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Chen, Z.-L.

Publications and source records attributed to Chen, Z.-L..

2 recordsLinked to original sources

Corilagin controls post-parasiticide schistosome egg-induced liver fibrosis by inhibiting Stat6 signalling pathway

This study aims to explore the effect of Corilagin (Cor) on post-parasiticide schistosome egg-induced hepatic fibrosis through the Stat6 signalling pathway in vitro and in vivo. Cellular and animal models were established and treated by Corilagin. The inhibitory effect of Corilagin was also confirmed in RAW264.7 cells in which Stat6 was overexpressed based on the GV367-Stat6-EGFP lentiviral vector system and in which Stat6 was knock-downed by gene specific siRNAs. As a result, Corilagin prevented increases in the protein level of Phospho-Stat6 (P-Stat6). Both the mRNA and protein levels of the downstream mediators SOCS1, KLF4, and PPAR{gamma}/{delta} were markedly suppressed after Corilagin treatment. Expression of ARG1 and FIZZ1/Retnla, Ym1, TGF-{beta} and PDGF in serum were also inhibited by Corilagin. The pathological changes, area of granulomas of liver sections, and degree of hepatic fibrosis were significantly alleviated in the Corilagin group. The areas of CD68- and CD206-positive cells stained by immunofluorescence were significantly decreased by Corilagin. In conclusion, Corilagin can suppress post-parasiticide schistosome egg-induced hepatic fibrosis by inhibiting the Stat6 signalling pathway and provide a new therapeutic strategy for schistosomiasis liver fibrosis.

pharmacology and toxicology

Open-pFind enables precise, comprehensive and rapid peptide identification in shotgun proteomics

Shotgun proteomics has grown rapidly in recent decades, but a large fraction of tandem mass spectrometry (MS/MS) data in shotgun proteomics are not successfully identified. We have developed a novel database search algorithm, Open-pFind, to efficiently identify peptides even in an ultra-large search space which takes into account unexpected modifications, amino acid mutations, semi- or non-specific digestion and co-eluting peptides. Tested on two metabolically labeled MS/MS datasets, Open-pFind reported 50.5-117.0% more peptide-spectrum matches (PSMs) than the seven other advanced algorithms. More importantly, the Open-pFind results were more credible judged by the verification experiments using stable isotopic labeling. Tested on four additional large-scale datasets, 70-85% of the spectra were confidently identified, and high-quality spectra were nearly completely interpreted by Open-pFind. Further, Open-pFind was over 40 times faster than the other three open search algorithms and 2-3 times faster than three restricted search algorithms. Re-analysis of an entire human proteome dataset consisting of [~]25 million spectra using Open-pFind identified a total of 14,064 proteins encoded by 12,723 genes by requiring at least two uniquely identified peptides. In this search results, Open-pFind also excelled in an independent test for false positives based on the presence or absence of olfactory receptors. Thus, a practical use of the open search strategy has been realized by Open-pFind for the truly global-scale proteomics experiments of today and in the future.

bioinformatics