Chromatographic fingerprint combined with quantitative analysis of multi‐components by single‐marker for quality control of total lignans from Fructus arctii by high‐performance liquid chromatography

Phytochemical Analysis(2022)

引用 2|浏览1
暂无评分
摘要
Introduction The total lignans from Fructus arctii (TLFA) is a mixture of a series of lignans isolated from dried ripe fruit of Arctium lappa L. We previously reported on the pharmacological activity of TLFA that is related to diabetes. An accurate and practical TLFA quantitative analysis method for utilising it needs to be established. Objective This study aimed to develop an effective quantitative analysis method for assessing the TLFA quality. Methods A total of 11 marker components were confirmed by analysing the high-performance liquid chromatography fingerprints of 24 batches of TLFA samples. The samples were prepared from TLFA and structurally identified as lappaol H, lappaol C, arctiin, arctignan D, arctignan E, matairesinol, arctignan G, isolappaol A, lappaol A, arctigenin, and lappaol F. In the quantitative analysis of multi-components by the single-marker (QAMS) method and with arctiin as an internal reference substance, the content of these lignans in TLFA was simultaneously determined according to their relative correction factors with arctiin. Results There was no significant difference between results measured by the QAMS and traditional external standard methods. Hierarchical cluster and principal component analyses were performed to evaluate 24 TLFA batches based on the contents of 10 marker components. The results revealed that QAMS method combined with chemometric analyses could accurately measure and clearly distinguish the different quality samples of TLFA. Conclusion The QAMS method is a reliable and promising quality control method for TLFA. It can provide a reference for promoting quality control of complex multi-component systems, especially for traditional Chinese medicine.
更多
查看译文
关键词
arctiin,fingerprint,Fructus arctii,quality evaluation,quantitative analysis of multi-components by single marker
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要