Research and development practice of traditional Chinese medicine based on network target theory and technology / 中国中药杂志

Network targets theory and technology have transcended the limitations of the "single gene, single target" model, aiming to decipher the mechanisms of traditional Chinese medicine(TCM) based on biological network from the perspective of informatics and system. As the core of TCM network pharmacology, with the development of computer science and high-throughput experimental techniques, the network target theory and technology are beginning to exhibit a trend of organic integration with artificial intelligence technology and high-throughput multi-modal multi-omics experimental techniques. Taking the network target analysis of TCM like Yinqiao Qingre Tablets as a typical case, network target theory and technology have achieved the systematic construction, in-depth analysis, and high-throughput multi-modal multi-omics validation of multi-level biological networks spanning from traditional Chinese and Western phenotypes to tissues, cells, molecules, and traditional Chinese and Western medicines. This development helps to address critical issues in the analysis of mechanisms of TCM, including the discovery of key targets, identification of functional components, discovery of synergistic effects among compound ingredients, and elucidation of the regulatory mechanisms of formulae. It provides powerful theoretical and technological support for advancing clinical precision diagnosis and treatment, precise positioning of TCM, and precise research and development of TCM. Thus, a new paradigm of TCM research gradually emerges, combining big data and artificial intelligence(AI) with the integration of human experience and scientific evidence.

Research on chemical constituents from Artemisia annua Ⅰ / 中国中药杂志

Chemical constituents were isolated and purified from the water extract of Artemisia annua by column chromatography of HP-20 macroporous resin, silica gel, ODS, Sephadex LH-20, HW-40, and semi-preparative RP-HPLC. Their structures were elucidated by physicochemical properties and spectral analyses. As a result, Fifteen compounds were isolated and identified as vitexnegheteroin M(1), sibricose A5(2), securoside A(3), citrusin D(4), annphenone(5), E-melilotoside(6), esculetin(7), scopoletin-7-O-β-D-glucoside(8), eleutheroside B_1(9), chrysosplenol D(10), patuletin-3-O-β-D-glucopyranoside(11), quercetin-7-O-β-D-glucoside(12), rutin(13), apigenin 6,8-di-C-β-D-glucopyranoside(14), isoschaftoside(15), among them, compounds 1-4 were identified from Artemisia for the first time. Additionally, the isolates were evaluated for their inhibitory effects on the production of PGE_2 in LPS-simulated RAW264.7 macrophages. The results showed that compounds 1, 2, 8, and 10-15 could reduce PGE_2 levels, to a certain extent.