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. 2005 Oct;95(4):276-82.
doi: 10.1007/s00421-005-0003-x. Epub 2005 Oct 27.

Metabolic and phenotypic characteristics of human skeletal muscle fibers as predictors of glycogen utilization during electrical stimulation

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Metabolic and phenotypic characteristics of human skeletal muscle fibers as predictors of glycogen utilization during electrical stimulation

Chris M Gregory et al. Eur J Appl Physiol. 2005 Oct.

Abstract

Characteristics of skeletal muscle such as fiber type composition and activities of key metabolic enzymes have been purported to affect glycogen utilization. However, the relative importance individual factors may have in predicting glycogen utilization of individual muscle fibers has not been addressed. Thus, we sought to determine the relative importance that metabolic characteristics and phenotypic expression of individual fibers have in predicting fiber specific glycogen utilization during neuromuscular electrical stimulation (NMES) exercise. Biopsies were taken from the m, vastus lateralis (VL) of eight recreationally active males before and immediately after 30 min of non-fatiguing NMES and analyzed for type (I, IIa and IIx), succinate dehydrogenase activity (SDH), glycerol-phosphate dehydrogenase activity (GPDH), quantitative-actomyosin adenosine triphosphatase activity (qATPase), and glycogen content. Our results demonstrate that a ratio of enzyme activities representing pathways for energy supply and energy demand (SDH: qATPase) accounted for more of the variance in glycogen utilization (y=0.2091 e(-0.0329x ), R2=0.622, P< or = 0.0001) than SDH (R2=0.321) or qATPase (R2=0.365) alone. Fiber phenotype was also a significant predictor of glycogen utilization, but to a lesser extent than the other variables studied (R2=0.201). A ratio of the activities of enzymes representing pathways of energy supply and energy demand, represented by SDH:qATPase, is a better predictor of glycogen utilization than either of its components independently while fiber phenotype, although a statistically significant predictor of glycogen utilization, may not be the most appropriate determinate of the functional characteristics of an individual fiber.

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