Literature DB >> 16096841

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

Chris M Gregory1, Richard H Williams, Krista Vandenborne, Gary A Dudley.   

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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Year:  2005        PMID: 16096841     DOI: 10.1007/s00421-005-0003-x

Source DB:  PubMed          Journal:  Eur J Appl Physiol        ISSN: 1439-6319            Impact factor:   3.078


  33 in total

1.  Metabolic enzymes and phenotypic expression among human locomotor muscles.

Authors:  C M Gregory; K Vandenborne; G A Dudley
Journal:  Muscle Nerve       Date:  2001-03       Impact factor: 3.217

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Review 3.  Recruitment patterns in human skeletal muscle during electrical stimulation.

Authors:  Chris M Gregory; C Scott Bickel
Journal:  Phys Ther       Date:  2005-04

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Journal:  Histochemistry       Date:  1986

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Authors:  S W Stevenson; G A Dudley
Journal:  Med Sci Sports Exerc       Date:  2001-08       Impact factor: 5.411

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Journal:  J Histochem Cytochem       Date:  1970-09       Impact factor: 2.479

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Authors:  L Guth; F J Samaha
Journal:  Exp Neurol       Date:  1969-09       Impact factor: 5.330

8.  Effects of stimulation intensity on the physiological responses of human motor units.

Authors:  S A Binder-Macleod; E E Halden; K A Jungles
Journal:  Med Sci Sports Exerc       Date:  1995-04       Impact factor: 5.411

9.  Quantitative histochemical determination of muscle enzymes: biochemical verification.

Authors:  T P Martin; A C Vailas; J B Durivage; V R Edgerton; K R Castleman
Journal:  J Histochem Cytochem       Date:  1985-10       Impact factor: 2.479

10.  Skeletal muscle enzyme activity, fiber composition and VO2 max in relation to distance running performance.

Authors:  C Foster; D L Costill; J T Daniels; W J Fink
Journal:  Eur J Appl Physiol Occup Physiol       Date:  1978-08-15
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  1 in total

1.  Electrical Stimulation Frequency and Skeletal Muscle Characteristics: Effects on Force and Fatigue.

Authors:  Maria Vromans; Pouran Faghri
Journal:  Eur J Transl Myol       Date:  2017-12-05
  1 in total

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