化学
指纹(计算)
主成分分析
偏最小二乘回归
色谱法
抗氧化剂
人工智能
统计
数学
生物化学
计算机科学
作者
Jianguang Zhang,Li Li,Junjun Wang,Wenfang Jin,Yue Wang,Zhifeng Zhang
标识
DOI:10.1016/j.arabjc.2023.104755
摘要
In this study, a fingerprint-activity relationship between ultrahigh performance liquid chromatography (UHPLC) fingerprints and antioxidant activity was established to evaluate the quality of Aster yunnanensis Franch.(AYF) from different collecting spots. First, the fingerprint of AYF was established by UHPLC, and the similarity analysis was analyzed based on twenty-one common peaks. Then the chemical constituents from AYF were analyzed and identified by UHPLC-quadrupole time-of-flight tandem mass spectrometry (QTOF-MS/MS). Next, the antioxidant activity of twelve batches of AYF was assessed in vitro. Subsequently, eleven chemical markers were screened out by fingerprints and antioxidant activity utilizing grey relational analysis (GRA) and partial least squares (PLS). Finally, the contents of eleven chemical markers in twelve batches of AYF were detected by UHPLC, and the antioxidant quality of AYF was evaluated using chemometric analysis, such as principal components analysis (PCA) and technique for order preference by similarity to ideal solution (TOPSIS). The results showed that the antioxidant efficacy was associated with the total content of eleven compounds of AYF. Moreover, this method to discover quality markers was reasonable by fingerprint-activity relationship combination with chemometric analysis. The present study will certify quality markers associated with therapeutic effects, and provide a powerful strategy for evaluating the resource quality of AYF.
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