2022
DOI: 10.1016/j.chroma.2022.463172
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An online stepwise background subtraction-based ultra-high pressure liquid chromatography quadrupole time of flight tandem mass spectrometry dynamic detection integrated with metabolic molecular network strategy for intelligent characterization of the absorbed chemical-fingerprint of QiangHuoShengShi decoction in vivo

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Cited by 4 publications
(2 citation statements)
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“…The contents of chemical components and biological activity of drugs may be changed by steaming, boiling, and frying under different air pressures ( Trakoontivakorn et al, 2012 ; Guo et al, 2022 ). Maillard reaction often occurs in the heat treatment process of food and pharmaceutical, which is the main chemical reaction to produce new flavor and new color in the processing food and Chinese botanical drugs.…”
Section: Applications Of Digital and Intelligent Technologies In Proc...mentioning
confidence: 99%
“…The contents of chemical components and biological activity of drugs may be changed by steaming, boiling, and frying under different air pressures ( Trakoontivakorn et al, 2012 ; Guo et al, 2022 ). Maillard reaction often occurs in the heat treatment process of food and pharmaceutical, which is the main chemical reaction to produce new flavor and new color in the processing food and Chinese botanical drugs.…”
Section: Applications Of Digital and Intelligent Technologies In Proc...mentioning
confidence: 99%
“…Hence, recognizing all the metabolites produced by a drug in vivo and defining their structures is an indispensable step for drug development. Ultra-high-performance liquid chromatography-high-resolution mass spectrometry (UHPLC-HRMS), a powerful analytical technique that has been developed over the past years, is widely used for the metabolic analysis of various Chinese herbal compounds and monomers with its superiority of high sensitivity, high selectivity, and high mass accuracy [16][17][18]. Yet, the signals of numerous trace metabolites are highly susceptible to being overwhelmed by the matrix effects and background noise generated during sample detection.…”
Section: Introductionmentioning
confidence: 99%