Title |
Use of imaging biomarkers to assess perfusion and glucose metabolism in the skeletal muscle of dystrophic mice
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Published in |
BMC Musculoskeletal Disorders, June 2011
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DOI | 10.1186/1471-2474-12-127 |
Pubmed ID | |
Authors |
Nabeel Ahmad, Ian Welch, Robert Grange, Jennifer Hadway, Savita Dhanvantari, David Hill, Ting-Yim Lee, Lisa M Hoffman |
Abstract |
Duchenne muscular dystrophy (DMD) is a severe neuromuscular disease that affects 1 in 3500 boys. The disease is characterized by progressive muscle degeneration that results from mutations in or loss of the cytoskeletal protein, dystrophin, from the glycoprotein membrane complex, thus increasing the susceptibility of contractile muscle to injury. To date, disease progression is typically assessed using invasive techniques such as muscle biopsies, and while there are recent reports of the use of magnetic resonance, ultrasound and optical imaging technologies to address the issue of disease progression and monitoring therapeutic intervention in dystrophic mice, our study aims to validate the use of imaging biomarkers (muscle perfusion and metabolism) in a longitudinal assessment of skeletal muscle degeneration/regeneration in two murine models of muscular dystrophy. |
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Geographical breakdown
Country | Count | As % |
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Canada | 1 | 100% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 1 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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Canada | 2 | 3% |
United States | 1 | 1% |
Netherlands | 1 | 1% |
Brazil | 1 | 1% |
Unknown | 71 | 93% |
Demographic breakdown
Readers by professional status | Count | As % |
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Researcher | 15 | 20% |
Student > Ph. D. Student | 11 | 14% |
Student > Master | 11 | 14% |
Other | 8 | 11% |
Student > Bachelor | 7 | 9% |
Other | 18 | 24% |
Unknown | 6 | 8% |
Readers by discipline | Count | As % |
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Medicine and Dentistry | 18 | 24% |
Agricultural and Biological Sciences | 17 | 22% |
Pharmacology, Toxicology and Pharmaceutical Science | 5 | 7% |
Nursing and Health Professions | 4 | 5% |
Biochemistry, Genetics and Molecular Biology | 4 | 5% |
Other | 15 | 20% |
Unknown | 13 | 17% |