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- W3096687029 endingPage "461679" @default.
- W3096687029 startingPage "461679" @default.
- W3096687029 abstract "The quantification of metabolites in various samples, including body fluids, tissues, cells, and foodstuffs, contributes to our understanding of their biological activities and roles in the body, diagnosis for many diseases, drug and biomarker discovery, and many aspects of human health. Liquid chromatography (LC)/tandem mass spectrometry (MS/MS) is the most powerful and reliable methodology for the quantification of metabolites due to its high specificity and sensitivity, and broad coverage of various compounds. Derivatization often makes the quantification power of LC/MS/MS stronger due to the desirable LC behavior and enhanced MS/MS detectability of the derivatized metabolites. On the other hand, LC/MS/MS-based quantification has room for improvement regarding its analysis throughput. Derivatization is also a promising approach to overcome this drawback; the multiplexing of samples in the same LC/MS/MS injection, which is achieved by derivatization of multiple samples with multiple well-designed reagents, can enhance the throughput. Based on this background, this article reviews the derivatization-based sample-multiplexing strategy, especially the characteristics and applications of the derivatization reagents, for the LC/MS/MS quantification of metabolites. This strategy has been used for the relative and absolute quantification of a variety of metabolites, and expansion of the coverage of metabolites." @default.
- W3096687029 created "2020-11-09" @default.
- W3096687029 creator A5014254992 @default.
- W3096687029 creator A5033392956 @default.
- W3096687029 date "2020-12-01" @default.
- W3096687029 modified "2023-10-14" @default.
- W3096687029 title "Derivatization-based sample-multiplexing for enhancing throughput in liquid chromatography/tandem mass spectrometry quantification of metabolites: an overview" @default.
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- W3096687029 doi "https://doi.org/10.1016/j.chroma.2020.461679" @default.
- W3096687029 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/33189958" @default.
- W3096687029 hasPublicationYear "2020" @default.
- W3096687029 type Work @default.