Journal
JOURNAL OF APPLIED PHYSIOLOGY
Volume 115, Issue 11, Pages 1714-1724Publisher
AMER PHYSIOLOGICAL SOC
DOI: 10.1152/japplphysiol.00848.2013
Keywords
cross-sectional area; image segmentation; muscle; myonuclei counting
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Funding
- National Institutes of Health (NIH) [AG-34453, AR-60701]
- Ellison Medical Foundation/American Federation of Aging Research Fellowship [EPD 12102]
- Jeane B. Kempner Postdoctoral Scholar Award
- NIH National Center for Advancing Translational Sciences [UL1TR000117]
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Skeletal muscle is an exceptionally adaptive tissue that compromises 40% of mammalian body mass. Skeletal muscle functions in locomotion, but also plays important roles in thermogenesis and metabolic homeostasis. Thus characterizing the structural and functional properties of skeletal muscle is important in many facets of biomedical research, ranging from myopathies to rehabilitation sciences to exercise interventions aimed at improving quality of life in the face of chronic disease and aging. In this paper, we focus on automated quantification of three important morphological features of muscle: 1) muscle fiber-type composition; 2) muscle fiber-type-specific cross-sectional area, and 3) myonuclear content and location. We experimentally prove that the proposed automated image analysis approaches for fiber-type-specific assessments and automated myonuclei counting are fast, accurate, and reliable.
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