An ergometer dataset to measure muscle bioenergetics with magnetic resonance techniques.

IF 1 Q3 MULTIDISCIPLINARY SCIENCES Data in Brief Pub Date : 2024-11-07 eCollection Date: 2024-12-01 DOI:10.1016/j.dib.2024.111114

Usman Rehman, Gwenaelle Begue, Armin Ahmadi, Paolo Taboga, Jorge Gamboa, Baback Roshanravan, Thomas Jue

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Abstract

Applying magnetic resonance methods to measure the metabolic response in exercise poses a technical challenge because the construction of the ergometer must use non-magnetic components and assess work in the confined space of a magnet bore. The present report details the fabrication of a non-magnetic ergometer for use in a standard Siemens 3 Tesla (T) spectrometer. Using the ergometer, researchers can measure the ³¹P magnetic resonance spectroscopy (MRS) signals during leg muscle exercise and exercise recovery. In particular, the phosphocreatine (PCr) kinetics during exercise recovery reflects the mitochondrial oxidative capacity, and the inorganic phosphate (P_i) signal tracks the cellular pH. The ergometer allows for the use of a personalized, and variable load that normalizes the work for all study participants regardless of their leg strength. The ergometer then enables a standardized MRS comparison of leg muscle bioenergetics.

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一个用磁共振技术测量肌肉生物能量的测力计数据集。

应用磁共振方法来测量运动中的代谢反应是一项技术挑战，因为测力仪的构造必须使用非磁性元件，并在磁力孔的密闭空间中评估工作。本报告详细介绍了用于标准西门子3特斯拉(T)光谱仪的非磁性测功仪的制造。通过使用测力计，研究人员可以测量腿部肌肉锻炼和运动恢复过程中的31P磁共振波谱（MRS）信号。特别是，运动恢复过程中的磷酸肌酸（PCr）动力学反映了线粒体氧化能力，无机磷酸盐（Pi）信号跟踪细胞ph。测力仪允许使用个性化的可变负荷，使所有研究参与者的工作正常化，而不管他们的腿部力量如何。然后，测力器可以对腿部肌肉生物能量学进行标准化的MRS比较。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Data in Brief MULTIDISCIPLINARY SCIENCES-

CiteScore

3.10

自引率

0.00%

发文量

996

审稿时长

70 days

期刊介绍： Data in Brief provides a way for researchers to easily share and reuse each other''s datasets by publishing data articles that: -Thoroughly describe your data, facilitating reproducibility. -Make your data, which is often buried in supplementary material, easier to find. -Increase traffic towards associated research articles and data, leading to more citations. -Open up doors for new collaborations. Because you never know what data will be useful to someone else, Data in Brief welcomes submissions that describe data from all research areas.