详细信息
基于Python语言的藏医对治“年壬”(瘟疫)方剂数据库构建及配伍规律分析 被引量:8
Construction of Tibetan Medicine Prescription Database for Treating"Gnyan-rims"and Analysis of Their Medication Law Based on Python Language
文献类型:期刊文献
中文题名:基于Python语言的藏医对治“年壬”(瘟疫)方剂数据库构建及配伍规律分析
英文题名:Construction of Tibetan Medicine Prescription Database for Treating"Gnyan-rims"and Analysis of Their Medication Law Based on Python Language
作者:文成当智[1];刚焕晨雷[2];热增才旦[1];尕藏扎西[1];贡保东知[3];才让南加[1]
第一作者:文成当智
机构:[1]青海民族大学药学院,西宁810007;[2]成都中医药大学民族医药学院,成都611137;[3]甘肃中医药大学藏医学院,甘肃合作747000
第一机构:青海民族大学药学院,西宁810007
年份:2021
卷号:27
期号:14
起止页码:193
中文期刊名:中国实验方剂学杂志
外文期刊名:Chinese Journal of Experimental Traditional Medical Formulae
收录:CSTPCD;;北大核心:【北大核心2020】;CSCD:【CSCD2021_2022】;
基金:国家社会科学基金项目(20XMZ026)。
语种:中文
中文关键词:藏族医药;瘟疫;方剂;新型冠状病毒肺炎(COVID-19);数据库;味性化味;Python代码
外文关键词:Tibetan medicine;plague;formulas;coronavirus disease 2019(COVID-19);database;Ro-nus-zhu-rjes;Python code
摘要:目的:构建藏族医学(简称藏医)对治"年壬"方剂数据库,挖掘其方剂配伍规律和药性组合等隐形用药规律。方法:以《四部医典》《藏医临床札记》《秀多医学汇集》《零星方剂汇集》4部藏医文献中检索用于治疗"年壬"的方剂,在Python代码下构建数据库,运用Apriori算法、味性化味矢量结构模型等方法进行分析。结果:针对藏医方剂数据特点,以方名、组方、剂量、功效、出处、原文6个字段为核心建立了具有清洗、检索、导出等功能为一体的藏医对治"年壬"方剂数据库,数据库共收纳方剂7602首,其中同时具有对治"年"病和"壬"病功效的方剂共有598首。配伍规律分析发现麝香、诃子、红花、穆库尔没药、铁棒锤、天竺黄、榜嘎等组方药物频次最高,药对中麝香-穆库尔没药、红花-天竺黄、麝香-诃子、麝香-铁棒锤等关联度最强,并在前十位关联中出现五味麝香丸的所有组方药味。对含高频组方药物的40首方剂进行药性分析,发现19首方剂苦味偏盛,其次为三臣散等9首方剂甘味偏盛,占比均>35%,甘味和苦味偏盛方剂合计占总方剂的70%;三化味中苦化味偏盛,十七效中以凉效、顿效、重效突出。结论:构建的藏医对治"年壬"方剂数据库可促进民族医药防治瘟疫研究的高质量发展;藏医治疗"年壬"以五味麝香丸的组方药味为核心,具有"凉-苦甘-苦化味-凉钝重"等为主的药性组合,主要对治"热锐轻-赤巴-热"等疾病特性,可为藏医药治疗瘟疫的方剂及其组方药物筛选提供数据基础和理论参考。
Objective:To construct the database of Tibetan medicine prescriptions for"Gnyan-rims"disease,and to explore the invisible medication law of Tibetan medicine in the treatment of"Gnyan-rims"disease,such as prescription compatibility and combination of drug properties.Method:The prescriptions for treating"Gnyan-rims"were retrieved from four Tibetan medical literatures such as The Four Medical Tantras,Kong-sprul-zin-tig,Phyag-rdor-gso-rig-phyogs-bsgrigs and Sman-sbyor-lag-len-phyogs-bsgrigs,and the database was constructed under Python code,and the Apriori algorithm and the vector structure model of taste property flavor transformation were used for analysis.Result:According to the characteristics of Tibetan medicine prescription data,with six fields of prescription name,formula,dosage,efficacy,source and original text as the core,a Tibetan medicine treatment"Gnyan-rims"prescription database with functions of cleaning,searching and exporting was established.A total of 7602 prescriptions were included in the database,among which 598 prescriptions had therapeutic effects of"Gnyan"and"Rims".The results of compatibility analysis showed that Shexiang,Hezi,Honghua,Mukuer Moyao,Tiebangchui,Tianzhuhuang and Bangga were the most frequently used drugs,while the correlation degrees of Shexiang-Mukuer Moyao,HonghuaTianzhuhuang,Shexiang-Hezi and Shexiang-Tiebangchui were the strongest,and all the drug composition of Wuwei Shexiang pills appeared in the top ten correlations.According to the property analysis of 40 prescriptions containing high-frequency drugs,19 prescriptions were found to have excessive bitter taste,followed by 9 prescriptions such as Sanchen powders with excessive sweetish taste,and the ratios of sweetish and bitter tastes in six tastes were>35%.The total of sweetish and bitter prescriptions accounted for 70%of the total prescriptions.Among the three flavors,the bitter flavor was the most abundant.The cool effect,dull effect and heavy effect were prominent among the seventeen effects.Conclusion:The prescription database of Tibetan medicine for"Gnyan-rims"can promote the high-quality development of research on prevention and treatment of plague with ethnic medicine.Tibetan medicine treatment of"Gnyan-rims"focuses on the composition of Wuwei Shexiang pills,with the property combination of"cool-bitter and sweet-bitter flavor-cool,dull and heavy",which mainly treats diseases such as"heat sharp light-mkhris pa-heat".These studies can provide data basis and theoretical reference for the selection of Tibetan medicine prescription and its composition for treating plague.
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