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Yu Cheng

Researcher at Shanghai Jiao Tong University

Publications -  15
Citations -  527

Yu Cheng is an academic researcher from Shanghai Jiao Tong University. The author has contributed to research in topics: Amino acid & Metabolite. The author has an hindex of 7, co-authored 15 publications receiving 425 citations. Previous affiliations of Yu Cheng include East China Normal University & Shanghai University.

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Distinct urinary metabolic profile of human colorectal cancer.

TL;DR: These findings confirm distinct urinary metabolic footprints of CRC patients characterized by altered levels of metabolites derived from gut microbial-host co-metabolism and provide a novel and promising molecular diagnostic approach for the early detection of CRC.
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Metabonomics identifies serum metabolite markers of colorectal cancer.

TL;DR: A follow-up replication study aiming to identify a distinct serum metabolic signature of CRC with diagnostic potential demonstrated that a panel of serum metabolite markers is of great potential as a noninvasive diagnostic method for the detection of CRC.
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Metabolic Fate of Tea Polyphenols in Humans

TL;DR: This study demonstrates that the metabonomic strategy will enable us to integrate the overwhelming amount of metabolic end points as a systems' response to the absorption, metabolism, and disposition of a multicomponent botanical intervention system, leading to a direct elucidation of their mechanisms of action.
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An ultrasonication-assisted extraction and derivatization protocol for GC/TOFMS-based metabolite profiling

TL;DR: An ultrasonication-assisted protocol is reported which reduces the derivatization time from hours to about 30 min and significantly enhances the deriv atization efficiency prior to a GC/TOFMS analysis.
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A simultaneously quantitative profiling method for 40 endogenous amino acids and derivatives in cell lines using hydrophilic interaction liquid chromatography coupled with tandem mass spectrometry

TL;DR: This quantified analytical method meets the requirement of quantification in specific expanded metabolomics studies with good sensitivity and was successfully applied to the analysis of amino acids and their derivatives in breast cancer cell samples.