Clinica Chimica Acta 433 (2014) 225–231

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Clinica Chimica Acta

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Invited critical review

Matrix metalloproteinase 9 (MMP-9) in osteosarcoma: Reviewand meta-analysis

Jing Wang a, Qiong Shi a, Tai-xian Yuan a, Qi-lin Song a, Yan Zhang a, Qiang Wei a, Lan Zhou a, Jinyong Luo a,Guowei Zuo a, Min Tang a, Tong-Chuan He a,b, Yaguang Weng a,⁎a College of Laboratory Medicine, Key Laboratory of Laboratory Medical Diagnostics designated by Chinese Ministry of Education, Chongqing Medical University, 400016, Chinab Molecular Oncology Laboratory, Department of Orthopaedic Surgery, The University of Chicago Medical Center, Chicago, IL 60637, USA

Abbreviations: MMP-9, matrix metalloproteinase 9; Ounder the receiver operating characteristic curve; H, healtodds ratio.⁎ Corresponding author at: School of Laboratory Med

University, #1 Yi-Xue-Yuan Rd., Yu-zhong District, ChongqE-mail address: yaguangweng@126.com (Y. Weng).

http://dx.doi.org/10.1016/j.cca.2014.03.0230009-8981/© 2014 Elsevier B.V. All rights reserved.

a b s t r a c t

a r t i c l e i n f o

Article history:Received 11 January 2014Received in revised form 28 February 2014Accepted 19 March 2014Available online 1 April 2014

Keywords:Meta-analysisDiagnosisMMP-9Osteosarcoma

The aimof this study is to determine the value ofmatrixmetalloproteinase 9 (MMP-9) in diagnosis of osteosarcoma(OS). A systematic review and meta-analysis was conducted using MEDLINE, Embase, ISI Web of Knowledge, theCochrane Library, Scopus, BioMedCentral, ScienceDirect, China Biomedical literatureDatabase (CBM)andChinaNa-tional Knowledge Internet (CNKI) from inception through Aug 29, 2013. Articles written in English or Chinese thatinvestigated the accuracy ofMMP-9 for the diagnosis of OSwere included. Pooled sensitivity, specificity and the areaunder the receiver operating characteristic curve (AUC) were determined. I2 was used to test heterogeneity andsource of heterogeneity was investigated by meta-regression (tested with Meta-DiSc and STATA 12.0 statisticalsoftwares). A total of 3729 articles were retrieved, of which 18 were included, accounting for 892 patients. Overall,the pooled sensitivity, specificity and AUC were 0.78 (95% CI 0.730–0.83), 0.90 (95% CI 0.79–0.95), and 0.87(95% CI 0.83–0.89), respectively. The studies had substantial heterogeneity (I2 = 84%, 95% CI 65–100) (96%, 95%CI 94–99). Assay kit subgroup was the main source of the heterogeneity. Although MMP-9 was identified as apotential biomarker for OS, more studies were clearly needed to establish its diagnostic value.

© 2014 Elsevier B.V. All rights reserved.

Contents

1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2262. Methods . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 226

2.1. Search strategy and selection criteria . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2262.2. Procedures . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2262.3. Statistical analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 226

3. Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2263.1. Study characteristics and quality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2263.2. Summary data and performance estimates . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2273.3. Heterogeneity analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2273.4. Possible sources of heterogeneity and subgroup analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2283.5. Clinical application of the index test . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 229

4. Discussion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 229Conflict of Interest Statement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 230Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 230References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 230

S, detecting osteosarcoma; CBM, China Biomedical literature Database; CNKI, China National Knowledge Internet; AUC, areahy group; BBD, benign bone disease; TP, true-positive; FP, false-positive; FN, false-negative; TN, true-negative; DOR, diagnostic

icine, Key Laboratory of Laboratory Medical Diagnostics designated by Chinese Ministry of Education, Chongqing Medicaling 400016, China. Tel.: +86 23 68485045; fax: +86 23 68485005.

Fig. 1. Schematic representation of the study selection. Some studieswere excluded formorethan one reason. *Did not investigate the diagnostic accuracy of MMP-9 as a marker for OS.

226 J. Wang et al. / Clinica Chimica Acta 433 (2014) 225–231

1. Introduction

Osteosarcoma (OS) is a class of malignancy originating from thebone that mainly afflicts children or young adults. It is the secondhighest cause of cancer-related death in these age groups due to devel-opment of often fatal metastasis, usually in the lungs [1]. While OS canarise in any bone, the most common sites of primary tumors are thedistal femur, proximal tibia and proximal humerus [2]. Typical signsand symptoms include history of pain, followed by localized swellingand limitations of joint movement and typical findings on X-rays.Plain radiographic films are usually the first diagnostic imaging studyundertaken and should include the entire affected bone [3]. The classicalappearance of OS on plain films shows destruction of the normal tra-becular bone with presence of a Codman's Triangle formed by newperiosteal formation and elevation of the cortex [4]. CT and MRIscanning are used to delineate the extent of the primary tumor andplanning of definitive surgery [1]. Even though radiographic imagingis highly suggestive, tissue biopsy of OS must be obtained to confirmthe diagnosis, which is generally obtained by open biopsy [5]. Labo-ratory evaluation is generally normal. However, serum alkalinephosphatase and lactate dehydrogenase levels have been reportedelevated in 30%–40% of patients and have been associated with apoorer prognosis [1,4].

Biomarkers are used as tools in cancer diagnostics and in treatmentstratification [6]. In most cancers, there are increased levels of one orseveral members of the matrix metalloproteinases (MMPs), whichcould serve as diagnostic markers in cancer patients [7]. MMPs are afamily of zinc- and calcium-dependent proteolytic enzymes. This is afamily of proteolytic enzymes that are involved in many phases ofcancer progression, including angiogenesis, invasiveness, and metasta-sis. In a study of colorectal cancer (CRC), MMP-9 showed a sensitivityof up to 99% and a specificity of 63% [8]. There are also studies showingthat the presence of MMP-2 and MMP-9 can be a valuable predictor ofbladder and prostate cancers [9,10]. The aim of this report is to evaluatethe diagnostic value of MMP-9 in the detection of OS, with the purposeto guide the clinical diagnosis.

2. Methods

2.1. Search strategy and selection criteria

We systematically searched MEDLINE (via PubMed), Embase (viaOvidSP), ISI Web of Knowledge, the Cochrane Library, Scopus, BioMedCentral, ScienceDirect, China Biomedical literature Database (CBM),and CNKI for studies that assessed the accuracy of MMP-9 for thediagnosis of OS.

Studies were searched using the key words including “osteosarcomaand (mmp-9 OR mmp9 OR “matrix metalloproteinase 9” OR “"matrixmetalloproteinase-9” OR “gelatinase B” OR “matrix metalloproteinase”)”in the way of full-text. We searched the databases between inceptionand Aug 29, 2013. We also searched the reference list of each primarystudy identified and of previous systematic reviews.

Inclusion criteria: 1) Measurement of MMP-9 in OS using com-mercial reagents. 2) Pathological diagnosis (gold standard) con-firmed for newly diagnosed patients with OS as the case group andpatients with osteochondroma or benign bone disease (BBD), andhealthy people as the control group. 3) The studies had to providesufficient information to construct the 2 × 2 contingency Table. 4)More than 20 subject samples were performed. 5) Publicationswritten in English or Chinese.

Exclusion criteria: 1) OS diagnosed without a biopsy and there wasno clear cut-off value in the literature; 2) No control groups. 3) Similarstudies from the same author as well as multiple duplicate data in thedifferent works, excluding earlier and smaller sample data. 4) Animalexperiments, reviews, correspondences, case reports, talks, expertopinions, and editorials were excluded.

2.2. Procedures

Two investigators (JW and QLS) independently extracted data, in-cluding the quality assessment from the retrieved studies. Discrepancieswere resolved in a consensusmeeting.We contacted the correspondingauthors if further information was needed. If no response was receivedafter sending a reminder, the study was excluded.

We assessed the methodological quality of the studies with theQuality Assessment of Diagnostic Accuracy Studies checklist [11]. Theguidelines for scoring each item of the checklist to our review weretailored [12].

2.3. Statistical analysis

The true positives, false negatives, false positives, and true negativesin each study were tabulated. We used the numbers to calculate sensi-tivity and specificity and a corresponding CI by the MIDAS module[13] for STATA (version 12.0).

To analyze the dataset, we used an exact binomial rendition [14] ofthe bivariate mixed-effects regression model developed by vanHouwelingen [15,16] for meta-analysis. Based on this model, weestimated mean logit sensitivity and specificity with their standarderror and 95% CIs, the between-study variability in logit sensitivityand specificity, summary receiver operating curve for MMP-9.

I2 was calculated to assess heterogeneity. If heterogeneity amongstudies was recorded, the potential source of heterogeneity was investi-gated by sensitivity analysis and metaregression. We used study-specific covariates such as cut-off value, assay kit, and control group.To investigate publication bias, we constructed Deeks' regression testand a Begg funnel plot.

3. Results

3.1. Study characteristics and quality

Our database search retrieved 3729 articles. After reviewing thetitles and abstracts, we excluded 3587. After a full text review weexcluded a further 124, leaving 18 studies [17–34] for inclusion(Fig. 1). Search of the reference lists of the identified articles and previoussystematic reviews did not identify any more relevant articles.

The Table 1 shows the main characteristics of 18 studies. 892 OS pa-tientswere included in the analysis. The prevalence of OS among studies

Table 1Main characteristics of 18 studies.

Author Year Assay kit n Cases of OS Cases ofcontrol

Prevalence (%) Cut-off TP FP FN TN

H BBD

Chen et al. 2001 Maxim 100 70 15 15 70% 2 Score 61 0 9 30Peng et al. 2002 MAIXIN 69 51 18 – 74% 5% 39 9 12 9Huanget al.

2005 Maxim 49 38 – 11 78% 2 Score 29 5 9 6

Li et al. 2005 Zhongshan 51 36 15 – 71% 10% 31 2 5 13Li et al. 2006 MAIXIN 105 85 – 20 81% 0% 64 0 21 20Luo et al. 2006 MAIXIN 74 54 20 – 73% 2 Score 47 2 7 18Liu et al. 2007 MAIXIN 65 45 – 20 69% 10% 40 0 5 20Zhang et al. 2007 MAIXIN 68 48 – 20 71% 2 Score 39 5 9 15Lei et al. 2009 MAIXIN 67 35 – 32 52% 25% 24 9 11 23Liao et al. 2009 Santa Cruz 75 57 – 18 76% 10% 38 1 19 17Lu et al. 2009 Maxim 70 55 15 – 79% 2 Score 44 0 11 15Zhou et al. 2009 Zhongshan 58 46 – 12 79% 2 Score 37 0 9 12Du et al. 2010 Zhongshan 60 41 – 19 68% 3 Score 36 0 5 19Jie et al. 2010 – 129 89 – 40 69% 2 Score 53 8 36 32Xu et al. 2010 MAIXIN 53 28 – 25 53% 1 Score 23 7 5 18Wang et al. 2011 Zhongshan 37 27 10 – 73% 0 Score 24 1 3 9Liao et al. 2013 – 49 35 – 14 71% 0% 25 5 10 9Meng et al. 2013 Santa Cruz 92 52 – 40 57% 10% 29 10 23 30

227J. Wang et al. / Clinica Chimica Acta 433 (2014) 225–231

ranged between 52% and 81% (mean 70%). 9 of 18 studies reportedclassification of clinical stages according to Enneking System [35](Stages 1, 2, and 3; Table 2).

All of the studies used immunohistochemistry (IHC) to determine theexpression of MMP-9. The results were judged by cut-off in 2 ways: per-centage of positivity and immunoreactivity (intensity) score (IRS). A finalIRS was obtained for each case by multiplying the percentage and the in-tensity score. Only 8 studies were decided as positive by percentages,whereas 10 by scores (Table 1). Four sources of assay kits (MAIXIN,Zhongshan, Maxim, and Santa Cruz diagnostics) were used in 16 studies.Two papers used Santa Cruz diagnostics, and the number is too small tobe testedwithMeta-DiSc. Three kits (MAIXIN, Zhongshan, andMaximdi-agnostics) were tested, and the summary data were listed in Table 3.Taken together, Zhongshan diagnostics kit has the best pooled sensitivity,pooled specificity, area under the curve (AUC), andwithout heterogeneityexists. In one study the investigators used osteochondroma and healthypeople as the control group, and the study was divided into two partsonly in the subgroup analysis. The control group of 6 studies was healthyindividuals, while 13 studies being bone tumor (Table 1).

When the methodological quality of the included studies wasassessed according to the Quality Assessment of Diagnostic Accuracy

Table 2Summary characteristics of 9 studies.

Author Year Cases of Stage 1 Cases o

TP FN TP

Chen et al. 2001 1 2 58Li et al. 2005 3 2 25Li et al. 2006 7 10 32Luo et al. 2006 6 2 30Zhanget al.

2007 3 2 20

Liao et al. 2009 5 10 11Du et al. 2010 7 4 15Xu et al. 2010 4 2 11Liao et al. 2013 – – 15

Table 3Summary result of kits for the diagnostic value of MMP-9 for osteosarcoma.

Assay kit Number of studies Threshold (p-value) Pooled sensi

MAIXIN diagnostics 7 0.0 0.82 (0.75–0Zhongshan diagnostics 4 1.0 0.85 (0.79–0Maxim diagnostics 3 0.31 0.80 (0.75–0

Studies, none of the studies fulfilled all of the required items. Butall studies fulfilled at least eight items. The scores of the studies rangedbetween 8 and 11.

3.2. Summary data and performance estimates

Pooled sensitivitywas 0.78 (95% CI 0.730–0.83), and pooled specific-ity was 0.90 (95% CI 0.79–0.95; Figs. 2 and 3). The AUCwas 0.87 (95% CI0.83–0.89; Fig. 4). Pooled positive likelihood ratio (PLR) was 7.61(95% CI 3.56–16.29), pooled negative likelihood ratio (NLR) was 0.24(95% CI 0.19–0.32), and the diagnostic odds ratio (DOR) was 31.20(95% CI 11.969–81.31). At the same time, we tested the diagnosticaccuracy of MMP-9 as a marker for OS at different clinical stages, andthe results are listed in Table 4. The diagnostic sensitivity and AUC ofMMP-9 increased alongwith the progression of OS,while the diagnosticspecificity has no changes.

3.3. Heterogeneity analysis

Substantial heterogeneity exists among the studies (overall I2 for bi-variate model 84%, 95% CI 65–100). Differences of sensitivity and

f Stage 2 Cases of Stage 3 Cases of control

FN TP FN FP TN

6 2 1 0 303 3 0 2 13

11 25 0 0 204 11 1 2 183 16 4 5 15

8 22 1 1 171 14 0 0 193 8 0 7 188 10 2 5 9

tivity (95%CI) Pooled specificity (95%CI) AUC(Q*) Heterogeneity (I2)

.88) 0.91 (0.80–0.97) 0.86 (0.79) 86.30%

.91) 0.95 (0.85–0.99) 0.94 (0.87) 0.00%

.84) 0.79 (0.72–0.85) 0.86 (0.79) 68.20%

Fig. 2. Sensitivity of MMP-9 assay for osteosarcoma.

228 J. Wang et al. / Clinica Chimica Acta 433 (2014) 225–231

specificity and DOR by various research conditions designed differentlylead to a threshold effect. When there is a threshold effect, a shoulderarm-shaped style appears. In our analysis, we found no evidence ofa threshold effect (tested with the STATA MIDAS module) (Fig. 4), whilethe Spearman correlation coefficient was−0.424 (p= 0.080), which in-dicates that there is no heterogeneity from threshold effects. Sensitivityanalysis was used to shows influence by any individual study. No matterwhich study removed, the heterogeneity does not change significantly,suggesting that the results of our analysis do not overly rely on onestudy and the conclusions are fairly consistent. We did not find publica-tion bias by Deeks' regression test of asymmetry (t = 4.46; p N 0.05)(Fig. 5). To validate the result, we performed also a Begg funnel plot,and no publication bias was found too (z = 1.52; p N 0.05).

Fig. 3. Specificity of MMP-9

3.4. Possible sources of heterogeneity and subgroup analysis

To identify the sources of heterogeneity, we performed meta-regression analyses. We considered the cut-off values, assay kits,and the different control groups as the possible source(s) of the het-erogeneity. Through meta-regression analysis, we found the p-valuefor Joint Model of assay kit (tested with the STATA MIDAS module)was b0.05 (p = 0.01), while the p-value (tested with Meta-DiSc, version 1.4) was 0.013, which suggests that the assaykits may be the source of heterogeneity for MMP-9 in OS. The resultsof meta-regression and summary data of subgroup analysis areshown in Tables 5 and 6 (tested with Meta-DiSc, version 1.4),respectively.

assay for osteosarcoma.

Fig. 4. Summary receiver operating characteristic curve.

229J. Wang et al. / Clinica Chimica Acta 433 (2014) 225–231

3.5. Clinical application of the index test

Likelihood ratios and post-test probabilities provide informationabout the likelihood that a patient with a positive or negative test actu-ally has OS or not. A positive likelihood ratio of 6 means that a personwith disease is six-times more likely to have a positive test result thanis a healthy person. To describe the Fagan plot, a straight line whichcrossing the likelihood ratio was used to link the pretest probabilitywith the post-test probability. When 20% was selected as the pre-testprobability, the post-test probability for a positive test result is 66%with a positive likelihood ratio of 8 (Fig. 6). Likewise a negative likeli-hood ratio of 0.24 reduces the post-test probability to 6% for a negativetest result.

4. Discussion

MMPs are enzymes normally involved in the breakdown of the ex-tracellular matrix within the context of physiological tissue remodelingand angiogenesis [36]. MMP-9, otherwise known as gelatinase B, isnormally associated with bone remodeling, and in dysregulated statessuch as rheumatoid arthritis and OS [37]. Excessive production ofMMP-9 has been recognized as an important factor in cancer invasionand metastasis [38]. The diagnostic value of MMP-9 has been reportedfor various other cancers such as breast, prostate, esophageal, pancreatic,oral, and brain cancers [39–46].

In this meta-analysis, the pooled sensitivity and pooled specificity ofMMP-9 for OS are 0.78 (95% CI 0.730–0.83) and 0.90 (95% CI 0.79–0.95).DOR combines the strengths of sensitivity and specificity as prevalencein dependent indicators and has the advantage of accuracy as a singleindicator [47]. The DOR of MMP-9 is 31.20 (95% CI 11.97–81.31),which means MMP-9 could be an ideal biomarker in the diagnosis ofOS. The AUC is determined to assess the discriminating ability [48]. To

Table 4Summary diagnostic accuracy of MMP-9 for osteosarcoma in different clinical stages.

Stage Number of studies Cases of OS Cases of contro

Stage 1 8 70 167Stage 2 9 264 181Stage 3 9 120 181

demonstrate excellent accuracy, the AUC should be in the regionof 0.97 or above. An AUC of 0.93 to 0.96 is very good; 0.75 to 0.92is good. Less than 0.75 can still be reasonable [49,50]. The AUC ofMMP-9 is 0.87 in this meta-analysis. As 9 of 18 studies reported classifi-cation of clinical stages by Enneking, We have also tested the diagnosticaccuracy of MMP-9 as a marker for OS in different clinical stages, andfound that even the pooled specificity of MMP-9 in clinical stages 1–3is the same; the pooled sensitivity of MMP-9 was increasing with themalignancy of OS (as shown in Table 4).

Substantial heterogeneity exists among the studies (overall I2 forbivariate model 84%). We found no evidence of a threshold effect(analyzed with the STATA MIDAS module and Spearman correlationcoefficient in Meta-DiSc). Sensitivity analyses show that the results ofthis analysis do not overly rely on one study and the conclusions are sta-ble. What's more, we did not find publication bias by Deeks' regressiontest of asymmetry (t = 4.46; p N 0.05) and Begg funnel plot (z = 1.52;p N 0.05).

Therefore, we further explored the sources of heterogeneity bymeta-regression analysis. Meta-regression analysis shows that assaykits are the main source of heterogeneity (tested with the STATAMIDAS module and Meta-DiSc; p b 0.05). From the subgroup analysis,the result was confirmed.

Ourmeta-analysis has its limitations. First, although there is no pub-lication bias by Deeks's regression, potential publication bias may stillexist. Studies with desirable results might be published more easily,which can lead to an overestimation of overall diagnostic accuracy. Sec-ond, the studies included differ in several ways—e.g., methodologicalquality, cut-off values, assay kits, and the different control groups. Wedetected substantial heterogeneity between studies and found thatthe use of different assay kits may be responsible for the majority ofthis heterogeneity. Third, all of the studies included are written inChinese.Wehave conducted a full-text search inMedline (via PubMed),Embase (via OvidSP), ISI Web of Knowledge, the Cochrane Library,

l Pooled sensitivity(95% CI)

Pooled specificity(95% CI)

AUC(Q*)

0.51 (0.39–0.64) 0.88 (0.84–0.94) 0.77 (0.71)0.82 (0.77–0.87) 0.88 (0.82–0.92) 0.90 (0.83)0.93 (0.86–0.97) 0.88 (0.82–0.92) 0.95 (0.89)

Fig. 5. Deeks' regression test of publication bias.

Table 5Univariable bivariate mixed-effects binary meta-regression.

Subgroup MIDAS (p-value) Meta-disc

RDOR p-Value

Cut-off value 0.31 2.27 0.183Assay kit 0.01 0.63 0.013Control group 0.11 3.60 0.053

Fig. 6. Fagan nomogram of the MMP-9 test for diagnosis of osteosarcoma.

230 J. Wang et al. / Clinica Chimica Acta 433 (2014) 225–231

Scopus, BioMed Central, Science Direct, CBM, and CNKI database, andfound 3729 articles. After we reviewed all of these articles, only 18studies were included, which is an inherent drawback of literatures be-yond our control. Finally, we only included studies that were publishedin English or Chinese, which could affect our results.

Conflict of Interest Statement

Authors' conflict of interest disclosure: The authors stated that thereare no conflicts of interest regarding the publication of this article.Research funding played no role in the study design; in the collection,analysis, and interpretation of data; in the writing of the report; or inthe decision to submit the report for publication.

Employment or leadership: None declared.Honorarium: None declared.

Acknowledgments

This study was supported in part by research grants from the973 Program of the Ministry of Science and Technology of China

Table 6Summary data of subgroup analysis.

Subgroup Number of studies Cases of OS Cases of con

Cut-off valuePercentage 8 396 177Score 10 496 202

Assay kitMAIXIN 7 346 155Zhongshan 4 150 56Maxim 3 163 56

Control groupHealthy 6 393 93BBD 13 669 286

(2011CB707906 to LZ, JL and TCH) and by National Natural ScienceFoundation of China (NSFC30872770; NSFC31200971) and by NationalMinistry of Education Foundation of China (20115503110009) and bythe Ministry of Education Foundation of China (KJ120327) and by theProgram of theMinistry of Science and Technology of Yu-zhongDistrict,CQ (20130136).

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