Home Journals Articles Updates About
CN
image
收藏切换
Integrated machine learning and network pharmacology approach for exploring the material basis of Buyang Huanwu Decoction for ischemic stroke
收藏切换
PDF
Feng WANG1, Qing-qi MENG1, Qing LIU2, Ying LIU3, Lu SUN3, Yan MI1, Dan-yang MU1, Da-kuo HE2, *, Yue HOU1, *
Acta Pharmaceutica Sinica | 2025, 60(3) : 627 - 636
Less
收藏切换
Acta Pharmaceutica Sinica | 2025, 60(3): 627-636
• Special Reports: Multi-disciplinary exploration in the current situation and future direction of the modernization of Traditional Chinese Medicine •
Integrated machine learning and network pharmacology approach for exploring the material basis of Buyang Huanwu Decoction for ischemic stroke
Full
Feng WANG1, Qing-qi MENG1, Qing LIU2, Ying LIU3, Lu SUN3, Yan MI1, Dan-yang MU1, Da-kuo HE2, *, Yue HOU1, *
Affiliations
  • 1. College of Life and Health Sciences, Northeastern University, Key Laboratory of Bioresource Research and Development of Liaoning Province, National Frontiers Science Center for Industrial Intelligence and Systems Optimization, Shenyang 110170, China
  • 2. College of Information Science and Engineering, State Key Laboratory of Synthetical Automation for Process Industries, Shenyang 110004, China
  • 3. School of Pharmacy, Shenyang Pharmaceutical University, Benxi 117004, China
Published: 2025-03-12 doi: 10.16438/j.0513-4870.2024-0971
Outline
收藏切换

The study investigates the therapeutic effects and mechanisms of Buyang Huanwu Decoction (BHD) in treating ischemic stroke (IS). Using a middle cerebral artery occlusion/reperfusion (MCAO/R) rat model, we evaluated the neuroprotective effects of BHD, demonstrating significant improvements in neurological function scores, prolonged rotarod retention time, and reductions in both infarct volume and brain water content. An unsupervised clustering algorithm was employed to identify active components of BHD by clustering them with FDA-approved drugs for ischemic stroke treatment. Combined with network pharmacology analysis, the mechanisms of these active components were predicted to be associated with anti-inflammatory pathways. Further validation using a lipopolysaccharide (LPS)-induced BV-2 cell model demonstrated the anti-inflammatory efficacy of seven key active components, with their effects on anti-inflammatory activity and cell viability assessed via the Griess and MTT assays. Additionally, the content of these active components in BHD was quantified using liquid chromatography-mass spectrometry (LC-MS). In conclusion, this study elucidates the critical active components of BHD and their potential pharmacological mechanisms, providing valuable insights for the modernization of traditional Chinese medicine and its application in ischemic stroke therapy. All animal experiments were approved by the Animal and Medical Ethics Committee of Northeastern University (approval No.: NEU-EC-2023A052S).

stroke  /  machine learning  /  network pharmacology  /  Buyang Huanwu Decoction  /  unsupervised clustering
Feng WANG, Qing-qi MENG, Qing LIU, Ying LIU, Lu SUN, Yan MI, Dan-yang MU, Da-kuo HE, Yue HOU. Integrated machine learning and network pharmacology approach for exploring the material basis of Buyang Huanwu Decoction for ischemic stroke[J]. Acta Pharmaceutica Sinica, 2025 , 60 (3) : 627 -636 . DOI: 10.16438/j.0513-4870.2024-0971
Appendix
Less
Year 2025 volume 60 Issue 3
PDF
220
95
Cite this Article
BibTeX
Article Info
doi: 10.16438/j.0513-4870.2024-0971
  • Receive Date：2024-10-09
  • Online Date：2025-11-06
  • Published：2025-03-12
Article Data
Affiliations
History
  • Received：2024-10-09
  • Revised：2025-01-19
Funding
Affiliations
    1. College of Life and Health Sciences, Northeastern University, Key Laboratory of Bioresource Research and Development of Liaoning Province, National Frontiers Science Center for Industrial Intelligence and Systems Optimization, Shenyang 110170, China
    2. College of Information Science and Engineering, State Key Laboratory of Synthetical Automation for Process Industries, Shenyang 110004, China
    3. School of Pharmacy, Shenyang Pharmaceutical University, Benxi 117004, China
References
Share
https://castjournals.cast.org.cn/joweb/yxxb/EN/10.16438/j.0513-4870.2024-0971
Share to
QR

Scan QR to access full text

Cite this article
BibTeX
Citations
表12种不同金属材料的力学参数
科
Family		 属数
Number of
genus		 种数
Number of
species		 占总种数比例
Percentage of
total species (%)		 属
Genus		 种数
Number of
species		 占总种数比例
Percentage of total
species (%)
鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
关闭全屏
  • BibTeX
  • EndNote
  • RefWorks
  • TxT
Links
Articles
Latest Articles
Most Read
Collections
Updates
Events
News
Multimedia
About
About Us
Contact
No. 86 Xueyuan South Road, Haidian District, Beijing
100081
010-62199257
qkjq@cast.org.cn

Copyright © 2025 China Association for Science and Technology. All rights reserved. For all open access content, the relevant licensing terms apply.
Sponsored by the Office of the Leading Group for Cybersecurity and Informatization of CAST, and supported by Science and Technology Review Publishing House