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Articles by Z. Yuan
Total Records ( 2 ) for Z. Yuan
  Q Liu , Z Dai , Z Liu , X Liu , C Tang , Z Wang , G Yi , L Liu , Z Jiang , Y Yang and Z. Yuan

It has been reported that oxidized low-density lipoprotein (Ox-LDL) can increase the expression of adipophilin. However, the detailed mechanisms are not fully understood. The aim of this study was to investigate the mechanism of Ox-LDL on adipophilin expression and the intracellular lipid droplet accumulation. A mouse macrophage-like cell line, RAW264.7, was used throughout, and it was found that Ox-LDL induced adipophilin expression in a dose-dependent manner. Moreover, Ox-LDL induced peroxisome proliferator-activated receptor- (PPAR) expression and PPAR-specific inhibitor T0070907 abrogated Ox-LDL-induced adipophilin expression, but specific agonist GW1929 not. Furthermore, Ox-LDL induced phosphorylation of ERK1/2, and ERK1/2-specific inhibition by PD98059 suppressed the Ox-LDL-induced PPAR and adipophilin expression. The results showed that ERK1/2 or PPAR-specific inhibition decreased the amounts of intracellular lipid droplets. Meanwhile, the PPAR-specific agonist increased intracellular lipid droplets. These results suggested that Ox-LDL-induced increase in adipophilin level via ERK1/2 activation is one of the mechanisms of inducing greater amounts of intracellular lipid droplets in RAW264.7 cells, which indicated that adipophilin is involved in atherosclerotic progression.

  L Zhang , X Jia , X Peng , Q Ou , Z Zhang , C Qiu , Y Yao , F Shen , H Yang , F Ma , J Wang and Z. Yuan

This paper presents an liquid chromatography (LC)/mass spectrometry (MS)-based metabonomic platform that combined the discovery of differential metabolites through principal component analysis (PCA) with the verification by selective multiple reaction monitoring (MRM). These methods were applied to analyze plasma samples from liver disease patients and healthy donors. LC–MS raw data (about 1000 compounds), from the plasma of liver failure patients (n = 26) and healthy controls (n = 16), were analyzed through the PCA method and a pattern recognition profile that had significant difference between liver failure patients and healthy controls (P < 0.05) was established. The profile was verified in 165 clinical subjects. The specificity and sensitivity of this model in predicting liver failure were 94.3 and 100.0%, respectively. The differential ions with m/z of 414.5, 432.0, 520.5, and 775.0 were verified to be consistent with the results from PCA by MRM mode in 40 clinical samples, and were proved not to be caused by the medicines taken by patients through rat model experiments. The compound with m/z of 520.5 was identified to be 1-Linoleoylglycerophosphocholine or 1-Linoleoylphosphatidylcholine through exact mass measurements performed using Ion Trap–Time-of-Flight MS and METLIN Metabolite Database search. In all, it was the first time to integrate metabonomic study and MRM relative quantification of differential peaks in a large number of clinical samples. Thereafter, a rat model was used to exclude drug effects on the abundance of differential ion peaks. 1-Linoleoylglycerophosphocholine or 1-Linoleoylphosphatidylcholine, a potential biomarker, was identified. The LC/MS-based metabonomic platform could be a powerful tool for the metabonomic screening of plasma biomarkers.

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