Quality evaluation of Keteling capsules based on fingerprinting, multicomponent quantification, and quantitative prediction

指纹(计算) 绿原酸 计算机科学 活性成分 定量分析(化学) 色谱法 化学 生物系统 人工智能 生物 生物信息学
作者
Ting Yang,Xiang Li,Lili Lan,Dandan Gong,Fan Zhang,Xinrong Liu,Guixia Ling,Guoxiang Sun
出处
期刊:Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy [Elsevier BV]
卷期号:303: 123274-123274 被引量:7
标识
DOI:10.1016/j.saa.2023.123274
摘要

The Keteling capsule (KC) is a traditional Chinese medicine (TCM) made from the dried extract of Ficus microphylla and an appropriate amount of chlorpheniramine maleate. It is widely used to treat cough and relieve asthma. Despite its extensive usage, a rapid and comprehensive quality evaluation strategy for KC remains a challenge. This study introduces an electrochemical fingerprint analysis technique, in addition to the commonly employed HPLC fingerprints, for efficient and convenient quality evaluation. Moreover, a cost-effective, rapid, and accurate multi-component quantification technique known as the "Multi-markers assay by the monolinear method (MAML)" and the "FT-IR quantitative model" were explored. The HPLC fingerprints were evaluated using a systematically quantified fingerprint method, while the electrochemical fingerprints, based on the Belousov-Zhabotinsky oscillation reaction principle, were effectively analyzed and characterized using oxidation induction times and oscillation lifetimes. Multi-component quantitative analysis was carried out through the MAML and FT-IR quantitative models. The HPLC fingerprint successfully classified the 22 samples into eight grades with excellent discrimination. Active ingredient content analysis was achieved using reliable parameters obtained from electrochemical fingerprinting. The no significant difference in the quantitative results proves the accuracy of the MAML method. Additionally, successful FT-IR quantitative prediction models were developed for chlorogenic acid, isovitexin, and chlorpheniramine maleate. This study offers a dependable and effective approach for enhancing the quality control of KC, and it can provide new insights for improving the quality analysis methods in the field of TCM.
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