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Mol. Hum. Reprod. Advance Access published online on June 7, 2007

Molecular Human Reproduction, doi:10.1093/molehr/gam036
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© The Author 2007. Published by Oxford University Press on behalf of the European Society of Human Reproduction and Embryology. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

Proteomic analysis of human ovaries from normal and polycystic ovarian syndrome

Xiang Ma1,2, Lu Fan1, Yan Meng2, Zheng Hou1, Yun-Dong Mao2, Wei Wang2, Wei Ding2 and Jia-Yin Liu2,3

1 Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing 210029, People's Republic of China 2 The Center of Clinical Reproductive Medicine, The First Affiliated Hospital of Nanjing Medical University, 300 Guangzhou Road, Nanjing 210029, People's Republic of China

3 Correspondence address. Tel: +86-25-83674442; Fax: +86-25-83674442; E-mail: jyliu{at}njmu.edu.cn


    Abstract
 Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 Acknowledgements
 References
 
Polycystic ovary syndrome (PCOS) is the most common cause of anovulatory infertility, affecting 5–10% of females of reproductive age. Currently, little is known about the changes in whole proteins between PCOS and normal ovaries. In the present study, a proteomic approach comprised two-dimensional gel electrophoresis (2DE) analysis and mass spectroscopy was used to identify proteins and examine expression patterns in three PCOS and normal ovaries. One hundred and ten protein spots were separated and showed different intensities between PCOS and normal ovaries. Sixty-nine proteins associated with cellular metabolism and physiological process were identified from 72 spots. Fifty-four proteins were up-regulated in PCOS ovaries and 15 other proteins were up-regulated in normal ovaries. These data demonstrate, for the first time, the complexity in the regulation of ovarian protein expression in human PCOS, and will provide important insight for a better understanding of the pathogenetic mechanisms underlying this clinical disorder.

Key Words: proteome/ovary/PCOS/human


    Introduction
 Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 Acknowledgements
 References
 
Polycystic ovary syndrome (PCOS) is the most common cause of female infertility (Dunaif, 1997), and affects ~5–10% of women of reproductive age. Although hyperandrogenism and polycystic ovaries (assessed by ultrasound and chronic anovulation) are major characteristics in PCOS patients, insulin resistance/glucose dysregulation (Dunaif, 1997), obesity and increased serum luteinizing hormone (LH) levels (Knochenhauer et al., 1998) are also frequently observed in these patients. Women with PCOS also appear to be at long-term risk for several diseases associated with morbidity and mortality, including diabetes mellitus (Rowe et al., 1993; Dunaif, 1997; Solomon, 1999), endometrial carcinoma (Hardiman et al., 2003) and coronary artery disease (Legro, 2003). Although previous studies have demonstrated that many candidate genes expressed in PCOS ovaries were distinctly different from those in normal ovaries of regularly cycling women (Mason et al., 1991), genetic changes do not always reflect cellular function or the complexity and diversity of the mammalian proteome due to post-translational modifications or protein–protein interactions. In addition, although proteomics research is becoming increasingly important in the understanding of cellular and molecular mechanisms, information on proteins and their expression in PCOS is limited.

A classical proteomics approach includes 2D polyacrylamide gel electrophoresis (PAGE) and mass spectrometry in which proteins are identified by their expression profile and peptide sequencing (Hale et al., 2003; Shankar et al., 2005). Comparative protein profiling has been developed for the detection of specific protein expression patterns as a reflection of biological statuses (Shau et al., 2003; Rocken et al., 2004). The present study examined the protein expression patterns in PCOS and normal ovaries, and demonstrated that 69 proteins were up- or down-regulated in PCOS ovaries.


    Materials and Methods
 Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 Acknowledgements
 References
 
Ovarian collection
Protocols for tissue collection and sample preparation were approved by the Institutional Ethics Committee of Nanjing Medical University and its First Affiliated Hospital. Normal females and PCOS patients were recruited from the hospital or University from 2000–2005. Written consents were obtained from all individuals. Normal adult ovaries from three women were obtained from the Body Donor Center (Nanjing Medical University, Nanjing, China). Only women at the follicular phase with normal ovulation menstrual cycles (25–35 days) less than 30 years of age were selected for this study (Table 1). All ovarian biopsies were conducted as for the PCOS ovarian biopsies described below.


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Table 1: Details of normal women

 
Ovarian tissue from three PCOS patients was obtained during wedge resection surgery under laparoscopy at Clinical Reproductive Medicine Center of the First Affiliated Hospital. PCOS patients were included in the study if they had more than 12 follicles (smaller than 10 mm) in at least one ovary or at least two of the following four criteria: irregular menstrual cycles, polycystic ovaries (detected by ultrasound), hyperandrogenism and chronic anovulation (Table 2). All ovarian biopsies constituted minimal wedges taken at the equatorial plane at the antimesovarian edge of each ovary. Care was taken to ensure that both the cortical and stromal components were collected. In general, biopsies constituted about one-tenth of each ovary and had a pyramidal shape with the top of the pyramid located at the ovarian hilus. Biopsies were cut in quarters. A randomly selected quarter was snap frozen in liquid nitrogen immediately after collection, and the remaining tissue samples were subjected to immunohistochemistry analysis.


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Table 2: Details of PCOS patients

 
Protein extraction
Proteins were extracted separately from each of the ovarian tissues from PCOS patients and normal adults, as described previously (Huo et al., 2004). Protein concentration was determined by the Bradford method (Bradford, 1976).

Two-dimensional gel electrophoresis
First-dimensional Iso-Electric Focusing (IEF) was performed using the IPGphor IEF system (Amersham Bioscience, Uppsala, Sweden). The 0.3 mm x 24 cm IPG strips were rehydrated overnight in a mixture of 50 µg ovarian protein for silver staining and 800 µg ovarian protein for Coomassie Brilliant Blue (CBB) staining. After IEF, the gel strips were equilibrated and then loaded on the second-dimensional 12.5% SDS-acrylamide slab gels. The second-dimensional SDS–PAGE was performed, using the Ettan Dalt II system (Amersham Bioscience). After 2DE, gels were stained with silver staining and Coomassie Blue G250 as described previously (Neuhoff et al., 1988; Berkelman and Stenstedt, 1998).

Imaging and statistical analysis
The stained gels were scanned with Artix Scan 1010 plus (Taiwan, China) for spot detection, and the ImageMasterTM 2D Platinum Software (Version 4.9; Amersham Bioscience, Swiss Institute of Bioinformatics, Geneva, Switzerland) was used for quantification, comparison and statistical analysis. A set of spots (weakest spot, smallest spot and size of the largest spot) and related generation conditions (a selected region of the background) were used to do gel-to-gel comparison. The total density in a gel image was used to normalize each spot volume and minimize inter-gel variation. The amount of each protein spot was expressed in terms of its volume. To reflect the quantitative variations in the protein spot volumes, the spot volumes were normalized as a percentage of the total volume of all of the spots present in a gel. Within each experiment, the protein expression profile of PCOS ovary was compared with that of a normal ovary. 2DE was repeated three times using triplicate ovarian samples collected from three different individuals. Protein samples from the individual experiments were not pooled for the 2DE analysis because combining them would have obscured the biological variability between replicates. Instead, means and standard deviations were calculated and statistical significance assessed between normal and PCOS ovaries from three independent replicates using the ImageMasterTM 2D Platinum software package. Statistical significance was inferred at P-values <0.05.

Protein preparation for MS
In-gel digestion was performed as follows. Briefly, protein spots were excised from the CBB-stained gel and cut into small pieces which were then destained twice in 50 µl of 50 mmol/l NH4HCO3/ACN (50:50 v/v), shrunk by dehydration in 50 µl of ACN (two times) and completely dried at 37°C for 20 min. The gel pieces were incubated in freshly prepared 10 mM DTT/25 mM NH4HCO3 at 56°C for 45 min, and proteins were then alkylated using 55 mM iodoacetamide in 25 mM NH4HCO3 (freshly prepared) in a dark room at room temperature for 30 min. The gel pieces were subsequently dehydrated in 25 mM NH4HCO3, 50% ACN and ACN, respectively, and completely dried at room temperature for 30 min. Next, the samples were incubated in a digestion buffer containing 25 mmol/l NH4HCO3 and 10 ng/µl trypsin (sequencing grade, Promega Diagnostics, Madison, WI, USA) at 4°C for 30 min, and replaced with 10 µl of 25 mmol/l NH4HCO3 without trypsin. Samples were incubated for at least 12 h at 37°C and the reaction was terminated with 2% trifluoroacetic acid (TFA). Peptides were then assessed by mass spectrometry.

MALDI-TOF-MS and database search
The monoisotopic masses of the tryptic peptides observed in the Bruker Bi-flex IV MALDI-TOF-MS spectra (Bruker Daltonik, Bremen, Germany) were used to query the SWISSS-PROT/TrEMBL or NCBI sequence database, using MASCOT search programs (http://www.matrixscience.com/cgi/index.pl?page=/search_form_select.html). The peptide masses were compared with the theoretical peptide masses of all available proteins from human species. The following search conditions were applied: 100 ppm for external calibration or a peptide mass tolerance of 0.3 Da of relative error range, one missed cleavage allowed, modification of cysteines by iodoacetamide, methionine oxidation and N-terminal pyroglutamylation allowed as variable modifications.

Western blot
Aliquots of 50 µg protein extracts from three PCOS and normal ovaries were loaded and separated by SDS–PAGE. Proteins were then transferred to a nitrocellulose membrane, which was blocked for 2 h at 25°C with 5% non-fat milk in PBS buffer (20 mM Tris, 500 mM NaCl and 0.01% Tween 20) and incubated with polyclonal antibodies to HSP27 (1:300, Santa Cruz Biotechnology, Santa Cruz, CA, USA), HSP10 (1:1000, ABCAM, Cambridge Science Park, Cambridge, UK), HSP47 (1:100, Santa Cruz Biotechnology), ANX A2 (1:300, Santa Cruz Biotechnology), hnRNPA1 (1:1500, ABCAM) and ß-tubulin (1:500, ABCAM) at 4°C overnight. Proteins were then incubated with second antibodies for 1 h at 37°C, and visualized by enhanced chemiluminescence (Amersham Biosciences). The membrane was then scanned, and the signal intensity of each band was determined using Alpha easeFC (Fluorchem 5500) software (Alpha innotech Corp., CA, USA). Relative protein levels in each sample were then normalized to ß-tubulin.

Immunohistochemistry
After fixation in 10% neutral buffered formalin, ovarian samples were processed and embedded in paraffin. Sections (4 µm in thickness) were cut and placed on 4% polylysine (APES, Zhongshan Biotechnology Co. Ltd, Beijing, China) coated glass slides. The sections were de-waxed and rehydrated through descending grades of alcohol. Briefly, sections were incubated in 1% hydrogen peroxide to eliminate endogenous peroxidase. After washing in PBS, non-specific protein binding was blocked with rabbit serum (ZhongShan Biotechnology Co. Ltd). Sections were then incubated overnight in a humidified chamber at 4°C with purified antibodies [HSP27 (1:2000 dilution, Goat polyclonal, sc-1048), HSP10 (1:2000, Rabbit polyclonal, ab-13528) and HSP47 (1:250, sc-8352); all from Santa Cruz Technology]. Following three washes in PBS, sections were incubated with HRP-conjugated secondary antibody (Zhongshan Biotechnology Co. Ltd). Signals were visualized with 3,3'-diaminobenzidine tetrahydrochloride dihydrate and weakly counterstained with hematoxylin. As negative controls, sections were incubated with dilutent in the absence of primary antibody.


    Results
 Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 Acknowledgements
 References
 
Identification of proteins differentially expressed between PCOS and normal ovaries
In the present study, more than 2000 protein spots were detected on the 2DE gels with similar patterns between PCOS and normal ovaries (Fig. 1). One hundred and ten protein spots with significant differences in expression levels were observed between the two groups (P < 0.05).


Figure 1
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Figure 1: Representative images of the overall 2DE protein patterns. (A) Normal and (B) PCOS ovaries. ImageMasterTM 2D Platinum Software (Version 4.9) was used to analyze these patterns. One hundred and ten protein spots were differentially expressed between PCOS and normal ovaries. Of them, 72 protein spots (69 proteins) indicated by arrows were identified using MALDI-MS (C)

 
Further analysis showed that 69 proteins from 72 protein spots were successfully identified by MALDI-TOF-MS peptide mass fingerprinting (Fig. 1). Among them, 54 proteins were up-regulated in PCOS ovaries and 15 proteins were up-regulated in normal ovaries. Several proteins were identified as the same protein with different molecular weights and pIs in the 2D map, and were differentially expressed between PCOS and normal ovaries; one such protein was Lamin A/C (spot 11, spot 12). Table 4 summarizes these molecules with accession numbers, protein names, mean normalized volumes (% volume) and standard deviations of the protein spots in PCOS and normal ovaries.


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Table 4: Detailed statistical analysis of detected proteins by 2D gels

 
Proteome analysis
FatiGO, a web-based (http://fatigo.bioinfo.cnio.es) database, was used to collect relevant information on biological functions for significantly regulated proteins between PCOS and normal ovaries. The two major categories included cellular physiological process and metabolism (Table 3), and 36 proteins were common to both of these two categories. Three proteins including HSPs, HnRNPA1 and ANX A2 were selected for further analysis by Western blot to validate the data from 2D gels. FatiGO analysis showed that HSPs including HSP27, HSP47 and HSP10 were involved in the regulation of multiple biological processes, and therefore, they were selected for further immunohistochemistry analysis.


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Table 3: Ontology analysis of proteins detected

 
Western blot
Protein levels of HSP10, HSP27, HSP47, ANX A2 and hnRNP A1 were markedly higher in normal ovaries than in the PCO counterparts, whereas HSP47 protein levels were significantly increased in PCO ovaries compared with normal ones (Fig. 2A and B). These protein expression changes were consistent with the results observed in 2D gels.


Figure 2
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Figure 2: Representative Western blot images (A) of HSP10, HSP27, HSP47, ANXA2 and hnRNP A1 of normal and PCOS ovaries (ß-tublin as control) and statistical analysis using t-test was shown in (B). Asterisk represents statistical difference between PCOS and normal ovaries (P < 0.05)

 
Immunohistochemistry
Immunohistochemical analysis was used to compare the localization of HSP10, HSP27 and HSP47 proteins in PCOS and normal ovaries; HSP27 was highly expressed in the oocytes of normal ovaries compared with PCOS ovaries (Fig. 3A). Interestingly, HSP10 was highly expressed in all of the cell types in the ovarian follicle, and its immunoreactivity was markedly decreased in granulosa cells of PCOS ovaries compared with normal ovaries (Fig. 3B). HSP47 was extensively expressed in granulosa and stroma cells of PCOS ovaries compared with normal ones (Fig. 3C).


Figure 3
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Figure 3: Immunohistochemistric analysis of HSP27, HSP10 and HSP47 in PCOS and normal ovaries. Positive immunoreactive signals were visualized brown. Hsp27 was strongly expressed in oocytes (indicated by arrows), and its intensity was decreased or disappeared in PCOS ovaries (A). HSP10 was highly expressed in all of the cell types in the ovarian follicle, and its immunoreactivity was markedly decreased in granulosa cells of PCOS ovaries compared with normal ovaries (B). Hsp47 was extensively expressed in granulosa and stroma cells of PCOS ovaries compared with normal ones (C)

 

    Discussion
 Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 Acknowledgements
 References
 
The present study identified 69 proteins and demonstrated for the first time that 110 proteins are differentially expressed between PCOS and normal ovaries. Although some of these proteins such as vimentin and Lamin A/C are known regulators of ovarian function (Gordon et al., 1998), some of the identified proteins such as HSP27 and HSP10 are novel and their potential roles in the regulation of human folliculogenesis remain to be determined.

The present study demonstrated that most of the proteins differently expressed in PCOS ovaries and normal ovaries were involved in the regulation of cellular physiological processes and metabolism. For example, cellular physiological processes including cell homeostasis and proliferation (such as protein HSP27 and HSP10), regulation of cellular physiological process (such as protein fibrinogen, alpha chain and fibrinogen gamma chain) and regulation of metabolism (such as protein FUSE-binding protein 1 and FUSE-binding protein 2). There are often metabolic disorders connected with carbohydrate and adipose metabolism in patients with PCOS (Wild, 1997). In this context, comparison of protein expression changes between PCOS and normal ovaries will allow for the identification of different cellular signaling and metabolism pathways that may play important roles in PCOS.

Several of the differentially expressed proteins identified in the present study, such as annexin 2 (A2), antithrombin III, fibrinogen, alpha chain, fibrinogen gamma chain and plasminogen-related protein A, are involved in the regulation of fibrinolysis and thrombosis. Expression changes of these proteins might contribute to the impaired vascular permeability, fibrinolysis, abnormal fibrogenesis and thrombosis in PCOS, as reported previously (Michiels and Van Vliet, 1984; Blomback, 1996; Kang et al., 1999). Higher spontaneous abortions rates and complications in pregnancy are often observed in PCOS patients because of hypofibrinolysis and thrombophilia, and impaired fibrinolysis could contribute to the development of cardiovascular disease in PCOS (Glueck et al., 1999, 2000; Yildiz et al., 2002). For example, annexin 2 (A2) and its ligand p11 have been implicated in fibrinolysis due to their ability to accelerate tissue plasminogen activator (tPA)-mediated activation of plasminogen to plasmin (Kang et al., 1999). Moreover, studies using RNAi and interfering antibodies have indicated that annexin A2 also participates in the insulin-stimulated plasma membrane translocation of the glucose transporter GLUT-4 (Huang et al., 2004) and is a mediator of local fibrinolytic action in endothelial cells (Lennon et al., 2003). The present study demonstrated that annexin A2 expression is down-regulated in PCOS ovaries. Further investigations are required to determine whether these findings are associated with oocyte arrest, increased risk of cardiovascular disease, spontaneous abortions and complications in pregnancy in these patients.

Since the initial observation of hyperinsulinemia in PCOS patients (Burghen et al., 1980), increasing evidence suggests that PCOS is associated with an increased risk of insulin-resistance, abnormal glucose metabolism and type-2 diabetes (Reaven, 1993). Our study identified several differentially expressed proteins which are known regulators of insulin function, such as FUSE binding protein 1, flotillin-1, glyoxylate reductase/hydroxypyruvate reductase, malate dehydrogenase and methionine adenosyltransferase II (Song, 2000; Fahien and MacDonald, 2002; Paneda et al., 2002; Genolet et al., 2005). For example, in the present study, we found that methionine adenosyltransferase II was down-regulated in the PCOS ovary. Methionine adenosyltransferase plays an important role in the removal of homocysteine. Hyper-homocysteinemia has been shown to be a stronger risk factor for cardiovascular disease and mortality in patients with type-2 diabetes (Wijekoon et al., 2005). Previous studies have shown that phosphatidylinositol 3-phosphate kinase (PI 3-k) activity is significantly decreased in PCOS, which is closely associated with insulin resistance (Dunaif et al., 2001; Corbould et al., 2005). Moreover, PI 3-k pathways are required for up-regulation of methionine adenosyltransferase II (Paneda et al., 2002). Although the present study showed that methionine adenosyltransferase II was down-regulated in PCOS ovary, whether this was associated with insulin resistance in PCOS ovary is unknown, and warrants further investigation.

HSP27 has been shown to play an important role in a variety of physiological processes including protein chaperoning, steroidogenesis and especially protection against apoptosis. HSP27 has been shown to protect cells against apoptosis by suppressing reactive oxygen species (ROS) generation, mediating MAP kinase pathway, inhibiting cytochrome c-mediated activation of caspase-3 and blocking caspase 9 cascade and Fas-induced apoptosis. In the present study, proteomic and Western blot analyses demonstrated that HSP27 expression was decreased in the PCOS ovary; immunohistochemical staining showed that HSP27 was mainly localized in the oocyte, and its intensity was decreased in the PCOS ovary. These findings are consistent with the notion that HSP27 prevents cell apoptosis during follicular oogenesis. Down-regulation of HSP27 may contribute to oocyte apoptosis in small antral follicles of PCOS ovaries, which is consistent with a previous study in PCOS patients (Laven et al., 2001). Moreover, it has been demonstrated that HSP27 has a potential role to prevent the activation of IKK-beta pathway and may combat insulin resistance (McCarty, 2006). These findings suggest that the down-regulation of HSP27 may simultaneously affect multiple signaling pathways and contribute to the development of various abnormalities in PCOS ovary.

HSP10 (10 kDa), also known as a co-chaperonin for HSP60, can protect cells against apoptosis. The present study showed that HSP10 was expressed in all follicular cell types and was down-regulated in granulosa cells in PCOS ovary. These findings suggest that HSP10 might play an important role in the induction of granulosa cell apoptosis and follicular atresia. Theca cells are major androgen-secreting cells in the human ovarian follicle. Previous studies suggested that over-expression of HSP10 increased the abundance of IGF-1 receptor and amplified activation of IGF-1R signaling in diabetic cardiac muscle (Shan et al., 2003). Another study also showed that IGF-IR expression in PCO ovaries was increased in thecal and stromal cells but decreased in granulosa cells compared with normal ovaries, which may inhibit follicular maturation (Samoto et al., 1993). Data in the present study showed that HSP10 expression was not down-regulated in the theca cells of PCO ovaries, suggesting that HSP10 might contribute to hyperandrogen by enhancement of IGF-1 pathway and inhibition of theca cell apoptosis.

HSP47, located in collagen-secreting cells such as fibroblasts, serves as a collagen-specific molecular chaperone and has been implicated in the pathogenesis of fibrotic diseases and collagen metabolism (Thomson et al., 2005). It is the only heat-inducible protein, which transiently binds to pro-collagen in the endoplasmic reticulum (Saga et al., 1987; Tasab et al., 2000) and collagen type I–V (Natsume et al., 1994; Nagata and Hosokawa, 1996). Collagen is the most abundant protein in mammals and plays an essential role in the function of extracellular matrix (Kadler, 1995; Kadler et al., 1996). Abnormal collagen accumulation and autoimmunity are characteristics of fibrotic diseases. PCOS is a common disorder characterized by bilateral polycystic ovaries with a thickened, fibrotic tunica albugine. The present study showed that HSP47 was extensively expressed in ovarian cells, in particular, in stoma cells and up-regulated in the PCOS ovary. Thus, it is possible that altered expression of HSP47 in PCOS is associated with cyst formation and/or physiological properties of the thick ovarian capsule.

It should be noted that due to the nature of the heterogenity of the cell types in the ovarian tissues collected, the detailed cellular contents of the ovarian biopsies in the present study were not known and the possibility of difference in stromal content between PCOS and control tissues could not be excluded. In addition, the sample size (n = 3) was relative small, although statistically significant differences in the expression of proteins were observed between the two groups. In this context, it will be needed to collect more ovarian samples and use of purified ovarian cell types is needed to validate the differences in protein expression and their functions in future studies.

In conclusion, the present study identified numerous proteins that are differentially expressed in normal and PCOS ovaries, and may be involved in the regulation of various biologic functions. These findings might provide important insight for a better understanding of the molecular mechanism underlying clinical manifestations of PCOS, the identification of causative molecular factors and the development of novel therapeutic strategies.


    Acknowledgements
 Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 Acknowledgements
 References
 
The present study was supported by The National Basic Research Program (China National 973 Program, 2006CB944005), Program for Changjiang Scholars and Innovative Research Team in University (PCSIRT), and we also acknowledg Dr Jinyi Jiang for critical reading of this paper and helpful discussions.


    References
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 Introduction
 Materials and Methods
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 Acknowledgements
 References
 
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