کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
8276735 | 1535116 | 2014 | 6 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Gait characteristics in a canine model of X-linked myotubular myopathy
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کلمات کلیدی
موضوعات مرتبط
علوم زیستی و بیوفناوری
بیوشیمی، ژنتیک و زیست شناسی مولکولی
سالمندی
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چکیده انگلیسی
X-linked myotubular myopathy (XLMTM) is a fatal pediatric disease where affected boys display profound weakness of the skeletal muscles. Possible therapies are under development but robust outcome measures in animal models are required for effective translation to human patients. We established a naturally-occurring canine model, where XLMTM dogs display clinical symptoms similar to those observed in humans. The aim of this study was to determine potential endpoints for the assessment of future treatments in this model. Video-based gait analysis was selected, as it is a well-established method of assessing limb function in neuromuscular disease and measures have been correlated to the patient's quality of life. XLMTM dogs (NÂ =Â 3) and their true littermate wild type controls (NÂ =Â 3) were assessed at 4-5 time points, beginning at 10Â weeks and continuing through 17Â weeks. Motion capture and an instrumented carpet were used separately to evaluate spatiotemporal and kinematic changes over time. XLMTM dogs walk more slowly and with shorter stride lengths than wild type dogs, and these differences became greater over time. However, there was no clear difference in angular measures between affected and unaffected dogs. These data demonstrate that spatiotemporal parameters capture functional changes in gait in an XLMTM canine model and support their utility in future therapeutic trials.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of the Neurological Sciences - Volume 346, Issues 1â2, 15 November 2014, Pages 221-226
Journal: Journal of the Neurological Sciences - Volume 346, Issues 1â2, 15 November 2014, Pages 221-226
نویسندگان
Melissa A. Goddard, Emily Burlingame, Alan H. Beggs, Anna Buj-Bello, Martin K. Childers, Anthony P. Marsh, Valerie E. Kelly,