Decreased sleep quality (increased scores of the PSQI)

subgroups

Figure 40: Means (95% C.I.) CD4 gradients over the five months study period from the Baseline to the

Post-intervention time point

Figure 41: CD4 gradients of one control subject at the Pre-intervention and Post-intervention periods

Figure 42: CD4 gradients of one Johrei subject at the Pre-intervention and Post-intervention periods

Figure 43: Individual changes in CD4 gradients (cell counts per �l per month) in the Self-hypnosis,

Johrei and Database-control groups between the Pre-intervention and Post-intervention

periods

Figure 44: Means (95% C.I.) CD4 gradients (count per �l per month) in the Self-hypnosis and Johrei and

Database-control groups in the Pre- and Post- intervention periods

Figure 45: (a) Individual (b) Mean (95% C.I.) NKCA levels at Time 0 and after 24hour incubation



Figure 46: (a) Individual (b) Mean (95% C.I.) NK-cell percentage in PBMCs at Time 0 and after 24hours

Figure 47: (a) Individual (b) Mean (95% C.I.) NKCA levels with cortisol at 0, 250 and 2500nM

Figure 48: (a) Individual (b) Mean (95% C.I.) NK-cell percentage with cortisol at 0, 250 and 2500nM

Figure 49: Correlation between flow-cytometry method and LDH-releasing method of the NKCA

Figure 50: (a) Individual (b) Mean (95% C.I.) NKCA (50:1) levels (% killing) at Time 0 and after 24hrs

Figure 51: (a) Individual (b) Mean (95% C.I.) NKCA (25:1) levels (% killing) at Time 0 and after 24hrs

Figure 52: Percentages of NK-cell in total and each subset at Time 0 and after 24 hours incubation

Figure 53: (a) Individual (b) Mean (95% C.I.) Nkp46 (m.f.i.) at Time 0 and after 24hrs incubation

Figure 54: (a) Individual (b) Mean (95% C.I.) Nkp30 (m.f.i.) at Time 0 and after 24hrs incubation

Figure 55: (a) Individual (b) Mean (95% C.I.) NKCA (50:1) levels(% killing) of PBMCs incubated with

or without cortisol

Figure 56: (a) Individual (b) Mean (95% C.I.) NKCA (25:1) levels(% killing) of PBMCs incubated with

or without cortisol

Figure 57: Mean (95% C.I.) of the NKCA at Time 0 and after 24hrs incubation of PBMCs with/out

250nM cortisol in the target: effector ratio of 25:1

Figure 58: Correlations between the changes and differences of the NKCA (% killing: between at Time 0

and after 24hrs incubation of PBMCs with/out 250nM cortisol in the ratio of 25:1

Figure 59: Percentages of NK-cell in total and each subset in the PBMCs after 24hours incubation with

and without 250nM cortisol

Figure 60: (a) Individual (b) Mean (95% C.I.) Nkp46 (m.f.i.) after 24hrs incubation of PBMCs with/out

cortisol

Figure 61: (a) Individual (b) Mean (95% C.I.) Nkp30 (m.f.i.) after 24hrs incubation of PBMCs with/out

cortisol

Figure 62: Mean (95% C.I.) and individual expression of Nkp46 (m.f.i.) on the cytotoxic NK-cells

(CD56dimCD16+) at Time 0 and after 24hrs incubation of PBMCs with/out 250nM cortisol

Figure 63: Mean (95% C.I.) and individual level of NKCA at Time 0 and after 24hrs incubation of

PBMCs with/out 250nM cortisol at target: effector ratio of 25:1

Figure 64: Groups defined by tertiary split of the NKCA levels after 24 hours incubation

Figure 65: Mean (95% C.I.) plasma levels of cortisol in the High, intermediate (Mid) and Low NKCA

level groups after 24 hours incubation

Figure 66: Mean (95% C.I.) plasma levels of DHEA-S in the High, intermediate (Mid) and Low NKCA


Figure 67: Mean (95% C.I.) plasma levels of melatonin in the High, intermediate (Mid) and Low NKCA


Figure 68: (a) Individual (b) Mean (95% C.I.) background proliferations of PBMCs cultured

Figure 69: (a) Individual (b) Mean (95% C.I.) proliferation response of PBMCs to the PPD antigen

Figure 70: (a) Individual (b) Mean (95% C.I.) proliferation response of PBMCs to the Herpes antigen

Figure 71: (a) Individual (b) Mean (95% C.I.) proliferation response of PBMCs to the SEB at Day 3

with/out cortisol



Figure 72: (a) Individual (b) Mean (95% C.I.) proliferation response of PBMCs to the PHA at Day 3

with/out cortisol

Figure 73: (a) Individual (b) Mean (95% C.I.) background percentages of CD8 T-cells expressing CD95


Figure 75: (a) Individual (b) Mean (95% C.I.) percentages of CD8 T-cells expressing CD95 in PHA

stimulated whole blood culture in the absence of cortisol




stimulated whole blood culture in the presence of cortisol



Figure 79: Mean (95% C.I.) percentages of PHA stimulated CD8 T-cells expressing CD95 after

(a) 24 hours, (b) 48 hours of incubation with and without cortisol



Figure 81: Individual percentages of apoptotic (a) CD8 T-cells (b) CD4 T-cells incubated 3 days with

and without cortisol















List of Tables

Table 1: Classification of the main components of the immune system

Table 2: CD expression by NK-cells and lymphocytes



Table 3: Definitions of various endogenous molecules

Table 4: Number and percentage of HIV-infected individuals who had CD4 T-cell counts chec at the

monthly time periods from the Recruitment to four months after the recruitment (Term 4)

Table 5: Number and month of subjects who started anti-retroviral medication and dropped from the

study (NB: Term X represents that X months after the Recruitment time point)

Table 6: Mean percentages and counts (standard deviation: SD) of NK-cells, CD4 and CD8 T-cells and

total lymphocyte counts using a single volunteer (9 tubes collected and averaged on three

separate occasions)

Table 7: Mean (95% C.I.) PSS scores at the Non-exam and Exam time points

Table 8: Mean (95% C.I.) State anxiety scores in the STAI at the Non-exam and Exam time points

Table 9: Mean (95% C.I.) NK-cell percentages in male and female students

Table 10: Mean (95% C.I.) levels of NKCA (% killing) in the Not-stressed and Stressed subgroups

Table 11: Mean (95% C.I.) levels of NKCA (% killing) in the Not-stressed and Stressed male students

Table 12: Mean (95% C.I.) ratios of NKCA to NK-cell in the Not-stressed and Stressed students

Table 13: Mean (95% C.I.) ratios of NKCA to NK-cell in the Not-stressed and Stressed male students

Table 14: Mean (95% C.I.) CD4 T-cell levels (%) of male and female

Table 15: The numbers of participant in the three groups (Self-hypnosis, Johrei and Relaxation control)

in the Not-stressed and Stressed subgroups based on the PSS scores at the Exam time point

Table 16: Mean (95% C.I.) State anxiety scores in the Self-hypnosis, Johrei and Relaxation control

groups at baseline and the Exam time point

Table 17: Numbers of participants in the three groups at the Exam time point

Table 18: Mean (95% C.I.) levels of NK-cell (%) in the Self-hypnosis, Johrei and Relaxation control


Table 19: Percentages (numbers) of subjects whose NK-cell counts maintained or increased

(Maintained) and decreased (Decreased) in the Self-hypnosis and Johrei and Relaxation

control groups for the Intention-to-treat analysis (missing data were added into the number in

the Decreased group)

Table 20: Mean (95% C.I.) levels of CD4 T-cell (%) in the Self-hypnosis, Johrei and Relaxation control




Table 22: Medians, means and standard deviations of the PSS of the university students at non-exam

and exams and of the HIV-infected individuals at recruitment and four months later

Table 23: Mean (95% C.I.) levels of the PSS in the Not-stressed and Stressed subgroups at the

recruitment and four months later

Table 24: Median, mean and standard deviation of the State anxiety score of the university students at

non-exam and exams and of the HIV-infected individuals at recruitment and four months later

Table 25: Mean (95% C.I.) levels of the State anxiety score of the STAI in the Not-stressed and Stressed

subgroups at the recruitment and four months later



Table 26: Mean (95% C.I.) levels of the IES in the subgroups of the Not-stressed and Stressed at the


Table 27: Mean (95% C.I.) levels of the LoC in the Not-stressed and Stressed subgroups at the


Table 28: Mean (95% C.I.) levels of the MCS in the Not-stressed and Stressed subgroups at recruitment


Table 29: Mean (95% C.I.) levels of the PSQI in the Not-stressed and Stressed subgroups at recruitment


Table 30: Correlation between the CD4 gradient (cells per �l per month) and the change scores of

perceived quality-of-life scales

Table 31: Mean (95% C.I.) CD4 T-cell change over the five month (cells per �l per month) in HIV-

infected individuals of the Increased control and Decreased control subgroups


infected individuals of the Improved QoL and Decreased QoL subgroups


infected individuals of the Improved sleep quality and Decreased sleep quality subgroups

Table 34: Mean (95% C.I.) levels of the IES in the HIV-individuals in the Self-hypnosis, Johrei and

Control groups at the Baseline and Post-intervention time points

Table 35: Summary of the numbers (percentages) of the HIV-individuals whose changes in the LoC

between the Baseline and post-intervention either decreased (Gained sense of control) or

increased (Lost sense of control) in the Self-hypnosis, Johrei and Control groups

Table 36: Summary of the numbers (percentages) of the HIV-individuals whose changes in the MCS

between the Baseline and post-intervention either increased (Improved mental quality of life)

or decreased (Decreased mental quality of life) in the Self-hypnosis, Johrei and Control

groups

Table 37: Summary of the numbers (percentages) of the HIV-individuals whose changes in the PSQI

between the Baseline and post-intervention either decreased (Improved sleep quality) or

increased (Decreased sleep quality) in the Self-hypnosis, Johrei and Control groups

Table 38: Mean (95% C.I.) levels of CD4 gradients (counts per �l per month) in HIV-infected

individuals in the Self-hypnosis, Johrei and Control groups

Table 39: Percentages (numbers) of participants whose CD4 T-cell counts maintained or decreased over

the five months in the Self-hypnosis and Johrei and Control groups for the Intention-to-treat

analysis (missing data were added into the number in the Decreased group)

Table 40: Mean (95% C.I.) levels of CD4 T-cell (counts per �l) in HIV-infected individuals in the

groups of the Self-hypnosis, Johrei and Database-controls at the Training period

Table 41: Mean (95% C.I.) CD4 gradients in HIV-individuals in the Self-hypnosis, Johrei and Database

control groups, and in all the 96 individuals (ALL) at the Pre-intervention period



Table 42: Percentages of HIV-individuals in the Self-hypnosis, Johrei and Database control groups

whose changes in CD4 gradients between the Pre-intervention and Post-intervention periods

were either increased, stayed the same or decreased with a judgement that a change of four of

less cells per �l per month was defined as the same change (Stayed the same subgroup), more

than four increase (Improving subgroup), and more than four decrease (Worsening subgroup)

Table 43: Mean (95% C.I.) CD4 gradients in HIV-individuals in the Self-hypnosis, Johrei and Database

control groups at the Pre-intervention and Post-intervention periods

Appendix 6

Table A-1: Mean (95% C.I.) PSS levels of the Cohorts A and B at the Non-exam and Exam time points

Table A-2: Mean (95% C.I.) State anxiety levels of the Cohorts of A and B at the Non-exam and Exam

time points

Table A-3: Mean (95% C.I.) NK cytotoxic activity in the Cohorts A and B at the Non-exam and Exam

time points

Table A-4: Mean (95% C.I.) NK-cell percentages in the Cohorts A and B at the Non-exam and Exam

time points

Table A-5: Mean (95% C.I.) CD4 T-cell percentages in the Cohorts A and B at the Non-exam and

Exam time points

Table A-6: Mean (95% C.I.) CD8 T-cell percentages in the Cohorts A and B at the Non-exam and

Exam time points

Table A-7: Mean (95% C.I.) NKCA levels at the Non-exam and Exam time points

Table A-8: Mean (95% C.I.) NK-cell and CD4 and CD8 T-cell (%) at the Non-exam and Exam time

points

Table A-9: Number of students in the Not-stressed and Stressed subgroups with regard to gender who

filled in the PSS and had blood collection for lymphocyte and NKCA level analyses

Table A-10: Mean (95% C.I.) NK-cell percentages in the Not-stressed and Stressed subgroups

Table A-11: Mean (95% C.I.) NK-cell percentages in the Not-stressed and Stressed male students

Table A-12: Mean (95% C.I.) NK-cell percentages in the Not-stressed and Stressed female students

Table A-13: Mean (95% C.I.) levels of NKCA (% killing) in the Not-stressed and Stressed female

students

Table A-14: Mean (95% C.I.) levels of NKCA (% killing) of male and female

Table A-15: Mean (95% C.I.) ratios of NKCA to NK-cell in the Not-stressed and Stressed female

students

Table A-16: Mean (95% C.I.) ratios of NKCA to NK-cell in male and female students

Table A-17: Mean (95% C.I.) CD4 and CD8 T-cell levels (%) in the Not-stressed and Stressed

subgroups



Table A-18: Mean (95% C.I.) CD4 and CD8 T-cell levels (%) in the Not-stressed and Stressed male

students

Table A-19: Mean (95% C.I.) CD4 and CD8 T-cell levels (%) in the Not-stressed and Stressed female

students

Table A-20: Mean (95% C.I.) CD8 T-cell levels (%) of male and female students

Table A-21: Mean (95% C.I.) PSS levels in the three groups at the Exam time point

Table A-22: Mean (95% C.I.) PSS scores in male subjects in the three groups at the Exam time point

Table A-23: Mean (95% C.I.) PSS scores in female subjects in the three groups at the Exam time point

Table A-24: Mean (95% C.I.) State anxiety scores in the male subjects of the Self-hypnosis, Johrei and

Relaxation control groups at baseline and the Exam time point

Table A-25: Mean (95% C.I.) State scores in the female subjects in the Self-hypnosis, Johrei and

Relaxation control group at baseline and the Exam time point

Table A-26: Mean (95% C.I.) NKCA levels (% killing) in the three groups at the Exam time point

Table A-27: Mean (95% C.I.) NKCA levels (% killing) in male subjects in the three groups at the Exam

time point

Table A-28: Mean (95% C.I.) NKCA levels (% killing) in female subjects in the three groups at the

Exam time point

Table A-29: Mean (95% C.I.) levels of NK-cell (%) of male students in the groups of the Self-hypnosis,

Johrei and Controls at baseline and the Exam time point

Table A-30: Mean (95% C.I.) levels of NK-cells (%) in the female subjects in the Self-hypnosis, Johrei

and Relaxation control groups at baseline and the Exam time point

Table A-31: Mean (95% C.I.) levels of CD4 T-cell (%) of male students in the Self-hypnosis, Johrei and


Table A-32: Mean (95% C.I.) levels of CD4 T-cells (%) in the female students in the Self-hypnosis,

Johrei and Relaxation control groups at baseline and the Exam time point

Table A-33: Mean (95% C.I.) levels of CD8 T-cell (%) of male students in the Self-hypnosis, Johrei and


Table A-34: Mean (95% C.I.) levels of CD8 T-cells (%) in the female students in the Self-hypnosis,

Johrei and Relaxation control groups at baseline and the Exam time point

Table A-35: Correlation between the CD4 gradient (cells per �l per month) and the stress perception

scores and the perceived quality-of-life at recruitment time point (pre) and four-months

after the recruitment (post)

Table A-36: Correlations between the CD4 gradient (cells per �l per month) and the change scores of

stress perception scales

Table A-37: Number of HIV-infected individuals who had viral load level check at the monthly time

periods from the Recruitment to four months after the recruitment (Term 4)



Table A-38: Correlation between the viral load level gradients (log-transformed viral copies per �l per

month) and the stress perception and the perceived quality-of-life scores at recruitment time

point (pre) and four months later (post)

Table A-39: Correlation between the viral load level gradient (log-transformed copies per �l per month)

and the change scores of perceived stress and quality-of-life scores

Table A-40: Correlation between the NK gradient (cells per �l per month) and the stress perception

scores and the perceived quality-of-life at recruitment time point (pre) and four-months

after the recruitment (post)

Table A-41: Correlation between the NK gradient (cells per �l per month) and the change scores of

perceived stress and quality-of-life scores

Table A-42: Mean (95% C.I.) levels of the State anxiety and PSS scores in the HIV-individuals in the

Self-hypnosis, Johrei and wait-listed control groups at the Baseline and the Post-

intervention time points

Table A-43: Mean (95% C.I.) levels of the LoC, MCS and PSQI in the HIV-individuals in the Self-

hypnosis, Johrei and wait-listed control groups at the Baseline and Post-intervention time

points

Table A-44: Mean (95% C.I.) levels of regression gradients in viral load levels (Log-transformed) in

HIV-infected individuals in the Self-hypnosis, Johrei and wait-listed control groups

Table A-45: Mean (95% C.I.) levels of regression gradients in NK-cell (counts per �l per month) in

HIV-infected individuals in the Self-hypnosis, Johrei and wait-listed control groups

List of Text boxes

Text box 1: Project synopsis 21

Text box 2: Appraisal of a stressor 38

Text box 3: Elements of coping with a threat 38

Text box 4: Psychological interventions in this project 43

Text box 5: Summary of hypotheses Re: Stress-related changes of endocrine system which may

contribute to suppress cellular immune responses under sustained stress 48



Abbreviations

ACTH: adrenocorticotrophic hormone

ANOVA: analysis of variance

AP-1: activation protein 1

ART: anti-retroviral treatment

CBG: cortisol binding globulin

CD: clusters of differentiation

CFSE: carboxyfluorescein succinimidyl ester

cpm: count per minute

CRF: corticotrophin releasing factor / (hormone)

CRP: C-reactive protein

CSF: Colony stimulating factor

CTL: (cytotoxic / cytolitic T lymphocyte)

CV: coefficient of variation

DHEA (-S): dehydroepiandrosterone (sulphate)

EEG: electroencephalogram

E:T ratio: Effector vs. Target ratio

FITC: fluorescein isothiocyanate

FCS: foetal calf serum

GABA: gamma aminobutyric acid

GCR: glucocorticoid receptor

HIV: human immunodeficiency virus

HPA: hypothalamus pituitary adrenal (axis)

HSV: herpes simplex virus

IES: Impact of Event Scale

IL: Interleukin

IFN: interferon

ITAM / ITIM: immunoreceptor tyrosine-based

activation / inhibitory motifs

KIR: killer immunoglobulin like receptor

KPSS: Kesseler Perceived Social Support

LoC: Locus of Control

LPS: lipopolysaccharide

MCR: mineral corticoid receptor

MHC: major histocompatiblity complex

NCR: natural cytotoxic receptors

NF�B: nuclear factor kappa B

NK cell: Natural Killer cell

NKCC: Natural killer cytotoxic activity

PBL: peripheral blood lymphocyte

PBMCs: peripheral blood mononuclear cells

PBS: phosphate buffer saline

PEI: Personalised Emotional Index

PFA: paraformaldehyde

PHA: phytohaemagglutinin A

PI: propidium iodide

PNI: psycho-neuro-immunology

PPD: purified protein derivative

PSS: Perceived Stress Scale

PSQ: Personality Syndrome Questionnaire

PSQI: Pittsburgh Sleep Quality Inventory

QoL: quality of life

RCT: randomised controlled trial

REM: rapid eye movement

SAM: sympathetic adreno-medulla

SAS: Statistical Analysis Software

SD: standard deviation

SEB: Staphylococcal Enterotoxin B

SIBS: Spiritual Involvement and Beliefs Scale

SoC: sense of coherence

SOPs: standard operating procedures

SPSS: Statistical Package for Social Sciences

STAI: State and Trait Anxiety Inventory

TCI: Temperament and Character Inventory

TCM: tissue culture medium

Th.: Helper T lymphocyte

TNF: Tumour necrosis factor

T-reg: regulatory helper T lymphocyte

TUNEL: TdT-mediated dUTP nick end labelling

WHO: World Health Organisation



Acknowledgements

I wish to thank all the participants who took parts in the project as study subjects.

The work in this thesis was funded by the Johrei Academy and Johrei Association. I am most grateful to

them for their generosity and for their kind support in developing materials of the Johrei intervention.

I would like to give special thanks to Dr. Don C. Henderson for his endurable close supervision and Prof.

John H. Gruzelier for allowing me to start and conduct the project. They have given me inspiration to see

the project through. Dr. Tannis M. Laidlaw, Dr. Prabudha Dwivedi and Mr. Bryan Bennett worked

together with me as a research team for the in vivo studies. I am very grateful to them. One of the

psychological interventions, the Self-hypnosis training and follow-up sessions, was planned and

conducted by Dr. Laidlaw. The mock neuro-feedback sessions (relaxation control) were conducted by Dr.

Dwivedi. Mr. Bennett was in charge of patient recruitment and organised meetings for the participants.

Without any of them, this project would undoubtedly have never been completed, or even started. I am

most indebted to their great contributions, personal help and warm support.

My special thanks also go to Prof. Adrian P. Burgess and Dr. Martin R. Goodier. They gave me very

useful and encouraging inputs at the transfer exam to Ph.D. from M.Phil. Dr. Alan W. Steel contributed to

the in vivo HIV-study as an independent researcher to select case matched controls. Dr. Simon E. Barton

kindly permitted and gave support to recruit HIV-patients in his clinic. Mr. Mohamed Shamji helped me

to start the in vitro experiments before the project commenced. I am indebted to their kind help and warm

support. I appreciate M.Sc. student researchers, Ijeoma Ugwu-Onuoha and Alex Gale, and B.Sc. student

researchers, Linda Farahani, Catrina Lynch, Nick Enzor, Christine Brincat, Tom French and Helena

Marconell, for their contribution to the studies. I appreciate the secretarial assistance given by Mrs. Ann

Ebberson throughout my Ph.D. course. Thanks also go to all the research staff / clinical laboratory staff /

students at Charing Cross Neuroscience Division, at Chelsea and Westminster Immunology Department

and St. Stephen’s AIDs Trust Kobler Centre who kept me going when I was struggling.

In addition, I am very grateful to Prof. Mark Jensen, Prof. Yukihisa Kurasawa, Dr. Graham Jamieson, Dr.

Gerald Stein, Prof. Frances Gotch, Dr. Nathalie Fouquet, Dr. Philippe Donatien, Dr. David Vernon, Dr.

Malcolm Hawken, Prof. Tom Sensky and Prof. Julia Buckingham for their comments on the manuscript. I

would like to thank my examiners, Prof. Phil Evans and Rev’d Prof. Nick Goulding, for their thoughtful

and useful suggestions. To the aforementioned and many other unnamed colleagues and friends, who

have also helped towards the completion of this thesis, I extend my sincere thanks.

Akira NAITO

London, August, 2006

- 17 -

Chapter I

Introduction



CONTENTS OF CHAPTER 1

Introduction

1.1 Project overview 19

1.2 Theoretical framework

1.2.1 Immune system 22

1.2.1.1 Innate and adaptive immunity 22

1.2.1.2 Communication between immune cells 27

1.2.2 Neuro-endocrino-immune interaction 30

1.2.2.1 Brain-to-immune pathway 30

1.2.2.2 Immune-to-brain pathway 32

1.2.2.3 Circadian rhythm in the neuro-endocrino-immune network 33

1.2.2.4 Circadian rhythm and subjective well-being 35

1.2.3 Psychological input in the psycho-neuro-endocrino-immune network 36

1.2.3.1 Stressor 36

1.2.3.2 Stress perception 37

1.2.3.3 Psychological training intervention 39

1.2.4 Stress-associated changes 43

1.2.4.1 Chronological definition of stress response 43

1.2.4.2 Acute stress responses in the neuro-endocrino-immune network 44

1.2.4.3 Sustained stress and changes in the psycho-neuro-endocrino-

immune network 46

1.3 Approach taken 49



1.1 The project overview

Stress is inevitable in everyday life and it affects mental and physical well-being both

beneficially and detrimentally [Cohen & Herbert, 1996; Evans et al., 2000; Marmot, 2004]. This

project is based on the hypothesis that the detrimental effects of stress upon psychological well-

being and general health can be alleviated by psychological intervention [Text box 1].

Psychological intervention in the context of psycho-somatic medicine [Waldstein et al.,

2001; Walker et al., 1999] has both training and practice aspects, both of which aim to provide

other perspectives of life events (stress perception) and coping skills (stress management) in

order to reduce the levels of stress. Two psychological interventions used in this project were

Self-hypnosis and Johrei, a Japanese system encompassing stress management. These

interventions aimed to encourage the participants to secure their own time for themselves with

relaxation techniques as well as to reduce stress by providing alternative perspectives of, and

coping strategies for, stressful life events.

The fields of ‘psycho-neuro-endocrinology’ [de Kloet, 2000; Sapolsky et al., 2000] and

‘psycho-neuro-immunology’ [Ader & Cohen, 1993] are based on the concept of Descartes'

‘mind and body’ or ‘ the way with the body-mind’ [Yuasa & Kasulis, 1987]. A growing body of

evidence suggests that there are cross regulatory influences between psychological, neurological,

endocrinological and immunological systems. This has led investigators to propose the

existence of an integrated psycho-neuro-endocrino-immune network, in which a change in one

facet has consequential influences upon other parts of the network. The primary mediators in the

network include catecholamines from the sympathetic-adreno-medulla (SAM) system, adrenal

hormones from the hypothalamus-pituitary-adrenal (HPA) axis and a myriad of components of

the immune system, including individual cells, cell surface receptors, and intracellular and

intercellular messengers (cytokines).

The field of stress research has not yet agreed upon a definition of stress that is used in all

studies. For example, the distinction between acute and sustained stress is ambiguous and varies

from study to study. In the current thesis, acute or sustained stress was distinguished on the

basis of time in a biological cycle. Acute stress was defined as when effect of stress or stress

response is contained within one day, i.e. a single circadian rhythm. In contrast, sustained stress

was defined as stress that the effect lasts for more than one day. This leads to a working

hypothesis that sustained stress is associated with altered circadian patterns of the psycho-



neuro-endocrino-immune network. Since the psychological interventions used in the project

require weeks of training and practice, this investigation focused on the sustained stress.

Previous research has shown that the stress-associated inappropriate response of the

immune system has been shown to comprise:

1. Impaired cellular immune responses, which lead to an increase in susceptibility to

infection and malignancy [Garssen, 2004]; and

2. Excessive inflammatory reactions, which may be due to impaired suppressive self-

regulation, or over-production of pro-inflammatory cytokines leading to an

augmented severity of symptoms of allergy or autoimmune diseases [Cleare, 2003].

This project focused on the first part - the stress-induced impairment of cellular immunity.

The effects of stress and psychological intervention upon the psycho-neuro-endocrino-

immune network were investigated in vivo in university students facing exams as an example of

individuals with time-limited sustained stress, and in HIV-infected adults as an example of

individuals with ongoing, life-long, disease-associated stress. General and mental well-being

were investigated through questionnaires designed to measure perceived stress, anxiety, quality-

of-life, and sleep quality. The effects of stress upon the psycho-neuro-endocrino-immune

network were examined through immune profiles including disease parameters. Associations

between the mediators of the psycho-neuro-endocrino-immune network were also investigated

in vitro in order to demonstrate any direct links between hormone levels and immune

parameters.



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1.2 Theoretical framework

1.2.1 Immune system

Humans are constantly prone to infection by a vast range of organisms (viruses, bacteria,

fungi, and multi-cellular parasites) and to malignancy through mutations from ‘self’ . It is the

functional responsibility of the immune system to recognise non-self and altered-self and to

produce an appropriate immune response to remove it in order to maintain the general health of

the body. Any immune response involves, first, recognition of the pathogen or mutation, and

then second, a reaction to eliminate it.

1.2.1.1 Innate and adaptive immunity

The immune system has been classified into two components: (1) innate (inborn: non-

specific) immunity; and (2) adaptive (acquired: pathogen-specific) immunity [Table 1].

Innate immunity

Innate immunity is non-specific and is defined as the in-born defence mechanism of the

body. The innate natural immune system is present at birth and is responsible for the early /

immediate defence against infection and malignancy. Although this form of immunity has no

memory of non-self, these cells are able to recognise non-self organisms (tumour cells or

infected cells) by ‘missing self’ -signal [Moretta et al., 2002], and defend the body, even when

the trigger is not sufficient to activate the adaptive immune system. There are two elements to

innate immunity, i.e. humoral and cell-mediated immunity:

1. Humoral immunity : the secreted molecules, which include complement, lysozome,

fibronectin, acute phase proteins (e.g. C-reacted protein (CRP)), eicosanoids, natural

antibodies and pro-inflammatory cytokines (e.g. Interleukins (ILs), Interferons (INFs),

colony stimulating factors (CSFs) and tumour necrosis factors (TNFs)).

2. Cellular immunity: the principal cell types in innate immune system are phagocytes

(e.g. macrophages, monocytes and granulocytes including neutrophils) and natural

killer (NK) cells.



Adaptive immunity

Adaptive immunity, on the other hand, is the defence mechanism that recognises and

fights against specific infectious organisms and develops memory of specific antigens of such

pathogens. This allows all subsequent responses to the same infection to proceed more rapidly

and effectively. This adaptive immunity also has humoral and cellular components.

1. Humoral immunity is mediated by a vast amount of pathogen-specific antibodies

produced by B-lymphocytes. Antibodies provide protection from pathogens by

neutralising toxic components of pathogens, by coating pathogens and thereby

targeting for disposal by phagocytes (this is known as opsonisation), and by activating

complement to trigger lyses and ingestion of pathogens by phagocytes. Specific

molecules produced by immune cells (namely, Th.1 and Th.2 cytokines) [see also

Table 1] also play a major role in regulation of the adaptive immune system as media

of cell-cell communication.

2. Cellular immunity is based on the activities of two types of lymphocytes, T- and B-

lymphocytes. Each lymphocyte can specifically recognise and react with one of the

thousands of foreign proteins, i.e. antigenic epitopes found on / in pathogens.

� The B-lymphocytes are responsible for the production of specific antibodies, and

have B-cell antigen receptor (BCR). The BCR is a membrane-bound form of the

antibody that the B-lymphocyte will secrete after following activation by specific

antigen and differentiation into plasma cells.

� The T-lymphocytes have been subdivided into two sub-populations according to

their functions, i.e. the cytotoxic T-lymphocyte (CTL) and the helper T-lymphocyte

(Th.). Both subsets express T-cell antigen receptors (TCR). The TCR is specially

adapted to detect antigens derived from foreign proteins and pathogens.



Table 1: Classification of the main components of the immune system HUMORAL CELLULAR

Natural Killer (NK) cells Cytotoxic NK-cells Regulatory NK-cells

Macrophages Monocytes INNATE

Cytokines (Pro-inflammatory) Acute phase proteins Complement Lysozome Natural antibodies

Phagocytes Granulocytes

Neutrophils Eosinophils Basophils

Cytotoxic T-cells (CTL)

Cytokines

Th. 1 (cellular)

Th. 2

(humoral)

T-lymphocytes Helper T-cells

Type I (Th. 1) Type II (Th. 2)

Regulatory (T-reg) ADAPTIVE

Antibodies (Immunoglobulin)

IgM IgG IgA IgE

B-lymphocytes (and Plasma cells)

Natural Killer (NK) cells

The Natural Killer (NK) cells are one of the principal cell types in the innate cellular

immune system. They are large granular lymphocytes [Figure 1], which develop from common

lymphoid progenitor cells. They make up about 5-15% of the mononuclear cell fraction in

normal peripheral blood.

Figure 1: A typical Natural Killer cell [Taken from Wasatch Health Group: http://www.wasatchhealth.com/Pages/NK-cell.html]

There are two subsets of NK-cells [Cooper, Fehniger & Caligiuri, 2001], i.e. 10-20% of

regulatory NK-cell subset (cytokine producing subset [Cooper, Fehniger, Turner et al., 2001])

and 80-90% of cytotoxic NK-cell subset [Jacobs et al., 2001], which has two possible killing

mechanisms:

1. Cytolitic granules make a hole in the membrane of target cells causing necrosis; and

2. Granules or a cell-cell contact (e.g. Fas - Fas-ligand contact) triggers a cascade for

‘programmed cell death’ (known as apoptosis) [Opferman & Korsmeyer, 2003] in the

target cell.



The cytolitic granule pathway employed by cytotoxic NK-cells is the same killing

mechanism as that applied by cytotoxic T-cells (CTL). Cytotoxic granules, which contain

Perforin and Granzyme A / B, are released onto the surface of the bound target cell, and the

Perforin makes a hole to destroy the cell membrane and Granzyme induces apoptosis. This

secretion of granules with contact to target cells takes a few seconds and is known as the ‘kiss of

death’ [Trambas & Griffiths, 2003]. Apoptosis is essential in the cell cycle to maintain cellular

homeostasis [Opferman & Korsmeyer, 2003]. The Fas-receptor [Hingorani et al., 2000] was

shown to trigger an intra-cellular cascade inducing apoptosis when the Fas-ligand from other

cells contacts [Alenzi & Warrens, 2003].

Target recognition by NK-cells

The main role of NK-cells is to recognise and kill virally infected-cells and tumour-cells

both of which have escaped recognition and death by other immune components. The exact

mechanism of the recognition by NK-cells is unclear, but there has been a hypothesis that NK-

cells can detect ‘missing self’ [Moretta et al., 2002]. In other words, NK-cells lack antigen

specificity but are able to identify ‘non-self’ . All human cells express the major

histocompatiblility complex (MHC) class I molecules on the cell-surface. The levels of

expression of this MHC decrease when cells are infected or turn into tumour cells, and this

decrease of the MHC class I molecule is called the ‘missing self’ [Moretta et al., 2002].

Recognition of target cells by NK-cells is achieved by combination of two categories of

receptors, i.e. activating and inhibitory receptor groups [Middleton et al., 2002]. Recognition of

‘missing-self’ means that balance between activating and inhibitory signals weighs toward

activation due to a lack of the MHC class I. Recognition of ‘self’ through normal expression of

MHC Class I triggers NK-cell inhibitory signals, which switch off activating signals.

NK-cell receptors

The NK-cell surface receptors comprise two families:

1. Immunoglobulin super family, including killer immunoglobulin-like receptors (KIR);

and

2. C-type lectin like receptors including NKG2D and natural cytotoxic receptors (NCR)

A single signal from one of these receptors is not sufficient to trigger either the beginning

or the end of NK-cell activation. Instead, the trigger is the result of combined signals of these



NK-cell receptors [Biassoni et al., 2001; Mandelboim & Porgador, 2001]. The mechanisms of

the intra-cellular signals cascades are complex [Middleton et al., 2002] and not clearly defined.

Middleton et al. [2002] have recently described one model, which is based on the intra-cellular

structure of these two family receptors, i.e. the immuno-receptor tyrosine-based inhibitory

motifs (ITIM) and the immuno-receptor tyrosine-based activation motifs (ITAM) [Bakker et al.,

2000].

The ITIM are the receptor motifs with long cytoplasmic tails that are responsible for the

inhibitory signals associated with recognition of MHC class I molecules, whereas the ITAM are

the receptor motifs with short cytoplasmic tails and give rise to the activation signals. All

reactions seem to be the result of the balance between these inhibitory and activation signals.

Middleton explained the regulation by means of the length of their cytoplasmic tails, i.e. ITAM

has shorter and ITIM has longer/deeper cytoplasmic tails. Activation signals can be blocked by

inhibitory signals in deeper or more peripheral levels of intra-cellular cascade when there are

enough inhibitory signals from the ITIM to overcome activation signals from the ITAM. By

these complex mutual mechanisms, the NK-cell maintains its balance between insufficient

reaction against the target (non-self or altered-self) and over-reaction extending to the ‘self’.

T-lymphocytes

The T-lymphocytes are one of the principal cell types in the adaptive cellular immune

system. They make up about 60-85% of the mononuclear cell fraction in normal peripheral

blood (peripheral blood mononuclear cells: PBMCs). There are two subsets of T-lymphocytes:

35-80% of them are helper T-lymphocytes (Th.) which orchestrate both cellular and humoral

immunological responses by producing cytokines and by cell-cell contacts via T-cell receptor

(TCR); and 20-65% of them are cytotoxic T-lymphocytes (CTL).

The helper T-lymphocytes have been further subdivided into three phenotypes (Table 1):

1. Type I helper T-lymphocyte (Th.1);

2. Type II helper T-lymphocyte (Th.2); and

3. Regulatory T-lymphocyte (T-reg)

according to their roles in defence [Jonuleit & Schmitt, 2003; McHugh & Shevach, 2002].

The Th.1 cells principally orchestrate cellular immunity, the Th.2 cells enable humoral

immunity to react against pathogens, and the T-reg cells mainly regulate to suppress excessive

inflammatory reactions in cellular immunity.



In contrast to NK-cells which can attack ‘non-self’ in a non-specific manner as described

above, each T-lymphocyte has a unique recognition against a specific antigen. This specificity

of an antigen works by using the MHC class I (for cytotoxic T-lymphocyte) or class II (for

helper T-lymphocyte) molecules. Because any ‘non-self’ particles can be an antigen, the total

population of T-lymphocytes collectively bears a huge repertoire of receptors, and most of them

in circulation are inactive or resting. These repertoires are the results of the high level of

diversity in the prototype antigen receptor. This mechanism in production of huge variety of

antigen specific T-cell receptors is similar to the mechanism in production of a wide range of

antigen specific antibodies by B-cells and plasma cells.

Recognition and elimination of specific pathogens by T-lymphocytes

The role of T-lymphocytes is to recognise and arrange, either, directly or indirectly to

eliminate foreign pathogens. This recognition of pre-exposed antigen (recall antigen) is based

on a huge variety of antigen receptors, and the elimination of a pathogen depends on the ability

of rapid proliferation of one specifically recognised set of lymphocytes. The proliferative

response of T-lymphocytes consists of four processes:

1. Recognition of the foreign pathogen to match a pre-exposed / recall antigen;

2. Activating cell cycle (G1-S-G2-M) progression of the one type of cell matched;

3. Actual cell divisions and proliferation; and

4. Apoptosis of excessive cells generated through the above proliferation.

This process of T-lymphocyte proliferation is known to occur also in peripheral

lymphocytes both in vivo and ex vivo, particularly significant in response to in vitro stimulation

with a mitogen, a super-antigen, or specific recall antigens [Antia et al. 2003; Kaech and Ahmed

2003; Seder and Ahmed 2003].

1.2.1.2 Communication between immune cells

Immune cells (e.g. NK-cells, lymphocytes and phagocytes) communicate with each other

either directly by cell-cell contact, or indirectly via various secreted molecules, which interact

with cell surface molecules or intra-cellular (cytoplasmic or nuclear) receptors.

Many surface markers (receptors) have been identified and named according to the

clusters of differentiation (CD) system [Table 2]. This allows cell types (phenotypes) to be

identified according to their expression of cell surface markers, e.g. helper T-lymphocytes

(CD3+CD4+), cytotoxic T-lymphocyte (CD3+CD8+), B-cells (CD19+), NK-cells (CD3-CD56+)

and NKT-cells (CD3+CD56+). This identification can be performed by using a flow cytometer



which detects fluorescently conjugated specific antibodies bound to unique CD markers /

molecules expressed on the cell surface.

For example, NK-cells are characterised by the expression of CD56 molecules on the

surface and the absence of a common lymphocyte marker (CD3) which distinguishes it from

another cytotoxic lymphocyte sub-population (NKT-cells: CD3+CD56+ lymphocytes) [Seaman,

2000]. Further CD16 can be used to distinguish between NK-cell subsets, i.e. the cytotoxic NK-

cells (CD56Dim) express CD16 while the regulatory NK-cells (CD56Bright) are CD16 negative

[see also Table 2].

Table 2: CD expression by NK-cells and lymphocytes

Cytotoxic CD56Dim & CD16+ NK-cells CD3 (-) & CD56+

Regulatory CD56Bright & CD16 (-)

CD3+ & CD56+ NKT-cell

Cytotoxic CD8+ T-lymphocytes CD3+

Helper CD4+

B-lymphocytes CD19+

The secreted molecules which act as intra-cellular messengers between immune cells are

known as cytokines. Cytokines consist of three groups [see also Table 1]: (1) pro-inflammatory

(IL-1, IL-6, TNF-�, INF-� etc); (2) Th.1 (IL-2, IL-12 etc.); and (3) Th.2 (IL-4, IL-10 etc.)

cytokines. They have been classified into the cytokine families such as Interleukins (IL),

Interferons (INF), Colony stimulating factors (CSF), Tumour necrosis factors (TNF) and a

range of chemokine families [Janeway et al., 2001].

As new cytokines were discovered [Janeway et al., 2001], the distinctions between

various types of endogenous molecules, which are utilised for cell-cell communication, became

increasingly ambiguous due to overlapping functions [Table 3]. Initially these molecules were

considered to be produced by specific cells and to affect specific cells only in each organ system.

Recent evidence, however, has revealed that these molecules can be produced by a variety of

different cells and that their receptors are expressed by a vast range of types of cells in different

organ systems [Hansen et al., 1998; Marz et al., 1999; Miller et al., 1994; Turnbull & Rivier,

1999].



Table 3: Definitions of various endogenous molecules Hormones

Chemical substances produced in an organ or gland in the body that are secreted into the blood and carried to other organs or parts of the body

Neurotransmitters (Catecholamines & Acetylcholine)

Chemical substances released from neurons in synapses that bind to corresponding receptors on nearby cell surfaces or activate secondary messenger cascade, i.e. channels, pumps, kinases, or proteases

Proteins that are the core of communication between immune cells themselves, and with cells belonging to other tissue types

Proteins that signal leukocytes to move in a specific direction; in other words, a class of chemotactic cytokines

Cytokines

. Chemokines

. Eicosanoids

(Arachidonic acid derivatives) Biosynthesised molecules from arachidonic acid (poly-unsaturated fatty acid), i.e. prostaglandins, prostacyclins, thromboxanes, leukotrienes etc.; in other words, a class of oxygenated hydrophobic cytokines

Communication and interaction between organ systems

The primary organ systems which are distributed throughout the body and in which

mediators are not-restricted in location are the nervous system, the endocrine system and the

immune system. They are considered to formulate independent cell-cell communication

networks by various signal transportation systems (e.g. electrical signals and molecules), and

these communication networks are shown to have their own independent regulatory

mechanisms including counter regulation, buffering mechanisms and/or feedback mechanisms.

For example, in the autonomic nervous system, the sympathetic and the parasympathetic

systems have opposite effects; the sympathetic nervous system suppresses the parasympathetic

nervous system and vice versa [Boeree, 2002].

In the endocrine system, the hypothalamus-pituitary-adrenal (HPA) axis has the

interactive modulation, namely ‘ corticotrophin-releasing-factor (CRF) – adrenocorticotrophic-

hormone (ACTH) – glucocorticoid (cortisol in human)’ modulation. This ‘CRF-ACTH-cortisol’

modulation has feedback mechanisms, by which increased levels of cortisol secreted from

adrenal glands suppresses production of CRF and ACTH in the brain [Tsigos & Chrousos,

2002]. This modulation also contains buffering mechanisms where the levels of free cortisol can

be maintained in a narrow window range with a minimum time of over fluctuation as in the

following mechanism. The level of free cortisol in serum depends on the ratio of cortisol to

cortisol binding globulin (CBG) so that a sudden change of free cortisol level can be buffered

by changing this cortisol-CBG ratio, i.e. percentages of cortisol which bind to the CBG

[McEwen et al., 1997].



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In the immune system, counter-regulatory mechanisms of the Th.1 cells and the Th.2 cells

work to maintain long term balance between them [Kidd, 2003], i.e. Th.1 (cellular) cytokines

can suppress Th.2 (humoral) cytokine production and vice versa.

Furthermore, it has been revealed that cells also communicate over these different organ

systems [see below 1.2.2 for the neuro-endocrino-immune interaction], and it has been

suggested that these nervous, endocrine and immune systems have mutual regulatory

mechanisms between themselves as an interactive neuro-endocrino-immune axis [Elenkov et al.,

2000; Haas & Schauenstein, 2001; McEwen et al., 1997].

1.2.2 Neuro-endocrino-immune interaction

The interactive neuro-endocrino-immune axis has often been discussed in the context of

stress responses [Besedovsky & del Rey, 2001; Biondi, 2001], and it has been proposed that

psychological stress can modulate the immune system via various interactive mechanisms in

this neuro-endocrino-immune axis [Moynihan & Stevens, 2001] [Figure 2].

Figure 2: Schema of the neuro-endocrino-immune interaction.

(HPA: hypothalamus-pituitary-adrenal axis, SAM: sympathetic-adrenal-medulla modulation)

1.2.2.1 Brain-to-immune pathway

In recent decades, two major axes have been proposed as an important pathways in the

stress response: (1) the sympathetic nervous system-adreno-medulla (SAM) and (2) the

hypothalamus-pituitary-adrenal (HPA) axes [de Kloet, 2000; de Kloet et al., 1998; Downing &

Miyan, 2000; Heuser & Lammers, 2003; Yang & Glaser, 2002] [Figure 2]. This section

introduces the pathway from the brain to the immune system [Elenkov et al., 2000; Lawrence &

Kim, 2000].



The ‘ fight or flight’ response [Cannon, 1914; Cannon, 1932; Cannon, 1934] and emotions

like anxiety and/or fear [LeDoux, 1998] are known to be associated with increased activity in

the sympathetic nervous system. There are two primary pathways by which the sympathetic

signals are conveyed to target organs [Elenkov et al., 2000]. One pathway is direct neural

connections, where norepinephrine functions as a neurotransmitter in a neural terminal. The

other is known as the sympathetic-adreno-medulla (SAM) pathway, where epinephrine (as a

response to the sympathetic neural activity) released from the adrenal glands travels through the

blood stream and acts as a hormone in various organs. For example, the sympathetic neural

fibres descend from the brain into a neural terminal both in the primary lymphoid tissues (bone

marrow and thymus) and the secondary lymphoid tissues (spleen and lymph nodes) [Felten &

Felten, 1994]. Immune cells themselves have also been reported to express catecholamine

receptors, but their profiles are unique, i.e. NK-cells have high-density and high-affinity beta-2-

adrenergic receptors, B-cells have high-density but low-affinity, and T-cells have low-density

and low-affinity [Anstead et al., 1998]. This is in line with the findings that catecholamines,

norepinephrine and epinephrine activate the immune response, including an increase of NK-

cells and cytotoxic T-cells in circulation [Hennig et al., 2000] and an increase of pro-

inflammatory cytokine production [Elenkov et al., 2000]. This series of evidence strongly

suggests that the sympathetic nervous system (particularly with the SAM axis) directly

communicates with immune cells in the brain-to-immune pathway.

On the other hand, hormones in the hypothalamus-pituitary-adrenal (HPA) axis have also

been considered to play an important role as connectors or modulators between the brain and

immune system [Flier & Underhill, 1995; Reichlin, 1993]. Cortisol, the main secreted hormone

to the blood stream in the HPA axis, is believed to be a major stress-related hormone

[Hucklebridge et al., 1998; Rohleder et al., 2001]. It has been demonstrated that the major

immune organs, i.e. spleen and thymus, and immune cells themselves are rich in cortisol

receptors [Miller et al., 1994]. The effect of cortisol upon individual target cells, however, is

suggested to vary from suppressive to stimulatory, i.e. suppressive, preparative, permissive and

stimulatory actions [Sapolsky et al., 2000]. The various factors contributing to this

differentiation include:

� Types of relevant target cells and their cortisol receptor profiles;

� Timing of secretion, duration of exposure, and concentration of cortisol; and

� Combination with cascading secretions of other molecules (hormones and

cytokines).



In addition to this complexity, the exact mechanisms at the gene level are also yet to be

made clear. For example, cortisol is known to be antagonistic against the nuclear factor kappa B

(NF�B) [Chrousos, 1995; Goulding, 2004], which is a known activator for the transcription of

pro-inflammatory cytokines (IL-1, IL-6 and TNF-�) [Barnes, 1997] as well as a genomic

inhibitor against the apoptotic cascades [Karin & Lin, 2002]. By contrast, the cortisol-induced

gene products are known to comprise a vast range of proteins including the Annexin I, which

has comprehensive anti-inflammatory intra-cellular actions [Goulding, 2004]. Nevertheless, the

evidence strongly supports the conclusion that the mediators of the HPA axis (particularly

cortisol) can exert direct influence upon immune cells in the brain-to-immune pathway.

Furthermore, in vivo laboratory stress studies have illustrated that there is a consistent

order of responses in the change levels of mediators between the SAM and the HPA axes, i.e. an

increase of cortisol levels was observed after an increase of catecholamine levels [Clow et al.,

1997; Clow et al., 2000; Hucklebridge et al., 1998; Madden, 2001; Rohleder et al., 2001;

Uchino et al., 2001]. This suggests that catecholamines may promote cortisol secretion, so that

these two main axes of the brain-to-immune pathway in the psycho-neuro-endocrino-immune

network may also communicate with each other.

1.2.2.2 Immune-to-Brain pathway

Reciprocally, it has been discovered that the pro-inflammatory cytokines (IL-1, IL-6 and

TNF-�) can activate the SAM and HPA axes [Besedovsky & del Rey, 2000; Buckingham et al.,

1996; Perlstein et al., 1993; Turnbull & Rivier, 1999; Wang & Dunn, 1999]. The blood-brain-

barrier generally prevents the transportation of large molecules from blood to the brain, however,

the pro-inflammatory cytokines (particularly IL-6) were shown to be capable of increasing

permeability of the blood-brain barrier [Castelnau et al., 1998; Mulla & Buckingham, 1999;

Turnbull & Rivier, 1999]. Furthermore, cytokines have been shown to be released from, and

affecting, peripheral nerves and the brain as well as peripheral immune cells [Hansen et al.,

1998; Marz et al., 1999]. The pro-inflammatory cytokines (IL-1 in particular) were also

demonstrated to initiate sickness behaviour (e.g. fever, fatigue, sleepiness and anorexia)

[Dantzer, 2004; Kelley et al., 2003; Vollmer-Conna, 2001; Watkins & Maier, 1999]. With the

finding that the IL-1 receptors have also been found on neurons and glial cells, particularly

dense in the hippocampus [Cunningham & De Souza, 1993], it was suggested that there is a

direct interaction between the immune cells and the brain in the immune-to-brain pathway

[Becher et al., 2000; Maier & Watkins, 1998] in the psycho-neuro-endocrino-immune network

[Figure 2].



The hippocampus and the amygdala, which play a core role in learning, memory and

cognition [Blank et al., 2002], are also known to have an important role in the stress response

[de Kloet, 2000; Heuser & Lammers, 2003]. The hippocampus has been shown to be rich in

cortisol receptors [de Kloet et al., 1998; Downing & Miyan, 2000; Miller et al., 1994], and

cortisol was shown to enhance memory by means of the glucocorticoid receptors (GCRs) in the

hippocampus [de Kloet et al., 1999]. In addition, the GCRs inhibition (by antagonists) in the

amygdala was also reported to impair memory consolidation including stressful memories. This

impairment of memory consolidation was suggested to result in decreasing the levels of fear and

anxiety [McGaugh & Roozendaal, 2002; Roozendaal, 2000]. Furthermore, it has been

demonstrated that the sympathetic nervous system and the HPA axis managed to provoke

anxiety [Tanaka et al., 2000].

Hence, it was suggested that the immune-to-brain pathway [Maier, 2003] can extend to

psycho-behavioural responses or ‘mind-body’ interaction [Yuasa & Kasulis, 1987] as in the

psycho-neuro-endocrino-immune network.

Consequently, it is proposed that these inter-cellular interactions and intra-cellular

mechanisms in each level of the psycho-neuro-endocrino-immune network enable the immune

system to maintain homeostasis in health, i.e. the balance of reactions between incompetent

immune responses, which may lead to malignancy or infection, and excessive inflammation,

which may lead to auto-immune disease or allergy.

1.2.2.3 Circadian rhythm in the neuro-endocrino-immune network

Each organ system is known to follow its own homeostatic rest-alert cycles. These rest-

alert cycles synchronise with the sleep-wake cycle [Lavie, 2001]. They have been observed as

diurnal variations [Clerici et al., 1997; Glaser et al., 2001; Maschke & Hecht, 2004; Sakami et

al., 2002] or had their own circadian patterns [Folkard, 1990] in the levels of their mediators.

The biological sleep-wake cycle, a circadian rhythm, is originally driven from a

physiological cycle of changes in body temperature, i.e. one cycle of diurnal changes in the set-

point temperature [Foster & Kreitzman, 2004]. One example of the observed circadian patterns

in the neuro-endocrino-immune network are the shifts in dominance in the balance of

interactions within each nervous, endocrine and immune system [Laycock & Wise, 2003;

Marshall & Born, 2002]:



1. The parasympathetic is dominant over the sympathetic at night, and vice versa

during the day in the nervous system;

2. A peak secretion of melatonin precedes sleep [Lavie, 2001] and a cortisol surge

precedes waking [Born et al., 1999; Spath-Schwalbe et al., 1992]; and

3. Th.1 cytokines (e.g. IL-2) are higher at night than during the day [Born et al.,

1997] and they can enhance sleep induction while Th.2 cytokines (e.g. IL-4 and L-

10) suppress sleep induction and disturb the sleep process [Marshall & Born, 2002].

It has also been shown that the circadian patterns of these secreted molecules in the neuro-

endocrino-immune network contribute to the sleep-wake cycle by promoting or inhibiting sleep

[Moldofsky, 1995]. For example, pro-inflammatory cytokines (e.g. TNF-�� IL-1 and IL-6) as

well as melatonin are known to induce sleep [Kronfol & Remick, 2000; Krueger & Majde, 1994,

2003]. In addition, cortisol and pro-inflammatory cytokine antagonists (e.g. IL-1ra) as well as

negative mood (e.g. anxiety and depression) can inhibit sleep [Sakami et al., 2002].

Reciprocally, disorganization of the sleep-wake cycle has been shown to induce

alterations:

1. In the levels of the neuro-endocrine hormones [van Reeth et al., 1994] including

impairment of melatonin secretion [Suzuki et al., 1993]; and

2. In immune parameters [Cruess et al., 2003; Moldofsky, 1995] including shifting the

balance of Th.1 / Th.2 cytokine production toward Th.2 dominance [Sakami et al.,

2002].

These alterations may be associated with each other since melatonin was reported to

stimulate Th.1 cytokine production [Garcia-Maurino et al., 1999; Inserra et al., 1998]. It has

also been shown that sleep deprivation, particularly the rapid eye movement (REM) sleep

deprivation, impairs immune responses [Casey et al., 1974]. The ‘sleep efficiency’, i.e. the

percentage of total sleep amount in available sleep-time (including awake time in bed), was

shown to correlate negatively with the clinical parameters representing disease severities both in

cystic-fibrosis patients [Milross et al., 2002] and in HIV-infected patients [Cruess et al., 2003].

The sleep efficiency was also reported to be significantly decreased in recurrent depressive

patients, and the percentage of the REM sleep was increased within the decreased time of sleep

[Thase et al., 1995]. This suggests the importance to health in maintaining an appropriate

amount of the REM sleep.



In patients with depression, who often report sleep problems, melatonin secretion is

reported to be impaired, and exogenous melatonin has been shown to restore sleep quality and

mood [Leppamaki et al., 2003]. Exogenous melatonin was also shown to improve mood and to

increase the REM sleep in depressed patients during the next day of administration [Bauer et al.,

1995; Spath-Schwalbe et al., 1998] although the improvement in mood and increased amount of

the REM sleep disappeared in the following day. Further, a high cortisol to melatonin ratio

(caused by impairment of night-time melatonin secretion) has also been shown to correlate with

impaired cell-mediated immune responses and with an increase in depressive mood [Fiorina et

al., 1999]. Hence melatonin, as well as cortisol appeared to have an important role regarding

sleep regulation in the psycho-neuro-endocrino-immune network.

Consequently it has been suggested that the sleep process itself plays an important role in

interactions in the psycho-neuro-endocrino-immune network [Krueger et al., 2003; Marshall &

Born, 2002].

1.2.2.4 Circadian rhythm and subjective well-being

Psychologically, the sleep-wake cycle is a robust regulator of human alertness [Hull et al.,

2003]. At the beginning of sleep, the body reduces the input of external stimuli (neural sensory

inputs) and there is also less physical movement (neural motor outputs). This sleep induction

and its maintenance are known to be helpful for consolidating memory in the awake learning

process, so that effective cognitive function in daytime can be preserved [Stickgold et al., 2001;

Stickgold & Walker, 2005; Walker et al., 2005]. Alertness and the cognitive effectiveness in

function have been discussed in relation to subjective well-being ratings and quality of life

during the daytime and to subsequent sleep quality at night. The most commonly used self-

report measure of sleep quality is the Pittsburgh Sleep Quality Index (PSQI) [Buysse et al.,

1989].

Sleep quality, as measured by the PSQI, has been reported to correlate with amount of

sleep, namely the sleep efficiency, and with the percentages of REM sleep in the total sleep-

time [Milross et al., 2002]. Sleep quality has also been shown to reported to correlate with the

quality-of-life [Cohen et al., 1998], and it has been suggested that improved sleep quality may

contribute to better quality-of-life [Myers & Badia, 1995]. Reciprocally, daytime relaxation

exercise has shown to improve the sleep quality [Shapiro et al., 2003]. It has also been

demonstrated that subjects with a high amplitude of alpha waves in daytime brain waves, which

represents a calmer or relaxed state of mind, sleep significantly longer and deeper [Ehlers et al.,



1998]. On the other hand, disorganization of the sleep-wake cycle was found to impair the

quality-of-life [Edell-Gustaffson, 2002; Edell-Gustaffson & Hetta, 2001].

Collectively, there may be an integrated relationship between night time well-being (sleep

quality) and day time well-being (quality-of-life), and the daytime well-being may contribute to

the night time well-being and vice versa in the psycho-neuro-endocrino-immune network.

1.2.3 Psychological input in the psycho-neuro-endocrino-immune network

The word ‘Stress’ was defined by Hans Selye, a physician and endocrinologist who

instigated stress research, as “the non-specific response of the body to any demand” [Selye,

1936]. Selye also emphasised the distinction between ‘Stressor’ (the cause) and ‘Stress’ (the

effect) [Selye, 1975a].

1.2.3.1 Stressor

Life events (such as trauma, disease, exercise and life-changing experiences) challenge

an individual’s capacity to adapt to inner and outer demands. These challenges may be

physiologically arousing and/or emotionally taxing, and these events may lead to cognitive and

behavioural responses.

Physiological stressors (including trauma, infection and starvation) affect human organ

systems directly through catabolic changes (energy consuming changes). Psychological

stressors(stimuli which arouse human emotions) can also affect human organ systems through

the effects of psychological stress, both directly via the psycho-neuro-endocrino-immune

network (i.e. appraisal of stressor acts as an input in the network) and by modulation of human

behaviour including eating habits, exercise, smoking and self-medication.

Stress related life-events have often been examined either in healthy populations using

academic examinations where NK-cells, in particular, were measured as a stress-related marker

[Deinzer & Schuller, 1998; Glaser et al., 1985; Gruzelier, Levy et al., 2001; Gruzelier, Smith et

al., 2001; Kiecolt-Glaser et al., 1986; Kiecolt-Glaser et al., 2001] [see also 1.2.4.2 and 1.2.4.3],

or in patient populations (i.e. clinically stressed individuals) who are persistently exposed to the

presence of life-long diseases. These life-long diseases often used in the literature include

malignancy (breast cancer in particular) [Antoni et al., 2001; Baider et al., 2003; Bakke et al.,

2002; Spiegel et al., 1989] and infections (particularly with the hepatitis virus or the human



immunodeficiency virus: HIV) [Antoni et al., 2002; Antoni et al., 2000; Carbone et al., 2000;

Cruess et al., 2003; Cruess et al., 1999]. The HIV infection is a life-threatening disease directly

related to the immune cells, particularly CD4 T-cells, so it may be considered as a good

example of a life-long stressor to both one’s biology and psychology. In addition, stress has

been shown to detrimentally affect the HIV disease progression [Catalan et al., 1995; Cole et al.,

2003; Cole et al., 1997; Cole et al., 1996].

Hence, the two subject groups used for in vivo investigation in this project were:

1. University students, facing academic examinations, as an example of individuals

with time-limited sustained stress, and the primary outcome measure was NK-cells;

and

2. HIV-infected adults, not receiving anti-retrociral medication, as an example of

individuals with on-going disease-associated stress, and the primary outcome

measure was CD4 T-cells.

1.2.3.2 Stress perception

One individual’s perception of a particular stressor will differ from another’s. Factors

affecting stress perception can be classified into three categories [Folkman & Moskowitz, 2004]

� Stressor-related: inherent quality (type), intensity and frequency;

� Environment-related: physical and social resources; and

� Individual-related: cognitive appraisal, coping skills, and personality.

Among these three factors, the individual-related factors are those most directly

susceptible to psychological influences [Han, 2002]. An individual’s appraisal of a stressor has

two elements [Lazarus & Folkman, 1984]:

1. Primary appraisal (perception of a demand, threat or stimulus); and

2. Secondary appraisal (judgement in one’s capability of coping with a threat).

Primary appraisal can be either neutral, benign or threatening [Text box 2]. When the

primary appraisal of a stressor was perceived as a threat, then consequently the secondary

appraisal would formulate and result in a coping action [Lazarus, 1999].



Text box 2: APPRAISAL OF A STRESSFUL LIFE EVENT

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Two types of coping with a threat have been hypothesised: (1) emotion-focused and (2)

problem-focused [Folkman & Moskowitz, 2004]. These may be mainly associated with the

levels of primary and secondary appraisal, respectively. Recently, an additional independent

coping strategy, meaning-making focused, has been proposed [Text box 3]. The meaning-

making-focused element was proposed as an independent coping strategy in which the person

weighs values, beliefs and goals to modify the meaning of a stressful transaction [Frankl, 1970],

particularly under sustained stress that may not be amenable to the first two elements [Park &

Folkman, 1997]. For example, the meaning-making coping was illustrated as the strategy

caregivers most frequently reported to employ when they have to cope with behaviours of

demented care-recipients [Gignac & Gottlieb, 1996].

Text box 3: ELEMENTS OF COPING WITH A THREAT

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These three coping strategies have been integrated and paraphrased into the concept of the

sense of coherence (SoC) [Antonovsky, 1993], in which stressful perception can be altered and

reduced through three components [Geyer, 1997]:

1. Comprehensibility: To make a stressor rational, understandable and/or predictable.

2. Manageability: To become capable of influencing directly upon and taking in

control of his/her stress-related environment.

3. Meaningfulness: To obtain worthy awareness by commitment in and investment of

his/her own existing resources.

It has been suggested that comprehensibility can be constructed through the individual’s

own thoughts and theories, despite an insecure situation; that manageability can be achieved by

active information-seeking strategies, by social support and by positive reinterpretation of the

situation; and that meaningfulness can be created by a close-relationship and a faith (or a belief

and confidence in one self and/or something greater) [Frankl, 1970] as well as by a behavioural

commitment / effort [Strang & Strang, 2001].

1.2.3.3 Psychological training intervention

Since psychotherapy began to appear as a formally recognised intervention within

medicine (particularly among mental health professions), hundreds of forms of psychotherapies

have been introduced [Roth & Fonagy, 1996]. In recent decades, the style of psychotherapy has

shifted in its main focus from a paternalistic style (i.e. giving a therapist-orientated therapy to a

client / patient) to an empowering style (i.e. training or providing a client / patient with self-help

/ self-administrated techniques including skills to get support so that they can manage stress by

themselves).

The latter type of psychological intervention has focused upon a training aspect, i.e.

teaching specific skills / techniques and encouraging clients / patients to use these in daily life

[Baider et al., 2001; Batey et al., 2000]. This type of intervention aims to help patients reduce

stress levels and improve well-being through the modification of behaviour, cognition, or

emotion [Miller & Cohen, 2001]. This type of intervention includes stress management

(behaviour therapy and/or cognitive-behavioural therapy [Antoni et al., 2000; Cruess et al.,

1999; Cruess et al., 2000]), relaxation methods [Gillani & Smith, 2001; Gruzelier, Levy et al.,

2001; Keefer & Blanchard, 2002], self-hypnosis or visualisation [Gruzelier, Levy et al., 2001;

Gruzelier, Smith et al., 2001; Whitehouse et al., 1996], and biofeedback or conditioning

interventions [Miller & Cohen, 2001; Raymond et al., 2005].



Based on the appraisal theories outlined above, it can be hypothesised that psychological

training and practice can alter stressful perception (primary and secondary appraisals) by

providing alternative or supplemental perspectives and coping skills for stressful life events.

Primary appraisal may be altered from a threat to a neutral or a benign stimulus by adjusting

individual reality, since one’s perception is based on one’s perspectives and experience. The

secondary appraisal may be altered by learning new coping skills in order to strengthen one’s

coping ability to the stressful perception.

Self-hypnosis

Among the many psychological interventions for self-administrated stress management,

one approach commonly used in clinical studies involves self-hypnosis training and practice

[Kiecolt-Glaser & Glaser, 1992; Kiecolt-Glaser et al., 2001]. Hypnosis (both with and without

self-hypnosis training) is arguably one of the more accepted therapies within complementary

medicine [Afari et al., 1999; Stewart, 2005], and self-hypnosis has been studied as a form of

psychological intervention for decades [Gruzelier, 2002a; Gruzelier, Levy et al., 2001; Schulz,

2001; Spiegel et al., 1989; Whitehouse et al., 1996].

One of the unique perspectives in hypnosis is the concept of the ‘hypnotic state’ , i.e. a

state of mind in which a person's normal critical or skeptic nature is bypassed [Gruzelier, 1998].

The hypnotic state is usually taught as an altered level of awareness or a state of mind where

one can gain more control over him- or herself and one’s cognitions about or perceptions of

‘ reality’ . This may increase the comprehensibility in the coping strategies [see above 1.2.3.2].

Self-hypnosis typically includes a focussing of attention, followed by mental and physical

relaxation, and mental imagery of ‘deepening’ in and ‘absorption’ into a hypnotic state. As a

‘suggestion’ in a hypnotic state, attention focused on exercises of anxiety-control, guided

imagery of health and the feelings of confidence and happiness, i.e. an increase in inner sense of

empowerment. This process aims to provide coping skills to increase the manageability

[1.2.3.2]. For the purpose of enhancing the manageability, some skills from the cognitive

behavioural therapy (CBT) were also provided as a supplementary technique in this project

[Appendix A-2i].

Johrei

The other training intervention for a self-administrated strategy applied in this project was

Johrei, a Japanese non-contact healing method which looks similar to the laying-on-of-hands



techniques. Johrei is classified under subtle energy medicine and as a category of

complementary medicine [Clarke, 2000] because it deals with imagery of ‘healing-light’ or

undiscovered ‘vital energy’ . During a Johrei session, the practitioner visualizes a spiritual

healing-light coming from an imaginary source (as if light comes from the Sun) and transmits

this to the recipient through the palm of his/her outstretched hand. As with other subtle energy

medicine methods like Therapeutic touch [Meehan, 1998; O'Mathuna et al., 2002], Ki [Chang,

2003] or Spiritual healing [Patterson, 1998], Johrei has its own philosophical background, in

other words, Johrei provides an alternative perspective of stressful life events.

The philosophical background of Johrei includes two key principles aiming to supply

alternative perspectives:

1. ‘Process of Purification’ which encourages changing one’s perspectives during

stressful and/or difficult periods, shifting from focusing on negativities of the moment

to focusing upon future outcomes when the problem period is over; and

2. ‘ IZUNOME’ which means a dynamic state of harmony in appropriate timing and

balance between two dichotomised concepts / attitudes, e.g. between endeavour to

persist making your own destiny with ‘Makoto’ (sincerity, integrity, truth and love

used for one’s self awareness) [Hardacre, 1988] and detachment to ‘ let go’ (trust in

natural time course which is beyond one’s control).

‘Johrei’ literally means “purification of spirit”, so the approach may also provide an

alternative or additional perspective on life events with the concept of spirituality [Seaward,

2000]. Experience of Johrei is a self -contained time when one can quietly, mindfully and kindly

concentrate upon the recipient’s benefit, as well as his/her own, since the Johrei practice is

based upon the concept that “one can heal oneself by healing others” [Naito, 2003].

Hence, Johrei differs from self-hypnosis in that it is practised mainly in pairs, although

self-Johrei and distant Johrei techniques can be provided, and in fact, were provided at the end

of training sessions in the current study. In addition, teaching appreciation of surroundings and

human relationships (namely ‘Spiritual Cords’ ) is given as a one of major five principles to

practise Johrei [Appendix A-2ii ]. These concepts may be collectively able to increase a sense of

receiving support (manageability) and to enhance the meaningfulness, both of which can

promote coping ability [1.2.3.2].



Possible alterations in the neural part of the network

Hypnosis, by definition, comprises three inter-linked processes [Stewart, 2005]:

1. Focused attention,

2. Induction of a hypnotic state, and

3. Receptiveness to suggestion.

Positive emission topography (PET) studies have implied that these processes of hypnosis

are not processes of simply following instructions but they involve a change of perception in the

brain, such as in visual perception [Kosslyn et al., 2000] and in pain sensation [Faymonville et

al., 2000]. Particularly in pain perception, it was suggested that there is a strong relationship

between the psychological state of mind and neurological response to pain stimulus, i.e. a pain

stimulus was shown to cause different neurological responses whether an increase or a decrease

in blood flow, depending upon the state of mind in the ‘hypnotic state’ [Montgomery et al.,

2000; Patterson & Jensen, 2003]. Hence, it was suggested that self-hypnosis may directly be

able to alter the primary appraisal at the unconscious level as well as at the conscious level.

On the other hand, few studies have investigated the physiological processes associated

with a Johrei session. Two preliminary studies have demonstrated that experienced practitioners

were shown to increase the power of alpha waves, which indicates an experience of relaxation,

during the Johrei session [Dwivedi et al. in preparation]. Single-blinded studies comparing a

Johrei session (receiver was sitting with eyes closed, separated by a curtain from the practitioner,

and given Johrei from behind) and mock session (the same setting with the same arm

movements of the same practitioner but with no intention by the practitioner to practise Johrei)

has demonstrated that simultaneously recorded brain waves from both practitioner and receiver

exhibited significantly increased levels of ‘mutual information’ in the alpha wave band (an

experience of relaxation) in the Johrei session, but not in the mock condition [Dwivedi et al. in

preparation]. This indicates that the Johrei session may increase their levels of relaxation.

Consequently, it was suggested that the practice of Johrei may directly be able to reduce stress

levels.

In summary, the two psychological training interventions, self-hypnosis and Johrei, were

intended to provide subjects with techniques to alter the perception of stressors, to enhance

coping skills and to provide profound relaxation [Text box 4], and thereby to reduce the effects

of stress upon the psycho-neuro-endocrino-immune network.



Text box 4: PSYCHOLOGICAL INTERVENTIONS IN THIS PROJECT

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1.2.4 Stress-associated changes

Published findings regarding stress-associated changes are complex and difficult to

summarize because of the huge variety of stressors, biological markers, and, time points at

which changes are observed or investigated that have been used in these studies. This latter

difference in published studies is particularly important with regard to the current project. It is

necessary, therefore, to be very specific regarding the timing of changes in stress responses that

will be measured.

1.2.4.1 Chronological definition of stress response

The chronological definition and distinction of stress responses are ambiguous and have

varied from study to study, even though Hans Selye introduced a concept that defined three

phases of stress responses as the name of the ‘general adaptation syndrome’ [Selye, 1975b]:

1. Alarm stage: triggering during which marshalled resources are organised;

2. Resistance stage: adaptation during which resistance to alarm rises above normal;

and

3. Exhaustion stage: when adaptation energy is used up.

Recently, it has been demonstrated by using a meta-analysis strategy that Selye’s three

categories of stress response may have counterparts within the immune system, and may

represent three different immunological modifications [Segerstrom & Miller, 2004]:

1. Up-regulation of innate immunity and suppression of adaptive immunity by short-

lasting (seconds to minutes) stress;

2. Cytokine shift from Th.1 to Th.2 [Elenkov & Chrousos, 1999] without consistent

changes in cellular immunity by temporal (hours to days) stress; and

3. Global immuno-suppression by long-lasting (weeks, months to years) stress.



In contrast, there is a well-used dichotomised chronological distinction in stress, i.e. acute

and sustained or chronic stress. In terms of the general adaptation syndrome, acute, momentary

or short lasting stress (henceforth acute stress) is defined conceptually as the stress that falls in

the period from the alarm stage to the resistance stage. Sustained or chronic stress (sustained

stress) is from the resistance stage to the exhaustion stage.

Considering the sleep-wake cycle as a biologically fundamental period, acute or sustained

stress in this thesis is defined on the basis of this cycle. That is, acute stress is defined as stress

that has its effects within one day or, in other words, a single circadian rhythm. In contrast,

sustained stress is defined as stress that has its effects for more than one day, i.e. over more than

one circadian rhythm. This can be construed as “Sustained stress alters circadian patterns of the

psycho-neuro-endocrino-immune network.”

Due to the nature of psychological intervention in which training and practice occur over

a protracted period (days, weeks and months), the effects of sustained stress upon mediators in

the psycho-neuro-endocrino-immune network are the central focus of interest in this thesis. The

working hypothesis in the project is that sustained stress disturbs psychological balance with

consequential influences upon the immune system, and the detailed changes observed under

sustained stress supporting this working hypothesis are explained below in conjunction with the

stress responses in the psycho-neuro-endocrino-immune network.

1.2.4.2 Acute stress responses in the neuro-endocrino-immune network

In the psycho-neural part of the psycho-neuro-endocrino-immune network, the primary

appraisal of acute stress, particularly reward and fear reactions, are bi-directionally regulated via

neuro-hormonal secretions [Charney, 2004]. In the nervous system, acute stress is shown to

activate the secretory neurons through aminergic and GABA-ergic innervations in the

autonomic nervous system [Cole & Sawchenko, 2002]. This aminergic pathway has been

reported to project directly to the CRF neurons in the HPA, but many of the other neural

networks utilise neural synaptic signals via an inhibitory GABA-ergic network [de Kloet, 2003]

including neurons in the SAM. For example, the excitatory inputs from limbic-cortical regions

modulate the GABA-ergic inter-neuronal network [Cole & Sawchenko, 2002; Herman et al.,

2002]. This has been suggested to provide a stressor a specific neuro-chemical signature to the

secretory neurons [Pacak & Palkovits, 2001].



In the neuro-endocrine part of the network, it was recently discovered that there are both

mineralocorticoid receptors (MCRs) and glucocorticoid receptors (GCRs) in the brain [de Kloet,

2000] as well as in the endocrine organs. Hence, de Kloet [2003] has hypothesised that the

MCRs and GCRs have inter-complementary effects against stress responses in the central

nervous systems. Specifically, it was hypothesized that (1) the sympathetic neurons and MCRs

respond to acute stress; and then that (2) soon after this response, the parasympathetic neurons

and GCRs facilitate:

1. Recovery of stress-induced acute immune responses;

2. Control of energy metabolism in the endocrine system; and

3. Promotion of information storage in the brain [de Kloet, 2003].

In the immune system, it has been elucidated via meta-analysis that acute stress increases

the number of NK-cells in the blood stream and NK cytotoxic activity, but that there is no

consistent effect upon the number of T-cells or B-cells [Segerstrom & Miller, 2004]. In addition,

it has been shown that the acute stress-induced increased NK cytotoxic activity, measured in

peripheral blood mononuclear cells (PBMCs), was not due to an increase in the per-NK-cell

cytotoxic activity but was due to an increase in percentages of NK-cells in PBMCs [Segerstrom

& Miller, 2004]. Furthermore, in the interaction between the endocrine and immune systems,

the acute stress-induced changes in immune cell distribution were shown to be associated with

the expression of the GCRs in mice [Dhabhar et al., 1996]. Diurnal changes in adrenal steroids

were known to be associated with changes of leukocyte distribution, i.e. the diurnal peak in

glucocorticoid (cortisol) levels coincided with a diurnal trough in the number of peripheral

blood lymphocyte and vice versa [McEwen et al., 1997].

Acute stress acting through the SAM and HPA axes of the neuro-endocrino-immune

network has been shown to have inter-complementary effects against stress responses, i.e. to

promote or to suppress inflammatory reactions [Chrousos, 1995; Huether, 1996]:

1. Promoting inflammation as the alarm or ‘ fight or flight’ response [Cannon, 1914;

Goligorsky, 2001]: the SAM axis is stimulated to produce catecholamines which

act as immunological ‘alarm signals’ by promoting secretion of pro-inflammatory

cytokines [Elenkov et al., 2000] by mainly stimulated monocytes [Straub, Mayer et

al., 2000]; and

2. Suppressing inflammation as a response to the alarm reaction (the resistance stage

in the general adaptation syndrome theory): acute stress is known to increase the



levels of cortisol [Rohleder et al., 2002] which can counteract the alarm signal and

suppress activation of the immune system [McEwen et al., 1997].

Historically, the concept of this counteracting mechanism in the endocrino-immune

pathway in the acute stress response was originally proposed by Besedovsky & Sorkin [1977]. It

was then paraphrased by Munck et al. [1984], who hypothesised that the stress-induced increase

in cortisol levels does not protect against the source of stress itself, but rather against the body’s

normal responses to stress. This process was suggested to prevent those stress responses from

excessive overshooting processes threatening homeostasis [Munck et al., 1984].

Although the whole picture of the mechanism of this cortisol-induced suppressive

immune response is yet to be investigated [Sapolsky et al., 2000], cortisol has been considered

as a main stress hormone which can suppress the immune response by affecting targets mainly

through its receptor (GCRs). This is considered to occur primarily by inhibiting the NF�B’s

genomic functions to promote non-specific inflammation and to inhibit apoptosis [Karin & Lin,

2002]. In contrast to cortisol, another adrenal hormone in the HPA axis, dehydroepiandrosterone

(DHEA; and its sulphate DHEA-S), has complicated effects. DHEA has been reported to

stimulate Th.1 cytokine (IL-2 etc.) production [Clerici et al., 1997; Cutolo et al., 2000; Loria,

2002] and to behave as an antagonist to cortisol in this Th.1 / Th.2 regulation [Wolf &

Kirschbaum, 1999]. DHEA, however, has also been shown to have a similar and/or synergistic

effect with cortisol, i.e. inhibiting the NF�B activation and suppressing pro-inflammatory

cytokines [Straub, Scholmerich et al., 2000].

Collectively, it has been suggested that adrenal hormones (cortisol in particular and

combined with DHEA/-S) play an important role in the endocrino-immune interaction with

regard to acute stress response in the psycho-neuro-endocrino-immune network.

1.2.4.3 Sustained stress and changes in the psycho-neuro-endocrino-immune network

Sustained stress has been demonstrated to induce various changes in the psycho-neuro-

endocrino-immune network. In the neuro-immune bi-directional interaction [Lawrence & Kim,

2000], the blood-brain-barrier permeability was found to be increased under Gulf War stress

[Freedman et al., 1996]. It has also been shown that inhibitory GABA-ergic nervous activity

was attenuated under sustained stress [Verkuyl et al., 2004]. These findings imply that the stress

responses in the neural level under sustained stress can be more hyperactive and then become

difficult to switch off, which may result in maintaining a vicious cycle of stress responses.



In the immune system, sustained stress has been demonstrated to alter tissue specific

distribution of lymphocyte sub-populations in vivo [Sudo et al., 1997]. Specifically, peripheral

NK-cell levels have been shown to decrease under sustained stress [Borella et al., 1999;

Gruzelier, Smith et al., 2001; Inoue-Sakurai et al., 2000; Maes et al., 1992; Segerstrom & Miller,

2004]. In contrast, the effects of sustained stress upon in vivo distribution of lymphocytes are

not clear-cut and are inconsistent in the literature, i.e. some investigators report increases and

others report decreases in the sub-population counts (e.g. helper T-lymphocytes [de Gucht et al.,

1999; Maes, Van Bockstaele et al., 1999] and cytotoxic T-lymphocytes [Gruzelier, Smith et al.,

2001; Maes, Lin et al., 1999]). Nonetheless, in functional in vitro measures of the immune

system, sustained stress has been shown to suppress cellular immune responses [Bauer et al.,

2001; Bonneau et al., 1998; Dhabhar & McEwen, 1997; Koh, 1998; Segerstrom & Miller, 2004].

Hence, sustained stress has been believed to cause a detrimental effect upon immune cells in

vivo resulting in an increased susceptibility to malignancy [Garssen, 2004] and infection [Cohen

& Herbert, 1996; Kiecolt-Glaser & Glaser, 1999].

Notably, there was a report [Bonneau et al., 1998] demonstrating that adrenalectomy in

mice prevented the suppressive effect of sustained stress upon the acute stress-induced immune

activation (measured by in vitro cytotoxic activity and cytokine production). Hence, adrenal

hormones were suggested to play an essential role in the immuno-suppressive effect of

sustained stress. Further, there are contradictive clinical findings with regard to cortisol levels

under sustained stress, i.e. cortisol levels are high in patients with the post traumatic stress

disorder (PTSD) and depression, and low (known as a hypocortisolism) in patients with

somatoform disorders (chronic fatigue syndrome, fibromyalgia, burnout syndrome etc.) [Heim

et al., 2000]. There have been two interlinked hypotheses regarding the mechanisms which

contribute to suppress cellular immune responses under sustained stress [Text box 5]:

1. Sustained exposure to high levels of cortisol; and

2. Attenuated responses caused by habituation to repetitive stimulation.

The primary mechanism of the first hypothesis, sustained exposure to high levels of

cortisol, is that the stress reaction in the HPA axis stays active if coping with stress falls under

the sustained stress, therefore targets are exposed to elevated levels of cortisol for a prolonged

time [de Kloet, 2003]. This may be associated with multiple positive feedback loops in the HPA

axis [Gold et al., 2002], then this sustained high levels of cortisol may exacerbate the imbalance

of interactions within the psycho-neuro-endocrino-immune network [de Kloet, 2003], including



loss of neurons in the hippocampus [Sapolsky, 2000]. Further, it is well-known that most

patients with depression have changed circadian patterns in the network, particularly in cortisol

levels, i.e. elevated trough and flattened peak levels with a narrowed range of fluctuation

[Goldsby et al., 2002; Weber et al., 2000]; as well as evidence of sympathetic hyperactivity

[Belanoff et al., 2002; Chrousos & Gold, 1992; Gold & Chrousos, 1999; Holsboer, 2001;

Schatzberg et al., 1985]. Furthermore, growing evidence suggests that the mediators of the SAM

and HPA axes are repeatedly elevated under sustained stress and often fail to shut off promptly

before experiencing another repetitive challenge by a stressor [McEwen et al., 1997].

The later mechanism, attenuated responses caused by habituation [Kirschbaum et al.,

1995; Schommer et al., 2003], is also known as a progressive diminution of the responses

against repetitive stimulation [Heim et al., 2000]. The attenuated response in hormonal secretion

has been observed in both the neural level (amygdala) [Carter et al., 2004] and the HPA axis

[Gaab et al., 2002; John & Buckingham, 2003; Pariante & Miller, 2001] as well as the cytokine

level [Gaab et al., 2005]. It has also been demonstrated that sustained stress attenuates the acute

stress responses in the endocrine and immune systems. As a commencing condition, acute stress

increases glucocorticoids and alter lymphocyte distribution in the blood stream of rats. The

greatest changes in these, glucocorticoid levels and alteration of lymphocyte distribution, were

seen on Day 1, but thereafter with repeated exposure to the same acute stress, the changes

decreased and reached their lowest at Day 35 [Dhabhar & McEwen, 1997]. Accordingly, it is

hypothesised that accumulated negative feedbacks from repetitive responses in both the SAM

and HPA axes result in impaired reactions in their hormone secretions.

Text box 5: SUMMARY OF HYPOTHESES Re: Stress-related changes of endocrine system which may

contribute to suppress cellular immune responses under sustained stress

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These may be able to represent the different stages of the sustained stress, i.e. the resistant

and the exhaustion stages in the Selye’s general adaptation syndrome. It should be noted,

however, that there remains confusion about the mechanisms that underlie sustained stress, and



whether these may be best thought of, as two consecutive stages that occur after another, or as

two distinct responses that occur in parallel. Other factors like genetic differences (e.g. gender)

may also contribute to this confusion, but reports still remain inconsistent [Lundberg, 2005;

Sauro et al., 2003]. Nonetheless, the cellular immune responses are believed to be impaired

mainly by either or both above mechanisms in the psycho-neuro-endocrino-immune network.

Hence, this project focused on the hypothesis that psychological intervention can counteract, or

at least buffer, the negative effects of sustained stress upon the psycho-neuro-endocrino-immune

network, particularly the immune system.

1.3 Approach taken

This thesis is based upon the hypothesis that psychological intervention acting through the

psycho-neuro-endocrino-immune network will counteract the detrimental effect of stress on the

immune system. Investigation was performed by using a series of in vivo and in vitro studies.

The psychological interventions used to counteract stress were Self-hypnosis and Johrei,

both of which provide training and practice of self-help stress management techniques.

University students facing examination were used as an example of a time-limited stressful

situation, and the primary outcome measures were NK-cell percentages and NKCA levels.

HIV-infected patients were used as an example of ongoing disease-associated stressful situation,

and the primary outcome measures was CD4 T-cell counts. A number of validated

questionnaires was used to demonstrate that examinations and on-going disease both induce

stress, and to explore the effects of the psychological interventions upon stress perception.

In addition, in vitro experiments were performed to explore the direct influence of the

stress hormone, cortisol, on the peripheral NK-cells and T-lymphocytes.



Chapter II

Materials and Methods




Materials and Methods

2.1 Participants with regards to outcomes and measurement time points

2.1.1 Student volunteers 53

2.1.2 Patient volunteers 56

2.1.3 Case matched patients from database 58

2.1.4 Laboratory volunteers 60

2.2 Psychological intervention

2.2.1 Self-hypnosis training 60

2.2.2 Johrei training 61

2.2.3 Mock intervention (Controls for the psychological trainings) 62

2.3 Self-report questionnaires

2.3.1 Stress perception 63

2.3.1.1 State anxiety score in the State and Trait Anxiety Inventory 63

2.3.1.2 Impact of Event Scale (IES) 63

2.3.1.3 Perceived Stress Scale (PSS) 63

2.3.2 Perceived quality of life 63

2.3.2.1 Locus of Control scale (LoC) 63

2.3.2.2 Mental Component Summary in the SF-36 (MCS) 64

2.3.2.3 Pittsburgh Sleep Quality Index (PSQI) 64



2.4 Materials and methods in vitro

2.4.1 Materials and experiment kits 64

2.4.1.1 Chemicals and reagents 64

2.4.1.2 Biological reagents 65

2.4.1.3 Fluorescently conjugated antibodies for flow cytometry analyses 65

2.4.1.4 Commercially available laboratory kits for colorimetric analyses 66

2.4.2 Equipments used for in vitro investigations 66

2.4.2.1 Flow cytometry 66

2.4.2.2 Colorimeter 68

2.4.3 Methods in vitro 69

2.4.3.1 Preparation of tissue culture medium for cell culture in vitro 69

2.4.3.2 NK cytotoxic activity measured by flow cytometry 70

2.4.3.3 NK-cell characteristics during NKCA assay measured by flow

cytometry 73

2.4.3.4 Proliferative response measured by [3H]-thymidine incorporation 74

2.4.3.5 T-cell characteristics after in vitro incubation measured by flow

cytometry 75

2.5 Statistical analyses 77



2.1 Participants with regards to outcomes and measurement time

points

2.1.1 Student volunteers

University students facing the academic examination period were recruited to investigate

the effects of a time-limited sustained stress (academic examinations) upon the perception of

stress and associated changes in immunological parameters, particularly NK-cell percentage and

NKCA levels. They were recruited through posters displayed in Imperial College London and

by word-of-mouth contacts using student research assistants (Psychology BSc students). Ethical

approval was granted from the Riverside Research Ethics Committee and all volunteers were

given detailed information sheets, interviewed and asked to sign an informed consent form [see

Appendix 1]. All subjects were asked to fast overnight before giving a morning blood sample

(between 8:00 and 9:00 a.m. in order to minimise diurnal effects [McGlone et al., 1991]), and

given a simple breakfast after their blood collection. At the end of the study, each participant

received £30 for travel expenses and inconvenience.

In total, 48 university students were recruited prior to their examinations. The median age

was 21 years and the range was 19-23 years with one participant of 37 years. There were 26

males and 22 females. Thirty nine of the participants were medical students at Imperial College

(from first to fifth year: specific years of the course were not recorded) and the remaining nine

were on other University of London courses (specific information was not recorded).

There were two examination periods and, for the Exam assessment point, students were

assessed within five days prior to their examinations [Figures 3 and 4]. Control (Non-exam)

periods for comparison with exam-periods were chosen as follows: for some students (Cohort

A), it was four weeks after examinations, and for the remainder (Cohort B), it was four weeks

after recruitment (which was four to eight weeks before Exams). Students were free to withdraw

from the study at any time without giving any specific reasons, and a total of 21 students

withdrew [Figures 3]. Blood samples were taken and questionnaires were completed at the

recruitment and at the Exam and Non-exam assessment points.



Withdrew (10) Withdrew (1) Withdrew (10)

Figure 3: Numbers of students recruited and remaining in the study at the Exam and Non-exam assessment time points. The number of drop-out students is also indicated.

Figure 4: Timing of the Exam and Non-exam assessment time points with respect to recruitment for individual students in the Cohorts A and B

Before combining Cohorts A and B to test the hypotheses that (1) academic examinations

cause stress in university students; and (2) psychological intervention can reduce stress effects,

comparability of the two groups at the Exam and Non-exam time points was confirmed by

statistical analyses comparing Cohorts A and B [Appendix 6: Tables A-1 to A-6]. The levels of

the PSS and the State anxiety score of the STAI, lymphocyte subsets distribution and NK

cytotoxic activity (NKCA) were compared. The levels of these measures were not different

between the two cohorts at the Non-exam time points, so the two cohorts were combined into a

single group in order to examine changes in the levels of these measurements.

A total of 27 students were studied, but not all of the participants provided complete data

sets. Some data were incomplete because of technical failure with the analyses and because

students did not turn up to provide samples or failed to complete questionnaires. Consequently,

the numbers in each analysis to test the first hypothesis that academic examinations cause stress

in university students were:

Cohort B

0

4

8

12

Exam

Cohort A

0

4

8

12

Exam

We

eks

from

the

Re

crui

tme

nt

Recruitment Recruitment

Non-exam

Non-exam

Non-exam [Cohort B (26)]

Recruitment(48)

Exams [Group B (16)]

Exams [Cohort A (21)]

Non-exam [Group A (11)]

4 weeks 4-8 weeks



� Perceived stress scale (PSS) analysis: 22 students

� State anxiety score analysis: 25 students

� NK cytotoxic activity analysis: 21 students

� CD4 and CD8 T-cells and NK-cell analyses: 26 students

In order to test the second hypothesis that psychological intervention can reduce stress

effects, the same 48 university students, as described above, were each randomly assigned to

one of three groups:

� Relaxation control group: experiencing mock neuro-feedback sessions,

� Self-hypnosis group: taught and practising Self-hypnosis with imagery, or

� Johrei group: taught and practising a novel Japanese stress management system.

For both Cohorts A and B, training and practice of either intervention commenced at

recruitment and was encouraged to continue until their examinations, therefore, for Cohort A,

training and practice lasted four weeks and, for Cohort B, eight to twelve weeks. For analyses,

both examination data were combined [Figure 5].

Withdrew (11) Figure 5: Timing of training, follow-ups and data-collection sessions (Baseline and Exams assessment

points) and numbers of students at the sessions

Of 48 students recruited, 11 withdrew from the study. Complete datasets were not

obtained for the 37 students remaining. Hence, the number of subjects varied for each analysis

comparing between the psychological intervention groups and the Relaxation control group:

� PSS 32 students

� State anxiety score in the STAI 35 students

� NK cytotoxic activity 31 students

� Lymphocyte sub-populations and NK-cells 34 students

4 weeks 4-8 weeks

PPrr aaccttiiccee && ffooll llooww--uuppss Training -session

Baseline(48)

Exams (16)

Exams (21)



2.1.2 Patient volunteers

After approval from the Riverside Research Ethics Committee, HIV-infected patients who

were not receiving anti-retroviral treatment (treatment naïve HIV-patients) were recruited to

investigate (1) the effects of on-going disease (HIV-infection) upon stress perception and

associated changes in immunological parameters, CD4 T-cell counts in particular; and (2)

whether psychological intervention can reduce stress effects. The clinical immunological data

were obtained from the patient record database at the Chelsea and Westminster Hospital.

A total of 63 HIV-infected individuals including three females, with a median age of 37

years (range 27-58 years) who were regular attendees to the St. Stephen’s clinic at the Chelsea

and Westminster Hospital, were recruited by a research assistant, Mr. Bryan M. Bennett, and

research nurses according to the inclusion criteria: (1) not receiving anti-retroviral treatment, (2)

no symptom regarding HIV-infection and (3) more than 200 cells per �L of CD4 T-cells’ in

their peripheral blood. The HIV-infected participants were given detailed information sheets and

each gave signed informed consent. They participated for more than five months in the study,

during August 2003 to December 2004.

For the study investigating the effects of on-going disease (HIV-infection) upon stress

perception and associated changes in disease parameters, the rate of decline in CD4 T-cell count

was calculated between the recruitment time point and four months later as the primary outcome

measure of the study. The timing of clinical check-ups with regard to the two time points for the

psychological assessment (the Recruitment and After 4 months) was as follows [Figure 6]:

Figure 6: Timing of the measurement collection time points (Recruitment and After 4 months) and the one-month blocks (Baseline, Term one to Term four) for clinical routine blood collections

Unfortunately, not all of the patients recruited had their CD4 T-cell counts measured at

each Term [Table 4].

Term one Baseline

-- RReeccrr uuii ttmmeenntt -

-- AAff tteerr 44 mmoonntthhss --

Term four

4 months

Term two Term three



Table 4: Number and percentage of HIV-infected individuals who had CD4 T-cell counts check at the monthly time periods from the Recruitment to four months after the recruitment (Term 4)

Numbers of patients (Total N = 63) Valid number Missing

N Percent N Percent Term 4 (four months after the Recruitment time point) 23 36.5% 40 63.5% Term 3 (three months after the Recruitment time point) 18 28.6% 45 71.4% Term 2 (two months after the Recruitment time point) 19 30.2% 44 69.8% Term 1 (one month after the Recruitment time point) 14 22.2% 49 77.8% Baseline (2 weeks before and after the recruitment) 22 34.9% 41 65.1%

The rate of decline in the CD4 T-cell counts (CD4 gradient) was therefore calculated from

those individuals who had at least two measurements made in the assessment period. Of the 63

participants recruited, only 38 patients (60.3%) had sufficient data from which to calculate the

rate of decline in the CD4 T-cells during the four month plus one month (five months

altogether) study period, and their data were used to investigate the association between stress

perception and disease progression.

The same 63 HIV-infected individuals were randomly assigned to one of three groups:

� Control (wait-listed control: waiting for four months before being randomly

assigned to the Self-hypnosis or Johrei) group,

� Self-hypnosis training and practice group, and

� Johrei training and practice group.

Randomisation utilised random numbers generated by a researcher blind with a computer.

It was performed by using study numbers at recruitment, and then these anonymised

participants were assigned to one of the groups. Although the initial number of people in each

group at randomisation generated by a computer was almost equal, some subjects withdrew

before the training session was started (i.e. they did not turn up the first session) resulting in

different numbers of participants in each group. There were 23 participants in the Self-hypnosis

and 16 participants in the Johrei and 24 in the wait-listed control groups. The psychological

interventions were administered to seven Self-hypnosis and eight Johrei training cohorts.

At recruitment (Baseline) and after the intervention period (after 4 months) [Figure 7], the

participants were asked to complete psychological questionnaires. Of 63 patients, a total of

twelve patients either withdrew from the study or failed to complete some of questionnaires

before the end of the one-month training sessions. Hence, a total of 51 subjects (21 in Self-

hypnosis, 12 in Johrei and 18 in wait-listed controls) completed questionnaires. Lymphocyte

subpopulation and HIV viral load data were obtained from the pre-existing patient database, and

only 38 subjects (15 in Self-hypnosis, 10 in Johrei and 13 in wait-listed control groups) had



sufficient data from which to calculate the rate of decline in the CD4 T-cells during the study

period.

Figure 7: Timing of the two measurement points (Recruitment and Post-intervention) with regard to the period of training and practice of the psychological interventions

2.1.3 Case matched patients from the database

The same HIV-infected individuals recruited to the above RCT study were analysed in

this case controlled study. The previous RCT study used a wait-listed control group, so after the

four months of the waiting period, they were randomly assigned to either the Self-hypnosis or

Johrei training group over the period from August 2003 to December 2004. This increased the

number in the two groups:

� Self-hypnosis: 34 subjects consisting of seven training cohorts

� Johrei: 29 subjects consisting of eight training cohorts

In addition to these participants, 58 matched database control patients were selected

blindly from the same HIV patient database with permission from the Ethics committee. This

selection was performed by an independent research doctor, Dr. Alan W. Steel, with the

following inclusion criteria:

1. CD4 T-cell counts > 200 cells /�L

2. HIV viral load > 1000 viral copies /ml

3. Study period – same 12 months spread to minimise seasonal variation; and this

results in eight control cohorts with regard to commencing month for analysis

4. Equivalent mean CD4 T-lymphocytes counts with that of participants at the

commencing month of training intervention.

CD4 T-cell counts and viral load levels were obtained from the patient database. The

Training time point was set as the midpoint of the one-month training interventions and

subsequent terms were named after the number of months from the Training time point (e.g.

Term one is one month from the Training time point) [Figure 8].

PPrr aacctt iiccee && FFooll llooww--uuppss

Term one Baseline -- RReeccrr uuii ttmmeenntt -- -- PPoosstt--iinntteerr vveenntt iioonn --

Term four

1 month 3 months

Training



Figure 8: Time-points (Training time point and the Terms according to the Training).

Intervals between the doted-lines represent one term (one month)

The CD4 change gradients were compared between the intervention groups (Self-

hypnosis and Johrei) and the database control group. For each individual, a CD4 decline

gradient (cells per �l per month) was calculated retrospectively from the preceding 12 months’

data held on the patient record database (Pre-intervention). These pre-intervention CD4

gradients were compared between the three groups. Similarly, a post-intervention CD4 gradient

was prospectively calculated. The CD4 gradients in the 12 month periods prior to and after the

Training (Pre-intervention vs. Post-intervention) [Figure 9] were compared within and between

the three groups.

Figure 9: Comparison format with regard to the Training time point (Pre-intervention vs. Post-

intervention). Intervals between dot-lines represent one term (one month) as in Figure 8

Seven patients in the Self-hypnosis group, ten patients in the Johrei group and nine

patients in Database-controls were excluded because no routine blood samples were taken

during the 12 months either prior to or after intervention commenced. In these excluded patients,

several patients commenced anti-retroviral medication during the Post-intervention period, and

they were dropped from the study. Table 5 shows the numbers of patients who started drug

therapy in each group.

Table 5: Number and month of subjects who started anti-retroviral medication and dropped from the

study (NB: Term X represents that X months after the Recruitment time point) Term 2 Term 5 Term 8 Term 11 Total

Database controls 0 1 3 3 7 Self-hypnosis 0 0 2 4 6

Johrei 1 0 1 1 3

PPrr aacctt iiccee && FFooll llooww--uuppss Training

Post-intervention Pre-intervention TTrr aaiinniinngg

4 months

TTrr aaiinniinngg

Baseline Term one Term four

1 month 3 months



2.1.4 Laboratory volunteers

Thirty one healthy volunteers, of whom 21 were males and 10 females, with an age range

of 21-60 years, were recruited to donate blood in order to investigate the effects of in vitro

exposure to the stress hormone, cortisol, upon both NK-cells and T-lymphocytes.

This recruitment was through word-of-mouth contacts with the author and colleagues

from the Department of Immunology and the Division of Neuroscience and Mental Health. All

blood samples were collected between 9:30 and 11:30 a.m. to eliminate the effects of diurnal

variation [McGlone et al., 1991] and then either isolated peripheral blood mononuclear cells

(PBMCs) or whole blood were assayed straight after collection.

2.2 Psychological intervention

2.2.1 Self-hypnosis training

The self-hypnosis training, designed and conducted by an experienced clinical hypnotist

Dr. Tannis M. Laidlaw, consisted of four weekly sessions (two hours each).

The participants learnt first a Spiegel-type eye-roll induction (synchronising upward eye-

rolls with a deep inspiration from the nose, followed by holding the breath for a few seconds,

then eye-rolls down with expiration from the mouth) for ‘instant relaxation.’ They were also

taught a slower relaxation-type induction technique to achieve getting into a state of mind,

‘hypnotic state.’ All participants were provided with a standard audio-recording [Appendix 2-i]

which provided instructions for both inductions. Previous research has shown that university

students practising immune strengthen imagery in the self-hypnosis training had less cold

symptoms during their academic examination period than students practising relaxation imagery

[Gruzelier, Levy et al. 2001]. It was also shown in patients with genital herpes that self hypnosis

contributes to a reduction in disease-related symptoms [Fox et al. 1999; Gruzelier et al. 2002].

Hence, the induction technique was later combined with a specific imagery of immune

strengthening, which participants were told to practise under the ‘hypnotic state’ . Further, all

participants were taught two anxiety management techniques:

1. How to use breathing techniques to control acute anxiety [Laidlaw, 1994]; and

2. The Interrupt Distraction Procedure (IDP) [Laidlaw, 1999] for worries and belief

change.



Each participant was requested to practise self-hypnosis daily to learn and familiarise

themselves with the technique [Gruzelier et al., 1998]. During one-month training period, each

participant attended four group sessions with the hypnotist and each was expected to perform, at

least, more than ten self-hypnosis sessions. Diaries were kept by the participants to record their

practice frequency at home. After the four weekly training sessions, monthly follow-up group

sessions were continued for at least four months by HIV-infected individuals.

2.2.2 Johrei training

The Johrei training was planned and conducted by the author who is a trained practitioner

with more than 20 years of practice and who is also medically qualified. Original teaching

textbooks and support were provided by the Johrei Academy [http://www.johrei.org.uk/] and

Johrei Association [http://www.johreiassociation.co.uk/] so that the author could teach, edit and

adjust for each group of participants in the studies [Appendix 2-ii ] [See also the Johrei

Foundation, http://www.johreifoundation.org/; Izunome, http://www.izunome.org/johrei.cfm;

and Johrei institute, http://www.johrei-institute.org/ourpeople.asp]

The Johrei intervention consists of four weekly training sessions (two hours each)

involving core principles needed to practise Johrei techniques such as “healing oneself by

healing others” ; state of harmony, balance and timing (IZUNOME), and an introduction to the

three foundations of Johrei philosophy which emphasises importance of:

1. Awareness of spiritual well-being (Art of living / Art of Healing);

2. Appreciation of aesthetics (Art and Beauty) ; and

3. Appreciation of Nature including farming practice (Art of Nature).

In Johrei practice, the practitioner imagines an ethereal ‘healing-light’ entering his body

and being transmitted through his/her hands towards the recipient. The practitioner, without

touching a recipient, slowly moves his/her hands from the head down to the kidney area, front

and back. The procedure takes approximately 15 minutes in silence. The participants were

requested to practise Johrei daily with a partner, but at the end of training period, self-Johrei and

distant Johrei techniques were introduced as supplementary tools so that participants could

practice when a partner was not available.



As in the hypnosis group, it was requested that each participant practise Johrei at least

four times a week to learn and familiarise themselves with the technique. Diaries were used to

record practice frequency at home. Group monthly follow-up sessions were continued for at

least four months.

2.2.3 Mock intervention (Controls for the psychological trainings)

This mock neuro-feedback condition was aimed to provide a control against possible

placebo effects from participants’ expectation and against factors of attention given and

experience of relaxation during their training sessions since this procedure was shown to

generate a relaxation response when used as a control condition [Egner et al., 2002].

This condition appeared to be high-tech, with two computers and electrodes fixed to

earlobes and the centre of the scalp, and with auditory relaxing feedback sounds (babbling

brook and ocean wave) heard over headphones. The sounds were supposedly representing alpha

and theta wave feedback from the participant’s own brain waves associated with relaxation.

Although the procedure was real, the feedbacks were false as the sounds were recorded

previously from another session.

The participants in this group had eight mock neuro-feedback sessions over one month,

and these sessions were performed by Dr. Dwivedi, a qualified clinical psychologist, with valid

neuro-feedback equipment.

2.3 Self-report questionnaires

Primary appraisal in stress perception (anxiety level and impact of a stressful event),

secondary appraisal, sense of ‘ taking control of one’s own life’ , psychological functioning

(mental quality of life) and sleep quality were measured by using the following published

questionnaires.



2.3.1 Stress perception

2.3.1.1 State anxiety score in the State and Trait Anxiety Inventory [Spielberger et al., 1970]

The State and Trait Anxiety Inventory scale was designed to measure the levels of anxiety

both at the exact time the questionnaire was filled in (state anxiety) and as a general tendency

(trait anxiety). State anxiety level was measured and analysed in the current project. High scores

are associated with anxiety.

2.3.1.2 Impact of Event Scale (IES) [Horowitz et al., 1979; Joseph, 2000; Sundin & Horowitz,

2002]

The Impact of Event Scale (IES) measures the amount of stress which results from a

psychologically traumatising event, such as a diagnosis of HIV infection. High scores are

associated when event being perceived as a stressor. This IES was measured and analysed in the

study using HIV-infected individuals in this current project. High scores are associated with

high impact of the event.

2.3.1.3 Perceived Stress Scale (PSS) [Cohen et al., 1983]

The Perceived Stress Scale (PSS) is a scale designed to measure the secondary appraisal

of stress over a period (two weeks or a month) with the definition that “perceived stress is the

degree to which situations in one’s life are appraised as stressful (unpredictable, uncontrollable

and overloading.” High scores are associated with stress.

2.3.2 Perceived quality of life

2.3.2.1 Locus of Control scale (LoC) [Furnham & Steele, 1993; Wallston et al., 1978]

The Locus of Control scale (LoC) measures the perception of capability of controlling a

event [Schmitz et al., 2000]. Low scores are associated with high sense of taking control of

one’s own life, as saled from 0 (totally internal) to 24 (totally external) [Rotter, 1967]:

� Individuals who have an internal locus of control believe that events result primarily

from their own behaviour and actions.

� Those who have an external locus of control believe that powerful other partners, fate

or chance, primarily determine events. High scores are associated with low control.



2.3.2.2 Mental Component Summary in the SF-36 (MCS) [Ware et al., 1994]*

The SF-36 is a scale developed to measure the levels of quality of life. This consists of

two subsets, i.e. Physical and Mental health clusters as scales of the Physical Components

Summary (PCS) and the Mental Components Summary (MCS). High scores in each subset are

associated with a high perceived quality of life physically (PCS) and mentally (MCS),

respectively. The MCS was measured and analysed in the study using HIV-infected individuals

in this current project. High scores are associated with high psychological functioning.

2.3.2.3 Pittsburgh Sleep Quality Index (PSQI) [Buysse et al., 1989]

The Pittsburgh Sleep Quality Index (PSQI) is a scale developed to measure the subjective

quality of sleep combined with behavioural items, e.g. sleep duration. High scores are

associated with low sleep quality.

All self-report data anonymised and depersonalised to protect the confidentiality of the

study participants. All data collection and entry was performed by research assistants blind to

the treatment conditions of the study participants.

* Note: The SF-36 scales, including the Mental Component Summary (MCS), are

scored such that higher scores represent better functioning (in this case, higher

psychological functioning), and lower scores represent poorer functioning. In all of

the other measurements used in this study, higher scores represent poorer functioning.

2.4 Materials and methods for in vitro investigation

2.4.1 Materials and experiment kits

2.4.1.1 Chemicals and reagents

The following Materials were purchased from Sigma (Dorset, U.K.,

http://www.sigmaaldrich.com/)

� RPMI 1640

� 1% glutamine (200 mM)

� 1% penicillin (5000 IU/ml) / streptomycin (5000 mcg/ml)

� 1% Hepes buffer



� 1% non-essential amino acids (100 x)

� 1% sodium pyruvate (100 mM).

� Foetal calf serum (FCS)

� Phosphate buffer saline (PBS)

� Lymphoprep® (for peripheral blood mononuclear cells separation)

� Paraformaldehyde (PFA)

� 0.05% Eosin dye

� Propidium iodide (PI)

� Phytohaemagglutinin (PHA: mitogen)

� Staphylococcal enterotoxin B (SEB: super antigen)

� Hydrocortisone

Radioactive [3H] thymidine was purchased from the Amersham [Amersham Pharmacia

Biotech, Buckinghamshire, U.K., http://www6.amershambiosciences.com/]

2.4.1.2 Biological reagents

The antigens of purified protein derivative (PPD: tuberculosis antigen) and Herpes

Simplex virus common antigen (Herpes) were provided by the Immunology clinical laboratory

at Chelsea and Westminster hospital.

The K562 cell line, a human chronic myelogenous leukaemia cell line for NK cytotoxic

activity measurement, was purchased from the European collection of cell cultures [ECACC,

Salisbury, U.K.].

2.4.1.3 Fluorescently conjugated antibodies for flow cytometry analyses

Antibody cocktails of CD45-FITC/CD3-PE/CD4-Cy-Chrome/CD8-APC and CD45-

FITC/CD3-PE/CD19-Cy-Chrome/CD56-APC, standard panels of fluorescently conjugated

antibody cocktails for lymphocyte subpopulation analyses, were purchased from Beckman

Coulter [Beckman Coulter, Bedfordshire, U.K., http://www.beckmancoulter.com/]

Individual antibodies of CD3, CD4, CD8, CD45, CD56, CD16, CD25, CD95, Nkp30,

Nkp46 and Annexin V (conjugated with FITC, PE, Cy-Chrome or APC) were purchased from

Becton Dickinson [Becton Dickinson, Oxford, U.K., http://www.bd.com/].



2.4.1.4 Commercially available laboratory kits for colorimetric measurement

The CytoTox96®, a kit measuring NK cytotoxic activity, was purchased from Promega

[Promega U.K., http://www.promega.com/]. This CytoTox96® analysis includes measurements

of released Lactate dehydrogenase (LDH) in the supernant of the cultured medium (after 4-hour

incubation of mixed K562 cells and PBMCs) which contains certain levels of LDH from dead

cells. This kit was used in order to avoid using radio-active substance which is required in the

gold standard method, the 56Cr-release assay [Promega, 2004].

ELISA kits for measuring the levels of cortisol, DHEA-S and melatonin were purchased

from iDS [iDS U.K., http://www.idsltd.com/].

2.4.2 Equipments used for in vitro investigation

2.4.2.1 Flow cytometry

Flow cytometry is a method for quantitating components or structural features of cells

primarily by optical means. Flow cytometry measures one cell at a time, but it can process

thousands of cells in a few seconds. The cells are passed single-file through a laser beam by

continuous flow of a fine stream of the suspension. Each cell scatters some of the laser light,

and also emits fluorescent light excited by the laser come from the labelled fluorescent

conjugated antibodies designed to bond specific particle on the cell surface or in the cytoplasma.

The five main components of flow cytometry are:

1. Flow cell - liquid stream (sheath fluid) carries and aligns the cells so that they pass in

single file through the light beam

2. Light source - commonly used is high power water-cooled argon and/or krypton laser

3. Electronic detector which can quantitate the faint flashes of scattered and fluorescent light

4. Analogue to Digital Conversion (ADC) system which generates forward scatter (FSC)

and side scatter (SSC) signals as well as labelled fluorescence signals

5. Computer for analysis of the signals, and to record data for thousands of cells per sample,

and to display the data graphically and numerically

6. Statistical analysis can be done simultaneously or afterward using an analysis programme



DDeebbrr iiss

LL yymmpphhooccyytteess

MM oonnooccyytteess

GGrr aannuullooccyytteess

FSC

SSC

Data acquisition

The cytometer typically measures several parameters simultaneously for each cell:

� Low angle forward scatter (FSC) intensity, proportional to cell diameter

� Orthogonal (90 degree) scatter intensity, approximately proportional to the quantity of

granular structures within the cell (SSC)

� Fluorescence intensities at several wavelengths

(each FL-1, FL-2, FL-3 and so on associate with a

defined structure identified by a fluorescent probe)

Light scatter alone (FSC and SSC graph: e.g. Figure 10)

is commonly used to exclude dead cells, cell aggregates, and

cell debris from the fluorescence data. It is sufficient to

distinguish lymphocytes from monocytes and granulocytes in

blood leukocyte samples. Figure 10: FSC vs. SSC dot plot

Fluorescence intensities are typically measured at several different wavelengths

simultaneously for each cell. Fluorescent probes are used to report the quantities of specific

components of the cells. Fluorescent antibodies are often used to report the densities of specific

surface receptors, and thus to distinguish subpopulations of different cell types.

Gating and data analysis

In order to analyse characteristics of specific immune cell sub-population, selection of the

cells needs to be precise and efficient. This selection is performed by making a gate of region in

a dot-plot during flow cytometry analyses, for example:

1. After setting up flow cytometer for acquisition, create a dot plot with the X-axis as

forward scatter (FSC) and the Y-axis as side scatter (SSC).

2. Acquire data from cells, and draw a circle around a region of the lymphocytes based

on their light scatter characteristics on the plot (FSC vs. SSC). This becomes a region

1 (R1), the red circle of lymphocyte in the Figure 10 for example.

3. For further analyses, create another dot plot that encompasses the cells from the R1 in

the plot with fluorescents (FL1 vs. SSC or FL1 vs. FL2 etc.).

Precision of percentage in lymphocyte sub-population measured by flow cytometry

Methodological variation in lymphocyte percentages was assessed in three preliminary

blood samples from one volunteer. Nine sample tubes of blood were taken at each time point,



and assessed for percentages of cells expressing CD45+CD3-CD56+ (henceforth NK-cells) and

CD45+CD3+CD4+ (CD4 T-cells) and CD45+CD3+CD8+ (CD8 T-cells).

Fluorescently conjugated single antibodies of CD3, CD4, CD8, CD45, CD56 and CD16

[Becton Dickinson, Oxford, U.K.] were used to determine NK cells (Cytotoxic and Regulatory

NK-cell subsets) and T-lymphocytes (CD4 T-cells and CD8 T-cells). Cell samples were

measured by a FACSCalibur flow cytometer [Becton Dickinson] and the data generated by flow

cytometer were analysed by a CellQuest software.

Means and ranges were within normal limits [Hannet et al., 1992] and standard deviations

were calculated in individual occasion and in total [Table 6].

Table 6: Mean percentages and counts (standard deviation: SD) of NK-cells, CD4 and CD8 T-cells and

total lymphocyte counts using a single volunteer (9 tubes collected and averaged on 3 separate occasions) NK %

(SD) CD4% (SD)

CD8% (SD)

NK count (SD)

CD4 count (SD)

CD8 count (SD)

Total lymph count (SD)

Time1.

9.7 (0.54)

48.1 (0.97)

29.6 (0.73)

94.8 (9.3)

438.4 (12.7)

270.0 (11.3)

894.3 (32.0)

Time2.

8.3 (1.31)

46.8 (0.89)

28.8 (0.33)

65.6 (12.6)

346.1 (10.7)

213.4 (9.8)

712.6 (36.2)

Time3.

14.3 (0.72)

44.4 (0.52)

28.2 (0.60)

130.3 (8.7)

381.0 (36.4)

249.3 (11.6)

859.2 (33.6)

Total mean (SD)

10.77 (0.86)

46.4 (0.79)

28.9 (0.55)

96.9 (10.2)

388.5 (19.9)

244.2 (10.9)

822.0 (33.9)

Hence, all changes in percentages of NK cells, CD4 T-cells and CD8 T-cells more than

twice of standard deviations in total means, i.e. 1.90, 1.58 and 1.10 % respectively, were

considered as in out of the 95 % confident interval. Changes in each cell sub-population more

than these percentages are considered as a difference between samples, and the statistical

analyses are performed with this consideration in the current project.

2.4.2.2 Colorimeter

The colorimeter is an apparatus that allows the absorbance of light at a particular wave-

length or frequency (colour) of visual light to be determined. Different chemical substances

absorb varying frequencies of the visible spectrum. Colorimeters rely on the principle that the

absorbance of a substance is proportional to its concentration, i.e. a more concentrated solution

gives a higher absorbance reading.

A quantitative reading for the concentration of a substance can be found by making up a

series of solutions of known concentration of the chemical under study, and plotting a graph of



absorbance against concentration. By reading the absorbance of the specimen substance on the

graph, a value for its concentration is found.

Method of the enzyme linked immuno-sorbant assay (ELISA) [Voller, 1978]

The ELISA is ideally suited to assaying protein factors e.g. hormones but can be adapted

to measure small molecules as well. In the current project, various commercially available

ELISA kits [iDS U.K., http://www.idsltd.com/] and CytoTox96® [Promega U.K.,

http://www.promega.com/] were purchased and used for measurements of the hormone levels

and LDH levels to determine these concentrations.

2.4.3 Methods in vitro [See also Appendix 4. for detailed procedures]

2.4.3.1 Preparation of tissue culture medium for cell culture in vitro

Tissue culture medium (TCM) was used for incubation of cells in the project. It consists

of RPMI 1640 supplemented with 1% glutamine (200 mM), 1% penicillin (5000 IU/ml)/

streptomycin (5000 mcg/ml), 1% Hepes buffer, 1% non-essential amino acids (100 x), 1%

sodium pyruvate (100 mM).

Cortisol level in the tissue culture medium

In order to supply essential nutrition for cell culture, 10% Fetal Calf Serum (FCS:

Sigma®) was added in tissue culture medium (TCM) when cells were incubated in vitro.

ELISA assays show that the tissue culture medium containing 10% FCS contains 5.9nM

cortisol; and this was small in comparison to the amount of cortisol found in plasma in the 34

volunteers (29.5 - 265.8nM; mean 131.8, SD = 50.3) [Figure 11].

0

50

100

150

200

250

300

Figure 11: Individual cortisol levels in the tissue culture medium (left: 5.9 nM)

and in plasma from 34 volunteers (right: 29.5 - 265.8 nM)



Conclusion:

The level of cortisol in the TCM was low, and thereafter in this thesis, TCM only was

considered to be cortisol free.

2.4.3.2 NK cytotoxic activity measured by flow cytometry [Godoy-Ramirez et al., 2000]

Detailed procedures are given in the Appendix 4.

Effector cells (PBMCs):

Peripheral venous blood samples were collected using Vacutainers [Becton Dickinson,

Oxford, U.K.]. Heparinized blood was centrifuged (1500 rpm for 10 minutes at room

temperature). The plasma was removed and the blood pellet reconstituted by the addition of

RPMI 1640. This was then mixed and overlaid onto Lymphoprep. PBMC were recovered from

the interface after centrifuging (1500 rpm) for 30mins at room temperature [Boyum, 1974].

Viability was assessed and adjusted by dye (Eosin 0.05 %) exclusion.

The separated effector cells (PBMCs) by LymphoPrep® were washed twice and

suspended in the TCM; then 10 �l of anti-human CD45 monoclonal antibody directly

conjugated with fluorescein isothiocyanate (FITC) was added and incubated for 20 minutes.

These cells were washed again, and after the last wash, concentration of cells was assessed by

counting cells with dye exclusion, and the cell concentration adjusted to 5 x 106 cells / ml by

adding TCM prior to mixing with target cells, i.e. K562 cells, for the NKCA assay.

Target cells (K562 cell line):

K562 haematopoietic tumour cells served as the target cell for determining NK cytotoxic

activity. K562 cells are a human erythromyelocytic leukaemia cell line, which may transform if

allowed to overgrow resulting in losing their sensitivity to be killed by NK-cells. Hence, the

K562 cell line should be renewed every one to two months, by starting with a new batch of

frozen cells from the liquid nitrogen freezer.

In order to maintain a ready supply of cells in the optimal growth phase for the NKCA

assay, optimal duration and concentration of K562 cells during cell culture were examined by

determining the growth characteristics of this cell line.



Growth characteristics of K562 cell line used as targets for assessing NKCA

K562 cells should be in the logarithmic growth phase for the use of NKCA assay, as cells

in the early (developing) and late (saturated) phase of their development are resistant to killing.

K562 cells (recovered from frozen sample) were cultured at various seeding concentrations of

1.5 x 104, 1.5 x 105 and 1.0 x 106 cells per ml in 10 ml flasks with tissue culture medium, and

each flask was placed at 37oC in a 5% CO2 humidified incubator for 3 days. The K562 viable

cell concentration in each flask was assessed on Day 0, 1, 2, and 3 and simultaneously the

percentage of dead cells was measured [Figure 12].

Figure 12a: The growth rate curve of K562 cells Figure 12b: The dead cell % of K562 cells

(The red line in Figure 12b indicates the maximum acceptable level of dead K562 cells)

Figure 12: K562 cell growth at starting cell concentrations of 1.5x104, 1.5x105 and 1.0x106 cells per mL

Figure 12a shows that from Day 0 to 3, the K562 cells were in the log-growth phase

regardless of seeding concentration. The highest cell concentrations were obtained with a

seeding concentration of 1.5 x 105 cells per mL. Figure 12b illustrates that the lowest

percentage dead cells was obtained with a seeding concentration of 1.5 x 105 cells per mL.

Hence, it can be concluded that the cells should be passed every two to three days at

approximately 1.5 x 105 cells per ml of culture in TCM supplemented with 10% foetal calf

serum.

NKCA assay procedure:

Effector and target cells, i.e. fresh PBMCs and K562 cells, were added in duplicate in 12

x 75 mm round-bottom tubes [Beck Dickinson, Oxford, U.K.] to yield the Effector to Target

(E:T) ratio of 50:1, 25:1, 12.5:1 in 200 �l. Control tubes were set up with only target or effector

cells for determining spontaneous cell death rates. Tubes were mixed by gently tapping, and

K562 growth curve in culture

10000

100000

1000000

10000000

100000000

day0 day1 day2 day3

1.5x10̂ 4 cells/ml

1.5x10̂ 5 cells/ml

1.0x10̂ 6 cells/ml

Dead K562 % in culture condition

0

20

40

60

80

100

Day 1 Day 2 Day 3

1.5x10 4̂ cells/ml

1.5x10 5̂ cells/ml

1.0x10 6̂ cells/ml

Cel

l nu

mb

ers

per

mL

(in L

og-sca

le)

Dea

d c

ell p

erce

nta

ges



incubated at 37°C for three hours (in the university student study) or four hours. After

incubation, the tubes were placed on ice until analysed. Twenty microliters of propidium iodide

(PI), which stains the nucleus of dead cells, were added to each tube 10-15 minutes before

acquisition.

Flow cytometric acquisition:

Flow cytometry was performed with a FACS Calibur cytometer [Beck Dickinson]. The

instrument was set for two-colour analysis using FACScomp software in conjunction with

Calibrite beads [Beck Dickinson]. Data were collected in list mode and analysis was performed

using CellQuest software [Beck Dickinson]. A region was set on a dot plot of SSC vs.

fluorescence 1 (FL-1: CD45) around the cluster of target cells identified in the control sample

tubes and percentages of PI-stained cell number in the region were counted. NKCA was

calculated by subtraction of target total from individual totals [Figure 13].

Figure 13a: K562 cells only tube acquisition Figure 13b: PBMCs only tube acquisition

Figure 13d: K562 histogram by PI staining

(M1: PI staining positive cells) Figure 13c: testing tube (mixed with K562 and PBMCs) acquisition

Figure 13: Acquision settings of the flow cytometer for measuring the levels of NKCA

A region setting (R1) for K562 [Figure 13a,b] and a process of dead K562 detection [Figure 13c]

followed by histogram percentage analysis (counting PI stained cell numbers) [Figure 13d]

M1



Precision of levels in the NK cytotoxic activity measured by flow cytometry

Methodological variation in NK cytotoxic activity was assessed in preliminary blood

samples from three volunteers. Three sample tubes of blood were taken from them, and all nine

samples were duplicated to measure NK cytotoxic activity. Changes in the levels of NKCA

more than twice of standard deviations (1.44 % killing) were considered as out of the 95 %

confident interval. Changes in NKCA level more than 1.44 were considered as a difference

between samples, and results from the statistical analyses were examined with this definition.

2.4.3.3 NK-cell characteristics during NKCA assay measured by flow cytometry

Expression of Natural cytotoxic receptor (NCR) measured by flow cytometry

Cell surface staining was performed by incubating with 5 �l of particular monoclonal

antibodies for 15 min at room temperature in the dark. The analysis of natural cytotoxic receptor

(NCRs: Nkp30 or Nkp46) was performed using four-color flow cytometric acquision and

FlowJo® flow cytometry analyses [Figure 14].

Figure 14: Acquision settings of the flow cytometer in the NCR analyses

A region was set on a dot plot of FL-3 (CD56) vs. FL-4 (CD3) to target CD3-CD56+ NK-

cells [Figure 14a], and further regions for NK sub-populations were determined by a dot plot of

WWhhoollee llyymmpphhooccyytteess

GGaatteedd NNKKCC ssaammppllee

FL-4: CD3-APC staining

CD3-CD56+

(NK-cells)

FL-1: CD16-FITC staining

CD56brightCD16- Regulatory NK-cells

CD56dimCD16+

Cytotoxic NK-cells

FL

-3: CD

56-CyC

hrome staining

Figure 14b: NK-subsets of Cytotoxic and Regulatory NK-cells in dot plot

Figure 14a: CD3-CD56+NK-cells in dot plot

Figure 14c: Ppercentage of NCR expressions

NCRs(+) %

FL2: Nkp30 or Nkp46-PE staining

FL

-3: CD

56-CyC

hrome staining



FL-3 (CD56) vs. FL-1 (CD16) [Figure 14b: CD56dimCD16+ Cytotoxic and CD56brightCD16-

Regulatory NK-cell subsets]. The percentage expressions of NCRs were then measured as a

percentage of FL-2 (NCRs) positive cells within the population of a selected region (Cytotoxic

or Regulatory NK-cells) by histogram [Figure 14c: percentage of cells expressing NCRs].

2.4.3.4 Proliferative response measured by [3H]-thymidine incorporation

PBMC cultures with stimulus:

Peripheral blood mononuclear cells (PBMCs) were cultured with microbacterial protein

(purified protein derivative: PPD) and Herpes antigen (memory recall antigens) for 6 days in

tissue culture medium (TCM: containing 10% fetal calf serum) with/out cortisol [hydrocortisone,

Sigma®] to measure lymphocyte proliferative responses. In addition, Three day cultures with 1)

Staphylococcal enterotoxin B (SEB) used as a stimulant, a super antigen, which can stimulate

both naïve and memory cells; and 2) Phytohaemagglutinin A (PHA) chosen as a mitogen which

stimulates all T-cells and thereby acts as a positive control for proliferative responses.

Whole Blood Cell cultures with stimulus [Hutchinson et al., 1999] [See also Appendix 4]:

The whole blood assay for measuring proliferative responses was applied in order to

reduce cell handling and manipulation. In brief, whole blood (diluted 1/4) was incubated for 3

days with 12.5 �g/ml of SEB, super-antigen, or 12.5 �g/ml of PHA, mitogen, to measure

lymphocyte proliferative responses. PHA or SEB were incubated with 1:10 diluted blood with

or without 250 nM cortisol in 96 U-shaped well plates in total amount of 200 �L, and incubated

0, 24 and 48 hours followed by the [3H]-thymidine incorporation assay.

[3H]-thymidin e incorporation

The plates were incubated at 37°C in a 5% CO2 humidified atmosphere, and the cells were

pulsed with 1 �Ci tritium [mehyl-3H] Thymidine ([3H]-TdR) per well for the last four hours of

incubation. The supernatants were harvested using a Skatron AS Harvesting system [Shatron,

Suffolk] and the amount of [3H] incorporated with the cells determined on a Wallac 1205 Liquid

scintillation Counter [Pharmacia, Becks]. Results were presented as couts per minutes (cpm).



2.4.3.5 T-cell characteristics after in vitro incubation measured by flow cytometry

Cell preparation for proliferation analyses

Previously titrated concentration of PPD or Herpes antigen was incubated with 2.0 x 105

cells per mL PBMCs in total amount of 1.2 mL per well in 24 well culture plates with/out 250

nM cortisol. 12.5 �g/mL of PHA or SEB were incubated with 1:10 diluted blood with/out 250

nM cortisol in 24 U-shaped well plates in total amount 1.2 mL, and incubated for 0, 24 and 48

hours. The plates were incubated at 37°C in a 5% CO2 humidified atmosphere and, then cells

were allocated into FACS 12 x 75 round bottom tubes [Beck Dickinson, Oxford, U.K.] before

following procedures.

Staining cell surface markers upon T-lymphocyte sub-populations

Cell surface staining was performed by incubating with 5 �l of particular monoclonal

antibodies for 15 min at room temperature in the dark. In a whole blood assay, erythrocytes

were lysed for 20 min with 1 ml of 10 x diluted lysing solution [Becton Dickinson] in the dark.

In both methods, cells were washed three times with the TCM and fixed in 100 �l of 4% of

para-formaldehyde in PBS (fixation buffer) for 20 min at 4°C.

Expression of CD25 or CD95 upon T-lymphocytes measured by flow cytometry

Cell samples were run on a FACSCalibur flow cytometer (Becton Dickinson) and

analysed by CellQuest software. CD3-Cy-Chrome (FL-3) and CD8-APC (FL-4) fluorescent

conjugated antibodies were used to label lymphocyte sub-populations (CD3+CD8+ T-cells and

CD3+CD8- T-cells as CD4+ T-cells). At least 5000 events in the light-scatter (FSC/SSC)

lymphocyte region were acquired. Each lymphocyte sub-population was identified by a gate on

FL-3 versus FL-4 dot plots, i.e. CD3-CD8 scatter dot plots. The FITC-fluorescence intensities

(FL-1) of CD25 or CD95-labelled lymphocyte populations and isotype controls were displayed

and determined as mean channel values on a four-decade log scale in histogram plots.

The relative quantity of CD25 or CD95 expression was calculated by the percentage of

cell numbers in the positive intensity area, and mean fluorescence intensity (m.f.i.) was

calculated as the difference between mean values of CD25 or CD95 and isotype control labelled

samples. The instrument calibration was performed by CellQuest software using CaliBRITETM

beads.



Expression of Annexin V- PI on T-lymphocytes measured by flow cytometry

The Annexin V-FITC (FL-1) antibody & propidium iodine (PI: FL-3) staining method for

detection of apoptosis was used to determine the effect of cortisol upon apoptotic processes.

Four-color flow cytometric acquision and FlowJo® flow cytometry analyses were performed. A

region was set on a dot plot of SSC vs. FL-2 (CD3-PE) to target T-lymphocytes, and further

percentages of necrotic cells, apoptotic cells and live cells were determined by a dot plot of FL-

3 (PI) vs. FL-1 (Annexin V) [Figure 15].

Figure 15: Acquision settings of the flow cytometer in the Annexin V- PI analysis

A region was set on a dot plot of FL-2 (CD3) vs. SSC to target T-cells (Figure 15a) from

whole lymphocytes gated by the FSC-SCC plot previously, and further regions for apoptotic

cell subsets were determined by a dot plot of FL-3 (PI) vs. FL-1 (Annexin V) (Figure 15c:

apoptotic (Annexin V+ & PI-) and necrotic cell (PI+) subsets in the T-lymphocytes). Figure 15b

shows the method setting-up for the region of apoptotic cells by using negative isotype controls.

Side S

catter (SS

C)

FL -2: CD3 staining

FL-3: PI staining

FL

-1: Annexin V

staining F

L-1: A

nnexin V staining

Necrotic cells

Apoptotic cells

Live cells

Live cells

Apoptotic cells

Necrotic cells

T-lymphocytes

Whole lymphocytes (gated by the FSC-SSC plot)

Experiment samples

Negative control (for gating purpose)

FL-3: PI staining

Figure 15a: a region for T-cells in a dot plot

Figure 15c: a region for apoptotic cells in a dot plot

Figure 15b: setting-up a region for apoptotic cells using negative isotype control in a dot plot



2.5 Statistical analyses

All psychological and physiological laboratory samples were anonymised and processed

using an assigned study number to ensure that the analyses were performed blindly in terms of

the groups and subgroups to which the samples belong to.

To examine the a priori hypothesis that psychological intervention may counteract the

detrimental effect of stress on well-being, on-treatment analysis (analysis of results from only

those who completed the trial) was performed. When statistical differences were found in the

primary outcome measure in univariate analyses, Intention-to-treat analysis was performed in

order to confirm the results. The intention-to-treat is the analysis of results from every subject

enrolled in the trial regardless of whether they completed the trial, and all individuals who

withdrew were counted in the number of subjects who failed the hypothesis.

Univariate statistical analyses were performed to test specific hypotheses stated at each

point in the results section [3.1 and 3.2 in vivo studies; and 3.3 and 3.4 in virto experiments].

Sample sizes of each group were relatively small in the in vivo analyses [3.1 and 3.2], and

therefore essentially multivariate analyses are unlikely to achieve meaningful results. If

multivariate analyses were performed, standard errors would be relatively high giving very wide

95% confidential intervals (C.I.) indicating a lot of uncertainty in findings. For this reason, it

was felt inappropriate to perform multivariate analyses.

The Statistical Package of Social Science version 11.0 (SPSS®) [Field, 2003] was used

with a p value of less than 0.05 considered as a statistically significant value, and a p value of

less than 0.10 as a statistical trend. The Study Size Determination (SSD) programme [Lehmann,

2001] was used for sample size calculation at the 5% significance level and with the 90% power.

For independent normally distributed data, analyses of variance (ANOVA) were performed

followed by post-hoc Student t-tests. Repeated-measures ANOVA was used for longitudinal

data normally distributed [Tabachnick & Fidell, 1996]. For non-normally distributed data,

repeated-measure ANOVA followed by the 10% trimming method [Wilcox, 1997] was

performed. The 10% trimming method was applied in order to remove outliers so that the

ANOVA method can be applied. To confirm the finding from the ANOVA following the 10%

trimming method, the Non-parametric ANOVA (the Kruskal-Wallis rank tests) was used

[Tabachnick & Fidell, 1996]. The Wilcoxon rank tests were used for paired and non-normally

distributed data [Ajetunmobi, 2002].

- 78 -

Chapter III

Results




Results

3.1 The influence of psychological intervention upon stress-related changes in

university students facing academic examinations.

3.1.1 Validation of academic examination as a stress inducer for university students 83

3.1.1.1 Impact of academic examination upon psychological measures of

stress and anxiety 83

3.1.1.2 Impact of academic examination upon immune parameters 84

3.1.2 Differences in the levels of lymphocyte subsets and NK cytotoxic activity

(NKCA) between university students with high and low perceived stress levels 85

3.1.2.1 Difference in the percentage of NK-cells and the levels of NK

cytotoxic activity (NKCA) between university students with high

and low perceived stress levels 86

3.1.2.2 Difference in the percentage of T-cells between university students

with high and low perceived stress levels 91

3.1.3 The influence of psychological intervention upon stress-related changes in

university students facing academic examinations 93

3.1.3.1 Effect of psychological intervention upon stress perception in

university students anticipating academic examinations 93

3.1.3.2 Effect of psychological intervention upon stress-related

lymphocyte sub-populations in university students anticipating

academic examinations 95

3.2 The influence of psychological intervention upon perceived stress and quality-of-

life and various immunological disease-associated parameters in HIV-infected

individuals

3.2.1 Disease-associated and stress-related changes in HIV-infected individuals in

psychology immunological parameters 103

3.2.1.1 Psychological profiles of the HIV-infected individuals recruited

into the study 103

3.2.1.2 Stress-related perception and disease progression markers of HIV-

infection 110



3.2.2 The influence of psychological intervention upon disease progression

parameters in HIV-infected individuals (randomised controlled trial for four

months period) 117

3.2.2.1 Effect of psychological intervention upon perceived stress and

anxiety in HIV-infected individuals 117

3.2.2.2 Effect of psychological intervention upon CD4 T-cell counts in

HIV-infected individuals 119

3.2.2.3 Effect of psychological intervention upon other immunological

markers (log-transformed viral load levels and NK-cell counts) in

HIV-infected individuals 121

3.2.3 The influence of psychological intervention upon disease progression marker,

CD4 T-cells, in HIV-infected individuals (case controlled study over 24

months period) 122

3.2.3.1 Analysis of baseline differences between the three groups in the CD4 T-cell

count 122

3.2.3.2 Analysis of the rate of change in CD4 T-cell count (CD4 gradient) 123

3.3 In vitro investigation into the effect of exposure to stress hormones upon

Natural Killer cells

3.3.1 Development and optimisation of a flow cytometric method for measuring

NKCA 128

3.3.1.1 NKCA after incubation of PBMCs for 24 hours 128

3.3.1.2 NK-cell percentage in PBMCs after 24 hours incubation 129

3.3.1.3 NKCA after 24hrs incubation of PBMCs with cortisol 131

3.3.1.4 NK-cell percentage in PBMCs after 24 hours incubation with

cortisol 132

3.3.2 Comparison of two methods for measuring NK cytotoxic activity (NKCA): -

the flow cytometric method and the colorimetric method (CytoTox96®) 133

3.3.3 Investigation of NK-cell profiles and NKCA (colorimetric method) 134

3.3.3.1 NKCA, assessed by colorimetric method, after incubation of

PBMCs for 24 hours 134



3.3.3.2 Repeat assessment of NK-cell percentage and examination of NK

subpopulations in PBMCs after 24 hours incubation 135

3.3.3.3 Expression of Natural Cytotoxic Receptors (Nkp46 and Nkp30) by

cytotoxic NK-cells (CD3-CD56dimCD16+) pre and post 24hours

incubation 136

3.3.3.4 NKCA, assessed by colorimetric method, after 24 hours incubation

of PBMCs with 250nM cortisol 138

3.3.3.5 NKCA levels between pre and post 24 hours incubation with or

without 250nM cortisol 139 3.3.3.6 CD56 NK-cell subset profiles in PBMCs after 24 hours incubation

with 250nM cortisol 141

3.3.3.7 Expression of Natural Cytotoxic Receptors (Nkp46 and Nkp30) by

cytotoxic NK-cells (CD3-CD56dimCD16+) after 24hours

incubation with or without 250nM cortisol 142

3.3.3.8 Nkp46 expression on cytotoxic NK-cells pre and post 24 hours

incubation with or without 250nM cortisol 143

3.3.3.9 NKCA and Nkp46 expression on cytotoxic NK-cells pre and post

24 hours incubation with or without 250nM cortisol 144

3.3.4 Endogenous stress hormone levels and NKCA (colorimetric method) 145

3.3.4.1 Endogenous hormone levels and NKCA at Time 0 point 146

3.3.4.2 Endogenous hormones levels and the increased levels of NKCA

after 24 hours in vitro incubation of PBMCs without exogenous

cortisol 146


T-lymphocytes

3.4.1 T-lymphocyte proliferative responses against common antigens 151

3.4.1.1 T-lymphocyte proliferation after incubation of PBMCs for six days

with and without exogenous cortisol 152

3.4.1.2 T-lymphocyte proliferative response against purified protein

derivative (PPD) after incubation of PBMCs for six days with or

without exogenous cortisol 153



3.4.1.3 T-lymphocyte proliferative response against Herpes antigen after

incubation of PBMCs for six days with and without exogenous

cortisol 154

3.4.2 T-lymphocyte proliferative responses against super-antigen and mitogen 155

3.4.2.1 T-lymphocyte proliferative responses against staphylococcal

enterotoxin B (SEB) after incubation of diluted whole blood for

three days with or without exogenous cortisol 156

3.4.2.2 T-lymphocyte proliferative responses against phytohaemagglutinin

A (PHA) after incubation of diluted whole blood for three days

with or without exogenous cortisol 157

3.4.3 Cell surface markers on proliferating T-lymphocytes following stimulation

with PHA 158

3.4.3.1 Expression of an apoptosis (CD95: Fas) cell surface marker by T-

lymphocytes in vitro during PHA-induced proliferation with and

without exogenous cortisol 158

3.4.3.2 Expression of cell-surface Annexin-V and cytoplasmic Propidium

iodine (PI) in T-lymphocytes after incubation with PHA for three

days with or without cortisol 163

3.4.3.3 Expression of an activation (CD25: IL-2 receptor) cell surface marker

byT-lymphocytes during PHA-induced proliferation with and without

exogenous cortisol 164



3.1 The influence of psychological intervention upon stress-related changes in

university students facing academic-exams.

3.1.1 Validation of academic examination as a stress inducer for university students

This study was designed to examine the hypothesis that anticipating an academic

examination induces stress and stress-related changes in university students. The levels of stress

perception (Perceived Stress Score and State anxiety score) and NK-cell percentages and NK

cytotoxic activity were examined in university students facing academic examination (Exams)

and compared with results obtained in the non-exam periods of university life (Non-exam) in

order to detect exam-stress associated changes. In addition, CD4 and CD8 T-cell percentages

were examined.

3.1.1.1 Impact of academic examination upon psychological measures of stress and anxiety

Perceived stress levels (PSS)

There was a significant increase (t = 2.1, df = 21, p = 0.045) in the levels of the PSS at the

Exams compared to the Non-exam time point [Table 7 and Figure 16].

Table 7: Mean (95% C.I.) PSS scores at the Non-exam and Exam time points PSS

Non-exam Exams Mean score (95% C.I.)

21.5 (18.6 - 24.5)

26.2 (22.8 – 29.6)

n 22 22

2222N =

ExamsNon-exams

Mean (95%

C.I.) of P

SS sco

re

40

30

20

10

0

Figure 16: Mean (95% C.I.) PSS scores at the Non-exam and Exam time points

p = 0.045

Mea

n (

95

% C

.I.)

Pe

rcei

ved

Str

ess

Sco

res



Conclusion:

Perceived stress levels were increased in university students when faced with academic

examinations.

State anxiety levels

The students were shown to be more anxious (t = 2.1, df = 24, p = 0.048) at the Exam

time point than at the Non-exam time point [Table 8 and Figure 17].

Table 8: Mean (95% C.I.) State anxiety scores in the STAI at the Non-exam and Exam time points

State anxiety in the STAI Non-exam Exams

Mean score (95% C.I.)

36.6 (32.7 - 40.5)

41.8 (38.5 – 45.1)

n 25 25

2525N =

ExamsNon-exams

Mean (95%

C.I.

) of S

tate

sco

re in

STAI

50

40

30

20

10

0

Figure 17: Mean (95% C.I.) State anxiety scores in the STAI at the Non-exam and Exam time points

Conclusion:

Academic examinations increased anxiety levels in university students.

3.1.1.2 Impact of academic examinations upon immune parameters

Previous research suggested that the levels of NK cytotoxic activity (NKCA) and NK-cells

may be associated with psychological stress, i.e. the hypotheses are that exam-induced stress

decreases the NK cytotoxic activity and the levels of NK-cells in the university students. Hence

this study was designed to examine these hypotheses with an additional exploratory

investigation of the effects upon the levels of CD4 and CD8 T-cells.

Mea

n (

95

% C

.I.)

Sta

te S

core

s in

the S

TA

I

p = 0.048



NKCA levels

The NK cytotoxic activity levels were not statistically significantly different (t = 0.2, df =

20, ns) between the Non-exam and Exam time points [Appendix 6: Table A-7].

Conclusion:

Anticipation of academic examinations did not affect the levels of NKCA.

NK-cell and T-cell levels

The results from 26 students show that none of the NK-cell (t = 0.3, df = 25, ns), CD4 T-

cell (t =0.6, df = 25, ns) or CD8 T-cell (t =0.2, df = 25, ns) percentages were significantly

different between the Non-exam and Exam time points [Appendix 6: Table A-8].

Conclusion:

Anticipation of academic examinations did not affect NK-cell and CD4 and CD8 T-cell

percentage.

Summary:

The data indicated that an anticipation of academic examinations induces stress and

provokes anxiety in university students. However, the academic examinations did not appear to

affect the levels of NK-cells, CD4 and CD8 T-cells or NK cytotoxic activity in the university

students, in this study.

It is concluded that academic exams are a valid stressful life event (stressor) to increase

stress and anxiety levels for university students; but that academic exams did not appear to

provide concurrent changes in immunological parameters, i.e. levels of NK-cells, T-cells and

NK cytotoxic activity.

3.1.2 Differences in the levels of lymphocyte subsets and NK cytotoxic activity (NKCA)

between university students with high and low perceived stress levels

The previous section suggested that an anticipation of academic examinations did not

affect the levels of the immune parameters. However, as described in the introduction [1.2.3.2



and 1.2.4.3], individual’s perception of stress has been shown to be more associated with

immune parameters, particularly NK-cell profiles, than a stressful life event itself. Hence, in this

section, immune parameters (NK-cells [3.1.2.1], T-lymphocytes [3.1.2.2]) were compared in

two subgroups of students assessed to be stressed and not-stressed individuals according to their

PSS scores. The university students, who filled the PSS questionnaires and had blood collection

four weeks after recruitment, were divided into two subgroups on the basis of the PSS (Median

= 22.5, Mean = 23.1, Standard deviation = 7.7) and labelled as Not-stressed and Stressed

individuals in this study:

� Stressed individuals: PSS score was more than or equal to 22

� Not-stressed individuals: PSS score was less than 22

There was no statistically significant difference in the numbers of Subjects between the

Not-stressed and Stressed subgroups with regard to gender distribution [Appendix 6: Table A-9].

3.1.2.1 Differences in the percentage of NK-cells and the level of NK cytotoxic activity

(NKCA) between university students with high and low perceived stress levels

Research has suggested that NK-cells are affected by stress perception [1.2.3.2 and

1.2.4.3]. Accordingly, this study was performed to determine if, in university students,

perceived stress level is associated with

1. Low NK-cell percentage

2. Low NK cytotoxic activity level, and

3. Low per-NK-cell cytotoxic activity.

In addition, the influence of gender upon these parameters was investigated.

NK-cell levels

There was no significant difference between the Stressed and Non-stressed subgroups in

the percentages of NK-cells (t = 0.7, df = 39, ns) [Appendix 6: Table A-10].

Gender did not appear to affect the results. There was no significant gender vs. stress-

perception interaction (F = 1.7, df = 39, ns; male: t = 1.1, df = 18, ns; and female: t = 1.5, df =

18, ns) [Appendix 6: Tables A-11 and 12]. Hence, it was concluded that there was no gender

bias with regard to the result from comparison analysis between the Stressed and Not-stressed

subgroups.



With regard to gender difference, however, male students had a trend towards higher NK-

cell percentages than female students (t = 1.9, df = 38, p = 0.066) [Table 9 and Figure 18].

Table 9: Mean (95% C.I.) NK-cell percentages in male and female students

NK-cell (%) Male Female

Mean level (95% C.I.)

11.0 (8.5 – 13.5)

8.0 (6.1 – 10.0)

n 20 20

male female

0

5

10

15

Mean

(95%

C.I.)

NK-

cell (

%)

Figure 18: Mean (95% C.I.) NK-cell percentages in male and female students

Conclusion:

There was no difference in NK-cell levels between stressed and not-stressed students.

Male students appeared to have higher NK-cell percentages than females, but this difference

was not statistically significant.

Natural Killer cytotoxic activity (NKCA) levels

The Stressed students had significantly lower NKCA levels compared to the Non-stressed

students (t = 2.4, df = 39, p = 0.023) [Table 10 and Figure 19].

Table 10: Mean (95% C.I.) levels of NKCA (% killing) in the Not-stressed and Stressed subgroups

NKCA (% killi ng)

Not-stressed Stressed Mean level (95% C.I.)

12.0 (7.7 – 16.3)

5.8 (2.8 – 8.7)

n 20 21

p = 0.066



2120N =

StressedNon-stressed

NKCA le

vels (95%

C.I.) at Tim

e p

oint 1

20

15

10

5

0

Figure 19: Mean (95% C.I.) NKCA (% killing) in the Not-stressed and Stressed subgroups

Gender did not appear to affect the results. There was no significant gender vs. stress-

perception interaction (F = 0.6, df = 39, ns). This was confirmed when the Stressed and Not-

stressed subgroups were compared in each gender separately. The Stressed male students had

significantly lower NKCA levels compared to the Non-stressed male students (t = 2.2, df = 19, p

= 0.038) [Table 11 and Figure 20]. The same trend was shown in female students, but it did not

achieve statistical significance (t = 1.1, df = 18, ns) [Appendix 6: Table A-13]. With regard to

difference between male and female students, there was no significant difference in the levels of

the NKCA (t = 0.1, df = 39, ns) between male and female students [Appendix 6: Table A-14].

Table 11: Mean (95% C.I.) levels of NKCA (% killing) in the Not-stressed and Stressed male students

Not-stressed Stressed

0

5

10

15

20

Mean

(95%

C.I.)

NKC

A in

male

(%kil

ling)

Figure 20: Mean (95% C.I.) NKCA levels (% killing) in the Not-stressed and Stressed male students

Hence, it was concluded that there was no gender bias with regard to the result from

comparison analysis between the Stressed and Not-stressed subgroups.

NKCA (% killing)


12.9 (6.6 – 19.2)

4.7 (1.2 – 8.2)

n 11 10

NK

cyt

otox

ic a

ctiv

ity (

%ki

lling

)

p = 0.023

p = 0.038

NK

cyt

otox

ic a

ctiv

ity (

%ki

lling

)



Conclusion:

Stressed students had lower levels of NKCA compared to the not-stressed students.

NKCA levels were not significantly different between male and female students.

Per-NK-cell cytotoxic activity levels

It is known that NK cytotoxic activity (NKCA) is related to the number of NK-cells and

the promiscuity of the NK-cells. This promiscuity is dependent upon factors like:-

1. Relative concentrations of NK-cells, target cells and other isolated peripheral mono-

nuclear cells; and/or

2. Per-cell cytotoxic activity of individual NK-cells.

The first hypothesis was examined using a correlation analysis between NK-cell

percentage and NKCA level, and showed that there was a strong and statistically significant

positive association (r = 0.52, p = 0.001, n = 44). Hence, it was concluded that the number and

concentration of NK-cells were one of the most important factors for the NKCA levels.

Having demonstrated this positive correlation, the second hypothesis that low levels of

per-NK-cell cytotoxic activity associate with high stress perception was examined. This per-

NK-cell cytotoxic activity, which was calculated as a figure of a ratio of the NKCA to NK-cell

percentage as was suggested in the meta-analysis of Segerstrom and Miller [2004], were

compared between the Stressed and Not-stressed students. The results show that the Stressed

students had a trend towards lower levels of per-NK-cell cytotoxic activity (calculated as a ratio

of NKCA to NK-cell percentage) compared to the Non-stressed students (t = 2.0, df = 39, p =

0.056) [Table 12 and Figure 21].

Table 12: Mean (95% C.I.) ratios of NKCA to NK-cell in the Not-stressed and Stressed students

NKCA to NK-cell ratio

Not-stressed Stressed Mean ratio (95% C.I.)

1.29 (0.74 – 1.84)

0.64 (0.25 – 1.02)

n 20 21




0.0

0.5

1.0

1.5

2.0

2.5

Mean

(95%

C.I.)

ratio

s of N

KCA

to NK

C %

Figure 21: Mean (95% C.I.) per-NK-cell cytotoxic activity (calculated as a ratio: NK cytotoxic activity

(NKCA) / NK-cell percentage (NKC%)) in the Not-stressed and Stressed subgroups

Gender appeared not to influence the results significantly. There was no significant

gender vs. stress-perception interaction (F = 1.4, df = 39, ns). This was confirmed when the

Stressed and Not-stressed subgroups were compared in each gender separately. The Stressed

male students had lower per-NK-cell cytotoxic activity levels compared to the Non-stressed

male students (t = 2.3, df = 19, p = 0.035) [Table 13 and Figure 22]. There was, however, no

statistically significant difference between the Not-stressed and Stressed female students (t = 0.5,

df = 18, ns) [Appendix 6: Table A-15]. With regard to difference between male and female

students, there were no significant differences between male and female students in the ratios of

the NKCA to NK-cell percentage (t = 0.1, df = 40, ns) [Appendix 6: Table A-16].

Table 13: Mean (95% C.I.) ratios of NKCA to NK-cell in the Not-stressed and Stressed male students

NKCA to NK-cell ratio

Not-stressed Stressed Mean ratio (95% C.I.)

1.38 (0.53 – 2.24)

0.33 (0.14 – 0.52)

n 11 10


0.0

0.5

1.0

1.5

2.0

2.5

Mean

(95%

C.I.)

ratio

s of N

KCA

to NK

C %

in ma

le stu

dents

Figure 22: Mean (95% C.I.) per-NK-cell cytotoxic activity (calculated as a ratio: NKCA / NK-cell

percentage) in the Not-stressed and Stressed male students

p = 0.056

p = 0.035

Pe

r-NK

-cel

l cyt

otox

ic a

ctiv

ity

Pe

r-NK

-cel

l cyt

otox

ic a

ctiv

ity



Hence, it was concluded that there was no gender bias with regard to the result from


Conclusion:

It appears that stressed students may have lower levels of per-NK-cell cytotoxic activity

compared to the not-stressed students, and possibly, because of the small sample size, this

achieved statistical significance only for male students.

3.1.2.2 Differences in the percentages of T-cells between university students with high and low

perceived stress levels

Associations between stress perception and T-cells have been inconsistently reported

[1.2.3.2 and 1.2.4.3]. Hence, this study was performed to determine if there are any associations

between perceived stress level and CD4 T-cell and/or CD8 T-cell percentages in university

students. In addition, the influence of gender upon these parameters was investigated.

There was no significant difference between the Stressed and Non-stressed individuals in

the CD4 or CD8 T-cell levels (CD4 T-cells: t = 1.4, df = 39, ns; CD8 T-cells: t = 0.8, df = 39,

ns) [Appendix 6: Table A-17]. There was no significant gender vs. stress-perception interaction

(CD4 T-cells: F = 0.8, df = 39, ns; and CD8 T-cells: F = 0.5, df = 39, ns). This was confirmed

when the Stressed and Not-stressed subgroups were compared in each gender separately. There

was no significant difference between the Not-stressed and Stressed students (male: CD4 T-

cells: t = 1.1, df = 18, ns; CD8 T-cells: t = 1.1, df = 18, ns [Appendix 6: Table A-18]; and

female: CD4 T-cell: t = 1.7, df = 18, ns; CD8 T-cell: t = 1.1, df = 18, ns [Appendix 6: Table A-

19]). Hence, it was concluded that there was no gender bias with regard to the result from


Gender appeared to influence the results of CD4 T-cells (F = 6.0, df = 1, p = 0.019), but

not CD8 T-cells (F = 0.03, df = 1, ns). Female students have higher CD4 T-cell percentages than

male students (t = 2.4, df = 38, p = 0.020) [Table 14 and Figure 23]. There was no significant

difference between male and female students in the CD8 T-cell percentages (t = 0.4, df = 38, ns)

[Appendix 6: Table A-20].



Table 14: Mean (95% C.I.) CD4 T-cell levels (%) of male and female CD4 T-cell (%)

Male Female Mean level (95% C.I.)

43.2 (39.9 – 46.4)

48.7 (45.5 – 52.0)

n 20 20

male female

0

10

20

30

40

50M

ean

(95%

C.I.

) CD4

T-c

ell (

%)

Figure 23: Mean (95% C.I.) CD4 T-cell levels (%) of male and female students

Conclusion:

There was no significant difference in CD4 or CD8 T-cell levels between stressed and

not-stressed students. Female students showed higher CD4 T-cell percentages than male

students in this study.

Summary:

The analyses of NKCA and per-NK-cell cytotoxic activity levels suggested that the

students with high stress perception (the stressed individuals) may have lower levels of NKCA

and per-NK-cell cytotoxic activity compared to the students who expressed a low level of stress

(the not-stressed individuals). There were no significant differences between the stressed and

not-stressed students in NK-cell or CD4 and CD8 T-cell percentages, and these results had no

gender bias; although male students had higher NK-cell and lower CD4 T-cell percentages than

females. Hence, it is suggested that gender may not need to be separately analysed when the

levels of the NKCA or percentages of NK-cells and CD4 and CD8 T-cells are compared in

relationship with the levels of stress perception.

This study has shown that there are associations between one’s perceived stress level and

one’s levels of NKCA; and these findings support previous reports [Introduction: 1.2.4.3] that

p = 0.020

CD

4 T-

cell

perc

enta

ges



there are interactions among the proposed integrated psycho-neuro-endocrino-immune network,

and that it is warranted to investigate this network further [3.3 and 3.4].

3.1.3 The influence of psychological intervention upon stress-related changes in

university students facing academic examinations

The objective of this series of investigations was to determine if the practice of

psychological coping skills would reduce:

1. Increased levels of perceived stress (PSS) and anxiety (State score of the STAI),

2. Stress-related low NKCA levels, and

3. Stress-related decrease in NK-cell percentages

in university students facing academic examinations. The levels were compared between the

recruitment baseline time point and the Exam time point. Psychological intervention was given

prior to the examinations. In addition, the effects of psychological intervention upon CD4, CD8

T-cell percentages were explored by using the same comparison method.

3.1.3.1 Effect of psychological intervention upon stress perception in university students

anticipating academic examinations

Perceived Stress levels (PSS)

The PSS questionnaire was not ready for use when the students were recruited for the

baseline assessments. However, 32 participants completed the questionnaire at the Exam time

point. ANOVA showed that there was no statistical difference between the three groups (F =0.5,

df = 29, ns), and exploratory post-hoc t-tests showed no significant differences (Relaxation

control vs. Self-hypnosis: t = 0.6, df = 19, ns; Relaxation control vs. Johrei: t = 0.3, df = 18, ns)

[Appendix 6: Table A-21]. Further, there was no significant differences in the PSS levels

between the three groups with regard to;-

� Distribution of numbers of the participants in the Not-stressed and Stressed

subgroups (No differences: Pearson's Chi square: Relaxation cntrols vs. Self-

hypnosis = 0.2; Relaxation controls vs. Johrei = 2.6) [Table 15]; and

� Gender bias [Appendix 6: Tables A-22 and A-23].



Table 15: The numbers of participant in the three groups (Self-hypnosis, Johrei and Relaxation control) in the Not-stressed and Stressed subgroups based on the PSS scores at the Exam time point

Not-stressed Stressed Total

Self-hypnosis 5 7 12

Johrei 7 4 11 Group Controls 3 6 9

Total 15 17 32

Conclusion:

Students practising psychological interventions prior to academic exams did not show any

significant differences in perceived stress levels at the Exam time point when compared with

students in the Relaxation control group.


Thirty five participants completed the State score of the STAI questionnaires at baseline

and the Exam time point, allowing for an analysis of anxiety levels in the three groups before

the psychological intervention period and later at the exam stress period.

Anxiety levels increased significantly at the Exams stress time point compared to baseline

in all three groups (F = 11.0, df = 32, p = 0.002). Although repeated measure ANOVA showed

that there was no significant difference in the State anxiety scores in the STAI between the three

groups at baseline and Exam time point, i.e. there was no time x group interaction (F = 0.02, df

= 32, ns), post hoc t-tests showed that the increases were statistically significant for the

Relaxation control (mean change = 6.8, t = 3.3, df = 9, p = 0.027) and Self-hypnosis (mean

change = 4.9, t = 3.3, df = 12, p = 0.006) groups but not for the Johrei groups (mean change =

4.2, t = 1.1, df =11, ns) [Table 16 and Figure 24]. Analyses of the data by gender showed the

same trends [Appendix 6: Tables A-24 and 25].

Table 16: Mean (95% C.I.) State anxiety scores in the Self-hypnosis, Johrei and Relaxation control

groups at baseline and the Exam time point State score in the STAI

Baseline Exams Self-hypnosis Johrei Controls Self-hypnosis Johrei Controls


37.3 (34.0 - 40.6)

34.8 (29.7 – 40.0)

31.5 (28.5 - 34.5)

42.2 (39.1 - 45.4)

39.0 (33.9 – 44.1)

38.3 (31.9 - 44.7)

N 13 12 10 13 12 10



Self-hypnosis Johrei Controls

0

10

20

30

40Me

an (9

5% C

.I.) St

ate sc

ores i

n the

STAI

BaselineExams

Figure 24: Mean (95% C.I.) State anxiety scores in the STAI of the three groups at baseline and the Exam

time point

Conclusion:

Anxiety levels increased in university students facing academic examination, and the

training and practice of Johrei appeared to help students to control these provoked levels of

anxiety although this anti-anxiety effect did not achieve a statistical significance.

3.1.3.2 Effects of psychological intervention upon stress-related lymphocyte sub-populations in

university students anticipating academic examinations

NK cytotoxic activity (NKCA) levels

NKCA levels were determined in peripheral blood from 31 participants at the Exam time

points. Due to technical difficulties, the NKCA levels could not be collected at the baseline. The

mean level of the NKCA in the Relaxation control group were not significantly different from

those levels in the Self-hypnosis and the Johrei groups (Relaxation control vs. Self-hypnosis: t =

1.3, df = 18, ns; Relaxation control vs. Johrei: t = 0.2, df = 18, ns) [Appendix 6: Table A-26].

Gender did not appear to influence [Appendix 6: Tables A-27 and A-28]. It was confirmed that

there was no gender bias.

Conclusion:

Psychological intervention did not appear to influence NKCA levels of university students

facing academic examinations.

p = 0.006

p = 0.027 Not significant

Not significant



Peripheral NK-cell and CD4 and CD8 T-cell percentages

Peripheral NK-cell and CD4 and CD8 T-cell percentages were determined for 34

participants (19 male and 15 female) [Table 17] at baseline and the Exam time points allowing

analysis of the influence of psychological intervention upon exam-stress associated changes.

Table 17: Numbers of participants in the three groups at the Exam time point

Group

Self-hypnosis Johrei Relaxation

controls

Total

male 7 7 5 19

female 5 4 6 15

Total 12 11 11 34

NK-cell percentages

There was no difference between the three groups in the levels of NK-cell percentages at

baseline (Self-hypnosis and Relaxation control: t = 0.5, df = 21, ns; Johrei and Relaxation

control: t = 0.7, df = 20, ns).

Repeated measures ANOVA showed that there is a significant difference in the changes

from baseline to the Exams assessment point among the three groups (F = 5.8, df = 31, p =

0.007). At the Exams period, there was a decrease in NK-cell percentage in the Relaxation

control group (mean change = 2.1, SD = 4.7, t = 1.5, df = 10, ns), but this did not achieve

statistical significance. However, the change in the NK-cell percentages in the psychological

intervention groups were significantly different, i.e. there was a significant time x group

interaction (F = 5.8, df = 31, p = 0.007). This was confirmed by following post-hoc t-tests.

There was no significant change in the mean NK-cell percentage in the Self-hypnosis group

(mean change = 1.0, t = 0.7, SD = 4.5, df =11, ns), but there was a significant increase in the

Johrei group (mean change = 3.2, t = 6.9, SD = 1.7, df =10, p < 0.001) at the Exam time point

[Table 18 and Figure 25]. Analyses of the data by gender showed the same trends [Appendix 6:

Tables A-29 and 30].

Table 18: Mean (95% C.I.) levels of NK-cell (%) in the Self-hypnosis, Johrei and Relaxation control

(Controls) groups at baseline and the Exam time point NK-cells (%)



9.6 (7.7 - 11.5)

7.6 (4.9 – 10.3)

8.8 (6.3 - 11.3)

8.6 (5.7 - 11.5)

10.8 (8.1 – 13.6)

6.7 (4.7 - 8.7)

n 12 11 11 12 11 11



111112 111112N =

Control (relaxation)JohreiHypnosis

NK

cel

l per

cent

ages

(95

% C

.I.)

20

15

10

5

0

Baseline

Exams

Figure 25: Mean (95% C.I.) levels of NK-cells of the three groups at baseline and the Exam time point

Figure 26 shows the changes from baseline NK-cell percentages to that at the Exam time

point for individual students in each group. In the Johrei group, there was a clear increasing

trend with eight individuals increased while three stayed the same (less than 2.6% changes: 99%

Confidence Interval of the measure in NK-cell %). There was no clear trend in the Relaxation

control group with two individuals increased, four stayed the same and five decreased. In the

Self-hypnosis, three increased, five stayed the same and three decreased.

0

5

10

15

20

Baseline Exam

0

5

10

15

20

Baseline Exam

0

5

10

15

20

Baseline Exam

Self-hypnosis Johrei Relaxation control Figure 26: The individual levels of NK-cell percentages in the three groups at baseline and the Exam

time point

p < 0.001

Not significant Not significant N

K-c

ell p

erce

nta

ge




This finding was investigated by the Intention-to-treat analysis comparing percentages of

individuals between the two groups (Maintaind (increase or stay the same) NK-cell levels and

Decreased NK-cell levels). All the data from the subjects who withdrew were added into the

number in the group in which the subjects decreased their NK-cells [Table 19].

Table 19: Percentages (numbers) of subjects whose NK-cell counts maintained or increased (Maintained)

and decreased (Decreased) in the Self-hypnosis and Johrei and Relaxation control groups for the Intention-to-treat analysis (missing data were added into the number in the Decreased group)

Group Maintained NK-cells Decreased NK-cells Total Self-hypnosis 44% ( 7/16) 56% ( 9/16) 16 Johrei 75% (12 /16) 25% ( 4 /16) 16 Controls 38% (6 /16) 62% (10/16) 16

Total 25 23 48

The percentage of the students who maintained the NK-cell counts at the Exam time point

in the Johrei group (75%) was higher than that of Relaxation control group (38%) (Pearson’s

chi-square = 4.6, p = 0.033).

Conclusion:

As has been shown in the literature [see also Introduction: 1.2.4.3] but not in this study

[3.1.1.4], exam stress appeared to result in a decrease in peripheral blood NK-cell percentage in

university students in the Relaxation control group although this decrease did not achieve

statistical significance. However, training in and practise of Johrei reversed this effect and led to

an overall increase in NK-cell percentages. In contrast, training and practice of Self-hypnosis

did not significantly change the levels of NK-cells.

CD4 T-cell percentages

The results show that there was no difference between the three groups in the levels of

CD4 T-cell percentages at baseline (Self-hypnosis and Relaxation control: t = 0.2, df = 21, ns;

Johrei and Relaxation control: t = 0.5, df = 20, ns).

Repeated measures ANOVA showed that there is a trend toward difference in the changes

from baseline to the Exams assessment point between the three groups (F = 3.2, df = 31, p =

0.054). At the Exams period, there was an increase in CD4 T-cell percentage in the Relaxation

control group (mean change = 1.6, t = 1.2, SD = 4.5, df = 10, ns), but this did not achieve

statistical significance. The change in the CD4 T-cell percentages in the psychological

intervention groups had trends towards different changes from that of the Relaxation control

group (F = 3.2, df = 31, p = 0.054). There was no change in the mean CD4 T-cell percentage in

the Self-hypnosis group (mean change = 0.1, t = 0.1, SD = 3.5, df =11, ns), and there was a



trend toward decrease in the Johrei group (mean change = 3.4, t = 1.8, SD = 6.2, df =10, p =

0.094) [Table 20 and Figure 27]. Analyses of the data by gender showed the same trends

[Appendix 6: Tables A-31 and A-32].


(Controls) groups at baseline and the Exam time point CD4 T-cells (%)



45.6 (42.4 - 48.9)

46.5 (42.8 – 50.3)

45.3 (41.8 - 48.7)

45.8 (41.1 - 50.4)

43.1 (37.7 – 48.6)

46.9 (38.5 - 51.1)

n 12 11 11 12 11 11


0

10

20

30

40

50

Mean

(95%

C.I.)

levels

of CD

4 T-ce

lls (%

)

BaselineExams

Figure 27: Mean (95% C.I.) levels of CD4 T-cells of the three groups at baseline and the Exam time point

Figure 28 shows the changes from baseline CD4 T-cell percentages to that at the Exam

time point for individuals in each group. There appeared to have no clear trend.

In the Johrei group, one individual increased, five stayed the same (less than 2.4%

changes: 99% confident interval of the measure in CD4 T-cell %) and five decreased, while in

the Relaxation control group, five individuals increased, four stayed the same and two decreased.

In the Self-hypnosis group, three increased, seven stayed the same and two decreased.

p = 0.094 Not significant Not significant

Not significant

Not significant



28

34

40

46

52

58

64

Baseline Exam

28

34

40

46

52

58

64

Baseline Exam

28

34

40

46

52

58

64

Baseline Exam

Self-hypnosis Johrei Relaxation control Figure 28: The individual levels of CD4 T-cell percentages in the three groups at baseline and the Exam

time point

Conclusion:

Exam stress did not affect peripheral blood CD4 T-cell percentages. In addition, neither of

the psychological interventions affected CD4 T-cell percentages significantly.

CD8 T-cell percentages

The results show that there was no significant difference between the three groups in the

levels of CD8 T-cell percentages at baseline (Self-hypnosis and Relaxation control: t = 0.8, df =

21, ns; Johrei and Relaxation control: t = 0.2, df = 20, ns).

There was no significant difference statistically in the changes between the three groups

(F = 2.3, df = 31, ns). At the Exam time points, there was no significant change in CD8 T-cell

percentage in the Relaxation control and Johrei groups. However, an exploratory analysis with

paired t-tests showed that the CD8 T-cell percentages increased in the Self-hypnosis group

(mean change = 2.5, t = 3.1, SD = 2.8, df = 11, p = 0.010) [Table 21 and Figure 29]. Analyses of

the data by gender showed the same trends [Appendix 6: Tables A-33 and A-34].


(Controls) groups at baseline and the Exam time point CD8 T-cells (%)



25.1 (20.9 - 29.4)

26.8 (24.0 – 29.6)

27.2 (24.4 - 30.1)

27.6 (24.0 - 31.2)

27.6 (24.3 – 30.9)

26.8 (23.9 - 29.8)

N 12 11 11 12 11 11

CD

4 T

cel

l per

cen

tag

e




0

10

20

30

Mean

(95%

C.I.)

levels

of CD

8 T-ce

lls (%

)

BaselineExams

Figure 29: Mean (95% C.I.) levels of CD8 T-cells of the three groups at baseline and the Exam time point

Figure 30 shows the changes from baseline CD8 T-cell percentages to that at the Exam

time point for individual students in each group. In the Self-hypnosis group, there was an

increasing trend with seven individuals increased, four stayed the same (less than 1.7% changes:

99% confident interval of the measure in CD8 T-cell %) and one decreased. There was no clear

trend in the Johrei with four increased, five stayed the same and two decreased; and in the

Relaxation control groups, two individuals increased, six stayed the same and three decreased.

16

22

28

34

40

Baseline Exam

16

22

28

34

40

Baseline Exam

16

22

28

34

40

Baseline Exam

Self-hypnosis Johrei Relaxation control Figure 30: The individual levels of CD8 T-cell percentages in the three groups at baseline and the Exam

time point

Conclusion:

Exam stress did not appear to affect peripheral blood CD8 T-cell percentages. However,

the Self-hypnosis appeared to increase CD8 T-cell percentages.


Not significant

CD

8 T

cel

l per

cen

tag

e

Not-significant

Not-significant



Summary:

Practising Self-hypnosis or Johrei prior to academic exams, when compared with the

passive relaxation experience, did not appear to affect perceived stress levels in university

students facing academic exams. Johrei, however, appeared to decrease the increased anxiety

levels in university students facing at academic exams.

NKCA levels in the university students practising either Self-hypnosis or Johrei at

academic exams were similar to the levels in the students following the control relaxation

experiences. On the other hand, academic exam stress appeared to be associated with a decrease

in NK-cell levels in university student with relaxation experience although this decrease did not

achieve statistical significance, and interestingly this decrease was reversed in the students

trained in and practising Johrei. Self-hypnosis did not appear to differ significantly from

Relaxation control in the effect on NK-cell levels. On this occasion, exam stress was not found

to affect the levels of CD4 and CD8 T-cells, and the levels of these cells were not affected by

Johrei intervention while Self-hypnosis increased CD8 T-cell percentages when students faced

academic exams.

These findings partially supported the hypothesis that psychological intervention may

counteract the effect of stress upon the proposed integrated psycho-neuro-endocrino-immune

network; and warrant the need to investigate this hypothesis further, in a patient population.

Hence, the next study employs HIV-infected individuals [3.2].

3.2 The influence of psychological intervention upon perceived stress and

quality -of-life and various immunological disease-associated parameters in

HIV -infected individuals

The objective of this study was to determine if the training and practice of psychological

stress coping skills would influence stress perception as well as immunological parameters

particularly the disease progression marker, CD4 T-cell counts, in HIV-infected individuals.



3.2.1 Disease-associated and stress-related changes in HIV -infected individuals

This part investigates the proposed integrated psycho-neuro-endocrino-immune network

by examining psychological and immune (disease) parameters and associations between the

parameters, i.e. between the levels of stress perception and perceived quality-of-life and CD4 T-

cell counts as primary outcome measures.

3.2.1.1 Psychological profiles of the HIV-infected individuals recruited into the study

The HIV-infected individuals recruited into the study were asked at recruitment and four

months later to complete the psychological questionnaires listed below in order to assess their

levels of stress perception and perceived quality-of-life:

� General and HIV-infection related stress perception

Perceived Stress Score (PSS): secondary appraisal scale

State anxiety in the State Trait Anxiety Inventory (STAI): anxiety scale

Impact Event Scale (IES): primary appraisal against a stressor scale

� Quality-of-life (QoL) perception

Locus of Control (LoC): sense of taking control of one’s own life scale (recall:

inner or outer locus of control = low or high score)

Mental Component Summary in the SF-36 (MCS): mental quality-of-life scale

Pittsburgh Sleep Quality Inventory (PSQI): sleep quality scale

With all of these questionnaires, except the MCS, lower scores mean better functioning.

Analyses of these data involved, first, a comparison of the PSS and the State anxiety scores of

the participants in this study with those of the university students in the previous study. Second,

the other psychological profiles collected specifically to this study were analysed by comparing

the two stress-related subgroups (labelled as Not-stressed and Stressed subgroups) defined by

the midline split of the PSS at recruitment, i.e. individuals scoring more than 31 in the PSS were

placed in the Stressed subgroup and individuals scoring equal to or below 31 were placed into

the Not-stressed subgroup.

Perceived stress levels (PSS)

The HIV-infected individuals had higher PSS scores (mean difference = 7.2, t = 4.5, df =

81, p < 0.001) than the university students facing examinations, and the PSS scores did not

change significantly (F = 0.02, df = 46, ns) from recruitment to the four months later time point

in HIV-infected individuals [Table 21].



Table 22: Medians, means and standard deviations of the PSS of the university students at non-exam and

exams and of the HIV-infected individuals at recruitment and four months later University students HIV -infected individuals

Non-exam Exams Recruitment After 4 months Median 22 25 32 31 Mean 23.3 24.4 31.6 31.7 SD 8.8 7.5 7.0 5.6 n 34 32 51 51

Conclusion:

Patients with HIV have higher stress perception than university students facing exams.

The subgroups of Not-stressed and Stressed were defined by the judgement of a midline

split of the PSS score at recruitment. The Stressed subgroup had 26 subjects (including two

females) and the Not-stressed subgroup had 25 subjects (one female). The results from 51

subjects (three females and 48 males) and the results from 48 male subjects only are similar and

they have the same trend, so only the results from 48 male subjects are presented.

The result from 48 HIV-infected male individuals shows that there were differences

between the Stressed and Non-stressed subgroups in the levels of PSS at recruitment and four

months later [Table 23].

Table 23: Mean (95% C.I.) levels of the PSS in the Not-stressed and Stressed subgroups at the recruitment and four months later

PSS levels Recruitment After 4 months

Not-stressed Stressed Not-stressed Stressed Mean score (95% C.I.)

26.0 (24.6 – 29.5)

36.8 (34.9 – 38.6)

27.4 (25.8 – 28.9)

35.5 (33.2 – 35.5)

n 24 24 24 24

There were significant differences between the two subgroups both at recruitment (t = 9.2,

df = 46, p < 0.001) and four months later (t = 5.9, df = 46, p < 0.001). There was a significant

time x subgroup interaction (F = 5.8, df = 49, p = 0.020), but the PSS scores did not change

significantly over the four months study period in the Not-stressed (t = 1.2, df = 23, ns) or in the

Stressed subgroup (t = 1.6, df = 23, ns) [Figure 31].




0

10

20

30

40

Mean

(95%

C.I.)

PSS

leve

ls

RecruitmentAfter 4 months

Figure 31: Mean (95% C.I.) PSS levels of the Not-stressed and Stressed subgroups at recruitment and

four months later

Conclusion:

PSS levels in HIV-infected individuals did not change significantly over the four months

of the study period, and this consistency in the levels of PSS scores was also shown when the

Stressed or Not-stressed subgroups were separately compared.


In contrast to the PSS, anxiety levels in the HIV-infected individuals were similar to the

levels of the university students (mean difference = 1.1, t = 0.4, df = 85, ns), and state anxiety

level in the HIV-infected individuals did not change significantly (F = 0.7, df = 46, ns) from

recruitment to four months later [Table 24].

Table 24: Median, mean and standard deviation of the State anxiety score of the university students at

non-exam and exams and of the HIV-infected individuals at recruitment and four months later University students HIV -infected individuals

Non-exam Exams Recruitment After 4 months Median 37 40 36 38 Mean 37.9 39.7 38.9 40.8 SD 9.4 8.3 12.5 14.4 n 37 36 51 51

Conclusion:

This result suggested that there was little difference in the State anxiety scores in HIV-

infected individuals compared with the university students facing academic exams.

When comparisons were made between the 48 HIV-infected male individuals in the Not-

stressed and Stressed groups based on a median split of the PSS score, the individuals in the

Not-significant

Not-significant

p < 0.001

p < 0.001



Stressed subgroup had significantly higher anxiety levels than the individuals in the Not-

stressed subgroup both at recruitment (t = 7.0, df = 49, p < 0.001) and four months later (t = 6.1,

df = 49, p < 0.001). There was no significant time x subgroup interaction (F = 1.7, df = 49, ns),

and the State anxiety scores did not change significantly over the study period in the Not-

stressed subgroup (mean change = 2.2, t = 1.1, df = 23, ns) or in the Stressed subgroup (mean

change = - 0.3, t = 0.3, df = 23, ns) [Table 25 and Figure 32].

Table 25: Mean (95% C.I.) levels of the State anxiety score of the STAI in the Not-stressed and Stressed

subgroups at the recruitment and four months later State anxiety score of the STAI

Recruitment After 4 months

Not-stressed Stressed Not-stressed Stressed Mean level (95% C.I.)

30.2 (26.9 – 33.4)

49.6 (45.1 – 54.1)

30.5 (27.6 – 33.3)

47.4 (42.6 – 52.2)

n 24 24 24 24


0

10

20

30

40

50

60

Mea

n (9

5% C

.I.) S

tate

anx

iety

sco

res

Recruitmentafter 4 months

Figure 32: Mean (95% C.I.) levels of the State anxiety scores in the STAI of the Not-stressed and Stress

subgroups at recruitment and four months later

Conclusion:

HIV-infected individuals reporting low levels of stress also report lower scores of the

State anxiety than individuals reporting high levels of stress.

Primary appraisal against a specific life event levels (IES)

The primary appraisal of the awareness of carrying HIV-infection was measured by the

IES. The mean IES scores of the Stressed individuals were significantly higher than the levels

for the Not-stressed individuals at recruitment (t = 3.2, df = 23, p = 0.003) and after four months

(t = 3.2, df = 23, p = 0.003). The IES scores decreased significantly over the study period (F =

Not-significant

p < 0.001

p < 0.001

Not-significant



18.8, df = 46, p < 0.001), and this was observed in both the Stressed subgroup (mean change =

7.3, t = 3.5, df = 23, p = 0.002) and the Not-stressed subgroup (mean change =6.2, t = 2.7, df =

23, p = 0.013), but there was no significant time x subgroup interaction (F = 0.5, df = 49, ns)

[Table 26 and Figure 33].

Table 26: Mean (95% C.I.) levels of the IES in the subgroups of the Not-stressed and Stressed at the

recruitment and four months later IES


Not-stressed Stressed Not-stressed Stressed Mean

(95% C.I.) 16.5

(10.0 – 23.1) 31.4

(24.7 – 38.1) 10.4

(5.9 – 14.8) 24.2

(16.6 – 31.7) n 24 24 24 24


0

10

20

30

40

Mea

n (9

5% C

.I.) I

ES le

vels


Figure 33: Mean (95% C.I.) levels of the IES in the Not-stressed and Stress subgroups at recruitment and

four months later

Conclusion:

The impact in the primary appraisal from diagnosed as carrying HIV-infection decreased

over the study period. Although the decreased levels of impact in the HIV-infected individuals

were not different between the stressed and not-stressed subgroups, individuals with a high

perceived stress level consistently showed higher levels of impact than the individuals in the

not-stressed subgroup both at recruitment and four months later.

Locus of control (LoC: Sense of control of one’s own life levels)

The sense of taking control of one’s own life was measured by using the LoC. The LoC

scores were significantly higher in the Stressed individuals than the Not-stressed individuals at

p = 0.002

p = 0.003

p = 0.003

p < 0.001



recruitment (t = 2.8, df = 23, p = 0.007) and four months later (t = 1.0, df = 23, p = 0.002), but

there was no significant time x subgroup interaction (F = 0.1, df = 49, ns), and the scores did not

change significantly over the study period (F = 0.4, df = 46, ns) [Table 27 and Figure 34].

Table 27: Mean (95% C.I.) levels of the LoC in the Not-stressed and Stressed subgroups at the

recruitment and four months later LoC score


Not-stressed Stressed Not-stressed Stressed Mean level (95% C.I.)

9.3 (5.9 – 14.8)

12.6 (11.0 – 14.2)

8.7 (7.5 – 11.0)

12.6 (11.0 – 14.2)

n 24 24 24 24


0

5

10

15

Mea

n (9

5% C

.I.) L

oC le

vels


Figure 34: Mean (95% C.I.) levels of the LoC in the Not-stressed and Stressed subgroups at recruitment


Conclusion:

The locus of control did not change significantly over the study period, and less stressed

HIV-infected individuals reported the lower scores (a higher sense of taking control of one’s

own life) than did higher stressed individuals.

Mental aspect of quality of life levels (MCS: psychological functioning)

The psychological functioning in the HIV-infected individuals not receiving anti-

retroviral medication and not experiencing disease-related symptoms in this study was

examined by measuring mental aspect of quality of life, i.e. the MCS scores. The MCS scores

were significantly higher in the Not-stressed individuals than in the Stressed individuals at

recruitment (t = - 5.8, df = 23, p < 0.001) and four months later (t = - 4.6, df = 23, p < 0.001),

Not-significant

Not-significant

p = 0.007

p = 0.002



but there was no significant time x subgroup interaction (F = 1.2, df = 49, ns), and the scores did

not change significantly over the study period (F = 0.8, df = 46, ns) [Table 28 and Figure 35].

Table 28: Mean (95% C.I.) levels of the MCS in the Not-stressed and Stressed subgroups at recruitment

and four months later MCS score



(95% C.I.) 51.8

(48.7 – 54.8) 35.3

(30.5 – 40.1) 52.1

(48.8 – 55.4) 37.6

(32.2 – 42.9) n 24 24 24 24


0

10

20

30

40

50

60

Mea

n (9

5% C

.I.) M

CS le

vels


Figure 35: Mean (95% C.I.) levels of the MSC in the Not-stressed and Stressed subgroups at recruitment


Conclusion:

Psychological functioning, as measured by the mental health component of the SF-36

(MCS), did not change significantly over the study period, and HIV-infected individuals in the

stressed subgroup reported lower levels of psychological functioning than individuals in the

non-stressed subgroup both at recruitment and four months later.

Sleep quality levels (PSQI)

The PSQI scores of the Stressed individuals were significantly higher than that of the Not-

stressed at recruitment (t = 2.1, df = 46, p = 0.039) and after four months (t = 2.9, df = 46, p =

0.005), but there was no significant time x subgroup interaction (F = 0.6, df = 49, ns), and the

scores did not change significantly over the study period (F = 0.6, df = 46, ns) [Table 29 and

Figure 36].

Not-significant

Not-significant

p < 0.001

p < 0.001



Table 29: Mean (95% C.I.) levels of the PSQI in the Not-stressed and Stressed subgroups at recruitment and four months later

PSQI Recruitment After 4 months


(95% C.I.) 8.1

(6.9 – 9.4) 10.3

(8.7 – 11.8) 7.5

(6.6 – 8.4) 10.2

(8.6 – 11.8) n 24 24 24 24


0

2

4

6

8

10

12

Mean

(95%

C.I.)

PSQ

I sco

res


Figure 36: Mean (95% C.I.) levels of the PSQI in the Stress and Not-stressed subgroups at recruitment and four months later

Conclusion:

The sleep quality scores did not change significantly over the study period, and HIV-

infected individuals in the stressed subgroup reported worse sleep quality than HIV-infected

individuals in the non-stressed subgroup at recruitment and four months later.

3.2.1.2 Stress-related perception and disease progression markers of HIV infection

CD4 T-cell counts and HIV viral load levels are routinely measured for the purpose of

clinically monitoring disease progression. Therefore, relationships between the CD4 T-cell

counts and HIV viral load levels and levels of stress perception were examined.

Rate of decline in CD4 T-cell count (CD4 gradient)

CD4 T-cell counts form a major part of the routine monitoring of HIV-infected patients.

As described in the methods section [2.1.2], of the 63 participants recruited, only 38 patients

(60.3%) had sufficient data from which to calculate the CD4 gradients during the (four month

plus one month, five months altogether, i.e. Baseline to Term four) study period. Within the 38

patients, 32 participants (30 males and two females) completed their questionnaires. The results

obtained from 32 subjects and the results from 30 male subjects only are similar and they have

Not-significant

Not-significant

p = 0.005

p = 0.039



the same trend, so only the results from 30 male subjects were presented. Mean CD4 gradient of

30 male subjects was a decline of 3 cells per �l per month.

The CD4 gradient over the five months was investigated by correlation analyses for

associations with the levels of the stress-related perceptions (State anxiety score of the STAI,

the Perceived Stress Score: PSS and Impact Event Scale: IES) and the perceived quality-of-life

(Locus of Control: LoC, Mental Component Summary in the SF-36: MCS and Pittsburgh Sleep

Quality Index: PSQI). The CD4 gradients over the five months was not significantly associated

with the scores of State anxiety, IES or PSS at either recruitment or after the four months time

points, and that there was no significant associations with scores of the MCS or PSQI at either

recruitment or after four months [Appendix 6: Table A-35]. There was a trend towards a

positive correlation (r = 0.32, n = 30, p = 0.085) between the CD4 gradients and LoC scores at

recruitment, but this relationship was not statistically significant at four months after the

recruitment [Appendix 6: Table A-35].

Conclusion:

The scores of stress perception, quality of life and sleep quality either at recruitment or at

four months had no significant association with the CD4 gradients over the five months period,

i.e. none of the scores at a one assessment point in this study could be used to predict or to

indicate the rate of change in the CD4 counts in HIV-infected patients not receiving anti-

retroviral treatment.

The CD4 gradient represents the rate of change in CD4 counts over a five month period,

therefore change scores of the various perceived stress scales (State anxiety scores, PSS and

IES) over the same period were analysed with the CD4 gradient. The CD4 gradients had no

significant association with the State anxiety, IES or PSS [Appendix 6: Table A-36].

Further, change scores of the various perceived quality-of-life were analysed, and it was

found that the CD4 gradients had a significant negative correlation with the change scores of the

LoC; and a significant positive correlation with the change scores of the MCS, while there was a

trend towards a negative correlation with the change scores of the PSQI [Table 30].



Table 30: Correlations between the CD4 gradient (cells per �l per month) and the change scores of perceived quality-of-life scales in:

LoC* MCS* PSQI R - .40 .44 - .32

2-tailed p 0.029 0.015 0.086 N 30 30 30

*: p < 0.05

The correlations between CD4 gradient and the change scores in the (1) LoC, (2) MCS

and (3) PSQI can imply that:

1. Individuals with an increased sense of taking control of one’s own life (decreased

their LoC scores) showed an increase in their CD4 T-cell counts (recall that low LoC

= inner locus of control), and individuals who decreased the sense of control

(increased their LoC scores) showed a decrease in their CD4 T-cell counts;

2. Individuals who improved their psychological functioning (increased MCS levels)

showed an increase in their CD4 T-cell counts, and individuals who reported a

decrease in psychological functioning (decreased MCS scores) showed a decrease in

their CD4 T-cell counts; and

3. Individuals with improvement in their sleep quality (decreased PSQI scores) showed

an increase in their CD4 T-cell counts (recall that low PSQI = better sleep quality),

and individuals who reported a decrease in sleep quality (increased PSQI scores)

showed a decrease in their CD4 T-cell counts.

Therefore, further analyses were performed after grouping the patients according to

change scores of these perceived quality-of-life scales (increased or decreased), and similar

trends of associations between changes in these scales and the CD4 gradients were

demonstrated. There were significant differences in the CD4 gradient when CD4 gradients were

compared between the two subgroups according to change scores of:

1. LoC (t = 2.1, df = 30, p = 0.049): Increased sense of control of one’s own life

(Increased control: 16 individuals with a decreased LoC score) and Decreased sense

of control (Decreased control: 14 individuals with an increased LoC score) subgroups

[Table 31 and Figure 37];

2. MCS (t = 2.4, df = 30, p = 0.027): Improved psychological functioning (Improved

QoL: 16 individuals with an increased MCS score) and Decreased psychological

functioning (Decreased QoL: 14 individuals with a decreased score) subgroups [Table

32 and Figure 38]; and



3. PSQI (t = 2.1, df = 30, p = 0.047): Improved sleep quality (23 individuals had a

decreased PSQI score) and Decreased sleep quality (7 individuals had an increased

score) subgroups [Table 33 and Figure 39].


infected individuals of the Increased control and Decreased control subgroups CD4 T-cell change (cells per �l per month) Increased control Decreased control

Mean CD4 gradient (95% C.I.)

+ 9 (- 2.8 to + 21.7)

- 15 (- 34.7 to - 5.2)

n 16 14

Increased control Decreased control

-40

-20

0

20

40

Mean

(95%

C.I.)

CD4

grad

ient (

cells

/ul/m

onth)

Figure 37: Mean (95% C.I.) CD4 gradients (cells per �l per month) in the Increased control (decreased

scores of the LoC) and Decreased control (increased scores of the LoC) subgroups

Table 32: Mean (95% C.I.) CD4 T-cell change over the five month (cells per �l per month) in HIV-infected individuals of the Improved QoL and Decreased QoL subgroups

CD4 T-cell change (cells per �l per month) Improved QoL Decreased QoL

Mean CD4 gradient (95% C.I.)

+ 11 (- 1.4 to 21.4)

- 19 (- 40.5 to + 2.5)

n 16 14

Improved QoL Decreased QoL

-40

-20

0

20

40

Mean

(95%

C.I.)

CD4

grad

ient (

cells

/ul/m

onth)

Figure 38: Mean (95% C.I.) CD4 gradients (cells per �l per month) in the Improved mental psychological

functioning (Improved QoL: increased scores of the MCS) and Decreased psychological functioning (Decreased QoL: decreased scores of the MCS) subgroups

p = 0.049

p = 0.027




infected individuals of the Improved sleep quality and Decreased sleep quality subgroups CD4 T-cell change (cells per �l per month)

Improved sleep quality Decreased sleep quality Mean CD4 gradient (95% C.I.)

+ 4 (- 8.4 to + 18.2)

- 26 (- 48.9 to - 1.9)

n 23 7

Improved sleep quality Decreased sleep quality

-60

-40

-20

0

20

40

60

Mea

n (9

5% C

.I.) C

D4 g

radie

nt (c

ells/u

l/mon

th)

Figure 39: Mean (95% C.I.) CD4 gradients (cells per �l per month) in the Improved sleep quality

(decreased scores of the PSQI) and Decreased sleep quality (increased scores of the PSQI) subgroups

Conclusion:

These findings suggest that the rate of decline in the CD4 T-cell count of HIV-infected

individuals is associated with change scores in the perceived control, psychological functioning

and sleep quality scales rather than actual scores on one occasion, i.e. those who increased CD4

T-cell counts over the five month period improved in the scores of LoC, MCS and PSQI.

Rate of change in HIV viral load (HIV viral load gradient)

Viral load levels are another major part of the routine monitoring of the HIV-infected

patients, particularly with regard to drug treatment. Although none of the HIV-infected

individuals in this study had taken any anti-retroviral treatment, the rate of change in viral load

levels (log-transformed figures) was calculated between the recruitment time point and four

months later. Similar to the results of the CD4 T-cell blood collection, not all of the HIV-

individuals recruited had viral load levels measured during the study period [Appendix 6: Table

A-37]. Of the 63 participants recruited, only 38 patients (60.3%) had sufficient data from which

to calculate the viral load level (log-transformed) gradients during the study period. Within the

above 38 patients, 32 participants (29 males and three females) completed their questionnaires.

The results obtained from 32 subjects and the results from 29 male subjects are similar and they

have the same trend, so only the results from 29 male subjects are presented.

p = 0.047



This viral load level gradient over the five months was investigated by correlation

analyses for association with the scores of the State anxiety score, PSS, IES, LoC, MCS and

PSQI. There was no significant correlation at either recruitment or after four months time points

[Appendix 6: Table A-38]. Similar to the analyses of the CD4 gradient, change scores of the

stress perceptions (State anxiety scores, PSS and IES) and perceived quality-of-life scales (LoC,

MCS and PSQI) over the same period were correlated with the viral load level gradient.

However, the viral load level gradients were not significantly associated with the change scores

of any self-report variable [Appendix 6: Table A-39].

Conclusion:

Viral load level was not significantly associated with any of the perceived stress or

quality-of-life measures used in this study.

Rate of change in NK-cell count (NK gradient)

Because NK-cell levels were shown to be associated with the stress perception in the

university students [3.1], for exploratory purposes, the NK gradient was also calculated from the

same blood sample data as the CD4 T-cell gradients. One sample datum was missing for NK-

cell calculation. Hence 37 subjects had sufficient data from which to calculate the NK gradients

during the study period. Within the above 37 patients, 31 participants (29 males and two

females) completed their questionnaires. The results obtained from 31 subjects and the results

from 29 male subjects are similar and they have the same trend, so only the results from 29 male

subjects were presented.

The NK gradient over the five months and the scores of the psychological measures were

further investigated by correlation analyses for associations with the levels of the stress-related

perceptions (State anxiety score, PSS and IES) and the perceived quality-of-life and sleep (LoC,

MCS and PSQI). Results show that the NK gradients over five months were not significantly

associated with the scores of State anxiety, IES, PSS LoC, MCS or PSQI at either recruitment or

after four months, except with the PSQI at recruitment [Appendix 6: Table A-40]. There was a

significant correlation (r = 0.44, p = 0.017) between the NK gradient and the PSQI score at

recruitment but this correlation was not replicated at the four month assessment point [Appendix

6: Table A-40]. Similar to the analyses of the CD4 gradient, change scores of the stress

perceptions (State anxiety scores, PSS and IES) and quality-of-life scales (LoC, MCS and

PSQI) over the same period were correlated with NK gradients. However, none of these

correlations were statistically significant [Appendix 6: Table A-41].



Conclusion:

The levels of or changed levels of NK-cell count were not significantly associated with

any of the stress perception or quality of life measures used in this study.

Summary:

Patients with HIV diagnosis have higher stress perception than university students facing

exams, and the higher levels did not change significantly over the four months of the study

period. On the other hand, there was little difference in the State anxiety levels between the

HIV-infected individuals and the university students facing academic exams, and HIV-infected

individuals who reported low levels of stress also reported lower State anxiety scores than

individuals who reported high levels of stress. The impact of being diagnosed as carrying HIV-

infection decreased over the study period. Although the impact levels decreased, individuals

with high perceived stress consistently showed higher scores of the impact than the individuals

who reported low stress.

The perceived quality-of-life (locus of control, psychological functioning and sleep

quality) scales did not change significantly over the study period, and lower stressed HIV-

infected individuals constantly reported having a higher sense of taking control of one’s own

life, better psychological functioning and better sleep quality than the higher stressed

individuals.

Notably, it was concluded that the scores of stress perception and perceived quality-of-life

scales at a single assessment point (recruitment or four months later) were not associated with

the rate of change in the CD4 counts in HIV-infected patients (not receiving anti-retroviral

treatment); but that the rate of decline in the CD4 T-cell count of HIV-infected individuals was

associated with changes in the perceived quality-of-life (LoC, MCS and PSQI) scores.

These results support the central hypothesis that stress causes detrimental effects upon

well-being; and further, that an improvement in perceived quality-of-life may have beneficial

effect upon disease progression, i.e. psychological improvement may be beneficial for health.

This leads onto the next investigation of psychological intervention upon the psycho-neuro-

endocrino-immune network, particularly upon the perceived quality-of-life scales and the

disease progression marker, CD4 T-cell count [3.2.2].



3.2.2 The influence of psychological intervention upon disease progresion parameters in

HIV -infected individuals (randomised controlled trial over a four month period)

This study investigates the hypothesis that psychological intervention can counteract

detrimental effect of stress upon disease progression, i.e. decline of the CD4 T-cell counts,

acting through the proposed integrated psycho-neuro-endocrino-immune network.

3.2.2.1 Effect of psychological intervention upon perceived stress and anxiety in HIV-infected

individuals

The influence of the psychological intervention upon mental well-being (perceived stress

and quality-of-life) was examined by comparing the scores on the self-report questionnaires

between the Self-hypnosis, Johrei groups and the wait-listed control group.

The State anxiety scores or the PSS scores did not change significantly from the Baseline

to the Post-intervention time point (four months after the Baseline) in any group, and the scores

did not differ between groups at either assessment point [Appendix 6: Table A-42]. The Impact

Event Scale (IES) scores improved significantly between the pre- and post- intervention time

points (F = 14.1, df = 48, p < 0.001). There were, however, no significant group differences in

this change, i.e. no significant time x group interaction (F = 0.8, df = 48, ns) [Table 34].

Table 34: Mean (95% C.I.) levels of the IES in the HIV-individuals in the Self-hypnosis, Johrei and wait-

listed control groups at the Baseline and Post-intervention time points IES

Baseline Post-intervention Self-hypnosis Johrei Controls Self-hypnosis Johrei Controls


23.1 (19.2 - 27.0)

23.5 (18.3 - 28.7)

28.4 (24.2 - 32.6)

16.0 (12.3 - 19.7)

20.1 (15.2 - 25.0)

21.2 (17.2 - 25.2)

N 21 12 18 21 12 18

The Locus of Control (LoC) (F = 1.1, df = 48, ns), Mental Components Summary of SF-

36 (MCS) (F = 0.8, df = 48, ns) or Pittsburgh Sleep Quality Inventory (PSQI) (F = 1.9, df = 48,

ns) scores did not change significantly from the Baseline to the Post-intervention time point in

any group, nor did it differ between groups at either assessment point, i.e. no significan time x

group interactions [Appendix 6: Table A-43]. Hence, it was concluded that psychological

intervention did not affect stress perception or perceived quality-of-life significantly.

However, having shown in the previous section that the worsining in the levels of the LoC,

MCS and PSQI over the study period were positively associated with the decline in the CD4 T-



cell count [3.2.1.3], the distributions of the number of people who were improving or worsening

in the levels of (1) LoC [Table 35], (2) MCS [Table 36] and (3) PSQI [Table 37] were further

examined using the Intention-to-treat analysis (The participants who failed to provide self-report

questionnaire data were added in the numbers of the Decreased control, Decreased QoL or

Decreased sleep quality groups) for the exploratory purpose.

Table 35: Summary of the numbers (%) of the HIV-individuals whose changes in the LoC between the Baseline and post-intervention either decreased (Increased control: increased sense of control in one’s own life) or increased (Decreased control) in the Self-hypnosis, Johrei and wait-listed control groups

Increased control Decreased control Total Self-hypnosis 10 / 21 (48%) 11 / 21 (52%) 21 Johrei 9 / 12 (75%) 3 / 12 (25%) 12 Control 10 /18 (55%) 8 /18 (45%) 18

Total 29 22 51

Table 36: Summary of the numbers (%) of the HIV-individuals whose changes in the MCS between the Baseline and post-intervention either increased (Improved QoL: improved psychological functioning) or

decreased (Decreased QoL) in the Self-hypnosis, Johrei and wait-listed control groups Improved QoL Decreased QoL Total

Self-hypnosis 11 / 21 (52%) 10 / 21 (48%) 21 Johrei 7 / 12 (58%) 5 / 12 (42%) 12 Control 7 /18 (38%) 11 /18 (62%) 18

Total 25 26 51 Table 37: Summary of the numbers (%) of the HIV-individuals whose changes in the PSQI between the Baseline and post-intervention either decreased (Improved sleep quality) or increased (Decreased sleep

quality) in the Self-hypnosis, Johrei and wait-listed control groups Improved sleep quality Decreased sleep quality Total

Self-hypnosis 15 / 21 (71%) 6 / 21 (29%) 21 Johrei 9 / 12 (75%) 3 / 12 (25%) 12 Control 10 /18 (55%) 8 /18 (45%) 18

Total 34 17 51

The percentages of the HIV-infected individuals who improved the LoC. MCS or PSQI

scores in the Johrei group were all higher than those in the wait-listed control group, although

these different percentages between the three groups did not achieve statistical significance

(Self-hypnosis vs. wait-listed control: chi-square = 0.2, and Johrei vs. wait-listed control: chi-

square = 1.2 for the LoC; Self-hypnosis vs. wait-listed control: chi square = 0.7, and Johrei vs.

wait-listed control: chi-square = 1.1 for the MCS; and Self-hypnosis vs. wait-listed control: chi-

square = 1.1, and Johrei vs. wait-listed control: chi-square = 1.2 for the PSQI).

Sample size calculation shows that it would need 121, or 133, subjects per group in order

to show that 75%, or 58% in the Johrei group, is significantly different to the 55%, or 38% in

the wait-listed control group, respectively.



Conclusion:

Neither Self-hypnosis nor Johrei appeared to alter anxiety or perceived stress levels in the

HIV-infected individuals (not receiving anti-retroviral treatments). The impact of being aware

of carrying HIV-infection decreased over the study period, but neither the intervention of the

Self-hypnosis nor Johrei affected the decrease over that found in the wait-listed control group.

None of the LoC, MCS and PSQI scores changed, and the Johrei and Self-hypnosis group did

not alter these scores significantly over the study period, although the Johrei group showed the

highest percentages who improved in their scores in all the perceived quality-of-life scales.

Sample size calculation showed that the numbers in each group were too few to demonstrate

statistically significant changes.

3.2.2.2 Effect of psychological intervention upon CD4 T-cell counts in HIV-infected

individuals

The influence of psychological intervention upon the change in the CD4 T-cell counts

(CD4 gradient: the disease parameter) was examined in order to test the hypothesis that

psychological intervention may counteract the detrimental effect of stress upon disease

progression in HIV-infected individuals.

CD4 gradients were constructed for 15 participants in the Self-hypnosis, ten in the Johrei

and 13 in the wait-listed control groups. A mean decline of 12 cells per �l per month in CD4 T-

cell counts was shown in the wait-listed control group. The Kruskal-Wallis rank test showed a

trend towards difference among the three groups (chi-square = 5.5, df = 2, Monte Carlo

significance = 0.064). These different trends among the three groups were confirmed by

following chi-square analyses. There was a significant decrease in the rate of decline of CD4 T-

cells in participants who were trained in and practising Johrei compared with individuals in the

wait-listed control (chi-square = 3.9, df = 1, two-tailed p = 0.047) and Self-hypnosis (chi-square

= 4.5, df = 1, two-tailed p = 0.033) groups. There was, however, no difference in CD4 gradient

between the Self-hypnosis and wait-li sted control groups (chi-square = 0.1, df = 1, ns) [Table 38

and Figure 40].

Table 38: Mean (95% C.I.) levels of CD4 gradients (counts per �l per month) in HIV-infected individuals

in the Self-hypnosis, Johrei and wait-listed control groups CD4 gradient (counts per �l per month)

Self-hypnosis Johrei Controls Mean change (95% C.I.)

- 9 (-17 to -1)

+ 17 (+ 6 to + 28)

- 12 (- 20 to - 3)

n 15 10 13



131015N =

ControlJohreiHypnosis

CD4 g

radient (9

5%

C.I.

) ce

lls/m

onth 50

0

-50

Figure 40: Means (95% C.I.) CD4 gradients over the five months study period from the Baseline to the Post-intervention time point

This finding was further investigated by the Intention-to-treat analysis comparing

percentages of individuals between the two groups (decrease or maintained the CD4 T-cell

counts). All the data from the subjects who withdrew were added into the number in the group

in which the subjects decreased their CD4 T-cells [Table 39].

Table 39: Percentages (numbers) of participants whose CD4 T-cell counts maintained or decreased

over the five months in the Self-hypnosis and Johrei and wait-listed control groups for the Intention-to-treat analysis (missing data were added into the number in the Decreased group)

Group Maintained CD4 T-cells Decreased CD4 T-cells Total Self-hypnosis 29% (6 /21) 71% (15/21) 21 Johrei 58% (7 /12) 42% (5 /12) 12 Controls 33% (6 /18) 67% (12/18) 18

Total 19 32 51

The percentage of the HIV-infected individuals who maintained the CD4 T-cell counts in

the Johrei group (58%) was higher than that of wait-listed control group (33%), but the different

percentages between the three groups did not achieve statistical significance. The sample size

calculation shows that it would need 84 subjects per group to show that 58% in the Johrei group

is significantly different to the 33% in the wait-listed control group.

Conclusion:

As shown in the previous analysis [3.2.1], CD4 T-cell counts in HIV-infected individuals

who were not receiving anti-retroviral treatment decreased in the wait-listed control group.

However, this decreasing trend of CD4 T-cell count appeared to be reversed by the training and

practice of Johrei, although this was not supported by the intention-to-treat analysis, while the

Not significant

p = 0.047 p = 0.033



training and practice of Self-hypnosis did not appear to affect this trend. Sample size calculation

showed that the numbers of each group were too few to demonstrate statistically significant

changes.

3.2.2.3 Effect of psychological intervention upon other immunological markers (log-

transformed viral load levels and NK-cell counts) in HIV-infected individuals

Viral load level (log-transformed) gradients were constructed for 14 participants in Self-

hypnosis, 12 in Johrei and 12 in the wait-listed control groups; and NK gradients were

constructed for 15 participants in Self-hypnosis, 10 in Johrei groups and 12 in the wait-listed

controls. The viral load level (log-transformed) did not change significantly over the five

months nor did NK gradients, and there were no significant difference between the three groups

[Appendix 6: Tables A-44 and A-45, respectively].

Conclusion:

As shown in the previous analysis [3.2.1], neither viral load level nor NK-cell count

changed significantly in HIV-infected individuals who were not receiving anti-retroviral

treatment, and the training and practice of Johrei or Self-hypnosis did not affect the viral load

level or the NK-gradient.

Summary:

Although the results showed a possibility that Johrei may have helped to improve

perceived quality-of-life scores, neither Self-hypnosis nor Johrei appeared to alter the levels of

stress perception or perceived quality-of-life significantly in the HIV-infected individuals.

The major disease progression marker of HIV-infection, CD4 T-cell counts, was shown to

decrease over the study period in the wait-listed control group as expected. The training and

practice of Self-hypnosis did not appear to affect this decrease. In contrast, this decreasing trend

appeared to be reversed significantly by the training and practice of Johrei in those individuals

who completed the study. Significance was lost in the intention-to-treat analysis, but this was

suggested to be related to the small sample size. Hence, this counteracting effect of Johrei on

decreasing trend was further investigated in the next study [3.2.3] examining the rate of change

in CD4 T-cell counts in the 12 months periods both prior to (in order to examine baseline

difference) and after participants starting either of their trainings (in order to examine the effect

of the intervention trainings).



These results provide support for the hypothesis that learning and practising psychological

intervention, which provides alternative perspectives of, and coping skills for, stressful life

events, improves psychological and physical well-being.

3.2.3 The influence of psychological intervention upon CD4 T-cells (disease progression

marker) in HIV -infected individuals (case controlled study over 24 months period)

This study aimed to replicate and explore the above findings [3.2.2.4] by increasing the

sample size and extending the investigation period from five months to a total of 24 months

(CD4 gradients were calculated over 12 months prior to and after the psychological

interventions commenced).

Matched anonymised patients from the database [see Methods section 2.1.3] were used as

controls for this study. Comparability was confirmed by comparing CD4 T-cell counts and CD4

gradiens of the controls with the study groups as follows [3.2.3.1].

3.2.3.1 Analysis of baseline differences between the three groups in the CD4 T-cell count

There were no differences in absolute CD4 T-cell counts between the three groups at the

time point the interventions commenced (F = 0. 7, df = 94, ns; Self-hypnosis vs. Database-

control: t = 0.6, df = 74, ns; Johrei vs. Database-control: t = 0.9, df = 66, ns) [Table 40].

Table 40: Mean (95% C.I.) levels of CD4 T-cell (counts per �l) in HIV-infected individuals in the groups

of the Self-hypnosis, Johrei and Database-controls at the Training period CD4 T-cells (counts per �l)

Self-hypnosis Johrei Controls Mean

(95% C.I.) 397

(330 - 464) 346

(278 - 414) 375

(346- 404) n 27 19 49

Further, there were no statistical differences in CD4 gradients between the three groups at

the Pre-intervention period (F = 0.2, df = 93, ns; Self-hypnosis vs. database control: t = 0.5, df =

75, ns; Johrei vs. database control: t = 0.2, df = 67, ns); and the average CD4 gradient for all 96

HIV-infected individuals was a decline of seven cells per �l per month [Table 41].



Table 41: Mean (95% C.I.) CD4 gradients in HIV-individuals in the Self-hypnosis, Johrei and Database control groups, and in all the 96 individuals (ALL) at the Pre-intervention period

CD4 gradient (cells per �l per month) ALL Self-hypnosis Johrei Controls

Mean (95% C.I.)

- 7 (- 11 to - 3)

- 7 (-10 to -3)

- 9 (- 14 to - 4)

- 5 (- 8 to - 3)

n 95 27 19 49

Conclusion:

There were no statistical differences in absolute CD4 T-cell counts at Month 0 and CD4

gradients during the Pre-intervention period between the three groups.

3.2.3.2 Analysis of the rate of change in CD4 T-cell count (CD4 gradient)

The objective of this study was:

� To explore the influence of the psychological intervention, particularly of Johrei,

upon the rate of decline by comparing the CD4 gradients in each group between the

periods over the 12 months prior to (Pre-intervention) and after the interventions

commenced (Post-intervention).

The CD4 gradients from all subjects were calculated as described in the method section

[2.1.3]. Two individual examples of CD4 gradient regression lines are presented in Figures 41

and 42.

Figure 41 shows the CD4 gradient of one database control patient as an example of the

natural course of the CD4 T-cell counts in HIV-infected individuals. For this patient, there is an

average decline of six (cells per �l per month) in the Pre-intervention period and four (cells per

�l per month) in the Post-intervention period. The Self-hypnosis participants gave similar

profiles to those shown for the database control patients, so that an individual example of their

CD4 gradient regression lines is not presented here.

In contrast, Figure 42 shows the CD4 gradient of one Johrei participant. There is a decline

of 10 (cells per �l per month) in the Pre-intervention period, and an increase of seven (cells per

�l per month) in the Post-intervention period.



Figure 41: CD4 gradients of one control subject at the Pre-intervention and Post-intervention periods

Figure 42: CD4 gradients of one Johrei subject at the Pre-intervention and Post-intervention periods

The different trends in CD4 gradients between Pre- and Post- intervention periods was

examined by ANOVA repeated-measure analyses followed by using the 10% trimming method

[Wilcox, 1997] as described in the Methods section [2.5]. This subsequent ANOVA included 78

subjects (20 in the Self-hypnosis, 14 in the Johrei and 44 individuals in the Database-controls).

Figure 43 shows the individual changes in the CD4 gradients between the Pre- and Post-

intervention periods in the Self-hypnosis, Johrei groups and Database-control groups.

Months (Pre (-) and Post (+) from the Training)

Pre-intervention Post-intervention

Mean decline of 6 cells per ��l per month Mean decline of 4 cells per ��l per month

TTrraaiinniinngg

Months (Pre (-) and Post (+) from the Training) TTrraaiinniinngg


Mean decline of 10 cells per ��l per month Mean increase of 7 cells per ��l per month



Self-hypnosis group (n =20) Johrei group (n =14) Database-controls (n =44) Figure 43: Individual changes in CD4 gradients (cell counts per �l per month) in the Self-hypnosis, Johrei

and Database-control groups between the Pre-intervention and Post-intervention periods

There was a significant decrease in the CD4 gradients from the Pre-intervention period to

the Post-intervention period (F = 19.4, df = 75, p < 0.001). The greatest improvement in the

CD4 gradients was seen in the Johrei group among the three groups (F = 2.4, df = 75, p = 0.095).

Having this result, further explorative analyses were performed as follows. Table 42

shows the summary of the increasing and decreasing trends in CD4 gradients with the

assumption that a change of four or less in CD4 gradient was defined as staying the same since

four CD4 T-cells change per �l per month was within the 95% C.I. of the mean in 95 patients in

the Pre-intervention period. Accordingly, individuals in the Improving subgroup improved the

rate of decline more than four cells per �l per month in CD4 gradient between Pre- and Post-

intervention periods, individuals in the Worsening subgroup increased the rate of decrease by

more than four CD4 T-cells per �l per month, and the rest were in the Staying-the-same

subgroup.

Table 42: Percentages of HIV-individuals in the Self-hypnosis, Johrei and Database-control groups whose

changes in CD4 gradients between the Pre-intervention and Post-intervention periods were either increased, stayed the same or decreased with a judgement that a change of four of less cells per �l per

month was defined as the same change (Staying-the-same subgroup), more than four increase (Improving subgroup), and more than four decrease (Worsening subgroup)

Group Improving (%) Staying-the-same (%) Worsening (%) Total Self-hypnosis 9 / 20 (45%) 7 / 20 (35%) 4 / 20 (20%) 20 Johrei 11 / 14 (79 %) 2 / 14 (14%) 1 / 14 (7%) 14 Database-control 11 / 44 (25%) 21 / 44 (48%) 12 / 44 (27%) 44

Total 31 30 17 78

Gradient changes in Hypnosis

-30

-20

-10

0

10

20

30

Pre Post

Gradient changes in Johrei

-30

-20

-10

0

10

20

30

Pre Post

Gradient changes in Control

-30

-20

-10

0

10

20

30

Pre Post



This 11/14 (79%) of the Improving subgroup in the Johrei group is significantly different

to the 11/44 (25%) in the Database-control group (Pearson's chi-square = 12.9, df = 1, p <

0.001) while the 9/20 (45%) in the Self-hypnosis group was not significantly different to that in

the Database-control group (Pearson's chi-square = 2.6, df = 1, ns).

Having shown these findings using trimmed data set, further analyses using all of the 96

subjects were performed in order to confirm the results that Johrei may have maintained CD4 T-

cell counts. The analyses include comparisons between:

1. Three groups at the Post-intervention period (by using the Kruskal-Wallis rank tests);

2. Pre- and Post-intervention periods in the Database-control group (by using the

Wilcoxon Signed Rank tests); and

3. Pre- and Post- intervention periods in the Self-hypnosis and Johrei groups (by using

the Wilcoxon Signed Rank tests) [Table 43 and Figure 44].

Table 43: Mean (95% C.I.) CD4 gradients in HIV-individuals in the Self-hypnosis, Johrei and Database-

control groups at the Pre-intervention and Post-intervention periods CD4 gradient (cells per �l per month)


Self-hypnosis Johrei Controls Self-hypnosis Johrei Controls Mean

(95% C.I.) - 7

(-10 to -3) - 9

(- 14 to - 4) - 5

(- 8 to - 3) - 1

(- 4 to + 3) + 3

(- 2 to + 7) - 2

(- 5 to + 1) N 27 19 49 27 19 49

Self-hypnosis Johrei Database control

-30

-20

-10

0

10

20

30

Mean

(95%

C.I.)

CD4

grad

ients

(cells

/mcl/

month

) PrePost

Figure 44: Means (95% C.I.) CD4 gradients (count per �l per month)

in the Self-hypnosis and Johrei and Database-control groups in the Pre- and Post- intervention periods

p = 0.040

Not significant Not significant

Not significant

Not significant



The CD4 gradients of the individuals in the Database-control group showed a declining

trend in both the Pre-intervention and the Post-intervention periods (z = -1.5, df = 48, ns). In

contrast, the declining trend at the Pre-intervention period was halted and reversed in the Johrei

group at the Post-intervention period (z = - 2.1, df = 18, two-tailed p = 0.040), while patients in

the Self-hypnosis group continued to show a declining trend (z = - 1.1, df = 26, ns). Surprisingly,

however, there was no statistically significant difference between the psychological

interventions and Database-control in CD4 gradients at the 12 month of the Post-intervention

period (Self-hypnosis vs. Database-control: t = 0.2, df = 75, ns; Johrei vs. Database-control: t =

1.0, df = 67, ns).

Summary:

The results support the previous findings that there is a steady decline in peripheral blood

CD4 T-cell counts in HIV-infected individuals (not receiving anti-retroviral treatment); and that

the decline of CD4 T-cell counts appeared to be decreased or alleviated by the training and

practice of Johrei, but not by Self-hypnosis. Hence, it was suggested that learning and practising

Johrei may have improved disease progression in HIV-infected individuals.




Natural Killer cells

Background

NK-cells are important cellular components of the innate immune system in defence

against infection and malignancy, and they are known to be affected by stress as shown in

previous study [3.1.2] and in the literature [Segerstrom & Miller, 2004]. Pharmacological levels

of exogenous glucocorticoids are known to suppress inflammation in vivo and to suppress NK

cytotoxic activity in vitro [Zhou et al., 1997].

In this series of in vitro experiments, the effects of exposure to the major stress hormone,

cortisol, and other stress hormones (DHEA-S and melatonin), particularly within physiological

levels, on NK-cells were examined.

Aims

A. To confirm the suppressive effect of a major stress hormone, cortisol, upon NK

cytotoxic activity (NKCA), and to explore the underlying mechanisms at the cellular

level.

B. To examine the relationships between other endogenous stress associated hormones,

DHEA-S and melatonin, upon NKCA.

Working hypothesis

“An in vitro model of sustained stress impairs NK cytotoxic activity.”

In vitro model of sustained stress is defined as “more than 24 hours of exposure to upper

physiological levels of cortisol” .

3.3.1 Development and optimisation of a flow cytometric method for measuring NKCA

3.3.1.1 NKCA after incubation of PBMCs for 24 hours

To investigate the effect of cortisol upon NK-cells, PBMCs were cultured for 24 hours

with cortisol. Therefore this experiment was designed to determine if incubation itself of

peripheral blood mononuclear cells (PBMCs) had an effect upon NK cytotoxic activity (NKCA).



NKCA (50:1 ratio)

0

10

20

30

40

50

60

Time 0 24hrs

The flow cytometry method was used. PBMCs from 12 healthy subjects were incubated for 24

hours prior to assessing the NKCA.

Figure 45a and Figure 45b show mean (95% C.I.) and individual levels of NKCA pre and

post incubation for 24 hours. NKCA levels were increased in six individuals, decreased in three

and stayed the same in three. The repeated measures ANOVA showed a trend towards increased

levels of the NKCA (F = 4.3, df = 11, p = 0.063) when PBMCs were incubated in vitro for 24

hours.

1212N =

24hrsTime 0

NK

CA

leve

ls (

95

% C

.I.)

by

flow

cyto

met

ry

60

50

40

30

20

10

0

Figure 45a: Individual NKCA levels at Figure 45b: Mean (95% C.I.) NKCA levels

Time 0 and after 24hour incubation at Time 0 and after 24hour incubation

Conclusion:

The levels of the NKCA of PBMCs after 24 hours in vitro incubation showed a trend

towards increased levels compared with Time 0, but that the increase was short of statistical

significant.

3.3.1.2 NK-cell percentage in PBMCs after 24 hours incubation

Having shown that incubation of PBMCs for 24 hours resulted in a trend towards an

increase in NK cytotoxic activity, this experiment was performed to determine if this was

associated with an increase in total NK-cell percentage, perhaps due to adherence or loss by

selective cell death of other sub-populations of PBMCs.

Lymphocyte sub-populations within PBMCs were analysed by flow-cytometry performed

prior to and after 24 hours culture.

Indi

vid

ual N

KC

A le

vels

(%

kill

ing

at E

:T r

atio

= 5

0:1)

p = 0.063



CD56 NK cell%

0

5

10

15

20

25

30

Time 0 24hrs

Figure 46a shows that there was no consistent change in individual levels of total NK-cell

percentages in PBMCs after 24hrs in vitro incubation, i.e. five increased, four decreased and

three stayed the same regardless of their NKCA changes. Figure 46b shows that there was no

significant difference in the mean percentage of NK-cells after 24hrs incubation.

1212N =

24hrsTime0

CD

56 N

K c

ell%

(95%

C.I.

)

30

20

10

0

Figure 46a: Individual NK-cell percentage Figure 46b: Mean (95% C.I.) NK-cell percentage in PBMCs at Time 0 and after 24hours in PBMCs at Time 0 and after 24hours

Conclusion:

The trend towards an increase in NK cytotoxic activity in PBMCs after 24 hours

incubation was not associated with an increase in the percentage of NK-cells.

Indi

vid

ual N

K-c

ell

perc

ent

age

s in

PB

MC

s



NKCA (50:1 ratio)

0

10

20

30

40

50

60

0 nM 250nM 2500nM

3.3.1.3 NKCA after 24hrs incubation of PBMCs with cortisol

The aim of this experiment was to examine the effect of 24 hours of incubation of PBMCs

with cortisol at physiological and higher levels of NKCA. PBMCs were incubated with two

concentrations (250nM and 2500nM) of cortisol for 24 hours and NKCA was measured by

flow-cytometry. Due to technical problems, one sample from one volunteer was lost to the study,

so that results from 11 samples were analysed.

Figure 47a shows in each individual the effect of exposure of PBMCs to cortisol (250 and

2500nM) on the levels of the NKCA. Figure 47b shows a decrease in the mean level of the

NKCA when cortisol was present. The repeated measure ANOVA showed a significant

decrease in the levels of NKCA with cortisol concentration (F = 10.50 df = 10, p = 0.009). This

decrease was confirmed by post-hoc paired t-test comparisons (mean difference = 6.06, standard

error = 1.74, p = 0.018: between the NKCA with 0nM and with 250nM; and mean difference =

7.02, standard error, 2.17, p = 0.027: between the NKCA with 0nM and with 2500nM). There

was no significant difference between NKCA with 250nM and 2500nM.

2500 nM250 nM0 nM

NK

CA

leve

ls (

95

% C

.I.)

by

flow

cyto

met

ry

60

50

40

30

20

10

Figure 47a: Individual NKCA levels with cortisol Figure 47b: Mean (95% C.I.) NKCA levels at 0nM, 250nM, and 2500nM with cortisol at 0nM, 250nM, and 2500nM

Conclusion:

The incubation of PBMCs with 250nM or more cortisol for 24 hours had a suppressing

effect upon NKCA.

Indi

vid

ual N

KC

A (

% k

illin

g a

t E:T

ra

tio =

50:

1)

p = 0.018

p = 0.027



CD56 NK cell%

0

5

10

15

20

25

30

0 nM 250nM 2500nM

3.3.1.4 NK-cell percentage in PBMCs after 24 hours incubation with cortisol

Having shown that cortisol at 250nM or more had a suppressive effect upon NKCA, this

experiment was performed to determine if this suppressive effect was associated with a change

in the percentage of NK-cells in the PBMCs. NK-cells within PBMCs were analysed by flow-

cytometry, performed after 24 hours incubation with two cortisol concentrations (0nM, 250nM

and 2500nM).

There were no significant differences in the NK-cell percentage in the PBMCs after 24hrs

in vitro incubation with cortisol (0nM, 250nM and 2500nM). Figure 48a and Figure 48b show

individual and means levels of total NK-cell percentages in the PBMCs, respectively.

121212N =

2500 nM cortisol250 nM0 nM

CD

56 N

K c

ell%

(95%

C.I.)

30

20

10

0

Figure 48a: Individual NK-cell percentage Figure 48b: Mean (95% C.I.) NK-cell percentages with cortisol at 0nM, 250nM, and 2500nM with cortisol at 0nM, 250nM, and 2500nM

Conclusion:

The cortisol associated suppression of NKCA in PBMCs was not associated with a

change in NK-cell percentage.

Indi

vid

ual N

K-c

ell

perc

ent

age

s



3.3.2 Comparison of two methods for measuring NK cytotoxic activity (NKCA):

- the flow cytometric method and the colorimetric method (CytoTox96®) -

The flow cytometric method of assessing NK cytotoxic activity [Godoy-Ramirez et al.,

2000] was initially adopted to avoid the conventional radio-active 51Cr-release assay. However,

the flow cytometric method is laborious and requires a high degree of skill. A simpler

colorimetric method, namely the CytoTox96®, has been developed [Promega, 2004]. This

method measures levels of released lactic dehydrogenase (LDH) from killed K562 cells. The

amount of LDH is proportional to the numbers of killed K562 cells. The LDH level can be

accurately and simply measured colorimetrically.

The flow cytometric and the colorimetric assays were compared in this experiment.

PBMCs were separated from 45 healthy individuals and NKCA analysed, in parallel, by both

the flow-cytometric and the colorimetric methods.

Figure 49 shows the scatter graph of the correlation between the two methods. The

Pearson correlation analysis shows that there is a significant correlation between the two

methods (r = 0.367, 2-tailed p = 0.013).

NKCA by flowcytometry assay

6050403020100

NKCA b

y Cyt

oTox

(LDH) ass

ay

60

50

40

30

20

10

0 Rsq = 0.1349

Figure 49: Correlation between flow-cytometry method and LDH-releasing method of the NKCA

Conclusion:

It was determined that the levels of the NKCA should be measured by the less laborious

but still valid colorimetric method in subsequent experiments and to repeat the previous

experiments with a larger sample size to confirm the previous findings.

p = 0.013 n = 45 r = 0.367



Time course of NKCA 50:1

0

10

20

30

40

50

Time 0 24 hours incubation

3.3.3 Investigation of NK-cell profiles and NKCA (colorimetric method)

The flow cytometric assessment of NKCA showed that incubation of PBMCs for 24 hours

resulted in increased NK cytotoxicity. This repeat experiment was performed with PBMCs from

a larger number of volunteers using the colorimetric method with the objective of confirming

these results.

3.3.3.1 NKCA, assessed by colorimetric method, after incubation of PBMCs for 24 hours

PBMCs were obtained from 31 healthy subjects and incubated for 24 hours prior to

assessing the NKCA at effector: target ratios of 50:1 and 25:1 by the colorimetric assay.

Individual and mean (95% C.I.) NKCA levels with effector: target ratios of 50:1 and 25:1

pre and post incubation are shown in Figure 50 (a), (b) and Figure 51 (a), (b), respectively. In

agreement with previous findings, there was a significant increase in the mean NKCA level

after incubating PBMCs for 24 hours. The repeated measure ANOVA shows that the levels of

NKCA were increased after 24hrs incubation in a 50:1 ratio (mean difference = 6.38 (15.67 to

22.05), sd = 14.9, p = 0.024, t = 2.38, df = 30) and 25:1 ratio (mean difference = 10.47 (8.78 to

19.25), sd = 11.1, p < 0.001, t = 5.32, df = 30).

Time 0 After 24hours

0

10

20

30

40

Mea

n (9

5% C

.I.)

NK

CA

leve

ls a

t E:T

= 5

0:1

Figure 50a: Individual NKCA (50:1) levels Figure 50b: Mean (95% C.I.) NKCA (50:1) levels (% killing) at Time 0 and after 24hrs incubation (% killing) at Time 0 and after 24hrs incubation

Indi

vid

ual N

KC

A (

% k

illin

g a

t E:T

ra

tio =

50:

1)

p = 0.024



Time course of NKCA 25:1

0

10

20

30

40

50

Time 0 24 hours incubation Time 0 After 24hours

0

10

20

30

40

Mea

n (9

5% C

.I.)

NK

CA

leve

ls a

t E:T

= 2

5:1

Figure 51a: Individual NKCA (25:1) levels Figure 51b: Mean (95% C.I.) NKCA (25:1) levels (% killing) at Time 0 and after 24hrs incubation (% killing) at Time 0 and after 24hrs incubation

Conclusion:

The colorimetric assay results confirmed previous flow cytometric findings that

incubation of PBMCs for 24 hours leads to a significant increase in the levels of NKCA.

3.3.3.2 Repeat assessment of NK-cell percentage and examination of NK subpopulations in

PBMCs after 24 hours incubation

Although previous results showed no association between the increase in NKCA after 24

hours incubation of PBMCs and NK-cell (CD3-CD56+) percentages, the association was re-

examined pre and post 24 hours incubation with this increased number of subjects. In addition,

the distribution of NK cells according to the level of expression of CD56 and CD16 was

examined. The level of expression of these markers can be used to define cytotoxic and

regulatory NK-cells. However, due to technical problems with the flow cytometer, only the last

16 subjects from the above 31 were analysed.

Figure 52 (a), (b) and (c) show mean (95% C.I.) percentages of NK-cells (CD3-CD56+)

with subpopulations of cytotoxic NK-cells (CD3-CD56dimCD16+) and regulatory NK-cell (CD3-

CD56brightCD16-) in the PBMCs at Time 0 and after 24hrs incubation, respectively. There were

no significant differences in NK-cell profiles between Time 0 and 24hrs after incubation.

Indi

vid

ual N

KC

A (

% k

illin

g a

t E:T

ra

tio =

25:

1) p < 0.001



1616N =

Incubated 24hrsTime 0

To

tal C

D56

+ N

K c

ell%

in P

BM

Cs

40

30

20

10

0

1616N =

Incubated 24hrsTime0

Cyt

oto

xic

NK

(C

D56d

im)%

in P

BM

Cs 40

30

20

10

0

1616N =

Incubated 24hrsTime 0

Reg

ula

tory

NK

(C

D5

6b

righ

t) c

ells

% in

PB

40

30

20

10

0

Figure 52a: NK (%) in PBMCs Figure 52b: Cytotoxic NK (%) Figure 52c: Regulatory NK (%) at Time 0 and after 24hrs at Time 0 and after 24hrs at Time 0 and after 24hrs

Figure 52: Percentages of NK-cell in total and each subset at Time 0 and after 24 hours incubation

Conclusion:

The increase in NK cytotoxic activity in PBMCs after 24 hours incubation was not

associated with increases in the percentage of NK-cells or alteration in the cytotoxic / regulatory

NK-cell subpopulations.

3.3.3.3 Expression of Natural Cytotoxic Receptors (Nkp46 and Nkp30) by cytotoxic NK-cells

(CD3-CD56dimCD16+) pre and post 24hours incubation

Having shown that the increase in NKCA in PBMCs after 24 hours incubation was not

associated with increases in the percentage of total NK-cells or cytotoxic and regulatory NK-

cells, this experiment was performed to determine if the increase in NKCA was associated with

an increase in the expression of the Natural Cytotoxic Receptors (Nkp46 and Nkp30) on the

cytotoxic NK-cells. The expression (mean florescent intensity: m.f.i.) of the Nkp46 (major

cytotoxic receptor) on cytotoxic NK (CD3-CD56dimCD16+) cells within PBMCs from the same

16 healthy subjects were analysed by flow-cytometry performed prior to culture and after 24

hours.

Figure 53 (a) and (b) show that there was a significant increase (+44%) in the expression

of the Nkp46 on cytotoxic NK-cells after 24hrs in vitro incubation (Repeated measures

ANOVA: F = 38.1, p < 0.001, n = 16; mean difference = 27.0, se = 4.4). Figure 54 (a) and (b)

show that there was a significant decrease (-22%) in the expression of the Nkp30 on cytotoxic

NK-cells after 24hrs in vitro incubation (F = 18.0, p = 0.001, n = 16; mean difference = 5.4, se =

1.3).



Nkp46 m.f.i. on Cytotoxic NK cells

0

20

40

60

80

100

120

140

Time 0 24hrs

1616N =

24hrsTime0N

kp4

6 m

.f.i.

on

Cyt

oto

xic

NK

cel

ls

125

100

75

50

25

0

Figure 53a: Individual Nkp46 (m.f.i.) Figure 53b: Mean (95% C.I.) Nkp46 (m.f.i.) at Time 0 and after 24hrs incubation at Time 0 and after 24hrs incubation


0

20

40

60

80

100

120

140

Time 0 24hrs

1616N =

24hrsTime 0

Nkp

30

m.f.

i. o

n C

yto

toxi

c N

K c

ells

125

100

75

50

25

0

Figure 54a: Individual Nkp30 (m.f.i.) Figure 54b: Mean (95% C.I.) Nkp30 (m.f.i.) at Time 0 and after 24hrs incubation at Time 0 and after 24hrs incubation

Conclusion:

These results show that the increase in NKCA in PBMCs after 24 hours incubation was

associated with an increase in the expression of Nkp46 on cytotoxic NK-cells, and it was also

associated with a decrease in the expression of Nkp30 although the amplitude of this decrease

was small.

Nkp

46 m

.f.i.

on

Cyt

otox

ic N

K-ce

lls

Nkp

30 m

.f.i.

on

Cyt

otox

ic N

K-ce

lls

p < 0.001

p = 0.001



3.3.3.4 NKCA, assessed by colorimetric method, after 24 hours incubation of PBMCs with

250nM cortisol

This experiment aimed to confirm the results from the previous experiment 3.3.2.3 by

using a colorimetric method with a larger number of subjects, i.e. to determine if 24hrs

incubation of PBMCs with 250nM cortisol inhibits an increase in the levels of the NKCA.

PBMCs from 31 healthy subjects were incubated for 24 hours with or without 250nM

cortisol prior to assessing the NKCA by the colorimetric method at effector: target ratios of both

50:1 and 25:1.

Individual (a) and mean (b) NKCA levels after exposure of PBMCs to cortisol are shown

in Figure 55 (a), (b) and 56 (a), (b). As previously found, there was a significant reduction

following exposure of PBMCs to 250nM of cortisol in the mean NKCA levels at effector: target

ratio = 50:1 (mean difference = 6.69, SD = 6.9, p < 0.001, t = 5.41, df = 30) and 25:1 (mean

difference = 9.73, SD = 8.1, p < 0.001, t =6.66, df = 30), respectively [Figure 55b and Figure

56b].

NKCC % (LDH assay) 50:1

0

10

20

30

40

50

Without drug Cortisol 250 nM

3131N =

250nM cortisol0nM

NK

CA

leve

ls (

95

% C

.I.)

50

:1 r

atio

40

30

20

10

0

Figure 55a: Individual NKCA (50:1) levels Figure 55b: Mean (95% C.I.) NKCA (50:1) levels (% killing) of PBMCs incubated (% killing) of PBMCs incubated with or without cortisol with or without cortisol

Indi

vidu

al N

KC

A (

% k

illin

g at

E:T

rat

io =

50:

1)

p < 0.001



NKCC % (LDH assay) 25:1

0

10

20

30

40

50

Without drug Cortisol 250 nM

3131N =

250nM cortisol0nMN

KC

A le

vels

(9

5%

C.I.

) 2

5:1

rat

io

40

30

20

10

0

Figure 56a: Individual NKCA (25:1) levels Figure 56b: Mean (95% C.I.) NKCA (25:1) levels (% killing) of PBMCs incubated (% killing) of PBMCs incubated with or without cortisol with or without cortisol

Conclusion:

Incubation of PBMCs for 24 hours with cortisol (250nM) causes an inhibition of NKCA.

3.3.3.5 NKCA levels between pre and post 24 hours incubation with or without 250nM cortisol

Having shown that there was an increase in the levels of NKCA (p < 0.001, n = 31)

following in vitro culture of PBMCs for 24 hours; and that the addition of 250nM cortisol to the

culture medium inhibited this rise (p < 0.001, n = 31), the association between these degree of

the increases and the inhibition were analysed.

The independent t-tests showed that the NKCA levels of the PBMCs before 24 hours

incubation were not different from the levels of PBMCs after 24 hours of incubation with

250nM cortisol [Figure 57].

Indi

vidu

al N

KC

A (

% k

illin

g at

E:T

rat

io =

25:

1)

p < 0.001



313131N =

24hrs Cortisol24hrs No drugTime 0

NKC

A 2

5:1

ratio

(95%

C. I.)

30

20

10

0

Figure 57: Mean (95% C.I.) of the NKCA at Time 0 and after 24hrs incubation of PBMCs

with/out 250nM cortisol in the target: effector ratio of 25:1

Conclusion

The degrees of an increase in NKCA level after 24 hours of incubation and an inhibition

of this increase in NKCA of the PBMCs incubated with 250nM cortisol are statistically the

same.

This finding was also confirmed by correlation analyses, in which the association between

time changes (after 24 hours incubation without cortisol - Time 0) and differences (after 24

hours incubation without cortisol – with cortisol) both at the ratio of 50:1 (p = 0.042, r = 0.37, n

= 31) and 25:1 (p < 0.001, r = 0.72, n = 31) [Figure 58].

Reduction of NKCA 25:1 (No-drug - Cortisol)

3020100-10-20-30

Increase

in N

KCA 2

5:1

(24h - T

ime 0

)

40

30

20

10

0

-10 Rsq = 0.5220

Figure 58: Correlations between the changes and differences of the NKCA (% killing: between at Time 0 and after 24hrs incubation of PBMCs with/out 250nM cortisol in the ratio of 25:1)

p < 0.001 n = 31 r = 0.72

p < 0.001 p < 0.001

Not significant



Conclusion:

The degree of inhibition in the NKCA by the in vitro exposure to the 250nM cortisol was

almost the same degree of increase in the levels of NKCA after 24 hours in vitro incubation of

PBMCs.

3.3.3.6 CD56 NK-cell subset profiles in PBMCs after 24 hours incubation with 250nM cortisol

Having confirmed in the larger cohort of subjects that 24 hours incubation with cortisol

inhibited NKCA, the experiment to determine if this was due to a change in NK-cell percentage

was repeated. In addition, NK-cell subset profiles (percentages of cytotoxic and regulatory NK-

cells within the PBMC) were examined. Due to technical problems in flow cytometer, only the

last 16 subjects from the above 31 subjects were analysed.

Figure 59 (a), (b) and (c) show (a) mean (95% C.I.) percentages of NK-cell (CD3-CD56+),

(b) cytotoxic NK-cell (CD3-CD56dimCD16+) and (c) regulatory NK-cell (CD3-CD56brightCD16-)

in the PBMCs after 24hours incubation with and without 250nM cortisol, respectively. As found

previously, there were no significant differences in NK-cell percentages and subpopulations in

PBMCs after 24hrs incubation with and without 250nM cortisol.

1616N =

CortisolNo drug

To

tal N

K (

CD

56)

cell%

in P

BM

Cs

40

30

20

10

0

1616N =

CortisolNo drug

Cyt

oto

xic

NK

(C

D5

6d

im)

cell%

in P

BM

Cs

40

30

20

10

0

1616N =

CortisolNo drug

Reg

ula

tory

NK

(C

D5

6b

righ

t) c

ell%

in P

BM

40

30

20

10

0

Figure 59a: NK (%) in the PBMCs Figure 59b: Cytotoxic NK (%) Figure 59c: Regulatory NK (%) after 24hrs with/out cortisol after 24hrs with/out cortisol after 24hrs with/out cortisol

Figure 59: Percentages of NK-cell in total and each subset in the PBMCs after 24hours incubation with and without 250nM cortisol

Conclusion:

The cortisol associated suppression of NKCA in PBMCs after 24 hours incubation was

not associated with a change in NK-cell profiles.

NK

-cel

ls (%

) in

PB

MC

s



3.3.3.7 Expression of Natural Cytotoxic Receptors (Nkp46 and Nkp30) by cytotoxic NK-cells

(CD3-CD56dimCD16+) after 24hours incubation with or without 250nM cortisol

Having shown that the inhibition of an increase in NKCA in PBMCs after 24 hours

incubation with 250nM cortisol was not associated with changes in the percentage distributions

of total or cytotoxic NK-cells, this experiment was performed to determine if the cortisol

induced inhibition was associated with the expression of the major cytotoxic receptor on

cytotoxic NK-cells. In experiment 3.3.4.3, this was shown to be increased after 24 hours

incubation.

The expression (mean florescent intensity: m.f.i.) of the Nkp46 and the Nkp30 on

cytotoxic NK (CD3-CD56dimCD16+) cells within PBMCs from 16 healthy subjects were

analysed by flow-cytometry performed after 24 hours incubation with or without 250nM

cortisol.

Figure 60 (a) and (b) show that there was a significant inhibition of an increase in the

expression of the Nkp46 on cytotoxic NK-cells after 24hrs in vitro incubation (Repeated

measures ANOVA: F = 58.4, p < 0.001, n = 16; mean difference = 13.3, se = 1.7). Figure 61 (a)

and (b) shows that there was a significant, but slight decrease in the expression of the Nkp30 on

cytotoxic NK-cells after 24hrs in vitro incubation (F = 13.2, p = 0.002, n = 16; mean difference

= 2.3, se = 0.6).


0

20

40

60

80

100

120

140

No drug Cortisol

1616N =

cortisolNo drug

Nkp

46

m.f

.i. o

n C

yto

toxi

c N

K c

ells

125

100

75

50

25

0

Figure 60a: Mean (95% C.I.) Nkp46 (m.f.i.) Figure 60b: Individual Nkp46 (m.f.i.) after

after 24hrs incubation of PBMCs with/out cortisol 24hrs incubation of PBMCs with/out cortisol

p < 0.001




0

20

40

60

80

100

120

140

No drug Cortisol

1616N =

cortisolNo drug

Nkp

30

m.f

.i. o

n C

yto

toxi

c N

K c

ells

125

100

75

50

25

0

Figure 61a: Mean (95% C.I.) Nkp30 (m.f.i.) Figure 61b: The individual Nkp30 (m.f.i.) after

after 24hrs incubation of PBMCs with/out cortisol 24hrs incubation of PBMCs with/out cortisol

Conclusion:

These results suggest that the inhibition of an increase in NKCA in PBMCs after 24 hours

incubation with cortisol was associated with an inhibition of an increase in the expression of

Nkp46 on cytotoxic NK-cells.

3.3.3.8 Nkp46 expression on cytotoxic NK-cells pre and post 24 hours incubation with or

without 250nM cortisol

Having shown that there was an increase in the expressions of Nkp46 (m.f.i.) on the

cytotoxic NK-cells (p < 0.001, n = 16) following in vitro culture of PBMCs for 24 hours; and

that the additive of 250nM cortisol to the culture medium inhibited this increase, the degree of

these increases and the inhibition were analysed. The independent t-tests showed that the

expression of Nkp46 (m.f.i.) on cytotoxic NK-cells before 24 hours incubation were lower than

that on cytotoxic NK-cells after 24 hours of incubation with 250nM cortisol [Figure 62].

p = 0.002



161616N =

24hrs cortisol24hrs No drugTime0

Nkp

46 m

.f.i.

on C

ytoto

xic

NK c

ells

125

100

75

50

25

0

Figure 62: Mean (95% C.I.) and individual expression of Nkp46 (m.f.i.) on the cytotoxic NK-cells

(CD56dimCD16+) at Time 0 and after 24hrs incubation of PBMCs with/out 250nM cortisol

Conclusion:

Although there was an increase in the expressions of Nkp46 (m.f.i.) on the cytotoxic NK-

cells following 24 hours incubation, the addition of 250nM cortisol inhibited this rise. This

inhibition did not reach complete suppression.

3.3.3.9 NKCA and Nkp46 expression on cytotoxic NK-cells pre and post 24 hours incubation

with or without 250nM cortisol

Having the discrepancy between the changes in NKCA levels and changes in the Nkp46

expression pre- and post- 24 hours incubation with or without 250nM cortisol, the same 16

volunteers whose Nkp46 were examined out of the 31 subjects were re-analysed according to

their levels of NKCA. A trend of changes that were similar to the results in Nkp46 analyses was

obtained in this analysis of NKCA levels. Although there was an increase in the levels of

NKCA (p < 0.001) following in vitro culture of PBMCs for 24 hours, and the addition of

250nM cortisol to the culture medium inhibited this rise, this inhibition did not reach complete

suppression [Figure 63].

p < 0.001 p < 0.001

p < 0.001



161616N =

24hrs cortisol24hrs No drugTime 0

Means

(95%

C.I.

) of N

KCA in

25:1

ratio

40

30

20

10

0

Figure 63: Mean (95% C.I.) and individual level of NKCA at Time 0 and after 24hrs incubation of PBMCs with/out 250nM cortisol at target: effector ratio of 25:1

Conclusion:

The inhibition of an increase in NKCA levels after 24hrs in vitro incubation with 250nM

cortisol has association with the inhibition of an increase in Nkp46 on cytotoxic NK-cells after

the 24hrs incubation.

3.3.4 Endogenous stress hormone levels and NKCA (colorimetric method)

Having shown that exposure of PBMCs to exogenous cortisol for 24 hours appeared to

block the culture associated rise in the levels of NKCA, the levels of endogenous cortisol in the

plasma of subjects was measured to determine if prior in vivo exposure affected NKCA levels.

In addition, the plasma levels of DHEA-S and melatonin were also measured in order to

examine the hypothesis that prior in vivo exposure to either of them is associated with NKCA

levels. The plasmas from the separated PBMCs were analysed to measure endogenous levels of

cortisol, DHEA-S and melatonin by ELISA assays. Correlation analyses between endogenous

levels of stress-associated hormones (cortisol, DHEA-S and melatonin) and NKCA levels were

used to test the hypothesis.

p < 0.001 p = 0.001

p = 0.012



3.3.4.1 Endogenous hormone levels and NKCA at Time 0 point

At Time 0 point, there was no significant correlation between endogenous cortisol levels

and NKCA levels at both analyses ratios of 50:1 (r = .09, n = 31, ns) and 25:1 (r = - .01, n = 31

ns). DHEA-S levels, on the other hand, had a significant positive correlation with NKCA levels

but only at the ratio of 25:1 (r = .38, n = 31, p = 0.03), and not with the levels at the ratio of 50:1

(r = .19, n = 31, ns). No significant correlation between endogenous melatonin levels and

NKCA levels at the ratio of 50:1 (r = - .09, n = 31, ns) and 25:1 (r = - .03, n = 31, ns) was found

at Time 0 point.

Conclusion:

These results suggest that prior in vivo exposure to cortisol or melatonin did not affect

NKCA levels at the Time 0 point, although there is still a possibility that prior in vivo exposures

to DHEA-S may be positively associated with NKCA levels at Time 0 point.

3.3.4.2 Endogenous hormones levels and the increased levels of NKCA after 24 hours in vitro

incubation of PBMCs without exogenous cortisol

The results from previous experiment [3.3.4] showed that there were individual

differences in the levels of NKCA after 24 hours incubation without exogenous cortisol, i.e.

some of them had high levels of NKCA and the others had low levels. Individuals were divided

into three groups (high, middle and low NKCA levels) according to averaged NKCA levels at

the ratio of 50:1 and 25:1 after 24 hours incubation without cortisol [Figure 64].

Figure 64: Groups defined by tertiary split of the NKCA levels after 24 hours incubation

NKCA after 24hrs incubation

0

15

30

45

Group of individuals with low levels of the NKCA (Low NKCA : mean = 7.1, SD = 4.8, n = 11)

Group of individuals with high levels of the NKCA (High NKCA : mean = 34.2, SD = 6.8, n = 11)

Group of individuals with middle levels of the NKCA (Mid NKCA : mean = 20.6, SD = 3.3, n = 9)



The group of people with high levels of the NKCA in the tertiary splits (High NKCA:

mean = 34.2, SD = 6.8, n = 11/31) and the group of people who have low levels (Low NKCA:

mean = 7.1, SD = 4.8, n = 11/31) were compared with regard to the levels of their endogenous

hormones by independent t-tests. In addition, correlation analyses were performed to examine

the associations between endogenous hormones levels and the increased levels of NKCA after

24 hours incubation.

Cortisol levels

Endogenous plasma levels of cortisol had no significant correlation with the levels of the

NKCA both at the ratio of 50:1 (r = .09, n = 31, ns) and 25:1 (r = .02, n = 31, ns), and no

statistically significant difference in means between the High NKCA group and the Low NKCA

group was found [Figure 65].

Low NKCA individuals

Mid NKCA individuals

High NKCA individuals

0

50

100

150

200

Mea

n (9

5% C

.I.) p

lasm

a co

rtiso

l leve

ls (n

M)

Figure 65: Mean (95% C.I.) plasma levels of cortisol in the High, intermediate (Mid) and Low NKCA level groups after 24 hours incubation

DHEA-S levels

Endogenous plasma levels of DHEA-S appeared to be positively associated with NKCA

levels both at the ratio of 50:1 (r = .38, n = 31, p = 0.037) and 25:1 (r = .37, n = 31, p = 0.038),

and the High NKCA group had significantly higher levels of DHEA-S compared with the levels

of the Low NKCA group [Figure 66] (mean difference = 1.6, t = 2.1, df = 20, p = 0.045).

Not significant






0

1

2

3

4

5

Mea

n (9

5% C

.I.) p

lasm

a D

HEA

-S le

vels

(mg/

dl)

Figure 66: Mean (95% C.I.) plasma levels of DHEA-S in the High, intermediate (Mid) and Low NKCA level groups after 24 hours incubation

Melatonin levels

Endogenous plasma levels of melatonin appeared to be positively associated with NKCA

levels both at the ratio of 50:1 (r = .42, n = 31, p = 0.020) and 25:1 (r = .38, n = 31, p = 0.038).

Moreover, the High NKCA group had significantly higher levels of melatonin compared with

the levels of the Low NKCA group [Figure 67] (mean difference = 15.2, t = 3.2, df = 20, p =

0.010).

In addition, endogenous plasma levels of melatonin showed significant correlations with

the increased levels of the NKCA after 24 hours from Time 0 time point at the ratio of 50:1 (r

= .47, n = 31, p = 0.008) and 25:1 (r = .42, n = 31, p = 0.019).

p = 0.045






0

10

20

30

40

Mea

n (9

5% C

.I.) p

lasm

a m

elat

onin

leve

ls (p

g/m

L)

Figure 67: Mean (95% C.I.) plasma levels of melatonin in the High, intermediate (Mid) and Low NKCA level groups after 24 hours incubation

Conclusion:

These results suggest that prior in vivo exposure to cortisol did not affect NKCA levels,

but that prior in vivo exposures to DHEA-S and melatonin were associated with the increased

levels of NKCA after 24 hours in vitro incubation.

Summary:

These results confirm, by the flow-cytometry and colorimetric methods that the levels of

the NKCA after incubation of PBMCs for 24 hours increased. There were no changes in NK-

cell and cytotoxic NK-cell percentages after the 24 hours incubation of PBMCs, but the

expression of the Nkp46 receptor was shown to increase while the expression of the Nkp30 was

not affected significantly. The increase of NKCA levels after 24 hours incubation was shown to

be associated with the increase in Nkp46 expression.

Upper physiological levels of cortisol (250nM), in vitro stress model, were shown to

inhibit the increase of NKCA seen after 24hrs incubation. The degree of inhibition in the NKCA

by the 250nM cortisol was almost to the same degree of increase in the levels of NKCA after 24

hours incubation of PBMCs. This inhibition in the NKCA level was not associated with a

numerical change in the levels of NK-cells and the cytotoxic NK-cell sub-population, but the

p = 0.037



inhibition was shown to be associated with inhibition of Nkp46 expression (m.f.i.) on cytotoxic

NK-cell subsets. However, the degree of inhibition of Nkp46 expression did not fully match the

suppression of the increase after 24 hours incubation. This finding implies that there are other

contributing factors apart from the Nkp46 expression.

The analyses in associations between endogenous levels of stress-hormones (cortisol,

dehydroepiandrosterone sulphate (DHEA-S) and melatonin) and NKCA levels at Time 0, i.e.

before the incubation of PBMCs, demonstrated that there were no significant relationships.

However, there appeared to be positive correlations between endogenous levels of DHEA-S and

melatonin, but not cortisol, and the NKCA levels after 24 hours of in vitro incubation, i.e. after

incubation without the presence of endogenous hormones. These results suggest that the levels

of prior in vivo exposure to DHEA-S and melatonin, but not cortisol, may have been positively

associated with the increased levels of NKCA after 24 hours in vitro incubation. Together with

the findings that the increased levels of NKCA were inhibited by the presence of upper

physiological levels of cortisol [3.3.1.3 and 3.3.3.4] and in the literature [1.2.2.3 and 1.2.4.2], it

was suggested that DHEA-S and melatonin may have affected to NK-cells in vivo as a counter

regulatory hormone against cortisol in NKCA levels.

These findings support the hypotheses that physiological levels of cortisol can suppress

NK cytotoxic activity directly; and that DHEA-S and melatonin may have counteracting effects

against cortisol upon the NK cytotoxic activity. This conclusion supports the premise that there

is a direct hormone-immunity linkage as an endocrino-immune arm of the proposed integrated

psycho-neuro-endocrino-immune network; and partially supports the hypothesis that stress may

have a detrimental effect upon health. This leads onto the next in vitro experiments examining

the effect of cortisol upon T-lymphocytes as an investigation of another direct hormone-

immunity linkage, i.e. linkage between cortisol and the adaptive immune system.



3.4 In vitro investigation into the effect of exposure to stress hormone upon T-

lymphocytes

Background

T-lymphocytes are important cellular components of the adaptive immune system, and

one of their major functions, proliferation (an increase of the specific cell types against specific

antigens) [see also 1.2.1.1] is known to be affected by the stress hormone, cortisol.

Pharmacological levels of exogenous glucocorticoids are known to suppress T-lymphocyte

proliferative activity in vitro. In this project, the effects of physiological levels of cortisol upon

T-lymphocytes were investigated by assessing proliferative responses against antigens and a

mitogen. The proliferation rate was assessed by using [3H]-thymidine incorporation method, and

later the expression of various cell surface receptors was examined by using flow-cytometry to

explore the profiles of T-lymphocyte sub-populations.

Aims

� To confirm the suppressive effect of a major stress hormone, cortisol, upon T-

lymphocyte proliferative responses, and to explore the underlying mechanisms at the

cellular level

Working hypothesis

“An in vitro model of sustained stress impairs T-lymphocyte proliferative activity.”

In vitro model of sustained stress is defined as “more than 24 hours of exposure to upper

physiological levels of cortisol” .

3.4.1 T-lymphocyte proliferative responses against common antigens

This series of experiments was designed to confirm the suppressive effect of cortisol upon

T-lymphocyte proliferation, and to explore the effect of cortisol at upper physiological levels.

When peripheral blood mononuclear cells (PBMCs) are incubated with previously

encountered antigens, memory T-lymphocytes are stimulated to divide leading to increased

incorporation of [3H]-thymidine. Under the culture conditions used, such cultures should give

radioactive counts in excess of 3,000 counts per minute (cpm).



6 day culture without antigen

0

1000

2000

3000

4000

0 nM 25 nM 250 nM 2500 nM

PBMCs from ten healthy subjects were incubated with or without antigens (purified

protein derivative (PPD) or Herpes zoster antigen) in various concentrations of cortisol (0, 25,

250 and 2500nM). All data were collected on the 6th day of incubation, and proliferative

responses were measured by the [3H]-thymidine incorporation method.

3.4.1.1 T-lymphocyte proliferation after incubation of PBMCs for six days with and without

exogenous cortisol

As expected, in vitro incubation of peripheral blood mononuclear cells (PBMCs) in tissue

culture medium (TCM) alone for six days did not cause lymphocyte proliferative responses

[Figure 68a, b]. Not surprisingly, the addition of various amounts of cortisol (upper

physiological levels: 250nM, 25nM and 2500nM) had no effect upon this result.

10101010N =

2500 nM250 nM25 nM0 nM

5000

4000

3000

2000

1000

0

Figure 68a: individual background proliferations of Figure 68b: mean background proliferation PBMCs cultured without antigen of PBMCs cultured without antigen

Indi

vid

ual 3 H

-thy

mid

ine

inco

rpor

atio

n pe

r P

BM

Cs

cultu

re w

ell

(cpm

)

Me

an

of 3 H

-thy

mid

ine

inco

rpor

atio

n pe

r P

BM

Cs

cultu

re w

ell

(cpm

)



Individual proliferation response to PPD

0

5000

10000

15000

20000

25000

30000

0 nM 25 nM 250 nM 2500 nM

3.4.1.2 T-lymphocyte proliferative response against purified protein derivative (PPD) after

incubation of PBMCs for six days with or without exogenous cortisol

PBMCs from nine volunteers out of ten responded satisfactoril y to in vitro stimulation

with mycobacterium antigen (purified protein derivative: PPD). Figure 69a shows the individual

responses from nine volunteers whose PBMCs responded satisfactorily to in vitro stimulation

with the PPD antigen and that all responses but one were reduced by the addition of 250nM

cortisol and all responses were suppressed by the addition of 2500nM cortisol. The addition of

cortisol induced a dose-dependent decrease in the amount of [3H]-thymidine incorporated (F =

34.95, p < 0.001) [Figure 69b]. Paired t-tests showed significant reductions from 0nM to 250nM

(t = 8604, p = 0.001), and from 0nM to 2500nM (t = 12017, p = 0.001)

9999N =

2500nM cortisol

250nM

25nM

No drug

Lym

phocy

te p

rolif

era

tive r

esp

onse

s to

PP

D

20000

15000

10000

5000

0

-5000

Figure 69a: individual proliferation response Figure 69b: Mean (95% C.I.) proliferation

of PBMCs to the PPD antigen responses of PBMCs to the PPD antigen

Conclusion:

Exogenous cortisol suppresses PPD-dependent T-lymphocyte proliferative responses, and

this can be seen at the upper physiological levels of cortisol, 250nM as well as 10 times higher

(2500nM).

Indi

vid

ual 3 H

-thy

mid

ine

inco

rpor

atio

n pe

r P

BM

Cs

cultu

re w

ell

(cpm

)

p = 0.001 p = 0.001



3.4.1.3 T-lymphocyte proliferative response against Herpes antigen after incubation of PBMCs

for six days with and without exogenous cortisol

Similar findings to those with PPD were obtained when a Herpes zoster antigen was used.

PBMCs from ten volunteers responded satisfactorily to in vitro stimulation with Herpes antigen.

Figure 70a shows individual responses from ten volunteers. All responses but one were reduced

by the addition of cortisol. The addition of cortisol induced a dose-dependent decrease in

proliferative responses measured by [3H]-thymidine incorporation (F = 15.96, p = 0.002)

[Figure 70b]. Post hoc paired t-test showed significant reductions from 0nM to 250nM (t = 9578,

p = 0.004), and from 0nM to 2500nM (t = 15386, p = 0.001).

Individual proliferation response to Herpes

0

10000

20000

30000

40000

50000

60000

70000

80000

0 nM 25 nM 250 nM 2500 nM

10101010N =

2500nM cortisol

250nM

25nM

No drugLym

ph

ocy

te p

rolif

era

tive

re

spo

nse

s to

He

rpe

s

60000

50000

40000

30000

20000

10000

0

Figure 70a: individual proliferation response of Figure 70b: Mean (95% C.I.) proliferation PBMCs to Herpes antigen responses of PBMCs to Herpes antigen

Conclusion:

Exogenous cortisol suppresses T-lymphocyte proliferative responses to memory antigens,

and this can be seen at the upper physiological levels of cortisol, 250nM as well as 10 times

higher (2500nM).

Me

an

3 H-t

hym

idin

e in

corp

ora

tion

per

PB

MC

s cu

lture

we

ll (c

pm)

p = 0.001 p = 0.004



3.4.2 T-lymphocyte proliferative responses against super-antigen and mitogen

Having shown that the addition of cortisol induced a dose dependent decrease in in vitro

antigen specific T-lymphocyte proliferative responses, this series of experiments was designed

to determine if concurrent exposure to cortisol (250nM) had similar effects following in vitro

stimulation with powerful pan T-cell stimulants, i.e. super-antigen - staphylococcal enterotoxin

B (SEB) and mitogen - phytohaemagglutinin A (PHA).

The number of cells particularly in the proliferative response to these SEB and PHA is

greater and the maximum response occurs earlier than for memory recall antigens. These

responses should give radioactive counts in excess of 10,000 counts per minute (cpm) on Day 3

of culture. With these more powerful stimuli, the assay was modified to use a whole blood

method rather than PBMCs which are time consuming to prepare.

Blood from twelve healthy subjects were diluted, one in four, with TCM and incubated

for three days with and without SEB and PHA, in the presence or absence of 250nM cortisol.

All data were collected on the third day of incubation.



Lymphocytes proliferative responsesto SEB

0

20000

40000

60000

80000

100000

120000

No drug Cortisol

3.4.2.1 T-lymphocyte proliferative responses against staphylococcal enterotoxin B (SEB) after

incubation of diluted whole blood for three days with or without exogenous cortisol

Lymphocytes in the diluted whole blood samples from twelve volunteers responded

satisfactorily to in vitro stimulation with staphylococcal enterotoxin B (SEB) [Figure 71a]. The

addition of 250nM cortisol induced a decreased response (mean difference = 18235, SD = 8672,

t = 7.3, df = 11, p < 0.001) [Figure 71b].

1212N =

CortisolNo drug

Pro

lifer

ativ

e re

spo

nse

s to

SE

B (

95

% C

. I.

)

100000

75000

50000

25000

0

Figure 71a: Individual proliferative Figure 71b: Mean (95% C.I.) proliferative

responses of PBMCs to the SEB responses of PBMCs to the SEB with/out cortisol at Day 3 with/out cortisol at Day 3

Conclusion:

Upper physiological level (250nM) of cortisol can decrease proliferative responses of T-

lymphocytes against a super-antigen, SEB.

Indi

vidu

al p

rolif

erat

ive

resp

onse

s to

SE

B

(cpm

)

Mea

n (9

5% C

.I.) p

rolif

erat

ive

resp

onse

s to

SE

B

(cpm

)

p < 0.001



Lymphocytes proliferative responsesto PHA

0

50000

100000

150000

200000

250000

No drug Cortisol

3.4.2.2 T-lymphocyte proliferative responses against phytohaemagglutinin A (PHA) after

incubation of diluted whole blood for three days with or without exogenous cortisol

Lymphocytes in the diluted whole blood samples from twelve volunteers responded

satisfactorily to in vitro stimulation with phytohaemagglutinin A (PHA) [Figure 72a and b]. The

addition of 250nM cortisol induced a decreased response (mean difference = 74514, SD =

22856, t = 11.3, df = 11, p < 0.001).

1212N =

CortisolNo drug

Pro

lifer

ativ

e re

spo

nse

s to

PH

A (

95

% C

. I.)

200000

150000

100000

50000

0

Figure 72a: Individual proliferative Figure 72b: Mean (95% C.I.) proliferative

responses of PBMCs to the PHA responses of PBMCs to the PHA with/out cortisol at Day 3 with/out cortisol at Day 3

Conclusion:

T-lymphocyte proliferative responses to in vitro stimulation with a super-antigen and a

mitogen were suppressed by the addition of cortisol (250nM).

Indi

vidu

al p

rolif

erat

ive

resp

onse

s to

PH

A

(cpm

)

p < 0.001



3.4.3 Cell surface markers on proliferati ng T-lymphocytes following stimulation with

PHA

Having shown that 250nM cortisol decreased T-lymphocyte proliferative responses

against a mitogen, a serious of investigations was performed to identify the underlying

mechanisms for this suppressive effect of cortisol upon lymphocyte proliferation.

3.4.3.1 Expression of an apoptosis (CD95: Fas) cell surface marker by T-lymphocytes in vitro

during PHA-induced proliferation with and without exogenous cortisol

This experiment examined the expression of CD95/Fas which is a marker of apoptosis on

T-lymphocytes during PHA-induced proliferative responses. Diluted whole blood from seven

healthy subjects were analysed by flow cytometry at time points of 0, 24, and 48 hours of

incubation after stimulation with PHA. The expression of CD95-FITC fluorescent conjugated

antibody on each lymphocyte sub-population surface was measured by flow cytometry.

In un-stimulated blood cultures, the expression of CD95/Fas, apoptosis marker, by CD4

and CD8 T-cells was unaltered over the 48 hours period [Figure 73a/b and Figure 74a/b].

0

20

40

60

80

0h 24h 48h Time 0 background24hrs background48hrs background

0

20

40

60

80

Mea

n (9

5% C

.I.) C

D95

exp

ress

ion

(%) o

n C

D8

T-ce

lls

Figure 73a: Individual background percentages Figure 73b: Mean (95% C.I.) background of CD8 T-cells expressing CD95 percentages of CD8 T-cells expressing CD95

Indi

vidu

al p

erce

ntag

es o

f C

D8

T-cel

ls

expr

essi

ng C

D95

(%

)



0

20

40

60

80

0h 24h 48h Time 0 24hrs 48hrs

0

20

40

60

80

Mea

n (9

5% C

.I.)

CD

95 e

xpre

ssio

n on

CD

4 T-

cells


When blood was stimulated with PHA, increasing percentages of CD4 and CD8 T-cells

expressed the CD95 marker at 24 and 48 hours incubation [Figure 75a and Figure 76a]. The

increases at 48 hours were statistically significant [Figure 75b and Figure 76b].

0

20

40

60

80

0h 24h 48h

Time 0 with PHA no cortisol

24hrs with PHA no cortisol


10

20

30

40

50

60

70

80

Mea

n (9

5% C

.I.) C

D95

exp

ress

ion

(%) o

n C

D8

T-ce

lls

Figure 75a: Individual percentages of CD8 Figure 75b: Mean (95% C.I.) percentages of CD8 T-cells expressing CD95 in PHA stimulated T-cells expressing CD95 in PHA stimulated

whole blood culture in the absence of cortisol whole blood culture in the absence of cortisol

p = 0.003

p < 0.001

Not significant

Indi

vidu

al p

erce

ntag

es o

f C

D4

T-cel

ls

expr

essi

ng C

D95

(%

)

Indi

vidu

al p

erce

ntag

es o

f C

D8

T-cel

ls

expr

essi

ng C

D95

(%

)



0

20

40

60

80

0h 24h 48h Time 0 with PHA no cortisol



0

20

40

60

80

Mea

n (9

5% C

.I.) e

xpre

ssio

n of

CD

95 (%

) on

CD

4 T-

cells


whole blood culture in the absence of cortisol whole blood culture in the absence of cortisol

Conclusion:

The stimulation by PHA leads to progressively increasing CD95 expression on both CD4

and CD8 T-cells at 24 hours and 48 hours incubation.

p < 0.001

Not significant

p = 0.001

Indi

vidu

al p

erce

ntag

es o

f C

D4

T-cel

ls

expr

essi

ng C

D95

(%)



Addition of cortisol in the culture with PHA had little or no effect upon the percentage of

both CD4 and CD8 T-cells expressing CD95 [Figure 77 and Figure 78].

0

20

40

60

80

0h 24h 48h Time 0 with PHA, cortisol

24hrs with PHA, cortisol


0

20

40

60

80

Mea

n (9

5% C

.I.) C

D95

exp

ress

ion

(%) o

n C

D8

T-ce

lls


whole blood culture in the presence of cortisol whole blood culture in the presence of cortisol

0

20

40

60

80




0

20

40

60

80

Mea

n (9

5% C

.I.) C

D95

exp

ress

ion

(%) o

n C

D4

T-ce

lls


whole blood culture in the presence of cortisol whole blood culture in the presence of cortisol

Collectively, these results showed that the addition of cortisol did not alter the

percentages of the cells expressing CD95 surface markers on CD8 T-lymphocyte [Figure 79]

and CD4 T-lymphocytes [Figure 80] at 24 (a) or 48 (b) hours of incubation.

p = 0.003

p < 0.001

Not significant

p = 0.001

p = 0.001

p = 0.053

Indi

vidu

al p

erce

ntag

es o

f C

D4

T-cel

ls

expr

essi

ng C

D95

(%

) In

divi

dual

per

cent

ages

of

CD

8 T-cel

ls

expr

essi

ng C

D95

(%

)



24hrs with PHA no Cortisol 24hrs with PHA + Cortisol

0

20

40

60

80

Mea

n (9

5% C

.I.) C

D95

expr

essio

n (%

) on

CD8

T-ce

lls


0

20

40

60

80

Mea

n (9

5% C

.I.) C

D95

expr

essio

n (%

) on

CD8

T-ce

lls

Figure 79a: Mean (95% C.I.) percentages of Figure 79b: Mean (95% C.I.) percentages of

PHA stimulated CD8 T-cells expressing CD95 PHA stimulated CD8 T-cells expressing CD95 after 24 hours of incubation with/out cortisol after 48 hours of incubation with/out cortisol


0

20

40

60

80

Mea

n (9

5% C

.I.) C

D95

exp

ress

ion

on C

D4

T-ce

lls


0

20

40

60

80

Mea

n (9

5% C

.I.) C

D95

expr

essio

n (%

) on

CD4

T-ce

lls



Conclusion:

Upper physiological levels of cortisol did not alter the expression of the CD95, the

apoptosis surface marker, on PHA stimulated proliferating T-lymphocyte sub-populations.

Cortisol (+) Cortisol (+)


Cortisol (-) Cortisol (-)




Annexin V(+) % inCD3CD8 cells

0

20

40

60

80

100

No drugCortisol

Annexin V(+) % inCD3+CD8- cell

0

20

40

60

80

100

No drug Cortisol

3.4.3.2 Expression of cell-surface Annexin-V and cytoplasmic Propidium iodine (PI) in T-

lymphocytes after incubation with PHA for three days with or without cortisol

Having shown that cortisol did not affect the percentages of cells expressing the CD95

apoptosis marker, this experiment was performed to investigate actual apoptotic changes of

PHA stimulated proliferating T-lymphocytes. Peripheral blood mononuclear cells (PBMCs)

from ten subjects were analysed at 48 hours of incubation by flow cytometry using Annexin-V-

FITC fluorescent conjugated antibody and propidium iodine (PI) to gate and to measure the

apoptotic changes on CD8 and CD4 T-lymphocyte sub-populations. Apoptotic cells were

defined as cells with Annexin-V-FITC positive (i.e. cell surface has changed) and PI negative

(i.e. cell has not been collapsed or necrosis) staining in flow cytometry.

There was no significant difference in the percentages of apoptotic cells (Annexin-V

positive and PI negative) between PHA stimulated PBMCs incubated with and without 250nM

cortisol both on CD3+CD8+ cells [CD8 T-lymphocyte: Figure 81a] and CD3+CD8- cells (CD4 T-

lymphocyte) [Figure 81b].

Figure 81a: Individual percentages of Figure 81b: Individual percentages of apoptotic CD8T-cells incubated 3 days apoptotic CD4T-cells incubated 3 days with and without cortisol with and without cortisol

Conclusion:

Upper physiological levels of cortisol did not alter the rate of apoptosis of PHA

stimulated T-lymphocytes.



3.4.3.3 Expression of an activation (CD25: IL-2 receptor) cell surface marker by T-

lymphocytes during PHA-induced proliferation with and without exogenous cortisol

This experiment examined the expression of the T-cell activation surface marker, CD25:

IL-2 receptor, on T-lymphocytes following stimulation of whole blood with PHA; and the effect

of 250nM cortisol on this expression.

Diluted whole blood from seven healthy subjects was stimulated with PHA and analysed

by flow cytometry at time points of 0, 24, and 48 hours of incubation. The expression of CD25-

FITC fluorescent conjugated antibody by each lymphocyte sub-population was measured at

each time point.

In un-stimulated blood cultures, the expression of CD25, IL-2 receptor, by CD4 and CD8

T-cells was unaltered over the 48 hours period [Figure 82 and Figure 83].

0

20

40

60

0h 24h 48h Time 0 background24hrs background48hrs background

0

20

40

60

Mea

n (

95%

C.I.

) C

D25

exp

ress

ion

(%)

on C

D8

T-c

ells

Figure 82a: Individual background percentages Figure 82b: Mean (95% C.I.) background Of CD8 T-cells expressing CD25 percentages of CD8 T-cells expressing CD25

Indi

vidu

al p

erce

ntag

es o

f C

D8

T-ce

lls e

xpre

ssin

g C

D25

(%

)



0

20

40

60

0h 24h 48hTime 0 24hrs 48hrs

0

20

40

60

Mea

n (9

5% C

.I.)

expr

essi

on o

f CD

25 (

%)

on C

D4

T-c

ells


When blood was stimulated with PHA, increasing percentages of CD4 and CD8 T-cells

expressed the CD95 marker at 24 and 48 hours incubation [Figure 84a and Figure 85a]. The

increases at 48 hours were statistically significant [Figure 84b and Figure 85b].

0

20

40

60




0

20

40

60

Mea

n (9

5% C

.I.) C

D25

exp

ress

ion

(%) o

n C

D8

T-ce

lls

Figure 84a: Individual percentages of CD8 Figure 84b: Mean (95% C.I.) percentages of CD8 T-cells expressing CD25 in PHA stimulated T-cells expressing CD25 in PHA stimulated whole blood culture in the absence of cortisol whole blood culture in the absence of cortisol

p = 0.003

p < 0.001

p = 0.001

Indi

vidu

al p

erce

ntag

es o

f C

D4

T-ce

lls e

xpre

ssin

g C

D25

(%

)



0

20

40

60




0

20

40

60

Mea

n (9

5% C

.I.)

CD

25 e

xpre

ssio

n (%

) on

CD

4 T

-cel

ls

Figure 85a: Individual percentages of CD4 Figure 85b: Mean (95% C.I.) percentages of CD4 T-cells expressing CD25 in PHA stimulated T-cells expressing CD25 in PHA stimulated whole blood culture in the absence of cortisol whole blood culture in the absence of cortisol

Conclusion:

PHA stimulation leads to progressively increasing CD25 expression on both CD4 and

CD8 T-cells after 24 hours and 48 hours incubation.

p < 0.001

p = 0.001

p = 0.003



Addition of cortisol to the culture with PHA had little or no effect upon the percentage of

both CD4 and CD8 T-cells expressing CD25 [Figure 86 and Figure 87].

0

20

40

60




0

20

40

60

Mea

n (9

5% C

.I.) C

D25

exp

ress

ion

(%) o

n C

D8

T-ce

lls

Figure 86a: Individual percentages of CD8 Figure 86b: Mean (95% C.I.) percentages of CD8 T-cells expressing CD25 in PHA stimulated T-cells expressing CD25 in PHA stimulated whole blood culture in the presence of cortisol whole blood culture in the presence of cortisol

0

20

40

60




0

10

20

30

40

Mea

n (9

5% C

.I.) C

D25

exp

ress

ion

(%) o

n C

D4

T-ce

lls

Figure 87a: Individual percentages of CD4 Figure 87b: Mean (95% C.I.) percentages of CD4

T-cells expressing CD25 in PHA stimulated T-cells expressing CD25 in PHA stimulated whole blood culture in the presence of cortisol whole blood culture in the presence of cortisol

p = 0.001

p = 0.003

p = 0.002

p < 0.001

p = 0.005

p = 0.001

Indi

vidu

al p

erce

ntag

es o

f C

D8

T-cel

ls

expr

essi

ng C

D25

(%

)



Collectively, these results showed that the addition of cortisol did not alter the

percentages of CD8 [Figure 88] and CD4 [Figure 89] T-cells expressing CD25 surface markers

at 24 (a) or 48 (b) hours of incubation.


0

20

40

60

Mea

n (9

5% C

.I.) C

D25

expr

essio

n (%

) on

CD8

T-ce

lls


0

20

40

60

Mea

n (9

5% C

.I.) C

D25

expr

essio

n (%

) on

CD8

T-ce

lls

Figure 88a: Mean (95% C.I.) percentages of Figure 88b: Mean (95% C.I.) percentages of PHA stimulated CD8 T-cells expressing CD25 PHA stimulated CD8 T-cells expressing CD25 after 24 hours of incubation with/out cortisol after 48 hours of incubation with/out cortisol


0

20

40

60

Mea

n (9

5% C

.I.) C

D25

expr

essio

n (%

) on

CD4

T-ce

lls


0

20

40

60

Mea

n (9

5% C

.I.) C

D25

expr

essio

n (%

) on

CD4

T-ce

lls



Conclusion:

Upper physiological levels of cortisol did not alter the expression of CD25, an activation

surface marker, on PHA stimulated proliferating T-lymphocytes sub-populations.







Summary:

T-lymphocyte proliferative responses to in vitro stimulation with memory recall antigens

(PPD and Herpes) as well as a super-antigen (SEB) and a mitogen (PHA) were suppressed by

the addition of the upper physiological level (250nM) of cortisol.

Stimulation by PHA leads to progressively increasing surface expressions of both CD95

(Fas-L: apoptosis marker) and CD25 (IL-2 receptor: activation marker) on CD4 and CD8 T-

cells at 24 hours and 48 hours incubation; and the addition of the upper physiological level

(250nM) of cortisol did not alter these expressions. Upper physiological level (250nM) of

cortisol was also shown not to alter percentages of the apoptotic surface changes of the cell

membrane (measured by Annexin V and PI) on PHA stimulated T-lymphocytes.

Although the underlying mechanisms are still to be elucidated, these results show that the

upper physiological level (250nM) of cortisol to suppresses T-lymphocyte proliferative

responses.

- 170 -

Chapter IV

Discussion



CONTENT OF CHAPTER 4

Discussion

4.1 The influence of psychological intervention upon sustained stress and stress-

associated changes in university students facing exams and in patients with

HIV-infection

4.1.1 The influence of psychological intervention upon stress perception in

university students and HIV-infected adults 173

4.1.1.1 Anticipation of stress - academic examinations by university students

and awareness of carrying HIV-infection by treatment naïve patients 174

4.1.1.2 The influence of psychological intervention upon psychological

well-being 176

4.1.2 The influence of psychological intervention upon immune parameters in

university students facing academic exams 181

4.1.2.1 Stress-associated changes and differences in immune parameters in

university students 181

4.1.2.2 The influence of psychological intervention upon immune

parameters in university students 184

4.1.3 The influence of psychological intervention upon disease progression marker

(CD4 T cell count) and stress-related perception in HIV-infected individuals 186

4.1.3.1 Disease progression marker and stress-related perception in HIV-

infected individuals 187

4.1.3.2 The influence of psychological intervention upon CD4 T-cells as a

disease progression marker in the HIV-infected individuals 188

4.2 Stress hormone associated changes in vitro in immune cells as an exemplar of

the psycho-neuro-endocrino-immune network interaction

4.2.1 Changes in NK-cells after in vitro incubation 191

4.2.1.1 NK cytotoxic activity (NKCA) and NK-cell profiles after incubation

of PBMCs for 24 hours in vitro 192

4.2.1.2 Cortisol-induced changes in NKCA levels and NK-cell profiles 193



4.2.1.3 Endogenous levels of stress hormones (cortisol and DHEA-S) and

NKCA 194

4.2.2 Changes in T-cells after in vitro incubation 195

4.2.2.1 Expression of CD25 during proliferative response 195

4.2.2.2 Expression of CD95 and Annexin V during proliferative response 196

4.3 Conclusions 198

4.4 Future directions

4.4.1 Psychological interventions 199

4.4.2 Measurements 199

4.4.2.1 Psychological measures 199

4.4.2.2 Immunological measures in vivo 199

4.4.2.3 In vitro investigation on NK-cells 200

4.4.2.4 In vitro investigation on T-lymphocytes 200

4.4.3 Proposal for future in vivo study 200



4.1 The influence of psychological intervention upon sustained stress and stress-

associated changes in university students facing exams and in patients with

HIV -infection

This project examined the hypothesis that the effects of stress upon psychological well-

being and general health can be alleviated by psychological intervention, acting through the

integrated psycho-neuro-endocrino-immune network.

Two groups of individuals with different life-event associated stresses were selected to

test the hypothesis:

1. University students facing academic examinations were used as an example of

individuals with sustained, but a time-limited, stressful situation, and the primary

outcomes were NK-cell percentages and NKCA levels; and

2. HIV-infected patients living with the ongoing stress of infection were used as an

example of subjects with sustained life-long stress, and the primary outcome was

CD4 T-cell counts.

4.1.1 The influence of psychological intervention upon stress perception in university

students and HIV-infected adults

The first parts of this section discuss the effects of stress (either anticipation of exams for

university students or awareness of carrying on-going life-threatening disease for patients with

HIV-infection) on psychological well-being [4.1.1.1].

Thereafter, the following parts of this section discuss the influence of psychological

intervention upon stress perception and of following the categorisation of the appraisal of the

stressful life event [1.2.3.2] as:

1. Primary appraisal: Perception as a neutral or benign stimulus or a threat; and

2. Secondary appraisal: Judgement of one’s capability of coping with the stressor

subsequent to the primary appraisal.

Finally the results as they relate to perceived quality-of-life, i.e. perception of control

(inner or outer locus of control), psychological functioning, and sleep quality, are discussed

[4.1.1.2].



4.1.1.1 Anticipation of stress - academic examinations by university students and awareness of

carrying HIV-infection by treatment naïve patients

Anticipation of academic examinations for university students was examined in the

current study to determine if it causes increases in stress levels. The mean PSS level of the

university students both at academic examination and when they were free from examination

were similar to the published mean levels for university students [Cohen et al., 1983]. In line

with previous findings [Maes, Van Bockstaele et al., 1999; Whitehouse et al., 1996], university

students in the current study reported more anxiety and stress when they faced academic

examinations compared to when they were free from academic examinations [3.1.1.1]. This

finding supports the validity of using academic examinations as a time-limited stressful

situation.

One possible criticism for using academic examinations as a stressor is the variability in

student responses to academic examinations. Some students experience more stress than others

in response to this situation, and some confident students may experience very little stress, if

any. Moreover, although expressed anxiety at academic examinations is usually thought of as a

negative experience [Deinzer & Schuller, 1998; Glaser et al., 1985; Gruzelier, Levy et al., 2001;

Gruzelier, Smith et al., 2001; Kiecolt-Glaser et al., 1986; Kiecolt-Glaser et al., 2001], some

students might feel academic examinations are an opportunity to test his/her capability, so that

the academic examinations for them can be perceived as an exciting experience, or in other

words, an impetus in primary appraisal [1.2.3.2]. For those students who perceive academic

examinations as an opportunity to show their capability, the examinations may be perceived as

not a fear but a positive anxious anticipation which can also cause a response towards fighting

or tackling for achievement in the ‘ fight or flight’ responses in the psycho-neuro-endocrino-

immune network as can be seen in acute stress responses.

Nevertheless, the perceived stressed scale (PSS) can be used to distinguish those who

perceive the life events as an excitement from those who perceive it as a stressful event since

the PSS were designed to assess the degree to which situations in one’s life are appraised as

stressful [Cohen et al., 1983]. This a priori exposition of the PSS was tested as discussed in the

following section.

Not surprisingly, awareness of carrying life-threatening ongoing disease, HIV-infection,

for patients was found to be more stressful than anticipation of academic examinations for

university students [3.2.1.1]. On the other hand, and perhaps contrary to intuition, the anxiety



levels expressed by individuals in these two different stressful situations were shown to be the

same [3.2.1.1]. Hence, it can be implied that the measured levels of anxiety by the State anxiety

score may characterise more an acute response of ‘ fight or flight’ in the primary appraisal

[1.2.3.2] whereas the measured levels of stress by the PSS may indicate the accumulated levels

of stress over the time period.

Notably, anxiety levels in the HIV-infected individuals did not change over the study

period, although those reporting high levels of stress consistently reported more anxiety than

individuals who reported low levels of stress [3.2.1.1]. This trend between the two types of

individuals (labelled as the Stressed and Not-stressed defined by a midline split of the PSS

scores) was also shown in the Impact Event Scale (IES) measurement of primary appraisal in

event-specific stress perception. The primary appraisal against awareness of carrying HIV-

infection decreased over the study period, but the levels of these decreases were almost

paralleled in the Stressed and Not-stressed subgroups so that Stressed HIV-infected individuals

also reported higher IES sores than the Not-stressed individuals [3.2.1.1].

The finding that the state anxiety did not change, but that the primary appraisal level did

decrease over the study period suggests the possibility that the stressful impact of being

diagnosed as carrying a life-threatening disease, HIV-infection, can decrease over time, (in this

case a four month period with access to psychological care when needed), but that the anxiety

associated with being aware of carrying this disease is less amendable to intervention, possibly

through anticipating future stressful life events related to the disease. This may indicate that

anxiety can be driven or provoked not only from the primary appraisal of the stressor, which has

occurred in the past or the present, but also from thoughts about and anticipation of possible

future negative events associated with the disease.

In contrast, there was little change over the four months period in perceived quality-of-life

levels, i.e. sense of taking control of one’s own life measured by the Locus of Control (LoC)

scale; levels of psychological functioning as measured by the Mental Component Summary of

the SF-36 (MCS); and levels of sleep quality as measured by the scale of Pittsburgh Sleep

Quality Index (PSQI). These findings suggest that these psychological domains may be more

stable over time (i.e. more than the four months used in this study) or a more powerful

intervention may be needed to detect changes. Alternatively, there is a possibility that other

measurements of quality of life domains may be more sensitive for detecting the change than

the above questionnaires. However, as was the case with the measures of anxiety and primary



appraisal, the Non-stressed HIV-infected individuals were shown to constantly report a greater

sense of taking control of one’s own life, better psychological functioning, and better sleep

quality than the Stressed individuals [3.2.1.1]. Hence, it can be concluded that the method to

compare two Stressed and Not-stressed subgroups based on the midline split of the PSS levels

may be a useful and practical way to identify the stress-related and the quality-of-life-related

differences in the measurements in the psycho-neuro-endocrino-immune network.

4.1.1.2 The influence of psychological intervention upon psychological well-being

As described in the Introduction [1.2.3], the stress perception to be examined in the

project was the participants’ appraisal of stressful life events. The results from both study

populations indicated that the psychological interventions had no clear benefit upon stress

perception and perceived quality-of-life. There are a number of factors that could explain the

generally negative results:

1. Psychological interventions may not impact upon the stress perception measured in

the current studies;

2. The short period of time in training and practice of the psychological interventions

for achieving to show clear effects; and/or

3. The relatively small sample sizes.

Despite these negative results, data from some of the psychological measures, i.e.

perceived quality-of-life (specifically, the LoC, MCS and PSQI), indicate some benefit from the

Johrei intervention on the sense of taking control of one’s own life, psychological functioning,

and sleep quality. Sleep quality may also indicate sense of control in their life, particurly in the

sense of control in relaxation at night-time both cognitively and physically, so change levels in

sleep quality may also represent changes in the sense of control. These benefits may have been

clearer had the study involved a greater number of subjects (e.g. more than 121 for the LoC and

PSQI or 133 for the MCS).

This section discusses the effect of psychological intervention upon these stress

perception (primary and secondary appraisals) and perceived quality-of-life as follows.

Primary appraisal

A major aim of stress management intervention is to alter the primary appraisal of the

stressful life event from a threat to a neutral (or even a benign stimulus) [1.2.3.2: Text box 2] so

that the event is no longer perceived as stressful. This was aimed to achieve by providing

alternative perspectives [1.2.3.3: Text box 4].



In the project, the university students in the Relaxation control group exhibited increased

levels of the State anxiety scores when they were facing exams, and the psychological

interventions did not show any effects on the increase in the State anxiety scores [3.1.3.1]. This

finding may be interpreted as their perception of the exams was not ‘neutral’ in the primary

appraisal category. As discussed before [4.1.1.1], the State anxiety scores might represent the

summed levels of anticipation of both threat and impetus, so there remains a possibility that

some of the participants might have been changing the way they view the exam as a way to cope

with this stressor, or even a way to up-lift the morale to tackle the exams. Hence, future studies

using university students should investigate this hypothesis by measuring the levels of

excitement as well as anxiety.

Similarly, there was no change in the State anxiety score over the four months period in

the HIV-infected individuals in either the wait-listed control group or the intervention groups.

On the other hand, the IES scores did decrease significantly as described before, but there was

no difference in the decrease between the psychological interventions and the wait-listed control

groups. One possible explanation for the improvement in their IES scores noted over time in the

wait-listed control group might be related to the timing in measuring the questionnaire. Due to

practical difficulties in asking the participants to fill in the questionnaires, the participants in the

wait-listed control group completed the questionnaires shortly before (and for some of

participants, during) the first week of either of the psychological training session. Hence, a

positive anticipation toward the forthcoming psychological intervention after a long waiting

period might explain, at least in part, the observed improvement in this domain.

Nonetheless, the psychological interventions showed no greater improvement or

alleviation in the State anxiety scores or the IES scores, relative to the wait-listed control group

in HIV-patients.

Secondary appraisal

The PSS scores showed no difference between the intervention groups and the Relaxation

control group at academic examinations, so it was concluded that the psychological intervention

did not affect the perceived stress levels in university students facing academic examinations

more than the relaxation might have done.



The scores of the PSS in the HIV-infected individuals at recruitment were much higher

than the levels in the university students facing exams, and the levels stayed at the same high

levels after four months period in the wait-listed control group participants. Moreover, the four

months of training and practice in the psychological interventions did not change these high

PSS scores. This finding suggests that perceived stress level in HIV-infected individuals was

not affected by the psychological interventions. It is possible that the high stress levels

associated with being HIV-positive may not be amenable to change with the brief interventions

used in this study. It is also possible that the relatively small sample size and short time period

limited the power to detect significant effects that might have been shown had there been more

participants and a longer intervention time period.

Novertheless, it is concluded that the psychological interventions showed no significant

improvement or alleviation in the Perceived Stress Scale scores relative to the relaxation in

university students facing exams or to the wait-listed controls in HIV-patients.

Quality -of-life

The measures of perceived control (locus of control), psychological functioning, and sleep

quality did not change in the wait-listed control group in the HIV-infected individuals over the

four months period. Moreover, neither of the psychological intervention groups showed any

statistical differences in these levels after four months of the intervention period. However,

although a larger sample size would be needed to confirm, there was a trend, in the Johrei group,

for improved scores across all the three outcome domains. Hence, there remains a possibility

that the training and practice of Johrei has improved perceived quality-of-life levels, which can

be associated with improvement in the meaning-focused coping skills [1.2.3.2: Text box 3].

Together with the clear different trends in the effect upon the immune cells (discussed

below [4.1.2.2 and 4.1.3.2]), and the fact that the effect seemed favourable to Johrei for

university students [3.1.3.2] and HIV-infected individuals [3.2.2.2 and 3.2.3.2], it is suggested

that unique psychological features in the Johrei training and practice may be worthwhile to

explore further.

The training and practice of the self-administered psychological intervention used in the

project aimed to achieve two objectives for the participants:

1. Behavioural domain: spending time and effort on oneself for one’s own benefit; and

2. Cognitive domain: acquiring additional concepts and perspectives for stressful events.



In the behavioural domain, one of the unique features of Johrei practice is that it requires

a partner to practise with while the Self-hypnosis practice requires only one’s own time and

effort. This involvement of others as a partner / receiver for their own Johrei practice comes

from two of its key concepts and principles [Naito, 2003]:

1. “Healing oneself by healing others” : healing is a mutual process and interaction, and

it benefits equally both the Johrei giver and receiver since the power of healing was

taught to arise from the spiritual healing-light which flows through giver and receiver

during the Johrei practice; and

2. ‘Spiritual cord’ : where the spiritual healing-light and love comes and travels beyond

time and space, and this Spiritual cord bonds a Johrei giver with all of the people

whom the giver cares about and also with something greater in the spiritual realm, i.e.

the source of the spiritual light itself.

Continued practice, which is a common feature in both Johrei and Self-hypnosis, can also

enhance a trainee’s sense of confidence in his or her own skills, the manageability in coping

strategies [1.2.3.2], which can be rephrased as ‘Self-empowerment.’ The above two concepts

found in the Johrei practice, therefore, can be strengthened synergistically with an increase in

their ‘Self-empowerment’, as they are repeated in practice.

In the cognitive domain, these tangible concepts may also have provided a Johrei giver

with both a sense of support from- and a sense of connectedness to- a receiver, and even

something greater in the spiritual realm, i.e. the source of the light. This may have buffered

against any feelings of loneliness or helplessness, and contributed to an overall sense of well-

being [Fromm, 1956], consistent with the findings from the Whitehall Study II which showed

that social support and self-confidence about one’s own skills are important factors for the

prevention of poor mental health [Stafford & Marmot, 2003; Stansfeld et al., 1997].

Furthermore, a belief and confidence in one self and/or something greater might have increased

the meaningfulness as Fromm [1956], Frankl [1970] and Strang et al. [2001] suggested.

Accordingly, Johrei might have enhanced their abilities in the meaning-focused coping

approach as well as the emotion- or problem- focused approaches [1.2.3.2: Text box 3].

In addition, the above two concepts, given repeatedly in the Johrei practice, have provided

the participants with a chance to recall or to give insight about their own perspectives related to

‘Spirituality’ . The word ‘Spirituality’ or ‘Spiritual’ may suggest various concepts according to

each individual and each occasion or situation [Richards & Bergin, 1997]. In the Johrei training

session, this variety of ‘Spiritual’ thoughts and concepts are allowed and shared in a group, and



could be left in ambiguity if total agreement could not be achieved, as long as they agree to feel

comfortable to practise Johrei [Appendix 2-ii ].

The Johrei participants were also encouraged to appreciate their own doubts about the

efficacy of the intervention, or the existence of the healing-light if doubts about these arose

naturally. These doubts can also be left in ambiguity although they were also encouraged to

practise even with doubts so that they can test or challenge the doubts by themselves [Appendix

2-ii ] in order to maintain one’s inner coherence. These methods used in the Johrei session are

based on the concept that ambiguity may provide important insights into self-cognition of one’s

own life [Empson, 1930; Toyama, 1973], so that the individuals left in ambiguity may be able to

(1) establish an alternative perspective to cope with stressful life events; (2) achieve a gradual

increase of their inner-personal coherence [Antonovsky, 1993]; and (3) weigh values and goals

to modify the meaning of a stressful transaction [Frankl, 1970; Park & Folkman, 1997] to

increase the sense of meaningfulness [1.2.3.2].

The possible link between the above behavioural and cognitive domains is found in a

concept of ‘Self-cultivation’ [Yuasa & Kasulis, 1987; Yuasa et al., 1993]. This ‘Self-cultivation’

may not be explicitly recognised in Western culture, but it has been emphasised in Eastern

culture including various traditional Japanese practices [Yuasa et al., 1993]. The mottos of this

self-cultivation include “practice makes perfect” and “practice precedes knowledge.” These

mottos mean that practice does not require a full understanding of knowledge in the subject, but

benefits can be obtained, and skills and knowledge can be developed through basic practice of

‘Kata’ - a standardised form or sequence of exercises [Yuasa & Kasulis, 1987]. The idea is that

practice can be used to develop, and also to bring to the fore of conscious awareness, ‘Tacit

knowledge’ , i.e. knowledge that would otherwise remain hidden [Nonaka & Takeuchi, 1995].

Collectively, the development of the above domains should result in the following gains:

1. Social support and sense of support;

2. Spiritual awareness; and

3. Inner-personal coherence and meaningfulness.

Hence, future investigations of Johrei should include examination of the effects on

perceived support and these quality-of-life domains using published questionnaires that assess

these constructs, such as the Kesseler Perceived Social Support (KPSS) [Coventry et al., 2004],

the Spiritual Involvement and Beliefs Scale (SIBS) [Hatch et al., 1998] and the Sense of



Coherence (SoC) [Antonovsky, 1993], as well as the scales of stress perception, used in the

project such as the Perceived Stress Scale (PSS) [Cohen et al., 1983], and sleep quality, the

Pittsburgh Sleep Quality Index (PSQI) [Buysse et al., 1989].

4.1.2 The influence of psychological intervention upon immune parameters in university

students facing academic exams

The changes in percentages of NK-cells and T-cells at academic examination time were

small, and similar in the degree of changes found elsewhere in the literature using university

students [Gruzelier, 2002b; Gruzelier, Smith et al., 2001; Halvorsen & Vassend, 1987; Kiecolt-

Glaser et al., 1986; Maes, Van Bockstaele et al., 1999; Uchakin et al., 2001]. In gender

difference, NK-cells have been reported to be lower in females than males under the age of 50

[Jentsch-Ullrich et al., 2005]. This study showed the same trend, but there was no gender bias

with regard to stress [3.1.2.3]. Similar fluctuations were also reported in studies that used

slightly different immuno-phenotyping: CD2 was used to gate T-cells & NK-cells instead of

CD45 [Maes, Van Bockstaele et al., 1999], and CD16 was combined with CD56 to detect NK-

cells [de Gucht et al., 1999; Uchakin et al., 2001]. Hence, changes and differences here may

have no apparent clinical impacts upon health, but the results are discussed in the light of stress

responses.

4.1.2.1 Stress-associated changes and differences in immune parameters in university students

The levels of lymphocyte sub-populations (NK-cells, CD4 and CD8 T-cells) and the NK

cytotoxic activity (NKCA) were analysed by comparing the Stressed and Not-stressed

subgroups in the university students. Although the results of NK-cell percentages from this

study did not support previous findings in the literature in which stressed students had lower

numbers or percentage of NK-cells in their circulation compared with not-stressed students, the

results showed that the Stressed students exhibit low NKCA levels compared with the Not-

stressed students [3.1.2.1] in line with published findings [de Gucht et al., 1999; Deinzer &

Schuller, 1998; Glaser et al., 1985; Gruzelier, Smith et al., 2001; Halvorsen & Vassend, 1987;

Kiecolt-Glaser et al., 1986].

This finding leads to the hypothesis that individuals with high stress levels, from

sustained stress [1.2.3.2], may have low NKCA levels regardless of the situation. This

hypothesis may be specified more such that the high perceived stress level may be associated



with a low per-NK-cell cytotoxic activity level. NK-cell percentages and NK cytotoxic activity

measured by using PBMCs are often used together or separately as stress benchmarks without

calculating the per-NK-cell cytotoxic activity [Dopp et al., 2000; Levy et al., 1989; Schedlowski

et al., 1993; Whitehouse et al., 1996]. This per-NK-cell cytotoxic activity, calculated as a NK

cell percentage to NK cytotoxic activity ratio, is known to be impaired in certain physical

conditions, such as in cirrhosis [Laso et al., 1997] and endometriosis [Oosterlynck et al., 1994].

In stress research, one meta-analysis paper calculated this per-NK-cell cytotoxic activity

in acute stress settings, and mentioned that acute stress did not alter per-NK-cell cytotoxic

activity, i.e. stress-induced changes in NKCA were due to alteration of NK-cell percentages

[Segerstrom & Miller, 2004]. This may only occur in acute stress situations, given the finding

that acute stress can increase both NK-cell percentage and NKCA levels [Dopp et al., 2000].

Therefore, it is suggested that future studies investigating the effect of stress upon NK-cells

should analyse the per-NK-cell cytotoxic activity.

In this current study, in the Stressed students, the levels of the per-NK-cell cytotoxic

activity and NKCA were found to be lower, although NK-cell percentages were not decreased

[3.1.2.1]. This implies that there may be other factor(s) affecting NKCA than a simple change in

NK-cell numbers / percentages. This was investigated by looking for direct effects of in vitro

exposure of blood to cortisol [3.3] and this will be discussed later [4.2.1].

In the analysis of CD4 T-cells (Helper T-lymphocytes and Regulatory T-cells), the results

showed that there was no significant difference in the levels of CD4 T-cells between the

Stressed and Not-stressed subgroups. This result is in line with previous reports; some studies

report an increase, others a decrease, and still others report no change [de Gucht et al., 1999;

Maes, Van Bockstaele et al., 1999]. The possible changes or no change in the CD4 T-cell

percentages may be due to:

1. A change of distribution in CD4 T-cells and/or in subsets (Th.1, Th.2 and T-reg), i.e.

a release of cells into the circulation or homing of cells into tissues;

2. A change in rate of cell production, i.e. generation or inhibition of new cells; or

3. A change in cell destruction, i.e. preventing or promoting cell death (programmed cell

death in the cell cycle).

These scenarios may occur in a specific time course, starting with a cell distribution

change and then generating new cells and the prevention of cell death. This consecutive course

may reflect a shift from an alarm reaction to a stage of resistance along the lines of Selye’s



classifications [1.2.4.1]. This alarm reaction means that perceiving a situation as stressful can be

responded to in the immune arm of the psycho-neuro-endocrino-immune network by a release

of CD4 T-cells into the circulation. This possible mechanism in the immune system was

suggested in a report stating that the increase in the blood stream of the CD4 T-cells was due to

an increase of one subset of CD4 T-cells (CD25+CD4+ T-cell subset) in nurses undergoing

sustained stress, i.e. nurses who were diagnosed with ‘burnout’ syndrome [de Gucht et al.,

1999]. This CD25+CD4+ T-cell subset is a main component of the Regulatory T-cells (T-reg)

which play a major role in anergy, tolerance or in switching off the immune responses to

pathogens [Akbar et al., 2003], so this could be an important factor in the suppressive effect of

sustained stress upon the immune responses.

Recently, the direction of stress-induced changes in CD4 T-cell percentages, whether to

increase or to decrease, was demonstrated to depend upon the conditions of the study, i.e. type

of stressor and timing when CD4 T-cell percentages were measured, as shown below

[Segerstrom & Miller, 2004]. The categories of detailed setting of the timing in the reviews

[Miller & Cohen, 2001; Segerstrom & Miller, 2004] are whether there is short lasting time-

limited acute stress or one of the following four categories of sustained stress:

1. Brief naturalistic (predictable self-limited life events, e.g. academic examination),

2. Chronic (on-going or persistent life event, e.g. disease),

3. Event sequence (discrete stressful events occur repeatedly), or

4. Distant (past but traumatic events).

The sustained stress in the current student study falls into the brief naturalistic stress, and

they mentioned that CD4 T-cells seemed not to change in numbers, but functional suppression

or a shift towards humoral immune activation would occur under the category of sustained

stress.

Further studies using university students facing academic examinations should consider

examining the T-reg sub-population and the suppression or shift of immune responses in the

functional measures (by measuring Th.1 and Th.2 cytokine production) to explore the stress-

induced effect of naturalistic sustained stress upon CD4 T-cells.

There was no difference in CD8 T-cells (Cytotoxic T-lymphocytes) percentages between

the Stressed and Not-stressed subgroups, and this is again consistent with the literature findings

showing that stress-induced changes in the levels of CD8 T-cells is inconsistent [Segerstrom &

Miller, 2004]. These inconsistent results may be due to the fact that the CD8 T-cell population



is not a homogeneous entity. The CD8 T-cell population consists of thousands of specific CD8

T-cells made for a specific antigen, and it takes much longer period to make a specific immune

response than an innate immune response. Hence, inconsistent results may be because the end

results of combinations of various changes in the heterogeneous entity of the CD8 T-cells were

shown and because the time period was shorter than needed to show any changes in numbers.

Future investigations of stress-induced changes in the CD8 T-cell, if any, should take this

heterogeneous feature of the CD8 T-cell population into account, so should use a specific

antigen to stimulate a specific CD8 T-cell subtype, preferably in combination with functional

examinations (proliferative responses or cytokine productions).

4.1.2.2 The influence of psychological intervention upon immune parameters in university

students

Although the subject numbers decreased by the time of the second set of academic

examinations leaving a total of 35 students, fortunately they were distributed almost evenly

across the three groups. The findings indicated that the Relaxation control group showed a

similar trend to the stressed individuals in the literature at exam time, i.e. the trend to decrease

NK-cell percentages; and that this was altered particularly in the Johrei group [3.1.3.2: Figure

26]. Baseline NK cytotoxic activity results were missed due to the development and adjustment

of the Godoy-Ramirez’s assessment method so that analyses of the effects of intervention upon

the NK cytotoxic activity were not possible to assess. Hence the following sections discuss the

results of the NK-cell and lymphocyte distributions only in each group.

Relaxation control group

The relaxation control group at academic exam time showed similar decreases in NK-cell

levels to published reports about high stressed individuals [Borella et al., 1999; Gruzelier, Smith

et al., 2001; Inoue-Sakurai et al., 2000; Maes et al., 1992; Segerstrom & Miller, 2004]. However,

in order to make the obtained changes statistically significant, the sample size calculation shows

that the subject number needs more than 39. The number of subjects was only 11, so definitive

conclusions from these findings cannot be made. This finding may be due to the following

possibilities:

1. Exam stress did not significantly change NK-cell levels;

2. The sample size was too small to detect the change; or



3. The relaxation, provided by the mock neuro-feedback procedure as shown previously

[Egner et al., 2002], itself only or with attention given to the students (i.e. placebo

effect) might have buffered the stress-induced NK-cell decrease.

In order to determine these hypotheses, as stated previously, future investigation should

have an intervention-free control group as well as the Relaxation control group.

Self-hypnosis group

In the previous reports in the literature, self-hypnosis training and practice were shown to

buffer the stress-induced decline levels in either NK-cell levels (labelled as CD3-CD56+ or/and

CD16+) [Bakke et al., 2002] or CD8 T-cell counts [Gruzelier, Levy et al., 2001], or in both NK

cells and CD8 T-cells [Gruzelier, Smith et al., 2001] whereas non-intervention controls showed

a significant decline. The Self-hypnosis group in the current study showed no changes in the

NK-cells levels at academic exams. However, it is also possible that the number of subjects was

too small to detect differences; or that stress-induced changes in the NK-cells were cancelled as

a result of alteration of the primary appraisal from stressful to ‘neutral.’ In contrast, CD8 T-cell

levels were increased in the Self-hypnosis group as shown previously [Gruzelier, Levy et al.,

2001] although the changed levels of the CD8 T-cells were not related to the stress perception in

this study [3.1.2.2].

Hence, it was concluded that this study partially supports the hypothesis that Self-

hypnosis may have acted as stress-buffering for university students facing academic exams,

therefore, it would be worth examining it further in a study using a greater number of subjects,

and with measurements of functional activity of CD8 T-cells, i.e. cytotoxic T-cell activity to a

specific antigen, using a diseased population in which the antigen(s) can be specified as

proposed above.

Johrei group

Interestingly, the result from the current study showed that the levels of NK-cell

percentage in the Johrei group were increased at academic exams. Although the amplitudes of

this increase were relatively small and all percentages and counts were within the normal range

[Hannet et al., 1992], eight of eleven Johrei participants showed raised percentages of NK-cells

in their peripheral blood. This trend was significantly different from that of the Relaxation

control and the Self-hypnosis groups; and the expected direction in the change of the NK-cells



based on the observation of stressed individuals both in the current study and in the literature

was opposite to that of the Johrei group in the current study [3.1.3.2].

As described in the introduction [1.2.4.2 and 1.2.4.3], acute stress is known to increase the

levels of NK-cell percentages and NK cytotoxic activity [Dopp et al., 2000] while sustained

stress is known to decrease the levels. Borella et al. [1999] reported that students who are

emotionally stable in personality profile have increased NK cytotoxic activity during their

academic exams. Further, in the other not-diseased population, De Gucht et al. also reported

[1999] that sustained stress increased NK-cell count in the group with high professional stress

(measured by the Nurse Stress Index) but low psychopathology (those who have good adaptive

coping abilities to their symptoms). These findings and the results from the current study

suggested the possibility that Johrei may have increased the emotional stability or decrease

pathological impact of stress. Future research on Johrei using university students facing exams

should employ a larger sample size with measures of per-NK-cell cytotoxic activity levels in

order to confirm this finding.

Despite the limitations, it is, nevertheless, concluded that the psychological interventions,

particularly Johrei, appeared to have possible buffering or even counteracting effects of

examination stress upon the distribution of the NK-cells, and/or CD8 T-cells, in the university

students.

4.1.3 The influence of psychological intervention upon disease progression marker (CD4 T

cell count) and stress-related perception in HIV -infected individuals

The human immunodeficiency virus (HIV),�a lentivirus of a subgroup of retro-viruses,

progressively destroys the immune cells, CD4 T-cells in particular, and this leads to the life-

threatening disease, the acquired immunodeficiency syndrome (AIDS), and death. The decline

of CD4 T-cells is known to be associated with a risk of developing opportunistic infections such

as Pneumocystis carinii pneumonia or oesophageal candidiasis as well as the risk of developing

tumours, particularly those related to immune suppression, such as the Kaposi’s sarcoma or

Non-Hodgkins lymphoma.

Hence, HIV infection may be considered to be a life-long biological and psychological

stressor, and it is known that stress levels contribute to detrimental outcomes associated with



HIV disease progression [Catalan et al., 1995; Cole et al., 2003; Cole et al., 1997; Cole et al.,

1996]. The current project aimed to decrease the level of stress in the HIV-infected individuals

so that their disease progression can be delayed, allowing these individuals to maintain their

health and well-being and delay the requirement to commence antiretroviral drug therapy and its

inherent complications.

4.1.3.1 Disease progression marker and stress-related perception in HIV-infected individuals

CD4 T-cell counts in HIV-infected individuals, a major clinical parameter for monitoring

disease progression, is known to decline over the course of this life-long infection [de Wolf et

al., 1997]. A steady decline in CD4 T-cell counts of 7 ± 3 cells per �l per month over a 12

months period prior to their enrolment into the study was observed in the total of 95 HIV-

infected individuals [3.2.3.1]. Similarly, HIV-infected individuals who are not receiving any

anti-retroviral treatments in our wait-listed control group showed a decline in CD4 T-cell counts

of 12 ± 17 cells per �l per month over a five-month period [3.2.2.2]. These were within the

average range of published findings (8 to 16 cells per �l per month) [de Wolf et al., 1997]. In

the current project, this rate of decline in the number of CD4 T-cells was analysed in order to

determine if stress perception has any associations with this rate of decline.

The results in the HIV-infected individuals showed that observational single time point

measurements of perceived stress, quality-of-life and sleep quality did not correlate with the rate

of change in the CD4 T-cell counts, i.e. scores at one single time point did not predict or

indicate the rate of change in the CD4 T-cell counts. In addition, the change levels over the

study period in the Perceived Stress Scale (PSS) also did not correlate with the rate of decline.

However, the results did show that decreases over a four-month period in the sense of taking

control of one’s own life or inner-personal coping ability (LoC), psychological functioning

(MCS) and sleep quality (PSQI) were strongly correlated with a decline in the CD4 T-cell

counts [3.2.1.2].

These findings may imply the possibility that change levels of autonomy or attitudes of

actively being engaged in their life, as opposed to measures of passively experienced stress

(stress perception), may be associated with the rate of change in the CD4 T-cell count in HIV-

infected individuals. This possibility is consistent with the suggestion in the Whitehall Study II

[Bosma et al., 1998] that ‘self-empowerment’ may have beneficial effects on tackling disease

physiologically. For the purpose of examining this hypothesis that an increase of the sense of

‘self-empowerment’ improves (delays) disease progression in HIV-infection or maintains health,



the Sense of Coherence (SoC) [Antonovsky, 1987] may be a good domain to assess in future

studies, because the SoC is designed to measure a positive inner-personal coherence which

consists of the levels of comprehensibility, manageability and meaningfulness [1.2.3.2].

In contrast to the analysis of the CD4 T-cell counts, there was no trend in the levels of the

HIV viral load or NK-cell counts in HIV-infected individuals (not receiving anti-retroviral

treatment) across the five months period with regard to either the CD4 gradient or the levels of

the perceived stress, quality-of-life or sleep quality [3.2.1.2]. The levels of HIV viral load are

clinically used to monitor disease progression in combination with the result of the CD4 T-cell

counts, and they are used to examine the response to anti-retroviral treatments, so the viral load

levels might not be a suitable outcome measure for study subjects who are not receiving anti-

retroviral treatment. Similarly, although NK-cells are known to play an important role in

defensive mechanisms against HIV infection and progression [Fauci et al., 2005], no consistent

trend was found between the number of NK-cells and disease progression in HIV-infected

individuals, so NK-cell levels might also not be a suitable outcome measure for study subjects.

Collectively, it can be concluded that the rate of decline in CD4 T-cell count (CD4

gradient) in treatment naïve HIV-infected patients is an important and useful practical outcome

measurement for the investigation of the effect of psychological intervention upon disease

progression. Notably, it is also demonstrated that the change levels of perceived quality-of-life,

which can be interpreted as the change in attitude of actively being engaged in their life and/or

the change in the sense of meaningfulness, may have direct associations with this change in the

CD4 T-cell count in HIV-patients. Accordingly, improvement of the meaning-focused coping

skills [1.2.3.2] may have beneficial effects upon health and well-being, and therefore it can be

of great interest for the effect of psychological intervention.

4.1.3.2 The influence of psychological intervention upon CD4 T-cells as a disease progression

marker in the HIV-infected individuals

The results showed that, in all three groups, there was a steady decline in the CD4 T-cell

counts before the study commenced and the absolute CD4 T-cell counts were similar [3.2.3.2].

After commencement, this decline of CD4 T-cells continued in controls (the wait-listed controls

in the five months study [3.2.2.2: Figure 40] and the Database controls in the 24 months study

[3.2.3.2: Figure 44]). The on-treatment analysis showed that this decline rate of CD4 T-cells

was stopped, and even reversed, in the HIV-infected individuals following Johrei training and

practice over the five months period while there was no change in the Self-hypnosis group. This



interesting different trend shown by the on-treatment analysis in the five months study, however,

was not confirmed by the Intention-to-treat analysis suggesting that future studies examining

this effect of Johrei will require a larger sample size (more than 84 subjects per each group)

[3.2.2.2: Table 39].

The reduction in the decline of the CD4 T-cells in the individuals in the Johrei group may

have contributed to both psychological and physiological stress reduction. In addition to

improving individual’s well-being, there is both an individual and economic benefit in that any

reduction in the speed of decline of CD4 T-cell counts will effectively delay the time when an

individual patient will commence expensive anti-retroviral treatments. This will only be delayed

rather than avoided, but may help to keep away from a vicious circle of stress-induced

detrimental changes towards acceleration of the disease process towards AIDS and will delay

exposure to the toxic side effects of anti-retroviral drugs.

Limitation should also be mentioned. Recruiting and motivating participants for a

randomised controlled trial (RCT) is known to be challenging. Walker suggested in his review

that performing explanatory and pragmatic RCTs can minimise these problems [Walker &

Anderson, 1999]. In fact, the university student study did not have a high drop-out rate up until

the time the training sessions were completed. This may be due to the fact that the current study

using university students employed the mock neuro-feedback sessions as a control condition,

which is similar to explanatory and pragmatic trial since the same amount of care and attention

was given to the control individuals. On the other hand in the HIV study, the control group

subjects were randomly assigned and had to wait for four months, and had higher drop-out rate

compared with the Self-hypnosis and Johrei groups.

Further, although the study subjects were randomly assigned to the three groups, actual

numbers for the analyses were different and the number in the Johrei group was the smallest in

the HIV-patient study. This was not associated with the drop-out rate but because the number of

subjects who were assigned to the group but did not turn around the first training session was

the largest in the Johrei group. It may have reflected some psychological difficulties in trying a

novel (or even strangely sounding) procedure like Johrei. This may have resulted in a self-

selection within the Johrei group towards a particular personality type, e.g. open mindedness or

novelty seeking in the Temperament and Character Inventory (TCI) [Cloninger et al., 1993].

This personality factor should be examined in future investigation.



Compliance of using procedure after the training for the study period was similar between

Johrei and Self-hypnosis, but with regard to collection of the data in the HIIV-patient study,

participants in the Self-hypnosis group attended more sample collection time points. The

appointments for the data-collection sessions in both Self-hypnosis and Johrei groups were

made by the same research assistant (Mr. B. Bennett) who had attended both intervention

sessions. Hence, this may indicate that individuals in the Self-hypnosis group were more

committed to the study or benefited more from contacts with the study personnel (Dr. T.

Laidlaw et al.) than the Johrei participants, remembering that Johrei, for the most part, was

performed with a partner. Nonetheless, an extra caution should be given when the psychological

effect from the result was discussed. One procedure to overcome this bias is to use the method

of the Intention-to-treat analysis as applied in the current study.

Although there remain limitations, these in vivo studies demonstrated that:

� Academic examinations can induce stress in university students [3.1.1.1];

� NK-cell function appeared to be associated with stress perception in university

students [3.1.2.1];

� Psychological intervention may counteract, or at least buffer, exam-stress-induced

loss of NK-cell percentage in university students [3.1.3.1: Figure 26];

� Psychological intervention, particularly Johrei, may slow the disease progression in

HIV-infected patients [3.2.3.2: Figure 43]; and

� Improved perceived quality-of-life scores are negatively associated with disease

progression in HIV-infected patients [3.2.1.2: Table 30], and Johrei appeared to

improve perceived quality-of-life scores [3.2.2.1: Tables 35-37].

These findings support the hypothesis that psychological intervention may alleviate the

detrimental effects of stress upon well-being; and warrant the need of further investigation on

the psycho-neuro-endocrino-immune network, particularly the influence of Johrei upon the

network.



4.2 Stress hormone associated changes in vitro in immune cells as an exemplar of

the psycho-neuro-endocrino-immune network interaction

The studies using university students and HIV-infected patients demonstrated that

psychological stress affected in vivo distribution of immune cells including NK-cells and T-cells.

There has been a growing body of evidence which suggests that cortisol (particularly interaction

with the glucocorticoid type II receptor) may play an important role in stress-induced changes

[Bauer et al., 2003] in both lymphocyte distribution [Dhabhar et al., 1996] and impaired cell-

mediated response [Bauer et al., 2001].

Hence, the effects of stress hormones (cortisol in particular) upon the immune cells were

investigated in vitro in order to examine if there are any direct interactions between the stress

hormones and immune cells which could functionally demonstrate a part of the psycho-neuro-

endocrino-immune network.

This approach consisted of two series of experiments: (1) an investigation of NK-cells and

(2) an analysis of T-cells. The functional parameters in cellular immunity [Rose, 2002], which

were reported to decrease under sustained stress, include:

1. Cytotoxic activity of NK-cells and/or cytotoxic T-cells against target cells (tumour

cells and virally infected cells) [Borella et al., 1999; Gruzelier, Smith et al., 2001;

Inoue-Sakurai et al., 2000; Maes et al., 1992; Pike et al., 1997]; and

2. T-lymphocyte proliferative responses to a mitogen, a super-antigen or specific

antigens [Silberman et al., 2002].

Hence, in this project, the effect of in vitro exposure to the stress hormone (cortisol), in

the upper physiological levels and for more than 24 hours, upon the NK cytotoxic activity and

the T-lymphocyte proliferative responses were investigated.

4.2.1 Changes in NK -cells after in vitro incubation

Using peripheral blood mononuclear cells (PBMCs), NK cytotoxic activity (NKCA) level

was investigated by using the Godoy-Ramirez’s flow cytometry method [Godoy-Ramirez et al.,

2000] to obtain a pilot result, and then examined by using the CytoTox96® which measures an

amount of released Lactate dehydrogenase (LDH) from the dead cells. These two different sets



of results from the two alternative methods of measuring NKCA levels provided a more

comprehensive account.

4.2.1.1 NK cytotoxic activity (NKCA) levels and NK-cell profiles after incubation of PBMCs

for 24 hours in vitro

NKCA levels were shown to increase after incubation of PBMCs for 24 hours and this

increased level was associated with an increased levels of the per-NK-cell cytotoxic activity but

not to an increase in cytotoxic NK-cell subset [Cooper, Fehniger & Caligiuri, 2001] numbers.

To minimise the possibility of activation caused by an interaction between antigen

presentation cells (APC) and NK-cells during the 24 hours in vitro incubation, monocytes were

removed from PBMCs by culturing for 1 hour in a plastic flask. Previously, NKCA level was

reported to be higher in the NK-cell subset adhered to plastic flasks than in the non-adherent

NK-cell subset when incubated with IL-2, and these two NK sub-sets express different

chemokine receptor profiles [Inngjerdingen et al., 2001]. The PBMCs prepared with this

monocyte depletion procedure should have removed the NK-cell subset adhered to plastic flasks

as well as monocytes, but per-NK-cell cytotoxic activity was increased in the current study, so

this suggests that there were other factors which contribute to the increase.

NK-cells are rich in their surface receptors which convey inhibition or activation signals

[Middleton et al., 2002]. The Nkp46 is known as a main activation signal for the cytotoxic

lysing activity of NK-cells, namely the Natural Cytotoxic Receptor (NCR) [Spaggiari et al.,

2001], and the expression of this receptor was shown to increase after the incubation although

the expression of the other NCR, the Nkp30, was not affected. Hence, the increased levels of the

per-NK-cell cytotoxic activity after the incubation could be on account of:

1. Increasing this Nkp46 activation signals; and/or

2. Decreasing effects of inhibitory processes of the activation by other unidentified

factors.

One possible decreasing inhibitory effect is the removal of endogenous humoral

substances (such as stress hormones) in the preparation for in vitro incubation. The plasma

separated from the PBMCs was replaced by a culture medium with a one-tenth, low

concentration of Foetal Calf Serum which contains little or no levels of endogenous cortisol.

The hypothesis that this removal of endogenous cortisol causes the activation in the levels of



per-NK-cell cytotoxic activity and the expression of the Nkp46 (and Nkp30) was investigated in

the following experiments.

4.2.1.2 Cortisol-induced changes in NKCA levels and NK-cell profiles

Cortisol was shown to inhibit the increase of the per-NK-cell cytotoxic activity after 24hrs

incubation of PBMCs and this inhibition of the increase was shown to be associated with an

inhibition of the expression of the Nkp46 (and also with the inhibition of the Nkp30) on the

cytotoxic NK-cell subsets. However, these inhibitions of the increase in the per-NK-cell

cytotoxic activity were not fully achieved in terms of their amplitude of NKCA and Nkp46

expression. This again implies that there may be other contributing factors.

Recently, in vivo studies using mice (c.f. glucocorticoid is the equivalent hormone in mice

to cortisol in human) have shown that glucocorticoid resistance can be induced by social

disruption stress (i.e. repetitive disruptions by inserting intruders into a cage to stress mice)

[Avitsur et al., 2001; Quan et al., 2001]. This glucocorticoid resistance was reported to be

associated with the reduced function in the glucocorticoid receptor in the CD11b positive

macrophages (i.e. one of major antigen presentation cells; CD11b is part of the cells’

intracellular adhesion molecules which are expressed upon activation) in association with their

impaired nuclear translocation of glucocorticoid receptor and the lack of transcriptional

suppression of NF-kB by glucocorticoid when NK-cells interact with the macrophages [Quan et

al., 2003]. It is therefore suggested that monocyte depletion cause a removal of the CD11b

positive macrophages resulting in a decrease in the inhibitory processes of the activation.

It is well-known that pharmacological levels of cortisol affect genomic manifestations in

NK-cells, for example, the levels of the Granzyme A (a major cytotoxic molecule contained in

the cytoplasm of NK-cells) have been reported to be reduced when NK-cells were exposed to

three �M of cortisol [Zhou et al., 1997]. However, there is also a growing body of evidence

which has demonstrated that there are also non-genomic cortisol effects such as the direct non-

specific non-genomic steroid action through high-affinity membrane-binding sites, i.e. cortisol

can affect the activity of NF-kB via steroid-membrane interactions without involvement of the

genomic cortisol receptor in the nucleus [Falkenstein et al., 2000]. Although these were based

on the observations when cortisol was given in pharmacological dose, there remains a

possibility that these genomic and non-genomic mechanisms of cortisol may also be involved in

the effect caused by the upper levels of physiological dosage of cortisol shown in the current

study.



These possible contributing factors remain to be elucidated in the future investigation, but

this series of experiments concluded that upper physiological level of cortisol can suppress per-

NK-cell cytotoxic activity and Nkp46 expression.

4.2.1.3 Endogenous levels of stress hormones (cortisol and DHEA-S) and NKCA

The other proposed stress-associated hormones, i.e. DHEA-S and melatonin, are known to

be antagonistic against the suppressive effects of cortisol upon lymphocytes as described in the

introduction [1.2.2.3 and 1.2.4.2], but the results demonstrated that there was no significant

relationship between endogenous levels of stress-associated hormones and the NKCA levels

before the incubation of PBMCs. However, there appeared to be positive correlations between

endogenous levels of stress-associated hormones (DHEA-S and melatonin) and the NKCA

levels after 24hrs incubation free from endogenous hormones.

This finding was hypothesised to be associated with the long term effects of the DHEA-S

and melatonin upon NK-cells in balance with a suppressive effect of cortisol. In other words,

the difference between these NKCA levels may be associated with the stage of alarm to

resistance and the stage of exhaustion in Selye’s classification [1.2.4.1]:

� NK-cells with high NKCA level after 24 hours incubation (with high levels of

DHEA-S and melatonin) may be mixture of NK-cells in a stage of alarm reaction

and resistance where cells are able to respond with both activation and inhibition

from the various factors including hormones, so they can be activated when various

inhibitory factors (including endogenous cortisol) were removed; and

� NK-cells with low NKCA level after 24 hours incubation (with low levels of

DHEA-S and melatonin) may be NK-cells in an exhausted stage, so they can not

respond.

This hypothesis can be summarised and paraphrased by stating that the suppressive

effects of cortisol upon NK-cells is counteracted by:

� DHEA-S: another major adrenocortical hormone in the HPA axis; and

� Melatonin: a major hormone associated with sleep in the circadian rhythm.

In order to test this hypothesis, the diurnal pattern in the levels of these hormones together

with cortisol and diurnal changes in the levels of NKCA both at Time 0 and 24 hours after in

vitro incubation would need to be examined, and then the association between these



combinations would need to be analysed in future in vitro studies investigating the effect of

stress-associated hormones upon NK-cells.

Nonetheless, the results support the direct interaction between stress hormones and NK-

cells as a part of the psycho-neuro-endocrino-immune network.

4.2.2 Changes in T-cells after in vitro incubation

One of major functions of T-cells in self-defence is the ability to proliferate and generate

appropriate cell phenotypes which have specific affinity against a specific antigen. One method

used to measure this ability has been the [3H]-thymidine incorporation, proliferative T-cell

response assay [Weyts et al., 1997] based on the findings that in vitro stimulation with a

mitogen, super-antigen or specific antigens activates T-cells resulting in proliferation [Antia et

al., 2003; Kaech & Ahmed, 2003; Seder & Ahmed, 2003].

It is well-known that pharmacological levels of cortisol (or glucocorticoids) can suppress

the proliferative responses of human cells [Hettmannsperger et al., 1993]. In the current study,

the upper physiological level of cortisol (250nM) was also shown to suppress T-cells’

proliferative responses against mitogen, super antigen and recall antigens, and expression of

their cell-surface markers were measured concurrently in order to investigate the possible sites

of the suppressive effects of cortisol.

4.2.2.1 Expression of CD25 during proliferative responses

The proliferative response in T-lymphocytes consists of four processes: (1) recognition of

a stimulus; (2) activating cell cycle progression; (3) process of actual cell division; and (4)

apoptosis of excessive cells. Within this process, the following two possibilities for suppressive

effect of cortisol on the proliferative responses were investigated in the current study:

1. Decreasing activation, and

2. Increasing apoptosis.

Flow cytometry technique has been introduced to examine the mechanisms of

proliferative responses using some major cell surface activation markers, i.e. CD69, CD71 and

HLA-DR, but it was shown that the expression of these markers can not be alternatives to



reflect the levels of proliferation in comparison with the method using the [3H]-thymidine

incorporation [Caruso et al., 1997; Hutchinson et al., 1999; Rutella et al., 1999].

Interleukin-2 (IL2) is known as a major cytokine to induce T-cell proliferation by binding

with the IL-2 receptor, i.e. CD25, and this IL2-CD25 interaction is also known to be essential

for T-cells to proliferate with other cytokine stimuli [Malek et al., 2001]. Hence, one of the

above hypotheses of suppressive effects of cortisol upon proliferative responses, that cortisol

decreases activation process of T-lymphocytes, was tested by examining the levels of CD25

expression on the cell surface.

The expression of CD25 in the current study showed a dramatic increase after 48 hours of

incubation with PHA or PPD, but this increased rate was again not decreased by the

physiological level of cortisol. Hence, although the possibility of impairment in other activation

markers on the cell surface, such as HLA-DR, is still to be examined in future experiments, it

appears that there may be another unidentified mechanism that has a greater impact on the

suppressive effect of cortisol in proliferative responses.

4.2.2.2 Expression of CD95 and Annexin V during proliferative response

Previously in the literature, it was reported that altering the level of cortisol in carp

lymphocytes was associated with an increase in apoptosis during the proliferation response to a

mitogen (PHA) and a super-antigen such as lipopolysaccharide (LPS) [Weyts et al., 1997]. In

their study, the rate of apoptosis was measured by the method using the TdT-mediated dUTP

nick end labelling (TUNEL) assay, so the actual apoptotic process in a nucleus was detected and

the amount of apoptotic changes was measured.

Apoptosis is known to start from either the cell-surface mechanism (e.g. a cascade

induced by CD95/Fas and CD95L/Fas-ligand contacts) or the cytoplasmic mechanism (e.g.

mitochondria releases the cytochrome C; a genomic cascade [Bedner et al., 1999] mediated by

Bax complexes within a nucleus). For the purpose of detecting apoptotic change on the cell

surface, a method using Annexin V which can bind the phosphatidylserine has been developed

[van Engeland et al., 1998]. Phosphatidylserine is one component of the cell-membrane and it is

located inside the membrane in live cells; and it comes outside of the membrane when the cell

dies and looses this tight control.



In the current study, sharp increases in the levels of the CD95 (Fas) expression on the

surface of CD4 and CD8 T-cells were observed after 24 and 48 hours in vitro incubation with

PHA or PPD, but the physiological level of cortisol did not influence these increases. Further,

the physiological level of cortisol did not affect the levels of Annexin V on the cell surface after

48 hours incubation. Hence, it was concluded that cortisol did not alter apoptotic cell surface

changes on proliferating T-lymphocytes. In order to confirm the apoptotic change by the

physiological level of cortisol further, the TUNEL assay needs to be performed.

On the other hand, in the nucleus, cortisol has been shown to inhibit the NF-�B activation

[Barnes, 1997] and to induce an early G1 phase block in cell-cycle (G1-S-G2-M) progression in

a tumour cell line [Sanchez et al., 1993] resulting in delay of the cell division. The process of

actual cell division can be measured by the method using carboxyfluorescein succinimidyl ester

(CFSE) [Lyons, 2000], in which the level of intensity of the CFSE can be measured in the

stained cells of the cytoplasm and this level halves with each cell division. Hence, future

investigation on the effect of cortisol upon T-lymphocytes should include this cell-cycle

progression analysis in addition to the further analyses of apoptotic changes.

Nevertheless, the physiological level of cortisol was shown to suppress human T-cells

proliferative responses. This may or may not increase apoptosis, but this possible increased

apoptotic change by cortisol was not detected through the change on the cell surface.

These in vitro experiments demonstrate the feasibility of the endocrino-immune network.

The in vitro model of stress was shown to suppress:

� NK-cell function, i.e. per-NK-cell cytotoxic activity to tumor cells; and

� T-cell function, i.e. proliferative response to substances related to infection.

In addition, DHEA-S (in adrenocortical hormones) and melatonin (in hormones

associated with circadian regulation) may have antagonistic associations against cortisol as

shown by their effects on NK-cell function.

These support that there is a direct relationship between hormones (cortisol, in particular,

and DHEA-S and melatonin) and immune cells (NK-cells and T-lymphocytes) and demonstrate

possible interaction within the psycho-neuro-endocrino-immune network.



4.3 Conclusions

The in vivo study using university students confirmed that exam preparations provoke

anxiety and increase stress in students. The study showed that stress perception was associated

with NK cytotoxic activity levels; and it demonstrated that psychological intervention may

buffer and/or reverse detrimental effects of stress upon the immune cells, particularly the effects

on NK-cells. The in vivo study using HIV-infected individuals confirmed that there is a steady

decline in CD4 T-cell counts in the patients who are not receiving anti-retroviral treatment; and

it demonstrated that psychological intervention may decrease this decline. These effects were

particularly associated with the training and practice of Johrei.

In addition, the decline in CD4 T-cell counts in HIV-infected patients was found to be

positively associated with declines in the perceived quality-of-life scores. Although a larger

sample size would be needed for statistical significance, Johrei appeared to improve these

quality-of-life scores. These raise a possibility that improvement of the meaning-focused coping

skills may have beneficial effects upon disease progression more than the emotion- and/or

problem-focused coping strategies.

In vitro exposure to the stress hormone, cortisol, suppressed NK-cell and T-lymphocyte

functions. Other stress-associated hormones (DHEA-S and melatonin) appeared to be

antagonistic against the effect of cortisol on NK-cell function. These showed direct interactions

of stress hormones on cells of the immune system, and demonstrate a mechanism whereby

stress could act upon the psycho-neuro-endocrino-immune network to regulate immune function.

These findings support the hypothesis that psychological intervention may counteract the

detrimental effects of stress upon psychological well-being and general health acting through an

integrated psycho-neuro-endocrino-immune network; and clearly warrant the need for further

investigation of interactions in the network, particularly the influence of Johrei upon the

network.



4.4 Future directions

In order to investigate the psycho-neuro-endocrino-immune network interactions further,

several suggestions were raised in the preceding report. This section lists those suggestions and

proposes future work.

4.4.1 Psychological interventions

� Intervention-free controls as well as relaxation control group for students study

� A larger sample size (e.g. more than 84 subjects per group for HIV-patients study)

4.4.2 Measurements

4.4.2.1 Psychological measures

Comparison analysis between two subgroups based on:

1. The midline split of the stress perception scales for the stress-related differences:

� The Perceived Stress Scale (PSS) [Cohen et al., 1983]

� The Kesseler Perceived Social Support (KPSS) [Coventry et al., 2004]

2. The criterion whether the quality-of-life scores improving or worsening for the

change in disease progression or maintenance of health:

� The Sense of Coherence (SoC) [Antonovsky, 1987]

� The Spiritual Involvement and Beliefs Scale (SIBS) [Hatch et al., 1998]

� The Pittsburgh Sleep Quality Index (PSQI) [Buysse et al., 1989]

3. A covariate factor: personality trait

� The Temperament and Character Inventory (TCI) [Cloninger et al., 1993]

4.4.2.2 Immunological measures in vivo

NK-cells: Per-NK-cell cytotoxic activity, NK-cell subset counts and percentages for

individuals with acute or sustained, but limited, stress



CD4 T-cells: Subset (Regulatory T-cell in particular) counts and percentages, functional

measures e.g. Th.1 and Th.2 cytokine productions for both healthy

individuals and patients with sustained stress

4.4.2.3 In vitro investigation on NK-cells

� CD11b positive macrophages analysis concurrently with per-NK-cell cytotoxic

activity

� NF-kB analysis with cortisol receptor (GCR) analysis

� Diurnal pattern in the endogenous stress hormone levels concurrently with the NKCA

levels both at Time 0 and 24 hours after in vitro incubation

4.4.2.4 In vitro investigation on T-lymphocytes

� Cell-cycle progression analysis (e.g. CFSE analysis)

� TUNEL assay for proliferative T-lymphocytes

4.4.3 Proposal for future in vivo study

Ethical approval and funding have been granted for a further study into the effects of

Johrei in HIV patients. The proposal aims to investigate the integrated psycho-neuro-endocrino-

immune network interactions; and to confirm and explore the major results from the Ph.D.

project that Johrei may have beneficial effect upon disease progression, (measured in CD4 T-

cell counts), in HIV-infected individuals not receiving anti-retroviral treatment [Appendix 7].

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Appendix 1: Ethics approval, information sheet and consent form

RIVERSIDE RESEARCH ETHICS COMMITTEE APPLICATION FORM

If you require more space to answer a question then please adjust the sizing

of the answer space accordingly.

Version 2003.01

Name of Lead Investigator: Prof. John H Gruzelier Department: Cognitive Neuroscience and Behaviour Address: Charing Cross Campus, Imperial College London, St Dunstan's Road, London, W6 8RF

[1] Please state project title. The Effects of Two Psychological Intervention Techniques, Self-Hypnosis and the Johrei Healing Method, on Quality of Life, Psychological Well-Being, EEG measures and Various Immunological Measures including CD4+ counts in early HIV: A Randomly Controlled Pilot Study.

[2] What question is the project seeking to answer, and what will be the value of obtaining this answer? This should also be clearly explained within the patient information sheet.

When patients are newly diagnosed with HIV, there is often a substantial period of time when their CD4+ counts are preserved, and antiretroviral treatment (ART) is not required. Patients are healthy in all other respects, and jobs and home life carries on. Over time, CD4+ counts fall and ultimately most patients start to take ART. Our primary question is whether we can prolong this state. This project seeks to investigate the possible impact upon Quality of Life, psychological well-being, various immune parameters and health status of two interventions, self-hypnosis and Johrei (a Japanese healing method). A third group will be put on a waiting list and act as ‘wait-listed' controls for the first 4 months of the study. Subjects will be randomly assigned after stratification on CD4+ levels to one of these three groups. The purposes of Johrei and self-hypnosis are similar. Each technique will be taught to participants randomly assigned to the specific intervention with the purposes of aiding in psychological adjustment to their condition, maintaining their quality of life and bolstering their immunological defence system through daily practice. In addition, cognitive assessments will be undertaken using electrophysiological (EEG) measures.

Should participants maintain this state where their CD4+ counts remain high and pharmacological treatment is still deemed unnecessary, or that their quality of life and psychological well-being is significantly better than those without the interventions, either of these two interventions could be easily added to treatment protocols in early HIV.

These two interventions are in addition to best conventional medical care given by the Chelsea & Westminster Healthcare NHS Trust, and will be administered with the participation of clinicians involved in the patients’ care.



[3] Please provide an outline of the project, this should include procedures to be used, measures to be made, justification of sample size & plans for statistical analysis. [Paras2.1 -2.8]

The two interventions are self-hypnosis and the Johrei healing method from Japan. Hypnosis is a well-recognised medically accepted psychological intervention. It has been used in many studies with medical conditions and our laboratory has carried out a series of interventionist hypnosis studies (Fox et al, 1999, Gruzelier et al, 2001, Laidlaw et al., 2003). It has been used in symptom control in various medical conditions, including pain control, and in normalising the immune system when under stress (Gruzelier et al., 2001). It has provided a buffer in the face of stress (Gruzelier et al, 2001, Laidlaw et al., 2003). In the present study, hypnosis will be taught as a skill so it can be practised in the form of self-hypnosis in the privacy of the participants' own homes. On-going support and supervision will be provided throughout the study period. Self-hypnosis will be taught by an expert in medical hypnosis. In Japan and many other countries, some 3 million people practise the Johrei lifestyle and healing method. It is primarily practised in the family setting and involves a healthy life-style and appreciation of beauty. In the first published Johrei study, medical students illustrated that practising Johrei provided help in coping with exam stress. An introduction to Johrei will be taught to participants, and supervision for participant and family member or another support person will be provided throughout the study period, as in the Hypnosis condition. Johrei will be taught by a medical doctor who has been trained in Johrei and practised it since childhood. The four areas of outcome measures are immunological variables, psychological variables, cognitive variables and, for the term of the study, markers of progression of disease, assessed pre-intervention and at the finish of the study. At the beginning of the study, all participants will provide descriptive, which will include demographic details and medical histories. Study design This randomised controlled trial will include 150 patients who have been diagnosed with HIV but are naïve-to-treatment, meaning that their CD4+ counts are sufficiently high that ART is not indicated. Realistically, this means that the CD4+ count is < 400 but above 200 (irrespective of viral load). The study duration for each participant is approximately 5 months. The planned monthly intake is of 6 – 9 patients to each of the three groups (i.e. 18 - 27 new people each month). The three groups will be recruited through Dr Simon Barton and his clinical colleagues at Chelsea & Westminster Healthcare NHS Trust. An independent statistician will randomly assign participants to either one of the two intervention groups or the wait-listed control group using a stratified randomisation on CD4+ counts. Outcome measures will include the psychological questionnaires, blood and urine samples for immune assays, and cognitive data detailed below and illustrated in the diagram following. Basically, the design involves 8 sessions with three major assessment points over, at the most, six months. The first four sessions in the first month are intervention intensive, followed by 4 monthly follow-up sessions. Each training session will take about 2 hours and is planned to be held after working hours at the Charing Cross Campus site. Participants will be recruited monthly to be in training groups of 6 – 9. The three assessment points include all the immunological and psychological tests described below and designated as outcome measures. INTERVENTION GROUPS SCHEDULE 1 2 3 4 5 6 7 Intervention sessions (first 4 are weekly, last 3 monthly)

� � � � � � �

1 &2 3 Main assessment points

End of Month: 1 2 3 4 Time



WAIT-LISTED CONTROL SCHEDULE:

0 1 2 3 4 5 6 7 Intervention sessions

� � � � � � �

1 &2 3 4 Main assessment points

End of Month: 1 2 3 4 5 6 7 8 Time

Assessment variables: Psychological variables: Series 1 (those not needing repetition) Hypnotisability and imaginative abilities: Creative Imagination Scale (Wilson & Barber, 1978), and Stanford Hypnotic Susceptibility Scale (Form-C) (Weisenhoffer & Hilgard, 1962). It is hypothesised that hypnotisability or ability to visualise will influence the outcome variables (Laidlaw et al., 1996) Personality: To study personality types and coping styles in relation to prognosis. (Watson et al., 1984). Assessed with the Marlowe-Crowne Social Desirability Scale (Crowne & Marlowe, 1960) and the Courtold: (Barger, Kircher & Croyle, 1997). Trait anxiety from Spielberger's STAI (Spielberger, Gorsuch & Lushene, 1970), and Personality Syndrome Questionnaire (Gruzelier, 2000) Social Support: Social support has been linked to mental health of patients. It can be easily assessed with the 10-min Significant Others Scale (Powers, Campion & Aris, 1988). Further to this is a scale to assess spirituality (Hatch et al., 1998). Psychological variables: Series 2 (dependent variables) Depression and anxiety: Beck Depression Inventory (BDI, Beck, 1990) arguably the most well-used instrument to assess depression in clinical studies, as is the State Trait Anxiety Inventory (STAI, Spielberger, Gorsuch & Lushene, 1970) for anxiety. PTSD- like symptoms: Impact of Event Scale (IES, Horowitz, Wilner, & Alvarez, 1979) used with HIV diagnosis as event in Nordin, Bergland, Glimelius & Sjoden, 2001. Can identify intrusive thoughts (associated with high cortisol which can have negative effects on immuno-regulation). Perceived Stress Scale (PSS). Quality of life and activity levels: WHOQOL (World Health Organisation, 1996) internationally used screen for quality of life changes and the SF36 (Jenkinson et al.,1994), a well-used generalised instrument for quality of life. Coping : The COPE, a multidimensional coping inventory (Carver, Scheier & Weintraub, 1989) includes information about turning to spiritual sources, denial and disengagement among other sub-scales, which are of interest in this study. Locus of Control. Psychological variables: Series 3 (continuous data) Diary data: Personalised Emotional Index (PEI, Laidlaw, 1999). Used with patients (Laidlaw, 2001). Mood parameters both positive and negative: anxious, energetic, tired, confident, unsure, elated, depressed, agreeable, hostile, clear-headed and ineffective rated on a Likert scale as a 5-min daily diary. Additional questions include sleep quality, homework practice, health status, as moderator variables that could influence outcome measures. External factors: space for qualitative comments after the prompt: 'Anything different happen today?' rated by researchers on a -3 to +3 scale.



Cognitive variables Neuropsychophysiological studies would include electroencephalographic (EEG), and electrodermal activity (EDA). These studies will address the following issues: Lateralised brain function and its relationship with immune status, mood, coping style, and response to intervention in patients: We hypothesise a relationship among these variables based on earlier work with HIV infection (Gruzelier et al., 1996) which showed that hemispheric asymmetry measures predicted immune competence and were correlated with mood status (also see Davidson and Tomarken, 1989; Kang et al.,1991; Wheeler et al.,1993; Lane et al.,1997;.Papousek and Schulter, 2001; Gruzelier et al., 2001) Immunological markers: - CD profile including numbers and percentages of CD3, CD4, CD45RA/RO, CD8, CD16 and

CD56 (Van der Pompe et al. 1997). & CD4 absolute count, CD4/CD8 ratio and HIV viral load as a marker of disease progression.

- NK cell activity as markers of anti-infection in innate immunity (Evans et al. 2000) - Cortisol (urine) as a marker of chronic stress and stimulator of Th2 (Dhabhar et al. 2001,

Evans et al. 2000, Schedlowski et al.1994) - DHEA (urine) as a marker of Th1/Th2 balance with Cortisol (Evans et al. 2000) - Melatonin (urine) correlating with sleep quality and might be a immune stimulating (Th1

predominantly) hormone (Maestroni 2001) - MAO-AI (as a marker of catecholamine secretion), INF-gamma, IL-2, Soluble IL-2 receptor

(as a Th1 dominant cytokine), IL-4, IL-10 (as a Th2 dominant cytokine) (serum), IL-6, CRP (as a marker of inflammation).

SAMPLE SIZE CALCULATION: The between group comparisons will take place using Johrei, hypnosis and control group data from groups sizes of 50 participant each. The within group data can include those participants who have been in the control groups prior to being randomly assigned to either Johrei or self-hypnosis. This will provide up to 75 participants in each of the two intervention groups. These numbers come from a power analysis using STATISTICAL ANALYSIS: Statistics will be calculated using SPSS v 11. Multivariate analyses will be used in the between-group comparisons, and repeated measures and correlational analyses for the within-group changes.

[4] Please specify the source and type of subjects to be recruited and how this will be done. Also state the expected numbers to be recruited.

150 patient volunteers will be recruited on a continuous basis from the clinics where they receive their diagnosis under the supervision of investigator and clinician Dr Simon Barton. Recruitment will be via a Research Nurse or by one of the investigators. Inclusion criteria include: 1. HIV positive 2. Age 18 – 70 3. CD4+ counts > 200. Exclusion criteria include: 1. On ART. 2. Abusing drugs or alcohol. 3. In another trial which would conflict.

[5] What will be the duration of the project and where will it be undertaken? The project will take place at the Department of Cognitive Neuroscience & Behaviour, 10th floor of the Lab block, Charing Cross Campus of Imperial College London. It will commence when Ethics approval is gained, and continue until 150 patient volunteers have completed their training. It is estimated that this will take approximately 18 months.

[6] Within this project, what treatment and procedures will be performed on subjects that are extra to normal patient care? These details should be clearly stated in the patient information form.



There are no specific treatment strategies for HIV positive patients at this stage of their disease. Normal care includes the monitoring of their CD4+ levels. ART will commence when appropriate. In addition to this monitoring, patients will be offered a chance of participating in this project, which offers training in one of self-hypnosis, or Johrei as described above.

[7] Please state the potential hazards to subjects, if any. What is the probability of these occurring? What precautions will be taken to meet them? This information should be clearly stated in the patient information form.

No potential hazards. [8] What procedures, if any, may cause discomfort or distress to subjects? What

degree of discomfort or distress may this entail? What is the probability of such discomfort or distress occurring? This information should be clearly stated in the patient information form.

Anecdotally, initial sessions of Johrei occasionally have been associated with minor symptoms of headache or congestion. This was not observed in either of the previous Johrei studies done at Imperial College.

[9] Please state the personal experience of the investigator in the field concerned. Prof Gruzelier has extensive research experience in the field of HIV (Baldeweg, Catalan et al, 1995, Baldeweg, Riccio et al, 1995, Gruzelier et al., 1996, Baldeweg et al, 1997). He has published many papers about hypnosis including its use as an intervention agent (Gruzelier et al., 2001; Fox et al, 1999), as has Dr Laidlaw (Laidlaw & Willett, 2002; Laidlaw, 1999). His research team has conducted two previous studies using similar designs to the present study involving both Johrei and self-hypnosis (one completed RR 2883, Laidlaw et al, 2003 and one ongoing, RR2959.).

[10] Written consent should be standard practice, please enclose copies of the consent form and information sheet. If non-written consent is proposed then this must be justified to the Committee. [Paras 3.1 -3.3] If a routine clinical procedure precedes or follows what is proposed to be done by way of this application, the Information and Consent Forms for those procedures should be also included with Patient Information and Consent forms for this application.

n/a [11a] Have the consultants responsible for the overall care of the patient been

informed and their approval given?

Dr Simon Barton is the consultant responsible and is a current investigator in this application.

[11b] Have you gone through the appropriate process within the Clinical Directorate in which you wish to undertake your research?

Yes and received approval from the research committee, November, 2002. [11c] Will the subjects' General Practitioner be informed of the recruitment of the

subject before the study begins? Is the subjects consent to this information being passed as a condition of participation?

[12] Please state any interest, i.e., of profit, personal or departmental, financial or otherwise, relating to the study. [Paras 7.1 -7.2]

None.

[13] Does the study involve the administration or application of a medicinal product or substance? [Para 5.1-5.3]

Yes No �



[15] Please list all staff involved with this project - all staff must sign this section:

Name & Title Signature Qualification(s) Involvement

Prof JH Gruzelier

PhD Principle investigator

Dr TM Laidlaw

PhD Overall supervision of data collection and patient interaction with the study.

Training in self-hypnosis

Dr A Naito MD and PhD candidate

Training in Johrei and immunological lab work.

Dr P Dwivedi

PhD EEG data collection and analysis.

Dr D Henderson

PhD Supervision of immunological lab work

Dr Simon Barton

MD Clinician responsible for patient treatment.

Research Assistant

to be appointed Data input, recruitment, lab assistance.

Date of submission:

1 February 2003

Signature of Investigator:

Name: Prof JH Gruzelier

Address: Dept of Cognitive Neuroscience & Behaviour, Charing Cross Campus, Imperial College London, St Dunstan's Road, London, W6 8RF

Contact Tel & Bleep No:

0208 846 7386

Clinical Team in which Investigator works: n/a Other Clinical Teams/Dept involved in research: Chelsea & Westminster Hospital

Name and Signature of Consultant, GP or Community Physician in overall charge. (You are reminded that by signing this form you take responsibility for the contents and accuracy of this Ethics Committee Application. You must be medically qualified): Dr Simon Barton



Participant Information Sheet

Study Title

The Effects of Two Psychological Intervention Techniques, Self-Hypnosis and the Johrei Healing Method, on Quality of Life, Psychological Well-Being, EEG measures and Various Immunological Measures in HIV: A Randomly

Controlled Pilot Study (or ‘The Self-hypnosis and Johrei Study’) Invitation paragraph You are being invited to take part in a research study. Before you decide, it is important for you to understand why the research is being done and what it will involve. Please take time to read the following information carefully and discuss it with friends, relatives and your GP if you wish. Ask us if there is anything that is not clear or if you would like more information. Take time to decide whether or not you wish to take part. Consumers for Ethics in Research (CERES) publish a leaflet entitled ‘Medical Research and You’ . This leaflet gives more information about medical research and looks at some questions you may want to ask. A copy may be obtained from CERES, PO Box 1365, London N16 0BW. What is the purpose of the study? We would like to invite you to be a participant in a 5-month long study that is intended to find out whether the addition of self-hypnosis or a healing method called Johrei to the regular treatment you receive at Chelsea and Westminster Hospital will help clinically or in your quality of life. Why have I been chosen? We would like to examine the efficacy of psychological interventions on the quality of life in HIV patients, so you have been invited to participate in the project. It is up to you to decide whether or not to take part. If you do decide to take part you will be given this information sheet to keep and be asked to sign a consent form. If you decide to take part you are still free to withdraw at any time and without giving a reason. Refusal to participate or subsequent withdrawal will not affect the standard of care you receive. What will happen to me if I take part? This research project is designed as a randomised trial. Sometimes because we do not know which way of treating patients is best, we need to make comparisons. In a randomised trial, people will be put into groups and then compared. The groups are selected by a computer that has no information about the individual – i.e. by chance. Patients in each group then have a different treatment and these are compared.

Dr TM Laidlaw Department of Cognitive Neuroscience & Behaviour Charing Cross Hospital St Dunstan’s Road LONDON W6 8RP



In this research project, you will be randomly assigned to one of three groups: self-hypnosis or Johrei which is a non-touch healing method from Japan and a waiting list before you are assigned to either self-hypnosis or Johrei. Please read the descriptions for all three groups. One-third of the people in the study will be put onto the waiting list to have their training in 4 months time, during which, if you are in this group, you will be asked to complete some psychological tests. This delay for some participants provides a comparison for the effects of training over the 4 months, a necessary requirement in a scientific study of this type. The remainder (2/3rds of people in the study) will have their training more-or-less immediately. You must feel all right about participating in either the immediate or delayed condition, as you could be randomly assigned to either. Meeting schedule: Sessions 1 to 4 are held weekly (2 hours each). Sessions 5 to 14 are held once a month (1 hour each). INTERVENTION GROUP’S SCHEDULE

1 2 3 4 5 6 7 Intervention sessions (first 4 are weekly, last 3 monthly)

� � � � � � �

1 &2 3 Main assessment points

End of Month: 1 2 3 4 Time

WAIT-LISTED CONTROL SCHEDULE:

0 1 2 3 4 5 6 7 Intervention sessions

� � � � � � �

1 &2 3 4 Main assessment points

End of Month: 1 2 3 4 5 6 7 8 Time

If you are in the wait-listed group, you will have your first EEG and testing session, and after 4 months you will enter into the sequence as detailed above. The main collections of data will be composed of paper-and-pencil test results about how you are feeling and coping, blood samples to monitor your stress levels and a brain wave study. All participants will be asked to give blood samples (20 mls) and fill out questionnaires both at the beginning of the project, at three months and follow-up (at 6 months) for further hormone and immune analysis. The measurements will include for some of you an EEG (electroencephalograph) which records the electrical activity of one’s brain. This is a completely non-invasive procedure, which involves the attachment of various electrodes to your head using a cap and some gel. Please note that the electrodes are placed on the surface of the skin only and there is no danger of electric shock.



Following attachment of the electrodes, you will be seated in front of a computer monitor and instructed to do certain tasks such as remembering some words and faces presented on the computer screen. There will be three EEG recording sessions spread throughout a whole period of the study each lasting about two hours. All details and data resulting from the study will remain strictly confidential. The two sets of training are in Self-Hypnosis and Johrei : Self-Hypnosis: Hypnosis is an altered state of consciousness that can feel like deep relaxation

during which a person can use their imagination in a powerful way. Several research studies have shown that many, although not all, people can control their pain and affect their emotions, and even alter their immune systems, determined by how they use the hypnotic state. One recent study by Dr Michael Antoni of the University of Miami showed that patients with HIV had, on average, a better quality of life, and indeed, many positively affected their immune system with a group programme including self-hypnosis, similar to the one we plan for those of you randomly assigned to this arm of the study. We think that such a programme should be properly tested here in London. If you are assigned to the hypnosis condition, you will first experience hypnosis, then learn how to use self-hypnosis. Various possible goals will be discussed and you will be taught how to use self-hypnosis for the goals you choose. You will be asked to practice your self-hypnosis daily during the project.

Johrei: Johrei is a Japanese healing method. Anyone can learn to do Johrei after

understanding the core principles and basic techniques. Healing methods have many variations and Johrei is based on the concept of ‘healing oneself by healing others’ using a non-touching method. Johrei has just begun to be scientifically tested with some encouraging results. Millions of people around the world use Johrei to improve their health, including people with HIV. During your time in the project, you will learn these techniques. Johrei is said to relieve symptoms, even though some people for a day or so as they learn the techniques can experience brief, minor discomfort such as mild symptoms of headache, sweating or diarrhoea, although we have seen none of this here in our previous studies. During the project, you will be asked to practise Johrei every day with someone (partner, daughter, friend etc.).

If you agree to participate, you will be one of 150 people like yourself with diagnosed HIV who will be invited to participate in the project. You, along with the others, will complete various tests, and will have your EEG (brain-waves) measured. You will have these tests at the beginning, and again at four - five months for a repeat set of tests. However, you will meet regularly in a group of 6 - 9 other study subjects if you are assigned to learn self-hypnosis or Johrei. In self-hypnosis, the group co-ordinator will be Dr Tannis Laidlaw, a psychologist with extensive experience in clinical hypnosis. If you are in the Johrei group, you will be trained by Dr Akira Naito, a doctor trained in both western medicine and the Johrei healing method. If you are in the waiting list group, you will be randomly assigned to either Johrei or self-hypnosis in 3 months time when you will join with others in the training. All the brain wave studies will be with Dr Prabuddh Dwivedi, who is a clinical psychologist with specialised knowledge of conducting EEG studies. The Self-hypnosis, Johrei and EEGs will be performed at the Charing Cross Hospital. Self-hypnosis or Johrei schedule: If you are in either of the self-hypnosis or Johrei groups, you will meet together with the other participants and your group co-ordinator one session a week for four weeks (1 to 4 on



the diagram above). You will learn self-hypnosis or Johrei in order to begin practice at home. A small daily diary will be created specifically for you, to be filled out at the end of each day (taking about 2 minutes) and kept for the duration of the project. After this month of weekly meetings, the shorter meetings will be spaced at one meeting a month for the duration of the project, and you are welcome to continue past your final assessment point. Altogether, you will have three testing sessions for EEG and two for psychological testing, lasting about 2 hours. The testing is for the purpose of monitoring your progress and your response to self-hypnosis or Johrei. When you attend our department on the 10th floor of the medical school for your EEG testing you will have plenty of time to fill out the psychological tests. They are not onerous and there are no right or wrong answers, although your opinion will be sought about many different aspects of your experience. Assessment times involving psychological tests and EEG are indicated by the arrows labelled 1,2 and 3. What do I have to do? There are no lifestyle restrictions. No special change is required for this specific study in your lifestyle other than incorporating into your daily schedule some time to practice your self-hypnosis or Johrei. What is the drug or procedure that is being tested? You will not be given any drugs in addition to your usual medications. What are the alternatives for diagnosis or treatment? You should feel free to ask your GP about your diagnosis and any alternative treatment for it. What are the side effects of taking part? We expect no side effects. What are the possible benefits of taking part? We hope that both interventions will help you. However, this cannot be guaranteed. The information we get from this study may help us to better treat future patients with HIV. What if new information becomes available?

Sometimes during the course of a research project new information becomes available about the treatment/drug that is being studied. If this happens, your research doctor will tell you about it and discuss with you whether you want to continue in the study. You may decide to withdraw but if you decide to continue in the study you will be asked to sign an updated consent form.

Alternatively, on receiving new information you research doctor might consider it to be in your best interests to withdraw you from the study. He/she will explain the reasons and arrange for your care to continue.

What happens when the research study stops?



The intension is that you will be independent in your self-hypnosis and Johrei skills and will not need further instruction. However, a list of qualified practitioners in London can be made available to you on completion of the study. What if something goes wrong?

If taking part in this research project harms you, there are no special compensation arrangements. If you are harmed due to someone’s negligence, then you may have grounds for legal action but you may have to pay for it. Regardless of this, if you wish to complain about any aspect of the way you have been approached or treated during the course of this study, the normal NHS complaints mechanisms may be available to you. Will my taking part in this study be kept confidential?

All information that is collected about you during the course of the research will be kept strictly confidential. All information about you will be kept securely at Imperial College, Charing Cross Hospital, London, and under personal supervision of the researchers when being transported from Chelsea & Westminster Hospital to Charing Cross Hospital.

What will happen to the results of the research study?

The results of this study are intended to provide new information about the treatment of people with newly diagnosed HIV, and will be published as academic papers in professional journals. It will be the basis of talks at conferences around the world. No names or other identifying aspects of the participants will be disclosed during any of these communications.

Who is organising and funding the research?

This research is sponsored by the organisation that teaches Johrei in Japan. It is organised by the Dept. of Cognitive Neuroscience and Behaviour, Imperial College London.

Who has reviewed this study? The Riverside Research Ethics Committee reviewed the study.

Contact for further information Dr Tannis Laidlaw can answer any further questions on 0208 846 7042 or email: [email protected] Thank you for considering taking part in our research project. Please take this information sheet home with you.



PARTICIPANT CONSENT FORM Title of Project:

The Effects of Two Psychological Intervention Techniques, Self-Hypnosis and the Johrei Healing Method, on Quality of Life, Psychological Well-Being, EEG measures and Various Immunological Measures in HIV: A Randomly

Controlled Pilot Study. (The patient/volunteer should complete the whole of this sheet him/herself) Have you read the Information Sheet? Yes No Have you had the opportunity to ask questions and discuss the study? Yes No Have you received satisfactory answers to all of your questions? Yes No Have you received enough information about the study? Yes No Whom have you spoken to? (write name) __________________________________ Do you understand that you are free to withdraw from the study, at any time, without having to give a reason, and without affecting the quality of your present or future medical care? Yes No Do you agree to take part in this study? Yes No I understand that the Local Ethics Committee may review this form as part of a monitoring process. NAME IN BLOCK LETTERS:

___________________________________________ Contacts: Address: _______________________________________________

Telephone number(s): _______________________________________________

Email: _______________________________________________ Signature: __________________________________Date: ____ / _____ / _______

Dr TM Laidlaw Department of Cognitive Neuroscience & Behaviour Faculty of Medicine Imperial College of Science, Technology and Medicine St Dunstan’s Road LONDON W6 8RP



Appendix 2: Psychological training intervention protocols

1. Self hypnosis training

� Session plans 227

� Instructor manual (with scrip of self-hypnosis for audio-recording) 230

2. Johrei training

� Course description 253

� One-hour Introductory Seminar Powerpoint Presentation (with notes:

as an example of, extract from, the explanation in the Johrei training

sessions) 256

� Johrei Handbook 272



��

Dr . Tannis M. Laidlaw




Self-hypnosis Group

Session 1: Instant Relaxation

1. Name tags 2. Introductions of people including me. 3. Topic of the Day: Introduction to hypnosis and PNI

- Story of my PhD - Story of using hypnosis in infections - Imagery to be used

4. Hypnosis Session 1: Instant Relaxation

� Hypnosis Session 1: ‘Introduction’ � The Hypnosis Procedure: ‘The Beaker Diagram’

Session 2: Viewing things differently to regain control

5. De-Bugging Negative Thoughts Record 6. Hypnosis Session 2: ‘Symbol’

Session 3: Breathing Away Anxiety and Panic

7. The Feedback Loop of Negative Thoughts � Physiological Reactions to Stress � Muscles becoming tense or weak � Some Catastrophic Thoughts � The Breathing Triangle

8. Hypnosis Session 3: ‘Sharks ’n’ Bats’ Session 4: Getting rid of pesky thoughts

9. Step-by-step Instructions for the Interrupt Distraction Procedure 10. Hypnosis Session 4: ‘Coastline’

Post-training Tracks: To provide some variety…

11. Hypnosis Post Training Sessions:

5: ‘Blue’ 6: ‘Beach’ 7: ‘Thrugmutton’



Welcome to the world of self-hypnosis.

Self-hypnosis is a very useful technique that has

been part of self-healing for millennia. In this

course of 4 sessions, you will learn how to use self-

hypnosis to enhance your immune system, to

control acute anxiety and to stop old thoughts

bothering you. Self-hypnosis can be used for many

other types of changes people want to make as well, but this set of sessions is aimed at stress

control and disease control from within.

Each session will be described in detail as we believe that it is beneficial to know and

understand what lies behind each instruction you hear on the CD tracks. Please read each

session notes before you use the appropriate CD track. This will enhance your participation and

allow you to get the most benefit from each session.



Session 1 : Instant Relaxation

Relaxation is an integral part of the type of self-hypnosis we are teaching in this module. The

first technique we would like you to master is a very quick method of achieving a degree of

relaxation. It takes only seconds to do, so is titled ‘instant relaxation’. It can be used on its own

or as a preliminary to entering into self-hypnosis, so will prove to be useful to you in the future.

Instructions for Instant Relaxation

�

�

�

�

�

�

� �



Hypnosis Session 1: ‘Introduction’



The Re-Alerting

Process

Stretch Relaxatio

WORK

6 . . . . .

0

The

Deepening

The Hypnosis Procedure: ‘The Beaker Diagram’

� � � � � � � � �

Session 2 : Viewing things differently to regain control

When we have negative thoughts, we have a tendency to focus on them to the exclusion of other

neutral or more positive thoughts. The consequence of this is that before you know it, the

negative thought has grown in intensity and is affecting your sense of control. These negative

thoughts can be debilitating and can make you miserable, affecting your self-esteem and self-

confidence. In addition, when we have negative thoughts we also interpret change in a negative

way, our attention to negative events is heightened and importantly, we forget about or don’t

notice any good things going on.

0

. . . . . 6



The problem of repeated negative thoughts is slightly different. A method for overcoming the

habit of persistent negative thinking is through the ‘De-bugging Thoughts Record’, an example

of which is found on page 263. On this record, you write down what the repetitive negative

thought is. Be as accurate as you possibly can. Note down what type of circumstances trigger

off the negative thought in the next column. Then rate on a 10-point scale how distressing the

negative thought is to you, that is give it a score from 0 to 10, where 0 would mean that the

thought causes absolutely no stress whatsoever and 1 is mile stress with 10 standing for a

negative thought that is as stressful as could be.



Figure 2: De-Bugging Negative Thoughts Record

Bothersome Thought Circumstances 0 – 10 Substitute Thought 0 - 10 I am useless at everything

In work, just had argument with boss over a report I produced that he criticised

9

I am very good at gathering the information but could brush up on computer skills

5

Hypnosis Session 2: ‘Symbol’



Session 3 : Breathing Away Anxiety and Panic

Often when we are faced with stress we notice changes in our body’s physiology. These

changes are normal and happen to everyone. We tend to notice only some changes, and

sometimes don’t notice them at all. But the changes are there due to the hormones that are

released when we are under stress. The degree of physiological reaction will depend on how

stressful we perceive the event to be, and on how well we can cope with the stress. Remember,

sometimes people can be faced with the same stress, but their reactions to that same stress are

individual.



When faced with stress we often notice these changes in our body. The table below shows some

of the more obvious changes people experience.

Physiological Reactions to Stress

Muscles becoming tense or weak

Heart pounding



Some Catastrophic Thoughts



The Breathing Triangle

Start



Diagram 3: The Feedback Loop of Negative Thoughts

Bad thought

Adrenalin surge

(‘Fight or Flight’) Physiological reactions:

Tense muscles

Heart rate up

Jittery

1. Breathing up

2. Carbon dioxide levels go down

3. Blood gases make the blood alkali.

4. Affects every cell in the body

5. We feel it mostly in our neurons.

6. We can experience a VERY BAD THOUGHT



Hypnosis Session 3: ‘Sharks’n’Bats’

This most popular of our tracks on the CD is based upon solid clinical practice and some

interesting scientific experiments. Here, we are encouraged to use our imagination to actually

influence the workings of the immune system. We do this very simply with self-generated

images that mean something to us for the reason that we make them up to suit ourselves. The

traditional immune-stimulating imagery uses the image of little sharks patrolling the blood

stream cleaning up any cancerous or infected matter that should not be there. You will meet

these little sharks in this track.

The track starts in a familiar way. Your eyes are encouraged to close, and the deepening is the

usual countdown from 6 to 0. You then go to a quiet and peaceful place where you can do some

work on your immune system.

The first images are to visualise a factory with an assembly line that produces t-cells. You will

have to imagine what this is like. Then, you can have the factory speed up production; it can

make immune cells that are strong and healthy and that know what to do in the body.



Session 4 : Getting rid of pesky thoughts



Step-by-step Instructions for the Interrupt Distraction Procedure



Hypnosis Session 4: Using The ‘IDP’



0-10 rating

0

1

2

3

4

5

6

7

8

9

1 2 3 4 5 6 7 8 9 10 11

0-10 rating

0

1

2

3

4

5

6

7

8

9

1 2 3 4 5 6 7 8 9 10 11

0-10 r at i ng

0

1

2

3

4

5

6

7

8

1 2 3 4 5 6 7 8 9 10 11



01457

839363

07000560309 BSMDH Mets & South (ph 0208 905 4342) or

BSMDH Scotland (ph 0141 556 1606). The websites

Hypnosis Session 4: ‘Coastline’

Post-training Tracks: To provide some variety…



Post Training: ‘Blue’

Post Training: ‘Beach’

Post Training: ‘Thrugmutton’



[email protected]

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a d

aily

hea

lth m

ain

ten

ance

tech

niq

ue

S

tudy

det

ails

: �

Jo

hre

i is a

hea

ling m

eth

od w

ith th

e co

nce

pt o

f ‘hea

l on

esel

f by

hea

ling

oth

ers

’ for

sel

f-car

e o

r m

ain

tain

ing

hea

lth &

hap

pin

ess.

�

S

tud

yin

g th

e su

bje

ct p

rovi

des

a w

ay

for

you

to b

alan

ce y

our

min

d &

bod

y in

dai

ly li

fe.

�

You

will

fin

d s

ome

ap

plic

atio

ns

of J

ohre

i fo

r yo

ur

dai

ly li

fe in

this

cou

rse.

T

he s

tudy

-sub

ject

can

be

divi

ded

into

two

part

s:

1.

Th

e st

ud

y of

Dai

ly J

ohre

i, in

clu

din

g te

chn

iqu

es h

ow to

per

form

the

hea

ling

met

hod

in a

co

mp

eten

t man

ner

.

2.

A s

tud

y o

f th

e p

hilo

sop

hy

& p

rinci

ple

s o

f Jo

hre

i, lo

oki

ng

par

ticu

larl

y at

the

wa

y th

e h

ealin

g p

roce

ss ta

kes

pla

ce a

nd

the

sign

ifica

nce

of t

hes

e m

ean

ings

in r

eal l

ife.

T

hose

two e

lem

ents

are

see

n as

inte

r-c

onne

ctin

g. It

pro

vide

s yo

u w

ith a

n op

port

unity

to a

pply

thes

e te

chni

ques

& p

hilo

soph

y in

to d

aily

life

.

Aim

s a

nd

Ob

ject

ive

s o

f D

aily

Jo

hre

i c

ou

rse

Ove

rall

A

ims:

T

o in

trod

uce

the

bas

ic c

once

pts

of J

ohre

i ph

iloso

ph

y, p

rinci

ple

s an

d p

ract

ice

T

o p

rovi

de

opp

ortu

niti

es, e

nco

ura

gem

ent a

nd

insp

iratio

n to

the

par

ticip

ants

to a

pp

ly J

ohre

i Art

of

Livi

ng

an

d J

ohre

i pra

ctic

e to

dai

ly li

fe.

T

o en

sure

the

par

ticip

ants

are

ab

le t

o gi

ve D

aily

Joh

rei c

omp

eten

tly a

nd

in s

afe

ma

nn

erin

a n

on-p

rofe

ssio

nal

cap

acity

.

Out

com

es: A

t th

e en

d o

f th

e co

urs

e p

artic

ipan

ts w

ill b

e ab

le to

: -

1. Id

entif

y th

e b

asic

prin

cip

les

and

cor

e co

nce

pts

of J

ohre

i

2. G

ive

dai

ly J

ohre

i com

pet

ently

in a

non-p

rofe

ssio

nal

cap

acity

3. S

tate

the

mai

n a

spec

ts c

once

rnin

g th

e sa

fe p

ract

ice

of J

ohre

i

4. B

e aw

are

of o

pp

ortu

niti

es in

the

futu

re fo

r re

info

rcin

g an

d fu

rth

er u

nd

erst

and

ing

of J

ohre

i ph

iloso

ph

y an

d p

ract

ice.

- 2

54 -

Ses

sion

1 A

ims:

T

o p

rovi

de

an o

verv

iew

an

d p

ract

ical

intr

odu

ctio

n to

Joh

rei

O

utco

mes

: At t

he

end

of

the

sess

ion

par

ticip

ants

will

be

able

to:

-

1. S

tate

the

mai

n e

lem

ents

of J

ohre

i as

a h

olis

tic w

ay

tow

ard

s h

ealth

ier

life

sty

le(3

fou

nd

atio

n, J

ohre

i vie

wp

oin

t of

illn

ess)

2. I

den

tify

how

Joh

rei m

ay

be

use

d in

dai

ly li

fe (

mea

nin

g o

f ‘Sp

iritu

ality

’, T

un

ing-

in,

Pra

ctic

al J

ohre

i) 3

. Dem

onst

rate

the

esse

ntia

l ele

men

ts o

f Jo

hre

i as

a d

aily

pra

ctic

e (

Dai

ly J

ohre

i tec

hniq

ues

) S

essi

on 2

Aim

s:

To

intr

odu

ce th

e b

asic

prin

cip

les

and

a c

ore

ph

iloso

ph

y su

pp

ortin

g Jo

hre

i pra

ctic

e an

d it

s ap

plic

atio

n fo

r d

aily

life

.

Out

com

es: A

t th

e en

d o

f th

e se

ssio

n p

artic

ipan

ts w

ill b

e ab

le to

: -

1. Id

entif

y th

e b

asic

prin

cip

les

supp

ortin

g Jo

hre

i pra

ctic

e (sp

irit p

rece

des

ph

ysic

al, t

oxi

ns

and

clo

ud

s, p

roce

ss o

f pu

rific

atio

n,

IZU

NO

ME

)

2. B

e aw

are

of ‘M

AK

OT

O’

(love

, si

nce

rity

and

inte

grity)

as a

co

re c

once

pt o

f Jo

hre

i ph

iloso

ph

y an

d p

ract

ice.

3

. Sta

te th

e fiv

e fi

nge

r ru

les

of J

ohre

i

4. R

ecog

nis

e the

brie

f his

toric

al b

ackg

rou

nd

of J

ohre

i an

d a

pp

reci

ate

the

wo

rks

of M

oki

chi O

kad

a

5. B

e aw

are

of th

e im

por

tan

ce o

f in

ten

tion

so

that

the

y ca

n a

pp

ly v

isu

alis

atio

n in

to J

oh

rei p

ract

ice

6

. Dem

onst

rate

a b

asic

tech

niq

ues

of J

ohre

i with

vis

ual

isat

ion

S

essi

on 3

Aim

s:

To

exp

lore

the

wid

er a

spec

ts o

f Jo

hre

i ph

iloso

ph

y em

bra

cin

g th

e va

lue

of a

rt a

nd

bea

uty

fo

r b

oth

insp

iratio

n a

nd

wel

l-b

ein

g T

o e

xplo

re J

ohre

i ph

iloso

ph

y of

nu

triti

on a

nd

the

valu

e of

a li

fest

yle

in h

arm

ony

with

Nat

ure

T

o en

cou

rage

stu

den

ts to

be

awar

e o

f th

e im

por

tan

ce o

f sp

iritu

al c

onn

ectio

n w

ith o

urs

elve

s, o

ther

s an

d N

atu

re

Out

com

es: A

t th

e en

d o

f se

ssio

n p

artic

ipan

ts w

ill b

e ab

le to

: -

1.

Rev

iew

seq

uen

ce o

f Dai

ly J

ohre

i tec

hn

iqu

e

2.

Be

awar

e of

the

wid

er a

spec

ts o

f Jo

hre

i ph

iloso

ph

y e

mb

raci

ng

the

valu

e of

art

an

d

bea

uty

for

bot

h in

spira

tion

an

d w

ell b

eing

3.

Ou

tlin

e th

e Jo

hre

i ph

iloso

ph

y on

nu

triti

on

, ‘N

atu

re F

arm

ing’

and

the

nat

ure

4.

Be

awar

e of

the

valu

e o

f sp

iritu

al c

onn

ectio

n ‘

Sp

iritu

al c

ord’

with

ou

rsel

ves,

oth

ers

and

Nat

ure

Ses

sion

4 A

ims:

T

o r

ein

forc

e th

e b

asi

c p

rinci

ple

s an

d c

ore

con

cep

ts o

f Jo

hre

i,

and

the

safe

pra

ctic

e

with

in a

non

-pro

fess

ion

al c

apac

ity O

utco

mes

: At t

he

end

of

sess

ion

par

ticip

ants

will

be

able

to: -

1

. Pra

ctic

e D

aily

Joh

rei c

om

pet

ently

with

in th

e h

ome

and

with

oth

ers

in a

non

-pro

fess

ion

al c

apacit

y 2

. Rev

iew

the

seq

uen

ce o

f Dai

ly J

ohre

i tec

hn

iqu

e an

d k

now

the

seq

uen

ce o

f Sp

iritu

al J

ohre

i & S

elf

-Joh

rei

3. B

e aw

are

of o

pp

ortu

niti

es in

the

futu

re fo

r re

info

rcin

g an

d fu

rth

er u

nd

erst

and

ing

of J

ohre

i ph

iloso

ph

y an

d p

ract

ice.

- 2

55 -

SC

HE

ME

OF

WO

RK:

D

aily

Joh

rei c

ours

e

Cou

rse

: Dai

ly J

ohre

i hea

ling

met

hod

s w

ith b

ackg

rou

nd

ph

iloso

ph

ies

Le

ctu

rer:

Dr.

Aki

ra N

aito

Un

it N

o/ T

itle

4

un

its

Leve

l: b

egi

nn

er

Ses

sion

N

o.

Top

ics

(Aim

s) &

Con

ten

ts (

Ob

ject

ives

) T

each

ing

met

hod

s

Lear

nin

g activ

ities

A

sses

smen

t te

chn

iqu

es R

esou

rces

Ke

y-co

nce

pts

1

Dai

ly J

ohre

i F

oun

dat

ions

of J

ohre

i ph

iloso

ph

y D

aily

Joh

rei t

ech

niq

ues

Fac

ilita

ting

brai

nst

orm

ing

Pow

er-p

oin

t pre

sen

tatio

n D

emon

stra

tion

Pra

ctic

al Q

& A

G

iven

info

rmat

ion

Bra

in s

torm

ing

Pai

r w

ork

Gro

up

wor

k Q

& A

G

uid

ed r

eadin

g

Ob

serv

atio

n Q

& A

P

ower

-poi

nt

Wh

ite b

oard

“R

ealia

” C

D

Han

dou

ts

Joh

rei

“Sp

irit p

rece

des

p

hys

ical

” “h

eal o

nes

elf b

y h

ealin

g ot

her

s”

2

Prin

cipl

es o

f Joh

rei p

ract

ice

His

toric

al b

ackg

rou

nd

His

tory

of

Joh

rei

Pro

cess

of P

urif

icat

ion

Vis

ual

isat

ion

Inte

ntio

n

Fac

ilita

ting

dis

cuss

ion

P

ower

-poi

nt p

rese

nta

tion

Dem

onst

ratio

n P

ract

ical

Q &

A

Giv

en in

form

atio

n

Dis

cuss

ion

Pai

r w

ork

Gro

up

wor

k G

uid

ed r

eadin

g Q

& A

Dis

cuss

ion

O

bse

rvat

ion

Q &

A S

PO

C

Pow

er-p

oin

t W

hite

boa

rd

“Rea

lia”

CD

H

and

outs

“Pro

cess

of

purif

icat

ion

” “M

AK

OT

O”

In

ten

tion

: “Y

ou a

re w

hat

yo

u th

ink”

3

Art

an

d B

eau

ty A

rt o

f Nat

ure

N

atu

re f

arm

ing

S

piri

tual

Cor

d

Pow

er-p

oin

t pre

sen

tatio

n D

emon

stra

tion

Pra

ctic

al Q

& A

G

iven

info

rmat

ion

Gu

ided

rea

din

g P

air

wor

k Q

& A

Ob

serv

atio

n Q

& A

Pow

er-p

oin

t W

hite

boa

rd “R

ealia

” C

D

Han

dou

ts

“Par

adis

e on

eart

h”

Ap

pre

ciat

ions

&

gra

titu

de

N

utr

ition

“S

piri

tual

cor

d”

4

Rev

iew

ing

Joh

rei s

essi

ons S

piri

tual

Joh

rei

Sel

f-Joh

rei

C

ertif

icat

ion

for

atte

nd

ance

Pow

er-p

oin

t pre

sen

tatio

n D

emon

stra

tion

Pra

ctic

al Q

uiz

Q

& A

G

iven

info

rmat

ion

Pai

r w

ork

Gu

ided

rea

din

g Q

uiz

Q

& A

G

rou

p w

ork

Fee

db

ack

Ob

serv

atio

n Q

uiz

Q

& A

Pow

er-p

oin

t W

hite

boa

rd

“Rea

lia”

CD

H

andb

ook

“IZ

UN

OM

E”

Love

for

oth

ers



Welcome! And thank you for coming. I am very honoured and happy to be able to have this opportunity to talk to you about Johrei. Let me introduce my self, I am …… First thing I would like to start with is a self-introduction session. Could you state your name, where you come from and what kind of thought has brought you here, in other words, the objective or expectation to come to today’s talk briefly, please? What do you want to take away from Today’s session?

Daily Johrei



First of all, I would like to start with this brain storming session. In Brainstorming, there are no right or wrong answers. Please discuss in the group that what do you consider ‘spirit’ or ‘spirituality’ to be? By this I mean, what sort of thinking comes to your mind when you hear the word ‘spirit’ or ‘spirituality’. Do you have any definition about these? Any difference between ‘spirit’ and ‘spirituality’? Then next question is when do you think about the concepts of ‘spirit’ or ‘spirituality’, in other words, what sort of situation makes you think these? Are you always thinking of these? Or you have never thought of these? You surely know the word, so at least once you have, haven’t you? Any ideas please. Anything you may think of would be very helpful and useful for us.

What do you consider ‘Spirit’ or ‘Spirituality’ is ?

&

When do you think about it?

Brain storming!

High spirit, low spirit, mean spirit, team spirit…..



This slide is a summary of what I have heard from previous groups of the situations when they may think of the spirit or spirituality. These are typical examples of the ways to be aware of spirit in Johrei as well. Life challenges include when you are suffering something difficult like attengding funerals or emotionally draining time. Spiritual practice includes worship, meditation, and spiritual healing. In Johrei this ‘Beauty’ is highly emphasized and it includes a piece of art like masterpieces in which you may find a spirit of an artist, and somewhere with beautiful scenery in which you may feel your spirit is uplifted. As you have raised and heard from others’ thoughts about ‘spirit’ and ‘spirituality’ , there are quite a lot of meanings or concepts you could think when you hear these words. The purpose of having this brain storming was that I would like you to know that the spirit is not very much far from everyday life nor for certain special people only. It is, in a way, for everyone of us in everyday life. It is in ‘anytime and anywhere for anyone’

Three ways in which to attain spiritual awareness

Life Challenges

Spiritual Practice

Beauty



This is a picture of Mokichi Okada, a founder of Johrei. The message he had tried to convey was that as spirituality is for all, healing or ability to heal other people is also for all. Johrei is one of a practical and effective application of and a tangible example of realisation of what you may see the future in this empowering message. It is always emphasised in Johrei philosophy that “EVERY ONE OF YOU CAN APPLY JOHREI to ANYTHING at ANYTIME and ANYWHERE you want” .

Healing and Spirituality for ALL

Mokichi Okada 1882-1955



The word ‘JOHREI’ is in Japanese and consists of two Chinese characters, Joh and Rei. This literately means purifying the spirit and implies uplifting our soul. Johrei has a lot of facets, so I would like to introduce them one by one.

Johrei Purifying our spirit and uplifting our soul



The Johrei practice is a daily exercise like meditation, jogging or walking. The purpose of Johrei practice, a main objective in the training workshop i.e. learning why and how to practise Johrei, is to maintain health and happiness in family and friends, in other words, to create “a better and beautiful world” from your environment. By this I mean that to become confident and comfortable to practise Johrei within a non-professional capacity.

Maintaining health and happiness in a family

Home practice

Daily Johrei practice



In addition, since Johrei historically began as a therapeutic act, you can support friends and family with Johrei when they are suffering from some tough conditions as well.

Supporting people who suffer



This is the central concept on which Johrei philosophy and practice is based. It is not just giving or receiving healing. It is a mutual process.

‘You can heal your self by healing others’ Hence you can play a role in creating ‘a better and beautiful world’ . A couple of people is the smallest unit of the society. Happiness and health can be realised and spread from this smallest unit within family and friends to larger units, say community, society and ultimately all the world. This process is called by Johrei creating ‘Paradise on Earth’ : a better and beautiful world -- first personally and eventually as a community. This realisation can be achieved through Johrei practice itself, and also through tangible practice of other tenets of Johrei philosophy. In order to practise Johrei effectively and to enjoy Johrei thoroughly, appreciations and acknowledgements of this Johrei philosophy is very important and also encouraging.

Mutual Healing ‘Healing oneself by healing others’



The Johrei philosophy consists of three foundations as you can see here: Art of Healing which is Johrei practice itself, and emphasising the importance and appreciation of ‘Art and Beauty’ and ‘Art of Nature’ . In Johrei, it is emphasised that to be aware of these ideal ultimate goals is very important, but it also is equally important to make one step towards the goals. In other words, you are encouraged to participate in tangible activities of the Johrei philosophy in all aspects in everyday life from your own environment, which means to start creating “a better and beautiful world.” Details of these tangible activities are covered in the training workshop. In the training workshop, first Art of healing is the main objective to learn and to apply but the other two foundations will be touched upon for further understanding of first Art of healing, since these three philosophies are inter-connecting with each other.

Three foundations of Johrei philosophy- Appreciation with gratitude in a daily life -

Art of Healing Art and Beauty Art of Nature



This is a brief introduction and overview of Johrei. Do you have any questions about it? Now, if someone asked you “What is Johrei?” , what would you tell them? Suppose I was the person who asked you what is Johrei. Tell me about it. What would you say to me?



Here are the summarised keys to open the door of your Johrei experience which you will be cover in the training workshop. Three foundations of Johrei philosophies, which I have already given the titles. Three requirements to start practising or to get ready to Johrei. Five principles in order to practise Johrei properly. Five finger rules for memorising and reminding what the key thoughts are when you practise Johrei. Please start exploring these details in the training session, shall we? Today, I would like to show you just the title names of those and want you to try the first step of Johrei experience, named as Tuning-in.

Key objectives

Three foundations

Three requirements

Five principles

(Five fingers rule)



In order to practise Johrei, there are only three requirements. You are encouraged to hold your doubts if you have any, so you do not have to BELIEVE these two, but please TRUST these as you can trust someone even you can not truly believe them ;-). The two are 1. Trust the power of the LIGHT, and 2. the ABILITY of your self. You are quite all right to feel that you can not trust yourself right now, but I am sure that you can trust the ABILITY of your self if you are wishing to be or making some efforts towards your ideal self. Do not ignore your negativities but focus more into the other side rather than concentrating on negatives. This is not ignoring, hiding from or even denying that you have doubts. It is just waiting for the right time to deal with them. The next requirement is the intention to channel the Johrei, and the final one is so-called ‘tuning-in’. Metaphorically speaking, the source of the light keeps sending the LIGHT like a radio station. Like a radio or a TV, there are always waves but you can not see nor sense. Mokichi Okada said that every one of us has got an antenna to receive it. Once you have tuned it in the right channel, then you will be able to practise Johrei as once you tuned a TV tuner in a right channel then you can get beautiful sound and picture. It constantly flows. This is it. When you are comfortable to accept these three requirements, it is time when you can practise Johrei. It is very important to be comfortable your self to begin with, so make sure that you are comfortable enough.

Three requirements for practice

• TRUST (although you do not have to believe if you practise)

– in the power of the source of LIGHT

– in the ABILITY of your SELF

• INTENTION to channel the JOHREI

• TUNING-IN with appreciation



Next, I would like to show a summary of core principles for Johrei practice by showing title names. These are the core five principles of Johrei practice. Each will be covered in detail in the training session.

Five principles for Johrei practice

‘Toxins’ and ‘Clouds in the spirit’

The process of ‘Purification’

‘Spirit’ precede ‘Physical’

‘Spiritual Cord’

‘IZUNOME’



These are five practical concepts in order to memorise and to remind yourself when you are applying Johrei in each session and also in everyday life. These are the title names which you will master in the training session.

FFiivvee FFiinnggeerrss RRuullee

TThhuummbb ((TT)) TTUUNNIINNGG IINN tthhee ssoouurrccee // yyoouurr sseell ff

IInnddeexx FFiinnggeerr ((II)) IINNTTEENNTTIIOONN aanndd iinnssppii rraattiioonn

MMiiddddllee FFiinnggeerr ((MM)) MMiiddddllee wwaayy && bbaallaannccee ((IIZZUUNNOOMMEE))

RRiinngg FFiinnggeerr ((RR)) RReellaaxx ssoo tthhaatt yyoouu ccaann EENNJJOOYY!!

OOppeenn ppaallmm aanndd rreecceeiivvee ggrraattii ttuuddee wwii tthh aapppprreecciiaattiioonn

LLii ttttllee FFiinnggeerr ((LL)) LLeett tthhee LLIIGGHHTT ff llooww



As many psychology or self-realisation text books say nowadays, Mokichi Okada was emphasizing this concept almost a century ago. We are what we think and what we wish to be. It is exactly the same to the Johrei practice, of course! Are you ready to try one simple exercise, which is the first step for the Johrei practice?

““ GGrr aatt ii ttuuddee aatt tt rr aaccttss ggrr aatt ii ttuuddee””

‘‘ II nnggrr aatt ii ttuuddee aatt ttrr aaccttss iinnggrr aatt ii ttuuddee’’

We are determined by our intentions

OOuurr ll ii ffee iiss aall tteerr eedd bbyy tthhee wwaayy wwee tthhiinnkk



The first step for the Johrei practice is this TUNING-IN exercise. Shall we begin? Have you got any experience in meditation, visualisation, or even some spiritual practice like Spiritual Healing, Therapeutic Touch, Tai Chi or Reiki? Those who have such kind of experience, please use your technique if you feel comfortable and want to, but please combine this ‘LIGHT’ concept with it. I think this FLOWING LIGHT is a very powerful metaphor, so bear this in mind, please. Those who have got no experience, you may want to use one visualisation technique I usually teach. Imagine a beautiful place you have been before, say like a beach or park on a sunny but not a too hot day. You are sitting there having the sun shining behind you. The light comes from the Sun and you can feel warmth on the back of your neck and shoulders. How about this? Try to FEEL the light, please. By this ‘Feel’ I mean, any five sense you can experience, brightness (seeing), warmth (touch), or even sounds (hearing), scent (smell), and flavour (taste) of the light if you can. It is totally up to you whether you have your eyes open or closed. Shall we begin? Please make your self comfortable first, and think THE LIGHT.

Feel the ‘Flow of Light’

TTuunniinngg iinn



Introduction

Welcome to Johrei practice! Some of you may be new to healing or spirituality, and some of

you may already be an experienced healer, however, either way, we hope you find in Johrei an

inspiration and simple means to accessing the intimate and spiritual space into which you may

bring healing and beauty.

This handbook is to remind you various techniques taught on the course, and practical ways

of applying Johrei philosophy. Once you have mastered them, naturally, you will no longer

require this handbook.

Johrei is a wonderful way of maintaining health and happiness, but also a useful skill for

helping people you care about out of the goodness of your heart. (Remember you can heal

yourself by healing others, and, if you want, you can learn to practice Johrei professionally with

the Johrei practitioner training at the Johrei Academy. Please note that Johrei techniques you

have learned is not a therapeutic technique, and you will not be able to either medically

diagnose or treat people.)

We very much hope that you will continue with the Johrei practice, and in whichever way

you chose to practise it, you will be contributing, little by little from your surroundings, to

making this world better, beautiful and harmonious place to live.

May the light and beauty be always with you!



1 Overview of Johrei principles and practice

What is Johrei ?

Johrei is a therapeutic art, and in other words: an Art of Living, founded in 1920’s

by a Japanese artist, healer and spiritual leader, Mokichi Okada.

Johrei literally means purification of spirit. Its primary aim is to facilitate the

elimination of toxins from our body and dispersing of ‘clouds’ from our spirit in order to

revitalise us and uplift our soul, thus restoring harmony and well-being.

Johrei can be practised as a therapy that treats illness from all levels (mind, body

and spirit) or as a wonderful and simple way to relieve stress and provide us with

spiritual oasis within our hectic lives.

What is unique about Johrei is that it has a simplified, easy-to-learn technique for

you to practise at home in order to maintain health and well-being. These handouts

outline these techniques for you to learn and practise.

Johrei also extends beyond its healing practice. It is an Art of Living that covers

the following three aspects:-

1. HEALING (Art of life) - Trust the ability of human being

2. BEAUTY - Appreciation of Beauty, enjoy beauty in life

3. NATURE - Living in harmony with nature, Natural farming, diet and nutrition

Johrei activity over the decades gave rise to its own unique flower arrangement

school, SANGETSU, its own chemical-free farming technique, NATURE FARMING, its own

tea ceremony, BONTEMAE, and various art museums, gardens of exquisite beauty and

sacred grounds. As a practitioner of Johrei you will have access to all of these.

Principles of Johrei

Toxins

These are entities (chemicals, inappropriate medicine, pollution, etc.) that are not

intended for our natural consumption. Problems begin to occur when they exceed

beyond our natural capacity and begin to accumulate in our body as toxins. In this

sense, food in excess can become toxic.

Clouds

Think of these as the gloom that looms over us in our spirit when we are ‘under the

weather’. They manifest when we are under stress, emotionally challenged or

become toxin infested.



The Process of Purification

The Toxins and Clouds are constantly undergoing a natural process of eliminating.

This is called the process of purification. This is a naturally occurring process of

detoxification and spiritual uplift. Johrei encourages this process in a directed way

and alleviates discomfort.

Spirit precede physical

We are what we think and feel. Our mental, emotional and spiritual well-being is of

utmost importance. The problem begins if we ignore this simple truth and let our

mind and spirit go out of synch with our body. (See also next page)

IZUNOME

IZUNOME is a state of balance, harmony and appropriateness. It is the middle way

which gives us the ability to look at both sides of a situation so that you can

maintain the balance. Sometimes we need to trust and let go, other times we need to

take our destiny into our own hands and act. Knowing when to act or when to let go

is not easy unless you can sense that. You will be able to sense it by being in the

state of Izunome which practices of Johrei lead you to.

The Process of Purification

This is a naturally occurring process that eliminates toxins and clouds from the

body and the spirit.

It occurs in two stages:

(1) Accumulation

Toxins accumulate around different areas of the body, which are used frequently.

This means that the areas of toxin accumulation vary from person to person. Areas

of stiffness, ‘knots’ in the muscles, swelling, and the areas of pain are said to be due

to the toxin accumulation. Toxins also accumulate deep within our body and affect

our internal organs.

(2) Elimination

When we are well, our body naturally eliminates toxins. This happens when we go

to the toilet, sneeze, cough, and sweat or shed skins. When the toxin accumulation

is severe, elimination process may also be pronounced and accompanied with



discomfort. For example, flu-like symptoms or diarrhoea are symptoms occurring as

the result of toxin elimination. We tend to see this elimination process as an

incident of minor illness, however, they are our body’s way of maintaining our

health.

How Johrei Works

Johrei works by dispersing the clouds in the spirit. This eliminates the negativities

within us, thus giving us greater vitality and encouraging our body’s natural ability

to eliminate toxins.

Furthermore, it is thought that Johrei itself helps to dissolve away the

accumulated toxins or ‘burn away’ the toxins themselves, thus helping to support

the body’s immune function and the function of other organs especially kidneys

which filters out toxins from our blood.

Johrei

Toxins Body Spirit Clouds

Us

Interaction between Body and Spirit In Johrei it is believed that the spirit and body interact in such way that

accumulated toxins cast ‘clouds’ in our spirit, and the ‘clouds’ themselves cause impurities in our blood that leads to toxin build up and hence illness.

Spirit precedes Physical

On the other hand, when the ‘clouds’ in the spirit are dispersed this encourages

toxins in the body to be eliminated. Just as our will leads to the action in our body,

it is believed that the state of our spirit (mind and emotion) influences our physical

well-being. This principle is called the Spirit precedes Physical. Based on this

principle, Johrei practitioner works by channelling the Universal Energy (referred to

as “the Light”) with the intention of dispersing the ‘clouds’ in the spirit and

eliminating toxins.



2. The Finger Rule for preparing yourself for the Johrei experience

You can use the following rules to help you not only with Johrei practice but to prepare yourself

consciously for anything, from flower arranging, art, music, sports to the life in general.

Visualise these rules as you count them out with the fingers of your hand,

starting with: Thumb (T) -Tuning in

First, tune in to the source. Tune into the source of your energy, with love, inspiration and your very being. The source

exists at the centre of the Universe and it is up to you whether you think of it as your higher self, God, the Spirit of the Sun, Nature or the Cosmic Consciousness.

This process is like a TV or a radio; if you do not tune in, you can not obtain a beautiful picture or clear sounds although you have an antenna to receive it. You also empower the antenna by practising Johrei. Index finger (I) –Inspiration and Intention

Be Inspired and hold healing intention Let the source of Universal Love inspire you by your loving intention for the healing of yourself

and others. Middle finger (M) (with Index finger (I))

–Mentality; the Middle way (IZUNOME) Still the mind & balance and harmony with timing: Try hard first then trust!

If your intentions are always for the good of mankind, there is nothing to be afraid of. Allow your stress to melt away and clear your mind. Everything that happens to you is enable you to help you become happier, healthier and stronger. A raw diamond has to be polished to shine. You will find your soul is purified & enlightened by these processes. Keep a smile on your face always.

Ring finger (R)

–Relax so that you can ENJOY yourself Relax your body and take it easy so that you can enjoy yourself!

Rocks can be crushed if the force is strong enough, but free flowing water is adaptable to its surroundings. Always keep the body relaxed and flowing and you will never be crushed. It is all about learning to trust and let go. Relaxing your body will also improve your Johrei practice. Little finger (L) –Let the Light flow!

with Love & MAKOTO (integrity, sincerity, love) Trust in the universal flow & trust your self. Love for others & MAKOTO to you.

Let go and let the light flow. Once you are relaxed, open and tuned in, you can flow with the light.

OOppeenniinngg yyoouurr ppaallmm ttoo rreecceeiivvee ggrraattiittuuddee!!

Gratitude attracts gratitude!

Everything that happens leads to your elevation. If you are in the state of gratitude

and appreciation, things you desire, will always come your way.



3. Points to note before giving Johrei

1. Take note of how you are feeling before you give Johrei. 2. Choose comfortable surrounding where you will not be interrupted or disturbed during

Johrei. Try choosing an area where there is harmony or beauty, possible nears a flower arrangement.

3. Choose two comfortable seats, if possible stools with swivelling seats. However, seating

must be chosen to suit the person receiving Johrei. If the person cannot remain seated for more than 10-20 minutes, adapt your Johrei accordingly. It is important that person who is receiving Johrei is informed that it will take this long before hand.

4. A guide to the positioning of your self and your partner is as follows:-

� The Light is said to flow from the northeast so ideally position yourself with your back to the northeast.

� It is more important that you do not have your back to the door. Position your self so that you are in the opposite part of the room from the door.

5. Take care to note if the person about to receive Johrei is already undergoing some sort of

Purification Process or the person is known to undergo pronounced Purification when receiving Johrei or other forms of healing. Remember that Johrei is about encouraging the Process of Purification. Although, Johrei will generally alleviate any discomfort, use your best judgment to decide whether it is best to proceed with Johrei or allow the process to take its own course and support it with Johrei at a later stage. If you decide to give Johrei in such a situation, it may be more advisable to adapt or shorten your Johrei accordingly, rather than doing the whole sequence. If in any doubt seek professional help before proceeding.

6. If the person to whom you are intending to give Johrei is suffering from acute pain,

severe discomfort or very high fever, especially if the person is a child or pregnant please seek professional help without delay.

7. Be prepared for emerging emotions. Even though the person you are giving Johrei may be

suffering from physical discomfort or no obvious discomfort at all, you may find that there are underlying emotions needing to be expressed, Johrei often allows these emotions to emerge. It can be the case that such emotions are dispersed by Johrei however, you should be ready to talk. Talking can sometimes be hard amongst friends or family. Ask yourself if you are prepared to handle it. If the person wishes to talk or cry, let the person lead the situation. Humility and sincerity is the key. Be there, listen with an open heart but do not advise or judge. If in doubt seek professional help.

8. Heal your self by healing others. Johrei can benefit you when you give it to others. This is

because you receive the Light before you channel it, and through the healing in your partner you are also healed. The feeling of appreciation and gratitude from your partner will also provide you with an up-lift.

9. Make sure you are comfortable when you give Johrei. If you cannot remain in a seated

position for a long time, arrange your seating or length of Johrei accordingly. If you cannot raise your arm for a long time support it with the other arm or rest it on an armrest or a table.

10. You must feel comfortable to give Johrei. If you are too unwell, just receive Johrei from

whoever is offering to give it to you and then rest, don’t feel you are obliged to give Johrei each time.

11. JUST ENJOY the feeling of intimacy, happiness and joy of returning the love and care

you have received from others. Empower your self to help others and in so doing, help yourself.



4. Basic Johrei sequence for family practice

1. Sit facing each other. 2. Take a moment to relax and prepare yourself (with the 5 finger guide) 3. Greet and acknowledge each other. 4. Tune in by visualising the source of the Light. Channeling the Light is like ‘playing the

music of the universe’. Appreciate the occasion and if you can, fill your self with gratitude and joy. Sense of gratitude will allow yourself to be healed in the process of giving Johrei and you will feel less tired during Johrei. The effect may be further enhanced if you can feel and visualise the happiness and the positive outcome for the person you are giving Johrei.

5. Gently raise your hand, relax your arm, cup your palm and begin by channelling to the

forehead (2 minutes) 6. Gently lower your hand to the area near the heart and give Johrei there. (2 minutes) 7. Ask your partner to turn around. Take a moment to tune in again.

Stand up, and steady your partner. Then gently proceed to channel to the crown of your partner’s head. (2 minutes)

8. Channel to the both sides of the neck with your hand (left side first and then right). Remember to cup them. (2 minutes (1 minute each))

9. Cup your hand and place them on the shoulders (left side first and then right again). (2 minutes (1 minute each))

10. Then proceed by cupping your hands and giving Johrei to the centre of your partner’s back so as to channel to the liver, pancreas and stomach. (2 minutes)

11. Place your hands on either sides of your partner’s lower back and give Johrei. This stimulates the kidneys. The Kidneys are important organs for purifying the blood. General fatigue can also be supported by energising the kidneys. (4 minutes (2 minutes each))

12. Finish off by raising one hand as if to give a shower of Light. (1-2 minute) 13. Signal your partner that you have finished with a gentle tap on the shoulders and ask

your partner to face you once more. Thank each other. (Remember you have benefited by giving Johrei too).

14. If your partner also practised Johrei then do not hesitate in proceeding to receive Johrei because Johrei is something to be shared!

Points to note after Johrei:

It does not matter whether your partner or your self did not feel anything during

Johrei, or even that your partner did not immediately feel any effect of it. The effect of

Johrei can just as well be delayed, subtle or unnoticeable.

Reflect more how it was like for you, how you felt afterwards. And think of how you

might do it differently in future for even better results.



5. Basic technique of Self Johrei

1. Sit on a comfortable chair. It will be more effective if you sit upright. 2. Close your eyes and take a moment to relax and tune in with the Five-finger guide. 3. Tune into the source of the Light by visualising the spirit of the Sun over and above you

shining down a beautiful Light. 4. When you can feel the flow of the Light reaching down to you, slowly raise one hand and

channel to your forehead. Your arm should be relaxed, as it would be when channelling Johrei in pairs. (2 minutes)

5. Slowly move your hand down to your chest area passing through the throat. Channel Johrei to your heart. Enjoy the warmth & any alleviation of tension. (2 minutes)

6. Lower your hand further to your stomach area. This area is related to anger and irritation. Channel Johrei here in order to calm you and make you feel more positive. (2minutes)

7. With one hand at a time, channel Johrei to your groin (left side first then right). (1 minutes each side)

8. Cover your tailbone with one hand and channel Johrei to the sacrum. This will help the womb in women, and also your intestines and digestive system. If you have a particularly problematic digestive system, you may also combine this with channelling Johrei to the lower abdomen from the front.

9. If you are suffering from period pains, irregular period cycles, menopause or fertility problems you can follow this up with channelling Johrei with two hands placed on either side of your abdomen followed by one hand three finger width below your belly button. (in this occation1-2 minutes each position)

10. Then from the front, channel to the kidneys (left side first) or cup you hand and place it on

your lower back (left first then right). (2 minutes each) Your lower back is related to your kidneys. Kidneys are important organs for eliminating toxins and filtering blood. Stiffness in your lower back indicates that kidneys are weakened and that excessive toxins have accumulated there. If the kidneys are over worked, it will take extra energy to filter your blood hence you will feel physically drained. Use your hands to press away the stiffness and then channel Johrei if you feel comfortable.

11. Cup your hands and gently place them on your shoulders. You may prefer to do this one shoulder at a time. Your shoulder is a barometer for your general health. Make sure they are always free of stiffness and tension. Your left shoulder is closely associated to your heart. Spend more time channelling to your left shoulder if you have a heart condition. (1-2 minutes each side)

12. With one hand at a time, channel Johrei to both sides of your neck (left side first the right). (1-2 minutes each side) This will help the toxins to move down from your head and support the alleviation of headache.

13. Finally, channel to the forehead like a shower of Johrei! (1 minute) 14. Please note that Johrei, just like every other healing, is effective both when you give it and

receive it. So treat Self-Johrei as a daily self-maintenance practice for improving your Johrei. Always try to look out for anyone who will receive Johrei.

Remember, with Johrei,

YOU HEAL YOURSELF BY HEALING OTHERS



6. Visualisation for Johrei practice

The founder of Johrei, Mokichi Okada said that we are what we think and our

intention alters our life, and also that whatever is created in the spiritual dimension pre-empts the changes taking place in the physical dimension (Spirit precedes physical). These concepts parallel the work carried out by the Simontons in the USA. Based on this, it is obvious that visualization plays an important role in whatever we do. Visualisation is so powerful such that it can even determine the direction of the flow of Light or the outcome of Johrei. Directing the flow

In Johrei, you tune in by visualizing the source of the Light and asking it to help you by channelling the Light to the receiver. The channeller visualizes the flow of the Light from the source, through him/her to the receiver.

The channeller can intensify the effect of the Light by visualizing it being focused by the cupped hand as if it is a magnifying lens and beamed through the body of the receiver to the other side.

Those who are sensitive to people’s energy and internal emotional states, visualize your self as a river rather than a bowl of water. When people wash their dirty linen in your bowl of water, it leaves the water dirty. However, if you are a free flowing river, the dirt is washed away and the water is always pure and clean. Visualising the outcome It is helpful to know beforehand the hope and the wishes of the receiver. As a

channeller, you can visualize the wishes of the receiver while you give Johrei. It may be helpful to visualize a film screen onto which the films of the future events as wished by the receiver are screened. The receiver can be encouraged to visualize the future outcomes in the same way if

you want, but do not compel him/her to do so please. Visualisation by the receiver It is often found that the receiver is unsure how to sit during Johrei and also asks

the channeller whether it is necessary for them to make his/her mind blank. It is undesirable for the receiver as well as the channeller to be struggling to visualize or to blank their minds. It is far more important to remain in a natural state. Visualise only if it becomes

natural to you and to the receiver. A useful way of quietening the mind Johrei way is to allow any thoughts to arise in the head and imagine them to be clouds which are dispersed by the Light of Johrei. More Johrei you practice, you will find that the mind quietens naturally without making a conscious effort. Visualising the past and the future In Johrei, it is said that spirit precedes physical. By uplifting the past and the future

with Johrei, you can uplift the present. When you are giving Johrei from the front of the receiver especially at forehead, visualize a pathway from the past behind the receiver, along which he/she had to travel. It is his/her passage from the past. Visualise to clear the hurdles in it with your Johrei. When the receiver turns and you are giving Johrei from behind, visualize a passage in front of the receiver. It is his/her path into the future. Visualise that you enlighten, energise and heal the path for your receiver with Johrei.

It is up to you as a Johrei practitioner to choose which visualization to use or not to use

visualization at all. With practice, you will find these come to you naturally



7. Sensations felt during Johrei The following is a guide to understanding the meaning of some of the sensations felt by the channeller

or the receiver during the Johrei process. It must be noted that these are not official teachings as taught by Mokichi Okada, the founder of Johrei. Use this information as examples. Heat

In the Johrei principle of the purification process, it is understood that when the accumulated and solidified toxins begin to ‘melt’, the process is accompanied by a localised temperature rise. The characteristic of this is that you will feel the heat upon contact as well as away from the body. If you feel the heat from the receiver yet you feel COLDNESS in your hand when channelling Johrei, it usually indicates that the purification process of melting toxins is taking place in the area and it is drawing in the Light from your hand to support it (see coldness below).

The heat felt by the receiver is the Light which is being channelled. It is usually felt below the surface. How deep the receiver feels the heat depends on how far away the channeller's hand is. The further away the hand from the receiver, the DEEPER the heat of receiver. Try not to confuse the channeller's body heat with the heat sensation of the Light (it has been known that a person with cold hands can still produce the heat sensation within the receiver). If the channeller feels the heat coming from the receiver with no resulting to temperature rise, it usually indicates that the area requires no further channelling. Coldness

The most well recognised sensation other than the heat is the sensation of coldness. The areas with cold sensation are the areas in need of healing. If the channeller feels the coldness in his/her hand when giving Johrei, it indicates that the area is drawing the Light in and healing is taking place. Notice if the area becomes warmer as Johrei is given. If the receiver feels the coldness in the area being given Johrei, find out if the channeller is feeling the heat in his/her hand. If so, it usually indicates that the Light is flowing in the wrong direction. Stop, tune in again and channel by visualising the Light being focused by the channeller's hand and flowing from the channeller to the receiver.

It will help to visualise that the beam of Light piercing through the receiver's body to the other side. Other cold sensations may exist such as the sensation of coldness at the core of the receiver's body, which melts away like melting ice. This in the past has indicated a profound healing. Tingling, magnetic repulsion and the sensation of movement

Tingling sensation in the hand of the channeller can occur to varying degrees. Such tingling sensation indicates that a healing process in which the Light is drawn through the channeller to the area where the purification process is taking place. For Johrei, any tingling sensation indicates that toxins are on the move. So the tingling sensation in the channeller's body may mean that the purification process is taking place there.

The sensation of magnetic repulsion mean that the polarity of the channeller's hand and the area receiving Johrei may be the same, hence the repulsion. Johrei is about channelling the Light from the Universe and not the magnetic energy of the channeller's body. Therefore, if the channeller feels the sensation of magnetic repulsion in Johrei, then stop and tune in again. Pain

When the elimination takes place and the toxins begin to melt and move away from the area being given Johrei, the receiver may feel the sensation of toxins flowing away. If the receiver feels such sensation, it can only be a positive indication. If such sensation is uncomfortable or painful, further Johrei may be given to make the process more comfortable.

Pain indicates that the toxins in that area are melting and moving away. During Johrei, it may be found that the area of pain, knots and stiffness progressively moves down towards the kidneys. If it does, the purification process is proceeding as it should. Encourage the receiver by letting them know that this is a good sign. If the area of pain is not moving, is becoming intense or is moving in the wrong direction (upwards away from the kidneys), use stroking to encourage the toxin flow downwards. Cold draft

If the channeller or the receiver feels a draft of cold wind flowing horizontally across the area receiving Johrei, it is said to indicate that the area requires no further Johrei at that time.

These are guidelines only and true understanding can only come from your own experience gained through repeated practice.



8. Taking Care of Symptoms of Purification

It is likely that through the Johrei practice, toxins within your system start to be eliminated. This will lead to better health and improvement of your current condition. The symptoms of elimination (process of purification) vary from cold like symptoms to diarrhoea. The severity depends upon various factors. The following may be a useful to note. 1. History of illness, (how long have you suffered from your current condition, how severe is it,

what other illness have you had in the past)? 2. Symptomatic medication you have been using (medicine is useful in suppressing the

discomfort, however, later your body will need to eliminate it if it is not appropriate.) 3. Your general well being. As your health improves, you may find that your body will start to

eliminate the toxins that were accumulated in the past.

The above will take place irrespective of whether you give or receive Johrei or not. With Johrei you will find that the elimination process is quicker, with less discomfort. You will also find that more toxins are eliminated; the elimination process will be less prolonged and less intense.

How to manage the ‘purification’ symptoms Fever:

We know that our immune system can be most activated at the body temperature of 38 to 40 degrees Celsius. If you are feverish, just take a rest, relax and sleep well in peace (ideally with supportive Johrei to the kidneys).

When fever causes you to be unable to drink or sleep, an antipyretic such as aspirin helps to prevent dehydration or exhaustion. Diarrhoea:

Warm water is the best thing to take at this time as well as keeping your stomach warm. Diarrhoea is usually a self-limiting symptom, it should last at most about 1-2 days with or

without a severe period of less than 12 hours. What a doctor worries about is dehydration and exhaustion. Consequently, if you cannot drink water for 12 hours, you should go and see a doctor to have fluid supplied intravenously. Sweating or chilling

Once again, warm water is the best thing to take at these times. Keep yourself comfortable by changing your clothes, wearing warm clothes etc. Coughing

Coughing is the way to throw sputum out. In Johrei philosophy, toxins can gather in sputum or in other discharges as well as into urine. When it hurts, give Johrei from the middle of back to alleviate it. Pain

If you or your partner gets acute discomfort, contact a doctor without delay. In Johrei philosophy, it is thought that accumulating or melting toxins cause some discomfort.

This can be a sign that the elimination process is taking place. Johrei, however, is a wonderful and simple way to alleviate discomfort and help your body to detoxificate.

9. The key areas 1. Forehead 2. Crown 3. Temples 4. Back of the neck and the base of skull (medulla oblongata) 5. Both sides of the neck from the dip behind the ears down to the collarbone or

shirt collar (lymphatic nodes) 6. Kidneys: The motion is always down from the head towards the kidneys. 7. And lymph areas (such as heart area, arm pits, groin).



10. Brief historical background of Johrei

Johrei is a philosophy and practice, which has its foundation in a Japanese therapeutic art developed by Mokichi Okada (1882-1955) in the early part of the last century. Mokichi Okada was born into a poor family Okada was not a healthy youth and indeed his various afflictions and life threatening diseases kept him from fulfilling his potential of becoming a professional artist. Following a vegetarian diet, he gradually recovered and with the death of his father in 1905, he became the sole supporter of his family.

He opened a small retail store in Tokyo where his artistic ability contributed to his success, however, he was again forced to abandon this business due to illness.

During the next twenty years, the periods of success alternated with times of abysmal tragedy and disappointment. He lost his wife and their baby due to complications during childbirth.

At one point, the failure of his main bank plunged his firm into bankruptcy, and the Great Kanto earthquake of 1923, in addition to destroying much of Tokyo, ruined Okada financially, along with thousands of others.

Around this time, Okada, who had been an atheist, began to search for a spiritual meaning to life. He became acquainted with various religions and beliefs that were popular at the time, and in this vein, in 1920, he attended a lecture on Omoto at a movie theatre, which he regularly visited. Omoto was one of the New Religions making the headlines at the time. It is based on Shinto, which is the oldest national religion of Japan, and much of what the lecturer said seemed to be refreshingly straight to the point. Okada later joined Omoto and began studying its teachings. One thing unique about Omoto was that it had its own healing ministry called Chikon kishinho, Okada made it his own and began practicing it in 1929. However, by 1934, dissatisfied with the limitations of religious activities and desperately wanting to reach out to all those who needs help, he left Omoto in order to develop his gift as a healer and a therapeutic artist.

The major influence Omoto had on Okada, was to make him realise the importance of the Spiritual. During his time in Omoto, he also discovered that he had a special ability to heal the sick.

He had closely studied the way in which people became ill and the way in which people recovered from illness. He also closely studied medical writings of the day including those on traditional medicine, and had collaborated closely with the leading medical practitioners of the day. Through this process, he developed and perfected the unique spiritual therapy, which he called JOHREI, meaning purification (joh) of spirit (rei)

Okada was passionate about promoting a life style, free from disease, through the use of natural methods of preventing ourselves from becoming seriously ill. Based on his own experience, he knew our food played a crucial role in our health.

In 1935 he began research into the possibility of realising a chemical free farming technique, which he called Nature Farming. By the 1950’s he was able to set up experimental farms and the Nature Farming Society.

During that period, he also created the basis for the Sangetsu School of Flower Arrangement, which emphasised the freedom and the natural beauty of flowers. As a way of bringing beauty into daily life, Sangetsu Flower Arrangement is also practiced alongside the therapy of Johrei healing.

As an artist he knew that both artistic and natural beauty could inspire us and uplift our soul. He looked for a way to bring beauty into our daily lives, and he devoted the later part of his life to creating art museums and inspiringly beautiful gardens. The museums and the sacred gardens he created near Mount Fuji in Hakone and the seaside resort of Atami are enjoyed by millions of visitors today. His vision was to inspire and encourage everyone, in making this world an Earthly paradise.

Back in 1936, Okada set up the Health-care Society of Japan and invited medical professionals of the day, to contribute, to its promotion of a natural form of health maintenance. This was based on a way of living that respects our body’s natural ability, to heal itself and stresses the importance of truth, virtue and beauty within health care.

The Authorities of the day did not appreciate his vision, and he was discouraged from practicing Johrei as a therapy and healthcare measure. In order to be allowed to promote Johrei and both the medicinal and the spiritual aspects of its teaching, he decided, in 1950, to set it up, as a religious organisation, Sekai-Kyusei-Kyo in a style that everyone can practise Johrei. Following his death in 1955, his teachings spread around the world, and, today, there are 3



million people practicing Johrei within families, as a natural method of maintaining health and happiness.

This also helped the development of Nature Farming technique in countries such as Japan, the USA, Brazil, Thailand and encouraged further research into the possibility of totally fertiliser- and chemical - free farming techniques.

In 1996, Dr Rosy Daniel, former Medical Director of Bristol Cancer Help Centre and a leading proponent of the holistic approach to health creation in the UK, encountered Johrei in Japan and on her return to England, called for the formation of a Johrei society in the UK that would re-focus its attention on the original integrity of the Johrei philosophy and teach and promote Johrei practice, not as religion but as an individual’s truly holistic journey towards healing and health creation.

The British Johrei Society and the Johrei Academy was formed by Dr. Rosy Daniel, Sue Boyd, Koichi Sakakibara and Junichi Imura, as a secular organization, and on 15th May 2001, the British Johrei Society and the Johrei Academy were officially launched, commemorating 65th Anniversary of the launch of Mokichi Okada’s Health-care Society of Japan. The British Johrei Society is currently helping to oversee scientific research, taking place around the world, on the efficacy of Johrei. The main research is being directed by Prof. John Gruzelier of Imperial College, University of London.

11. Johrei practice

It is useful to be aware that their area three distinct styles in which Johrei is practiced: (1) Johrei as daily practice

This is the style of Johrei, which you will learn in these workshops as a way to maintain health on daily basis. It is derived from the Therapeutic Johrei technique, which is made short and simple so that it is easy for you to practice anywhere and at any time. By itself, it does not constitute a therapy, however, it is a wonderful way to maintain health, prevent illness and also to support those with chronic conditions at home. (2) Therapeutic Johrei

This is the style of Johrei, which is practiced as a therapeutic intervention. A Therapeutic

Johrei practitioner will scan with hands, and use gentle touch and pressure to find the areas of toxin accumulation and then channel the “Light” from the hand. If the toxin accumulation is severe, Therapeutic Johrei practitioner will also use the application of finger pressure and stroking action to encourage the movement of toxins to the kidneys, followed by channelling to the kidneys to affect the elimination process. The Johrei treatment is carried out with as much understanding of patient/client’s past medical history and lifestyle as possible, so that the application of Johrei is matched to the course of the possible Purification Process unique to the patient/client. (3) Spiritual Johrei

This style of Johrei is practiced by those wishing to obtain closer union with their inner

spirituality and the divine. It can be likened to the induced meditation for two. It involves channelling ‘the Light’ from the hand to the front and the back of the receiver’s body without guiding the hand to specific areas. It is totally hands off and carried out with sincerity, love and faith. This style of Johrei is sometimes referred as Prayer in Action.



Appendix 3: Self-report questionnaires

� Stress perception

� Perceived Stress Scale (PSS) 287

� State anxiety scale in the State and Trait Anxiety Inventory (STAI) 288

� Impact of Event Scale (IES) 289

� Sense of taking control of one’s own life scale

� Locus of Control (LoC) 290

� Quality of life

� Mental Components of Summary in the SF-36 (MCS) 292

� Sleep quality

� Pittsburgh Sleep Quality Inventory (PSQI) 295



Perceived Stress Scale

Nev

er

0 Alm

ost

neve

r 1 S

omet

imes

2 F

airl

y of

ten

3 V

ery

ofte

n

4

1. In the last few days, how often have you been upset because of something that happened unexpectedly?

� � � � �

2. In the last few days, how often have you felt that you were unable to control the important things in your life?

� � � � �

3. In the last few days, how often have you felt nervous and stressed?

� � � � �

4. In the last few days, how often have you dealt with irritating life hassles?

� � � � �

5. In the last few days, how often have you felt that you were effectively coping with important changes that were occurring in your life?

� � � � �

6. In the last few days, how often have you felt confident about your ability to handle your personal problems?

� � � � �

7. In the last few days, how often have you felt that things were going your way?

� � � � �

8. In the last few days, how often have you found that you could not cope with all the things you had to do?

� � � � �

9. In the last few days, how often have you been able to control irritations in your life?

� � � � �

10. In the last few days, how often have you felt that you were on top of things?

� � � � �

11. In the last few days, how often have you been angered because of things that happened that were outside your control?

� � � � �

12. In the last few days, how often have you found yourself thinking about things that you have to accomplish?

� � � � �

13. In the last few days, how often have you been able to control the way you spend your time?

� � � � �

14. In the last few days, how often have you felt difficulties were piling up so high that you could not overcome them?

� � � � �



Self-Evaluation Questionnaire (Y) Developed by Charles D. Spielberger in collaboration with R. L. Gorsuch, R. Lushene, P. R. Vagg,

and G. A. Jacobs

STAI (-S) Form Y-1 NAME: DATE: AGE: SEX: M / F S: T:

DIRECTIONS: A number of statements which people have used to describe themselves are given below. Read each statement and then blacken in the appropriate circle to the right of the statement to indicate how you feel RIGHT NOW, that is, AT THIS MOMENT. There are no right or wrong answers. Do not spend too much time on any one statement but give the answer, which seems to describe your present feeling best.

1. I feel calm.………………………………………………………… 1 2 3 4

2. I feel secure…………...…………………………………………… 1 2 3 4

3. I am tense………………………………………………………….. 1 2 3 4

4. I am strained. ……………………………………………………… 1 2 3 4

5. I feel at ease. ………………………………………………………. 1 2 3 4

6. I feel upset. ………………………………………………………... 1 2 3 4

7. I am presently worrying over possible misfortunes.………………. 1 2 3 4

8. I feel satisfied...……………………………………………………. 1 2 3 4

9. I feel frightened…………………………………………….……… 1 2 3 4

10. I feel comfortable. …………………………………………………. 1 2 3 4

11. I feel self-confident. ……………………………….………………. 1 2 3 4

12. I feel nervous. ……………………………………………………... 1 2 3 4

13. I am jittery. ……………………………………….…………….…. 1 2 3 4

14. I feel indecisive….………………………………………………… 1 2 3 4

15. I am relaxed. …………………………………….………………… 1 2 3 4

16. I feel content..……………………………………………………… 1 2 3 4

17. I am worried…….……………………………….………………… 1 2 3 4

18. I feel confused..……………………………………………………. 1 2 3 4

19. I feel steady.………………….………………….………………… 1 2 3 4

20. I feel pleasant. …………………………………..………………… 1 2 3 4

V

ery m

uch so�

Mode

rately so�

Som

ew

hat�

Not at a

ll�



Impact Event Scale

Name __________________________ Date ___________________

Frequency during the past week

Below is a list of comments made by people distressed about some aspect of living with cancer. Please check each item, indicating how frequently these comments were true for you DURING THE PAST SEVEN DAYS. If they did not occur during that time, please mark the ‘not at all’ column.

Not at all Rarely Sometimes Often 1 I thought about it when I didn’t want to. � � � �

2 I avoided letting myself get upset when I thought about it or was reminded of it.

� � � �

3 I tried to remove it from memory. � � � �

4 I had trouble falling asleep or staying asleep. � � � �

5 I had waves of strong feelings about it. � � � �

6 I had dreams about it. � � � �

7 I stayed away from reminders of it. � � � �

8 I felt as if it hadn’t happened or it wasn’t real. � � � �

9 I tried not to talk about it. � � � �

10 Pictures about it popped into my mind. � � � �

11 Other things kept making me think about it. � � � �

12 I was aware that I still had a lot of feelings about it, but I didn’t deal with them.

� � � �

13 I tried not to think about it. � � � �

14 Any reminder brought back feelings about it. � � � �

15 My feelings about it were kind of numb. � � � �

0 1 3 5



Rotter's Locus of Control Scale

Name ___________________

Please choose a. or b. by ticking the box beside your choice: a. b.

1. � a. Children get into trouble because their patents punish them too much.

or � b. The trouble with most children nowadays is that their parents are too easy with them.

2. � a. Many of the unhappy things in people's lives are partly due to bad luck.

or � b. People's misfortunes result from the mistakes they make.

3. � a. One of the major reasons why we have wars is because people don't take enough interest in politics.

or � b. There will always be wars, no matter how hard people try to prevent them.

4. � a. In the long run people get the respect they deserve in this world.

or � b. Unfortunately, an individual's worth often passes unrecognised no matter how hard he tries.

5. � a. The idea that teachers are unfair to students is nonsense.

or � b. Most students don't realize the extent to which their grades are influenced by accidental happenings.

6. � a. Without the right breaks one cannot be an effective leader.

or � b. Capable people who fail to become leaders have not taken advantage of their opportunities.

7. � a. No matter how hard you try some people just don't like you.

or � b. People who can't get others to like them don't understand how to get along with others.

8. � a. Heredity plays the major role in determining one's personality

or � b. It is one's experiences in life which determine what they're like.

9. � a. I have often found that what is going to happen will happen.

or � b. Trusting to fate has never turned out as well for me as making a decision to take a definite course of action.

10� a. In the case of the well-prepared student there is rarely if ever such a thing as an unfair test.

or � b. Many times exam questions tend to be so unrelated to course work that studying in really useless.

11� a. Becoming a success is a matter of hard work, hick has little or nothing to do with it.

or � b. Getting a good job depends mainly on being in the right place at the right time.

12� a. The average citizen can have an influence in government decisions.

or � b. This world is run by the few people in power, and there is not much the little guy can do about it.

13� a. When I make plans, I am almost certain that I can make them work.

or � b. It is not always wise to plan too far ahead because many things turn out to- be a matter of good or bad fortune anyhow.

14� a. There are certain people who are just no good.

or � b. There is some good in everybody.



15� a. In my case getting what I want has little or nothing to do with luck.

or � b. Many times we might just as well decide what to do by flipping a coin.

16� a. Who gets to be the boss often depends on who was lucky enough to be in the right place first.

or � b. Getting people to do the right thing depends upon ability; luck has little or nothing to do with it.

17� a. As far as world affairs are concerned, most of us are the victims of forces we can neither understand, nor control.

or � b. By taking an active part in political and social affairs the people can control world events.

18� a. Most people don't realize the extent to which their lives are controlled by accidental happenings.

or � b. There really is no such thing as "luck."

19� a. One should always be willing to admit mistakes.

or � b. It is usually best to cover up one's mistakes.

20� a. It is hard to know whether or not a person really likes you.

or � b. How many friends you have depends upon how nice a person you are.

21� a. In the long run the bad things that happen to us are balanced by the good things.

or � b. Most misfortunes are the result of lack of ability, ignorance, laziness, or all three.

22� a. With enough effort we can wipe out political corruption.

or � b. It is difficult for people to have much control over the things politicians do in office.

23� a. Sometimes I can't understand how teachers arrive at the grades they give.

or � b. There is a direct connection between how hard I study and the grades I get.

24� a. A good leader expects people to decide for themselves what they should do.

or � b. A good leader makes it clear to everybody what their jobs are.

25� a. Many times 1 feel that I have little influence over the things that happen to me.

or � b. It is impossible for me to believe that chance or luck plays an important role in my life.

26� a. People are lonely because they don't try to be friendly.

or � b. There's not much use in trying too hard to please people, if they like you, they like you.

27� a. There is too much emphasis on athletics in high school.

or � b. Team sports are an excellent way to build character.

28� a. What happens to me is my own doing.

or � b. Sometimes I feel that I don't have enough control over the direction my life is taking.

29� a. Most of the time I can't understand why politicians behave the way they do.

or � b. In the long run the people are responsible for bad government on a national as well as on a local level.



SF-36 Quality of Life Scale (revised version)

1. In general would you say your health is: excellent very good good fair poor

Tick one box: �5 �4 �3 �2 �1

2. Compared to one year ago, how would you rate your health in general now? (Tick one box) Much better than one year ago �5

Somewhat better than one year ago �4 About the same as one year ago �3 Somewhat worse than one year ago �2 Much worse than one year ago �1

3. The following items are about activities you might do during a typical day. Does your health limit

you in these activities? If so, how much? Tick one box.

Yes, limited a lot1

Yes, limited a little2

No, not limited at all3

a) Vigorous activities such as running, lifting heavy objects, participating in strenuous sports.

� � �

b) Moderate activities such as moving a table, pushing a vacuum cleaner, bowling or golf.

� � �

c) Lifting or carrying groceries. � � � d) Climbing several flights of stairs. � � � e) Climbing one flight of stairs. � � � f) Bending, kneeling or stooping. � � � g) Walking more than a mile. � � � h) Walking several hundred yards. � � � i) Walking 100 yards. � � � j) Bathing or dressing yourself. � � � 4. During the past 4 weeks, have you had any of the following problems with your work or other

regular daily activities as a result of your physical health? Yes1 No2

a) Cut down the amount of time spent on work or other activities � � b) Accomplished less than you would like � � c) Were limited in the kind of work or other activities � � d) Had difficulty performing work or other activities (for example, it took extra effort)

� �



5. During the past 4 weeks, have you had any of the following problems with your work or other regular daily activities as a result of any emotional problems (such as feeling depressed or anxious).

Yes1 No2

a) Cut down the amount of time spent on work or other activities � � b) Accomplished less than you would like � � c) Didn’t do work or other activities as carefully as usual � � 6. During the past 4 weeks, to what extent have your physical health or emotional problems

interfered with your normal social activities with family, friends, neighbours or groups?

Not at all5 Slightly4 Moderately3 Quite a bit2 Extremely1

� � � � � 7. How much bodily pain have you had in the past 4 weeks?

None6 Very mild5 Mild4 Moderate3 Severe2 Very severe1

� � � � � � 8. During the past 4 weeks, how much did pain interfere with your normal work (including

both work outside the home and housework)?

Not at all5 A little bit4 Moderately3 Quite a bit2 Extremely1

� � � � � 9. These questions are about how you feel and how things have been with you during the past

4 weeks, for each question, please give one answer that comes closest to the way you have been feeling. How much time during the past 4 weeks…

Tick one box . All of

the time6 Most of the time5

A good bit of the time4

Some of the time3

A little of the time2

None of the time1

a) Did you feel full of energy? � � � � � � b) Have you been a very nervous

person? � � � � � �

c) Have you felt so down in the dumps that nothing could cheer you up?

� � � � � �

d) Have you felt calm and peaceful? � � � � � � e) Did you have a lot of energy? � � � � � � f) Have you felt downhearted and

sad? � � � � � �



All of

the time6 Most of the time5

A good bit of the time4

Some of the time3

A little of the time2

None of the time1

g) Did you feel worn out? � � � � � � h) Have you been a very happy

person? � � � � � �

i) Did you feel tired? � � � � � � j) Have you had difficulty reasoning

and solving problems, e.g. making plans, making decisions, learning new things?

� � � � � �

k) Did you forget things that happened recently e.g. where you put things, appointments?

� � � � � �

l) Did you have trouble keeping your attention on any activity for long?

� � � � � �

m) Did you have difficulty doing activities involving concentration and thinking?

� � � � � �

10. During the past 4 weeks, how much of the time has your physical or emotional problems

interfered with your social activities (like visiting friends, relatives etc)?

All of the time1 Most of the time2 Some of the time3 A little of the time4

None of the time5

� � � � � 11. How TRUE or FALSE is each of the following statements for you?

Tick one box: Definitely

true1 Mostly true2

Don’t know3

Mostly false4

Definitely false5

a) I seem to get sick a little easier than other people.

� � � � �

b) I am as healthy as anybody I know. � � � � � c) I expect my health to get worse. � � � � � d) My health is excellent. � � � � �



Pittsburgh Sleep Quality Index

Name: ________________________________ Age: _____ Date: _____________ The following questions relate to your usual sleep habits during the past month. Your answers should indicate the most accurate reply for the majority of days or nights in the past month. Please answer ALL QUESTIONS . 1 During the past month, when have you usually gone to bed at night? 2 During the past month, how long (in minutes) has it taken you to fall asleep? 3 During the past month, when have you usually got up in the morning? 4 During the past month, how many hours of actual sleep did you get at night?

(this may be different from the number of hours you spent in bed)

5 During the past month, how would you rate your sleep quality overall? very good =1, fairly good =2, fairly bad =3, very bad =4

6 During the past month, how much of a problem has it been for you to keep up enough enthusiasm to get things done? No problem at all = 0 ; Only a slight problem = 1 ; Somewhat of a problem = 2 ; A very big problem = 3

7 During the past month, how often have you had trouble sleeping because you…

Please check the correct box:

not a

t all

le

ss th

an

once

a

wee

k

1

or 2

tim

es a

w

eek

3 or

mor

e tim

es a

w

eek

A Could not get to sleep in 30 minutes � � � �

B Woke up in the middle of the night or too early � � � �

C Had to get up to use the loo. � � � �

d Could not breathe comfortably � � � �

E Coughed or snored loudly � � � �

F Felt too cold � � � �

G Felt too hot � � � �

H Had bad dreams � � � �

I Had pain � � � �

J Had sweating � � � �

K Were disturbed by partner / children / pets � � � �

l Other reasons:__________________________ � � � �

8 In past month, how often did you take medication to help you sleep?

� � � �

9 In past month, how often have you had trouble staying awake while driving, eating, working or engaging in social activities?

� � � �



Appendix 4: Standard operating procedures (SOPs)

SOP-1: [3H]-thymidine incorporation using whole blood for proliferation assay 296

SOP-2: Flow cytometry assay for lymphocyte proliferation response in whole blood 297

SOP-3: NK cell cytotoxic activity assay by flow cytometry 302

[3H]-Thymidine incorporation proliferation assay protocol in whole blood

SOP-1 written by Dr. Akira Naito Oct. 2003

Materials: Buffers:

Tissue culture medium (TCM) consists of RPMI 1640 supplemented with 1% glutamine (200 mM), 1% penicillin (5000 IU/ml)/ streptomycin (5000 mcg/ml), 1% non-essential amino acids (100 x), 1% sodium pyruvate (100 mM).

Fresh (1-4 hours) 1:5 diluted heparinized whole blood samples are used for proliferation assay. The

blood is 1:5 with tissue culture medium and 200 �l cultured in triplicate wells of a 96-well plate. Mitogens/Anti gens: the Staphylococcal enterotoxin B (SEB) (product no. S-4881, Sigma-Aldrich®)

and the Phytohaemagglutinin A (PHA; Leucoagglutinin PHA-L) (Lectin: product no. L-4144, Sigma-Aldrich®) are used as stimuli for proliferation reaction (experimental solution is titrated 50 �g/ml.).

- Following concentration is from a stock (which means the REAL conc. in the well is 1/4). - Chemical (SEB/PHA) titration: original concentration is 5 mg/ml � 500, 250, to 0.78 �g/ml

Drug preparation:

- Hydrocortisone (cortisol) 250 nM (1 � in the adding solution) in TCM Hydrocortisone titration: (adding concentrations: real concentration in wells are 1/4) 32, 16, 8, 4,

2, 1, 0.5, 0.25, 0.125, 0.062, 0.031 �mol/L (underlined concentrations are physiological.) - Melatonin - DHEA-S

Method: � 10 ml of heparinized blood, 10 ml of 1 �M cortisol, 7 ml of previously titrated (50 �g/L) stimulus for

1 subject. � Preparation of 96 wells plates (one plate for two subjects PHA/SEB) incubating 72 hrs

TCM / TCM / TCM TCM / Cort / TCM TCM / Cort / Mel 50 TCM / Cort / Mel 500 SEB / TCM / TCM SEB / Cort / TCM SEB / Cort / Mel 50 SEB / Cort / Mel 500 PHA / TCM / TCM PHA / Cort / TCM PHA / Cort / Mel 50 PHA / Cort / Mel 500

a. 50 �l of stimulus (12.5 �g/ml PHA/SEB) into all wells except first background well. b. 50 �l of each drugs (0, 1 �M cortisol + 0, 200 or 2000 pg/ml of melatonin) into all wells c. Blood preparation: keep 5 ml EDTA tube for flowcytometry lymphocyte subsets analysis aside d. Mix 2 ml Li-heparinised blood with 3 ml TCM into 1:2.5 dilutions. (5 ml) e. Place 50 �l of diluted whole blood onto each well (at the end step of preparation of plates).



[3H]-Thymidine incorporation proliferation assay protocol in whole blood for 4-5th day of PPD stimulation and 2-3rd day of PHA stimulation

SOP-1b written by Dr. Akira Naito Apr. 2004 Materials: Buffers:

Tissue culture medium (TCM) consists of RPMI 1640 supplemented with 1% glutamine (200 mM), 1% penicillin (5000 IU/ml)/ streptomycin (5000 mcg/ml), 1% non-essential amino acids (100 x), 1% sodium pyruvate (100 mM).

Fresh (1-4 hours) 1:5 diluted heparinized whole blood samples are used for proliferation assay. The

blood is 1:5 with tissue culture medium and 200 �l cultured in triplicate wells of a 96-well plate. Mitogens/Anti gens: the Phytohaemagglutinin A (PHA; Leucoagglutinin PHA-L) (Lectin: product no.

L-4144, Sigma-Aldrich®: experimental solution is titrated 50 �g/ml.) and Purified protein (PPD) are used as stimuli for proliferation reaction.

- Following concentration is from a stock (which means the REAL conc. in the well is 1/4). - Chemical (PHA) titration: original concentration is 5 mg/ml � 500, 250, to 0.78 �g/ml

Drug preparation:

- Hydrocortisone (cortisol) 250 nM (1 � in the adding solution) in TCM - Melatonin 50 pg/ml (400 pg/ml in the adding solution) in TCM - DHEA-S

Method: � 4 ml of heparinized blood (10 ml of 1:2.5 diluted blood), 3 ml of 1 �M cortisol and 3 ml of 50 pg/ml

Melatonin, 3 ml of previously titrated (50 �g/L PHA, 1/100 PPD) stimulus for 1 subject. � Preparation of 96 wells plates (one plate for four subjects PHA / PPD) � 4 plates (2, 3, 4 & 5 days)

TCM/ TCM / TCM TCM / Melatonin Cortisol / Melatonin TCM / Cortisol / TCM PPD / TCM / TCM PPD / TCM / Mel PPD / Cort / Mel PPD / Cort / TCM

TCM/ TCM / TCM TCM / Melatonin Cortisol / Melatonin TCM / Cortisol / TCM PHA / TCM / TCM PHA / TCM / Mel PHA / Cort / Mel PHA / Cort / TCM a. 50 �l of stimulus (12.5 �g/ml PHA, or PPD) into all wells except first background well. b. 50 �l of each drugs (0, 1.0 �M of cortisol and 0, 200 pg/ml of melatonin) into all wells c. Blood preparation: (keep 5 ml EDTA tube for flowcytometry lymphocyte subsets analysis aside) d. Mix 2 ml Li-heparinised blood with 3 ml TCM into 1:2.5 dilutions. (5 ml) e. Place 50 �l of diluted whole blood onto each well (at the end step of preparation of plates). f. Prepare 2nd and 3rd day plates for PHA and 4th day plates (+ 5th day plates) for PPD.



Flowcytometry analysis of proliferation response in whole blood assay protocol

SOP-2 written by Dr. Akira Naito Oct. 2003 Materials: Buffers:

Tissue culture medium (TCM): RPMI 1640 supplemented with 1% glutamine (200 mM), 1% penicillin (5000 IU/ml)/ streptomycin (5000 mcg/ml), 1% non-essential amino acids (100 x), 1% sodium pyruvate (100 mM).

Fresh (1-4 hours) 1:5 diluted heparinized whole blood samples are used for proliferation assay. Mitogens/Anti gens: the Staphylococcal enterotoxin B (SEB) (product no. S-4881, Sigma-Aldrich®)

and the Phytohaemagglutinin A (PHA; Leucoagglutinin PHA-L) (Lectin: product no. L-4144, Sigma-Aldrich®) are used as stimuli for proliferation reaction (experimental solution is titrated 50 �g/ml.).

- Following concentration is from a stock (which means the REAL conc. in the well is 1/4). - Chemical (SEB/PHA) titration: original concentration is 5 mg/ml � 500, 250, to 0.78 �g/ml

Drug preparation:


2, 1, 0.5, 0.25, 0.125, 0.062, 0.031 �mol/L (underlined concentrations are physiological.) - Melatonin 50 pg/ml is upper physiological levels - DHEA-S

Method: � Time course CD95/(Annexin V)/CD25/(HLA-DR) expression at CD4/CD8/CD56 in 0/24/48/72hr

with/without 250 nM of Hydrocortisone (cortisol) and with/out 50/500 pg/ml of melatonin 1. Preparation of 24 wells plates (one plate for two subjects SEB/PHA) with/without cortisol

TCM / TCM / TCM TCM / Cort / TCM TCM / Cort / Mel 50 TCM / Cort / Mel 500 SEB / TCM / TCM SEB / Cort / TCM SEB / Cort / Mel 50 SEB / Cort / Mel 500 PHA / TCM / TCM PHA / Cort / TCM PHA / Cort / Mel 50 PHA / Cort / Mel 500

a. 400 �l of stimulus (12.5 �g/ml PHA/SEB) into all wells except first background well b. 400 �l of drug 1 (1 �M cortisol / TCM) into all wells c. 400 �l of drug 2 (200 or 2000 pg/ml melatonin / TCM) into all wells d. Place 400 �l 1:2.5 diluted whole blood onto each well (400 x 12 wells = 4.8 ml needed)

2. Collection of supernant from cultured wells: 500 �l from each well of 24-well-plates. 3. Allocate 500 �l of mixed solution of cultured cells into 2 FACS tubes. 4. Staining

a. 5 �l of antibodies (CD3/CD8/CD56, and FITC-CD95/Annexin V or FITC-CD25/HLA-DR) are added to 500 �l of 1:5 diluted cultured bloods.

b. One tube for isotype controls c. Incubate 20 min in room temperature

5. Lysing RBC: add 500 �l of lysing solution (5x not 10x) and incubate 20 min � Flow cytometry: always measure with the same setting (use saved file settings)!

a. R1 is gated for lymphocyte by FSC-SSC scatter dot-plot. At least 6,000 target cells (in R1) are collected per sample.

b. The fluorescence intensity of FL-1 (FITC) peaks are compared by overlaying the histograms of different lymphocyte populations (by gating the FL-2 +, FL-3+, FL-4 + cells).

c. All samples are tested in duplicate and the results are presented as average values.



Flowcytometry analysis of proliferation response in whole blood assay protocol

SOP-2b written by Dr. Akira Naito July 2004 Materials: Buffers:

Tissue culture medium (TCM): RPMI 1640 supplemented with 1% glutamine (200 mM), 1% penicillin (5000 IU/ml)/ streptomycin (5000 mcg/ml), 1% non-essential amino acids (100 x), 1% sodium pyruvate (100 mM).

Fresh (1-4 hours) 1:2.5 diluted heparinized whole blood samples are used for proliferation assay. Mitogens/Anti gens: the Phytohaemagglutinin A (PHA; Leucoagglutinin PHA-L) (Lectin: product no.

L-4144, Sigma-Aldrich®) are used as stimuli for proliferation reaction (experimental solution is titrated 50 �g/ml.).

- Following concentration is from a stock (which means the REAL conc. in the well is 1/4). - Chemical (PHA) titration: original concentration is 5 mg/ml � 500, 250, to 0.78 �g/ml

Drug preparation:


2, 1, 0.5, 0.25, 0.125, 0.062, 0.031 �mol/L (underlined concentrations are physiological.) - Melatonin 50 pg/ml is upper physiological levels - DHEA-S

Method: � Annexin V & PI staining on CD4/CD8 T cells in proliferation response to the PHA at 3rd day of

incubation with/out 250 nM hydrocortisone (cortisol) � HLA-DR expression at CD4/CD8 T cells in with/without 250 nM of Hydrocortisone (cortisol) 6. Preparation of 24 wells plates (one plate for four subjects PHA) with/without cortisol

TCM / TCM / TCM TCM / TCM / Mel 50 TCM / Cort / Mel 50 TCM / Cort / TCM PHA / TCM / TCM PHA / TCM / Mel 50 PHA / Cort / Mel 50 PHA / Cort / TCM

e. 50 �l of stimulus (12.5 �g/ml PHA) into all wells except first background well f. 50 �l of drug 1 (1 �M cortisol / TCM) into all wells g. 50 �l of drug 2 (200 pg/ml melatonin / TCM) into all wells h. Place 50 �l 1:2.5 diluted whole blood onto each well

7. Allocate 5 �l of mixed solution of cultured cells into 2 FACS tubes. 8. Staining

d. 5 �l of antibodies (CD3/CD8, and CD95/Annexin V-FITC or HLA-DR-FITC) are added to 500 �l of 1:5 diluted cultured bloods.

e. One tube for isotype controls f. Incubate 20 min in room temperature

� Flow cytometry: always measure with the same setting (use saved file settings)!

d. R1 is gated for lymphocyte by FSC-SSC scatter dot-plot. At least 6,000 target cells (in R1) are collected per sample.

e. The fluorescence intensity of FL-1 (FITC) peaks are compared by overlaying the histograms of different lymphocyte populations (by gating the FL-2 +, FL-3+, FL-4 + cells).

f. All samples are tested in duplicate and the results are presented as average values.



NK cytotoxic activity assay protocol using flow cytometry

SOP-3 written by Dr. Akira Naito Feb. 2004

Materials: Buffers:

Tissue culture medium (TCM): RPMI 1640 supplemented with 1% glutamine (200 mM), 1% penicillin (5000 IU/ml)/ streptomycin (5000 �g/ml), 1% non-essential amino acids (100 x), 1% sodium pyruvate (100 mM), LymphPrep (Invitrogen) In activated fetal calf serum & human AB serum (Sigma H-4522): 56oC for 35 min prior to be frozen.

Chemicals / antibodies: 1 �g/ml of propidium iodine (PI) (stock solution was 1 mg/ml: Sigma-Aldrich® product no. P-4170) and 0.05% of Eosin Y (Sigma-Aldrich®, HT110) for dyes, anti-CD45-FITC (BD®), anti-CD56-PE (BD® 555516), anti-CD3-APC (BD®), Hydrocortisone (Sigma-Aldrich® H-0135)

Materials needed: Universals, 1 ml pipettes, 20 ml pipettes, Tips (1ml, yellow), Flasks (40, 100 ml)5, FACS tubes, 24 wells plate, 96 wells plate (U-bottom, flat-bottom), CytoTox 96® kit (Promega G1780), ELISA kit for cortisol (plasmas & supernatants) (DRG #EIA-I887), Ice box and ice

Drug preparation:

- Hydrocortisone (cortisol) 250 nM (1 �M in the adding solution) in TCM Hydrocortisone titration: (adding concentrations: real concentration in wells are 1/4) 32, 16, 8, 4, 2, 1, 0.5, 0.25, 0.125, 0.062, 0.031 �mol/L (underlined concentrations are physiological.)

- Melatonin 50 pg/mL is upper physiological concentration (200 pg/mL in the adding solution) - DHEA-S

Cell preparation:

- Peripheral blood mononuclear cells (PBMCs) 1. Centrifuge fresh blood at 1500 rpm 10 min (4 tubes of 10 ml heparinized whole blood) 2. Collect the supernatant plasma into 1 tube (�stock in a freezer for further study) 3. Add TCM to each and get these bloods onto Lymph Prep gently with great care. 4. Centrifuge 1500 rpm 25 min 5. Collect the layer of PBMCs with upper layer 6. Wash with TCM Centrifuge 1500 rpm 10 min � (with K562 first centrifuge) 7. Wash with 10% FCS in TCM Centrifuge 1500 rpm 10 min � (with K562 second centrifuge) 8. Decant the supernatant and add 2 ml of foetal calf serum (FCS) + 18 ml of TCM 9. Transferred to a 250 ml culture flask for ‘monocyte depletion’, incubate 1 HOUR 10. Collect non-adherent cells from flask, centrifuge 1500 rpm 10 min 11. Add 1000 �L of TCM and get 10 �L of that + 90 �L of Eosin 12. Count in microscope (in 10 order: minimum >150)

150 x 10 x 104/ml =1.5 x 107/ml�add 500(=1500-1000) �L of TCM � 1.0 x107/ml (x1.3ml) <PBMCs 1>

� 1 tube (Time 0 data): 0.6 ml of this <PBMCs 1> + 0.3 ml of TCM + 0.1 ml of FCS � 5.0 x 106/ml (x 1.0ml) or 1.25 x 106/ml (x 4.0 ml)� collect in FACS tubes � 24-well-plate (incubate): 0.6 ml of <PBMCs 1> + 0.4 ml of TCM + 0.3 ml of FCS + 0.8 ml of 0, 50, 500 pg/mL MELATONIN + 0.8 ml of 0, 250, 2500 nM CORTISOL

� Take 1 ml of supernant to stock at –80 oC for further cortisol ELISA analysis � add 95 �l of anti CD-45 (80 �L+720 �L of PBS) and incubate 20 min

13. Wash with TCM, centrifuge 1500 rpm 6 min 14. Add 450 �l of TCM (to make 500 �l) and get 10 �l of that + 90 �l of Eosin (0.05% Eosin Y) 15. Count in microscope (in 5 order)

65 x 10 x 104/ml = 65 x 105/ml�add 150 (= 65/50 x 500 -500) �l of TCM � 50 x105/ml of PBMCs*(1) (100 �l has 50 x104 cells: minimum volume needed > 600 �l)

TCM Cortisol 2500 nM C (250 nM) C (250) + Mel. 50 pg C (250) + Mel. 500 pg



SOP-3: (continued)

- K562 tumour cells (require 2.0-5.0 x 106 cells / total) 1. Unfrozen stock K562 cells (5 x 106 cells/ml in 10% DSMO, 20% FCS, 70% TCM at –80 oC) and

culture them 1-2 weeks prior experiment start. (pass cells every 2-3 days) 2. Culture 10 ml of 2 x 105 cells/ml concentration 2 days prior to the experiment. 3. After 3rd wash, decant the supernatant and add 1000 �L of TCM 4. Get 10 �L of K562 + 90 �L of dye (0.05 % Eosin Y) 5. Count in microscope

50 x10 x104/ml = 5 x106/ml � add 4(=5-1) ml of TCM� 1.0 x106/ml <K> 1ml of <K> +2 ml of FCS +7ml of TCM =1.0 x105/ml of K562 (*2) in 40ml culture flask 0.5ml of <K> + 1 ml of Human AB serum + 3.5ml of TCM = 1.0 x105/ml of K562 (*3) � take 100 �L of this (*2) (= 1.0 x104 cells) into each incubation tube** (2) (duplication) � take 50 �L of this (*3) into each wells in 96-well plate**(3) (duplication)

Method:

a. Flow assay: Tubes (1-4) for setting-up for acquisition (gating K562 region & CD56 cut-off) Tube 1: take 100 �L for lymph only (for negative control) + 80 �L of TCM + 20 �L of FCS Tube 2: take 100 �L for lymph only (for positive control) + 80 �L of TCM + 20 �L of FCS Tube 3: take 200 �L for K562**(2) only for flow cytometric assay Tube 4: take 200 �L for K562**(2) only for duplication

Experimental tubes: from 5: Mix 100 �L of PBMCs*(1) into each FACS tube with K562** (2) (E:T ratio; K562: PBMCs = 1: 50; *(1) has 50 x104 cells)

1. Centrifuge at 250 x g for 1 min 2. Incubate 4 HOURS in humidified incubator at 37oC, after then put them on ICE!! 3. Add 3 �L of CD56-PE antibody into every tube and incubate 20 min 4. 20 �L of PI (1�g/ml) are added and incubate 10 min just before acquisition 5. Add 150 �l of PBS� Flow cytometry acquisition (within 75 sec acquisition time)

b. CytoTox96 assay: using U-bottom 96 well plate. (1 plate for 3 subjects)

Wells 1: take 50 �L of K562**(3) for Max, with 50 �L of TCM (quadruplicate) Wells 2: take 50 �L for K562**(3) only with 50 �L of TCM (quadruplicate) Wells 3: take 50 �L for medium only (10% Human AB serum) (quadruplicate) Wells 4: take 50 �L for lymph only with 50 �L of TCM (duplicate)

Experimental wells: Mix 50 �L of PBMCs*(1) into each well having with K562** (3) 1. Centrifuge at 250 x g for 3 min and incubate 4 HOURS in humidified incubator at 37oC 2. Centrifuge at 250 x g for 3 min (600 rpm) 3. Take 50 �L of supernant and transfer to flat 96 wells plate (for LDH assay: CytoTox 96®)

a. Flow cytometric acquisition:

1. Use saved templates 1st for NKCA, (then CD56 dim & bright measurement) 2. A region 1 (R1): SSC vs. fluorescence-1 (CD45-FITC: Fl-1), the cluster of target cells 3. AT LEAST 3,000 TARGET CELLS (IN R1) collected per sample 4. Tested in duplicate and the results presented as mean values

b. CytoTox96® LDH measurements:

1. Defrost Substrate Mix, & Add 10 �l of lysing solution in MAX quadruplicates 45 min prior to 2. 2. Centrifuge at 250 x g for 3 min (600 rpm) and transfer 50 �l of supernant and add 50 �l of

Substrate Mix, then incubate 30 min at room temp in the dark. 3. Add 50 �l of stop solution, and measure at 490 nm! (Test #30 on the machine programme)



CD56 NK cells (dim & bright) analysis concurrently with

NK cytotoxic activity (LDH) assay protocol

SOP-3b written by Dr. Akira Naito Jun. 2004

Materials: Buffers:

Tissue culture medium (TCM): RPMI 1640 supplemented with 1% glutamine (200 mM), 1% penicillin (5000 IU/ml)/ streptomycin (5000 �g/ml), 1% non-essential amino acids (100 x), 1% sodium pyruvate (100 mM), LymphPrep (Invitrogen) In activated fetal calf serum & human AB serum (Sigma H-4522): 56oC for 35 min prior to be frozen.

Chemicals / antibodies: 0.05% of Eosin Y (Sigma-Aldrich®, HT110) for dyes, anti-CD16-FITC (BD®), anti-CD56-PE (BD® 555516), anti-CD3-Cy-Chrome (BD®), Hydrocortisone (Sigma-Aldrich® H-0135), Melatonin (Sigma-Aldrich® M-)

Materials needed: Universals, 1 ml pipettes, 20 ml pipettes, Tips (1ml, yellow), Flasks (40, 100 ml), FACS tubes, 24 wells plate, 96 wells plate (U-bottom, flat-bottom), CytoTox 96® kit (Promega G1780), ELISA kit for cortisol and melatonin (plasmas & supernatants) (DRG #EIA-I887, #EIA-I)

Drug preparation: - Hydrocortisone (cortisol) 250 nM (1 ��in the adding solution) in TCM - Melatonin 50 pg/mL is upper physiological concentration (200 pg/mL in the adding solution) - DHEA-S

Cell preparation: - Peripheral blood mononuclear cells (PBMCs) 1. Centrifuge fresh blood at 1500 rpm 10 min (3.5 tubes of 10 ml heparinized whole blood) 2. Collect the supernatant plasma into 1 tube (�stock in a freezer for further study) 3. Add TCM to each and get these bloods onto Lymph Prep gently with great care. 4. Centrifuge 1500 rpm 25 min 5. Collect the layer of PBMCs with upper layer 6. Wash with TCM Centrifuge 1500 rpm 10 min � (with K562 first centrifuge) 7. Wash with 10% FCS in TCM Centrifuge 1500 rpm 10 min � (with K562 second centrifuge) 8. Decant the supernatant and add 2 ml of foetal calf serum (FCS) + 18 ml of TCM 9. Transferred to a 250 ml culture flask for ‘monocyte depletion’, incubate 1 HOUR 10. Collect non-adherent cells from flask, centrifuge 1500 rpm 10 min 11. Add 3000 �L of TCM and get 10 �L of that + 90 �L of Eosin 12. Count in microscope (in 10 order: minimum >150) 150 x 10 x 104/ml =1.5 x 107/ml�add 1500(= (1500-1000) x 3) �L of TCM

� 1.0 x107/ml (x1.5ml) <PBMCs 1> � 1 tube (Time 0 data): 0.5 ml of <PBMCs 1> + 0.5 ml of TCM

� 5.0 x 106/ml (x 0.6ml) � collect in FACS tubes � 24-well-plate (incubate): 0.7 ml of <PBMCs 1> + 0.4 ml of TCM + 0.3 ml of FCS + 0.7 ml of 0, 50 pg/mL MELATONIN + 0.7 ml of 0, 250 nM CORTISOL

TCM / TCM Cortisol 250 nM / TCM TCM / Melatonin 50 pg/ml Cortisol + Melatonin

� Take 1 ml of supernant to stock at –80 oC for further cortisol ELISA analysis 13. Wash with TCM, centrifuge 1500 rpm 6 min 14. Add 450 �l of TCM and get 10 �l of that + 90 �l of Eosin (0.05% Eosin Y) 15. Count in microscope (in 5 order)

65 x 10 x 104/ml = 65 x 105/ml�add 150 (= 65/50 x 500 -500) �l of TCM � 50 x105/ml of PBMCs*(1) (100 �l has 50 x104 cells: minimum volume needed > 500 �l) � Take 200 �l of *(1) and add 10 �l of anti CD-3-APC, CD-56-Cy-Chrome, CD16=FITC, and Nkp30-PE or Nkp46-PE antibodies and incubate 20 min (Controls: Non, FITC-CD45, PE-CD56, Cy-Chrome-CD3, APC-CD8 single stained tubes)



SOP-3: (continued)

- K562 tumour cells (require 2.0-5.0 x 106 cells / total) 6. Unfrozen stock K562 cells (5 x 106 cells/ml in 10% DSMO, 20% FCS, 70% TCM at –80 oC) and

culture them 1-2 weeks prior experiment start. (pass cells every 2-3 days) 7. Culture 10 ml of 2 x 105 cells/ml concentration 2 days prior to the experiment. 8. After 3rd wash, decant the supernatant and add 1000 �L of TCM 9. Get 10 �L of K562 + 90 �L of dye (0.05 % Eosin Y) 10. Count in microscope

50 x10 x104/ml = 5 x106/ml � add 4(=5-1) ml of TCM� 1.0 x106/ml <K> 1ml of <K> +2 ml of FCS +7ml of TCM =1.0 x105/ml of K562 (*2) in 40ml culture flask 0.5ml of <K> + 1 ml of Human AB serum + 3.5ml of TCM = 1.0 x105/ml of K562 (*3) � take 100 �L of this (*2) (= 1.0 x104 cells) into each incubation tube** (2) (duplication) � take 50 �L of this (*3) into each wells in 96-well plate**(3) (duplication)

Method:

b. Flow assay: Tubes (1-4) for setting-up for acquisition (gating K562 region & CD56 cut-off) Tube 1: take 100 �L for lymph only (for negative control) + 80 �L of TCM + 20 �L of FCS Tube 2: take 100 �L for lymph only (for positive control) + 80 �L of TCM + 20 �L of FCS Tube 3: take 200 �L for K562**(2) only for flow cytometric assay Tube 4: take 200 �L for K562**(2) only for duplication

Experimental tubes: from 5: Mix 100 �L of PBMCs*(1) into each FACS tube with K562** (2) (E:T ratio; K562: PBMCs = 1: 50; *(1) has 50 x104 cells)

6. Centrifuge at 250 x g for 1 min 7. Incubate 4 HOURS in humidified incubator at 37oC, after then put them on ICE!! 8. Add 3 �L of CD56-PE antibody into every tube and incubate 20 min 9. 20 �L of PI (1�g/ml) are added and incubate 10 min just before acquisition 10. Add 150 �l of PBS� Flow cytometry acquisition (within 75 sec acquisition time)

b. CytoTox96 assay: using U-bottom 96 well plate. (1 plate for 3 subjects)

Wells 1: take 50 �L of K562**(3) for Max, with 50 �L of TCM (quadruplicate) Wells 2: take 50 �L for K562** (3) only with 50 �L of TCM (quadruplicate) Wells 3: take 50 �L for medium only (10% Human AB serum) (quadruplicate) Wells 4: take 50 �L for lymph only with 50 �L of TCM (duplicate)

Experimental wells: Mix 50 �L of PBMCs*(1) into each well having with K562** (3) 4. Centrifuge at 250 x g for 3 min and incubate 4 HOURS in humidified incubator at 37oC 5. Centrifuge at 250 x g for 3 min (600 rpm) 6. Take 50 �L of supernant and transfer to flat 96 wells plate (for LDH assay: CytoTox 96®)

a. Flow cytometric acquisition:

5. Use saved templates 1st for NKCA, (then CD56 dim & bright measurement) 6. A region 1 (R1): SSC vs. fluorescence-1 (CD45-FITC: Fl-1), the cluster of target cells 7. AT LEAST 3,000 TARGET CELLS (IN R1) collected per sample 8. Tested in duplicate and the results presented as mean values

b. CytoTox96® LDH measurements:

16. Defrost Substrate Mix, & Add 10 �l of lysing solution in MAX quadruplicates 45 min prior to 2. 17. Centrifuge at 250 x g for 3 min (600 rpm) and transfer 50 �l of supernant and add 50 �l of

Substrate Mix, then incubate 30 min at room temp in the dark. 18. Add 50 �l of stop solution, and measure at 490 nm! (Test #30 on the machine programme)



Appendix 5: Papers

i. Peer reviewed publications

(1) Bennett, B. M., Laidlaw, T. M., Dwevidi, P., Naito, A., Gruzelier, J. H. (2006). "A

qualitative study of the experience of self-hypnosis or Johrei in metastatic breast cancer

using interpretative phenomenological analysis." Contemporary Hypnosis 23(3): 127-

140.

(2) Laidlaw, T. M., Naito, A., Dwivedi P., Hansi N. K., Henderson D. C., Gruzelier J. H.

(2006). "The Influence of 10min of the Johrei healing method on laboratory stress."

Complementary Therapies in Medicine, 14(2): 127-32.

(3) Laidlaw, T., Dwivedi, P., Naito, A., Gruzelier, J. (2005). Low self-directedness (TCI),

mood, schizotypy and hypnotic susceptibility. Personality and Individual Difference, 39,

469-480

(4) Laidlaw, T. M., Bennett, B. M., Dwevidi, P., Naito, A., Gruzelier, J. H. (2005). Quality

of Life and Mood Changes in Metastatic Breast Cancer after training in Self-hypnosis or

Johrei. Contemporary Hypnosis, 22(2): 84-93.

(5) Gruzelier, J.H., De Pascalis, V., Jamieson, G., Laidlaw, T., Naito, A. Dwivedi, P. (2004).

Relations between hypnotisability and psychopathology revisited. Contemporary

Hypnosis, 21, 169-170

(6) Laidlaw, T., Kerstein, R., Bennett, B. M., Naito, A., Dwivedi, P., Gruzelier, J. (2004).

Hypnotizability and immunological response to psychological intervention in HIV.

Contemporary Hypnosis, 21(3): 126-135.

(7) Naito, A., Laidlaw, T. M., Henderson, D. C., Farahani, L., Dwivedi, P., Gruzelier, J. H.

(2003). The impact of self-hypnosis and Johrei on lymphocyte subpopulations at exam

time: a controlled study. Brain Research Bulletin 62(3): 241-253.

(8) Laidlaw, T. M., Naito, A., Dwivedi, P., Enzor, N. A., Brincat, C. E. Gruzelier, J. H.

(2003). Mood Changes after self-Hypnosis and the Johrei healing method Prior to Exams.

Contemporary Hypnosis, 20(1), 25-40.

(9) Naito, A., Sugawara, H., Shimura, M., Azuma, T., Hujisawa, K., Kubo, C. (2000)

Behaviour-therapeutic approach to a patient of pain disorder, with a remarkable

avoidant-behaviour causing disused-atrophy of muscle. Psychosomatic Medicine, 4, 295-

299



ii . Presentation and workshop given (underlined person is the main speaker):

1) Young Scientist Day at the Graduate School of Life Science and Medicine Student

Symposium, London, U.K. May. 2006, “The influence of psychological intervention

upon disease progression in HIV-infected patients” , Naito, A., Laidlaw, T., Bennett, B,

Barton, S., Gruzelier, J., Henderson, D. Poster session

2) 18th World Congress on Psychosomatic Medicine, Kobe, Japan. Aug. 2005 “The

influence of psychological interventions upon stress related changes 1. In exam

associated stress in university students” Naito, A., Laidlaw, T., Dwivedi, P., Gruzelier, J.,

Henderson, D. Poster session and published in the Journal of Psychosomatic Research 58

(2005), S63-64

3) 18th World Congress on Psychosomatic Medicine, Kobe, Japan. Aug. 2005 “The

influence of psychological interventions upon stress related changes 2. In disease

associated stress in HIV-infected patients” Naito, A., Laidlaw, T., Bennett, B., Gruzelier,

J., Barton, S., Henderson, D. Poster session and published in the Journal of

Psychosomatic Research 58 (2005), S63-64

4) 18th World Congress on Psychosomatic Medicine, Kobe, Japan. Aug. 2005 “Stress

related changes associated with in vitro exposure to cortisol 1. Effects upon Natural

Killer cells” Naito, A., Ugwu-Onuoha, I., Henderson, D. Poster session and published in

the Journal of Psychosomatic Research 58 (2005), S63-64

5) 18th World Congress on Psychosomatic Medicine, Kobe, Japan. Aug. 2005 “Stress

related changes associated with in vitro exposure to cortisol 2. Effects upon T-

lymphocytes” Naito, A., Henderson, D. Poster session and published in the Journal of

Psychosomatic Research 58 (2005), S63-64


Symposium, London, U.K. May. 2005, “The influence of Psychological Intervention

upon Neuro-Endocrine-Immune interaction” , Naito, A., Laidlaw, T., Gruzelier, J.,

Henderson, D. Poster session


Symposium, London, U.K. May. 2005, “The influence of Psychological Intervention

upon disease progression in HIV-infected patients” , Naito, A., Laidlaw, T., Bennett, B.,

Barton, S., Henderson, D. and Gruzelier, J. Poster session



8) The Medical Research Society, the Academy of Medical Sciences and the Royal College

of Physicians joint fourth annual meeting for Clinician and Scientists in Training,

London, U.K. Feb. 2005, “The influence of Psychological Intervention upon Neuro-

Endocrine-Immune interaction.” Naito, A., Laidlaw, T. M., Gruzelier, J. H., Henderson,

D. C. Poster session

9) British Society of Immunology annual Congress, Harrogate, U.K. Dec. 2004, “The

effects of 24 hours incubation of human peripheral blood mononuclear cells with cortisol

upon Natural Killer cell cytotoxic activity.” Naito, A., Ugwu-Onuoha, I. C., Henderson,

D. C. Poster session (Naito, A., et al. (2004). Immunology 113 Sup.1: 133.

10) British Society of Immunology annual Congress, Harrogate, U.K. Dec. 2004, “The

effects of incubation of human peripheral blood mononuclear cells with the stress related

hormones, cortisol and melatonin, upon in vitro lymphocyte proliferative responses.”

Naito, A., Henderson, D. C. Poster session (Naito, A., et al. (2004). Immunology 113

Sup.1: 133.

11) British Society of Experimental and Clinical Hypnosis conference, London, July 2003.

“Hypnotisability and Problem Personalities” Laidlaw, T. M., Dwivedi, P., Naito, A.,

Gruzelier, J. H. Free paper

12) Ninth Congress of the European Society of Hypnosis and Psychosomatic Medicine,

Rome, Sept. 2002, “Self-hypnosis and Johrei practice on immunological measures”

Naito, A., Laidlaw, T. M., Dwivedi, P., Farahani, L., Gruzelier, J. H. Free paper


Rome, Sept. 2002, “Psychological effect of Self-hypnosis, Johrei and Relaxation”

Laidlaw, T. M., Naito, A., Dwivedi, P., Brincat, C., Enzor, N., Gruzelier, J. H. Free

paper


Rome, Sept. 2002, “A comparison, using EEG measures, between Self-hypnosis and a

Japanese healing method” Dwivedi, P., Lynch, C., Laidlaw, T. M., Naito, A., Gruzelier,

J. H. Free paper


Rome, Sept. 2002, workshop: “Johrei: Introductory Workshop” Naito, A., Laidlaw, T.

M., Dwivedi, P., Gruzelier, J. H. Free paper

16) British Society of Experimental and Clinical Hypnosis conference, Leamington Spa,

May 2002. “Self hypnosis, the Johrei healing method and relaxation-control groups: A

comparison” Laidlaw, T. M., Naito, A., Dwivedi, P., Gruzelier, J. H. Free paper



iii. Supervisor for research students:

Master of Science research project:

1) Alex Gale (Evaluation of naïve, memory and regulatory CD4+ T-cells in human

immunodeficiency virus infection. Kings College / University of London, MSc

Immunology 2006).

2) Ijeoma Ugwu-Onuoha (The effect of Stress hormone, cortisol, on Natural Killer

cell cytotoxic activity against K562 cells, in vitro. University of East London,

MSc Immunology 2004).*

Bachelor of Science research projects:

1) Linda Farahani (The Effect of Self-hypnosis, Johrei and Stress on Peripheral

Blood Immune Parameters, Imperial College London / University of London,

BSc Medicine 2002).*

2) Christine Brincat (Impact of Self-hypnosis and Johrei on Psychological

Parameters in the Healthy Population, Imperial College London / University of

London, BSc Medicine 2002).*

3) Nick Enzor (Individual differences in Cognitive Flexibility and its Relationship to

Profound State of Relaxation, Imperial College London / University of London,

BSc Medicine 2002).*

4) Navjot Hansi (Cortisol and Mood Changes with Johrei after an acute Stressor,

Imperial College London / University of London, BSc Medicine 2003).*

5) Anil Karmali (An EEG study of the Japanese Healing Method: Johrei, Imperial

College London / University of London, BSc Medicine 2003).

6) Ryan Kerstein (Hypnotisability and Immune Status in HIV blood results after

Self-hypnosis or Johrei, Imperial College London / University of London, BSc

Medicine 2004).*

Papers have been resulted from the projects marked with an asterisk.



Appendix 6: Additional results Analysis of the comparison between Cohorts A and B in the student study (3.1.1)

Table A-1: Mean (95% C.I.) PSS levels of the Cohorts A and B at the Non-exam and Exam time points

Perceived Stress Scale Non-exam Exams

Cohort A Cohort B Cohort A Cohort B Mean level (95% C.I.)

19.9 (12.7 – 27.1)

22.4 (15.0 – 29.8)

24.5 (18.1 – 30.9)

27.1 (20.4 – 33.8)

n 8 14 8 14

Table A-2: Mean (95% C.I.) State anxiety levels of the Cohorts of A and B at the Non-exam and Exam time points

State anxiety score Non-exam Exams

Cohort A Cohort B Cohort A Cohort B Mean level (95% C.I.)

34.0 (29.8 – 38.2)

36.7 (33.1 – 40.3)

34.9 (30.3 – 39.5)

46.9 (43.7 – 50.1)

n 8 14 8 14

Table A-3: Mean (95% C.I.) NK cytotoxic activity in the Cohorts A and B at the Non-exam and Exam time points

NK cytotoxic activity (%Killing) Non-exam Exams

Cohort A Cohort B Cohort A Cohort B Mean (95% C.I.)

6.07 (0 – 12.35)

9.37 (3.88 – 14.87)

3.21 (0 – 7.33)

10.38 (3.09 – 17.67)

N 9 12 9 12 Table A-4: Mean (95% C.I.) NK-cell percentages in the Cohorts A and B at the Non-exam and Exam

time points NK-cell percentage

Non-exam Exams


6.36 (3.476 – 8.87)

8.86 (6.66 - 11.05)

7.34 (4.20 – 10.48)

8.71 (6.72 – 10.69)

n 10 16 10 16 Table A-5: Mean (95% C.I.) CD4 T-cell percentages in the Cohorts A and B at the Non-exam and Exam

time points CD4 T-cell percentage

Non-exam Exams


48.54 (43.04 – 56.04)

43.88 (40.15 - 47.61)

48.29 (36.72 – 54.80)

43.24 (39.68 – 46.79)

n 10 16 10 16



Table A-6: Mean (95% C.I.) CD8 T-cell percentages in the Cohorts A and B at the Non-exam and Exam time points

CD8 T-cell percentage Non-exam Exams


26.26 (22.64 – 29.88)

28.90 (26.06 - 31.74)

26.34 (22.11 – 30.57)

28.74 (26.06 – 31.43)

N 10 16 10 16

Analysis of the comparison between Stressed and Non-stressed students (3.1.2) Table A-7: Mean (95% C.I.) NKCA levels at the Non-exam and Exam time points

NKCA (% killing) Non-exam Exams


7.96 (3.86 - 12.05)

7.31 (2.61 – 12.01)

N 21 21

Table A-8: Mean (95% C.I.) NK-cell and CD4 and CD8 T-cell (%) at the Non-exam and Exam time points

(%) Non-exam Exams

Mean NK-cell percentages (95% C.I.)

7.90 (6.20 – 9.60)

8.18 (6.48 - 9.88)

Mean CD4 T-cell percentages (95% C.I.)

45.7 (42.5 – 48.9)

45.2 (41.8 - 48.6)

Mean CD8 T-cell percentages (95% C.I.)

27.9 (25.6 – 30.1)

27.8 (25.5 – 30.1)

N 26 26

Table A-9: Number of students in the Not-stressed and Stressed subgroups with regard to gender who filled in the PSS and had blood collection for lymphocyte and NKCA level analyses

(Note: figures in the Stressed subgroup include one male whose result failed to obtain for lymphocyte) male female Total Not-stressed 11 9 20 Stressed 10 11 21

Total 21 20 41

Table A-10: Mean (95% C.I.) NK-cell percentages in the Not-stressed and Stressed subgroups NK-cell (%)


10.0 (7.6 – 11.7)

9.1 (6.8 – 11.4)

n 20 20

Table A-11: Mean (95% C.I.) NK-cell percentages in the Not-stressed and Stressed male students NK-cell (%)


10.2 (7.1 – 13.4)

12.0 (7.9 – 16.1)

n 11 9



Table A-12: Mean (95% C.I.) NK-cell percentages in the Not-stressed and Stressed female students NK-cell (%)


9.7 (6.0 - 13.4)

6.7 (5.2 – 8.1)

n 9 11

Table A-13: Mean (95% C.I.) levels of NKCA (% killing) in the Not-stressed and Stressed female students

NKCA (% killing)


10.9 (4.9 – 16.9)

6.7 (2.1 – 11.4)

n 9 11

Table A-14: Mean (95% C.I.) levels of NKCA (% killing) of male and female NKCA (% killing)

Male Female


9.0 (4.9 – 13.0)

8.6 (4.9 – 12.3)

n 21 20

Table A-15: Mean (95% C.I.) ratios of NKCA to NK-cell in the Not-stressed and Stressed female students NKCA to NK-cell ratio


Mean ratio (95% C.I.)

1.18 (0.50 – 1.87)

0.91 (0.23 – 1.60)

n 9 11

Table A-16: Mean (95% C.I.) ratios of NKCA to NK-cell in male and female students NKCA to NK-cell ratio

male female

Mean ratio (95% C.I.)

0.88 (0.38 – 1.38)

1.04 (0.56 – 1.52)

N 21 20 Table A-17: Mean (95% C.I.) CD4 and CD8 T-cell levels (%) in the Not-stressed and Stressed subgroups

(%) Not-stressed Stressed

Mean CD4 T-cell level (95% C.I.)

44.1 (40.0 – 48.3)

47.8 (45.5 – 50.1)


27.8 (25.4 – 30.2)

26.1 (23.7 – 28.6)

n 20 20

Table A-18: Mean (95% C.I.) CD4 and CD8 T-cell levels (%) in the Not-stressed and Stressed male students



40.8 (35.9 – 45.7)

46.1 (42.7 – 49.5)


28.5 (24.3 – 32.6)

25.2 (21.2 – 29.2)

n 11 9



Table A-19: Mean (95% C.I.) CD4 and CD8 T-cell levels (%) in the Not-stressed and Stressed female students



48.2 (41.9 - 54.6)

49.2 (46.2 – 52.2)


27.0 (24.9 - 29.1)

26.9 (23.7 – 30.1)

n 9 11

Table A-20: Mean (95% C.I.) CD8 T-cell levels (%) of male and female students

Analysis of the comparison between the intervention groups and control in the

student study (3.1.3)

Table A-21: Mean (95% C.I.) PSS levels in the three groups at the Exam time point

PSS score

Self-hypnosis Johrei Controls Mean score (95% C.I.)

24.5 (20.4 - 28.6)

22.8 (17.5 – 28.1)

26.3 (21.9 - 30.8)

N 12 11 9

Table A-22: Mean (95% C.I.) PSS scores in male subjects in the three groups at the Exam time point

PSS score


25.3 (19.5 - 31.0)

21.1 (16.6 – 25.7)

22.0 (11.9 - 32.1)

N 7 7 3

Table A-23: Mean (95% C.I.) PSS scores in female subjects in the three groups at the Exam time point

PSS score


23.4 (17.0 - 29.8)

25.8 (12.9 – 38.6)

28.5 (24.5 - 32.5)

N 5 4 6

Table A-24: Mean (95% C.I.) State anxiety scores in the male subjects of the Self-hypnosis, Johrei and Relaxation control groups at baseline and the Exam time point

State scores in the STAI Baseline Exams

Self-hypnosis Johrei Controls Self-hypnosis Johrei Controls Mean score (95% C.I.)

37.8 (32.7 - 42.8)

35.9 (29.6 – 42.1)

34.3 (30.2 - 38.3)

44.4 (40.1 - 48.7)

43.8 (39.6 – 47.9)

37.0 (28.7 - 45.3)

n 8 8 4 8 8 4

CD8 T-cell levels (%) male Female

Mean (95% C.I.)

27.0 (24.1 – 29.9)

26.9 (25.0 – 28.8)

n 20 20



Table A-25: Mean (95% C.I.) State scores in the female subjects in the Self-hypnosis, Johrei and Relaxation control group at baseline and the Exam time point

State score in the STAI Baseline Exams

Self-hypnosis Johrei Controls Self-hypnosis Johrei Controls Mean score (95% C.I.)

36.6 (33.0 - 40.2)

32.8 (23.1 – 42.4)

29.7 (25.9 - 33.4)

38.8 (35.9 - 41.7)

29.5 (24.1 – 34.9)

39.2 (29.5 - 48.9)

n 5 4 6 5 4 6

Table A-26: Mean (95% C.I.) NKCA levels (% killing) in the three groups at the Exam time point

NKCA (% killing)


(95% C.I.) 6.0

(0.3 - 11.7) 12.9

(6.3 – 19.6) 12.2

(4.4 - 19.9) N 11 11 9

Table A-27: Mean (95% C.I.) NKCA levels (% killing) in male subjects in the three groups at the Exam

time point

NKCA (% killing)


(95% C.I.) 7.3

(0.0 - 16.0) 16.2

(7.9 – 24.6) 9.8

(0.0 - 23.9) n 6 7 4

Table A-28: Mean (95% C.I.) NKCA levels (% killing) in female subjects in the three groups at the Exam

time point

NKCA (% killing)


(95% C.I.) 4.4

(0.0 - 12.2) 7.1

(0.0 – 16.8) 14.0

(4.6 - 23.4) n 5 4 5

Table A-29: Mean (95% C.I.) levels of NK-cell (%) of male students in the groups of the Self-hypnosis,

Johrei and Controls at baseline and the Exam time point NK-cells (%)



8.9 (6.4 - 11.3)

9.5 (3.5 – 12.5)

11.8 (8.4 - 15.3)

9.4 (7.0 - 11.8)

12.6 (9.5 – 15.8)

6.6 (4.2 - 9.1)

n 7 7 5 7 7 5

Table A-30: Mean (95% C.I.) levels of NK-cells (%) in the female subjects in the Self-hypnosis, Johrei and Relaxation control groups at baseline and the Exam time point

NK-cells (%) Baseline Exams

Self-hypnosis Johrei Controls Self-hypnosis Johrei Controls Mean level (95% C.I.)

10.6 (7.4 - 13.9)

4.4 (1.0 – 7.8)

6.3 (4.4 - 8.3)

7.5 (1.2 - 13.9)

7.7 (3.8 – 11.6)

6.8 (3.4 - 10.1)

n 5 4 6 5 4 6



Table A-31: Mean (95% C.I.) levels of CD4 T-cell (%) of male students in the Self-hypnosis, Johrei and Relaxation control groups at baseline and the Exam time point

CD4 T-cells (%) Baseline Exams


44.8 (40.0 - 49.6)

43.8 (39.9 – 47.7)

43.6 (38.9 - 48.4)

44.9 (38.2 - 51.6)

38.2 (33.8 – 42.6)

46.2 (38.9 - 53.4)

n 7 7 5 7 7 5

Table A-32: Mean (95% C.I.) levels of CD4 T-cells (%) in the female students in the Self-hypnosis, Johrei and Relaxation control groups at baseline and the Exam time point



46.8 (42.4 - 51.2)

51.3 (46.4. – 56.3)

46.6 (41.6 – 51.6)

47.0 (40.3 - 53.7)

51.7 (44.4 – 58.9)

47.5 (42.0 -52 9.)

n 5 4 6 5 4 6 Table A-33: Mean (95% C.I.) levels of CD8 T-cell (%) of male students in the Self-hypnosis, Johrei and

Relaxation control groups at baseline and the Exam time point CD8 T-cells (%)



25.0 (18.3 - 31.6)

26.7 (22.3 – 31.1)

26.6 (23.5 - 29.6)

27.7 (22.3 - 33.2)

28.8 (23.8 – 33.8)

26.8 (22.2 - 31.5)

n 7 7 5 7 7 5

Table A-34: Mean (95% C.I.) levels of CD8 T-cells (%) in the female students in the Self-hypnosis, Johrei and Relaxation control groups at baseline and the Exam time point



25.4 (17.6 - 33.4)

26.9 (24.6 – 29.3)

27.8 (23.0 – 32.5)

27.4 (22.5 - 32.3)

25.4 (23.6 – 27.3)

26.9 (22.7 - 31.1)

n 5 4 6 5 4 6

Analysis of the comparison between Stress perception and the disease parameters

in HIV -infected individuals (3.2.1)

Table A-35: Correlation between the CD4 gradient (cells per �l per month) and the stress perception scores and the perceived quality-of-life at recruitment time point (pre) and four-months after the

recruitment (post) State anxiety IES PSS LoC MCS PSQI

pre post pre post pre post pre post pre post pre post

R .15 .28 .28 .19 .14 .18 .32 .02 - .24 .15 .22 - .03 2-tailed p NS NS NS NS NS NS 0.085 NS NS NS NS NS

N 30 30 30 30 30 30 30 30 30 30 30 30 NS: p > 0.1



Table A-36: Correlations between the CD4 gradient (cells per �l per month) and the change scores of stress perception scales in:

State anxiety IES PSS R .13 - .18 .02

2-tailed p NS NS NS n 30 30 30

NS: p > 0.1

Table A-37: Number of HIV-infected individuals who had viral load level check at the monthly time periods from the Recruitment to four months after the recruitment (Term 4)

Valid number

N Percent Term 4 (four months after the Recruitment time point) 10 15.9% Term 3 (three months after the Recruitment time point) 17 27.0% Term 2 (two months after the Recruitment time point) 17 27.0% Term 1 (one month after the Recruitment time point) 14 22.2% Baseline (2 weeks before and after the recruitment) 18 28.6%

Table A-38: Correlation between the viral load level gradients (log-transformed viral copies per �l per month) and the stress perception and the perceived quality-of-life scores at recruitment time point (pre)

and four months later (post) State anxiety IES PSS LoC MCS PSQI

pre post pre post pre post pre post pre post pre post

R .04 .04 .25 .04 - .02 - .01 .21 .03 - .09 .08 .20 .11 2-tailed p NS NS NS NS NS NS NS NS NS NS NS NS

n 29 29 29 29 29 29 29 29 29 29 29 29 NS: p > 0.1

Table A-39: Correlation between the viral load level gradient (log-transformed copies per �l per month)

and the change scores of perceived stress and quality-of-life scores in: State anxiety IES PSS LoC MCS PSQI

R - .02 - .30 - .08 - .13 .29 - .15 2-tailed p NS NS NS NS NS NS

n 29 29 29 29 29 29 NS: p > 0.1

Table A-40: Correlation between the NK gradient (cells per �l per month) and the stress perception scores

and the perceived quality-of-life at recruitment time point (pre) and four-months after the recruitment (post)

State anxiety IES PSS LoC MCS PSQI

pre post pre post pre post pre post pre post pre* post R .26 .19 .01 - .04 .20 .11 .28 .17 - .30 - .24 .44 .28

2-tailed p NS NS NS NS NS NS NS NS NS NS 0.017 NS N 29 29 29 29 29 29 29 29 29 29 29 29

NS: p > 0.1; *: p < 0.05

Table A-41: Correlation between the NK gradient (cells per �l per month) and the change scores of perceived stress and quality-of-life scores in:

State anxiety IES PSS LoC MCS PSQI R - .19 - .07 - .23 - .16 .11 - .22

2-tailed p NS NS NS NS NS NS N 29 29 29 29 29 29

NS: p > 0.1



Analysis of the comparison between the intervention groups and control in HIV-

infected individuals (3.2.2)

Table A-42: Mean (95% C.I.) levels of the State anxiety and PSS scores in the HIV-individuals in the Self-hypnosis, Johrei and wait-listed control groups at the Baseline and the Post-intervention time points

Baseline Post-intervention Self-hypnosis Johrei Controls Self-hypnosis Johrei Controls Mean Anxiety

(95% C.I.) 41.5

(24.6 - 58.4) 35.7

(25.0 - 46.4) 43.4

(30.2 - 55.6) 37.6

(25.0 - 50.2) 35.9

(24.8 - 47.0) 42.4

(29.2 - 55.6) Mean PSS (95% C.I.)

31.8 (24.5 - 39.1)

31.3 (24.8 - 37.8)

31.7 (24.4- 39.0)

30.6 (24.9 - 36.3)

32.1 (27.2 - 37.0)

31.8 (26.7 - 38.7)

N 21 12 18 21 12 18

Table A-43: Mean (95% C.I.) levels of the LoC, MCS and PSQI in the HIV-individuals in the Self-hypnosis, Johrei and wait-listed control groups at the Baseline and Post-intervention time points

Baseline Post-intervention

Self-hypnosis Johrei Controls Self-hypnosis Johrei Controls Mean LoC (95% C.I.)

10.2 (9.3 - 11.1)

12.0 (10.8 - 13.2)

11.2 (10.2 - 12.2)

9.4 (8.4 - 10.4)

11.3 (10.0 - 12.6)

11.2 (10.2 - 12.2)

Mean MCS (95% C.I.)

43.0 (40.0 - 46.0)

46.7 (42.8 - 50.6)

39.7 (36.5 - 42.9)

47.4 (44.6 - 50.2)

48.0 (44.5 - 51.5)

39.5 (36.6 - 43.4)

Mean PSQI (95% C.I.)

9.2 (8.4 - 10.0)

8.6 (7.6 - 9.6)

9.4 (8.6 - 10.2)

8.5 (7.8 - 9.2)

7.5 (6.6 - 8.4)

9.6 (8.9 - 10.3)

n 21 12 18 21 12 18

Table A-44: Mean (95% C.I.) levels of regression gradients in viral load levels (Log-transformed) in HIV-infected individuals in the Self-hypnosis, Johrei and wait-listed control groups

HIV-viral load levels (log-transformed) Self-hypnosis Johrei Controls Mean change (95% C.I.)

- .016 (- .053 to + .019)

- .021 (- .082 to + .040)

- .031 (- .077 to + .014)

N 14 12 12 Table A-45: Mean (95% C.I.) levels of regression gradients in NK-cell (counts per �l per month) in HIV-

infected individuals in the Self-hypnosis, Johrei and wait-listed control groups NK-gradient (counts per �l per month)

Self-hypnosis Johrei Controls Mean change (95% C.I.)

- 2.4 (- 9.4 to + 4.7)

+ 2.8 (- 5.9 to + 11.4)

- 1.3 (- 9.1 to + 6.5)

n 15 10 12



Appendix 7: Research proposal for post-doctorial project

Investigation of stress management, Johrei, upon Health in HIV patients

not receiving anti-retroviral treatment (ART): An Open Study

Akira NAITO M.D. 2006

Background

Johrei is a Japanese stress management system which provides training and encouraging the practice

of self-help coping strategies for dealing with stress. Our recent research studies [Naito et al., 2005] have

shown that the progressive decline in CD4 T-cell counts in HIV infected patients, which is associated

with 'ill -health', was interrupted in patients trained in and practising Johrei over a period of five months. It

is believed [Catalan et al., 1995] that the maintenance of CD4 T-cells over this five months period will

have benefited the patients by prolonging the period of 'good health' and delaying the onset of HIV

related complications and the need for specific HIV treatment.

Purpose

The current study is proposed to:

� Confirm the previous findings;

� Demonstrate in HIV patients that Johrei improves quality of life;

� Determine if Johrei particularly affects CD4 sub-populations such as naïve, memory and

regulatory T-cells; and

� Identify on the basis of specific psychological and immunological profiles which patients would

benefit from practising Johrei.

Method

Subjects

Patients with HIV who have CD4 T-cell count more than 200 cells per microlittre and who are not

receiving anti-retroviral treatment (ART) will be recruited by completing the written consent form.

Study design

Open cohort study compared with concurrent and historical case-matched (age, gender and CD4

counts) control patients selected from the clinical database of results.

Johrei intervention

Training of Johrei, a Japanese stress management system which provides:

� Core philosophies and principles for Johrei practice; and

� Basic techniques: mental image of healing light and taking turns at receiving the light from the

imaginary source and channelling it to the recipient with the non-touching hand.

Johrei can be practised individually but is better in pairs and hence patients will be encouraged to

attend the training session with his/her partner and to practise Johrei with his/her partner.



One weekend training (ten hours excluding two one-hour lunch breaks) and five monthly follow-

ups (1.5-2 hours each) with practice at home a minimum of four 20 min sessions per week monitored

by a self-report record.

Measures

Primary outcome

Assessment of CD4 T-cell decline rate from prospective routine CD4 T-cell counts at one to two

month intervals during the study period and, where appropriate, by reference to historical CD4 T-

cell counts over the preceding six to 12 months.

Secondary outcomes

1. Immunological parameters (on three occasions alongside routine clinical monitoring)

� Naïve and Memory CD4 T-cells and Regulatory T-cell subpopulation

2. Psychological questionnaires (before and three and six months after the training):

� Stress perception: Perceived Stress Score [Cohen et al., 1983]

� Perceived social support: Kesseler Perceived Social Support [Coventry et al., 2004]

� Quality of Life (empowerment): Sense of Coherence [Antonovsky, 1993]

� Quality of Life (spirituality): Spiritual Involvement and Beliefs Scale [Hatch et al., 1998]

� Sleep quality: Pittsburgh Sleep Quality Index [Buysse et al., 1989]

3. Personality questionnaire (only at recruitment):

� Cloninger Temperament and Character Inventory [Cloninger et al., 1993]

4. Financial / Economical analyses (over the six months):

� The cost effective ratio analyses [Hlatky et al., 2004]

Recruitment

84 Johrei participants will be recruited and compared with database controls. This number was

calculated at 5% significance and 90% power on the basis of the previous finding that 58% of

subjects in the Johrei group stayed the same or increased in their CD4 T-cell count compared with

33% of subjects in the control group.

Data collection

Questionnaires: before and at three and six months after Johrei training

Blood samples: an additional 17ml blood sample will be taken at the same time patients come for

monthly routine monitoring checks, at month zero, three and six.

Analyses

The results will be statistically analysed by regression, correlation, analyses of variances

(ANOVA) and student t-test using the Statistical Package for Social Sciences (SPSS) and the

Statistical Analysis Software (SAS).

ph.d. thesis at imperial college london

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