five

Supplementary information.xlsx

收藏
Figshare2023-02-17 更新2026-04-08 收录
下载链接:
https://figshare.com/articles/dataset/Supplementary_information_xlsx/22110584/1
下载链接
链接失效反馈
官方服务:
资源简介:
Traditional Chinese medicine (TCM) has a wide range of clinical applications and good efficacy. However, due to the inherent multi-level, multi-linked, and multi-dimensional non-linear synergistic action characteristics, explaining the mechanism of action (MOA) of TCM in the treatment of diseases still faces great challenges. Therefore, a systematic and applicable research strategy that suits the therapeutic characteristics of TCM is urgently needed. Liu <em>et al.</em> proposed the Quality marker (Q-marker) opinion to monitor and evaluate the qualities of TCM products, which has significantly promoted the development of TCM in recent years. In this study, a Q-marker screening strategy for TCM formula which emphasizes efficacy and biological activities was proposed. In principle, we have integrated absorption, distribution, metabolism, and excretion (ADME) studies, systems biology, and experimental verification in the Q-marker screening workflow. Qianghuo Shengshi decoction (QHSSD) in treating rheumatoid arthritis (RA) was taken as an example to screen Q-markers. As a result, five Q-markers with significant<em> in vitro</em> anti-inflammatory effects were screened out from 159 compounds in QHSSD for treating RA, including notopterol, isoliquiritin, imperatorin, cimifugin, and glycyrrhizic acid. Moreover, much instructive information on pharmacological mechanisms was obtained through the integrated analysis of network pharmacology and metabolomics, such as the main targets and pathways that QHSSD plays important roles in the treatment of RA, which provided a research foundation for the further in-depth study of QHSSD. In conclusion, this work illustrates that the strategy is feasible and offers a practical reference model for the systematic research of TCM formula
提供机构:
Wang, Jiao
创建时间:
2023-02-16
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作