|Year : 2019 | Volume
| Issue : 1 | Page : 1-6
Metabolomic analysis of the brain and blood from rats exposed to high-dose chlorpyrifos
Hao Wu1, Qingtao Wei2, Yuzi Zheng1, Shiyong Fang1, Yingqiang Fu1, Linchuan Liao1
1 Department of Forensic Toxicological Analysis, The West China School of Basic Medical Sciences and Forensic Medicine, Sichuan University, Chengdu, Sichuan, China
2 Department of Forensic Toxicological Analysis, The West China School of Basic Medical Sciences and Forensic Medicine, Sichuan University; Department of Technology, The People's Procuratorate of Chenghua, Chengdu, Sichuan, China
|Date of Web Publication||28-Mar-2019|
Prof. Linchuan Liao
West China School of Preclinical and Forensic Medicine, Sichuan University, Chengdu, Sichuan 610041
Source of Support: None, Conflict of Interest: None
Chlorpyrifos is an organophosphate pesticide used to kill pests such as insects and worms. Wide use of chlorpyrifos has led to serious safety concerns worldwide. Research on the mechanism of action of chlorpyrifos poisoning is continuing. We investigated changes in the small-molecular metabolites in the brain and blood of rats upon exposure to chlorpyrifos at an acute-poisoning dose. Rats were given twice the lowest dose of chlorpyrifos that is lethal for 100% of exposed animals (2 × LD100) and then killed after 2 h. After treatment, gas chromatography-mass spectrometry was used to analyze the metabolomic changes in the brain and blood samples of rats. An increase in blood levels of creatinine and uric acid were noted, along with a decrease in levels of various amino acids. These changes suggested that chlorpyrifos exposure may damage kidney function and cause disorders in amino-acid metabolism of rats. Decreased concentrations of gamma-aminobutyric acid and niacinamide in the brain and increased concentrations of 3-hydroxybutyric acid in rats with acute poisoning by chlorpyrifos were observed, which may suggest oxidative damage in the body.
Keywords: Chlorpyrifos, gas chromatography-mass spectrometry, metabolomics
|How to cite this article:|
Wu H, Wei Q, Zheng Y, Fang S, Fu Y, Liao L. Metabolomic analysis of the brain and blood from rats exposed to high-dose chlorpyrifos. J Forensic Sci Med 2019;5:1-6
|How to cite this URL:|
Wu H, Wei Q, Zheng Y, Fang S, Fu Y, Liao L. Metabolomic analysis of the brain and blood from rats exposed to high-dose chlorpyrifos. J Forensic Sci Med [serial online] 2019 [cited 2019 Jun 16];5:1-6. Available from: http://www.jfsmonline.com/text.asp?2019/5/1/1/255127
| Introduction|| |
Since the dangers of pesticides became apparent in agricultural production, safety concerns have been documented by National Health Organizations constantly. According to a report from the World Health Organization, more than 1 million poisoning cases worldwide are associated with organophosphorus pesticides each year. As a large agricultural country, 20%–50% of acute poisoning cases in China each year are due to organophosphate use, and the mortality prevalence is 3%–40%.
Chlorpyrifos has been used widely as a substitute for highly toxic organophosphorus pesticides. In recent years, studies have shown that long-term exposure to chlorpyrifos may cause an increase in the risk of suicide, and increasing numbers of studies have focused on the toxic effects of chlorpyrifos.,
Conventional toxicology suggests that inhibition of acetylcholinesterase release by chlorpyrifos leads to disturbances in nerve conduction. Studies on lipid peroxidation and cellular oxidative damage to target organs by chlorpyrifos have also been carried out.,,,
Different from conventional toxicology, metabolomics can provide information on the effects of poisoning by toxic drugs on the functional integrity of the entire body based on full-spectrum analyses of low-molecular-weight compounds. At present, such technologies have been used widely in the study of the toxicity mechanism of paraquat, pyrethroid pesticides, and some organophosphorus pesticides., Metabolomics has been used to investigate the toxic effects of chlorpyrifos in nematodes and earthworms., However, little research has been conducted on metabolic changes after acute poisoning with chlorpyrifos, or the use of metabolomics to infer how chlorpyrifos causes poisoning.
We used metabolomics to screen the different metabolites present in pathologic and normal states. We also speculated on the in vivo process of chlorpyrifos poisoning by detecting differentially expressed metabolites.
| Materials and Methods|| |
Ethical approval of the study protocol
Experiments were carried out in accordance with the regulations of the Sichuan Provincial Laboratory Animal Management Committee (China) and in accordance with the Guidelines for the Management and Use of Laboratory Animals (National Institutes of Health, USA).
Reagents and equipment
Acetonitrile, pyridine, and n-heptane were chromatographically pure and obtained from Thermo Fisher (USA). Methoxyamine hydrochloride (98%) was purchased from Sigma-Aldrich (USA). N, O-Bis (trimethylsilyl) trifluoroacetamide (BSTFA) + 1% trimethylsilyl chloride (1 g) were obtained from Regis Technologies (USA). Methyl stearate (99.5%) was purchased from Sigma-Aldrich (USA). A very sensitive weighing scale was obtained from Sartorius (Germany). A refrigerated centrifuge was purchased from Thermo Fisher, and a nitrogen-gas generator was acquired from Sigma-Aldrich (USA). A gas chromatography-mass spectrometry (GC-MS) system (7890C/5975C) was obtained from Agilent Technologies (USA), along with AMDIS 6.51 analysis software. MetaboAnalyst 4.0 was obtained online (www.metaboanalyst.ca/).
Animals and treatment
Eighteen male Sprague–Dawley rats (191–249 g) were housed in a room at a controlled temperature (23°C ± 2°C) and humidity (50% ± 5%) with a light–dark cycle of 12 h.
After acclimatization to their environment for 1 week with free access to rodent chow and water, rats were divided randomly into control groups (K1–K6) and high-dose groups (H1–H6). After a 12-h fast, rats in high-dose groups underwent gavage with 40% chlorpyrifos emulsion at 2360 mg/kg body weight. This is equivalent to twice the lowest dose of chlorpyrifos that is lethal for 100% of exposed animals (2 × LD100). Rats administered with an identical volume of physiologic (0.9%) saline served as the control group.
Collection and pretreatment of samples
After gavage with chlorpyrifos for 2 h, all rats were decapitated. Brains and blood samples were collected and stored at −20°C before GC-MS.
Blood samples were thawed and vortex-mixed at room temperature. Then, 150 μL of ice-cold acetonitrile was added to 50 μL of the blood sample (to precipitate proteins), vortex-mixed for 2 min, and then centrifuged at 16,099 × g for 10 min at 4°C. Then, 100 μL of the supernatant was transferred to a new tube and dried. Next, 30 μL of a solution of methoxyamine hydrochloride in pyridine (15 mg/mL) was added to the residue. After vortex-mixing for 2 min, an oximation reaction was allowed to proceed for 16 h in the dark at 16°C. After oximation, 30 μL of a silylating agent (BSTFA + 1% TMCS) was added rapidly, the tube sealed and vortex-mixed, and then derivatized in an oven at 70°C for 1 h. After derivatization, the tube was cooled down to room temperature in the dark. Then, 100 μL of an internal standard solution (10 μg/mL of methyl stearate in heptane) was added, vortex-mixed for 1 min, allowed to stand for 10 min, centrifuged, and the supernatant injected into the GC-MS system.
Frozen tissues were cut and weighed rapidly. Ultrapure water, at twice the weight of tissue, was added. Then, tissues were homogenized in ice-cold ultrapure water. The remaining pretreatment steps were the same as those described for blood samples.
Ice-cold acetonitrile (100 μL) was added to control samples in a liquid vial. Samples were dried using a nitrogen-gas blower. The remainder of the operation was the same as that described for blood samples.
Quality control samples
50 mL of each original sample (blood or brain tissue homogenate) were pooled to generate the quality control (QC) sample. Then, 50 μL of the QC sample was added to a 1.5-mL centrifuge tube, and 100 μL of acetonitrile was added to precipitate proteins. The remaining operations were the same as those for blood samples. According to the sample size, the quantity of QC samples needed for injection was calculated to be six.
Instrumental setup and sampling
Established analytical conditions based on metabolomics using GC-MS were employed to analyze samples. The chromatographic column was DB-5MS (0.25 mm × 30 m × 0.25 μm). The carrier gas was high-purity helium at a flow rate of 1.0 mL/min. The inlet temperature was 250°C. The split ratio was 5:1. The system had programmed heating: the initial temperature was 60°C, which was maintained for 1 min, then increased to 325°C at 10°C/min, and maintained for 10 min. The MS interface temperature, ion-source temperature, and quadrupole temperature were 280°C, 230°C, and 150°C, respectively. Using an electrospray-ionization source, the collision voltage was set to 70 eV on full-scan mode (m/z 50–600) at a scanning speed of 2 spectra/s. The injection volume was 1 μL. The injection sequence in each group was: 3 blank samples – 3 QC samples – 6 samples – 1 QC sample – 6 samples – 1 QC sample – 6 samples – 1 QC sample – 6 samples – 3 QC samples.
Chromatograms were deconvoluted by AMDIS 6.51 software (Agilent Technologies, CA, USA) and spectral peaks identified. Matching of chromatographic peaks (>80%) using the National Institute of Standards and Technology (NIST) MS Library (2014) was a qualitative criterion for metabolites. Metabolite data (compound name, retention time, and peak area) were obtained.
The data subjected to the pretreatment described above were divided into two groups (blood and brain tissue) according to the tissue type and introduced, respectively, into the metabolomics website www.metaboanalyst.ca. Multivariate analysis was undertaken using the online tool MetaboAnalyst 4.0 (https://www.metaboanalyst.ca). First, an unsupervised pattern recognition method (principal component analysis [PCA]) was used to grasp the data in general. Then, partial least squares discriminant analysis (PLSDA) was employed to ascertain if there was effective separation between the two dose groups for each tissue.
| Results|| |
Stability of the method
The stability of the analytical method was tested through measurement of the retention time and peak area of methyl stearate in QC samples [Table 1] and [Table 2]. The relative standard deviation (RSD) of retention time was <5%, and the RSD of peak area was <20%. Data collected from analytical instruments were deemed to be reliable.
|Table 1: Perk area and retention time of six blood-group quality control samples|
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|Table 2: Perk area and retention time of six brain-group quality control samples|
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All samples were pretreated and analyzed by GC-MS to obtain a total-ion chromatogram. More than 60 peaks (excluding compounds from reagents and chlorpyrifos) were detected in the heart and brain tissues of rats, but only 53 and 54, respectively, matched the known substances in the NIST MS Library by >80% [Figure 1] and [Figure 2]. These metabolites included organic acids, amino acids, sugars, and lipids [Supplementary Table 1] and [Supplementary Table 2].
|Figure 1: Total-ion current spectrum of a quality control sample of blood using gas chromatography-mass spectrometry|
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|Figure 2: Total-ion current spectrum of a quality control sample of brain tissue using gas chromatography-mass spectrometry|
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PCA was carried out on the metabolomics of each tissue in high-dose and control groups. QC samples were clustered together [Figure 3] and [Figure 4], suggesting that the condition of the GC-MS instrument was stable.
|Figure 3: Principal component analysis score map of blood-group quality control and all samples|
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|Figure 4: Principal component analysis score map of quality control and all samples of the brain tissue|
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Initially, PCA was used to examine the intrinsic variation in all groups. PLSDA was carried out for the data to show the fundamental separations between control and experimental groups [Figure 5] and [Figure 6]. Cross-validation was used to confirm the reliability of the regression model.
|Figure 5: Partial least squares discriminant analysis score of the high-dose group and control group for blood (R2 = 0.89757, Q2 = 0.74832)|
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|Figure 6: Partial least squares discriminant analysis score of the high-dose group and control group for the brain tissue (R2 = 0.99375, Q2 = 0.98518)|
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Then, to ascertain the validity of the PLSDA model, a permutation test (200 times) on the corresponding PLSDA model was undertaken [Figure 7] and [Figure 8]. The intercepts of R2 and Q2 on the Y-axis in the permutation test reflect a measure of overfit. The R2 and Q2 values derived from the permuted data were lower than the original values, and regression of the Q2 line intersected at below zero, indicating validation of the PLSDA model.
|Figure 7: Validation plot of the high-dose group and control group for blood (R2= −0.233041, Q2 = 0.510891)|
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|Figure 8: Validation plot of the high-dose group and control group for brain tissue (R2= −0.148559, Q2 = 0.656443)|
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Identification of differentially expressed metabolites
PLSDA can be used to calculate the variable importance in the projection (VIP). In addition, each variable was tested using the Student's t-test. Finally, differentially expressed metabolites associated with chlorpyrifos poisoning were screened based on P(<0.01) and VIP (>1) values. In the established acute-poisoning model, 12 differentially expressed metabolites were screened in the blood group, and 3 differentially expressed metabolites were screened in the brain tissue group [Table 3] and [Table 4].
|Table 3: Differentially expressed metabolites in the high-dose and control groups|
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|Table 4: Differentially expressed metabolites in the high-dose group and control group for brain tissue|
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| Discussion|| |
Chlorpyrifos binds and phosphorylates cholinesterase from the central and peripheral nervous systems. This action leads to choline accumulation in key nerve cells, and ultimately, the clinical signs of toxicity. Cholinesterase inhibition is seen most commonly in the blood and brain.
We observed an increase in plasma creatinine levels in rats, which usually infers damage to kidney function. Levels of uric acid in rats treated with chlorpyrifos also increased in the present study, a finding that is consistent with the results of other studies., Most instances of hyperuricemia are caused by a decrease in the ability of the kidney to excrete uric acid. These biochemical results suggest that acute poisoning by chlorpyrifos results in kidney damage. In addition, serum levels of glycine and proline decreased in mice treated with chlorpyrifos. Proline is the precursor of arginine synthesis, and arginine is a semi-essential amino acid, which may be involved in the pathogenesis of renal diseases. It has also been reported that glycine can protect against glomerular injury induced by various factors., Taken together, these results suggest that renal function was impaired rapidly after acute poisoning by chlorpyrifos.
Simultaneously, reduced levels of various amino acids in the blood may also be the result of impaired kidney function. Decreases in protein levels are due mainly to excessive loss of protein through nephrosis and/or due to the reduction of protein synthesis or increased proteolytic activity/degradation.
Metabolomics data on brain tissue showed a decrease in gamma-aminobutyric acid (GABA) levels after acute poisoning with chlorpyrifos. GABA is the main inhibitory neurotransmitter of the central nervous system. GABA and other receptor-mediated pathways have a protective role in the abnormal excitatory activities of nerves, which can, for example, lead to convulsions. Studies of other organophosphorus pesticides have shown increased uptake of GABA in the brain after poisoning.,
We also noted a decrease in niacinamide levels in the brain following acute poisoning with chlorpyrifos. Niacinamide is a precursor of Vitamin B3 and nicotinamide adenine dinucleotide (NAD). The brain prefers niacinamide to niacin or tryptophan for NAD synthesis. Abnormal changes in niacinamide levels in brain tissue are usually accompanied by functional or organic abnormalities of the nervous system. Some studies have shown that niacinamide can protect cells (especially nerve cells) from degeneration or apoptosis during oxidative stress, cerebral ischemia, and other processes.,, The decrease in niacinamide levels in rats in the experimental group may have been due to the high consumption of niacinamide in the brain to maintain levels of the reduced form of NAD phosphate, and combat oxidative stress caused by chlorpyrifos poisoning.
3-hydroxybutyric acid (also known as “β-hydroxybutyric acid”) is a ketone body. In humans, 3-hydroxybutyric acid is synthesized in the liver by acetyl-coenzyme A. There are two main routes of production: (i) degradation of acetoacetate in the liver by an insufficient supply of glucose and (ii) decomposition of excess fatty acids. As an important intermediate in lipid metabolism, β-hydroxybutyrate can be used as a direct source of energy by the brain. If the body has abnormal energy metabolism (e.g. due to hypoxia, fasting) and the level of β-hydroxybutyrate in blood is high, brain tissue can obtain energy by oxidation of β-hydroxybutyrate. The kidneys, heart, spleen, muscles, gastric epithelium, and lungs can also use β-hydroxybutyric acid as a substrate for oxidative metabolism. Fukushima et al. found that 3-hydroxybutyric acid is involved in the antioxidant response of the body, and that its level is related to oxidative stress in the body. The level of 3-hydroxybutyric acid in the blood and brain tissue of rats in the present study increased significantly, presumably because the body developed respiratory failure rapidly after exposure to chlorpyrifos, causing systemic abnormalities in energy metabolism. At the same time, as the energy-metabolism disorder, oxidative stress also occurred rapidly. This synergistic action promoted the synthesis of 3-hydroxybutyric acid, leading to an increase in the 3-hydroxybutyrate level in the blood, thereby providing energy directly to brain tissue. Energy-supply problems were caused by a lack of oxygen.
| Conclusions|| |
Acute poisoning by chlorpyrifos may cause abnormal energy metabolism and oxidative stress in the whole body, as well as damage to kidney function and the nervous systems of the body.
This work was supported financially by the National Natural Sciences Foundation of China (81373239). We would like to thank Arshad Makhdum, PhD, from Liwen Bianji, Edanz Group, China (www.liwenbianji.cn/ac), for editing the English text of a draft of this manuscript.
Financial support and sponsorship
The study was financially supported by the Project of the National Natural Sciences Foundation of China (81373239).
Conflicts of interest
There are no conflicts of interest.
| References|| |
Chinese Society of Toxicology Poisoning and Treatment of Specialized Committee. Clinical guideline for the diagnosis and treatment of acute organophosphorus pesticide poisoning (2016). Chin J Crit Care Med 2016;36:1057-65.
Ruderman NB, Ross PS, Berger M, Goodman MN. Regulation of glucose and ketone-body metabolism in brain of anaesthetized rats. Biochem J 1974;138:1-10.
Freire C, Koifman S. Pesticides, depression and suicide: A systematic review of the epidemiological evidence. Int J Hyg Environ Health 2013;216:445-60.
Kousba AA, Sultatos LG, Poet TS, Timchalk C. Comparison of chlorpyrifos-oxon and paraoxon acetylcholinesterase inhibition dynamics: Potential role of a peripheral binding site. Toxicol Sci 2004;80:239-48.
Soltaninejad K, Abdollahi M. Current opinion on the science of organophosphate pesticides and toxic stress: A systematic review. Med Sci Monit 2009;15:RA75-90.
Masoud A, Sandhir R. Increased oxidative stress is associated with the development of organophosphate-induced delayed neuropathy. Hum Exp Toxicol 2012;31:1214-27.
Pearson JN, Patel M. The role of oxidative stress in organophosphate and nerve agent toxicity. Ann N Y Acad Sci 2016;1378:17-24.
Marty MS, Andrus AK, Bell MP, Passage JK, Perala AW, Brzak KA, et al.
Cholinesterase inhibition and toxicokinetics in immature and adult rats after acute or repeated exposures to chlorpyrifos or chlorpyrifos-oxon. Regul Toxicol Pharmacol 2012;63:209-24.
Wan X, Zhou C, Kang X, Hu D, Xue W, Li X, et al.
Metabolic profiling of amino acids associated with mortality in patients with acute paraquat poisoning. Med Sci Monit 2018;24:1397-407.
Jellali R, Zeller P, Gilard F, Legendre A, Fleury MJ, Jacques S, et al.
Effects of DDT and permethrin on rat hepatocytes cultivated in microfluidic biochips: Metabolomics and gene expression study. Environ Toxicol Pharmacol 2018;59:1-2.
Jones OA, Swain SC, Svendsen C, Griffin JL, Sturzenbaum SR, Spurgeon DJ, et al.
Potential new method of mixture effects testing using metabolomics and Caenorhabditis elegans
. J Proteome Res 2012;11:1446-53.
McKelvie JR, Wolfe DM, Celejewski MA, Alaee M, Simpson AJ, Simpson MJ, et al.
Metabolic responses of Eisenia fetida
after sub-lethal exposure to organic contaminants with different toxic modes of action. Environ Pollut 2011;159:3620-6.
Begum SA, Upadhyaya TN, Rahman T, Pathak DC, Sarma K, Barua CC, et al.
Hematobiochemical and pathological alterations due to chronic chlorpyrifos intoxication in indigenous chicken. Indian J Pharmacol 2015;47:206-11.
] [Full text]
Dutta AL, Sahu CR. Emblica officinalis
garten fruits extract ameliorates reproductive injury and oxidative testicular toxicity induced by chlorpyrifos in male rats. Springerplus 2013;2:541.
Cherla G, Jaimes EA. Role of L-arginine in the pathogenesis and treatment of renal disease. J Nutr 2004;134:2801S-6S.
Zhang X, Li Y, Zhou H, Fan S, Zhang Z, Wang L, et al.
Plasma metabolic profiling analysis of nephrotoxicity induced by acyclovir using metabonomics coupled with multivariate data analysis. J Pharm Biomed Anal 2014;97:151-6.
Gu L, Shi H, Zhang R, Wei Z, Bi KS, Chen XH, et al.
Simultaneous determination of five specific and sensitive nephrotoxicity biomarkers in serum and urine samples of four drug-induced kidney injury models. J Chromatogr Sci 2017;55:60-8.
Shakoori AR, Alam J, Aziz FAli SS. Biochemical effects of bifenthrin (Talstar) administered orally for one month on the blood and liver of rabbit. Pak Congr Zool 1990;10:61-81.
Mazurkiewicz M, Opolski A, Wietrzyk J, Radzikowski C, Kleinrok Z. GABA level and GAD activity in human and mouse normal and neoplastic mammary gland. J Exp Clin Cancer Res 1999;18:247-53.
Petit-Pedrol M, Armangue T, Peng X, Bataller L, Cellucci T, Davis R, et al.
Encephalitis with refractory seizures, status epilepticus, and antibodies to the GABAA receptor: A case series, characterisation of the antigen, and analysis of the effects of antibodies. Lancet Neurol 2014;13:276-86.
Gubert P, Avila DS, Bridi JC, Saurin S, Lugokenski TH, Villarinho JG, et al.
Low concentrations of methamidophos do not alter AChE activity but modulate neurotransmitters uptake in hippocampus and striatum in vitro
. Life Sci 2011;88:89-95.
Mohammadi M, Ghani E, Ghasemi A, Khoshbaten A, Asgari A. Synaptosomal GABA uptake decreases in paraoxon-treated rat brain. Toxicology 2008;244:42-8.
Crowley CL, Payne CM, Bernstein H, Bernstein C, Roe D. The NAD+ precursors, nicotinic acid and nicotinamide protect cells against apoptosis induced by a multiple stress inducer, deoxycholate. Cell Death Differ 2000;7:314-26.
Klaidman LK, Mukherjee SK, Adams JD Jr. Oxidative changes in brain pyridine nucleotides and neuroprotection using nicotinamide. Biochim Biophys Acta 2001;1525:136-48.
Sakakibara Y, Mitha AP, Ayoub IA, Ogilvy CS, Maynard KI. Delayed treatment with nicotinamide (Vitamin B3) reduces the infarct volume following focal cerebral ischemia in spontaneously hypertensive rats, diabetic and non-diabetic Fischer 344 rats. Brain Res 2002;931:68-73.
Hawkins RA, Williamson DH, Krebs HA. Ketone-body utilization by adult and suckling rat brain in vivo
. Biochem J 1971;122:13-8.
Robinson AM, Williamson DH. Physiological roles of ketone bodies as substrates and signals in mammalian tissues. Physiol Rev 1980;60:143-87.
Fukushima T, Iizuka H, Yokota A, Suzuki T, Ohno C, Kono Y, et al.
Quantitative analyses of schizophrenia-associated metabolites in serum: Serum D-lactate levels are negatively correlated with gamma-glutamylcysteine in medicated schizophrenia patients. PLoS One 2014;9:e101652.
[Figure 1], [Figure 2], [Figure 3], [Figure 4], [Figure 5], [Figure 6], [Figure 7], [Figure 8]
[Table 1], [Table 2], [Table 3], [Table 4]