Literature DB >> 7286772

Predicting percent fat in mice.

E J Eisen, J M Leatherwood.   

Abstract

Body energy/body weight (ENGY), percent water (WAT%) and proportional weight of the epididymal fat pad (FPAD%) were used as independent variables to predict fat percent (FAT%) in three independent studies with mice. Prediction equations were found to be valid based on the following criteria: 1) high correlations between observed FAT% and predicted fat percent based on prediction equations derived from an independent data set and 2) negligible correlations between predicted fat and FAT% minus predicted fat. Although any two of the independent variable generally provided a better fit than one variable, use of one of the three independent variables is probably sufficient for most applications. Based on the coefficient of determination, ENGY was the best single predictor of FAT% followed by WAT% and FPAD%. However, FPAD% may be most useful in large experiments where a rapid procedure is essential.

Entities:  

Mesh:

Year:  1981        PMID: 7286772

Source DB:  PubMed          Journal:  Growth        ISSN: 0017-4793


  4 in total

1.  Selection for components related to body composition in mice: direct responses.

Authors:  E J Eisen
Journal:  Theor Appl Genet       Date:  1987-10       Impact factor: 5.699

2.  A disputed evidence on obesity: comparison of the effects of Rcan2(-/-) and Rps6kb1(-/-) mutations on growth and body weight in C57BL/6J mice.

Authors:  Jing Zhao; Shi-Wei Li; Qian-Qian Gong; Ling-Cui Ding; Ye-Cheng Jin; Jian Zhang; Jian-Gang Gao; Xiao-Yang Sun
Journal:  J Zhejiang Univ Sci B       Date:  2016-09       Impact factor: 3.066

3.  Development of obesity following inactivation of a growth hormone transgene in mice.

Authors:  D Pomp; A M Oberbauer; J D Murray
Journal:  Transgenic Res       Date:  1996-01       Impact factor: 2.788

4.  Whole Blood RNA as a Source of Transcript-Based Nutrition- and Metabolic Health-Related Biomarkers.

Authors:  Petar D Petrov; M Luisa Bonet; Bárbara Reynés; Paula Oliver; Andreu Palou; Joan Ribot
Journal:  PLoS One       Date:  2016-05-10       Impact factor: 3.240

  4 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.