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Full-Text Articles in Nutrition
The Athletic Gut Microbiota, Alex E. Mohr, Ralf Jäger, Katie C. Carpenter, Chad M. Kerksick, Martin Purpura, Jeremy R. Townsend, Nicholas P. West, Katherine Black, Michael Gleeson, David B. Pyne, Shawn D. Wells, Shawn M. Arent, Richard B. Kreider, Bill I. Campbell, Laurent Bannock, Jonathan Scheiman, Craig J. Wissent, Marco Pane, Douglas S. Kalman, Jamie N. Pugh, Carmen P. Ortega-Santos, Jessica A. Ter Haar, Paul J. Arciero, Jose Antonio
The Athletic Gut Microbiota, Alex E. Mohr, Ralf Jäger, Katie C. Carpenter, Chad M. Kerksick, Martin Purpura, Jeremy R. Townsend, Nicholas P. West, Katherine Black, Michael Gleeson, David B. Pyne, Shawn D. Wells, Shawn M. Arent, Richard B. Kreider, Bill I. Campbell, Laurent Bannock, Jonathan Scheiman, Craig J. Wissent, Marco Pane, Douglas S. Kalman, Jamie N. Pugh, Carmen P. Ortega-Santos, Jessica A. Ter Haar, Paul J. Arciero, Jose Antonio
Faculty Scholarship
The microorganisms in the gastrointestinal tract play a significant role in nutrient uptake, vitamin synthesis, energy harvest, inflammatory modulation, and host immune response, collectively contributing to human health. Important factors such as age, birth method, antibiotic use, and diet have been established as formative factors that shape the gut microbiota. Yet, less described is the role that exercise plays, particularly how associated factors and stressors, such as sport/exercise-specific diet, environment, and their interactions, may influence the gut microbiota. In particular, high-level athletes offer remarkable physiology and metabolism (including muscular strength/power, aerobic capacity, energy expenditure, and heat production) compared to sedentary …
Use Of A Novel Whole-Body Imaging Approach To Predict Resting Metabolic Rates In Athletes, Nicole Vencil
Use Of A Novel Whole-Body Imaging Approach To Predict Resting Metabolic Rates In Athletes, Nicole Vencil
College of Education and Human Sciences: Dissertations, Theses, and Student Research
Prediction of energy expenditure allows for calculation of appropriate energy requirements, which is especially important for athletes. Resting metabolic rate (RMR) is the greatest contributor to total daily energy expenditure (TDEE) and is typically measured via indirect calorimetry. Indirect calorimetry is not always available, which results in the need for predictive equations. Most predictive equations have been developed with participants resembling the general population and have not been found to be appropriate for athletes, as they may incorrectly predict RMR due to the unique differences of body composition between athletes and the general population. The purpose of the present study …