Therapeutic potential of pharmacological components of Salvia miltiorrhiza against atherosclerosis: A preclinical systematic review and meta-analysis.

Atherosclerosis (AS) severely threatens global health, while current therapies exhibit limitations. Recognized as a 'superior-grade' herb in the Shennong Ben Cao Jing, Salvia miltiorrhiza Bunge (Danshen) has been shown in modern studies to protect against cardiovascular diseases.

The aim of this study was to investigate the therapeutic potential and protective mechanism of pharmacological components of Salvia miltiorrhiza against AS.

Relevant animal studies were collected from 8 databases, namely, PubMed, Web of Science, Embase, Cochrane Library, CNKI, Wanfang Data, VIP, and SinoMed. Risk of bias of the included studies was evaluated using the SYRCLE's tool. Statistical analysis was performed using R 4.2.0 and Python 3.14.2 software. Machine learning model was trained to predict optimal intervention parameters and was subsequently validated.

A total of 64 studies were included. The pharmacological components of Salvia miltiorrhiza ameliorated atherosclerotic plaque formation and stability, and modulated various biomarkers, including lipid profiles, inflammatory cytokines, oxidative stress indicators, endothelial function markers, as well as matrix metalloproteinases. Machine learning identified an optimal Tanshinone IIA regimen against AS, which was defined as a single dose of 33.18 mg/kg dose over 84 days and demonstrated predictive robustness in validation.

The pharmacological components of Salvia miltiorrhiza attenuate AS by regulating lipid metabolism, anti-inflammatory and antioxidant actions, improving endothelial function, modulating of vascular smooth muscle cells, remodeling extracellular matrix, and regulating programmed cell death. These findings provide translational insights that pave the way for subsequent preclinical and early-clinical studies, pending systematic validation through more rigorous research.
Cardiovascular diseases
Care/Management

Authors

Zhang Zhang, Sun Sun, Wang Wang, Sun Sun, Liu Liu, Huang Huang, Jiang Jiang, Yao Yao
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