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Improved Exercise-Related Skeletal Muscle Oxygen Consumption Following Uptake of Endurance Training Measured Using Near-Infrared Spectroscopy

Jones, S; D'Silva, A; Bhuva, A; Lloyd, G; Manisty, C; Moon, JC; Sharma, S; (2017) Improved Exercise-Related Skeletal Muscle Oxygen Consumption Following Uptake of Endurance Training Measured Using Near-Infrared Spectroscopy. Frontiers in Physiology , 8 , Article 1018. 10.3389/fphys.2017.01018. Green open access

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Abstract

Skeletal muscle metabolic function is known to respond positively to exercise interventions. Developing non-invasive techniques that quantify metabolic adaptations and identifying interventions that impart successful response are ongoing challenges for research. Healthy non-athletic adults (18–35 years old) were enrolled in a study investigating physiological adaptations to a minimum of 16 weeks endurance training prior to undertaking their first marathon. Before beginning training, participants underwent measurements of skeletal muscle oxygen consumption using near-infrared spectroscopy (NIRS) at rest (resting muscleVO˙ 2) and immediately following a maximal exercise test (post-exercise muscleVO˙ 2). Exercise-related increase in muscleVO˙ 2 (1mVO˙ 2) was derived from these measurements and cardio-pulmonary peakVO˙ 2 measured by analysis of expired gases. All measurements were repeated within 3 weeks of participants completing following the marathon and marathon completion time recorded. MuscleVO˙ 2 was positively correlated with cardio-pulmonary peakVO˙ 2 (r = 0.63, p < 0.001). MuscleVO˙ 2 increased at follow-up (48% increase; p = 0.004) despite no change in cardio-pulmonary peakVO˙ 2 (0% change; p = 0.97). Faster marathon completion time correlated with higher cardio-pulmonary peakVO˙ 2 (rpartial = −0.58, p = 0.002) but not muscleVO˙ 2 (rpartial = 0.16, p = 0.44) after adjustment for age and sex [and adipose tissue thickness (ATT) for muscleVO˙ 2 measurements]. Skeletal muscle metabolic adaptions occur following training and completion of a first-time marathon; these can be identified non-invasively using NIRS. Although the cardio-pulmonary system is limiting for running performance, skeletal muscle changes can be detected despite minimal improvement in cardio-pulmonary function.

Type: Article
Title: Improved Exercise-Related Skeletal Muscle Oxygen Consumption Following Uptake of Endurance Training Measured Using Near-Infrared Spectroscopy
Open access status: An open access version is available from UCL Discovery
DOI: 10.3389/fphys.2017.01018
Publisher version: http://doi.org/10.3389/fphys.2017.01018
Language: English
Additional information: © 2017 Jones, D'Silva, Bhuva, Lloyd, Manisty, Moon, Sharma and Hughes. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
Keywords: Science & Technology, Life Sciences & Biomedicine, Physiology, endurance exercise, oxygen consumption, NIRS, skeletal muscle, (V) over dot O-2 kinetics, PERFORMANCE, ADAPTATIONS, INTERVAL, METABOLISM, CAPACITY, RUNNERS, VO2MAX
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Cardiovascular Science
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Cardiovascular Science > Clinical Science
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Cardiovascular Science > Population Science and Experimental Medicine
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Health Informatics
URI: https://discovery.ucl.ac.uk/id/eprint/10040763
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