Estimation of activity related energy expenditure and resting metabolic rate in freely moving mice from indirect calorimetry data.

PloS One
Jan B van KlinkenKo Willems Van Dijk

Abstract

Physical activity (PA) is a main determinant of total energy expenditure (TEE) and has been suggested to play a key role in body weight regulation. However, thus far it has been challenging to determine what part of the expended energy is due to activity in freely moving subjects. We developed a computational method to estimate activity related energy expenditure (AEE) and resting metabolic rate (RMR) in mice from activity and indirect calorimetry data. The method is based on penalised spline regression and takes the time dependency of the RMR into account. In addition, estimates of AEE and RMR are corrected for the regression dilution bias that results from inaccurate PA measurements. We evaluated the performance of our method based on 500 simulated metabolic chamber datasets and compared it to that of conventional methods. It was found that for a sample time of 10 minutes the penalised spline model estimated the time-dependent RMR with 1.7 times higher accuracy than the Kalman filter and with 2.7 times higher accuracy than linear regression. We assessed the applicability of our method on experimental data in a case study involving high fat diet fed male and female C57Bl/6J mice. We found that TEE in male mice was higher due t...Continue Reading

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Mar 13, 2014·The Journals of Gerontology. Series A, Biological Sciences and Medical Sciences·Loes P M DuivenvoordeJaap Keijer
Aug 13, 2013·PloS One·Nachiket A NadkarniPatrick C Even
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Methods Mentioned

BETA
RMR

Software Mentioned

MATLAB

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