Analysis of application characteristics of acute liver injury animal model based on data mining
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Henan University of Traditional Chinese Medicine

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国中医药人教函2022-6;201300310100

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    Abstract:

    Objective To investigate the modeling elements of various types of animal models for acute liver injury, and to provide references and suggestions for the establishment and evaluation of animal models for ALI. Methods The animal experimental literature of acute liver injury from 2002 to 2022 was searched in the databases of China Knowledge Network, WanFang, Chongqing Vip, Chinese Medical Journal Full Text Data, PubMed, etc. The animal species, positive control drugs, modeling methods, modeling drugs and drug administration of the animal models of acute liver injury involved in the literature were summarized and summarized. The results were analyzed using Excel, SPSS Modeler18.0 and Cytoscape3.8.2. Results A total of 896 papers were included in the database. The most used animal models for acute liver injury were male KM mice; the modeling methods were mainly chemical liver injury, alcoholic liver injury, drug-related liver injury and immune liver injury, and the corresponding main modeling methods were : ① intraperitoneal injection of 10.0 mL 0.1% CCl4 vegetable oil, 24 h before the experiment; ② gavage of 12.0 mL 50.0%-56.0% ethanol, 16 h before the experiment; ③intraperitoneal injection of APAP 300 mg/kg, 24 h before the experiment; ④ tail vein injection of Con A 20 mg/kg, 8 h before the experiment. The evaluation of the model was based on liver pathological indexes as the gold index, combined with biochemical indexes Serum ALT, AST, liver tissue homogenate SOD, MDA content and activity were used as direct indicators. Conclusions Since the causes of acute liver injury vary in clinical practice, the preparation of animal models of acute liver injury should be based on the specific study content and characteristics of the study, and the corresponding modeling methods should be selected.

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History
  • Received:April 21,2023
  • Revised:May 25,2023
  • Adopted:January 17,2024
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