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| 基于数据挖掘和网络药理学分析痛风中药治疗的遣方用药规律及其作用机制 |
| Medication rules and mechanism of action in gout: A study based on data mining and network pharmacology |
| 投稿时间：2024-05-05 修订日期：2024-09-24 |
| DOI： |
| 中文关键词: 痛风 高尿酸血症 数据挖掘 网络药理学 四妙散 |
| 英文关键词: gout hyperuricemia data mining network pharmacology Simiao Decoction |
| 基金项目:国家自然科学基金项目（面上项目，重点项目，重大项目） |
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| 中文摘要: |
| 目的：运用数据挖掘和网络药理学探究中药内服治疗痛风的遣方用药规律及其作用机制；方法：数据挖掘收集中药内服治疗痛风的方剂，并对其进行中药频次、关联规则和聚类分析，总结用药规律和核心药对；网络药理学预测药物和疾病的作用靶点，获取核心靶点及核心通路；结果：共筛选出文献204篇，涉及方剂210个，用药总频次为2415次，得到高频药物30味（频次≥20），得到关联规则8条，有效聚类群4个组，最终获取9味核心药物；网络药理学分析得核心药物参与治疗痛风靶点95个，核心靶点12个，核心通路20条。结论：数据挖掘显示痛风的中医辨证以湿热蕴结型为主，治疗上多用清热祛湿的中药；网络药理学预测了核心药物治疗痛风的关键机制。 |
| 英文摘要: |
| Objective: Based on data mining and network pharmacology to investigate the prescription and medication rules and the mechanism of action of TCM internal treatment of gout; Methods: Collecting the prescriptions of TCM internal treatment of gout with data mining and analyzing the frequency, association rules and clustering of the Chinese medicines, and summarize the medication rules and core medicines. Predict the action targets of medicines and diseases with network pharmacology and obtain core targets and core pathways. Results: A total of 204 articles were screened out. 210 prescriptions was included and contained 199 herbs. The total frequency of medicines used is 2415, and obtain 30 high-frequency medicines (with a frequency of ≥20). The association rules were analyzed to obtain 8 association rules, and the clustering analysis obtained 4 effective clustering groups. Eventually gain 9 core drugs. 95 core targets, 12 main core targets and 20 core pathway has been found by network pharmacology. Conclusions: Data mining shows that the mainly TCM syndrome type of gout is damp-heat and amassing poison. Treatment is mostly with heat-clearing and dampness-eliminating herbs. The network pharmacological shows the key mechanism of the core drug in the treatment of gout. |
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