prr.hec.gov.pkprr.hec.gov.pk/jspui/bitstream/123456789/8361/1/syeda... · 2018-07-23 ·...

Evaluation of Nicotinic Acetylcholine Receptors in Learning

and Memory Using Mouse Model of Alzheimer’s Disease

By

Syeda Mehpara Farhat

2010-NUST-DirPhD-V&I-18

Atta-ur-Rahman School of Applied Biosciences

National University of Sciences and Technology

Islamabad Pakistan

2017

Evaluation of Nicotinic Acetylcholine Receptors in Learning

and Memory Using Mouse Model of Alzheimer’s Disease

By


2010-NUST-DirPhD-V&I-18

A thesis submitted in partial fulfillment of the requirement for the

degree of Doctor of Philosophy in

Applied Biosciences

Supervisor

Dr. Touqeer Ahmed

Atta-ur-Rahman School of Applied Biosciences

National University of Sciences & Technology

Islamabad Pakistan

2017

iv

DEDICATED TO MY

PARENTS AND FAMILY

I could never have done this without

their faith, support and constant

encouragement. Thanks to my parents

and family for teaching me to believe in

myself and in my dreams.

Acknowledgements

v

ACKNOWLEDGEMENTS

All praises to Almighty Allah, the Creator and Sustainer of the universe, Who

is the supreme authority, knowing the ultimate realities of universe and source of all

knowledge and wisdom. Without His will nothing could be happened. It has been

deemed a great favor of Allah that I was bestowed upon the vision, initiative, potential

and hope to complete my research project successfully. All regards to the Holy

Prophet Hazrat Muhammad (PBUH) who enable me to recognize my Creator and

His creations to understand the philosophy of life.

It is not a formality but the emotional association to acknowledge the person

who has helped me to achieve this goal. I would like to gratefully acknowledge my

supervisor Dr. Touqeer Ahmed, who truly made a difference in my life. It was under

his tutelage that I developed a focus and became interested in science. He provided

me with direction, technical support and became more of a mentor and friend, than a

professor. I doubt that I will ever be able to convey my appreciation fully, but I owe

him my eternal gratitude. I am thankful to Dr. Najam us Sahar Sadaf Zaidi, Dr. Saadia

Zahid and Dr. Arif Ullah Khan (Riphah Institute of Pharmaceutical Sciances,

Islamabad), my thesis committee members, for their support and guidance.

I owe colossal acknowledgement to Prof. Dr. Karri Lamsa from MRC

Anatomical Neuropharmacology Unit, University of Oxford, UK for accepting me in

his lab as visiting research scholar. He gave me very good scientific ideas and helped

me to excel in research work. I also enjoyed scientific discussions with him. We

would like to acknowledge Dr. Edward O Mann, Associate Professor, from

Department of Physiology, Anatomy and Genetics, University of Oxford, UK for

providing research facilities and technical help and his support during lab

Acknowledgements

vi

experiments. I am also are very thankful Dr. Simon Tuohy, post doc fellow, and Mr.

Julian Bartram from Department of Physiology, Anatomy and Genetics, University

of Oxford, UK for providing important research material to carry out

electrophysiology experiments.. I am also are very thankful to Ms. Kathryn Newton,

for not only helping me in research work but also for making my stay in UK

memorable.

I have no words to express my feelings and gratitude for my dignified father

and my loving mother to whom I owe all that I have in my life. All that I have is due

to their prayers. I am indebted to my parents and whole family for their moral support

and encouragement when it was most required. I would never have been able to get

this achievement without their support and help.

I gratefully acknowledge my respected teacher and HoD of Healthcare

Biotechnology, Dr. Attya Bhatti, for her guidance and moral support. I would like to

acknowledge the whole faculty, Dr. Peter John (Principal of ASAB), Dr. Mohammad

Tahir, (HoD of Plant Biotechnology), Dr Hajra Sadia and Dr. Sobia Manzoor for their

guidance, support and valuable suggestions.

My very special thanks to my dear friend Aamra Mahboob, who not only

helped me in my lab work but also shared all my depressive states during course of

PhD. I would also like to thank Ghazala Iqbal and Habiba Rashid for their guidance

and moral support. I would never forget their company that was the real source of

motivation and encouragement.

I am thankful to my lab fellows, my friends, Aisha Hashmi, Huma Syed, Aliya

Khalid, Saira Justin, Rabia Shakeel, Ayesha Idrees, Saima Rizwan, Nayab Nawaz,

Sara Ahmed, Syeda Ayesha Ali, Maryam Masood, Ayesha Karim Kiani, Asima Zia,

Acknowledgements

vii

Asma Naseer Cheema, Munazza Fatima and Deeba Amraiz who were very kind to me

and who motivated me towards research.

I would like to acknowledge Mr. Ghulam Rabbi, Tayyaba Bashir, Fouzia, and

Sadia for their help during documentation.

My very special thanks to my dear brothers Syed Naveed Farhat and Syed

Nadeem Farhat who supported me not only during my academic career but also in all

other aspects of my life. I owe deep gratitude to my dear brother Syed Munib Farhat,

whose tireless efforts made acquisition of this degree possible for me.

I am very thankful to Higher Education Commission for awarding me the

scholarship to continue my PhD studies and also providing IRSIP scholarship to visit

University of Oxford, UK. I specially acknowledge Rector NUST for his countless

efforts to make ASAB and NUST one of the prestigious institution in Pakistan.


Table of Contents

viii

TABLE OF CONTENTS

TITLE Page No.

Acknowledgements v

List of Abbreviations xii

List of Tables xiii

List of Figures xiv

Abstract xviii

Chapter -1

Introduction 01

1.1 Aims and Objectives 05

Chapter -2

Review of Literature 06

2.1 Alzheimer's Disease 07

2.2 Pathophysiology of the Alzheimer's Disease 07

2.2.1 Amyloid Plaques 08

2.2.2 Neurofibrillary Tangles 09

2.3 Factors responsible for Alzheimer’s disease 10

2.4 Aluminum and Alzheimer's disease 10

2.5 Aluminum in environment 11

2.6 Sources of Aluminum exposure to human 11

2.7 Aluminum via drinking water in Pakistan 13

2.8 Aluminum induced Alzheimer’s Model 15

2.9 Role of Cholinergic system in Alzheimer's disease pathogenesis 17

Table of Contents

ix

2.10 Nicotinic acetylcholine receptors 17

2.10.1 Structure of Nicotinic Acetylcholine Receptors 19

2.10.2 Involvement in Alzheimer’s disease 19

2.11 Toxic Effects of Aluminum on Cholinergic System 23

Chapter -3

Materials and Methods 26

3.1 Chemicals 27

3.2 Animals 27

3.3 Study Design 28

3.4 In-vivo Experiments 31

3.4.1 AlCl3 administration 31

3.4.2 Behavior Tests 31

3.4.2.1 Morris water maze test 31

3.4.2.2 Elevated Plus Maze test 34

3.4.2.3 Open field test 36

3.4.2.4 Social Novelty Preference Test 38

3.4.2.5 Novel Object Recognition 40

3.4.2.6 Fear Conditioning 42

3.4.2.7 Contextual fear memory testing 48

3.4.2.8 Fear Extinction 50

3.5 Gene expression studies 53

3.5.1 RNA extraction 53

3.5.2 RT-PCR for quantification of mRNA levels 54

3.5.3 Polymerase chain reaction (PCR) for expression of genes 54

3.5.3.1 Agarose gel image analysis of the PCR products 55

Table of Contents

x

3.6 Histological Studies 58

3.6.1 Transcardial Perfusion 58

3.6.2 Brain fixation and paraffin embedding 58

3.6.3 Tissue sectioning and cresyl violet staining 59

3.6.4 Quantification of cell number 60

3.7 Determination of aluminum concentration in brain 64

3.8 Determination of acetylcholine level in brain 64

3.9 In-vitro field potential gamma oscillation study 65

3.9.1 Hippocampal slice preparation 65

3.9.2 Electrophysiological recording and field potential analysis 66

3.9.3 Drug Application 66

3.10 Statistical analysis 68

Chapter -4

Results 69

4.1 Effect of aluminum on spatial memory in Morris water maze test 70

4.2 Effect of aluminum on anxiety in elevated plus maze test 73

4.3 Effect of aluminum on anxiety and exploration in open field test 75

4.4 Effect of aluminum on social novelty preference test 78

4.5 Effect of aluminum on novel object recognition test 78

4.6 Effect of aluminum on fear conditioning 82

4.7 Effect of aluminum on contextual fear memory 82

4.8 Effect of aluminum on fear extinction 82

4.9 Gene Expression 86

4.10 Aluminum concentration in brain 90

4.11 Effect of oral aluminum on acetylcholine and free choline levels 90

Table of Contents

xi

4.12 Quantitative analysis of neurodegeneration in brain 94

4.13 Nicotiic acetylcholine receptor modulation of gamma 102

oscillation power in hippocampal slices

4.14 Effect of aluminum on gamma oscillation peak power in 104

hippocampal slices

4.15 Semi-chronic Al treatment causes non reversible changes in 109

hippocampal circuitry

Chapter -5

Discussion 111

Conclusion 131

Future prospects 134

Suggestions for policy makers 135

Chapter -6

References 136

List of Abbreviations

xii

List of Abbreviations

ACh Acetylcholine

AChE Acetyl cholinesterase

AD Alzheimer's disease

Al Aluminum

CCh Carbachol

ChAT Choline acetyltransferase

DHβE Dihydro β erythroidine

DNA Deoxyribonucleic Acid

ICP-AES Inductively coupled plasma-atomic emission spectrometry

LC Locus coeruleus

MC Motor cortex

MLA Methyllycaconitine

nAChRs Nicotinic acetylcholine receptors

Nic Nicotine

SSC1 Somatosensory cortex (hind limb and fore limb region)

SSC2 Somatosensory cortex (dysgranular zone and barrel field)

SN Substantia nigra

VTA Ventral tegmental area

List of Tables

xiii

List of Tables

Table No. Title Page No.

3.1 The direction of animal release, during Morris water

maze test

33

3.2 Primer sequence for each gene used in the study along

with conditions

56

List of Figures

xiv

List of Figures

Figure No. Title Page No.

2.1 Major biological effects of Al on nervous system 16

2.2 Expression of nAChRs in brain 18

2.3 Structure of neuronal nicotinic acetylcholine receptors

(nAChRs)

20

3.1 Experimental study design 29

3.2 Diagrammatic presentation of the study timeline used for AlCl3

treatment in mice for in-vivo experiments

30

3.3 Morris Water Maze (MWM) Apparatus 33

3.4 The elevated plus maze test apparatus 35

3.5 The open field test apparatus 37

3.6 Social novelty preference test setup 39

3.7 Novel object recognition test setup 41

3.8 Fear conditioning protocol 44

3.9 Diagrammatic representation of the brain parts involved in fear

conditioning circuit

45

3.10 Fear conditioning test apparatus 46

3.11 Fear conditioning test. The red arrow shows fear conditioning

instrument and stimulus programming device connected to

computer and blue arrow represents the user interface on

computer screen showing live video recording of the subject

animal in the animal enclosure chamber during fear

conditioning testing procedure.

47

3.12 Contextual fear memory test. 49

3.13 Fear extinction test setup 51

3.14 Fear extinction setup. The red arrow shows fear conditioning

instrument and stimulus programming device connected to

computer and blue arrow represents the user interface on

computer screen showing live video recording of the subject

animal in the animal enclosure chamber during fear extinction

52

List of Figures

xv

testing procedure

3.15 ImageJ software used for densitometric analysis of PCR bands 57

3.16 Presentation of the mouse brain atlas coordinates from where

the sections were taken for histological examination and

quantification of cell number

61

3.17 Histological examination of AD mouse model and control

mouse cortex

62

3.18 Histological examination of AD mouse model and control

mouse hippocampus

63

3.19 Diagrammatic presentation of brain slicing in horizontal plane.

The inset shows different layers of hippocampus and area from

where the recording was done

67

4.1 Effect of Al on spatial and reference memory in Morris water

maze test (MWM)

71

4.2 Graph describing effect of Al on probe trial in MWM 72

4.3 Graphical presentation of measure of anxiety in control and

AD mouse model in EPM

74

4.4 Effect of Al on exploratory activity in open field test 76

4.5 Effect of Al on anxiety behavior in open field test 77

4.6 Effect of Al on Social novelty preference 79

4.7 Effect of Al on Novel object recognition 80

4.8 Graphical illustration of the recognition index for novel object

during test session by both the groups

81

4.9 Effect of Al on fear memory during fear conditioning 83

4.10 Effect of Al on contextual fear memory 84

4.11 Effect of Al on fear extinction. 85

4.12 Image showing sharp bands of 18S and 28S RNA on 2%

agarose gel

87

4.13 Comparison of alpha 7(α7), alpha 4 (α4) and beta 2 (β2)

nAChR gene expression in (a) hippocampus and (b) cortex of

control and AD mouse model

88

4.14 Expression of nicotinic acetylcholine receptor in amygdala and 89

List of Figures

xvi

choline acetyltransferase genes

4.15 The comparison of Al accumulation in cortex, hippocampus

and amygdala of control and AD mouse model

91

4.16 Comparison of acetylcholine level in cortex, hippocampus and

amygdala of the control and AD mouse model

92

4.17 Graphical illustration of total choline and free choline

concentration in control and AD mouse model

93

4.18 The photomicrograph showing representative slides of

hippocampus histology (Nissl staining) sections at 40X

magnification

96

4.19 Graphical elucidation of the cell number in different areas of

the hippocampus in control and AD mouse model. Reduced cell

number represents neurodegeneration after Al treatment

97

4.20 The representative slides of cortex histology (Nissl staining)

sections at 40X magnification

98

4.21 Comparison of cell number in motor cortex of the cortex in

control and AD mouse model

99

4.22 Comparison of cell number in somatosensory cortex of the

cortex in control and AD mouse model

100

4.23 Comparison of cell number in somatosensory cortex

(dysgranular zone and barrel field area) of the cortex in control

and AD mouse model

101

4.24 Field potential recording of gamma oscillation power 103

4.25 Effect of Al on CCh-induced gamma oscillation peak power 105

4.26 CCh-induced gamma oscillation peak power in slices incubated

acutely or semi chronically in Al

106

4.27 Plot shows oscillation peak frequency in experiments. Either

acute (1 hour) or semi-chronic (3-4 hours) incubation to Al did

not change CA3 field potential oscillation peak frequency

107

4.28 CCh-induced gamma oscillation power area 108

4.29 Wash-out of AlCl3 for 1-1.5 hours, after incubation of slices for

3-4 hours in Al, failed to restore oscillation power and its

110

List of Figures

xvii

modulation by nicotine

5.1 Proposed mechanism of learning and memory deficits caused

by Al due to its cholinotoxicity

125

5.2 Cholinergic hypofunction after Al accumulation investigated in

cortex, hippocampus and amygdala and its implications on

behavioral functions

132

Abstract

xviii

ABSTRACT

Background: Aluminum (Al) is known to be associated with etiology of different

neurodegenerative disorders especially of Alzheimer’s disease (AD) and is known to

produce AD like symptoms. It is widely reported that Al affects muscarinic

acetylcholine receptors but limited data is available for its effects on nicotinic

acetylcholine receptors (nAChRs). The aim of this study was to determine that how

Al affects hippocampus, amygdala and cortex dependent learning and memory

functions and expression of nAChRs and choline acetyltransferase (ChAT) genes.

Effect of Al on cholinergic biomarkers i.e. free choline and acetylcholine (Ach) level

were also investigated. Moreover acute effects of Al on nAChRs-mediated

modulation of persistent gamma oscillations in hippocampus was also studied.

Methods: In order to develop the AD mouse model, AlCl3.6H2O (250 mg/kg) was

administered to mice in drinking water 42 days. After completion of Al treatment the

learning and memory deficits were assessed via different behavior tests. nAChRs gene

expression was determined via RT-PCR in cortex, hippocampus and amygdala.

Inductively coupled plasma atomic emission spectrometry (ICP-AES) was used to

measure Al accumulation in brain. To determine how Al affects gamma oscillations,

field potential recordings were performed in CA3 area of acute hippocampal slices.

Results: The results of this study demonstrate that oral Al ingestion caused high

accumulation of Al in brain leading to neuropathological changes that suppressed

expression of nAChR genes and caused neurodegeneration. Longer in-vitro Al

exposure caused permanent changes in hippocampal oscillogenic circuitry and

changed its sensitivity to nAChR-modulation, leading to deficits in memory and

learning in AD mouse model. Moreover in spite of normal free choline availability

Abstract

xix

Ach synthesis was reduced as a result of oral Al exposure. The reduced Ach synthesis

is caused by impaired recycling of Ach due to lower expression of ChAT gene. The

reduced Ach level causes deficits in cholinergic neurotransmission which leads to

memory and cognitive deficits. Moreover, hippocampus is the most affected brain

part after Al intoxication. This study suggests that interference with cholinergic

neurotransmission can be the underlying mechanism through which Al causes

memory and learning deficits and contributes to neuropathological changes leading to

AD.

xx

Chapter 1

INTRODUCTION

Chapter 1 Introduction

Evaluation of Nicotinic Acetylcholine Receptors in Learning and Memory Using Mouse Model of Alzheimer’s

Disease 1

INTRODUCTION

Nervous system’s normal activity is altered as a result of exposure to some

environmental or synthetic toxic substances, which leads to neurodegeneration (Pohl

et al., 2011). Certain trace elements and few metals e.g. Aluminum (Al), Copper,

Mercury, Arsenic, Manganese and Lead can act as neurotoxins when exposed in high

concentrations (Hashmi et al., 2015). Al is a known neurotoxin for over a century

(Zatta et al., 2002) and is known to contribute in the pathogenesis of many

neurodegenerative disorders, including amyotrophic lateral sclerosis (ALS),

Parkinson’s disease (PD), Alzheimer’s disease (AD), (Hu et al., 2007b) and senile

dementia of Alzheimer’s type (Gulya et al., 1990).

Al is abundantly present in earth crust but its biological functions are unknown

(Kaizer et al., 2008). Anthropogenic activities and soil erosion are major factors

causing release of Al into the environment (Ferreira et al., 2008). Food, drinking

water and certain drugs such as antacids are the sources through which humans are

exposed to Al (Hu et al., 2007b). Average human intake of Al is about 10 mg/day,

from fresh vegetables and fruits, and 95 mg/day from additives in commercially

processed food (Edwardson et al., 1992, Walton, 2007b). Under neutral pH, Al is

poorly soluble in water but at low pH the solubility increases considerably. Human

exposure to Al has increased due to acidification of environment, as a result of

industrial development and acid rain, which results in Al mobilization from

environment and increased solubility of Al in drinking water (Krewski et al., 2007)

which has raised concerns about its toxicity (Brus et al., 1997). Due to small size of

Al and its ability to be involved in transport and enzymatic functions of blood brain



Disease 2

barrier (Grammas and Caspers, 1991), Al is found to cross blood brain barrier within

a few minutes after its exposure and therefore accumulates in brain (Peng et al., 1992)

especially in hippocampus and cortex (Djebli and Rebai, 2010).

Many epidemiological studies and toxicological studies on laboratory animals reveal

that high Al exposure causes biochemical changes in brain which suggests that Al is a

powerful neurotoxicant (Flaten, 2001, McLachlan et al., 1991). Dietary Al intake

may aggravate underlying events associated with neurodegeneration (Stevanović et

al., 2010), which leads to development of neurodegenerative diseases like AD, ALS

and Guam Parkinson's dementia etc. (Hu et al., 2007a). Early evidence for

neurodegenerative role of Al came from discovery of elevated levels of Al in brain

tissue of PD patients, its focal accumulation in AD patient's brain tissue and other

neurodegenerative diseases (Hu et al., 2007b). Therefore Al is considered to be a

contributing factor in AD development (Campbell et al., 2004). Once in the brain, Al

will exert pressure to change the constancy of the brain interstitial fluid resulting in

altered permeability of blood brain barrier for different ions (Exley, 1999). As a result

Al may cause inflammation and oxidative stress in the brain (Walton, 2007a) and co-

localization of Al with neurofibrillary tangles and senile plaques in AD patients is

also observed (Miu and Benga, 2006). Therefore Al is suggested to be aggravating

factor in AD pathogenesis (Miu and Benga, 2006). There are many epidemiological

and analytical studies which demonstrate that chronic Al exposure may cause

cognitive impairment and neurological pathology similar to AD (Lin et al., 2015).

The exact mechanism of Al-induced neurodegeneration is not known but it is widely

known to have toxic effects on different components of cholinergic system (Gulya et

al., 1990). Cholinergic system deficits are a common feature between AD and Al-



Disease 3

induced neurotoxicity (Zatta et al., 2002). Cholinergic system consists of

neurotransmitter acetylcholine and cholinergic receptors. Acetylcholine (Ach) is a

very important neurotransmitter because of its wide distribution in the brain and its

crucial role in sleep-wake cycle, arousal, modulation of cognitive performance and in

memory and learning processes (Fabian-Fine et al., 2001, Schliebs and Arendt, 2006).

In the brain, Al may interfere with many biochemical functions including Ach

synthesis (Stevanović et al., 2010). Very limited data is available about the effect of

Al on Ach synthesis and its recycling therefore it needs to be investigated. Al-induced

toxic effects on Ach synthesis may be the underlying cause of learning and memory

deficits observed in human diseases for which Al is considered a contributing factor,

such as AD and dialysis encephalopathy.

Cholinergic receptors comprise of nicotinic acetylcholine receptors (nAChRs) and

muscarinic receptors. These receptors have an important role in learning, memory

and cognition (Johnson and Jope, 1986). The effects of Al on muscarinic

acetylcholine receptor gene expression are already studied (Grammas and Caspers,

1991, Harkany et al., 1995, Hashmi et al., 2015) but Al effects on nAChRs are not

well known. The neuronal nAChRs modulate many physiological functions including

attention, memory and learning (Hu et al., 2007b). These receptors are permeable to

different cations, especially the flow of Ca+2

ions is of particular importance, because

the Ca+2

entry in cell causes release of Ach. Ca+2

regulated Ach release is of vital

importance in the process of memory and cognition. nAChRs are pentameric ligand

gated ion channels formed by combination of eleven subunits (α2 to α9 and β2 to β4)

either in heteromeric or in homomeric conformation (Itier and Bertrand, 2001). The

α7 and α4β2 nAChRs are most abundant subtypes in mammalian and rodent brain

(Dani and Bertrand, 2007).



Disease 4

The Al exposure is known to impair the cellular events underlying learning and

memory i.e long term potentiation (Liang et al., 2012, Platt et al., 1995).

Hippocampal oscillations are other cellular events involved during memory formation

and in learning process. Specifically gamma frequency oscillations are involved in

memory and higher cognitive skills like object recognition (Lee et al., 2014) (Lee et

al., 2014) and spatial information (Lu et al., 2011, Montgomery and Buzsáki, 2007).

Gamma frequency (20-80 Hz) oscillations, arise from synchronous activity of neural

networks (Ward, 2003) and occur during exploratory behavior (Akkurt et al., 2009,

Siok et al., 2006), memory and learning processes in the hippocampus (Sederberg et

al., 2003). Gamma oscillations are observed in various cortical areas (Gray, 1994) and

are often altered in neurodegenerative diseases, such as AD (Goutagny and Krantic,

2013). Acute hippocampal slices are widely used to study basic mechanisms of

gamma oscillations (Fisahn et al., 1998, Song et al., 2005) and carbachol (CCh), a

cholinergic agonist, is commonly used to induce cholinergic hippocampal oscillatory

activity (Traub et al., 2000). Critical role of metabotropic muscarinic acetylcholine

receptors (mAChRs) in these oscillations is well characterized (Fisahn et al., 1998,

Guo and Chiappinelli, 1999, Kilb and Luhmann, 2003), but contribution of ionotropic

nAChRs to the gamma oscillation is less known (Cobb et al., 1999, Williams and

Kauer, 1997). Although it is reported that nAChRs activation facilitates learning and

memory and promotes hippocampal oscillations (Akkurt et al., 2009, Akkurt et al.,

2010, Lu and Henderson, 2010, Song et al., 2005). Moreover keeping in view the

known toxic effects of Al on cholinergic system (Gulya et al., 1990, Julka et al.,

1995, Kaizer et al., 2008), the aim of the present study was to determine the effects of

Al on cognition and memory, nAChR gene expression, cholinergic biomarkers,



Disease 5

neurodegeneration and nicotinic receptor mediated modulation of gamma

oscillations.

1.1 Aims and Objectives

The underlying mechanism involved in effects of Al on cholinergic system and its

implications on cognition, learning and memory was investigated in this study.

Keeping in view the importance of nAChRs in cognition and memory processes, and

the unexplored effects of Al on these receptors in AD, the present study had been

designed to determine the effects of Al on learning, memory, on nAChRs gene

expression and neurodegeneration. The specific objectives of the study were

To investigate the effects of Al administration on behavioral functions of

mouse model for AD.

To determine the effect of Al on cholinergic biomarkers and expression of α7

and α4β2 nAChRs in brain of AD mouse model.

Determination of neurodegeneration in brain after Al exposure.

To determine the effect of Al on brain rhythms.

Chapter 2 Review of Literature


Disease 6

Chapter 2

REVIEW OF

LITERATURE



Disease 7

REVIEW OF LITERATURE

2.1 Alzheimer’s disease

AD is a progressive neurodegenerative disorder that affects 10% of individuals

above 60 years of age (Stavljenic–Rukavina). The disease is categorized into different

types depending on (1) the age of disease onset and (2) the genetic factors of the

disease. Age is greatest risk factor for AD development as it is known that AD affects

about 47% of the individuals above 80 years of age. The disease which appears at the

age of below 65 is termed as early onset AD. This type has very low prevalence of

less than 10% of all the AD cases. While if the disease appears at the age above 65

then this is termed as late onset AD disease which is more prevalent, accounting for

about 90% reported cases of the disease. If the disease has an inheritance pattern then

this is termed as familial AD. This type of disease occurs at much earlier age i.e often

in 40s and is very rare (Pandey et al., 2011).

2.2 Pathophysiology of Alzheimer’s disease

During AD the brain atrophy begins from the area of entorhinal cortex and then

spreads to hippocampus and cerebrum (Palmer, 2002, Rogers and Simon, 1999). AD

is clinically characterized by effecting temporal lobe, hippocampus and parietal

association cortices. While the frontal lobe is effected at advanced stages of the

disease (St George-Hyslop and Petit, 2005). The cerebral cortex and hippocampus are

the main areas for cognition and memory. Due to the disease progression these two

regions of the brain are greatly affected and undergo deterioration (Djebli and Rebai,

2010) that is why memory impairment is the first noticed symptom of the disease. The

neurodegeneration is the result of two pathological events, formation of amyloid



Disease 8

plaques and neurofibrillary tangles due to hyperphosphorylation of tau protein. In

addition, the loss of cholinergic system is also the reason for loss of cognition and

memory in patients of AD.

2.2.1 Amyloid plaques

Amyloid plaques are intra neuronal accumulations of protein named Aβ42 (Jones et

al., 2006b). Plaques are insoluble and dense accumulates of beta amyloid peptide and

are formed by different enzymatic breakdown of a protein named Amyloid Precursor

Protein (APP) (Stavljenic–Rukavina). APP is a transmembrane protein of 770 amino

acids, (St George-Hyslop and Petit, 2005) containing a stretch of 23 hydrophobic

amino acids that help to anchor it in the lipid bilayer of different membranes (Pastor

and Goate, 2004). The α and γ secretases normally cleave APP but, in certain

conditions the cleavage occurs by β and γ secretases. The APP fragment resulting

from cleavage by α and γ is nonpathogenic. The cleavage by α secretase cuts the APP

from within the Aβ fragment causing release of soluble N- terminal fragments leaving

behind C-terminal fragment of 10 kDa embedded in the membrane. The cleavage of

this 10 kDa fragment by γ secretase results in a 3 kDa fragment named as p3 and a 6

kDa fragment termed as p7. In case of cleavage by β secretase the C-terminal

fragment left is quite longer and of 12 kDa. The cleavage of this 12 kDa fragment by

γ secretase results in the production of Aβ peptide (Wolfe et al., 1999, Yokeş, 2007).

The site of cleavage for γ secretase is residue 712 of C terminal fragment. If the

cleavage takes place between the 712-713 residues then short fragment termed as

Aβ40 is produced while if the cleavage is after residue 714 then longer forms of

amyloid peptide are generated termed as Aβ42 (Hutton and Hardy, 1997). The 42

amino acid long amyloid peptide is highly hydrophobic and therefore aggregate



Disease 9

together in the form of amyloid plaques and therefore is thought to be more

amyloidogenic and neurotoxic as compared to 40 amino acid long amyloid peptide

fragment (Spillane et al., 1979, Stavljenic–Rukavina). Overproduction or abnormal

clearance of Aβ results in the plaques accumulation (Sun et al., 2009). The amyloid

plaques accumulate at interneuronal spaces and as a result the contact between the

neurons is disrupted and this results in death of neurons (Stavljenic–Rukavina).

Different mechanisms are proposed to explain Aβ-induced neurotoxicity including

free radical induction, disturbance in Ca+2

homeostasis and induction of apoptosis

through oxidative stress (Jones et al., 2006b, St George-Hyslop and Petit, 2005). This

mechanism has resulted in the formulation of amyloid hypothesis which states that

―that an imbalance in production or clearance of amyloid β (Aβ) results in

accumulation of Aβ and triggers a cascade of events leading to neurodegeneration and

dementia‖ (Christensen, 2007).

2.2.2 Neurofibrillary tangles

Amyloid plaques can lead to two processes, inflammation and tau

hyperphosphorylation, which eventually results in neuronal death. Tau protein can

help to maintain the microtubule integrity. The microtubules are involved in transport

of nutrients and other cell regulation components across the long neuronal exons

(Stavljenic–Rukavina). Amyloid plaques formation activates certain kinases that

hyperphosphorylate tau protein (Nathalie and Jean-Noel, 2008). The

hyperphosphorylation of tau protein causes it to lose its affinity for the microtubules

and start binding to each other resulting in the formation of neurofibrillary tangles

(Pandey et al., 2011, Rogers and Simon, 1999). The neurofibrillary tangle formation

causes the breakdown of microtubules which leads to the destruction of cellular



Disease 10

architecture and eventually the cell dies (Christensen, 2007, Pandey et al., 2011).

2.3 Factors responsible for Alzheimer’s disease

AD is a multifactorial disease and many factors (genetic and environmental) lead to

the disease development. Among genetic factors mutations in four loci contribute

most to the development of the disease (Hutton and Hardy, 1997). The loci on

chromosome 14 (Presenilin 1), chromosome 1 (Presenilin 2) and chromosome 21

(Amyloid precursor protein) (Kamimura et al., 1998) are associated with the early

onset and familial AD. Whereas the fourth loci Apolipoprotein E (ApoE) on

chromosome 19 is associated with the development of late onset AD (Rihn et al.,

2009). Age is the most effective and common risk factor for the disease advancement.

In addition previous head injury, low educational background and depression are

other risk factors for the disease (Yokeş, 2007). Among environmental factors

exposure to different metals, especially Al, is supposed to be an important

contributing factor towards the AD development.

2.4 Aluminum and Alzheimer's disease

The role of Al in AD is implicated by four independent lines of evidence, viz (a)

epidemiological studies (Rondeau, 2002, Rondeau et al., 2000) (b) toxicology studies

and experiments on learning and memory in animals administered with Al

(Hashimoto et al., 2002, Ribes et al., 2008) (c) biochemical changes caused by Al

similar to the changes reported in AD patients brain (Exley, 1999) and (d) slowing of

AD progression as a result of Al sequestering drugs (McLachlan et al., 1991).

Since 1989, more than 12 epidemiological studies have assessed the coalition of Al

and drinking water in AD development (Krewski et al., 2007). The ratio of dementia



Disease 11

was significantly high in individuals living in areas where Al concentration was high

in drinking water (Yokel et al., 2008). An analysis of previously published

epidemiological studies revealed that 9 out of 13 epidemiological studies have

reported a positive relation between AD and Al in drinking water (Flaten, 2001).

Another analysis of previously published data has reported that a relation between AD

and Al was established in 68% studies while 8.5% studies described that there was no

relation between Al and AD (Ferreira et al., 2008). A follow up study of 1,925

individuals aged 65 years or more, for a period of 15 years showed that individuals

having high daily intake of Al from drinking water had greater cognitive decline with

time therefore it was concluded that high daily Al intake is significantly correlated

with dementia development (Rondeau et al., 2009).

2.5 Aluminum in environment

Al is third most abundant metal in the earth crust (Jalbani et al., 2007) is released into

the environment by volcanic eruption, soil erosion and anthropogenic activities

(Ferreira et al., 2008). Al is used in many industries e.g. in electric industry,

automotive industry and construction industries. In addition Al is also used in the

production of different metal alloys, cooking utensils and food packaging (WHO,

2004). The industrial revolution has resulted in a great increase in availability and

distribution of this metal to biological systems (Kaizer et al., 2008).

2.6 Sources of aluminum exposure to human

Human exposure to Al occurs via different sources. Al compounds are added in

antiperspirants, antacids and as adjuvant in vaccines (WHO, 2004). The Al injected in

vaccines and during allergy immunotherapy provides complete absorption of Al in

body (Yokel and McNamara, 2001). Further exposure to Al may occur from other



Disease 12

sources for example occupational exposure (Elinder et al., 1991), exposure to dialysis

fluids containing high Al content (Alfrey et al., 1976) and illicit drug abuse (Yokel et

al., 2008).

Human exposure to Al is mainly via oral ingestion of a range of commercially

prepared foods containing Al additives (Walton, 2007b). Most of Al in average diet

comes from Al utensils used in cooking, preparing and eating foods (Brus et al.,

1997). Leaching of Al in food from Al food wraps was observed to be higher in acidic

solutions and further increased with addition of spices (Bassioni et al., 2012).

Moreover cooking foods in Al foil at high temperature, for longer time duration also

considerably increases Al content in food as a result of leaching from Al foil (Turhan,

2006). Al salts are used as conservant to many commercially prepared foods, to color

snacks and it is added in desserts and in order to make salt free pourings (Walton,

2007b). Almost 180 mg/serving of Al is found to be present in the ready to eat

pancakes (Saiyed and Yokel, 2005). Moreover cooking foods in Al utensils, cookware

and wrappings also increases the amount of Al in food (WHO, 2004). Some foods, for

example spinach, potato and tea are naturally high in Al. The infant formula, flour and

processed dairy products might be rich in Al content if they contain Al based food

additives (Pennington and Schoen, 1995).

Another major source of human exposure to Al may is drinking water (Walton,

2007b). Although food is an important contributor of Al exposure to humans

however, Al is more bio-available in drinking water (Ferreira et al., 2008). As Al in

food is complexed with other elements forming phytates and polyphenols which

greatly reduce its absorption but Al can be readily absorbed from drinking water in

gastrointestinal tract as it is present in un-complexed form in water (Yokel et al.,



Disease 13

2008). Al is minimally soluble at neutral pH of 5.5-6 but with increase or decrease in

pH the solubility of Al in water increases considerably (Brus et al., 1997). Decreased

pH, due to acid rain and release of industrial wastes in water reservoirs, results in Al

mobilization from environment and increased solubility of Al in drinking water,

causing a further rise in human exposure to this metal (Krewski et al., 2007). Al salts

are added for water purification and is used as coagulant to reduce organic matter,

microorganisms and turbidness. This treatment is although useful but may greatly

increase Al concentration in the water reaching to consumers (Ferreira et al., 2008).

This high residual concentration may cause Al to deposit in distribution system which

on disturbance may cause an increase in Al concentration in tap water (WHO, 2004).

2.7 Aluminum via drinking water in Pakistan

In Pakistan drinking water is mostly taken from rivers and canals or from

underground aquifers (Aziz, 2005). But with increasing urbanization, population

growth and industrial development the water resources are becoming more and more

polluted (Kahlown et al., 2005). As all industrial units use a large quantity of water

which after mixing with toxic substances is released in nearby water resources, i.e.

lakes, rivers or in agricultural land (Ullah et al., 2009). This water along with

dissolved toxic substances percolate down in soil resulting in contamination of

aquifers (Ullah et al., 2009). Moreover release of industrial effluents, farm and urban

sewage and municipal wastes in rivers further worsen and increase the water pollution

(Tariq et al., 2006). Because of this unchecked release of industrial wastes in water

resources, the drinking water quality in major cities of Pakistan is rapidly

deteriorating (Bhutta et al., 2005).

There are only a few reports that assess the drinking water quality from rural areas of



Disease 14

Rawalpindi (Tahir et al., 1998), Sialkot (Ullah et al., 2009), Hayatabad Industrial

State, Peshawar (Tariq et al., 2006), Southern Sindh (Memon et al., 2011), Punjab

(Aziz, 2001) and Kohat (Khan et al., 2012). These studies have mostly assessed the

physical parameters (pH, electrical conductivity, chemical oxygen demand, total

dissolved and suspended solids), biological parameters (biological oxygen demand

and fecal coliform) and presence of heavy metals (Cd, Zn, Cr, Pb, Mn, Ni, Cu, Fe) in

drinking water. Very little attention has been given to determining Al content in the

drinking water in Pakistan. There are only two reports that have assessed the Al

concentration in drinking water (Sehar et al., 2013, Tareen et al., 2014). Assessment

of drinking water from tube wells, in District Pishin, Baluchistan, has shown that the

quantities of Antimony and Al were higher than standard recommended values

(Tareen et al., 2014). Moreover the Al quantity was higher in low depth wells as

compared to wells with greater depths, which makes water unfit for public use

(Tareen et al., 2014). An evaluation of drinking water from water bores in Qasim

Abad area of Rawalpindi, where main drinking water source is from water bores, has

shown that water concentration of Al was 0.95 and 1.92 ppm. These values are

alarmingly high as the recommended value of 0.2 ppm of Al is permissible for

drinking water by Environmental Protection Agency (EPA) (Sehar et al., 2013). Oral

ingestion of Al in diet and drinking water is correlated with the risk of developing AD

and individuals who intake food having high Al content represent two times rise in

risk of AD development (Rogers and Simon, 1999). In a study in 1965 intracerebral

inoculation of Al in rabbit brain resulted in neurofibrilar degeneration akin to AD, an

article published in 1973 indicated that Al concentration is high in brain of patients

suffering from AD (Ferreira et al., 2008).



Disease 15

2.8 Aluminum induced Alzheimer’s model

Due to the involvement of Al in development of AD pathogenesis this metal is used to

develop AD animal models (Balgoon et al., 2015, Bitra et al., 2014, Chen et al., 2013,

He et al., 2012, Lakshmi et al., 2015). Several neurophysiological processes are

affected by Al (Fig 2.1) which are responsible for degenerative changes that are

characteristic of AD (Ferreira et al., 2008). It is proposed that Al causes an

overproduction of Aβ1-42 (Luo et al., 2009). It is aslo reported that high Al

concentration is related with the greater amyloid plaques accumulation (Exley and

Esiri, 2006) and neurofibrillary tangles (Walton, 2006) in brains of AD patients.

Similarly in experiments on rodents has shown that Al causes a rise in number and

size of amyloid plaques in cortical tissues (Praticò et al., 2002). Moreover Al is also

found to increase neurotoxicity of amyloid plaques causing a greater neuron

degeneration exposed to it (Kawahara et al., 2001) as Al may play crucial role in

cross linking of Aβ oligomers (Kawahara and Kato-Negishi, 2011).

The precise tissue localization via different analytical techniques has shown that high

concentration of Al is observed in neurofibrillary tangles in AD patient brains (Per

and Pendlebury, 1984, Perl and Brody, 1980). Moreover Al is reported to induce

abnormal phosphorylation of Tau (Guy et al., 1991) which support the idea that Al

accumulation occurs during the initial stages of AD development (McLachlan et al.,

1991).

Al induced oxidative stress (OS) is also considered a contributing factor for the

degeneration observed in AD. High OS is observed in brains exposed to Al and this

OS makes neurons more susceptible to excitotoxic lesions (Ferreira et al., 2008). In

addition a very small amount of AL can cause an imbalance in the brain iron



Disease 16

Fig 2.1: Major biological effects of Al on nervous system



Disease 17

homeostasis which ultimately causes neurodegeneration (Kaizer et al., 2005).

2.9 Role of cholinergic system in Alzheimer's disease pathogenesis

Cholinergic system is one of the most astringently affected systems during AD

(Burghaus et al., 2000). The pathology is caused by a decrease in activity of ChAT,

Acetyl cholinesterase (AChE) and loss of neurons carrying cholinergic receptors

(Hetnarski et al., 1980). The cholinergic receptors include muscarinic and nAChRs.

The nAChRs are very important in AD pathology which is manifested by the change

in function of nAChRs (Hernandez and Dineley, 2012).

2.10 Nicotinic acetylcholine receptors

The nAChRs are ligand gated ion channels and are expressed all over the brain (Fig

2.2). These receptors are pentameric, and five subunits are arranged in heteromeric or

homomeric conformation (Dani and Bertrand, 2007). There are eight α subunits (α2-

α9) and three β subunits (β2-β4) (Dani, 2001). The α2-α6 subunits are form

heteromeric receptors formed by coalescence of α and β subunits. Whereas α7-α9

subunits make homomeric receptors (Dani and Bertrand, 2007). This high number of

subunits can result in hundreds of different receptor combinations but only a few

stichiometries are physiologically favored. Among these combinations (α7)5,

(α4)3(β2)2 and (α4)2(β2)3 are most abundantly expressed in brain (Pohanka, 2012).

The β subunits alone cannot form functional receptor whereas α2-α6 alone can form

receptors with very weak affinity for ligand (Tohgi et al., 1998a). The agonist is

recognized and is bound to α subunits whereas β subunits help to stabilize the

receptor and to increase ligand binding affinity (Tohgi et al., 1998a).



Disease 18

Fig 2.2: Expression of nAChRs in brain. Hippo: hippocampus, LC: locus coeruleus, SN: substantia

nigra, VTA: ventral tegmental Area. Image modified from (Ahmed et al., 2016)



Disease 19

2.10.1 Structure of nicotinic acetylcholine receptors

Each nAChR subunit comprises of two extracellular hydrophilic N- and C- terminal

segments, four transmembrane domains (M1-M4) and an intracellular loop between

M3 and M4 domains (Lucas-Meunier et al., 2003). This intracellular loop is reported

to have putative phosphorylation sites (Lucas-Meunier et al., 2003). The domain M2

makes the central pore after alignment along the centre (Dani and Bertrand, 2007).

The receptor opens for penetration of cations (Ca+2

, Na+, K

+) only after binding of at

least two ligand molecules (Lucas-Meunier et al., 2003) (Fig 2.3).

2.10.2 Involvement in Alzheimer’s disease

Literature studies have shown that there is a contradiction about the α4β2 and α7

nAChR subtype expression, during AD, in different brain areas. Some report an

upregulation of nAChRs expression (Counts et al., 2007, Jones et al., 2006a, Liu et

al., 2012a), while others reported its downregulation during AD progression

(Banerjee et al., 2000, Lee et al., 2002, Pandya and Yakel, 2011, Tohgi et al., 1998b).

The mRNA expression of α4β2 and α7 receptors remains unaltered in cortex of

control and AD patients whereas a 30% reduction in protein expression of α4β2 and

α7 receptor subtypes was reported. The difference seen in expression of α4β2 and α7

receptors at mRNA and protein level might be because of deficits in post translational

modifications during synthesis of nAChR (Wevers et al., 1999). However, the definite

mechanism is unknown and requires further investigation. Examination of autopsy

samples of AD patient's cerebral cortex showed similar results (Burghaus et al., 2000)

where a 17% decrease in α7 and 40% reduction in α4 receptor expression



Disease 20

Fig 2.3: Structure of neuronal nicotinic acetylcholine receptors (nAChRs). (a) Pentameric assembly of

nAChRs (b) Membrane topology of single nAChR subunit. Each nAChR subunit contains four

transmembrane domains (M1-M4), an extracellular amino- and carboxy-terminus, and a prominent

M3-M4 intracellular loop (c) Homomeric nAChRs consist of only one type of subunits (α7)5 while

heteromeric nAChRs are formed by combination of α and β subunits(α4)2(β2)3 or (α4)3(β2)2. Small

blue circles represent ACh binding sites (d) Three dimensional structure of nAChRs.



Disease 21

was observed. A deficiency in ACh binding sites is caused by reduced expression of

nAChRs which results in cognitive deficit in AD (Burghaus et al., 2000). Contrary to

these observations, Hellstrom-Lindahl et al., 1999 reported upregulation of α7 mRNA

in brain of AD patients while no change in α4 receptor expression was found

(Hellstrom-Lindahl et al., 1999). nAChR expression was also increased in animal

models (Bednar et al., 2002, Dineley et al., 2001). This difference might be due to the

reason that, in animal model, nAChRs are reported to have biphasic expression which

is age dependent. As it is observed that at 9 months of age the expression of nAChR

increases 3-4 folds and then decreases at 12 months of age (Jones et al., 2006a).

In basal forebrain cholinergic system development the Aβ aggregates are co-localized

with α7 receptors during initial stages of AD (Parri et al., 2011). This early co-

localization may be because these two components have high affinity towards each

other (Jones et al., 2006b, Wang et al., 2000a). The Aβ1-42 and α7 nAChRs are also

found to co-precipitate during receptor binding experiments (Wang et al., 2000b). As

detergent fails to disintegrate these co-precipitates therefore it is inferred that Aβ1-42

and α7 nAChRs are strongly bound to each other (Jones et al., 2006b). A 5000 times

lesser affinity is observed between Aβ1-42 and heteromeric nAChRs as compared to

α7 receptors. In rat CA1 stratum radiatum interneurons the whole cell and single

channel currents are blocked due to binding of Aβ1-42 to nAChRs in hippocampal

slices (Pettit et al., 2001).

It is evident that nAChR are desensitized due to presence of high (nM) concentrations

of Aβ1-42. This desensitization can result in disruption of cognitive functions and

synaptic plasticity (Cleary et al., 2004). However nAChRs are activated by low (pM)

concentrations of Aβ1-42. Therefore at low concentration Aβ1-42 has an important



Disease 22

role in neuromodulation thus enhancing cognitive functions (Puzzo et al., 2008).

Activation of nAChRs with short exposure of low levels of Aβ initiates different

neuro-modulatory pathways but extended exposure at higher concentration of Aβ

causes dysregulation of these pathways. This dysregulation might possibly be

resulting from receptor desensitization which leads to cell death resulting in impaired

memory and learning (Dineley, 2006).

The long term depression (LTD) and long term potentiation (LTP), the two types of

synaptic plasticity,are also modulated by α7 nAChRs. Gu and Yakel has reported that

plasticity in schaffer collateral (SC) to CA1 projections is dependent on α7 receptors.

When septal cholinergic input is activated for 10ms or 100ms prior to stimulation of

SC resulting in LTD or LTP induction. The MLA (α7 receptor antagonist) resulted in

blockade of this synaptic plasticity but DHβE (non-α7 receptor antagonist) had no

effect. Moreover high concentrations of Aβ (10nM or 100nM) caused disruption of

this synaptic plasticity. These results propose that synaptic plasticity is negatively

affected when α7 receptors are inactivated due to presence of high concentration of

Aβ (Gu and Yakel, 2011) which results in memory and learning impairment.

The presence of α7 nAChRs on glial cells, especially astrocytes, suggests their

importance in inflammation process. Nagele et al. observed co-localization of α7

nAChRs, ChAT, and Aβ with green fluorescence activated protein (GFAP) positive

(activated) astrocytes in AD brains. Therefore, it is proposed that activated astrocytes

phagocytise α7 and Aβ. As a result neuronal debris accumulate in astrocytes which

compromise their viability. As a result the astrocytes are lysed which leads to amyloid

plaque formation derived from astrocyte (Nagele et al., 2003). Astrocyte apoptosis is

also induced by Aβ-dependant activation of caspase 3 (Wang et al., 2012). The



Disease 23

activated caspase 3 cause more astrocytes to undergo apoptosis as compared to

neuronal cells (Smale et al., 1995). Thus astrocytes apoptosis may also be a

contributing factor in AD pathogenesis (Liu et al., 2012b).

2.11 Toxic effects of aluminum on cholinergic system

Cholinergic system is critically involved in processes of learning and memory and

areas with cholinergic synapses are known to be greatly enriched with Al

accumulation (Kaizer et al., 2008). It is already known that Al is cholinotoxic and

affects the brain by interacting with cholinergic cells in the brain (Kaizer et al., 2005,

Kumar, 1998). The interaction of Al in the brain with cholinergic cells causes

degeneration and suppression of cholinergic system leading towards the cognitive

deficit (Gulya et al., 1990). The neurotransmitter Ach plays important role in the

cholinergic function of the central nervous system (Maheswari et al., 2014). Al is

known to affect cholinergic neurotransmission at all levels of Ach synthesis, binding

and degradation. Ach is an important player in learning and memory in mammalian

brain and is involved in various cognitive functions (Fabian-Fine et al., 2001). After

Al administration the level of Ach is known to be reduced (Julka et al., 1995). The

reduction in Ach concentration is due to the reduced activity of ChAT enzyme which

is involved in synthesis of Ach (Gulya et al., 1990, Julka et al., 1995). Moreover Al

suppresses the metabolism of acetyl Co-A which is a precursor of Ach synthesis

(Stevanović et al., 2010). The recycling of choline from synapses back into the

neurons is also suppressed because Al is known to inhibit action of (Na+/K

+)ATPase

(Silva et al., 2007) which causes a decrease in velocity of choline uptake that leads to

interference with the high affinity choline uptake (HACU) (Johnson and Jope, 1986,

Julka et al., 1995). As the choline uptake acts as the rate limiting factor in Ach



Disease 24

synthesis (Johnson and Jope, 1986) therefore impaired choline uptake will greatly

reduce the Ach synthesis which will result in cholinergic hypoactivity. Al also inhibits

hexokinase enzyme which is rate limiting factor in glucose utilization (Johnson and

Jope, 1986, Julka et al., 1995). The Ach synthesis is greatly sensitive to even slight

reductions in glucose utilization therefore inhibition of hexokinase will greatly reduce

synthesis of this neurotransmitter (Johnson and Jope, 1986). Al is not only impairs

activity of choline acetyl transferase and HACU but also affects the function of

acetylcholinesterase enzyme (Julka et al., 1995) which is involved in the hydrolysis of

Ach (Maheswari et al., 2014). As Al accumulates slowly in the brain therefore it has a

biphasic effect on the activity of AChE enzyme, i.e shorter exposure results in

increase in the activity of the enzyme while longer exposure results in reduction of its

activity (Kumar, 1998). Therefore fewer studies have reported its increased activity

(Brus et al., 1997) while most of studies reported a reduction in its activity (Dave et

al., 2002, Gulya et al., 1990, Kaizer et al., 2008, Stevanović et al., 2010, Yellamma et

al., 2010). The reduction in the activity of AChE enzyme is suggested due to the

ability of Al to bind with the thiol (-SH) group of the receptor which will interfere

with the functioning of the receptor in certain chemical reactions (Yellamma et al.,

2010). Al not only affects the Ach synthesis at biosynthetic and hydrolytic level but

also interferes with the binding of Ach with the cholinergic receptors. Al reduces the

number of binding sites (Bmax) of muscarinic receptors (Harkany et al., 1995, Julka et

al., 1995) and causes a reduction in the nicotine binding (Gulya et al., 1990) which

will result in the reduction of the transmission of nerve impulse which leads to deficits

in learning and cognitive functions. The literature substantiate the fact that Al affects

various steps in metabolic pathway of cholinergic system causing inhibition of end

product.



Disease 25

Al produces its toxic effects by disruption of cholinergic neurotransmission and

mimics the deficits in cholinergic neurotransmission seen in AD (Stevanović et al.,

2010) as, among other factors, marked modification of cholinergic system is also a

characteristic of AD (Zatta et al., 2002). Although the effect of Al on cholinergic

system is reported previously but its effects specifically on nicotinic receptors are not

yet evaluated. Keeping in view the vital importance of the cholinergic system in

memory and cognitive functions, the present study was designed to evaluate its

sensitivity to the disruption in the brain of Al induced AD mouse model.


Disease 26

CHAPTER 3

MATERIALS AND

METHODS

Chapter 3 Materials & Methods


Disease 27

MATERIALS AND METHODS

3.1 Chemicals:

Hexahydrate form of Aluminum chloride (AlCl3.6H2O) with product code AL0770

was obtained from Scharlau (Spain). It was a colorless, crystalline compound with

241.43g/mol molecular weight. The compound was almost pure with less than

0.005% heavy metals impurities. The AlCl3.6H2O was stored in air tight container to

avoid moisture exposure. Cresyl violet stain (229630250) and Paraformaldehyde

(PA0095100) were also purchased from Scharlau, while sodium chloride (SO0225),

ethanol (100983), sodium phosphate monobasic (567549), sodium phosphate dibasic

(567550) and xylene (108684) were obtained from Merck USA. Chemical solutions

were prepared fresh prior to experiment. Taq Polymerase, 10mM dNTPs and RT

enzyme were purchased from Fermentas, USA. Tri reagent was purchased from

Invitrogen, USA. For in vitro electrophysiology experiments Carbamylcholine

chloride (carbachol), dihydro-β-erythroidine (DHβE) and methyllycaconitine (MLA)

were obtained from Tocris Bioscience, USA. (-) Nicotine was purchased from Sigma

Aldrich, UK. For detection of free choline and Ach levels in brain the

choline/acetylcholine assay kit (ab65345) was purchased from Abcam.

3.2 Animals

The experiments involving use of lab animals were performed according to the

rulings of the Institute of Laboratory Animal Research, Division on Earth And Life

Sciences, National Institute of Health, USA (Guide for the Care and Use of

Laboratory Animals: Eighth Edition, 2011). Approval from Internal Review Board

Chapter 3 Materials &Methods


Disease 28

(IRB), Atta-urRahman School of Applied Biosciences (ASAB), National University

of Sciences and Technology (NUST) was also obtained. A total of 60, 3-6 months old

male BALB/c mice ( 30-45 gms) were onbtained from National Institute of Health

(NIH), Islamabad and were kept in the animal house of ASAB, NUST. Each mouse

was given a unique identity. The environmental conditions were kept controlled with

temperature maintained at 25 ± 2oC and 14 hours light and 10 hours dark light cycle

was followed in animal house. Animals were fed ad libitum diet consisting of 30%

crude protein, 4% crude fiber, 9% crude fat, and 10% moisture. One cage of 40 x 20.5

x 20.5 cm contained not more than three mice and all animals had equal access to

water and food.

3.3 Study design

In order to determine the effect of Al on cholinergic system and nicotinic

acetylcholine receptors in-vivo (Fig 3.1a) and in-vitro experiments (Fig 3.1b) were

performed. For In-vivo experiments animals were divided into two groups i.e. the

control group and AD mouse model. Animals were administered with AlCl3.6H2O for

a period of 42 days in order to develop AD model while control group was given

distilled water for the same time duration. Behavior tests were performed after

completion of treatment (Fig 3.2). Animals were dissected after behavior tests and

were either perfused for hitological examination or brain tissue was collected for

expression, Al and Ach concentration determination. The in-vitro experiments

involved field potential recordings from acute hippocampal slices to study effect of Al

on nAChR modulation of gamma oscillations.



Disease 29

Fig 3.1: Experimental study design.



Disease 30

Fig 3.2: Diagrammatic presentation of the study timeline used for AlCl3 treatment in mice for in-vivo

experiments



Disease 31

3.4 In-vivo experiments

3.4.1 AlCl3 administration

Animals were given 250 mg/kg body weight/day AlCl3 via drinking water for 42 days

and the respective controls were given distilled water for the same time duration.

3.4.2 Behavior tests

Morris water maze test was performed from 37th

to 41st day of oral treatment, while

rest of the behavior tests were performed on 42nd

and 43rd

day. Behavior tests were

performed between 10:00 am to 5:00 pm. Mice were shifted 15 minutes prior to the

start of behavior test to the behavior testing room in order to let it familiarize to the

conditions of behavior testing room. The testing room was well illuminated with

temperature maintained at a constant of 25 ± 2oC. The behavior tests were performed

in the absence of experimenter and all the tests were recorded by a video camera

which were analyzed later on.

3.4.2.1 Morris water maze test

The Morris water maze test is performed to determine the spatial learning and

memory of the animal. The test procedure was performed as described previously

(Bromley-Brits et al., 2011) with some modifications. The apparatus consisted of

round steel pool with 120 cm diameter and depth of 60 cm. The pool was

hypothetically divided into four quadrants, North (N), West (W), East (E) and South

(S) (Fig 3.1). A transparent platform of 13 cm diameter and 32 cm height was placed,

in the south-west quadrant, for the animals to escape swimming in water. Spatial cues

were placed on walls of the pool for the animals to navigate from the release location



Disease 32

around the pool’s perimeter to find a hidden platform. The pool was filled with

opaque water until water was 2 cm above the platform making the platform

completely submerged and invisible to the animal.

The trial started on the 37th

day. Total 5 trials were performed each day for 5 days.

The platform was placed at same position each day, i.e. south-west (SW), for 5 days

but the mouse release position was altered for each trial (Table 3.1). The release

position was kept the same as described by (Bromley-Brits et al., 2011). The mouse

was allowed to explore for the platform for 60 seconds in each trial and an inter-trial

interval of 10 minutes was given. If the mouse found the platform before cut-off time

(60 seconds), it was allowed to stay on the platform for 5 seconds, and then returned

to its home cage after drying. However, if the mouse did not find the platform in 60

seconds, it was placed on the platform by experimenter and allowed to stay there for

20 seconds before returning to its home cage. The average time taken by mouse to

reach platform was recorded and average of five trials was taken as the escape latency

of the animal for that particular day.

On 42nd

day of treatment probe trial was performed in which the platform was

removed and the release position of the animal was kept same i.e. West (W).

Reference memory of the mouse was checked by calculating the time spent by animal

in the quadrant in which the platform was previously placed. The number of crossings

over the previous platform position was also determined.



Disease 33

Table 3.1: The direction of animal release during Morris water maze test.

Days

Direction of Release

Trial 1 Trial 2 Trial 3 Trial 4 Trial 5

1st West (W) South (S) North (N) East (E) South (S)

2nd

North (N) West (W) East (E) West (W) South (S)

3rd

North (N) East (E) West (W) South (S) North (N)

4th

East (E) South (S) West (W) East (E) North (N)

5th

West (W) South (S) North (N) East (E) South (S)

6th

SINGLE TRIAL WITHOUT PLATFORM.

RELEASE DIRECTION, WEST*

*On 6th

day, Probe trial was performed without the platform and the time spent on previously learned

platform quadrant was noted (Bromley-Brits et al., 2011).

Fig 3.3: Morris Water Maze (MWM) Apparatus. Pool filled with opaque (blue) water and divided into

four quadrants. Distal cues are placed on the pool wall and a hidden platform is located in the North-

West quadrant.

Hidden

Platform



Disease 34

3.4.2.2 Elevated plus maze test

The test is used to check the anxiety in animals. The principal of this model is to

analyze aversion of rodents to open spaces. As result of aversion, thigmotaxis

behavior was observed, in which rodents confine their movement to closed ends and

avoid open areas.

The testing procedure was performed as described previously (Arendash et al., 2004)

with few modifications. Briefly, a plus shaped maze was used (Fig 3.3) which

consisted of four arms and is elevated 75.5cm above ground. Among the four arms of

maze, two arms were without walls referred to as open arms (50.5cm x 10cm), while

perpendicular to these open arms were two arms surrounded by opaque walls (49.5cm

x 10cm) referred to as close arms. The walls of closed arms were 49.5cm high. The

four arms were connected to central platform (10cm x 10cm). The apparatus was built

from opaque iron alloy.

In this test each mouse was placed in center platform facing the closed arm and

allowed to explore the maze for 5 minutes. The Animal was considered into an arm if

two of its paws and more than half of body were in the respective arm. Camera

recorded video was later analyzed for following parameters.

1) Time spent in closed and open arms.

2) Number of entries into the open arm.

After each trial the apparatus was cleaned with 70% ethanol to avoid biased result due

to olfactory cues.



Disease 35

Fig 3.4: The elevated plus maze test apparatus.

Open arm

Closed arm



Disease 36

3.4.2.3 Open field test

This test is useful to check exploratory behavior, locomotor activity and anxiety. The

test was performed according to the previously described procedure (Arendash et al.,

2004) with few modifications. Square opaque iron box (40cm x 40cm x 40cm) was

used for the test (Fig 3.4). The box was virtually divided into peripheral and central

areas. The box was placed in a well lit area. Each mouse was placed in the center of

arena for a period of 30 minutes. The animal behavior during test was recorded in a

camera and was analyzed later for following parameters.

1) Time spent in peripheral and central region.

2) Number of rearing. Rearing is used to measure exploratory behavior. It is a

posture when animal stands on its hind limbs in a vertical position.

3) Time spent in self grooming. In present study the grooming behavior was

assessed according to the criteria described by (Smolinsky et al., 2009) i.e. in

grooming in mouse follows cephalocaudal direction and anxiety causes

disturbance in this grooming pattern. Based on this criterion the anxious and

relaxed grooming was measured.

The test was conducted for a period of 30 minutes and these parameters were

measured in control and AD mouse model. In addition the behavior shown by animal

during initial five minutes of the test duration were compared to their behavior in last

five minutes of the test to determine how adaptation to a new environment is affected

by Al administration. The box was cleaned with 70% ethanol after completion of the

test.



Disease 37

Fig 3.5: The open field test apparatus



Disease 38

3.4.2.4 Social novelty preference test

The test was conducted as described previously (Hashmi et al., 2015). The test was

carried out in a square box made up of iron (40cm x 40cm x 40cm). Two small cages

(13cm x 11cm x 16cm), made up of iron gauze, were placed in the iron box in such a

way that both were diagonal to each other at a distance of 5cm from walls of the

square box. The animal was placed in the center of test box. In this way all the sides

of small cages were accessible to test animal. The test consisted of two sessions, each

session of 10 minutes duration and inter session interval was kept 20 minutes.

In the first session, which is known as ―social interaction session‖, one cage was

empty while the other cage had an unfamiliar mouse of same strain, age and weight

(Fig 3.5a). This unfamiliar mouse was named as ―stranger 1‖. The time spent by the

test mouse with stranger 1 and with empty cage was recorded separately. In the

second session called ―social novelty preference session‖ a second mouse, ―stranger

2‖, was introduced into the empty cage while the ―stranger 1 remained in the same

cage (Fig 3.5b). The interaction time of test animal with ―stranger 1‖ and ―stranger 2‖

was recorded manually. When the test animal touched the cage or physically

contacted with ―stranger 1 or stranger 2‖ it was considered as interaction. The social

activity box was cleaned properly with 70% ethanol after each session.



Disease 39

Fig 3.6: Social novelty preference test setup. (a) Social interaction session. (b) Social novelty

preference session.

a

b



Disease 40

3.4.2.5 Novel object recognition

The test was performed according to procedure as described previously (Hashmi et

al., 2015) with few modifications. The test was carried out in an iron box (40cm x

40cm x 40cm) (Fig 3.6). Initially the animal was given an acclimatization time of 5

minutes to become familiar with a new arena. The test consisted of two sessions i.e.

―familiarization session‖ and ―test session‖. Each session consisted of 10 minutes and

inter session duration was 20 minutes. In the ―familiarization session‖ two objects

were placed in two diagonally opposite corners of the box being 5cm away from walls

of the test box (Fig 3.6a). The test animal was allowed to explore both objects for 10

minutes and the time of interaction with the respective objects was calculated as

exploration time. Test animal was returned to its home cage after familiarization

session was over. In the test session, which consisted of 10 minutes, a novel object in

place of one of the objects and the test animal was observed for its memory for

familiar object and its ability to recognize novel object (Fig 3.6b). The time when test

animal physically touched the object was calculated as exploration time.

Recognition index

Recognition index was calculated as the ratio of time spent with novel object to the

time spent with object 1 + novel object.

Recognition Index =Time spent with Novel Object

Time spent with Object 1 + Novel Object



Disease 41

Fig 3.7: Novel object recognition test setup. (a) Test setup for "familiarization session". (b) Test setup

for "test session" of novel object recognition test.

a

b



Disease 42

3.4.2.6 Fear conditioning

Fear conditioning is associative learning in which animal learns to associate a

particular neutral stimulus (e.g. a tone), called conditioned stimulus (CS), with an

aversive stimulus (e.g. a shock), called unconditioned stimulus (UCS) (Fig 3.7b). This

can be done by pairing of conditioned and unconditioned stimulus, in this way animal

associates the aversive stimulus with context and the tone. The fear response, called

conditioned response, is measured as freezing time. Freezing is a commonly used

index of fear in rodents and is defined as "complete absence of any body movements

except for those associated with respiration" (Blanchard and Blanchard, 1969). Fear

conditioning is a standardized and extensively used test for animal cognition and

memory. Fear conditioning test is an amygdala dependant test (Fig 3.8).

Apparatus

The testing procedure was conducted according to the protocol described previously

(Lee et al., 2012) with slight modifications. An animal enclosure chamber (Fig 3.9a),

with dimensions 17cm x 17cm x 25cm, was used to induce fear conditioning. The

walls of the chamber were made of clear glass and floor consisted of stainless steel

rods which were connected to a shock delivery apparatus. The shock delivery

apparatus could deliver CS and UCS of known intensity, duration and frequency. The

top of the box was open to facilitate video recording via a recording camera. The

animal enclosure chamber was placed inside a sound attenuating chamber (Fig 3.9b)

to minimize travel of fear related ultrasonic vocalizations. The sound attenuating

chamber was lit with a light source. In addition a loud speaker to deliver acoustic

signal and a video camera above the animal enclosure chamber, were also present in



Disease 43

the sound attenuating chamber. Background noise (white noise) was provided by the

ventilation fan present inside the sound attenuating chamber. ANY-Maze software

was used to design and implement the protocol for tone and shock duration and

intensity. To prevent olfactory cues the test box was cleaned with 70% ethanol before

and after the experiment.

Fear conditioning procedure

The animal was placed in test box for 5 minutes to become acclimatized with the new

environment and to avoid any false positive freezing response resulting from anxiety

of the new space. Test session consisted of 5 tones with intensity of 80db at 3000 Hz.

Each tone consisted of 30 seconds (CS), co-terminated with a 0.5 mA foot shock (US)

(1 second). The inter tone interval (ITI) between each tone was kept 120 seconds (Fig

3.7a). The response to the US and CS was measured as ―freezing‖. ANY-Maze

software was used to measure freezing time and freezing episodes during the tone.

Following formula was used to express freezing time as percentage of total time.

% freezing =Time of freezing (sec)

30 sec x 100



Disease 44

Fig 3.8: Fear conditioning protocol. (a) Diagrammatic representation of the protocol used for fear

conditioning. (b) Cartoon presentation of fear conditioning setup with presentation of both CS and

UCS.

a

b



Disease 45

Fig 3.9: Diagrammatic representation of the brain parts involved in fear conditioning circuit.



Disease 46

Fig 3.10: Fear conditioning test apparatus. (a) Animal enclosure chamber. (b) Sound attenuated

chamber. (c) Fear conditioning system with stimulus programming device.

a b

c



Disease 47

Fig 3.11: Fear conditioning test. The red arrow shows fear conditioning instrument and stimulus

programming device connected to computer and blue arrow represents the user interface on computer

screen showing live video recording of the subject animal in the animal enclosure chamber during fear

conditioning testing procedure.



Disease 48

3.4.2.7 Contextual fear memory testing

The test was performed according to the protocol illustrated previously (Wood and

Anagnostaras, 2011) with slight modifications. The test was conducted 18 to 20 hours

after fear conditioning to assess learned aversion from the context (context-dependant

fear) in animals. This is hippocampus dependent memory. The animal was exposed to

the same context that was used in fear conditioning but no CS or US was delivered to

the animal. The test duration was 5 minutes and freezing was recorded with the ANY-

maze software which was plotted as percent freezing during test duration. After each

trial, the box was properly cleaned with 70% ethanol.



Disease 49

Fig 3.12: Contextual fear memory test. (a) Cartoon presentation of contextual fear memory test setup

showing placement of animal in fear conditioning instrument without presentation of CS or UCS. (b)

The red arrow shows fear conditioning instrument and stimulus programming device connected to

computer and blue arrow represents the user interface on computer screen showing live video recording

of the subject animal in the animal enclosure chamber during contextual fear memory testing

procedure.

a

b



Disease 50

3.4.2.8 Fear extinction

Fear extinction is classically conditioned behavioral paradigm. When the CS is

presented alone without UCS (Fig 3.12a). The animal develops a new learning that

CS no longer predicts the forthcoming of an aversive stimulus (foot shock in this

case) and hence conditioned freezing response gradually declines.

The testing procedure was performed as demonstrated previously (Lee et al., 2012)

with few modifications. Briefly, the experiment was conducted 4 hours after the

contextual fear memory test. For this test entirely different context, from the context

used in fear conditioning, was used so that only the memory associated with CS could

be measured. In the new context the floor and the walls of chamber were replaced

(Fig 3.12b). The animals was given a habituation time of 7 minutes to avoid anxiety

associated freezing in new environment. The test phase consisted of twenty tones (80

dB and 3000 Hz each) which served as CS; each of 30 seconds duration long and ITI

was 30 seconds. During fear extinction animal was not given US. The ANY-maze

software was used to measure freezing episodes and freezing time. The freezing time

was plotted as percent freezing (Fig 3.13). Upon completion of experiment 70%

ethanol was used to clean the box.



Disease 51

Fig 3.13: Fear extinction test setup. (a) Cartoon presentation of fear extinction test setup showing

placement of animal in a different context with presentation of only CS. (b) Animal enclosure box with

its floor and walls modified. (c) Sound attenuating chamber.

a

b

c



Disease 52

Fig 3.14: Fear extinction setup. The red arrow shows fear conditioning instrument and stimulus

programming device connected to computer and blue arrow represents the user interface on computer

screen showing live video recording of the subject animal in the animal enclosure chamber during fear

extinction testing procedure.



Disease 53

3.5 Gene expression studies

Previously described procedure (Ahmed et al., 2010) was used to carry out gene

expression studies.

3.5.1 RNA extraction

Tri-reagent was used to extract RNA, from cortex, hippocampus and amygdala,

according to the protocol provided by manufacturer. Animals were anesthetized with

chloroform before sacrifice. Hippocampus, cortex and amygdala were quickly

harvested from right hemisphere of mouse brain. With the glass homogenizer 50-100

mg of the mouse brain was homogenized in 1ml of Tri-reagent. A stand of 5 minutes

at room temperature was given to samples to allow nucleoprotein complexes to

dissociate completely. After stand, chloroform (0.2ml/ ml of Tri-reagent) was added

to samples and were rigorously shaken for 15 seconds until the mixture turned milky.

Another stand of 10 minutes was given to mixture at room temperature followed by a

centrifugation at 12,000xg at 4oC for 15 minutes. Centrifugation resulted in mixture

separation in three phases: a lower red phase having proteins, an opaque DNA

containing interphase and a colorless upper RNA containing aqueous phase. The RNA

containing phase was removed carefully avoiding contamination of DNA. To this

aqueous phase, isopropanol (0.5 ml) was mixed by 2-3 times eppendorf inversions

and was given a stand for 10 minutes at room temperature to limit the DNA

contamination chances. The mixture was again centrifuged at 12,000xg at 4oC for 10

minutes which caused the RNA to precipitate in the form of a white pellet along the

wall of the eppendorf tube. RNA pellet was washed with 1ml of 75% ethanol after

removing supernatant. The ethanol was diluted in DEPC water to inactivate RNase



Disease 54

enzyme. The centrifugation of RNA pellet with ethanol was performed at 7500 rcf for

5 minutes (4oC). After that RNA samples were stored at -80

oC until use.

To process the RNA for reverse transcription (RT), it was removed from -80oC. The

75% ethanol was removed and the pellet was re-suspended in 30 µl PCR water.

Following re-suspension the pellet was given a heat shock at 55oC for 5 minutes to

ensure complete dissolution of the pellet and to remove secondary structures from the

RNA sample. RNA concentration was measured quantitatively via spectrophotometer

after heat shock.

Quality of RNA

RNA samples were run on agarose gel (2% ) to ensure quality of RNA and to assess

quantity for authentic results. Only the samples showing clear sharp bands of 28S and

18S RNA were further processed.

3.5.2 RT-PCR for quantification of mRNA levels

The quantity of RNA was measured through spectrophotometer and equal quantity of

RNA (1µg in 40µl reaction volume) was used for RT-PCR (to make cDNA) using

Oligo dT primers. Equal quantity of RNA was used to ensure that the changes

observed in gene band intensity after PCR was actually due to changes in gene

expression.

3.5.3 Polymerase chain reaction (PCR) for expression of genes

The cDNA was used for PCR and the reaction mixture consisted of 10 µM primer, 25

mM MgCl2, 10 mM dNTPs and 1.25 units of Taq polymerase. Gene specific primers

(sequence mentioned in table 3.2) were used for PCR. The PCR cycle consisted of an



Disease 55

initial denaturation at 95oC (5 minutes), denaturation at 94

oC (30 seconds), annealing

at respective primer temperature (30 seconds) and a final extension at 72oC (30

seconds). The reaction was terminated with final extension at 72oC (10 minutes). The

reaction was repeated for 35 cycles.

The PCR products were visualized by 10 mg/ml of ethidium bromide solution (10µl

for 100ml of gel) on 2% agarose gel, visualized by ethidium bromide staining.

Densitometric analysis of each PCR band was done using ―Image J‖ software (Fig

3.14). The respective group PCR products were normalized with housekeeping gene

Actin.

DNA contamination check

The DNA contamination was ruled out by performing RT-PCR without addition of

RT enzyme with same primers. This was termed as NO-RT control and it did not give

any band.

3.5.3.1 Agarose gel image analysis of the PCR products

The gel images of amplified PCR products were captured. Density analysis in terms

of maximum and minimum gray value was done for each band. Later actin band was

used to normalize band density of respective gene band in each group and the results

were graphically represented.



Disease 56

Table 3.2 Primer sequence for each gene used in the study along with conditions.

S.No Gene Primer sequence (5' to 3') AT

*

No. of

cycles

1

Actin (F) GCCTTCCTTCTTGGGTATGG

55°C 35

(R) CAGCTCAGTAACAGTCCGC

2 α7 nAChR (F) TGCAAAGAGCCATACCCAGA

54oC 35

(R) TGATCCTGGTCCACTTAGGC

3 α4 nAChR (F) GTCTAGAGCCCGTTCTGTGA

54oC 35

(R) TAGTCATGCCACTCCTGCTT

4 β2 nAChR (F) GATGACCAGAGTGTGAGGGA

55oC 35

(R) CCCCCACCGTTAACACTACT

5. ChAT (F) CTGGTGGAGAGAATAAACCG

55oC 35

(R) CTGGTGGAGAGAATAAACCG

*AT= Annealing Temperature



Disease 57

Fig 3.15: ImageJ software used for densitometric analysis of PCR bands. (a) Software with gel image.

(b) Image representing band selection for measurement of maximum and minimum gray value. (c) The

results of maximum and minimum grey values measured by software.

a

c b



Disease 58

3.6 Histological studies

3.6.1 Transcardial perfusion

Transcardial Perfusion of animals was performed according to protocol described

previously (Gage et al., 2012). Mice were given i.p. injection of Ketamine anesthesia

(500 mg/10ml). After the animal was completely anesthetized and pedal reflex was

abolished an incision was made on abdomen proceeding up to the diaphragm. The

diaphragm was carefully cut to make rib cage accessible and to expose heart. The

heart was held at fixed position with the help of forceps and needle of the tubing,

containing normal saline, was inserted about 5 mm deep in left ventricle. About 80 ml

of normal saline was infused maintaining a slow and steady flow at a rate of about 5

ml/minute. Immediately after that, the right atrium was cut with sharp scissors.

Normal saline injection was followed by a replacement with 4% paraformaldehyde

solution. The perfusion was stopped after 100 ml of paraformaldehyde injection

followed by animal brain harvesting. Before starting the process of fixation the brain

tissue was kept at 4oC in 4% paraformaldehyde for 24-48 hrs.

3.6.2 Brain fixation and paraffin embedding

The brain tissue was dehydrated with ascending grades of ethanol (70%, 95% and

100% ethanol used respectively). The brain tissue was kept in each grade for 1 hour.

Complete dehydration was achieved in absolute alcohol which replaces water in the

tissue without causing shrinkage of cells. Two washes of xylene (each wash of 5

minutes duration) were given to the tissue section for the purpose of clearing. Xylene

replaces dehydrating agent and is also miscible with embedding agent (paraffin). The

brain was kept in xylene for 4 hours. After this paraffin infiltration was carried out.



Disease 59

For this purpose the brain was kept in molten paraffin for 4 hours at 60oC. In this step

the paraffin replaced xylene inside the tissue. After paraffin infiltration brain was

embedded in paraffin inside a special mould to form a solid block for microtome

sectioning at room temperature. The paraffin was kept at 4oC to solidify.

3.6.3 Tissue sectioning and cresyl violet staining

Coronal sections of approximately 3 µm thickness were cut using SLEE Mainz

microtome (CUT6062). After that the sections were stretched in water bath at 37oC

these were placed on glass slides, pre-coated with Mayer’s albumin (glycerol, egg

albumin 1:1). Then the slides were kept on hot plate at 65oC for 20 minutes in order to

melt the paraffin and to ensure complete adhesion of tissue to the slide. De-waxing

was carried out, to remove paraffin, by giving two washes in xylene for five minutes

each. The sections were rehydrated, through descending grades of alcohol as follows

5 minutes incubation in 95% ethanol

1 minute incubation in 70% ethanol

1 minute incubation in 50% ethanol

After rehydration, the tissue sections were kept in cresyl violet stain for 4 minutes for

staining of nissl bodies in neurons. The tissue sections were given few gentle dips in

distilled water to remove extra stain followed by incubation in 50% ethanol for 5

minutes. De-staining was done in 70% acid alcohol (2ml glacial acetic acid in 200ml

of 70% ethanol) for 2 minutes. Allow the slide to dry for 2 hours in covered container.

Before mounting, sections were placed in xylene for 2 minutes, and the cover slip was

placed using Canada balsam as mounting medium. Finally the brain sections were



Disease 60

examined under ordinary light microscope to determine the morphological changes in

neuronal cell bodies and cell number.

3.6.4 Quantification of cell number

Quantitative analysis of the cell number was carried out in cortical layers (Layer 1,

Layer 2-4, Layer 5 and Layer 6) in the areas of motor cortex, somatosensory cortex

(hind limb and fore limb region) and primary somatosensory cortex (dysgranular zone

and barrel field). The analysis was performed in area of 10000 µm2

(Fig 3.16) using

program image J software from three randomly selected regions in each cortical layer.

Similarly cell number was quantified in hippocampus from dentate gyrus (DG), CA1,

CA2 and CA3 regions. From each region three areas of 5000 µm2 were randomly

selected and cell number was quantified in these areas (Fig 3.17). Later the average of

values from all three areas in each layer of cortex and all four regions of hippocampus

were taken and were plotted.



Disease 61

Fig 3.16: Presentation of the mouse brain atlas coordinates from where the sections were taken for

histological examination and quantification of cell number. MC: motor cortex, SSC1: somatosensory

cortex (hind limb and fore limb region), SSC2: somatosensory cortex (dysgranular zone and barrel

field). Image modified from mouse brain atlas Franklin and Paxinos.



Disease 62

Fig 3.17: Histological examination of AD mouse model and control mouse cortex. (a) Motor cortex of

AD mouse model. (b) Somatosensory cortex (hind limb and fore limb region) of AD mouse model. (c)

Primary somatosensory cortex (dysgranular zone and barrel field) of AD mouse model. (d) Motor

cortex of control animals. (e) Somatosensory cortex (hind limb and fore limb region) of control

animals. (f) Primary somatosensory cortex (dysgranular zone and barrel field) of control animals.



Disease 63

Fig 3.18: Histological examination of AD mouse model and control mouse hippocampus. (a)

Presentation of the mouse brain atlas coordinates from where the section was taken for histological

examination and quantification of cell number. (b) Dentate gyrus and CA1 area of hippocampus. (c)

CA2 and CA3 area of hippocampus.

a

c b



Disease 64

3.7 Determination of aluminum concentration in brain

Al concentration was determined in hippocampus via inductively coupled plasma

atomic emission spectrometry (ICP-AES) as described by (Kazi et al., 2007) for blood

with some modifications. All propylene glass wares were rinsed with distilled water

and were then soaked in 10% (v/v) nitric acid for 48 hours and then thoroughly

washed with de-ionized water. Accurately 1g of wet tissue was weighed and was

digested by conventional wet digestion method by adding 3ml of freshly prepared

HNO3-H2O2 mixture (2:1 v/v). The samples were then digested at 70oC for 2 hours

after which the samples were treated with 2ml of HNO3 and few drops of H2O2 and

heating was continued at 80oC until the digested mixture became clear. The surplus

acid was evaporated to obtain a semi-dry mass to which de-ionized water was added

up to 3ml after which the concentration of Al was measured using ICP-AES at

analytical wavelength of 396.15 λ.

3.8 Determination of acetylcholine level in brain

Measurement of Ach level in the brain was carried out in cortex, hippocampus and

amygdale using choline/Ach assay kit ab65345 (Abcam, USA). The assay was

performed as described in the instruction manual provided with the kit. The kit

provides a sensitive colorimetric detection for choline and Ach. The end product,

formed by oxidation of free choline via betain aldehyde intermediate, generate color

at λ=570nm. First of all standard curve was obtained after making serial dilution of

choline standard, provided with the kit, according to instructions provided with the

kit. For Ach determination cortex, hippocampus and amygdala were freshly isolated

from test animals and the brain parts were weighed and equal amount of brain tissue



Disease 65

from all parts was further processed. The sample preparation was performed by

homogenizing brain tissue in choline assay buffer provided with the kit. The

homogenate was centrifuged at 12000xg and supernatant was collected. The

supernatant was mixed with choline + AChE reaction mixture was prepared according

to the instructions provided with the kit. About 50μl of sample was loaded in ELISA

plates and was incubated t room temperature for 30 minutes to allow reaction to

complete. Absorption was measured λ=570nm, after incubation, in ELISA plate

reader and the results were plotted.

3.9 In-vitro field potential gamma oscillation study

3.9.1 Hippocampal slice preparation

All in-vitro animal procedures followed the Animals (Scientific Procedure) Act, 1986,

UK. Hippocampal slice preparation was performed as previously described (Lamsa et

al., 2007). Briefly, three to five week old C57Bl/6J mice were anaesthetized

terminally using an i.p. injection of 0.13ml pentobarbitone sodium (20% w/v) and

were sacrificed by decapitation after pedal reflex was abolished. Brain tissue was

quickly harvested and bathed in ice cold (2-4oC) sucrose solution containing (in mM):

87 NaCl, 2.5 KCl, 7 MgCl2, 75 Sucrose, 0.5 CaCl2, 1.25 NaH2PO4, 25 NaHCO3, and

20 glucose bubbled with 95% O2 and 5% CO2. Horizontal 350 µm thick brain slices

with transversal cut of ventral hippocampus were made. The slices were kept at room

temperature (20-25oC) at interface storage chamber in bubbled artificial cerebrospinal

fluid (ACSF), for at least 60 minutes prior to recording. The composition of ACSF

was (in mM):119NaCl, 2.5 KCl, 2.5 CaCl2, 1.3 MgSO4, 1.25 NaH2PO4, 25 NaHCO3,

and 11 glucose.



Disease 66

3.9.2 Electrophysiological recording and field potential analysis

Extracellular field potential recordings were performed in the hippocampal CA3 area

with glass microelectrode filled with ACSF (resistance 2-5 MΩ) (Fig 3.18).

Temperature in recording chamber was maintained at 32 ± 2oC. Data were recorded

with Axoclamp 2A amplifier (Axon Instruments, Foster City, CA, USA), using signal

amplification of 1000x and low-pass filtered at 1 Hz. Signals were low pass filtered at

1 kHz using an 8 pole Bessel filter (LPBF-48DG NPI Electronic, Tamm, Germany).

Data was acquired at 5 kHz with analog to digital conversion by ITC16 computer

interface (Instrutech Corporation, Long Island, NY, USA). Field potential spectral

analysis was performed off line with the software Igor pro 6.34. The parameters used

to measure the oscillatory activity in the slices were peak power (mV2), peak

frequency (Hz) and area power (mV2/Hz). Area power was defined as the area in

power spectra under peak between 5 and 45 Hz.

3.9.3 Drug application

Nicotine (10µM), α7 nAChR antagonist MLA (100nM) and α4β2 nAChR antagonist

DHβE (2µM) were consecutively applied in continuous presence of CCh and nicotine.

Al was applied as Aluminum chloride hexahydrate AlCl3.6H2O in perfusion and

storage solution. For Al incubation, slices were incubated in AlCl3 (100µM) for 1

hour (acute treatment) or 3-4 hours (semi-chronic treatment) before CCh application.

For Al washout experiments slices were first incubated in AlCl3 containing ACSF for

3-4 hours and then were transferred to AlCl3 free ACSF for 1-1.5 hours to ensure

complete washout before the start of the experiment.



Disease 67

Fig 3.19: Diagrammatic presentation of brain slicing in horizontal plane. The inset shows different

layers of hippocampus and area from where the recording was done.



Disease 68

3.10 Statistical analysis

Data is presented as mean ± standard error of mean (SEM) and "n" represents number

of animals. The results were analyzed statistically using software ―Graphpad Prism‖

(version 5.01). Two way ANOVA followed by Bonferroni posthoc test was applied to

analyse the significance of the results. Results were taken significant only if the p

value was less than 0.05.

CHAPTER 4

RESULTS

Chapter 4 Results

Evaluation Of Nicotinic Acetylcholine Receptors In Learning and Memory Using Mouse Model Of Alzheimer’s

Disease 70

RESULTS

4.1 Effect of aluminum on spatial memory in morris water maze test

Spatial learning of the control and AD mouse model was assessed across multiple

trials for a period of five days in Morris water maze (MWM) test. MWM is a reliable

and robust test for assessment of hippocampus dependent learning. The results of our

experiments showed significant impairment of spatial memory in AD mouse model

relevant to control group (Fig 4.1a). The comparison of the last day escape latency

time revealed that the control animals found the platform in significantly shorter time

(6.67 ± 0.73 seconds) as compared to AD mouse model (21.28 ± 2.07 seconds,

p<0.001; Fig 4.1b). The reference memory in the animals was evaluated by preference

for the platform location in the absence of platform during probe trial (Fig 4.2b and

Fig 4.2c). The probe trial results revealed that the control animals spent significantly

more time (29.6 ± 2.01 seconds) in target quadrant as compared to AD mouse model

(16.7 ± 1.09 seconds, p<0.001; Fig 4.2a). Number of crossings over the platform

position revealed that control animals crossed the previous platform position

significantly more times (8.66 ± 0.88) as compared to AD mouse model (3.16 ± 0.47,

p<0.01; Fig 4.2d).

Chapter 4 Results


Disease 71

Morris Water Maze

1 2 3 4 50

20

40

60

80Control group (n=9)

AD mouse model (n=9)

Days

Escap

e L

ate

ncy

(se

c)

Morris Water Maze Last Trial

0

5

10

15

20



Escap

e L

ate

ncy (

se

c)

Fig 4.1: Effect of Al on spatial and reference memory in Morris water maze test (MWM). (a)

Comparison of spatial memory in control and AD mouse model during five training days of MWM

test. (b) Comparison of spatial memory in control and AD mouse model on last day of MWM

training ***p<0.001; n = sample size.

a

b

Morris Water Maze Last Trial

0

5

10

15

20

25Control (n=9)


Escap

e L

ate

ncy

(se

c)

Chapter 4 Results


Disease 72

Fig 4.2: Graph describing effect of Al on probe trial in MWM. (a) Comparison of reference memory

in control and AD mouse model during probe trial. (b) Pathway followed by control mice in probe trial.

(c) Pathway followed by AD mouse model in probe trial. (d) Comparison of the number of crossings

over the platform position in control and AD mouse model in probe trial. **p<0.01; n = sample size.

Probe Trial

0

10

20

30

40 Control group (n=10)

AD mouse model (n=10)**

Tim

e s

pe

nt in

Tar

ge

t

Qua

dra

nt (

Se

c)

0

5

10



**

Num

be

r o

f C

rossin

gs O

ver

Pla

tfo

rm P

ositi

on

a

b c

d

Chapter 4 Results


Disease 73

4.2 Effect of aluminum on anxiety in elevated plus maze test

Elevated plus maze (EPM) is a method for assessing anxiety in animals. The

percentage of time spent in open arms or in closed arms was chosen to index anxiety

in EPM. Results of EPM showed increased anxiety in the AD mouse model, as

control animals spent significantly higher time in open arms (120.6 ± 11.54, p<0.001)

as compared to the AD mouse model (55.13 ± 9.152; Fig 4.3a). Similarly, number of

entries in open arm were also significantly lower in AD mouse model (6.62 ± 0.86) as

compared to control animals (13 ± 1.48, p<0.05; Fig 4.3b).

Chapter 4 Results


Disease 74

0

50

100



***

Tim

e s

pe

nt in

op

en a

rm (

se

c)

Fig 4.3: Graphical presentation of measure of anxiety in control and AD mouse model in EPM. (a)

Comparison of control and AD mouse model for time spent in open arm. (b) Comparison of control

and AD mouse model for the number of entries in open arm. *p<0.05, ***p<0.001; n = sample size.

0

5

10

15


AD mouse model (n=8)*

Num

be

r o

f E

ntr

ies

in O

pe

n A

rma

b

Chapter 4 Results


Disease 75

4.3 Effect of aluminum on anxiety and exploration in open field test

High anxiety level was observed in AD mouse model in open field test, as these

animals preferred to spend significantly more time in periphery of the test box (22.19

± 0.5 seconds) as compared to control group (16.71 ± 0.4 seconds, p<0.001). In

comparison the control animals spent significantly greater time in center (8.03 ± 0.41

seconds, p<0.001) as compared to AD mouse model (2.95 ± 0.57 seconds; Fig 4.4a).

Greater exploratory activity in new environment was observed in control animals as

revealed by higher rearing number (45 ± 3.06) as compared to AD mouse model

(22.57 ± 2.68, p<0.001) during initial 5 minutes of 30 minutes test duration. Whereas

control animals showed greater adaptation to the new environment as depicted by

significantly decreased rearing (7.5 ± 1.47) as compared to AD mouse model (21.28 ±

1.94, p>0.05; Fig 4.4b) during last 5 minutes of total test duration. The analysis of

grooming activity showed that during initial 5 minutes none of the animals showed

relaxed grooming. While relaxed grooming increased in control animals (41.93 ± 7.21

seconds) as compared to the AD mouse model (4.38 ± 1.07 seconds, p<0.001) during

the last 5 minutes of test (Fig 4.5a) revealing a greater adaptation to the novel

environment. The AD mouse model showed high anxious grooming (45.28 ± 5.18

seconds) during the initial 5 minutes as compared to control animals (11.79 ± 1.89

seconds, p<0.001). While during the last 5 minute, control animals showed almost

negligible anxious grooming (2.8 ± 0.31 seconds) while AD mouse model were

unable to adapt to new environment and showed high anxious grooming even during

the last 5 minute (21.54 ± 2.42 seconds, p<0.001; Fig 4.5b) of 30 minute test duration.

Chapter 4 Results


Disease 76

Open Field Test

0

5

10

15

20



***

***

Exp

lora

tion T

ime

(m

in)

Initial 5 min Last 5 min0

20

40



**

******

Num

be

r o

f R

ear

ing

s

Fig 4.4: Effect of Al on exploratory activity in open field test. (a) Graph depicting time spent

(minutes) by control and AD mouse model in center and periphery of open field test box. (b)

Comparison of number of rearings in control and AD mouse model during the initial and last 5

minutes of 30 minute open field test duration. *p<0.05, **p<0.01, ***p<0.001; n = sample size.

a

b

Chapter 4 Results


Disease 77


20

40



***

***

Gro

om

ing

tim

e (

se

c)

Fig 4.5: Effect of Al on anxiety behavior in open field test. (a) The time spent (seconds) by control

and AD mouse model in relaxed grooming during the initial and last 5 minutes of 30 minute test

duration. (b) The time spent (seconds) by control and AD mouse model in anxious grooming during the

initial and last 5 minutes of 30 minute test duration. ***p<0.001; n = sample size.


20

40



***

Re

laxe

d G

roo

min

g tim

e (

se

c)

a

b

Chapter 4 Results


Disease 78

4.4 Effect of aluminum on social novelty preference

In social interaction session the control animals spent significantly more time with

stranger 1 (mouse 1) (114.22 ± 17.41) as compared to AD mouse model (68.55 ±

13.7, p<0.05) and empty cage (40.44 ± 4.85, p<0.001). While AD mouse model spent

same time with stranger 1 (68.55 ± 13.7) and empty cage (41.55 ± 5.29, p>0.05; Fig

4.6a) showing impaired social interaction. In social novelty preference session control

animals spent greater time with stranger 2 (mouse 2) (86.66 ± 11.66) as compared to

AD mouse model (53.11 ± 8.91, p<0.05) and stranger 1 (47.66 ± 7.34, p<0.01; Fig

4.6b) revealing the intact memory for stranger 1 in control animals. Whereas the AD

mouse model spent similar time with stranger 2 (53.11 ± 8.91) and stranger 1 (37 ±

7.53).

4.5 Effect of aluminum on novel object recognition

The results revealed that control animal prefer to spend significantly more time with

novel object (82.20 ± 9.45, p<0.05) as compared to AD mouse model (52.20 ± 6.40;

Fig 4.7a and 4.7b) and object 1 (51 ± 6.03, p<0.05). AD mouse model spent same

time with novel object (52.20 ± 6.40) and object 1 (42.8 ± 5.18, p>0.05) showing

impaired recognition for novel object after Al treatment. Comparison of recognition

index of control (0.63 ± 0.031, p<0.05) and AD mouse model (0.48 ± 0.046) for

known and novel object (Fig 4.8) showed that control group had higher recognition

for novel object as compared to AD mouse model.

Chapter 4 Results


Disease 79

Session 1

Empty Cage Stranger 10

50

100



****

Inte

ractio

n tim

e (

Se

c)

Session 2

Stranger 1 Stranger 20

50

100


AD mouse model (n=9)***

Inte

ractio

n tim

e (

Se

c)

Fig 4.6: Effect of Al on social novelty preference. (a) The interaction time in first session by control

and AD mouse model with empty cage and mouse 1. (b) The time spent by control and AD mouse

model interacting with mouse 1 and mouse 2 (stranger mouse) in second session of the test. *p<0.05; n

= sample size

a

b

Chapter 4 Results


Disease 80

Session 1

Object 1 Object 20

20

40

60

80



Exp

lora

tion T

ime

(se

c)

Session 2

Object 1 Novel Object0

20

40

60

80

100

Control group (n=8)


**

Exp

lora

tion T

ime

(se

c)

Fig 4.7: Effect of Al on novel object recognition. (a) Graph represents the time spent, by control and

AD mouse model, in exploration of object 1 and 2 during familiarization session. (b) Comparison of

novel object preference by control and AD mouse model during second session (test session). *p<0.05;

n = sample size.

a

b

Chapter 4 Results


Disease 81

0.0

0.2

0.4

0.6

0.8 Control group (n=8)


*

Re

co

gniti

on I

nd

ex

Fig 4.8: Graphical illustration of the recognition index for novel object during test session by both the

groups. *p<0.05; n = sample size.

Chapter 4 Results


Disease 82

4.6 Effect of aluminum on fear conditioning

Fear conditioning results showed that the memory development in AD mouse model

(57.04 ± 9.96) and their control group (62.18 ± 11.99; p>0.05; Fig 4.9a) was similar.

The freezing episode is defined as time duration between two animal movements.

Therefore as the freezing percentage increases the animal movement decreases

resulting in decrease in freezing episodes (Fig 4.9b).

4.7 Effect of aluminum on contextual fear memory

During contextual fear memory test control animals show higher freezing (46.16 ±

4.64) as compared to AD mouse model (25.7 ± 3.18, p<0.01; Fig 4.10a). The freezing

episodes were similar in control and AD mouse model during contextual fear memory

test (Fig 4.10b).

4.8 Effect of aluminum on fear extinction

During fear extinction the control animals show progressive decline in the freezing

response (Fig 4.11a) and showed very little freezing during the last 5 tones of fear

extinction (3.52 ± 1.38 seconds; Fig 4.11b). While AD mouse model were unable to

develop new memories associated with fear extinction and showed very high freezing

(27.39 ± 6.26 seconds, p<0.01, Fig 4.11b) even during the last 5 tones of fear

extinction. The freezing episodes increased with decrease in fear percentage in control

animals during fear extinction (Fig 4.11c).

Chapter 4 Results


Disease 83

Fear Conditioning

1 2 3 4 50

20

40

60

80



Tone Trials

% F

ree

zing

Fear Conditioning

1 2 3 4 5

0

2

4

6

8



Tone Trials

Fre

ezin

g E

pis

od

es

Fig 4.9: Effect of Al on fear memory during fear conditioning. (a) Percent freezing response in control

and AD mouse model across five cue-foot shock pairing trials of amygdala dependant delay fear

conditioning test. (b) Graph illustrating freezing episodes response in control and AD mouse model

across five cue-foot shock pairing trials of fear conditioning test.

a

b

Chapter 4 Results


Disease 84

Contextual Fear Memory

0

20

40



% F

ree

zing

**

Contextual Fear Memory

0

20

40

60



Fre

ezin

g E

pis

od

es

Fig 4.10: Effect of Al on contextual fear memory. (a) Graph demonstrating percent freezing response

in control and AD mouse model, in the same context in which fear conditioning was done, as a

measure of hippocampus dependant contextual memory for Pavlovian fear. (b) Freezing episodes in

control and AD mouse model in contextual fear memory test. **p<0.01; n = sample size.

a

b

Chapter 4 Results


Disease 85

Fear Extinction

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 200

20

40

60



Tone Trials

% F

ree

zing

Fear extinction last 5 tones

0

10

20

30



**

% F

ree

zing

Fear Extinction

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 210

5

10



Tone Trials

Fre

ezi

ng E

pis

od

es

Fig 4.11: Effect of Al on fear extinction. (a) Percent freezing response in control and AD mouse

model across twenty presentations of CS during fear extinction test. (b) The average freezing response

in control and AD mouse model during last five tones of fear extinction. (c) Freezing episodes in

control and AD mouse model during fear extinction test. **p<0.01; n = sample size.

a

c

b

Chapter 4 Results


Disease 86

4.9 Gene expression

The RNA was run on 2% agarose gel to ensure quality of RNA and only samples

showing sharp 18S and 28S bands were further processed (Fig 4.12). The expression

of α4 nAChRs was significantly less in hippocampus of AD mouse model (0.23 ±

0.037) as compared to control animals (0.74 ± 0.14, p<0.05). A greater difference was

observed in the expression of α7 (0.78 ± 0.23) and β2 (0.519 ± 0.15) nAChRs as

compared to α7 (2.64 ± 0.68, p<0.001) and β2 (2.25 ± 0.25, p<0.001; Fig 4.13a)

nAChRs in control animals.

The gene expression of α7 (0.81 ± 0.08), α4 (0.19 ± 0.02) and β2 (0.91 ± 0.14)

nAChRs was significantly reduced in cortex of AD mouse model as compared to the

α7 (2.35 ± 0.61, p<0.05), α4 (0.88 ± 0.0.15, p<0.05) and β2 (2.06 ± 0.52, p<0.05; Fig

4.13b) nAChRs in cortex of control animals. Whereas in amygdala only the

expression of α7 (0.57 ± 0.16) and β2 (1.06 ± 0.12) nAChRs were reduced in AD

mouse model as compared to the α7 (1.74 ± 0.18, p<0.001) and β2 (1.6 ± 0.12,

p<0.05; Fig 4.14a) nAChRs of control animals while the level of α4 nAChR remained

unaltered after Al treatment.

The ChAT gene expression was significantly reduced in hippocampus after Al

treatment (0.87 ± 0.13) as compared to control animals (1.9 ± 0.39, p<0.01). While

the ChAT expression remained same in cortex and amygdala of AD mouse model (0.4

± 0.12, 0.43 ± 0.1 respectively) and control animals (1 ± 0.19, 0.42 ± 0.08

respectively, p>0.05; Fig 4.14b)

Chapter 4 Results


Disease 87

Fig 4.12: Image showing sharp bands of 18S and 28S RNA on 2% agarose gel. Hippo: hippocampus,

Amyg: amygdala.

Chapter 4 Results


Disease 88

Fig 4.13: Comparison of alpha 7(α7), alpha 4 (α4) and beta 2 (β2) nAChR gene expression in (a)

hippocampus and (b) cortex of control and AD mouse model. *p<0.05, ***p<0.001; n = sample size.

a

b

a

Chapter 4 Results


Disease 89

Fig 4.14: Expression of nicotinic acetylcholine receptor in amygdala and choline acetyltransferase

genes. (a) Comparison of alpha 7 (α7), alpha 4 (α4) and beta 2 (β2) nAChR gene expression in

amygdala of control and AD mouse model. (b) Comparison of ChAT gene expression in cortex,

hippocampus and amygdala of control and AD mouse model. *p<0.05, **p<0.01, ***p<0.001; n =

sample size.

a

b

Chapter 4 Results


Disease 90

4.10 Aluminum concentration in brain

The evaluation of Al concentration in brain of AD mouse model showed that AD

mouse model had significantly high concentration of Al in hippocampus (688.14 ±

242.82 μg/g) and cortex (462.57 ± 121.08 μg/g) of AD mouse model as compared to

hippocampus (115.14 ± 18.18 μg/g, p<0.01) and cortex (98.85 ± 6.71 μg/g, p<0.05) of

control animals (Fig 4.14). Whereas the Al did not accumulated much in amygdala as

only a slight, non significant increase was observed in amygdala of AD mouse model

(870.83 ± 251.90 μg/g) as compared to the control animals (488 ± 73.23 μg/g, p>0.05;

Fig 4.15).

4.11 Effect of oral aluminum on acetylcholine and free choline levels

The Ach level in cortex of AD mouse model was significantly lower (4.42 ± 1.06) as

compared to the Ach levels in the cortex of control animals (22 ± 5.98, p<0.01).

Similarly highly significant difference was observed between the Ach concentration

in hippocampus of AD mouse model (3.71 ± 1.48) as compared to the control animals

(37.9 ± 2.59, p<0.001). The Ach level remained unaltered in amygdala of AD mouse

model (9.6 ± 1.11) and control animals (11.84 ± 2.2, p>0.05 ; Fig 4.16).

The total choline concentration was significantly high in hippocampus (77.3 ± 14.69)

and cortex (43.4 ± 8.75) of control animals as compared to hippocampus (20.53 ±

3.41, p<0.001) and cortex (16.67 ± 0.92, p<0.05; Fig 4.17a) of control animals but

remained unaltered in amygdala. The results indicated that free choline level remained

the same in cortex, hippocampus and amygdala of AD mouse model (11.6 ± 1.34,

16.82 ± 3.9 and 13.59 ± 3.26 respectively) as compared to the free choline levels in

cortex, hippocampus and amygdala of the control animals (21.39 ± 5.89, 20.66 ± 5.07

and 21.25 ± 5.38 respectively, p>0.05; Fig 4.17b).

Chapter 4 Results


Disease 91

Fig 4.15: The comparison of Al accumulation in cortex, hippocampus and amygdala of control and

AD mouse model. *p<0.05; n = sample size.

Cor

tex

Hippo

cam

pus

Am

ygda

la

0

500

1000


AD mouse model (n=7)* *

Alu

min

um

co

nce

ntr

atio

n

(

g/g

)

Chapter 4 Results


Disease 92

Fig 4.16: Comparison of Ach level in cortex, hippocampus and amygdala of the control and AD

mouse model. *p<0.05, **p<0.01, ***p<0.001; n = sample size

Cortex

Hippocampus

Amygdala

0

10

20

30

40


AD mouse model (n=4)**

***

AC

h C

once

ntr

atio

n

pm

ol/m

g o

f tis

sue

Chapter 4 Results


Disease 93

Fig 4.17: Graphical illustration of total choline and free choline concentration in control and AD

mouse model. (a) Comparison of total choline concentration in cortex, hippocampus and amygdala of

the control and AD mouse model. (b) Comparison of free choline concentration in cortex, hippocampus

and amygdala of control and AD mouse model. *p<0.05, ***p<0.001; n = sample size.

Cor

tex

Hippo

cam

pus

Am

ygda

la

0

10

20

30

40

50Control Group (n=4)


Fre

e C

ho

line

Co

nce

ntr

atio

n

pm

ol/m

g o

f tis

sue

Cor

tex

Hippo

cam

pus

Am

ygda

la

0

20

40

60

80



***

*

To

tal C

ho

line

co

nce

ntr

atio

n

pm

ol/m

g o

f tis

sue

a

b

Chapter 4 Results


Disease 94

4.12 Quantitative analysis of neurodegeneration in brain

The cresyl violet staining in hippocampus (Fig 4.18) revealed that AD mouse model

had significantly reduced cell number in CA1 (14.12 ± 0.5), CA2 (17.18 ± 0.87), CA3

(17.54 ± 0.81) and DG (23.75 ± 0.54) as compared to CA1 (19.62 ± 0.85, p<0.001),

CA2 (22.06 ± 0.83, p<0.001), CA3 (22.29 ± 0.54, p<0.001) and DG (30 ± 0.92,

p<0.001; Fig 4.19) of control animals.

The cresyl violet staining in cortex (Fig 4.20) showed that in left motor cortex of AD

mouse model there was a remarkable decrease in cell number in layer 2-4 (28.5 ±

1.91), layer 5 (26.5 ± 0.99) and layer 6 (29.66 ± 1.53) as compared to the layer 2-4

(34.8 ± 0.76, p<0.01), layer 5 (32.86 ± 1.13, p<0.01) and layer 6 (35.13 ± 1.09,

p<0.05) of control animals. Whereas the cell number in layer 1 of left motor cortex in

AD mouse model (9.77 ± 0.26) remained unaltered as compared to control animals

(11.13 ± 0.79, p>0.05; Fig 4.21a). In right motor cortex the reduction in cell number

was observed only in layer 2-4 of AD mouse model (28.77 ± 1.51) as compared to

layer 2-4 of control animals (34.86 ± 1.16, p<0.05; Fig 4.21b). The cell number in all

other layers of right motor cortex remained unchanged.

No difference in cell number in any of the layer in left soamtosensory cortex (hind

limb and forelimb region) (Fig 4.22a) or right soamtosensory cortex (hind limb and

forelimb region) (Fig 4.22b) was observed between control and AD mouse model.

The comparison of cell number in histological sections of left somatosensory cortex

(dysgranular zone, barrel field area) showed that the cell number in layer 2-4 (26 ±

1.89) was significantly reduced in AD mouse model as compared to the layer 2-4

(31.86 ± 0.87, p<0.01). The cell number on layer 1, 5 and 6 of left somatosensory

Chapter 4 Results


Disease 95

cortex (dysgranular zone, barrel field area) was same in control and AD mouse model

(Fig 4.23a). In dysgranular zone and barrel field area of right somatosensory cortex

there was a significant reduction in layer 2-4 (24.83 ± 1.3) and layer 5 (20 ± 1.25) of

AD mouse model as compared to the layer 2-4 (32.73 ± 1, p<0.001) and layer 5

(24.73 ± 1.56, p<0.05) of control animals. While cell number in layer 1 (5.52 ± 0.61)

and layer 6 (27.72 ± 0.89) of right somatosensory cortex (dysgranular zone, barrel

field area) in AD mouse model remained unaffected as compared to layer 1(7 ± 0.9,

p>0.05) and layer 6 (30.33 ± 1.96, p>0.05; Fig 4.23b) of control animals.

Chapter 4 Results


Disease 96

Fig 4.18: The photomicrograph showing representative slides of hippocampus histology (Nissl

staining) sections at 40X magnification. (a) Dentate gyrus of control animals. (b) Dentate gyrus of AD

mouse model. (c) CA1 area of control animals. (d) CA1 area of AD mouse model. (e) CA2 area of

control animals. (f) CA2 area of AD mouse model. (g) CA3 area of control animals. (h) CA3 area of

AD mouse model.

a

h g

f e

d c

b

Chapter 4 Results


Disease 97

DG CA1 CA2 CA30

10

20

30


AD mouse model (n=8)***

*********

Ce

ll C

ount/5

00

0

m2

Fig 4.19: Graphical elucidation of the cell number in different areas of the hippocampus in control and

AD mouse model. Reduced cell number represents neurodegeneration after Al treatment. ***p<0.001;

n = sample size.

Chapter 4 Results


Disease 98

Fig 4.20: The representative slides of cortex histology (Nissl staining) sections at 40X magnification.

(a) Motor cortex of control animals. (b) Motor cortex of AD mouse model. (c) Hind limb and fore limb

sensory motor cortex of control animals. (d) Hind limb and fore limb sensory motor cortex of AD

mouse model. (e) Dysgranular zone and barrel field area sensory motor cortex of control animals. (f)

Dysgranular zone and barrel field area sensory motor cortex of AD mouse model.

f

d

b

e

c

a

Chapter 4 Results


Disease 99

Fig 4.21: Comparison of cell number in motor cortex of the cortex in control and AD mouse model.

(a) Cell count in different layers of left motor cortex in control and AD mouse model. (b) Cell count in

different layers of right motor cortex in control and AD mouse model. *p<0.05, **p<0.01; n = sample

size.

Cell Count in Left Motor Cortex

1 2-4 5 60

10

20

30



** ***

Cortical Layers

Ce

ll C

ount/1

0,0

00

m2

Cell Count in Right Motor Cortex

1 2-4 5 60

10

20

30



*

Cortical Layers

Ce

ll C

ount/1

0,0

00

m2

a

b

Chapter 4 Results


Disease 100

Fig 4.22: Comparison of cell number in somatosensory cortex of the cortex in control and AD mouse

model. (a) Cell count in different layers of left hind limb and fore limb sensory motor cortex in control

and AD mouse model. (b) Cell number in different layers of right hind limb and fore limb sensory

motor cortex in control and AD mouse model. n = sample size

Cell Count in Left Somatosensory Cortex(Hind Limb and Fore Limb Region)

1 2-4 5 60

10

20

30



Cortical Layers

Ce

ll C

ount/1

0,0

00

m2

Cell Count in Right Somatosensory Cortex(Hind Limb and Fore Limb Region)

12-

4 5 6

0

10

20

30



Cortical Layers

Ce

ll C

ount/1

0,0

00

m2

a

b

Chapter 4 Results


Disease 101

Fig 4.23: Comparison of cell number in somatosensory cortex (dysgranular zone and barrel field area)

of the cortex in control and AD mouse model. (a) Graph depicting cell count in different layers of left

dysgranular zone and barrel field area sensory motor cortex in control and AD mouse model. (b) Cell

number in different layers of right dysgranular zone and barrel field area sensory motor cortex in

control and AD mouse model. *p<0.05, **p<0.01, ***p<0.001; n = sample size.

Cell Count in Left Somatosensory Cortex(Dysgranular Zone and Barrel Field Region)

1 2-4 5 60

10

20

30



**

Cortical Layers

Ce

ll C

ount/1

0,0

00

m2

Cell Count in Right Somatosensory Cortex(Dysgranular Zone and Barrel Field Area)

1 2-4 5 60

10

20

30



****

Cortical Layers

Ce

ll C

ount/1

0,0

00

m2

a

b

Chapter 4 Results


Disease 102

4.13 Nicotinic acetylcholine receptor modulation of gamma

oscillation power in hippocampal slices

Carbachol (CCh) induced field gamma oscillations (25-30 Hz), in hippocampal slices,

which were persistent for long time periods (2 hrs). CCh was applied as

carbamylcholine chloride via perfusion. Stable baseline of gamma frequency (>20

Hz) oscillation was confirmed before starting recording in CCh. Following, stable

baseline for at least 10 minute, drugs were applied via perfusion in the continuous

presence of CCh. The bath application of nicotine along with CCh augmented the

gamma oscillation peak power (1.32 ± 0.09, p<0.01, Fig 4.24a) relative to baseline in

CCh. Further application of nAChR antagonist DHβE reversed the facilitatory effect

of nicotine and gamma oscillation peak power back to the baseline level (0.85 ± 0.21,

p<0.05). However, specific nAChR α7 subunit antagonist MLA had no effect (1.36 ±

0.097) on nicotine induced increase in gamma oscillation peak power (Fig 4.24b and

4.24c).

Chapter 4 Results


Disease 103

Fig 4.24: Field potential recording of gamma oscillation power. (a) Baseline-normalised effect of

nicotine and nAChR antagonists MLA and DHβE on oscillation power. Facilitatory effect of nicotine is

reversed by application of a broad-spectrum non-α7 nAChR antagonist DHβE but not by a specific α7

nAChR blocker MLA. (b) Example traces of extracellular field recordings in area CA3 of hippocampus

after bath application of cholinergic agonist CCh, nicotine, MLA and DHβE. (c) Sample transform plot

showing power analysis from one experiment defining peak power in CCh induced oscillation (blue),

versus nicotine (black), MLA (red) and DHβE (green). *p<0.05, **p<0.01, ***p<0.001. CCh:

carbachol, Nic: nicotine, MLA: methyllycaconitine, DHβE: dihydro-β-erythroidine, n = sample size

a b

c

Chapter 4 Results


Disease 104

4.14 Effect of aluminum on gamma oscillation peak power in

hippocampal slices

Acute exposure to Al (1-2 hours before recording) did not significantly affect gamma

oscillation peak power (11.3 ± 2.5) compared to control slices stored in standard

ACSF (18.06 ± 2.1, p>0.05; Fig 4.25a), and it also maintained nicotine’s effect to

facilitate gamma oscillation peak power (18.2 ± 3.8; Fig 4.25b and 4.25c). However,

semi-chronic exposure to Al (3- 4 hours before recording) significantly reduced (5.4 ±

1.8, p<0.05) the field potential gamma oscillation peak power and completely

abolished nicotine’s effect on peak power (5.5 ± 1.8; Fig 4.25d).

In order to manifest that the reduced gamma peak power and the diminished nicotine

facilitation was due to Al, and not because of prolonged slice incubation, slices were

incubated in Al free ACSF for more than 4 hours before CCh introduction. Incubation

of brain slices in Al free ACSF, for >4 hours, revealed no difference, in baseline with

CCh, between the slices incubated for 1-2 hrs (18.06 ± 2.1) and for >4 hours (19.13 ±

2.6) or with further application of nicotine, MLA or DHβE (Fig 4.26). The extended

incubation in control conditions (without Al) showed that the suppressive effect was

specific for Al. There was no difference between the peak frequency recorded from

slices incubated in normal ACSF or Al pre-incubated slices (acute or semi chronic)

with CCh alone or by further application of nicotine, MLA or DHβE (Fig 4.27). The

gamma oscillation power area (Fig 4.28a) was significantly reduced after acute (1-2

hrs) Al incubation (58.5 ± 9.6), as compared to control slices (incubated in normal

ACSF with CCh) (149.6 ± 8.3; p<0.05). Slices incubated semi-chronically in Al had

highly significant reduction in power area (25.7 ± 5.8; p<0.001) compared to control

slices.

Chapter 4 Results


Disease 105

Fig 4.25: Effect of Al on CCh-induced gamma oscillation peak power. (a) Oscillation peak power is

smaller in slices incubated for 1 or 3-4 hrs with Al (100µM), than in slices kept in standard ACSF

without Al. Wash in of nicotine (10µM) increased the power of carbachol induced gamma oscillations

in slices without Al and those incubated with Al for 1 hour. Nic (10µM) failed to increase oscillation

power in slices incubated in Al for 3-4 hours. The plots b, c and d are example traces and sample

transform plots showing CCh-induced gamma oscillation power from a control slice (no Al pre-

incubation), and slices incubated with Al for 1 hour and 3-4 hours, respectively. Blue lines indicate

baseline recording before and black lines following application of nicotine. **p<0.01, ***p<0.001.

CCh: carbachol, Nic: nicotine, n = sample size.

a

c b

d

Chapter 4 Results


Disease 106

Fig 4.26: CCh-induced gamma oscillation peak power in slices incubated acutely or semi chronically

in Al. Slices in control conditions (incubated without Al) for 1-2 hour or >4 hours before application of

CCh exhibit similar oscillation power in the baseline (CCh, 10uM), and effects of further application of

MLA and DHβE were similar in both groups. CCh: carbachol, Nic: nicotine, MLA:

methyllycaconitine, DHβE: dihydro-β-erythroidine, n = sample size.

Chapter 4 Results


Disease 107

Fig 4.27: Plot shows oscillation peak frequency in experiments. Either acute (1 hour) or semi-chronic

(3-4 hours) incubation to Al did not change CA3 field potential oscillation peak frequency. CCh:

carbachol, Nic: nicotine, MLA: methyllycaconitine, DHβE: dihydro-β-erythroidine, n = sample size.

Chapter 4 Results


Disease 108

Fig 4.28: CCh-induced gamma oscillation power area. (a) Plot showing power area in CCh, CCh +

Nic, CCh + Nic + MLA and CCh + Nic + DHβE in control and Al pre-incubated (1 hr and 3-4 hrs)

condition. (b) Sample plot of oscillation frequency (fourier transformation) from one experiment. The

arrow shows the oscillation peak frequency and the grey shaded area represents the gamma power area.

*p<0.05, **p<0.01, ***p<0.001. CCh: carbachol, Nic: nicotine, MLA: methyllycaconitine, DHβE:

dihydro-β-erythroidine, n = sample size

a

b

Chapter 4 Results


Disease 109

4.15 Semi-chronic aluminum treatment causes non reversible

changes in hippocampal circuitry

Finally, Al was washed-out after semi chronic Al incubation. Removal of Al failed to

restore the CCh-induced gamma oscillation peak power and its modulation by

nicotine. The CCh-induced gamma oscillation peak power remained un altered

between Al wash-out slices (3.4 ± 1.1) and slices without wash-out after semi-chronic

Al incubation (3.6 ± 0.9). Furthermore, application of nicotine on Al washed out

slices failed to augment the gamma oscillation peak power (5.03 ± 1.6; Fig 4.29).

Chapter 4 Results


Disease 110

Fig 4.29: Wash-out of AlCl3 for 1-1.5 hours, after incubation of slices for 3-4 hours in Al, failed to

restore oscillation power and its modulation by nicotine. For comparison data show new recordings in

the presence of Al without wash-out, interleaved with wash-out experiments. CCh: carbachol, Nic:

nicotine, n = sample size

CHAPTER 5

DISCUSSION

Chapter 5 Discussion


Disease 112

DISCUSSION

Aluminum is abundantly present in earth crust (Kaizer et al., 2008) and its exposure

beyond adaptive capability may result in the development of Alzheimer’s like

symptoms including dementia (Wills and Savory, 1985). Considerable evidence

suggests that Al causes neurotoxicity and has a role in the pathogenesis and etiology

of AD (Flaten, 2001).

Al accumulation in the brain might aggravate the causative mechanisms associated

with development of neurodegeneration (Campbell et al., 2004). For this reason it is

imperative to understand the neurotoxic effects of high Al consumption. Certain

individuals who consume antacids or buffered aspirin chronically are exposed to very

high amounts of Al (Abd-Elhady et al., 2013). This study was aimed to elucidate the

Al neurotoxicity at high levels of the human exposure resulting in high Al content in

brain. Previously it has been reported that 2000 μg Al/g (260 mg Al/kg) for 5 weeks is

within the order of magnitude of estimated maximal human intake (Commissaris et

al., 1982, Golub et al., 1989). Keeping in view these facts and Al-induced

neurotoxicity studies from my own laboratory (Iqbal et al., 2016, Syed et al., 2015), a

dose of 250 mg/kg Al was administered for a period of six weeks.

The exact mechanism of Al-induced neurodegeneration is not well known but it is

well known for its cholinotoxic effects which includes deleterious effects on activities

of ChAT and AChE enzymes, reduced level of Ach, reduction in high affinity choline

uptake, and reduced binding of nicotine (Gulya et al., 1990). Due to its ability to

rapidly cross blood brain barrier, chronic exposure to high amounts of Al results in its

accumulation in brain, and affects cholinergic system (Harkany et al., 1995, Peng et

al., 1992). The cholinergic system, which mainly depends on neurotransmitter Ach,



Disease 113

plays important role in memory formation, retention and new learning processes

(Maheswari et al., 2014, Shafer et al., 1993).

Behavior is the net output of motor, cognitive and sensory functions of nervous

system. Therefore behavioral alterations are potentially a sensitive indicator of

xenobiotic induced neurotoxicity (Julka et al., 1995). In order to determine how the

Al induced deficits in nAChR expression and neurodegeneration affect the behavioral

functions, behavior tests dependent on cortex, hippocampus and amygdala were

conducted.

Spatial learning and memory is assessed via MWM (Vicens et al., 2003). The spatial

memory used in MWM is allocentric type, which involves orientation remembrance

in relation to object arrangements in the environment. The hippocampal cholinergic

system plays most prominent role in this type of memory acquisition (Deiana et al.,

2011). Among other neurotransmitter systems Ach is reported to be most important in

the learning and memory of MWM task (Myhrer, 2003). Therefore in this study

MWM task was used to assess cognitive decline in AD mouse model. The results

showed that AD mouse model have longer escape latency time in MWM. Similarly,

in the probe trial, which is a measure of retrieval of learned memory for platform

position (Vicens et al., 2003), lesser time in the target quadrant was spent and less

number of crossings over the platform position were observed in AD mouse model.

Similarly previous studies also report a deficit in spatial memory after Al

administration (Liang et al., 2012, Sethi et al., 2008). Previously, there was no study

that reports the association of Al effect on nicotinic receptor modulation of spatial

memory in MWM. Although nicotine administration had no effect on spatial memory

in normal NMRI mice (Vicens et al., 2003) and female Sprague-Dawley rats (Nott



Disease 114

and Levin, 2006). But antagonism of α4β2 receptor (Fedotova and Frolova, 2013) is

reported to impair spatial memory in MWM. Similarly spatial learning and memory

deficits in MWM were observed in α7 antisense knocked down mouse (Curzon et al.,

2006) and the α7 receptor agonist PNU-282987 enhanced memory and learning in

MWM (Vicens et al., 2011). These studies substantiate that nAChRs are involved in

learning and memory of MWM and the observed deficits in this study during this test

might be due to the observed down-regulation of nicotinic receptor genes resulting

from Al neurotoxicity.

Elevated plus maze test is helpful to assess anxiety in animals (Tejada et al., 2010)

and higher number of entries and more activity in open arm is thought to be an

interpretation of anxiolytic behavior (Anderson and Brunzell, 2012). The present

findings in elevated plus maze revealed that animals treated with Al have higher level

of anxiety as revealed by lesser entries in open arm and less time spent in open arm of

maze. The elevated plus maze is limbic system dependent and the neurons of limbic

system are enriched in β2 containing nicotinic receptors (Grady et al., 2010).

Moreover higher anxiety level was observed in α4 nicotinic acetylcholine receptor

knockout mice (Ross et al., 2000). Therefore the reduced expression of α4 and β2

receptor genes in cortex and hippocampus (as reported in present results) might have

produced anxiogenic effect in AD mouse model. In addition nicotine is known to have

anxiolytic effect in elevated plus maze test (Brioni et al., 1993). This may also

substantiate that absence of nAChRs may lead to increased anxiety.

In open field test grooming activity, exploration and anxiety were measured.

Grooming is an evolutionarily important behavior in all animal taxa but in addition to

being a normal behavior it is also displayed by animals in anxiety because grooming



Disease 115

helps in stress reduction (Terry, 1970). In this study the grooming behavior, in open

field, was evaluated according to the criteria defined by Smolinsky et al., 2009 which

states that grooming in mouse follows cephalocaudal direction and any grooming

activity that does not follow this pattern is due to anxiety (Smolinsky et al., 2009).

Based on this criterion the relaxed and anxious grooming was scored and the results

indicate that the AD mouse model showed more anxious grooming during the first

and last five minutes of 30 minute test duration when compared with the control

animals. It is previously reported that if animals stay in an environment for 30

minutes then the habituation for that environment occurs (Pepeu and Giovannini,

2004). But, high anxious grooming, even during the last five minutes of 30 minute

test period, manifests high anxiety and lesser adaptability to the novel environment as

a result of Al administration. Moreover high relaxed grooming observed in our

experiments in control animals during the last 5 minutes of test duration also manifest

that control animals are better able to adapt to a new environment as compared to AD

mouse model. Higher anxiety in AD mouse model was validated by the observation

that the AD mouse model spent more time in the periphery of test box. The findings

of this study are in accordance to the previously reported high anxiety in open field

after Al treatment (Sethi et al., 2008). Intriguingly, although a higher level of anxiety

was observed in AD mouse model, this high anxiety does not seem to influence

exploratory activity in AD mouse model as these animals maintained high rearing

during the entire test duration. Rearing is a measure of the exploratory behavior in

rodents (Rosana and Marco Antonio Campana, 2012) but with increasing familiarity

of the environment the animals show a reduction in rearing as was observed in control

animals in our experiment. High rearings in AD mouse model observed in our

experiments are contradictory to those observed by Platt et al., who reported no



Disease 116

change in rearing after Al administration (Platt et al., 2001). This difference might be

due to the lack of Al accumulation in cortex in experiments of Platt et al., (Platt et al.,

2001). Moreover in histological examination neurodegeneration in layer 4 of the

barrel field cortex was observed. The specific neuronal arrangement in the form of

barrels in barrel cortex are associated with whiskers (Petersen, 2007), which plays an

important role during exploratory activity (Grant et al., 2014). Therefore in spite of

damage caused by Al in barrel field cortex the preservation of high exploration is

quite intriguing and needs to be further investigated. This preservation of rearing in

AD mouse model might be due to the decreased expression of α4 nAChR in cortex

after Al treatment. As α4 nAChR are required to activate some inhibitory neural

circuits that inhibit some behavioral patterns therefore its absence will result in

elevation of some behavior topographies (Ross et al., 2000) and rearing might be one

of them. Moreover the possibility that locomotor hypoactivity may be interpreted as

higher anxiety could be ruled out from histological examination results of

sensorymotor cortex of hind limb and forelimb region. No significant difference

between the cell number in control and AD mouse model in all these cortical areas

that are associated with locomotion.

The results of the social novelty preference test showed that Al treatment resulted in

impaired social interaction as animals treated with Al preferred to spend more time

sitting in the corner of the test box and showed little interaction with mouse 1 or

empty cage during social interaction trial. Similarly in social novelty preference trial

the AD mouse model spent similar time with mouse 1 and mouse 2 (stranger mouse)

which manifested that Al intoxicated animals could not differentiate the familiar

mouse from strange mouse. The present results are in agreement to the previously



Disease 117

reported lack of sociability in mice intraperitoneally administered with AlCl3 (Hashmi

et al., 2015). Similar low social activity is observed in patients suffering from AD

(Isaev et al., 2015). Therefore Al has the ability to produce some of the symptoms that

are associated with AD and Al intoxicated animals can be used as model for studying

cholinergic system impairment.

The novel object recognition test is widely used for the measurement of memory

alterations (Antunes and Biala, 2012) and cholinergic system is reported to have

important role in object recognition (Kruk-Słomka et al., 2014). Therefore novel

object recognition test (NOR) was done in this study to determine the memory

impairment. The results of NOR showed that control animals had significantly higher

recognition memory, for the novel object, as compared to AD mouse model.

Presentation of a novel object is further useful for the reason that recognition of

novelty necessitates the involvement of more cognitive skills from subject than the

exploration of a novel environment or a single object (Silvers et al., 2007). Moreover

novel object preference also means that familiar object still remains in the animal

memory (Ennaceur, 2010). The NOR is dependent on both cortex and hippocampus,

the most affected brain parts in our experiments, as the lesions in these two brain parts

have impaired activity in NOR (Buckmaster et al., 2004, Clark et al., 2000). The

present results demonstrated that the cholinergic system in cortex and hippocampus

were translated in neurobehavioral functions which manifest memory impairment in

Al induced neurotoxicity. Moreover, it is reported that NOR is dependent on both

nicotinic and muscarinic components of cholinergic system and nicotine

administration increases novel object exploration time in NOR (Kruk-Słomka et al.,



Disease 118

2014) therefore impairment in NOR in our experiments might be due to impaired

nAChR gene expression after Al treatment.

In order to elucidate the neuronal substrates of memory and learning, classical fear

conditioning is a powerful tool (Ehrlich et al., 2009). Although the effect of Al is

previously investigated on passive and active avoidance test (Connor et al., 1988,

Julka et al., 1995, Stevanović et al., 2010) however the studies on its effect on

Pavlovian fear response are very limited. The acquisition and storage of fear memory

is amygdala dependant (Raybuck and Lattal, 2011). Although in this study a reduction

in the gene expression of α4 and α7 nAChRs in amygdala was observed however, it

was also revealed that Al administration has no effect on fear conditioning.

Previously it was reported that in dorsal hippocampus trace fear conditioning, a

hippocampus dependent behavior, is regulated by cholinergic transmission but delay

fear conditioning, amygdala dependent fear conditioning paradigm used in present

experiments, is not dependent on cholinergic transmission (Pang et al., 2010).

Moreover in another study on hippocampus it is reported that nicotine administration

enhances trace fear conditioning but delay fear conditioning remains unaffected

(Gould et al., 2004). In view of reported literature it is deduced that the deficit in

nAChR gene expression in amygdala does not influence delay fear conditioning as

both groups showed similar learning during this testing paradigm, however it needs to

be further investigated. Hippocampus plays a pivotal role in acquisition of contextual

fear memory in Pavlovian fear conditioning (Tinsley et al., 2004). The contextual fear

memory results demonstrate that AD mouse model showed a decreased freezing in the

same context in which conditioning was performed. These findings are in agreement

with the effect observed on active and passive avoidance test (Connor et al., 1988,



Disease 119

Julka et al., 1995). The fact that nicotine administration enhances contextual learning,

which is blocked by nAChR antagonist mecamylamine, (Gould and Wehner, 1999)

manifests that the nAChRs play a very important role in context dependant fear

learning. Moreover the inhibition of β2 nAChRs leads to decreased fear response

(Anderson and Brunzell, 2012) therefore the reduced contextual fear memory

observed in present experiments might be the due to interference of Al in nAChR

expression. The results also showed that the fear extinction is greatly impaired in AD

mouse model as these animals are unable to develop new memories related to fear

extinction. As the cholinergic system plays a vital role in fear extinction (Wilson and

Fadel, 2016) therefore the lack of fear extinction observed in this study might be due

to the nAChR gene expression deficit in amygdala.

The Al exposure is also well documented for its neurotoxic effects on cholinergic

system. It interacts with the cholinergic system causing suppression of cholinergic

receptor expression and disruption of calcium regulation (Kaizer et al., 2005).

Although it is already known that Al exposure causes reduced nicotine binding in rat

brain (Gulya et al., 1990) but its effects on specific nAChR gene expression were not

investigated earlier.

Among several different possible combinations of the nAChRs the α7 and α4β2

receptor subtype combinations are most abundant in the mammalian and rodent brain

(Dani, 2001). Therefore these two receptor combinations were the focus of interest in

this study. The nicotinic receptors are cation channel permeable and especially the

flow of Ca+2

ions is particularly important. The Ca+2

regulated Ach release is of vital

importance in the process of cognition and memory (Wang et al., 2000b). This study

demonstrated that the oral Al administration results in reduced expression of nAChR



Disease 120

genes in all the brain areas investigated in this study i.e. hippocampus, cortex and

amygdala. It is therefore deduced that the reduced gene expression will lead to

reduced expression of the nAChRs in neurons. Similar observations were made by

Gulya et al., who reported a reduced nicotine binding in AD mouse model (Gulya et

al., 1990). It has been reported previously that Al accumulates on DNA containing

component of cell nucleus (Crapper et al., 1980) resulting in reduced expression of

neuronal genes (McLachlan et al., 1989) and nAChRs might be among those genes.

The reduced expression of nAChRs may result in reduced excitation of these

receptors as a result not only the postsynaptic depolarization is affected but also

presynaptic Ca+2

dependent intracellular signaling cascades and neurotransmitter

release (Stevanović et al., 2010). As a result, all these factors will affect cognition and

memory in AD mouse model which may lead to neurobehavioral changes, which

corresponds to those observed in AD patients (Julka et al., 1995).

The effect of Al on activity of ChAT enzyme has been reported by various workers

previously. Therefore, it was aimed to determine whether the Al exposure has any

effect on ChAT gene expression or not, which is not previously reported. There are

controversial reports about the activity of ChAT enzyme in Al induced neurotoxicity.

A few studies reported a decrease in ChAT enzyme activity (Cherroret et al., 1996,

Gulya et al., 1990) while others reported no alteration in ChAT enzyme activity after

Al treatment (Connor et al., 1988, Zhang et al., 2014). These findings indicated that

the expression of ChAT gene was significantly reduced after Al treatment in

hippocampus but remained unaltered in cortex and amygdala. Previously Gulya et al.,

1990 (Gulya et al., 1990) reported a decline in activity of ChAT enzyme in both

hippocampus and cortex. These differences in results in the present study from that of



Disease 121

Gulya et al., 1990 (Gulya et al., 1990) may be due to the reason that they have

measured the activity of ChAT enzyme, while the expression of ChAT gene was

focused in this study. According to present findings, for Al accumulation in the

hippocampus and cortex, more Al accumulated in the hippocampus as compared to

cortex. Therefore, it is assumed that Al affects the activity of enzymes even at lesser

concentrations, whereas at high Al concentrations the expression of genes is also

significantly affected. Therefore higher Al levels in hippocampus affects the ChAT

gene expression along with its effects on ChAT enzyme (as reported by (Gulya et al.,

1990), whereas in the cortex, lower concentration of Al did not affect the ChAT gene

expression, though, a decreasing trend in the expression was evident in the present

study.

After Al ingestion the Al entry in brain via blood brain barrier had already been

established a long time ago (Yokel et al., 1999). The present results also support this

notion as a high Al concentration was found in brain of AD mouse model. Previously

high Al content has been reported in whole brain after oral ingestion of Al (Linardaki

et al., 2012). In present study high Al accumulation, in the hippocampus, was also

observed. An increase in Al content in brain is previously reported following Al

administration (Cherroret et al., 1996, Kaizer et al., 2008, Kumar, 1998) but these

studies did not determine the Al accumulation specifically in hippocampus. Similar

high accumulation of Al in cortex of rats was observed that were orally administered

with Al (Sánchez-Iglesias et al., 2007) however the present observations are in

contradiction to those reported by Doming et al., (Doming et al., 1996). The

difference in present results from that of Doming et al., might be due to the reason

that Doming et al., had studied Al accumulation in brain of aged rats (8 months and



Disease 122

16 months old rats) while the mice used in present experiments were 3 months old. In

old age rats there might be a decline in the retention of Al (Golub et al., 2000) as it is

reported previously that high Al accumulation occurs in brain of 3 months old rats

while 8 and 16 months old rats do not show much Al accumulation in brain (Gómez et

al., 1997). Although the difference in Al accumulation in amygdala of control and AD

mouse model was non-significant but amygdala showed higher Al accumulation as

compared to the cortex. This might be due to the reason that Al exposure results in

glutamate overproduction (Nayak and Chatterjee, 2001), in turn, Al binds to glutamic

acid and forms a stable glutamic acid salt which gets deposited in the brain (Chen et

al., 2013). As amygdala is rich in glutamatergic neurons (Chen et al., 2013),

therefore, Al is likely to accumulate more in amygdala. Moreover, Al is known to

cause depression in animals, as revealed by the present open field results. The number

of neurovascular cells in amygdala increase in response to depression resulting in

impaired blood brain barrier functioning (Rubinow et al., 2016). Therefore, it is

postulated, that in addition to increased accumulation of Al and impaired clearance

from amygdala, it can result in high Al concentration in amygdala.

The results of this study elucidate that there was a decrease in Ach concentration in

cortex and hippocampus while in amygdala the Ach concentration remains unaltered.

The results obtained, for cortex and hippocampus, are in accordance to previously

reported observation (Julka et al., 1995) but in contrary to reported increase in Ach

level observed by (Yellamma et al., 2010) after Al toxicity. The difference in the

present results from Yellamma et al., 2010 might be due to the reason that they had

provided 140 mg/kg of dose for 25 days. As Al is reported to accumulate slowly in

brain (Kumar, 1998), therefore, during treatment time reported by Yellamma et al., Al



Disease 123

might not have accumulated in enough amount to cause a damage to Ach level. While

in this study the dose of 250 mg/kg for 42 days was designed to mimic the Al

accumulation conditions at advanced stages of Al intoxication. AD, for which Al is

considered an etiopathogenic factor, is also characterized by a decrease in the Ach

level (Mayeux and Stern, 2012). The decrease in Ach level results in behavioral

deficits (Pepeu and Giovannini, 2004). It is previously reported that impairment in

acquisition in water maze task (Leanza et al., 1995) was observed following decrease

in Ach level. The impairment observed in our experiments during MWM task might

be the result of observed decrease in Ach level following Al treatment. Similarly, high

Ach release is reported during the recall of spatial memory task that were already

learned (Stancampiano et al., 1999). Therefore during probe trial the decreased Ach

level, after Al administration, might have caused impairment in recall of platform

position in present experiments. Moreover when an animal is placed in an arena with

novel objects there is 150%-200% rise in the Ach level (Giovannini et al., 2001) and

an impairment in acquisition of object discrimination is observed following decrease

in Ach level (Vnek et al., 1996). Therefore the deficits observed in present

experiments during NOR might also be due to the observed decrease in Ach level in

this study.

Interestingly, in spite of the decrease in Ach level the free choline level in the brain

tissues remained unchanged in AD mouse model. This was surprising, as with

previous reports of a decrease in the activity of AChE enzyme after Al treatment

(Brus et al., 1997, Julka et al., 1995, Kaizer et al., 2008) one would expect a rise in

the Ach level and reduced level of free choline. It might be anticipated that the lower

Ach concentration, in spite of normal free choline availability, are either because of



Disease 124

lower reuptake of choline in presynaptic terminal or most probably because of an

impaired synthesis of Ach caused by reduction in expression of ChAT. Therefore,

expression of ChAT gene was measured. Intriguingly, the expression of ChAT gene

reduced only in hippocampus and was not significantly reduced in cortex of AD

mouse model. However, a clear trend for the reduction of ChAT gene expression was

also evident in cortex which caused significant reduction in the levels of Ach in both

cortex and hippocampus. The reduction in the activity of acetyl CoA after Al

exposure has already been reported (Bielarczyk et al., 1998, Jankowska et al., 2000,

Szutowicz et al., 1998) therefore it is assumed that, after Al exposure, reduction in

ChAT gene expression along with previously reported reduction of acetyl-CoA

activity results in a greater reduction in Ach concentration in different brain parts

which may lead to behavioral deficits.

From present results it is speculated that reduction in ChAT expression, following Al

treatment, results in decreased synthesis of Ach followed by a reduction in the

neurotransmitter concentration at synapse. This decreased Ach concentration in

synaptic cleft is insufficient to activate enough cholinergic receptors which are

required for acquisition and/or storage of learning during different behavioral tasks.

This will result in impaired memory and learning in the animals administered with Al.

Moreover, reduced synthesis of Ach might have reduced recycling of choline leading

to an elevation in the choline concentration in synaptic cleft (Fig 5.1).

Histological evaluation of the hippocampus of control and AD mouse model showed a

marked reduction in the cell number in all the subfields of hippocampus i.e. CA1-3

and dentate gyrus. The results obtained are in accordance with the decrease in cell

number in CA1 and CA3 fields of hippocampus after Al administration observed by



Disease 125

Fig 5.1 Proposed mechanism of learning and memory deficits caused by Al due to its cholinotoxicity



Disease 126

Sethi et al., (Sehar et al., 2013). The present results revealed that Al administration

causes neurodegeneration and reduces the cell number in CA2 and dentate gyrus, as

well, in addition to the areas reported by Sethi et al. Buraimoh et al., also reported

similar observations after oral administration of AlCl3 (Buraimoh et al., 2011).

The histological examination of cortex showed a severe neurodegeneration in motor

cortex which is in agreement to the previously observed motor neuron degeneration

by Al administration (Shaw and Petrik, 2009). Although the results obtained in this

study are contradictory to those obtained by Platt et al. who have reported no

histological changes in cortical tissue following Al administration (Platt et al., 2001).

The reason could be that, Platt et al did not observe histological effects of Al on

specific cortex areas, moreover, Al was administered via intra-cerebroventricular

injection, while in this study Al was administered via drinking water which is more

close to the natural route of Al intoxication in humans. Moreover, Platt et al. had

observed Al accumulation in the brain areas that were in immediate vicinity of

injection site which might be the reason that they were unable to observe degenerative

changes caused by Al in cortex.

The results of present study reveal that hippocampus, which plays crucial role in

memory and learning, is the most affected brain region after Al treatment. This is

supported by the fact that hippocampus receives maximum cholinergic innervations

from forebrain (Woolf, 1991). Although there are several studies that report the

degeneration of cholinergic neurons of basal forebrain after Al treatment (Jelenković

et al., 2014, Peng et al., 1992, Stevanović et al., 2011) but the region specific

degeneration is not studied in basal forebrain after Al treatment. As cortex and

amygdala are innervated by cholinergic projections coming from horizontal limb of



Disease 127

diagonal band of basal forebrain while hippocampus receives its cholinergic

innervations from vertical limb of diagonal band (Woolf, 1991). Therefore it can be

speculated that damage caused to the hippocampus, more than other brain parts, might

be due to the damage of selective basal forebrain structures, however this needs to be

further investigated.

Aging and Al are both associated with declined cognition and memory. An age

dependent reduction in in-vitro gamma oscillations (underlying brain activity in

various cognition and memory processes) is observed in mouse hippocampus

(Vreugdenhil and Toescu, 2005). Gamma oscillation patterns in hippocampus are

controlled by GABAergic and cholinergic innervations from medial septum diagonal

band of brocha. These fibers innervate hippocampus in stratum oriens of the CA3 area

(Crutcher et al., 1981). In-vitro gamma oscillations generated pharmacologically by

cholinergic activation via CCh, can be considered akin to activation of septo-

hippocampal cholinergic fibers that are active during oscillatory activity in-vivo.

Therefore, CA3 area was selected for field potential recordings in the present study.

CCh-induced gamma oscillations are known to predominantly depend on mAChR

(Kilb and Luhmann, 2003). However, contribution of nAChRs to the CCh-induced

gamma oscillations has been poorly known (Cobb et al., 1999). Facilitatory effect of

nAChRs is reported in gamma oscillations generated by co-administration of CCh and

mGluR1 receptor agonist (Wang et al., 2014). To the best of my knowledge these

experiments demonstrate for the first time that nAChR activation alone can modulate

gamma oscillations generated by CCh.

The results also showed that peak power of CCh-induced gamma oscillations was

augmented by broad spectrum nAChR agonist nicotine. In these experiments, further



Disease 128

application of antagonists to homomeric α7 and heteromeric α4β2 nAChR showed

that nicotine-mediated facilitation of oscillation peak power was mediated via non-α7

nAChRs. These results are different from previously reported role of α7 nAChRs in

gamma oscillations evoked by tetanic stimulation (Song et al., 2005). This difference

in present results from Song et al. (2005) might be because of different methods used

for generation of gamma oscillations. The effect of α4β2 antagonist observed in this

study is similar to the effects reported earlier in inhibition of α4β2 in CCh-induced

theta oscillations in hippocampus (Cobb et al., 1999, Rushforth, 2013). The results

speak for differences in nAChR-mediated modulation in electrically and

pharmacologically evoked gamma oscillations.

As nicotine-induced facilitation in our experiments was observed to be dependent on

heteromeric non-α7 nAChRs which are found to be preferentially expressed on

hippocampal GABAergic interneurons (Aracri et al., 2010, Bell et al., 2011).

Moreover the nAChR inactivation or desensitization has the same effect on CCh-

induced hippocampal oscillations as produced by GABAA receptor antagonist,

bicuculline, (Cobb et al., 1999, Williams and Kauer, 1997). These studies elucidate

that observed effect on CCh-induced gamma oscillations in present experiments by

non-α7 nAChRs might be mediated particularly via GABAergic inhibitory

interneurons.

Application of Al to hippocampal slices for one hour or three to four hours reduced

the peak power of CCh-induced gamma oscillations. The Al was also observed to

diminish the facilitatory effect of nicotine on gamma oscillation power in slices

incubated with Al for three to four hours. Al is well known for its cholinotoxic effects

through multiple mechanisms, particularly due to decreased binding of nicotine



Disease 129

(Gulya et al., 1990). Moreover the washout of Al, after three to four hours in-vitro

treatment, did not restore CCh-induced gamma oscillation power. The observed effect

might be due to allosteric binding of Al to the nAChRs as reported earlier (Hu et al.,

2007b). Hu et al., (2007) demonstrated that Al potentiated the nicotine-evoked inward

currents in acutely isolated brain slices. The fact that effect of Al on nAChRs was not

mimicked by Ga+3

indicates that the effect was not mediated by surface charge

screening and was specific for Al (Hu et al., 2007b). It is supposed that in three to

four hours incubation with Al, in present experiments, might have caused similar

potentiation of nAChRs leading to receptor desensitization which resulted in

irreversible damage to the gamma oscillation generating hippocampal circuitry. There

is also a possibility that if Al binds to nAChRs or other receptors then this might not

have been completely washed out, leading to a continuous suppression of gamma

oscillations.

This study elucidate that exposure of hippocampal brain slices to Al rapidly

suppressed cholinergic gamma oscillations and their facilitation by nicotine. A few

hour in-vitro exposure to Al caused irreversible suppression in hippocampal

cholinergic gamma oscillations. These results with reduced gamma oscillation power,

after Al exposure, are similar to effects observed in theta oscillations in amyloid β

overproducing transgenic mice Scott, 2012 #212. This suggests that neurotoxicity

caused by Al and amyloid β might have similar toxic effects on brain rhythmic

activity. Therefore subtle changes in gamma rhythm may occur during early stages of

AD and may possibly predict disease initiation Goutagny, 2013 #208.

The hippocampal oscillations are believed to create a permissive environment that

favor the development of long term potentiation (LTP) which is principal cellular



Disease 130

mechanism for acquisition and encoding of learned information Pepeu, 2004 #403.

Therefore the damage to the oscillogenic circuitry after Al administration leads to an

impairment in acquisition of various behavioral tasks. The gamma oscillations are

involved in NOR and impaired performance in recognition of novel object is followed

by reduced gamma oscillations Lee, 2014 #80. Object recognition in NOR is also

reported to be dependent on glutamate vesicle release from astrocytes Lee, 2014

#80. Al induced reduction in recognition of novel object may be, at least partially,

due to its effects on glutamatergic and cholinergic system which are both important

components in gamma oscillations generation. Moreover it is reported that gamma

frequency oscillations are also involved in storing and retrieval of spatial information

Lu, 2011 #408. As tasks involving spatial memory increase synchronization of

gamma oscillations in CA3 area of hippocampus Montgomery, 2007 #409 and

reduced hippocampal gamma oscillations result in impaired spatial reference memory

Fuchs, 2007 #410. Therefore, it is deduced that reduced gamma oscillation power

in CA3 area of hippocampus, as a result of Al incubation, might be the reason for

impaired performance during probe trial and memory acquisition in MWM in this

study. As it is known that the gamma generating capacity in-vitro and in-vivo are

correlated Lu, 2011 #408 therefore it might be inferred that the reduction in gamma

frequency oscillations after in-vitro Al incubation, in present experiments, might be a

useful index for in-vivo gamma oscillation strength. Moreover this reduced gamma

oscillation power might be the underlying reason for behavioral deficits observed

after Al neurotoxicity.


Disease 131

CONCLUSIONS

It is evident from results of this study that after chronic exposure to Al via drinking

water results in high Al accumulates in brain which results in neurodegeneration in

cortex and hippocampus and reduction in nAChRs expression in all the brain parts

investigated. The cholinergic hypofunction caused by Al administration and

neurodegeneration in hippocampus results in impaired memory and elevated anxiety

in hippocampus dependent behaviors (Fig 5.2).

To the best of my knowledge the effect of Al on cortex and amygdala dependent

functions like grooming and fear memory and on hippocampal gamma oscillations

and their nAChR-mediated modulation is presented for the first time in this study.

Moreover, the effect of Al on nAChR gene in cortex and amygdala has also not been

reported earlier. This study demonstrates that chronic Al exposure in drinking water

results in decreased ChAT gene expression. Reduced ChAT expression leads to

decreased Ach synthesis in spite of normal free choline availability. The cholinergic

hypofunction results in neurobehavioral deficits in the form of reduced sociability and

impaired recognition for novel object. The irreversible damage caused to the

hippocampal circuits after longer in-vitro Al treatment is a novel discovery. Al is

considered to be a contributing factor for AD and the Al-induced reduction in gamma

oscillation power might be underlying mechanism for AD like symptoms in living

brain with deficits in memory and learning. Although exact mechanisms of Al effects

reported here are still unknown, and it has multiple targets in gamma oscillation

circuitry, therefore it is proposed that the effects may be because of altered function of


Disease 132

Fig 5.2: Cholinergic hypofunction after Al accumulation investigated in cortex, hippocampus and

amygdala and its implications on behavioral functions


Disease 133

nAChRs on GABAergic inhibitory interneurons but this needs to be further

investigated.

Our data provide conclusive evidence that Al causes neuropathological changes via

interference with cholinergic system. In summary the Al toxicity has important

contribution in onset and to increase severity of neurodegenerative disease. The

findings of the study will help to understand the mechanism through which Al

aggravates the neuropathological changes involved in AD progression. This will help

to develop of appropriate therapeutic interventions for treatment of AD.


Disease 134

FUTURE PROSPECTS

The effect of Al on other neurotransmitter systems which are involved in

memory and learning, i.e glutamatergic and GABAergic, needs to be

investigated

The study of Al effect on gamma oscillations in live animals should be

investigated as it might help to better understand the mechanisms involved in

memory and learning deficits caused by Al.

The effects of Al should be studied in transgenic animals with nicotinic

receptor genes knockout to better understand the cholinotoxicity of Al.


Disease 135

SUGGESTIONS FOR POLICY MAKERS

The results of this study suggested that human exposure to Al should be limited,

which, in addition to avoiding head trauma, will be the only change in lifestyle that

may help to reduce the risk of developing neurodegenerative disorders like AD.

The Al toxicity to human beings need environmentalist's and policy makers special

attention because it can increase risk of neurological disorders. The Al content in

processed food should be mentioned and people should be made aware to limit Al

intake to 3mg or less. Moreover Al concentration in processed water should be

ensured to be less than 50μg/L.

Chapter 6 References


Disease 136

REFERENCES

Abd-Elhady, R. M., Elsheikh, A. M. and Khalifa, A. E. (2013). Anti-amnestic

properties of Ginkgo biloba extract on impaired memory function induced by

aluminum in rats. International Journal of Developmental Neuroscience, 31

(7): 598-607.

Ahmed, T., Enam, S. and Gilani, A. (2010). Curcuminoids enhance memory in an

amyloid-infused rat model of Alzheimer's disease. Neuroscience, 169 (3):

1296-1306.

Akkurt, D., Akay, Y. M. and Akay, M. Year. Investigating the effects of nicotine on

hippocampal oscillations in rats. In: Neural Engineering, 2009. NER'09. 4th

International IEEE/EMBS Conference on, 2009. IEEE, 147-150.

Akkurt, D., Akay, Y. M. and Akay, M. (2010). Research Investigating the

synchronization of hippocampal neural network in response to acute nicotine

exposure. J Neuroeng Rehabil, 7: 31.

Alfrey, A. C., Legendre, G. R. and Kaehny, W. D. (1976). The dialysis

encephalopathy syndrome: possible aluminum intoxication. New England

Journal of Medicine, 294 (4): 184-188.

Anderson, S. M. and Brunzell, D. H. (2012). Low dose nicotine and antagonism of

β2 subunit containing nicotinic acetylcholine receptors have similar effects on

affective behavior in mice. PloS one, 7 (11): e48665.

Antunes, M. and Biala, G. (2012). The novel object recognition memory:

neurobiology, test procedure, and its modifications. Cognitive processing, 13

(2): 93-110.



Disease 137

Aracri, P., Consonni, S., Morini, R., Perrella, M., Rodighiero, S., Amadeo, A. and

Becchetti, A. (2010). Tonic modulation of GABA release by nicotinic

acetylcholine receptors in layer V of the murine prefrontal cortex. Cerebral

Cortex, 20 (7): 1539-1555.

Arendash, G. W., Lewis, J., Leighty, R. E., Mcgowan, E., Cracchiolo, J. R., Hutton,

M. and Garcia, M. F. (2004). Multi-metric behavioral comparison of APPsw

and P301L models for Alzheimer's disease: linkage of poorer cognitive

performance to tau pathology in forebrain. Brain research, 1012 (1): 29-41.

Aziz, J. (2005). Management of source and drinking-water quality in Pakistan.

Aziz, J. A. Year. Drinking water quality in Punjab. In: Proceedings of the 68th

annual session of the Pakistan Engineering Congress, 2001. 241-9.

Balgoon, M. J., Raouf, G. A., Qusti, S. Y. and Ali, S. S. (2015). ATR-IR Study of the

Mechanism of Aluminum Chloride Induced Alzheimer’s Disease; Curative

and Protective Effect of Lipidium sativum Water Extract on Hippocampus

Rats Brain Tissue. World Academy of Science, Engineering and Technology,

International Journal of Medical, Health, Biomedical, Bioengineering and

Pharmaceutical Engineering, 9 (11): 782-792.

Banerjee, C., Nyengaard, J. R., Wevers, A., De Vos, R. A., Jansen Steur, E. N.,

Lindstrom, J., Pilz, K., Nowacki, S., Bloch, W. and Schröder, H. (2000).

Cellular expression of α7 nicotinic acetylcholine receptor protein in the

temporal cortex in Alzheimer's and Parkinson's disease—a stereological

approach. Neurobiology of Disease, 7 (6): 666-672.

Bassioni, G., Mohammed, F. S., Al Zubaidy, E. and Kobrsi, I. (2012). Risk

assessment of using aluminum foil in food preparation. Int. J. Electrochem.

Sci, 7 (5): 4498-4509.



Disease 138

Bednar, I., Paterson, D., Marutle, A., Pham, T. M., Svedberg, M., Hellstrom-Lindahl,

E., Mousavi, M., Court, J., Morris, C., Perry, E., Mohammed, A., Zhang, X.

and Nordberg, A. (2002). Selective nicotinic receptor consequences in

APP(SWE) transgenic mice. Molecular and Cellular Neuroscience, 20 (2):

354-365.

Bell, K. A., Shim, H., Chen, C.-K. and Mcquiston, A. R. (2011). Nicotinic excitatory

postsynaptic potentials in hippocampal CA1 interneurons are predominantly

mediated by nicotinic receptors that contain α4 and β2 subunits.

Neuropharmacology, 61 (8): 1379-1388.

Bhutta, M., Chaudhry, M. and Chaudhry, A. Year. Groundwater quality and

availability in Pakistan. In: Proceedings of the seminar on strategies to

address the present and future water quality issues, 2005.

Bielarczyk, H., Tomaszewicz, M. and Szutowicz, A. (1998). Effect of Aluminum on

Acetyl‐CoA and Acetylcholine Metabolism in Nerve Terminals. Journal of

Neurochemistry, 70 (3): 1175-1181.

Bitra, V. R., Rapaka, D., Mathala, N. and Akula, A. (2014). Effect of wheat grass

powder on aluminum induced Alzheimer's disease in Wistar rats. Asian

Pacific journal of tropical medicine, 7: S278-S281.

Blanchard, R. J. and Blanchard, D. C. (1969). Crouching as an index of fear. Journal

of comparative and physiological psychology, 67 (3): 370.

Brioni, J. D., O'neill, A. B., Kim, D. J. and Decker, M. W. (1993). Nicotinic receptor

agonists exhibit anxiolytic-like effects on the elevated plus-maze test.

European journal of pharmacology, 238 (1): 1-8.



Disease 139

Bromley-Brits, K., Deng, Y. and Song, W. (2011). Morris water maze test for

learning and memory deficits in Alzheimer's disease model mice. Journal of

visualized experiments: JoVE, (53).

Brus, R., Szkilnik, R., Popieluch, I., Kostrzewa, R. M. and Mengel, K. (1997). Effect

of aluminium exposure on central serotonine and muscarine receptors

reactivity in rats. Medical Science Monitor, 3 (5): BR631-BR636.

Buckmaster, C. A., Eichenbaum, H., Amaral, D. G., Suzuki, W. A. and Rapp, P. R.

(2004). Entorhinal cortex lesions disrupt the relational organization of memory

in monkeys. The Journal of Neuroscience, 24 (44): 9811-9825.

Buraimoh, A., Ojo, S., Hambolu, J. and Adebisi, S. (2011). Effects of oral

administration of aluminium chloride on the histology of the hippocampus of

wistar rats. Current Research Journal of Biological Sciences, 3 (5): 509-515.

Burghaus, L., Schutz, U., Krempel, U., De Vos, R. A. I., Steur, E. N. H. J., Wevers,

A., Lindstrom, J. and Schroder, H. (2000). Quantitative assessment of

nicotinic acetylcholine receptor proteins in the cerebral cortex of Alzheimer

patients. Molecular Brain Research, 76 (2): 385-388.

Campbell, A., Becaria, A., Lahiri, D., Sharman, K. and Bondy, S. (2004). Chronic

exposure to aluminum in drinking water increases inflammatory parameters

selectively in the brain. Journal of neuroscience research, 75 (4): 565-572.

Chen, S.-M., Fan, C.-C., Chiue, M.-S., Chou, C., Chen, J.-H. and Hseu, R.-S. (2013).

Hemodynamic and neuropathological analysis in rats with aluminum

trichloride-induced Alzheimer's disease. PloS one, 8 (12): e82561.

Cherroret, G., Desor, D., Hutin, M., Burnel, D., Capolaghi, B. and Lehr, P. (1996).

Effects of aluminum chloride on normal and uremic adult male rats. Biological

trace element research, 54 (1): 43-53.



Disease 140

Christensen, D. D. (2007). Alzheimer's disease: progress in the development of anti-

amyloid disease-modifying therapies. CNS spectrums, 12 (2): 113-123.

Clark, R. E., Zola, S. M. and Squire, L. R. (2000). Impaired recognition memory in

rats after damage to the hippocampus. The Journal of Neuroscience, 20 (23):

8853-8860.

Cleary, J. P., Walsh, D. M., Hofmeister, J. J., Shankar, G. M., Kuskowski, M. A.,

Selkoe, D. J. and Ashe, K. H. (2004). Natural oligomers of the amyloid-β

protein specifically disrupt cognitive function. Nature neuroscience, 8 (1): 79-

84.

Cobb, S. R., Bulters, D. O., Suchak, S., Riedel, G., Morris, R. G. and Davies, C. H.

(1999). Activation of nicotinic acetylcholine receptors patterns network

activity in the rodent hippocampus. The Journal of physiology, 518 (1): 131-

140.

Commissaris, R., Cordon, J., Sprague, S., Keiser, J., Mayor, G. and Rech, R. (1982).

Behavioral changes in rats after chronic aluminum and parathyroid hormone

administration. Neurobehavioral Toxicology and Teratology, 4 (3): 403.

Connor, D. J., Jope, R. S. and Harrell, L. E. (1988). Chronic, oral aluminum

administration to rats: cognition and cholinergic parameters. Pharmacology

Biochemistry and Behavior, 31 (2): 467-474.

Counts, S. E., He, B., Che, S., Ikonomovic, M. D., Dekosky, S. T., Ginsberg, S. D.

and Mufson, E. J. (2007). α7 nicotinic receptor up-regulation in cholinergic

basal forebrain neurons in alzheimer disease. Archives of neurology, 64 (12):

1771-1776.

Crapper, D., Quittkat, S., Krishnan, S., Dalton, A. and De Boni, U. (1980).

Intranuclear aluminum content in Alzheimer's disease, dialysis



Disease 141

encephalopathy, and experimental aluminum encephalopathy. Acta

Neuropathologica, 50 (1): 19-24.

Crutcher, K., Madison, R. and Davis, J. (1981). A study of the rat septohippocampal

pathway using anterograde transport of horseradish peroxidase. Neuroscience,

6 (10): 1961-1973.

Curzon, P., Anderson, D. J., Nikkel, A. L., Fox, G. B., Gopalakrishnan, M., Decker,

M. W. and Bitner, R. S. (2006). Antisense knockdown of the rat α7 nicotinic

acetylcholine receptor produces spatial memory impairment. Neuroscience

letters, 410 (1): 15-19.

Dani, J. A. (2001). Overview of nicotinic receptors and their roles in the central

nervous system. Biological Psychiatry, 49 (3): 166-174.

Dani, J. A. and Bertrand, D. (2007). Nicotinic acetylcholine receptors and nicotinic

cholinergic mechanisms of the central nervous system. Annu. Rev. Pharmacol.

Toxicol., 47: 699-729.

Dave, K. R., Syal, A. R. and Katyare, S. S. (2002). Effect of long-term aluminum

feeding on kinetics attributes of tissue cholinesterases. Brain Research

Bulletin, 58 (2): 225-233.

Deiana, S., Platt, B. and Riedel, G. (2011). The cholinergic system and spatial

learning. Behavioural Brain Research, 221 (2): 389-411.

Dineley, K. T. (2006). Beta-amyloid peptide--nicotinic acetylcholine receptor

interaction: the two faces of health and disease. Frontiers in bioscience: a

journal and virtual library, 12: 5030-5038.

Dineley, K. T., Westerman, M., Bui, D., Bell, K., Ashe, K. H. and Sweatt, J. D.

(2001). beta-amyloid activates the mitogen-activated protein kinase cascade

via hippocampal alpha 7 nicotinic acetylcholine receptors: In vitro and in vivo



Disease 142

mechanisms related to Alzheimer's disease. Journal of Neuroscience, 21 (12):

4125-4133.

Djebli, N. and Rebai, O. (2010). Neurotoxic effect of aluminium exploratory

behaviors and spatial learning in mice. Movement Disorders, 25: S400.

Doming, J., Llorens, J., Sanchez, D., Gomez, M., Llobet, J. and Corbella, J. (1996).

Age-related effects of aluminum ingestion on brain aluminum accumulation

and behavior in rats. Life sciences, 58 (17): 1387-1395.

Edwardson, J. A., Candy, J. M., Ince, P. G., Mcarthur, F. K., Morris, C. M., Oakley,

A. E., Taylor, G. A. and Bjertness, E. (1992). Aluminum Accumulation, Beta-

Amyloid Deposition and Neurofibrillary Changes in the Central-Nervous-

System. Ciba Foundation Symposia, 169: 165-185.

Ehrlich, I., Humeau, Y., Grenier, F., Ciocchi, S., Herry, C. and Lüthi, A. (2009).

Amygdala inhibitory circuits and the control of fear memory. Neuron, 62 (6):

757-771.

Elinder, C.-G., Ahrengart, L., Lidums, V., Pettersson, E. and Sjögren, B. (1991).

Evidence of aluminium accumulation in aluminium welders. British Journal of

Industrial Medicine, 48 (11): 735-738.

Ennaceur, A. (2010). One-trial object recognition in rats and mice: methodological

and theoretical issues. Behavioural Brain Research, 215 (2): 244-254.

Exley, C. (1999). A molecular mechanism of aluminium-induced Alzheimer's

disease? Journal of inorganic biochemistry, 76 (2): 133-140.

Exley, C. and Esiri, M. (2006). Severe cerebral congophilic angiopathy coincident

with increased brain aluminium in a resident of Camelford, Cornwall, UK.

Journal of Neurology, Neurosurgery and Psychiatry, 77 (7): 877-879.



Disease 143

Fabian-Fine, R., Skehel, P., Errington, M. L., Davies, H. A., Sher, E., Stewart, M. G.

and Fine, A. (2001). Ultrastructural distribution of the α7 nicotinic

acetylcholine receptor subunit in rat hippocampus. The Journal of

Neuroscience, 21 (20): 7993-8003.

Fedotova, I. and Frolova, H. (2013). [Effect of alpha4beta2 nicotinic acetylcholine

receptor agonists and antagonists on learning in female rats during different

phases of ovary cycle]. Fiziolohichnyi zhurnal (Kiev, Ukraine: 1994), 60 (4):

80-86.

Ferreira, P. C., Piai, K. D. A., Takayanagui, A. M. M. and Segura-Muñoz, S. I.

(2008). Aluminum as a risk factor for Alzheimer's disease. Revista latino-

americana de enfermagem, 16 (1): 151-157.

Fisahn, A., Pike, F. G., Buhl, E. H. and Paulsen, O. (1998). Cholinergic induction of

network oscillations at 40 Hz in the hippocampus in vitro. Nature, 394 (6689):

186-189.

Flaten, T. P. (2001). Aluminium as a risk factor in Alzheimer’s disease, with

emphasis on drinking water. Brain Research Bulletin, 55 (2): 187-196.

Gage, G. J., Kipke, D. R. and Shain, W. (2012). Whole animal perfusion fixation for

rodents. Journal of visualized experiments: JoVE, (65).

Giovannini, M., Rakovska, A., Benton, R., Pazzagli, M., Bianchi, L. and Pepeu, G.

(2001). Effects of novelty and habituation on acetylcholine, GABA, and

glutamate release from the frontal cortex and hippocampus of freely moving

rats. Neuroscience, 106 (1): 43-53.

Golub, M. S., Donald, J. M., Gershwin, M. E. and Keen, C. L. (1989). Effects of

aluminum ingestion on spontaneous motor activity of mice. Neurotoxicology

and Teratology, 11 (3): 231-235.



Disease 144

Golub, M. S., Germann, S. L., Han, B. and Keen, C. L. (2000). Lifelong feeding of a

high aluminum diet to mice. Toxicology, 150 (1): 107-117.

Gómez, M., Sánchez, D. J., Llobet, J. M., Corbella, J. and Domingo, J. (1997). The

effect of age on aluminum retention in rats. Toxicology, 116 (1): 1-8.

Gould, T. J., Feiro, O. and Moore, D. (2004). Nicotine enhances trace cued fear

conditioning but not delay cued fear conditioning in C57BL/6 mice.

Behavioural Brain Research, 155 (1): 167-173.

Gould, T. J. and Wehner, J. M. (1999). Nicotine enhancement of contextual fear

conditioning. Behavioural Brain Research, 102 (1): 31-39.

Goutagny, R. and Krantic, S. (2013). Hippocampal Oscillatory Activity in

Alzheimer’s Disease: Toward the Identification of Early Biomarkers? Aging

and disease, 4 (3): 134.

Grady, S. R., Drenan, R. M., Breining, S. R., Yohannes, D., Wageman, C. R.,

Fedorov, N. B., Mckinney, S., Whiteaker, P., Bencherif, M. and Lester, H. A.

(2010). Structural differences determine the relative selectivity of nicotinic

compounds for native α4β2*-, α6β2*-, α3β4*-and α7-nicotine acetylcholine

receptors. Neuropharmacology, 58 (7): 1054-1066.

Grammas, P. and Caspers, M. (1991). The effect of aluminum on muscarinic

receptors in isolated cerebral microvessels. Research communications in

chemical pathology and pharmacology, 72 (1): 69-79.

Grant, R., Itskov, P. M., Towal, B. and Prescott, T. J. (2014). Active touch sensing:

finger tips, whiskers, and antennae. Frontiers in behavioral neuroscience, 8:

50.

Gray, C. M. (1994). Synchronous oscillations in neuronal systems: mechanisms and

functions. Journal of computational neuroscience, 1 (1-2): 11-38.



Disease 145

Gu, Z. and Yakel, J. L. (2011). Timing-dependent septal cholinergic induction of

dynamic hippocampal synaptic plasticity. Neuron, 71 (1): 155-165.

Gulya, K., Rakonczay, Z. and Kasa, P. (1990). Cholinotoxic effects of aluminum in

rat brain. Journal of neurochemistry, 54 (3): 1020-1026.

Guo, J. Z. and Chiappinelli, V. A. (1999). Muscarinic receptors mediate enhancement

of spontaneous GABA release in the chick brain. Neuroscience, 95 (1): 273-

282.

Guy, S. P., Jones, D., Mann, D. M. and Itzhaki, R. F. (1991). Human neuroblastoma

cells treated with aluminium express an epitope associated with Alzheimer's

disease neurofibrillary tangles. Neuroscience Letters, 121 (1-2): 166-168.

Harkany, T., Lengyel, Z., Kasa, P. and Gulya, K. (1995). Chronic aluminum

treatment results in aluminum deposits and affects Ml muscarinic receptors in

rat brain. Neurobiology (Budapest, Hungary), 4 (1-2): 35-43.

Hashimoto, M., Hossain, S., Shimada, T., Sugioka, K., Yamasaki, H., Fujii, Y.,

Ishibashi, Y., Oka, J. I. and Shido, O. (2002). Docosahexaenoic acid provides

protection from impairment of learning ability in Alzheimer's disease model

rats. Journal of Neurochemistry, 81 (5): 1084-1091.

Hashmi, A. N., Yaqinuddin, A. and Ahmed, T. (2015). Pharmacological effects of

Ibuprofen on learning and memory, muscarinic receptors gene expression and

APP isoforms level in pre-frontal cortex of AlCl3-induced toxicity mouse

model. International Journal of Neuroscience, 125 (4): 277-287.

He, X., Zhong, Z. and Che, Y. (2012). Locomotor activity and learning and memory

abilities in Alzheimer's disease induced by aluminum in an acid environment

in zebrafish. Dong wu xue yan jiu= Zoological research, 33 (2): 231-236.

Disease 146

Hellstrom-Lindahl, E., Mousavi, M., Zhang, X., Ravid, R. and Nordberg, A. (1999).

Regional distribution of nicotinic receptor subunit mRNAs in human brain:

comparison between Alzheimer and normal brain. Molecular Brain Research,

66 (1-2): 94-103.

Hernandez, C. M. and Dineley, K. T. (2012). α7 nicotinic acetylcholine receptors in

Alzheimer's disease: neuroprotective, neurotrophic or both? Curr Drug

Targets., 13 (5): 613-622.

Hetnarski, B., Wisniewski, H. M., Iqbal, K., Dziedzic, J. D. and Lajtha, A. (1980).

Central Cholinergic Activity in Aluminum-Induced Neurofibrillary

Degeneration. Annals of Neurology, 7 (5): 489-490.

Hu, M., Schurdak, M. E., Puttfarcken, P. S., El Kouhen, R., Gopalakrishnan, M. and

Li, J. (2007a). High content screen microscopy analysis of Aβ 1–

42-induced neurite outgrowth reduction in rat primary cortical neurons:

Neuroprotective effects of α7 neuronal nicotinic acetylcholine receptor

ligands. Brain research, 1151: 227-235.

Hu, W.-P., Li, X.-M., Chen, J.-G. and Li, Z.-W. (2007b). Potentiation of the nicotinic

acetylcholine receptor by aluminum in mammalian neurons. Neuroscience,

149 (1): 1-6.

Hutton, M. and Hardy, J. (1997). The presenilins and Alzheimer's disease. Human

Molecular Genetics, 6 (10): 1639-1646.

Iqbal, G., Iqbal, A., Mahboob, A., M Farhat, S. and Ahmed, T. (2016). Memory

Enhancing Effect of Black Pepper in the AlCl3 Induced Neurotoxicity Mouse

Model is Mediated Through Its Active Component Chavicine. Current

pharmaceutical biotechnology, 17 (11): 962-973.



Disease 147

Isaev, N., Stelmashook, E., Genrikhs, E., Oborina, M., Kapkaeva, M. and Skulachev,

V. (2015). Alzheimer’s disease: An exacerbation of senile phenoptosis.

Biochemistry (Moscow), 80 (12): 1578-1581.

Itier, V. and Bertrand, D. (2001). Neuronal nicotinic receptors: from protein structure

to function. FEBS Letters, 504 (3): 118-125.

Jalbani, N., Kazi, T. G., Jamali, M. K., Arain, B. M., Afridi, H. I. and Baloch, A.

(2007). Evaluation of aluminum contents in different bakery foods by

electrothermal atomic absorption spectrometer. Journal of Food Composition

and Analysis, 20 (3): 226-231.

Jankowska, A., Madziar, B., Tomaszewicz, M. and Szutowicz, A. (2000). Acute and

chronic effects of aluminum on acetyl‐CoA and acetylcholine metabolism in

differentiated and nondifferentiated SN56 cholinergic cells. Journal of

Neuroscience Research, 62 (4): 615-622.

Jelenković, A., Jovanović, M. D., Stevanović, I., Petronijević, N., Bokonjić, D.,

Živković, J. and Igić, R. (2014). Influence of the green tea leaf extract on

neurotoxicity of aluminium chloride in rats. Phytotherapy Research, 28 (1):

82-87.

Johnson, G. V. and Jope, R. S. (1986). Aluminum impairs glucose utilization and

cholinergic activity in rat brain in vitro. Toxicology, 40 (1): 93-102.

Jones, A. D., Westmacott, A., Chan, E., Jones, A. D., Dineley, K., O’neill, M. J. and

Wonnacott, S. (2006a). α 7 Nicotinic Acetylcholine Receptor Expression in

Alzheimer’s disease Receptor Densities in Brain Regions of the APP (SWE)

Mouse Model and in Human Peripheral Blood Lymphocytes. Journal of

Molecular Neuroscience, 30: 83-84.



Disease 148

Jones, I. W., Westmacott, A., Chan, E., Jones, R. W., Dineley, K., O'neill, M. J. and

Wonnacott, S. (2006b). α7 nicotinic acetylcholine receptor expression in

Alzheimer's disease. Journal of Molecular Neuroscience, 30 (1): 83-84.

Julka, D., Sandhir, R. and Gill, K. D. (1995). Altered cholinergic metabolism in rat

CNS following aluminum exposure: implications on learning performance.

Journal of neurochemistry, 65 (5): 2157-2164.

Kahlown, M., Tahir, M. and Ashraf, M. Year. Water quality issues and status in

Pakistan. In: Proceedings of the seminar on strategies to address the present

and future water quality issues, 2005.

Kaizer, R., Correa, M., Gris, L., Da Rosa, C., Bohrer, D., Morsch, V. and Schetinger,

M. R. C. (2008). Effect of long-term exposure to aluminum on the

acetylcholinesterase activity in the central nervous system and erythrocytes.

Neurochemical research, 33 (11): 2294-2301.

Kaizer, R. R., Corrêa, M. C., Spanevello, R. M., Morsch, V. M., Mazzanti, C. M.,

Gonçalves, J. F. and Schetinger, M. R. (2005). Acetylcholinesterase

activation and enhanced lipid peroxidation after long-term exposure to low

levels of aluminum on different mouse brain regions. Journal of inorganic

biochemistry, 99 (9): 1865-1870.

Kamimura, K., Tanahashi, H., Yamanaka, H., Takahashi, K., Asada, T. and Tabira,

T. (1998). Familial Alzheimer's disease genes in Japanese. Journal of the

Neurological Sciences, 160 (1): 76-81.

Kawahara, M. and Kato-Negishi, M. (2011). Link between aluminum and the

pathogenesis of Alzheimer's disease: the integration of the aluminum and

amyloid cascade hypotheses. International Journal of Alzheimer’s Disease,

2011.



Disease 149

Kawahara, M., Kato, M. and Kuroda, Y. (2001). Effects of aluminum on the

neurotoxicity of primary cultured neurons and on the aggregation of β-amyloid

protein. Brain Research Bulletin, 55 (2): 211-217.

Kazi, T. G., Afridi, H. I., Jamali, M. K., Arain, M. B., Jalbani, N. and Syed, N.

(2007). Evaluation of zinc status in whole blood and scalp hair of female

cancer patients. Clinica Chimica Acta, 379 (1): 66-70.

Khan, N., Hussain, T., Hussain, J., Jamila, N., Ahmed, S., Ullah, R., Ullah, Z. and

Saboor, A. (2012). Physiochemical evaluation of the drinking water sources

from district Kohat, Khyber Pakhtunkhwa, Pakistan. Afr. J. Pharm.

Phamacol.(Accepted for Publication).

Kilb, W. and Luhmann, H. J. (2003). Carbachol-induced network oscillations in the

intact cerebral cortex of the newborn rat. Cerebral Cortex, 13 (4): 409-421.

Krewski, D., Yokel, R. A., Nieboer, E., Borchelt, D., Cohen, J., Harry, J., Kacew, S.,

Lindsay, J., Mahfouz, A. M. and Rondeau, V. (2007). Human health risk

assessment for aluminium, aluminium oxide, and aluminium hydroxide.

Journal of Toxicology and Environmental Health, Part B, 10 (S1): 1-269.

Kruk-Słomka, M., Michalak, A., Budzyńska, B. and Biała, G. (2014). A comparison

of mecamylamine and bupropion effects on memory-related responses induced

by nicotine and scopolamine in the novel object recognition test in mice.

Pharmacological Reports, 66 (4): 638-646.

Kumar, S. (1998). Biphasic effect of aluminium on cholinergic enzyme of rat brain.

Neuroscience letters, 248 (2): 121-123.

Lakshmi, B., Sudhakar, M. and Prakash, K. S. (2015). Protective effect of selenium

against aluminum chloride-induced Alzheimer’s disease: behavioral and



Disease 150

biochemical alterations in rats. Biological Trace Element Research, 165 (1):

67-74.

Lamsa, K. P., Heeroma, J. H., Somogyi, P., Rusakov, D. A. and Kullmann, D. M.

(2007). Anti-Hebbian long-term potentiation in the hippocampal feedback

inhibitory circuit. Science, 315 (5816): 1262-1266.

Leanza, G., Nilsson, O., Wiley, R. and Björklund, A. (1995). Selective Lesioning of

the Basal Forebrain Cholinergic System by Intraventricular 192 IgG–saporin:

Behavioural, Biochemical and Stereological Studies in the Rat. European

Journal of Neuroscience, 7 (2): 329-343.

Lee, H. S., Ghetti, A., Pinto-Duarte, A., Wang, X., Dziewczapolski, G., Galimi, F.,

Huitron-Resendiz, S., Piña-Crespo, J. C., Roberts, A. J. and Verma, I. M.

(2014). Astrocytes contribute to gamma oscillations and recognition memory.

Proceedings of the National Academy of Sciences, 111 (32): E3343-E3352.

Lee, J., Durst, R. and Wrolstad, R. (2002). 4 but not 3 and 7 nicotinic acetylcholine

receptor subunits are lost from the temporal cortex in alzheimer's disease.

Journal of neurochemistry.

Lee, S., Ahmed, T., Lee, S., Kim, H., Choi, S., Kim, D.-S., Kim, S. J., Cho, J. and

Shin, H.-S. (2012). Bidirectional modulation of fear extinction by mediodorsal

thalamic firing in mice. Nature Neuroscience, 15 (2): 308-314.

Liang, R.-F., Li, W.-Q., Wang, X.-H., Zhang, H.-F., Wang, H., Wang, J.-X., Zhang,

Y., Wan, M.-T., Pan, B.-L. and Niu, Q. (2012). Aluminium-maltolate-induced

impairment of learning, memory and hippocampal long-term potentiation in

rats. Industrial health, 50 (5): 428-436.

Disease 151

Lin, W.-T., Chen, R.-C., Lu, W.-W., Liu, S.-H. and Yang, F.-Y. (2015). Protective

effects of low-intensity pulsed ultrasound on aluminum-induced cerebral

damage in Alzheimer's disease rat model. Scientific reports, 5.

Linardaki, Z. I., Orkoula, M. G., Kokkosis, A. G., Lamari, F. N. and Margarity, M.

(2012). Investigation of the neuroprotective action of saffron ( Crocus

sativus L.) in aluminium-exposed adult mice through behavioral and

neurobiochemical assessment. Food and Chemical Toxicology.

Liu, Y., Hu, J., Wu, J., Zhu, C., Hui, Y., Han, Y., Huang, Z., Ellsworth, K. and Fan,

W. (2012a). α7 nicotinic acetylcholine receptor-mediated neuroprotection

against dopaminergic neuron loss in an MPTP mouse model via inhibition of

astrocyte activation. Journal of neuroinflammation, 9 (1): 98.

Liu, Y., Hu, J., Wu, J., Zhu, C., Hui, Y., Han, Y., Huang, Z., Ellsworth, K. and Fan,

W. (2012b). α7 nicotinic acetylcholine receptor-mediated neuroprotection

against dopaminergic neuron loss in an MPTP mouse model via inhibition of

astrocyte activation. J Neuroinflammation, 9 (98): 2094-9.

Lu, C. and Henderson, Z. (2010). Nicotine induction of theta frequency oscillations

in rodent hippocampus in vitro. Neuroscience, 166 (1): 84-93.

Lu, C. B., Jefferys, J. G., Toescu, E. C. and Vreugdenhil, M. (2011). In vitro

hippocampal gamma oscillation power as an index of in vivo CA3 gamma

oscillation strength and spatial reference memory. Neurobiology of Learning

and Memory, 95 (3): 221-230.

Lucas-Meunier, E., Fossier, P., Baux, G. and Amar, M. (2003). Cholinergic

modulation of the cortical neuronal network. Pflügers Archiv, 446 (1): 17-29.

Luo, J.-H., Qiu, Z.-Q., Shu, W.-Q., Zhang, Y.-Y., Zhang, L. and Chen, J.-A. (2009).

Effects of arsenic exposure from drinking water on spatial memory, ultra-



Disease 152

structures and NMDAR gene expression of hippocampus in rats. Toxicology

Letters, 184 (2): 121-125.

Maheswari, S., Venkatakrishna Murali, R. and Balaji, R. (2014). Aluminium induced

cholinotoxicity in zebra fish brain-A sequel of oxidative stress. Int J Adv Res,

2: 322-335.

Mayeux, R. and Stern, Y. (2012). Epidemiology of Alzheimer disease. Cold Spring

Harbor perspectives in medicine, 2 (8): a006239.

Mclachlan, D., Kruck, T. P., Lukiw, W. J. and Krishnan, S. S. (1991). Would

decreased aluminum ingestion reduce the incidence of Alzheimer's disease?

CMAJ: Canadian Medical Association Journal, 145 (7): 793.

Mclachlan, D. C., Lukiw, W. and Kruck, T. (1989). New evidence for an active role

of aluminum in Alzheimer's disease. Canadian Journal of Neurological

Sciences/Journal Canadien des Sciences Neurologiques, 16 (S4): 490-497.

Memon, M., Soomro, M. S., Akhtar, M. S. and Memon, K. S. (2011). Drinking water

quality assessment in Southern Sindh (Pakistan). Environmental monitoring

and assessment, 177 (1-4): 39-50.

Miu, A. C. and Benga, O. (2006). Aluminum and Alzheimer's disease: a new look.

Journal of Alzheimer's disease, 10 (2, 3): 179-201.

Montgomery, S. M. and Buzsáki, G. (2007). Gamma oscillations dynamically couple

hippocampal CA3 and CA1 regions during memory task performance.

Proceedings of the National Academy of Sciences, 104 (36): 14495-14500.

Myhrer, T. (2003). Neurotransmitter systems involved in learning and memory in the

rat: a meta-analysis based on studies of four behavioral tasks. Brain Research

Reviews, 41 (2): 268-287.



Disease 153

Nagele, R. G., D’andrea, M. R., Lee, H., Venkataraman, V. and Wang, H.-Y. (2003).

Astrocytes accumulate Aβ42 and give rise to astrocytic amyloid plaques in

Alzheimer disease brains. Brain research, 971 (2): 197-209.

Nathalie, P. and Jean-Noel, O. (2008). Processing of amyloid precursor protein and

amyloid peptide neurotoxicity. Current Alzheimer Research, 5 (2): 92-99.

Nayak, P. and Chatterjee, A. (2001). Effects of aluminium exposure on brain

glutamate and GABA systems: an experimental study in rats. Food and

Chemical Toxicology, 39 (12): 1285-1289.

Nott, A. and Levin, E. D. (2006). Dorsal hippocampal α7 and α4β2 nicotinic

receptors and memory. Brain research, 1081 (1): 72-78.

Palmer, A. M. (2002). Pharmacotherapy for Alzheimer's disease: progress and

prospects. Trends in Pharmacological Sciences, 23 (9): 426-433.

Pandey, P., Singh, M. and Gambhir, I. (2011). Alzheimer's disease: A Threat to

mankind. Journal of Stress Physiology & Biochemistry, 7 (4).

Pandya, A. and Yakel, J. L. (2011). Allosteric modulator desformylflustrabromine

relieves the inhibition of α2β2 and α4β2 nicotinic acetylcholine receptors by

β-Amyloid1–42 peptide. Journal of Molecular Neuroscience, 45 (1): 42-47.

Pang, M.-H., Kim, N.-S., Kim, I.-H., Kim, H., Kim, H.-T. and Choi, J.-S. (2010).

Cholinergic transmission in the dorsal hippocampus modulates trace but not

delay fear conditioning. Neurobiology of Learning and Memory, 94 (2): 206-

213.

Parri, H. R., Hernandez, C. M. and Dineley, K. T. (2011). Research update: Alpha7

nicotinic acetylcholine receptor mechanisms in Alzheimer's disease.

Biochemical pharmacology, 82 (8): 931-942.



Disease 154

Pastor, P. and Goate, A. M. (2004). Molecular genetics of Alzheimer’s disease.

Current psychiatry reports, 6 (2): 125-133.

Peng, J.-H. F., Xu, Z.-C., Xu, Z.-X., Parker, J. C., Friedlander, E. R., Tang, J.-P. and

Melethil, S. (1992). Aluminum-induced acute cholinergic neurotoxicity in rat.

Molecular and chemical neuropathology, 17 (1): 79-89.

Pennington, J. A. and Schoen, S. A. (1995). Estimates of dietary exposure to

aluminium. Food Additives and Contaminants, 12 (1): 119-128.

Pepeu, G. and Giovannini, M. G. (2004). Changes in acetylcholine extracellular

levels during cognitive processes. Learning and Memory, 11 (1): 21-27.

Per, D. and Pendlebury, W. (1984). Aluminium accumulation in neurofibrillary

tangle-bearing neurones of senile dementia of the Alzheimer's type: detection

by intraneuronal X-ray spectrometry studies of unstained tissue. Journal of

Neuropathology and Experimental Neurology, 43: 349.

Perl, D. P. and Brody, A. R. (1980). Alzheimer's disease: X-ray spectrometric

evidence of aluminum accumulation in neurofibrillary tangle-bearing neurons.

Science, 208 (4441): 297-299.

Petersen, C. C. (2007). The functional organization of the barrel cortex. Neuron, 56

(2): 339-355.

Pettit, D., Shao, Z. and Yakel, J. (2001). Beta-amyloid (1-42) peptide directly

modulates nicotinic receptors in the rat hippocampal slice. The Journal of

neuroscience: the official journal of the Society for Neuroscience, 21 (1):

RC120-RC120.

Platt, B., Carpenter, D. O., Büsselberg, D., Reymann, K. G. and Riedel, G. (1995).

Aluminum impairs hippocampal long-term potentiation in rats in vitro and in

vivo. Experimental neurology, 134 (1): 73-86.



Disease 155

Platt, B., Fiddler, G., Riedel, G. and Henderson, Z. (2001). Aluminium toxicity in the

rat brain: histochemical and immunocytochemical evidence. Brain research

bulletin, 55 (2): 257-267.

Pohanka, M. (2012). Alpha7 nicotinic acetylcholine receptor is a target in

pharmacology and toxicology. International journal of molecular sciences, 13

(2): 2219-2238.

Pohl, H. R., Roney, N. and Abadin, H. G. (2011). Metal ions affecting the

neurological system. Met Ions Life Sci, 8 (247): 62.

Praticò, D., Uryu, K., Sung, S., Tang, S., Trojanowski, J. Q. and Lee, V. M.-Y.

(2002). Aluminum modulates brain amyloidosis through oxidative stress in

APP transgenic mice. The FASEB Journal, 16 (9): 1138-1140.

Puzzo, D., Privitera, L., Leznik, E., Fà, M., Staniszewski, A., Palmeri, A. and

Arancio, O. (2008). Picomolar amyloid-β positively modulates synaptic

plasticity and memory in hippocampus. The Journal of Neuroscience, 28 (53):

14537-14545.

Raybuck, J. D. and Lattal, K. M. (2011). Double dissociation of amygdala and

hippocampal contributions to trace and delay fear conditioning. PloS one, 6

(1): e15982.

Ribes, D., Colomina, M., Vicens, P. and Domingo, J. (2008). Effects of oral

aluminum exposure on behavior and neurogenesis in a transgenic mouse

model of Alzheimer's disease. Experimental Neurology, 214 (2): 293-300.

Rihn, B., Berahmoune, S., Jouma, M., Chamaa, S., Marcocci, L. and Le Faou, A.

(2009). APOE genotyping: comparison of three methods. Clinical and

experimental medicine, 9 (1): 61-65.



Disease 156

Rogers, M. and Simon, D. G. (1999). A preliminary study of dietary aluminium

intake and risk of Alzheimer's disease. Age and Ageing, 28 (2): 205-209.

Rondeau, V. (2002). A review of epidemiologic studies on aluminum and silica in

relation to Alzheimer's disease and associated disorders. Reviews on

Environmental Health, 17 (2): 107-122.

Rondeau, V., Commenges, D., Jacqmin-Gadda, H. and Dartigues, J.-F. (2000).

Relation between aluminum concentrations in drinking water and Alzheimer's

disease: an 8-year follow-up study. American Journal of Epidemiology, 152

(1): 59-66.

Rondeau, V., Jacqmin-Gadda, H., Commenges, D., Helmer, C. and Dartigues, J.-F.

(2009). Aluminum and silica in drinking water and the risk of Alzheimer's

disease or cognitive decline: findings from 15-year follow-up of the PAQUID

cohort. American journal of epidemiology, 169 (4): 489-496.

Rosana, A. and Marco Antonio Campana, V. (2012). High-and Low-Rearing Rats

Differ in the Brain Excitability Controlled by the Allosteric Benzodiazepine

Site in the GABA A Receptor. Journal of Behavioral and Brain Science,

2012.

Ross, S. A., Wong, J. Y., Clifford, J. J., Kinsella, A., Massalas, J. S., Horne, M. K.,

Scheffer, I. E., Kola, I., Waddington, J. L. and Berkovic, S. F. (2000).

Phenotypic characterization of an α4 neuronal nicotinic acetylcholine receptor

subunit knock-out mouse. The Journal of Neuroscience, 20 (17): 6431-6441.

Rubinow, M. J., Mahajan, G., May, W., Overholser, J. C., Jurjus, G. J., Dieter, L.,

Herbst, N., Steffens, D. C., Miguel-Hidalgo, J. J. and Rajkowska, G. (2016).

Basolateral amygdala volume and cell numbers in major depressive disorder: a



Disease 157

postmortem stereological study. Brain Structure and Function, 221 (1): 171-

184.

Rushforth, S. L. 2013. Neuronal nicotinic receptors as targets for enhancing

cognition in schizophrenia. Newcastle University.

Saiyed, S. M. and Yokel, R. A. (2005). Aluminium content of some foods and food

products in the USA, with aluminium food additives. Food Additives and

Contaminants, 22 (3): 234-244.

Sánchez-Iglesias, S., Soto-Otero, R., Iglesias-Gonzalez, J., Barciela-Alonso, M. C.,

Bermejo-Barrera, P. and Méndez-Álvarez, E. (2007). Analysis of brain

regional distribution of aluminium in rats via oral and intraperitoneal

administration. Journal of Trace Elements in Medicine and Biology, 21: 31-

34.

Schliebs, R. and Arendt, T. (2006). The significance of the cholinergic system in the

brain during aging and in Alzheimer’s disease. Journal of neural transmission,

113 (11): 1625-1644.

Sederberg, P. B., Kahana, M. J., Howard, M. W., Donner, E. J. and Madsen, J. R.

(2003). Theta and gamma oscillations during encoding predict subsequent

recall. The Journal of Neuroscience, 23 (34): 10809-10814.

Sehar, S., Naz, I., Ali, N. and Ahmed, S. (2013). Analysis of elemental concentration

using ICP-AES and pathogen indicator in drinking water of Qasim Abad,

District Rawalpindi, Pakistan. Environmental monitoring and assessment, 185

(2): 1129-1135.

Sethi, P., Jyoti, A., Singh, R., Hussain, E. and Sharma, D. (2008). Aluminium-

induced electrophysiological, biochemical and cognitive modifications in the

hippocampus of aging rats. Neurotoxicology, 29 (6): 1069-1079.



Disease 158

Shafer, T. J., Mundy, W. R. and Tilson, H. A. (1993). Aluminum decreases

muscarinic, adrenergic, and metabotropic receptor-stimulated

phosphoinositide hydrolysis in hippocampal and cortical slices from rat brain.

Brain research, 629 (1): 133-140.

Shaw, C. A. and Petrik, M. S. (2009). Aluminum hydroxide injections lead to motor

deficits and motor neuron degeneration. Journal of Inorganic Biochemistry,

103 (11): 1555-1562.

Silva, V. S., Nunes, M. A., Cordeiro, J. M., Calejo, A. I., Santos, S., Neves, P., Sykes,

A., Morgado, F., Dunant, Y. and Gonçalves, P. P. (2007). Comparative

effects of aluminum and ouabain on synaptosomal choline uptake,

acetylcholine release and (Na+/K+) ATPase. Toxicology, 236 (3): 158-177.

Silvers, J. M., Harrod, S. B., Mactutus, C. F. and Booze, R. M. (2007). Automation

of the novel object recognition task for use in adolescent rats. Journal of

neuroscience methods, 166 (1): 99-103.

Siok, C., Rogers, J., Kocsis, B. and Hajos, M. (2006). Activation of α7 acetylcholine

receptors augments stimulation‐induced hippocampal theta oscillation.

European Journal of Neuroscience, 23 (2): 570-574.

Smale, G., Nichols, N. R., Brady, D. R., Finch, C. E. and Horton Jr, W. E. (1995).

Evidence for Apoptotic Cell Death in Alzheimer's Disease. Experimental

Neurology, 133 (2): 225-230.

Smolinsky, A. N., Bergner, C. L., Laporte, J. L. and Kalueff, A. V. (2009). Analysis

of grooming behavior and its utility in studying animal stress, anxiety, and

depression. Mood and anxiety related phenotypes in mice. Springer.



Disease 159

Song, C., Murray, T. A., Kimura, R., Wakui, M., Ellsworth, K., Javedan, S. P.,

Marxer-Miller, S., Lukas, R. J. and Wu, J. (2005). Role of α7-nicotinic

acetylcholine receptors in tetanic stimulation-induced γ oscillations in rat

hippocampal slices. Neuropharmacology, 48 (6): 869-880.

Spillane, J., Curzon, G., Meier-Ruge, W., White, P., Goodhardt, M., Iwangoff, P.,

Davison, A. and Bowen, D. (1979). Accelerated ageing or selective neuronal

loss as an important cause of dementia? The Lancet, 313 (8106): 11-14.

St George-Hyslop, P. H. and Petit, A. (2005). Molecular biology and genetics of

Alzheimer's disease. Comptes rendus biologies, 328 (2): 119-130.

Stancampiano, R., Cocco, S., Cugusi, C., Sarais, L. and Fadda, F. (1999). Serotonin

and acetylcholine release response in the rat hippocampus during a spatial

memory task. Neuroscience, 89 (4): 1135-1143.

Stavljenic–Rukavina, A. 15. MOLECULAR MECHANISMS IN ALZHEIMER'S

DISEASE.

Stevanović, I. D., Jovanovic, M., Colic, M., Jelenkovic, A., Bokonjic, D., Ninkovic,

M. and Stojanovic, I. (2011). N-nitro-L-arginine methyl ester influence on

aluminium toxicity in the brain. Folia Neuropathol, 49 (3): 219-229.

Stevanović, I. D., Jovanović, M. D., Čolić, M., Jelenković, A., Bokonjić, D. and

Ninković, M. (2010). Nitric oxide synthase inhibitors protect cholinergic

neurons against AlCl 3 excitotoxicity in the rat brain. Brain research bulletin,

81 (6): 641-646.

Sun, Z.-Z., Chen, Z.-B., Jiang, H., Li, L.-L., Li, E.-G. and Xu, Y. (2009). Alteration

of Aβ metabolism-related molecules in predementia induced by AlCl3 and d-

galactose. Age, 31 (4): 277-284.



Disease 160

Syed, H., Ikram, M. F., Yaqinuddin, A. and Ahmed, T. (2015). Cyclooxygenase I and

II inhibitors distinctly enhance hippocampal-and cortex-dependent cognitive

functions in mice. Molecular medicine reports, 12 (5): 7649-7656.

Szutowicz, A., Bielarczyk, H., Kisielevski, Y., Jankowska, A., Madziar, B. and

Tomaszewicz, M. (1998). Effects of aluminum and calcium on acetyl-CoA

metabolism in rat brain mitochondria. Journal of Neurochemistry, 71: 2447-

2453.

Tahir, M. A., Chandio, B. A., Abdullah, M. and Rashid, A. Year. Drinking water

quality monitoring in the rural areas of Rawalpindi. In: National Workshop

on Quality of Drinking Water, 1998. 35.

Tareen, A. K., Sultan, I. N., Parakulsuksatid, P., Shafi, M., Khan, A., Khan, M. W.

and Hussain, S. (2014). Detection of heavy metals (Pb, Sb, Al, As) through

atomic absorption spectroscopy from drinking water of District Pishin,

Balochistan, Pakistan. Int. J. Curr. Microbiol. App. Sci, 3 (1): 299-308.

Tariq, M., Ali, M. and Shah, Z. (2006). Characteristics of industrial effluents and

their possible impacts on quality of underground water. Soil Environ, 25 (1):

64-69.

Tejada, J., Bosco, G. G., Morato, S. and Roque, A. C. (2010). Characterization of the

rat exploratory behavior in the elevated plus-maze with Markov chains.

Journal of Neuroscience Methods, 193 (2): 288-295.

Terry, R. L. (1970). Primate grooming as a tension reduction mechanism. The Journal

of psychology, 76 (1): 129-136.

Tinsley, M. R., Quinn, J. J. and Fanselow, M. S. (2004). The role of muscarinic and

nicotinic cholinergic neurotransmission in aversive conditioning: comparing

Disease 161

pavlovian fear conditioning and inhibitory avoidance. Learning & Memory, 11

(1): 35-42.

Tohgi, H., Utsugisawa, K., Yoshimura, M., Nagane, Y. and Mihara, M. (1998a).

Age-related changes in nicotinic acetylcholine receptor subunits alpha 4 and

beta 2 messenger RNA expression in postmortem human frontal cortex and

hippocampus. Neuroscience Letters, 245 (3): 139-142.

Tohgi, H., Utsugisawa, K., Yoshimura, M., Nagane, Y. and Mihara, M. (1998b).

Age-related changes in nicotinic acetylcholine receptor subunits α 4

and β 2 messenger RNA expression in postmortem human frontal

cortex and hippocampus. Neuroscience letters, 245 (3): 139-142.

Traub, R. D., Bibbig, A., Fisahn, A., Lebeau, F. E., Whittington, M. A. and Buhl, E.

H. (2000). A model of gamma‐frequency network oscillations induced in the

rat CA3 region by carbachol in vitro. European Journal of Neuroscience, 12

(11): 4093-4106.

Turhan, S. (2006). Aluminium contents in baked meats wrapped in aluminium foil.

Meat science, 74 (4): 644-647.

Ullah, R., Malik, R. N. and Qadir, A. (2009). Assessment of groundwater

contamination in an industrial city, Sialkot, Pakistan. African Journal of

Environmental Science and Technology, 3 (12).

Vicens, P., Carrasco, M. C. and Redolat, R. (2003). Effects of early training and

nicotine treatment on the performance of male NMRI mice in the water maze.

Neural plasticity, 10 (4): 303-317.



Disease 162

Vicens, P., Ribes, D., Torrente, M. and Domingo, J. L. (2011). Behavioral effects of

PNU-282987, an alpha7 nicotinic receptor agonist, in mice. Behavioural Brain

Research, 216 (1): 341-348.

Vnek, N., Kromer, L. F., Wiley, R. G. and Rothblat, L. A. (1996). The basal

forebrain cholinergic system and object memory in the rat. Brain Research,

710 (1): 265-270.

Vreugdenhil, M. and Toescu, E. (2005). Age-dependent reduction of γ oscillations in

the mouse hippocampus in vitro. Neuroscience, 132 (4): 1151-1157.

Walton, J. (2006). Aluminum in hippocampal neurons from humans with Alzheimer's

disease. Neurotoxicology, 27 (3): 385-394.

Walton, J. (2007a). An aluminum-based rat model for Alzheimer’s disease exhibits

oxidative damage, inhibition of PP2A activity, hyperphosphorylated tau, and

granulovacuolar degeneration. Journal of Inorganic Biochemistry, 101 (9):

1275-1284.

Walton, J. (2007b). A longitudinal study of rats chronically exposed to aluminum at

human dietary levels. Neuroscience letters, 412 (1): 29-33.

Wang, G., Dinkins, M., He, Q., Zhu, G., Poirier, C., Campbell, A., Mayer-Proschel,

M. and Bieberich, E. (2012). Astrocytes secrete exosomes enriched with

proapoptotic ceramide and prostate apoptosis response 4 (PAR-4) potential

mechanism of apoptosis induction in Alzheimer disease (AD). Journal of

Biological Chemistry, 287 (25): 21384-21395.

Wang, H.-Y., Lee, D. H., D'andrea, M. R., Peterson, P. A., Shank, R. P. and Reitz, A.

B. (2000a). β-Amyloid1–42 Binds to α7 Nicotinic Acetylcholine Receptor

with High Affinity IMPLICATIONS FOR ALZHEIMER'S DISEASE

PATHOLOGY. Journal of Biological Chemistry, 275 (8): 5626-5632.



Disease 163

Wang, H. Y., Lee, D. H., Davis, C. B. and Shank, R. P. (2000b). Amyloid Peptide

Aβ1‐42 Binds Selectively and with Picomolar Affinity to α7 Nicotinic

Acetylcholine Receptors. Journal of neurochemistry, 75 (3): 1155-1161.

Wang, Y.-L., Wang, J.-G., Ou-Yang, G.-X., Li, X.-L., Henderson, Z. and Lu, C.-B.

(2014). Co-activation of nAChR and mGluR induces γ oscillation in rat medial

septum diagonal band of Broca slices. Acta Pharmacologica Sinica.

Ward, L. M. (2003). Synchronous neural oscillations and cognitive processes. Trends

in cognitive sciences, 7 (12): 553-559.

Wevers, A., Monteggia, L., Nowacki, S., Bloch, W., Schütz, U., Lindstrom, J.,

Pereira, E., Eisenberg, H., Giacobini, E. and De Vos, R. (1999). Expression of

nicotinic acetylcholine receptor subunits in the cerebral cortex in Alzheimer’s

disease: histotopographical correlation with amyloid plaques and

hyperphosphorylated‐tau protein. European Journal of Neuroscience, 11 (7):

2551-2565.

Williams, J. H. and Kauer, J. A. (1997). Properties of carbachol-induced oscillatory

activity in rat hippocampus. Journal of neurophysiology, 78 (5): 2631-2640.

Wills, M. R. and Savory, J. (1985). Water content of aluminum, dialysis dementia,

and osteomalacia. Environmental Health Perspectives, 63: 141.

Wilson, M. A. and Fadel, J. R. (2016). Cholinergic regulation of fear learning and

extinction. Journal of Neuroscience Research.

Wolfe, M. S., Xia, W., Ostaszewski, B. L., Diehl, T. S., Kimberly, W. T. and Selkoe,

D. J. (1999). Two transmembrane aspartates in presenilin-1 required for

presenilin endoproteolysis and γ-secretase activity. Nature, 398 (6727): 513-

517.

Disease 164

Wood, S. C. and Anagnostaras, S. G. (2011). Interdependence of measures in

pavlovian conditioned freezing. Neuroscience Letters, 505 (2): 134-139.

Woolf, N. J. (1991). Cholinergic systems in mammalian brain and spinal cord.

Progress in neurobiology, 37 (6): 475-524.

Yellamma, K., Saraswathamma, S. and Kumari, B. N. (2010). Cholinergic system

under aluminium toxicity in rat brain. Toxicology international, 17 (2): 106.

Yokel, R. A., Allen, D. D. and Ackley, D. C. (1999). The distribution of aluminum

into and out of the brain. Journal of inorganic biochemistry, 76 (2): 127-132.

Yokel, R. A., Hicks, C. L. and Florence, R. L. (2008). Aluminum bioavailability

from basic sodium aluminum phosphate, an approved food additive

emulsifying agent, incorporated in cheese. Food and Chemical Toxicology, 46

(6): 2261-2266.

Yokel, R. A. and Mcnamara, P. J. (2001). Aluminium toxicokinetics: an updated

minireview. Pharmacology and Toxicology, 88 (4): 159-167.

Yokeş, M. B. (2007). Molecular genetics of Alzheimer's Disease. Journal of cell and

Molecular Biology, 6: 73-97.

Zatta, P., Ibn-Lkhayat-Idrissi, M., Zambenedetti, P., Kilyen, M. and Kiss, T. (2002).

 In vivo and in vitro effects of aluminum on the activity of

mouse brain acetylcholinesterase. Brain research bulletin, 59 (1): 41-45.

Zhang, R., Zhang, J., Fang, L., Li, X., Zhao, Y., Shi, W. and An, L. (2014).

Neuroprotective effects of sulforaphane on cholinergic neurons in mice with

Alzheimer’s disease-like lesions. International journal of molecular sciences,

15 (8): 14396-14410.

prr.hec.gov.pkprr.hec.gov.pk/jspui/bitstream/123456789/8361/1/syeda... · 2018-07-23 ·...

Documents