{"title":"肥胖大鼠模型中身体状况评分与身体成分的相关性研究","authors":"Parkpoom Siriarchavatana, M. Kruger, F. Wolber","doi":"10.12982/vis.2022.040","DOIUrl":null,"url":null,"abstract":"The incidences of obesity-associated chronic diseases are increasing worldwide. Research into the causes of obesity as well as potential treatments has highlighted the crucial role of preclinical studies using animal models. Rats are one of the most widely used species in obesity research. However, even with decades of research in both genetically obese rats and diet-induced obese rat models, definitive criteria to practically classify levels of obesity in the rat are not well established. The current study proposes new criteria modified from a 5-point body condition score (BCS) using in an animal health monitoring system and added a half-point scale to extend the range of body weight associated with subcutaneous fat deposition. The modified criteria were tested and compared with body composition from dual energy X-ray absorptiometry scans and selected adipose tissue weights. The results showed that the modified body condition scale was highly correlated with fat deposition in the rat body, particularly the visceral and inguinal fat pads. Both pads were closely related to changes in some specific landmarks used for the scale determination. These finding should extrapolate to obese rats in other models, with the advantage that data classified in BCS can pair the animal data with human body mass index. This will enhance the value of information from preclinical studies to design and predict outcomes of subsequent human clinical trials.","PeriodicalId":36378,"journal":{"name":"Veterinary Integrative Sciences","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2022-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Correlation between body condition score and body composition in a rat model for obesity research\",\"authors\":\"Parkpoom Siriarchavatana, M. Kruger, F. Wolber\",\"doi\":\"10.12982/vis.2022.040\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The incidences of obesity-associated chronic diseases are increasing worldwide. Research into the causes of obesity as well as potential treatments has highlighted the crucial role of preclinical studies using animal models. Rats are one of the most widely used species in obesity research. However, even with decades of research in both genetically obese rats and diet-induced obese rat models, definitive criteria to practically classify levels of obesity in the rat are not well established. The current study proposes new criteria modified from a 5-point body condition score (BCS) using in an animal health monitoring system and added a half-point scale to extend the range of body weight associated with subcutaneous fat deposition. The modified criteria were tested and compared with body composition from dual energy X-ray absorptiometry scans and selected adipose tissue weights. The results showed that the modified body condition scale was highly correlated with fat deposition in the rat body, particularly the visceral and inguinal fat pads. Both pads were closely related to changes in some specific landmarks used for the scale determination. These finding should extrapolate to obese rats in other models, with the advantage that data classified in BCS can pair the animal data with human body mass index. This will enhance the value of information from preclinical studies to design and predict outcomes of subsequent human clinical trials.\",\"PeriodicalId\":36378,\"journal\":{\"name\":\"Veterinary Integrative Sciences\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-06-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Veterinary Integrative Sciences\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.12982/vis.2022.040\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"Veterinary\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Veterinary Integrative Sciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.12982/vis.2022.040","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Veterinary","Score":null,"Total":0}
Correlation between body condition score and body composition in a rat model for obesity research
The incidences of obesity-associated chronic diseases are increasing worldwide. Research into the causes of obesity as well as potential treatments has highlighted the crucial role of preclinical studies using animal models. Rats are one of the most widely used species in obesity research. However, even with decades of research in both genetically obese rats and diet-induced obese rat models, definitive criteria to practically classify levels of obesity in the rat are not well established. The current study proposes new criteria modified from a 5-point body condition score (BCS) using in an animal health monitoring system and added a half-point scale to extend the range of body weight associated with subcutaneous fat deposition. The modified criteria were tested and compared with body composition from dual energy X-ray absorptiometry scans and selected adipose tissue weights. The results showed that the modified body condition scale was highly correlated with fat deposition in the rat body, particularly the visceral and inguinal fat pads. Both pads were closely related to changes in some specific landmarks used for the scale determination. These finding should extrapolate to obese rats in other models, with the advantage that data classified in BCS can pair the animal data with human body mass index. This will enhance the value of information from preclinical studies to design and predict outcomes of subsequent human clinical trials.