Xinjie Zhao

Dalian Institute of Chemical Physics, Lü-ta-shih, Liaoning, China

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Publications (65)159.68 Total impact

  • [Show abstract] [Hide abstract]
    ABSTRACT: Major depressive disorder (MDD) is a debilitating mental disease with a pronounced impact on quality of life of a lot of people. However, it is still difficult in diagnosing MDD accurately. In this study, a non-targeted metabolomics approach based on ultra high performance liquid chromatography equipped with quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF/MS) was used to find the differential metabolites in plasma samples from patients with MDD and healthy controls. Furthermore, a validation analysis focusing on the differential metabolites was performed in another batch of samples using a targeted approach based on dynamic multiple reactions monitoring (MRM) method. Levels of acyl carnitines, ether lipids and tryptophan pronouncedly decreased, whereas LPCs, LPEs and PEs markedly increased in MDD subjects as compared to the healthy controls. Disturbed pathways, mainly located in acyl carnitine metabolism, lipid metabolism, and tryptophan metabolism, were clearly brought to light in MDD subjects. Binary logistic regression result showed that carnitine C10:1, PE-O 36:5, LPE 18:1 sn-2 and tryptophan can be used as a combinational biomarker to distinguish not only moderate but also severe MDD from healthy control with good sensitivity and specificity. Our findings on one hand provide critical insight to pathological mechanism of MDD, on the other hand supply a combinational biomarker to aid the diagnosis of MDD in clinical usage.
    Journal of Proteome Research 03/2015; DOI:10.1021/acs.jproteome.5b00144 · 5.00 Impact Factor
  • 02/2015; 2. DOI:10.3389/fmolb.2015.00004
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    ABSTRACT: Metabolic profiling of silkworm, especially the factors that affect silk synthesis at the metabolic level, is little known. Herein, metabolomic method based on gas chromatography-mass spectrometry was applied to identify key metabolic changes in silk synthesis deficient silkworms. Forty-six differential metabolites were identified in Nd group with the defect of silk synthesis. Significant changes in the levels of glycine and uric acid (up-regulation), carbohydrates and free fatty acids (down-regulation) were observed. The further metabolomics of silk synthesis deficient silkworms by decreasing silk proteins synthesis using knocking out fibroin heavy chain gene or extirpating silk glands operation showed that the changes of the metabolites were almost consistent with those of the Nd group. Furthermore, the increased silk yields by supplying more glycine or its related metabolite confirmed that glycine is a key metabolite to regulate silk synthesis. These findings provide important insights into the regulation between metabolic profiling and silk synthesis. Copyright © 2014. Published by Elsevier Ltd.
    Insect Biochemistry and Molecular Biology 12/2014; 57. DOI:10.1016/j.ibmb.2014.12.007 · 3.42 Impact Factor
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    ABSTRACT: Hepatocellular carcinoma (HCC) is one of the pestilent malignancies leading to cancer-related death. Discovering effective biomarkers for HCC diagnosis is an urgent demand. To identify potential metabolite biomarkers, we developed a urinary pseudo-targeted method based on liquid chromatography-hybrid triple quadrupole linear ion trap mass spectrometry (LC-QTRAP MS). Compared with non-targeted method, the pseudo-targeted method can achieve better data quality which benefits differential metabolites discovery. The established method was applied to cirrhosis (CIR) and HCC investigation. It was found that urinary nucleosides, bile acids, citric acid and several amino acids were significantly changed in liver disease groups compared with the controls, featuring the dysregulation of purine metabolism, energy metabolism and amino metabolism in liver diseases. Furthermore, some metabolites such as cyclic adenosine monophosphate (AMP), glutamine, short- and medium-chain acylcarnitines were the differential metabolites of HCC and CIR. Based on binary logistic regression, butyrylcarnitine (carnitine C4:0) and hydantoin-5-propionic acid were defined as a combinational marker to distinguish HCC from CIR. The area under curve (AUC) was 0.786 and 0.773 for discovery stage and validation stage samples, respectively. These data show that the established pseudo-targeted method is a complementary one of targeted and non-targeted methods for metabolomics study.
    Journal of Proteome Research 12/2014; 14(2). DOI:10.1021/pr500973d · 5.00 Impact Factor
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    ABSTRACT: Atopic dermatitis (AD) is the most common inflammatory skin disease in children. In the study, ultra high performance liquid chromatography-mass spectrometry was used to investigate serum metabolic abnormalities of AD children. Two batch fasting sera were collected from AD children and healthy control, one of them was for nontargeted metabolomics analysis, the other for targeted eicosanoids analysis. AD children were divided into high immunoglobulin E (IgE) group and normal IgE group. Based on the two analysis approaches, it was found that the differential metabolites of AD, leukotriene B4, prostaglandins, conjugated bile acids, etc. were associated with inflammatory response and bile acids metabolism. Carnitines, free fatty acids and lactic acid etc. increased in the AD group with high IgE, which revealed energy metabolism disorder. Amino acids metabolic abnormalities and increase levels of Cytochrome P450 epoxygenase metabolites were found in the AD group with normal IgE. The results provided a new perspective to understand mechanism and find potential biomarkers of AD, and may provide a new reference for personalized treatment.
    Journal of Proteome Research 10/2014; DOI:10.1021/pr5007069 · 5.00 Impact Factor
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    ABSTRACT: Lung cancer is currently the leading cause of cancer-related mortality worldwide. It is, therefore, important to enhance understanding and add a new auxiliary detection tool of lung cancer. In this work, serum metabolic characteristics of lung cancer were investigated with a non-targeted metabolomics method. The metabolic profiling of 23 patients with lung cancer and 23 healthy controls were analyzed using ultra high performance liquid chromatography/quadrupole time of flight mass spectrometry (UPLC/Q-TOF MS). Partial least squares discriminant analysis (PLS-DA) model of the metabolic data allowed the clear separation of the lung cancer patients from the healthy controls. In total, 27 differential metabolites were identified, which were mostly related to the perturbation of lipid metabolism, including choline, free fatty acids, lysophosphatidylcholines, etc. Choline and linoleic acid were defined as one combinational biomarker using binary logistic regression, which was supported by the validation with a smaller sample-set (9 patients and 9 healthy controls). These findings show that LC/MS-based serum metabolic profiling has potential application in complementary identification of lung cancer patients, and could be a powerful tool for cancer research.
    Journal of chromatography. B, Analytical technologies in the biomedical and life sciences 05/2014; DOI:10.1016/j.jchromb.2014.04.047 · 2.69 Impact Factor
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    ABSTRACT: Polycystic ovary syndrome (PCOS) is a complex, heterogeneous disorder, which seriously impacts the health of reproductive age women. Thus reasonable individual-based treatment is important. In this study, the serum samples of 15 overweight PCOS patients before and after treatment with berberine for three months were collected for clinic biochemical test and metabolomic research. Metabolomic profiling based on ultra high performance liquid chromatography (UHPLC) coupled with quadrupole time-of-flight mass spectrometry (q-TOF MS) was used to investigate metabolic changes of PCOS. Compared with before treatment, the patients after berberine treatment can be separated into distinct clusters as displayed by the orthogonal signal correction partial least-squares discriminant analysis (OSC-PLS-DA) score plot with model parameter: R2Y = 0.892, Q2 (cum) = 0.577, which indicated changes in metabolites after berberine treatment. The differential metabolites related to berberine treatment were selected when their variable importance values were more than 1, and p < 0.05 with nonparametric test. These differential metabolites were all involved in lipids metabolism, including phosphatidylcholines, sphingomyelin, stearic acid and erucamide. The pharmacological results and metabolomic data revealed that berberine can strengthen the sensitivity of insulin and rectify the dyslipidemia of overweight PCOS patients. This study also illustrates that the LC-MS based metabolomic method is helpful for evaluating the treatment of traditional Chinese medicines.
  • Xinjie Zhao, Jihong Chen, Lei Ye, Guowang Xu
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    ABSTRACT: Acute graft rejection is one of the most common and serious post complications in renal transplantation. Non-invasive method is needed to specifically monitor acute graft rejection. We investigated metabolic alterations of acute graft rejection in human renal transplantation by applying a metabolomics approach. Sera from 11 acute graft rejection subjects and 16 non-acute graft rejection subjects were analyzed by a non-targeted liquid chromatography-mass spectrometry (LC-MS) metabolomics approach including both hydrophilic interaction chromatography and reversed-phase liquid chromatography separations. Discriminative metabolites of acute graft rejection after transplantation were detected including creatinine, kynurenine, uric acid, poly-unsaturated fatty acid, phosphatidylcholines, sphingomyelins, lysophosphatidylcholines, etc. The lower level of serum dehydroepiandrosterone sulfate was found in acute graft rejection group before transplantation. The results revealed comprehensive metabolic abnormalities in acute graft rejection. The findings are valuable for the clinic noninvasive diagnosis or therapy of acute graft rejection.
    Journal of Proteome Research 03/2014; 13(5). DOI:10.1021/pr5001048 · 5.00 Impact Factor
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    ABSTRACT: Polycystic ovary syndrome (PCOS) is a complex, heterogeneous disorder, which produces in 5%-10% reproductive age women. In this study, a non-targeted metabolomics approach based on ultra high-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry is used to investigate serum metabolic characteristics of PCOS. PCOS women and healthy control can be clustered into two distinct groups based on multivariate statistical analysis. Significant increase in the levels of unsaturated free fatty acids, fatty acid amides, sulfated steroids, glycated amino acid and the decrease in levels of lysophosphatidylcholines, lysophosphatidylethanolamines etc. were found. These metabolites showed abnormalities of lipid- and androgen-metabolism, increase of stearoyl -CoA desaturase (SCD) activity and accumulation of advanced glycation end-products in PCOS patients. Based on the binary logistic regression model, free fatty acid (FFA) 18:1/FFA 18:0, FFA 20:3, dihydrotestosterone sulfate, glycated phenylalanine and uridine were combined as a diagnostic biomarker. The area under the curve (AUC) of combinational biomarker was 0.839 in 131 discovery phase samples, and 0.874 in 109 validation phase samples. The findings of our study offer a new insight to understand the pathogenesis mechanism, and the discriminating metabolites may provide a prospect for PCOS diagnosis.
    Journal of Proteome Research 01/2014; 13(2). DOI:10.1021/pr401130w · 5.00 Impact Factor
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    ABSTRACT: Lung cancer is currently the leading cause of cancer-related mortality worldwide. It is, therefore, important to enhance understanding and add a new auxiliary detection tool of lung cancer. In this work, serum metabolic characteristics of lung cancer were investigated with a non-targeted metabolomics method. The metabolic profiling of 23 patients with lung cancer and 23 healthy controls were analyzed using ultra high performance liquid chromatography/quadrupole time of flight mass spectrometry (UPLC/Q-TOF MS). Partial least squares discriminant analysis (PLS-DA) model of the metabolic data allowed the clear separation of the lung cancer patients from the healthy controls. In total, 27 differential metabolites were identified, which were mostly related to the perturbation of lipid metabolism, including choline, free fatty acids, and lysophosphatidylcholines etc. Choline and linoleic acid were defined as one combinational biomarker using binary logistic regression, which was supported by the validation with a smaller sample-set (9 patients and 9 healthy controls). These findings show that LC/MS-based serum metabolic profiling has potential application in complementary identification of lung cancer patients, and could be a powerful tool for cancer research
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    ABSTRACT: Sphingolipids are a family of bioactive molecules with high structural diversity and complexity. They not only serve as integral components of cellular membrane, but also play pivotal roles in signaling and other cellular events. It is desirable for the development of sensitive, robust and structural-specific analytical approaches enabling rapid determination of as many sphingolipid species as possible. Herein we present an analytical method for large-scaled profiling of sphigolipids in human serum, which consisted of an improved extraction protocol using tert-butyl methyl ether combined with mild alkaline hydrolysis, and an ultra high performance reversed-phase liquid chromatography-dynamic multiple reaction monitoring-mass spectrometric (RPLC-dynamic MRM-MS) method. In total 84 endogenous sphingolipid species covering six subcategories (i.e. free sphingoid base, dihydroceramide, ceramide, hexosylceramide, lactosylceramide, and sphingomyelin), were separated and quantified in a single run within 10min. A broad linear range over 2.5-4 orders of magnitude (r(2)>0.99), a limit of detection of 0.01-0.17pmol/mL, and a limit of quantitation of 0.02-0.42pmol/mL were obtained for each subcategory. Average recovery of each subcategory was within 85.6-95.6%. Median values of coefficient of variation (CV) of all detected 84 sphingolipids were 3.9% and 6.8% for intraday and interday precision, respectively. This method was exemplarily applied in a study regarding dysregulated sphingolipid homeostasis in hepatocellular carcinoma. The establishment of this method provides a useful tool for serum-based high throughput screening of sphingolipid biomarkers and mechanism investigation of sphingolipid metabolic regulation in human disease.
    Journal of Chromatography A 10/2013; 1320. DOI:10.1016/j.chroma.2013.10.064 · 4.26 Impact Factor
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    ABSTRACT: In this study, an ultra fast LC/IT-TOF MS (UFLC/IT-TOF MS)-based serum lipidomics method was employed to characterize the serum lipid profile of patients with chronic hepatitis B, cirrhosis, and hepatocellular carcinoma (HCC). After data collection and processing, 96 lipids including lysophosphatidylcholines, phosphatidylcholines, sphingomyelins, triacylglycerides, and cholesterol esters were identified and used for subsequent data analysis. Partial least squares-discriminant analysis revealed that patients with liver diseases had distinctly different serum lipid profile from that of healthy controls; while cirrhosis and HCC patients had a similar serum lipid profile, but different from that of hepatitis patients. The ANOVA analysis found 75 of the 96 identified lipids to be abnormally regulated, among which most of these lipids were downregulated in cirrhosis and HCC patients compared with those of healthy controls and hepatitis patients, while hepatitis patients induced several lipids downregulated and others upregulated compared with those of healthy controls, indicating the aberrant lipid metabolism in patients with liver diseases. This work demonstrated the utility of UFLC/IT-TOF MS-based serum lipidomics as a powerful tool to investigate the lipid metabolism of liver diseases.
    Electrophoresis 07/2013; 34(19):2848-56. DOI:10.1002/elps.201200629 · 3.16 Impact Factor
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    ABSTRACT: A common challenge for scientists working with animal tissue or human biopsy samples is the limitation of material and consequently, the difficulty to perform comprehensive metabolic profiling within one experiment. Here, we present a novel approach to simultaneously perform targeted and non-targeted metabolomics as well as lipidomics from one small piece of liver or muscle tissue by ultra-high performance liquid chromatography/mass spectrometry (UHPLC/MS) following a methyl tert-butyl ether (MTBE)-based extraction. Equal relative amounts of the resulting polar and non-polar fractions were pooled, evaporated and reconstituted in the appropriate solvent for UHPLC/MS analysis. This mix was comparable or superior in yield and reproducibility to a standard 80% methanol extraction for the profiling of polar and lipophilic metabolites (free carnitine, acylcarnitines and FFA). The mix was also suitable for non-targeted metabolomics, an easy measure to increase the metabolite coverage by 30% relative to using the polar fraction alone. Lipidomics was performed from an aliquot of the non-polar fraction. This novel strategy could successfully be applied to one mouse soleus muscle with a dry weight of merely 2.5mg. By enabling a simultaneous profiling of lipids and metabolites with mixed polarity while saving material for molecular, biochemical or histological analyses, our approach may open up new perspectives toward a comprehensive investigation of small, valuable tissue samples.
    Journal of Chromatography A 05/2013; 1298. DOI:10.1016/j.chroma.2013.05.019 · 4.26 Impact Factor
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    ABSTRACT: Context:Acylcarnitines are biomarkers of incomplete β-oxidation and mitochondrial lipid overload but indicate also high rates of mitochondrial fatty acid oxidation. It is unknown whether the production of acylcarnitines in primary human myotubes obtained from lean, metabolically healthy subjects reflects the fat oxidation in vivo.Objective:Our objective was to quantify the acylcarnitine production in myotubes obtained from subjects with low and high fasting respiratory quotient (RQ).Methods:Fasting RQ was determined by indirect calorimetry. Muscle biopsies from the vastus lateralis muscle were taken from 6 subjects with low fasting RQ (mean 0.79 ± 0.03) and 6 with high fasting RQ (0.90 ± 0.03), and satellite cells were isolated, cultured, and differentiated to myotubes. Myotubes were cultivated with 125μM (13)C-labeled palmitate for 30 minutes and 4 and 24 hours. Quantitative profiling of 42 intracellular and 31 extracellular acylcarnitines was performed by stable isotope dilution-based metabolomics analysis by liquid chromatography coupled to mass spectrometry.Results:Myotubes from donors with high fasting RQ produced and released significant higher amounts of medium-chain acylcarnitines. High (13)C8 and (13)C10 acylcarnitine levels in the extracellular compartment correlated with high fasting RQ. The decreased expression of medium-chain acyl-coenzyme A dehydrogenase (MCAD) in these myotubes can explain the higher rate of incomplete fatty acid oxidation. A lower intracellular [(13)C]acetylcarnitine to carnitine and lower intracellular (13)C16/(13)C18 acylcarnitine to carnitine ratio indicate reduced fatty acid oxidation capacity in these myotubes. Mitochondrial DNA content was not different.Conclusion:Acylcarnitine production and release from primary human myotubes of donors with high fasting RQ indicate a reduced fatty acid oxidation capacity and a higher rate of incomplete fatty acid oxidation. Thus, quantitative profiling of acylcarnitine production in human myotubes can be a suitable tool to identify muscular determinants of fat oxidation in vivo.
    The Journal of Clinical Endocrinology and Metabolism 04/2013; 98(6). DOI:10.1210/jc.2012-3976 · 6.31 Impact Factor
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    ABSTRACT: Investigations of complex metabolic mechanisms and networks have become a focus of research in the post-genomic area, thereby creating an increasing demand for sophisticated analytical approaches. One such tool are lipidomics analyses that provide a detailed picture of the lipid composition of a system at a given time. Introducing stable isotopes into the studied system can additionally provide information on the synthesis, transformation and degradation of individual lipid species. Capturing the entire dynamics of lipid networks, however, is still a challenge. We developed and evaluated a novel strategy for the in-depth analysis of the dynamics of lipid metabolism with the capacity for high molecular specificity and network coverage. The general workflow consists of stable isotope-labeling experiments, ultra high-performance liquid chromatography (UHPLC)-high resolution Orbitrap-MS lipid profiling and data processing by a software tool for global isotopomer filtering and matching. As a proof of concept, this approach was applied to the network-wide mapping of dynamic lipid metabolism in primary human skeletal muscle cells cultured for 4, 12 and 24 h with [U-13C]-palmitate. In the myocellular lipid extracts 692 isotopomers were detected that could be assigned to 203 labeled lipid species spanning 12 lipid (sub-) classes. Interestingly, some lipid classes showed high turnover rates but stable total amounts while the amount of others increased in the course of palmitate treatment. The novel strategy presented here has the potential to open new detailed insights into the dynamics of lipid metabolism that may lead to a better understanding of physiological mechanisms and metabolic perturbations.
    Analytical Chemistry 03/2013; 85(9). DOI:10.1021/ac400293y · 5.83 Impact Factor
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    ABSTRACT: BACKGROUND: Metabolomics is a powerful tool that is increasingly used in clinical research. Although excellent sample quality is essential, it can easily be compromised by undetected preanalytical errors. We set out to identify critical preanalytical steps and biomarkers that reflect preanalytical inaccuracies.METHODS: We systematically investigated the effects of preanalytical variables (blood collection tubes, hemolysis, temperature and time before further processing, and number of freeze-thaw cycles) on metabolomics studies of clinical blood and plasma samples using a nontargeted LC-MS approach.RESULTS: Serum and heparinate blood collection tubes led to chemical noise in the mass spectra. Distinct, significant changes of 64 features in the EDTA-plasma metabolome were detected when blood was exposed to room temperature for 2, 4, 8, and 24 h. The resulting pattern was characterized by increases in hypoxanthine and sphingosine 1-phosphate (800% and 380%, respectively, at 2 h). In contrast, the plasma metabolome was stable for up to 4 h when EDTA blood samples were immediately placed in iced water. Hemolysis also caused numerous changes in the metabolic profile. Unexpectedly, up to 4 freeze-thaw cycles only slightly changed the EDTA-plasma metabolome, but increased the individual variability.CONCLUSIONS: Nontargeted metabolomics investigations led to the following recommendations for the preanalytical phase: test the blood collection tubes, avoid hemolysis, place whole blood immediately in ice water, use EDTA plasma, and preferably use nonrefrozen biobank samples. To exclude outliers due to preanalytical errors, inspect the biomarker signal intensities reflecting systematic as well as accidental and preanalytical inaccuracies before processing the bioinformatics data.
    Clinical Chemistry 02/2013; 59(5). DOI:10.1373/clinchem.2012.199257 · 7.77 Impact Factor
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    ABSTRACT: In a non-hypothesis driven metabolomics approach plasma samples collected at six different time points (before, during and after an exercise bout) were analyzed by gas chromatography-time of flight mass spectrometry (GC-TOF MS). Since independent component analysis (ICA) does not need a priori information on the investigated process and moreover can separate statistically independent source signals with non-Gaussian distribution, we aimed to elucidate the analytical power of ICA for the metabolic pattern analysis and the identification of key metabolites in this exercise study. A novel approach based on descriptive statistics was established to optimize ICA model. In the GC-TOF MS data set the number of principal components after whitening and the number of independent components of ICA were optimized and systematically selected by descriptive statistics. The elucidated dominating independent components were involved in fuel metabolism, representing one of the most affected metabolic changes occurring in exercising humans. Conclusive time dependent physiological changes of the metabolic pattern under exercise conditions were detected. We conclude that after optimization ICA can successfully elucidate key metabolite pattern as well as characteristic metabolites in metabolic processes thereby simplifying the explanation of complex biological processes. Moreover, ICA is capable to study time series in complex experiments with multi-levels and multi-factors.
    Journal of chromatography. B, Analytical technologies in the biomedical and life sciences 07/2012; 910. DOI:10.1016/j.jchromb.2012.06.030 · 2.69 Impact Factor
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    ABSTRACT: Acute graft rejection is one of the most common and serious post complications in renal transplantation, noninvasive diagnosis of acute graft rejection is essential for reducing risk of surgery and timely treatment. In this study, a non-targeted metabonomics approach based on ultra performance liquid chromatography (UPLC) coupled with quadrupole time-of-flight mass spectrometry (MS) is used to investigate the effect of acute graft rejection in rat renal transplantation on metabolism. To collect more metabolite information both hydrophilic interaction chromatography and reversed-phase liquid chromatography were used. Using the partial least squares-discriminant analysis, we found that the change of metabonome in a sham-operated group and a non-graft rejection group had a similar trend, while that of the acute graft rejection group was clearly different. Several discriminating metabolites of the acute graft rejection were identified, including creatinine, phosphatidyl-cholines, lyso-phosphatidylcholines, carnitine C16:0, free fatty acids and indoxyl sulfate etc. These discriminating metabolites suggested that acute graft rejection in renal transplantation can lead to the accumulation of creatinine in the body, and also the abnormal metabolism of phospholipids. These findings are useful to understand the mechanisms of the rejection, it also means that a UPLC-MS metabonomic approach is a suitable tool to investigate the metabolic abnormality in the acute graft rejection in renal transplantation.
    Molecular BioSystems 03/2012; 8(3):871-8. DOI:10.1039/c2mb05454j · 3.18 Impact Factor
  • 12/2011; 2(Supplement A):A173-A178. DOI:10.5355/JAST.2011.A173

Publication Stats

1k Citations
159.68 Total Impact Points

Institutions

  • 2005–2014
    • Dalian Institute of Chemical Physics
      Lü-ta-shih, Liaoning, China
  • 2013
    • Technical Institute of Physics and Chemistry
      Peping, Beijing, China
  • 2006–2013
    • Chinese Academy of Sciences
      • • Laboratory of Analytical Chemistry for Life Science
      • • Dalian Institute of Chemical Physics
      Peping, Beijing, China
    • Shanghai Jiao Tong University
      • State Key Laboratory of Oncogenes and Related Genes
      Shanghai, Shanghai Shi, China
  • 2011
    • Second Military Medical University, Shanghai
      • International Cooperation Laboratory on Signal Transduction
      Shanghai, Shanghai Shi, China
  • 2008
    • Nanjing General Hospital
      Nan-ching, Jiangsu Sheng, China