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. 2022 Sep 2;17:103. doi: 10.1186/s13020-022-00658-9

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© The Author(s) 2022

Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

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Fig. 5 — Network pharmacology analysis of 29 serum-absorbed constituents of TSMT showing PPI network of 236 disease-drug targets (A), the module of selection of 34 hub targets (B), GO analysis (C), KEGG pathway enrichment (D) and the “Compounds-Targets -Pathways-Disease” network of TSMT in anti-AS mechanism (E) (This network consisted of 215 nodes and 1170 edges. the green elliptical nodes represented 29 active therapeutic ingredients, yellow V Triangle nodes represented 34 overlapped hub gene, red diamond nodes represented 151 signaling pathways and the bright green triangle node represented atherosclerosis disease)