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Effects of ursolic acid on sub-lesional muscle pathology in a contusion model of spinal cord injury
Journal article   Open access   Peer reviewed

Effects of ursolic acid on sub-lesional muscle pathology in a contusion model of spinal cord injury

Gregory E. Bigford, Andrew J. Darr, Valerie C. Bracchi-Ricard, Han Gao, Mark S. Nash and John R. Bethea
PloS one, v 13(8), pp e0203042-e0203042
29 Aug 2018
PMID: 30157245
url
https://doi.org/10.1371/journal.pone.0203042View
Published, Version of Record (VoR)CC BY V4.0 Open

Abstract

Multidisciplinary Sciences Science & Technology Science & Technology - Other Topics
Spinal Cord Injury (SCI) results in severe sub-lesional muscle atrophy and fiber type transformation from slow oxidative to fast glycolytic, both contributing to functional deficits and maladaptive metabolic profiles. Therapeutic countermeasures have had limited success and muscle-related pathology remains a clinical priority. mTOR signaling is known to play a critical role in skeletal muscle growth and metabolism, and signal integration of anabolic and catabolic pathways. Recent studies show that the natural compound ursolic acid (UA) enhances mTOR signaling intermediates, independently inhibiting atrophy and inducing hypertrophy. Here, we examine the effects of UA treatment on sub-lesional muscle mTOR signaling, catabolic genes, and functional deficits following severe SCI in mice. We observe that UA treatment significantly attenuates SCI induced decreases in activated forms of mTOR, and signaling intermediates PI3K, AKT, and S6K, and the upregulation of catabolic genes including FOXO1, MAFbx, MURF-1, and PSMD11. In addition, UA treatment improves SCI induced deficits in body and sub-lesional muscle mass, as well as functional outcomes related to muscle function, motor coordination, and strength. These findings provide evidence that UA treatment may be a potential therapeutic strategy to improve muscle-specific pathological consequences of SCI.

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22 citations in Scopus

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Collaboration types
Domestic collaboration
Web of Science research areas
Clinical Neurology
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