基于数据挖掘技术分析不育验方与验案的用药规律及潜在机制OA

Objective:This study employs data mining and bioinformatics to analyze the medication rules of empirical prescriptions and cases for treating infertility,and to predict the potential mechanisms of the core herbal combinations.Methods:Prescriptions for infertility were collected from Chinese Medicine Formula Database and CNKI.The Traditional Chinese Medicine Inheritance Support System V3.0 was used to analyze herb frequencies and compatibility rules.Network stability was assessed by comparing topological features before and after target removal to inform clinical grading recommendations.DAVID database was used for GO and KEGG pathway enrichment analysis of the GradeⅠ core prescriptions.Enrichment was also performed on clinical infertility datasets from the GEO database.Results:From 166 historical formulas,three GradeⅠ core prescriptions were identified,characterized by tonifying deficiency as the principal method,supplemented by astringent and interior-warming herbs.From 179 modern journal-documented prescriptions,one Grade Ⅰ core formula was identified,also primarily tonifying deficiency,while incorporating heat-clearing and blood-activating methods.Enriched pathways for GradeⅠ prescriptions,consistent with GEO clinical data,included steroid hormone receptor signaling,mitochondrial ATP binding,and metabolic processes.Conclusion:This study elucidates the medication rules of effective historical and modern prescriptions for infertility.The identified GradeⅠ core formulas and their associated biological pathways provide a reference for clinical prevention,treatment,and novel drug screening for infertility.