Literature DB >> 35167089

Analysis of Thermogenesis Experiments with CalR.

Marissa D Cortopassi1, Deepti Ramachandran1, William B Rubio1, Daniel Hochbaum2, Bernardo L Sabatini2, Alexander S Banks3.   

Abstract

Modern indirect calorimetry systems allow for high-frequency time series measurements of the factors affected by thermogenesis: energy intake and energy expenditure. These indirect calorimetry systems generate a flood of raw data recording oxygen consumption, carbon dioxide production, physical activity, and food intake among other factors. Analysis of these data requires time-consuming manual manipulation for formatting, data cleaning, quality control, and visualization. Beyond data handling, analyses of indirect calorimetry experiments require specialized statistical treatment to account for differential contributions of fat mass and lean mass to metabolic rates.Here we describe how to use the software package CalR version 1.2, to analyze indirect calorimetry data from three examples of thermogenesis, cold exposure, adrenergic agonism, and hyperthyroidism in mice, by providing standardized methods for reproducible research. CalR is a free online tool with an easy-to-use graphical user interface to import data files from the Columbus Instruments' CLAMS, Sable Systems' Promethion, and TSE Systems' PhenoMaster. Once loaded, CalR can quickly visualize experimental results and perform basic statistical analyses. We present a framework that standardizes the data structures and analyses of indirect calorimetry experiments to provide reusable and reproducible methods for the physiological data affecting body weight.
© 2022. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.

Entities:  

Keywords:  Adrenergic agonist; Body weight; Cold exposure; Energy expenditure; Hyperthyroid; Indirect calorimetry; Metabolic rate; Thermogenesis; Weight gain; Weight loss

Mesh:

Year:  2022        PMID: 35167089     DOI: 10.1007/978-1-0716-2087-8_3

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  8 in total

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Authors:  Patrick C Even; Nachiket A Nadkarni
Journal:  Am J Physiol Regul Integr Comp Physiol       Date:  2012-06-20       Impact factor: 3.619

2.  Gut Microbiota Orchestrates Energy Homeostasis during Cold.

Authors:  Claire Chevalier; Ozren Stojanović; Didier J Colin; Nicolas Suarez-Zamorano; Valentina Tarallo; Christelle Veyrat-Durebex; Dorothée Rigo; Salvatore Fabbiano; Ana Stevanović; Stefanie Hagemann; Xavier Montet; Yann Seimbille; Nicola Zamboni; Siegfried Hapfelmeier; Mirko Trajkovski
Journal:  Cell       Date:  2015-12-03       Impact factor: 41.582

3.  New methods for calculating metabolic rate with special reference to protein metabolism.

Authors:  J B DE B WEIR
Journal:  J Physiol       Date:  1949-08       Impact factor: 5.182

4.  Dissociation of Adaptive Thermogenesis from Glucose Homeostasis in Microbiome-Deficient Mice.

Authors:  Tibor I Krisko; Hayley T Nicholls; Curtis J Bare; Corey D Holman; Gregory G Putzel; Robert S Jansen; Natalie Sun; Kyu Y Rhee; Alexander S Banks; David E Cohen
Journal:  Cell Metab       Date:  2020-02-20       Impact factor: 27.287

5.  Comparison of the Effects of High-Fat Diet on Energy Flux in Mice Using Two Multiplexed Metabolic Phenotyping Systems.

Authors:  Jamie E Soto; Colin M L Burnett; Patrick Ten Eyck; E Dale Abel; Justin L Grobe
Journal:  Obesity (Silver Spring)       Date:  2019-03-28       Impact factor: 5.002

6.  Measuring energy metabolism in the mouse - theoretical, practical, and analytical considerations.

Authors:  John R Speakman
Journal:  Front Physiol       Date:  2013-03-14       Impact factor: 4.566

7.  Essential role of UCP1 modulating the central effects of thyroid hormones on energy balance.

Authors:  Mayte Alvarez-Crespo; Robert I Csikasz; Noelia Martínez-Sánchez; Carlos Diéguez; Barbara Cannon; Jan Nedergaard; Miguel López
Journal:  Mol Metab       Date:  2016-02-10       Impact factor: 7.422

8.  A big-data approach to understanding metabolic rate and response to obesity in laboratory mice.

Authors:  June K Corrigan; Deepti Ramachandran; Yuchen He; Colin J Palmer; Michael J Jurczak; Rui Chen; Bingshan Li; Randall H Friedline; Jason K Kim; Jon J Ramsey; Louise Lantier; Owen P McGuinness; Alexander S Banks
Journal:  Elife       Date:  2020-05-01       Impact factor: 8.713

  8 in total

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