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Comparing distress of mouse models for liver damage
Guanglin Tang1, Nico Seume1, Christine Häger2
1Rudolf-Zenker, Institute of Experimental Surgery, Rostock University Medical Center, Rostock, Germany.
Scientific Reports
|November 14, 2020
Summary
Evaluating animal distress requires multiple parameters. This study used receiver operating characteristic curve analysis and Support Vector Machine classification to compare liver damage models, finding bile duct ligation causes more distress.
Area of Science:
- Animal welfare and biomedical research
- Toxicology and pharmacology
Background:
- Legal mandates require evaluation of animal experiment severity for welfare and research quality.
- Assessing animal distress typically involves multiple parameters, but optimal methodologies and parameter performance are poorly defined.
Purpose of the Study:
- To quantify the performance of burrowing activity, body weight change, and distress scores in mice models of liver damage.
- To compare the distress levels induced by bile duct ligation versus carbon tetrachloride using multivariate analysis.
Main Methods:
- Receiver operating characteristic (ROC) curve analysis was employed to assess individual parameter performance.
- Support Vector Machine (SVM) classification was utilized for multivariate analysis and comparison of animal models.
- Two distinct mouse models of liver damage were investigated: bile duct ligation and carbon tetrachloride induction.
Main Results:
- ROC analysis quantified the performance of burrowing activity, body weight change, and distress scores.
- SVM classification revealed that bile duct ligation induced significantly greater distress compared to carbon tetrachloride.
- The study provides a prototype for comparing animal models using multiple readout parameters.
Conclusions:
- Multivariate analysis methods, such as ROC and SVM, are effective for assessing and comparing animal model severity.
- Bile duct ligation is a more severe model of liver damage in mice than carbon tetrachloride induction.
- Standardized multivariate approaches are essential for future assessments and comparisons of animal models in research.

