Profiling and analysis of multiple constituents in Crataegi Fructus before and after processing by ultrahigh‐performance liquid chromatography quadrupole time‐of‐flight mass spectrometry

化学 四极飞行时间 色谱法 质谱法 主成分分析 化学成分 串联质谱法 人工智能 计算机科学
作者
Qianqian Xue,Yulin Wang,Chenghao Fei,Chenchen Ren,Wenjing Li,Weidong Li,Fangzhou Yin,Lin Li
出处
期刊:Rapid Communications in Mass Spectrometry [Wiley]
卷期号:35 (7): e9033-e9033 被引量:13
标识
DOI:10.1002/rcm.9033
摘要

RATIONALE: Crataegi Fructus (CF) is one of the most commonly used herbal medicines with a long history of clinical applications. CF is often processed to minimize gastric membrane irritation, although differently processed products can have different biological effects. The purpose of this study was to comprehensively identify the chemical composition of CF, determine the changes caused by processing, and elucidate the active constituents causing the clinical effects. This study aimed to define a theoretical basis for intensive mechanistic studies of CF processing and its reasonable clinical applications. METHODS: An optimized ultrahigh-performance liquid chromatography quadrupole time-of-flight mass spectrometry (UHPLC/QqTOFMS) method in positive and negative ion modes, coupled with multivariate statistical analyses, was developed for the identification and analysis of chemical components in raw and processed products of CF. RESULTS: A total of 87 compounds were identified, including 61 marker compounds that were found to be primary contributors to the significant differences (p < 0.01) between raw and processed products using principal component analysis, t-test, and Venn analysis. The conversion mechanism for a subset of the changed compounds was inferred by analyzing 25 unique differential components between the raw and processed CF. CONCLUSIONS: A rapid and efficient analytical method for identifying the chemical components in CF before and after processing was successfully established. We show how the changes in the chemical constituents in processed CF could be investigated using multivariate statistical analysis methods, and thus facilitate understanding of the processing mechanism of CF.
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