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基于数据挖掘的肝纤维化动物模型应用分析 被引量:3

Application Analysis of Animal Model of Liver Fibrosis Based on Data Mining
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摘要 目的:了解肝纤维化动物模型应用情况。方法:收集肝纤维化动物模型文献1 304篇,纳入符合要求文献的动物类型、造模方法、给药周期、表观指标、检测指标等,进行统计分析。结果:实验动物多为8 w~10 w龄雄性Sprague Dawley (SD)大鼠、6 w~8 w龄雄性C57BL/6J小鼠、6 w~8 w Wistar雄性大鼠;造模方法使用频次最多的依次为化学损伤性肝纤维化动物模型和复合因素肝纤维化动物模型;给药周期多为8 w,造模方式多为腹腔注射;5种检测方法中常规检测指标有丙氨酸转氨酶(ALT)、天冬氨酸转氨酶(AST)、血清透明质酸(HA)、血清层粘连蛋白(LN)、总胆红素(TBIL)等。结论:肝纤维化造模方法大多仍以化学诱导法为主,病证结合动物模型应用较少,完善的病证结合肝纤维化动物模型可能成为中医药抗肝纤维化研究领域的重点。 Objective:To research the application condition of animal models of liver fibrosis. Methods: A total of 1,304 studies on animal models of liver fibrosis were collected in CNKI, Pubmed and Wanfang databases, from August 2018 to August 2020. The animal types, establishment methods, a course of treatment, observation indexes, and detection indexes of the included standard literature were input into Excel, and the changes of their types and indexes were statistically analyzed. Results: Most of the experimental animals were male SD rats aged 8-10 weeks, male C57 BL/6 J mice aged 6-8 weeks and male Wistar rats aged 6-8 weeks. Most of the establishment methods were chemical injury liver fibrosis model and complicated factors fibrosis animal model. The course of treatment was mainly 8 weeks, through intraperitoneal injection. The routine detection indexes of five detection methods were ALT, AST, HA, LN, TB, etc. Conclusion: The main liver fibrosis model is the chemical injury model, while models with disease-syndrome combination are small amount. A well-developed liver fibrosis animal model with disease-syndrome combination is important to research the liver fibrosis in traditional Chinese medicine.
作者 留甜甜 宋亚刚 苗明三 Liu Tiantian;Song Yagang;Miao Mingsan(Henan University of Chinese Medicine,Zhengzhou 450046)
机构地区 河南中医药大学
出处 《中药药理与临床》 CAS CSCD 北大核心 2021年第4期220-224,共5页 Pharmacology and Clinics of Chinese Materia Medica
基金 国家自然科学基金(编号:81274154) 中原学者(编号:162101510003) 国家国际合作基地(编号:2016-65)。
关键词 肝纤维化 动物模型 数据挖掘 造模要素 应用分析 liver fibrosis Animal model Data mining Modeling factors applied analysis
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