2011
DOI: 10.1038/nmeth.1806
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A guide to analysis of mouse energy metabolism

Abstract: We present a consolidated view of the complexity and challenges of designing studies for measurement of energy metabolism in mouse models, including a practical guide to the assessment of energy expenditure, energy intake and body composition and statistical analysis thereof. We hope this guide will facilitate comparisons across studies and minimize spurious interpretations of data. We recommend that division of energy expenditure data by either body weight or lean body weight and that presentation of group ef… Show more

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Cited by 669 publications
(629 citation statements)
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References 48 publications
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“…S4 A-C) were detected. Because body weight differed between genotypes, we performed an "analysis of co-variance (ANCOVA)" for total EE (18) and found no significant difference between genotypes (WT/cTg = 61.52 ± 0.92 J/min and AKO/cTg = 62.63 ± 1.13 J/min based on a body weight of 41.09 g). We assume that the small changes in daily EE that lead to the obesity resistant phenotype over the time course of many weeks are too small for the detection sensitivity of indirect calorimetry.…”
Section: Lipogenesis and Lipid Synthesis Are Decreased In Gwat Of Akomentioning
confidence: 99%
“…S4 A-C) were detected. Because body weight differed between genotypes, we performed an "analysis of co-variance (ANCOVA)" for total EE (18) and found no significant difference between genotypes (WT/cTg = 61.52 ± 0.92 J/min and AKO/cTg = 62.63 ± 1.13 J/min based on a body weight of 41.09 g). We assume that the small changes in daily EE that lead to the obesity resistant phenotype over the time course of many weeks are too small for the detection sensitivity of indirect calorimetry.…”
Section: Lipogenesis and Lipid Synthesis Are Decreased In Gwat Of Akomentioning
confidence: 99%
“…To determine the effect of cachexia on energy metabolism, energy expenditure data were analyzed by ANCOVA. 68 …”
Section: Indirect Calorimetrymentioning
confidence: 99%
“…Some data were analyzed using ANCOVA to remove the effects of confounding variables. 68 MINITAB 16, Microsoft Excel, and IBM SPSS v21 were used for data analysis. P-value < 0.05 was considered significant.…”
Section: Statisticsmentioning
confidence: 99%
“…Metabolic rate data were analysed using ANCOVA as recommended by Tschop et al . (Tschop et al ., 2012) using body composition parameters as covariates.…”
Section: Methodsmentioning
confidence: 99%