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基于阴阳理论阐明金匮肾气丸与明目地黄丸治疗糖尿病肾病的差异机制
Authors Bi S, Xu Z, Yuan A, Wang Z, Liu Y, Yu B, Tian J, Liu C, Qiao L, Wang Z, Zhang Y
Received 12 January 2025
Accepted for publication 3 April 2025
Published 10 April 2025 Volume 2025:19 Pages 2817—2831
DOI http://doi.org/10.2147/DDDT.S517143
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 2
Editor who approved publication: Dr Tuo Deng
Shijie Bi,1,* Zhenzhen Xu,1,* Anlei Yuan,1 Zewen Wang,1 Yanxia Liu,1 Bin Yu,1 Jiaye Tian,1 Chaoqun Liu,1 Liansheng Qiao,1 Zhibin Wang,2 Yanling Zhang1
1Key Laboratory of TCM-information Engineer of State Administration of TCM, School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing, 102488, People’s Republic of China; 2Beijing Tong Ren Tang Technology Development Co., Ltd, Beijing, 100000, People’s Republic of China
*These authors contributed equally to this work
Correspondence: Yanling Zhang, Email zhangyanling@bucm.edu.cn Zhibin Wang, Email wangzhibin4804@126.com
Background: The Yin-Yang attributes of MMDH and JGSQ in treating diabetic nephropathy (DN) remain unexplored.
Methods: UPLC-MS identified formula components, network pharmacology analyzed common DN targets, and in vitro renal fibrosis models assessed efficacy. Transcriptomics revealed key pathways, and molecular docking simulated component-target interactions.
Results: UPLC-MS confirmed the compositional complexity of MMDH and JGSQ. Network pharmacology indicated their involvement in multiple DN-related pathways. In vitro, JGSQ alleviated fibrosis and enhanced adhesion via FN and E-cad, while MMDH reduced interstitial fibrosis via FN and VIM. Transcriptomics showed JGSQ regulates the TGF-β pathway, and MMDH modulates the TNF pathway. Molecular docking confirmed key components binding to TGFB1 and TNFA.
Conclusion: MMDH and JGSQ exhibit distinct chemical compositions, targets, and pathways, underscoring their Yin-Yang regulatory roles in kidney function.
Keywords: diabetic nephropathy, Mingmu Dihuang pill, Jingui Shenqi pill, network pharmacology, transcriptomics