Phytomedicine : international journal of phytotherapy and phytopharmacology · 2026
Therapeutic efficacy and dosing regimen evidence synthesis of Ursolic Acid for liver injury: A preclinical systematic review with machine learning.
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Peng Xi-Yuan, Miao Juan, Du Wei, Shi Li, Li Wei, Lu Xin-Rui, Zhong Kang, Feng Rui, Chen Hong-Lin
Аннотация
BACKGROUND: Ursolic acid (UA), a pentacyclic triterpene, shows hepatoprotective efficacy and favorable safety in various animal models of liver injury. However, robust preclinical evidence remains scarce.
PURPOSE: To synthesize the preclinical evidence for UA and explore how UA dose and treatment duration are associated with alanine aminotransferase (ALT) improvement in animal models of liver injury.
STUDY DESIGN: This preclinical systematic review integrating meta-analysis and machine learning followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA).
METHODS: Relevant preclinical studies through April 11, 2026 were systematically retrieved from PubMed, Embase, Scopus, Web of Science, OVID, CNKI and Wanfang. Machine learning analyses were used to identify factors associated with ALT improvement, particularly human equivalent dose (HED) and treatment duration.
RESULTS: Forty-seven articles were included in this analysis. UA markedly improved histopathological parameters, liver function, biochemical parameters, serum lipid levels, oxidative stress indicators, and inflammatory markers in liver injury animal models. Random forest was selected as the final predictive model. The analysis further identified model administration route, treatment duration, HED, and time of administration as key determinants for the improvement rate of ALT. An exploratory HED range of approximately 5-7 mg/kg was associated with greater predicted ALT improvement.
CONCLUSION: The study indicates that UA exerts hepatoprotective effects in animal models of liver injury. Potential mechanisms include modulation of the gut-liver axis, attenuation of hepatic and systemic oxidative stress, and suppression of inflammation and fibrosis. Given the exploratory nature of these preclinical findings, the translational potential of UA warrants further rigorous validation.
PURPOSE: To synthesize the preclinical evidence for UA and explore how UA dose and treatment duration are associated with alanine aminotransferase (ALT) improvement in animal models of liver injury.
STUDY DESIGN: This preclinical systematic review integrating meta-analysis and machine learning followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA).
METHODS: Relevant preclinical studies through April 11, 2026 were systematically retrieved from PubMed, Embase, Scopus, Web of Science, OVID, CNKI and Wanfang. Machine learning analyses were used to identify factors associated with ALT improvement, particularly human equivalent dose (HED) and treatment duration.
RESULTS: Forty-seven articles were included in this analysis. UA markedly improved histopathological parameters, liver function, biochemical parameters, serum lipid levels, oxidative stress indicators, and inflammatory markers in liver injury animal models. Random forest was selected as the final predictive model. The analysis further identified model administration route, treatment duration, HED, and time of administration as key determinants for the improvement rate of ALT. An exploratory HED range of approximately 5-7 mg/kg was associated with greater predicted ALT improvement.
CONCLUSION: The study indicates that UA exerts hepatoprotective effects in animal models of liver injury. Potential mechanisms include modulation of the gut-liver axis, attenuation of hepatic and systemic oxidative stress, and suppression of inflammation and fibrosis. Given the exploratory nature of these preclinical findings, the translational potential of UA warrants further rigorous validation.