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• W2889133751 abstract "Targeted quantification and untargeted global profiling are the two mainstream approaches, a merging of which could provide enhanced analytical potential in metabolomics research. Here, a simultaneous targeted quantification and untargeted metabolomics (STQUM) strategy was developed for more efficient, accurate and comprehensive metabolomics research by using ultra-high-performance liquid chromatography coupled with high-resolution tandem mass spectrometry (UPLC-HRMS/MS). First, we selected 110 cancer-related metabolites as targets and established a dual LC sequential separation method for simultaneous analysis of strong and weak polar metabolites. In order to achieve efficient acquisition for synchronous qualitative and quantitative analysis, high-resolution, data-dependent parallel reaction monitoring (PRM) method and data-independent all ion fragmentation (AIF) method were established. Their performance in targeted confirmation and quantification, and untargeted analysis were systematically investigated and assessed. In total, 78 metabolites were confidently confirmed in positive ion mode in both PRM and AIF assays, in which 73 metabolites can be accurately quantified. In addition, simultaneously untargeted profiling of 4651 features of high reliability and validity were achieved. Both AIF and PRM methods revealed high confidence, sensitivity and accuracy. In the STQUM approach, another 15 metabolites could be accurately quantified in negative ion mode. The method offers a new perspective for merging the hypothesis-based targeted quantitative validation and untargeted biomarkers discovery in one run for improved analysis efficiency and integrity." @default.
• W2889133751 created "2018-09-07" @default.
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• W2889133751 date "2018-12-01" @default.
• W2889133751 modified "2023-09-24" @default.
• W2889133751 title "Development of simultaneous targeted metabolite quantification and untargeted metabolomics strategy using dual-column liquid chromatography coupled with tandem mass spectrometry" @default.
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• W2889133751 doi "https://doi.org/10.1016/j.aca.2018.08.042" @default.
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• W2889133751 hasPublicationYear "2018" @default.
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