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Therapeutic Strategies to Augment Muscle Rehabilitation

Therapeutic Strategies to Augment Muscle Rehabilitation
增强肌肉康复的治疗策略
批准号:
7945352
负责人:
KRISTA H VANDENBORNE
金额:
$113.69万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2009
资助国家:
美国
项目状态:
已结题
起止时间:
2009-09-30 至 2012-08-31

项目摘要

项目成果

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中文摘要
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英文摘要
The long-range of this project is to develop novel therapeutic strategies that ameliorate muscle atrophy and accelerate muscle rehabilitation following pathological conditions such as spinal cord injury. This application is consistent with the vision of the Christopher and Dana Reeve Paralysis Act (CDRPA) which promotes the interaction of scientists conducting similar work to further enhance understanding and expedite the search for effective treatment interventions for millions of Americans living with paralysis. "The CDRPA encourages coordination of research to prevent redundancies and hopefully hasten discovery of better treatments and cures and, as importantly, to improve the daily lives today for those living with paralysis". The proposed application presents a unique collaboration between a group of productive scientists with diverse, yet complimentary expertise and a common interest in the recovery of muscle and motor function. This team of national experts explores a new area of research focusing on complimentary treatment strategies utilizing pharmacological/molecular therapies modulating muscle growth in conjunction with emerging rehabilitation interventions. The specific objectives of this 2 year application are: 1) To identify novel pharmacological strategies to ameliorate muscle atrophy induced by disuse/unloading and promote muscle recovery; 2) To validate a new animal model of incomplete spinal cord injury for the assessment of rehabilitation strategies. This Project will provide important preclinical data in an area of rapid pharmacological development and will set the stage for a more clinical relevant model of spinal cord injury. The drugs that are targeted are either approved for human use or they are in clinical development and will allow rapid translation to animal models. This proposal provides some unique opportunities and presents an important step forward in the translation towards human trials. The results of the individual studies will also make important new contributions to the science base of muscle rehabilitation and spinal cord injury.
期刊论文(3)
专著(0)
科研奖励(0)
会议论文
Hindlimb muscle morphology and function in a new atrophy model combining spinal cord injury and cast immobilization.
结合脊髓损伤和石膏固定的新型萎缩模型中的后肢肌肉形态和功能。
DOI: 10.1089/neu.2012.2504
发表时间: 2013
期刊: Journal of neurotrauma
影响因子: 4.2
作者: [Ye,Fan, Baligand,Celine, Keener,JonathonE, Vohra,Ravneet, Lim,Wootaek, Ruhella,Arjun, Bose,Prodip, Daniels,Michael, Walter,GlennA, Thompson,Floyd, Vandenborne,Krista]
通讯作者: Vandenborne,Krista
DOI: 10.1007/s00421-013-2810-9
发表时间: 2014-04
期刊: EUROPEAN JOURNAL OF APPLIED PHYSIOLOGY
影响因子: 3
作者: [Shah, Prithvi K., Ye, Fan, Liu, Min, Jayaraman, Arun, Baligand, Celine, Walter, Glenn, Vandenborne, Krista]
通讯作者: Vandenborne, Krista
DOI: 10.1310/sci2016-0007
发表时间: 2016-01-01
期刊: Topics in spinal cord injury rehabilitation
影响因子: 2.9
作者: [Phadke, Chetan P, Flynn, Sheryl, Behrman, Andrea L]
通讯作者: Behrman, Andrea L
IMPACT OF VIRAL-MEDIATED IGF-I GENE TRANSFER ON SKELETAL MUSCLE FOLLOWING
  • 批准号:
    8361458
  • 项目类别:
  • 资助金额:
    $1.22万
  • 财政年份:
    2011
  • 负责人:
    KRISTA H VANDENBORNE
  • 依托单位:
Magnetic Resonance Imaging and Biomarkers for Muscular Dystrophy
  • 批准号:
    10259678
  • 项目类别:
  • 资助金额:
    $120.79万
  • 财政年份:
    2010
  • 负责人:
    KRISTA H VANDENBORNE
  • 依托单位:
Magnetic Resonance Imaging and Biomarkers for Muscular Dystrophy
  • 批准号:
    8069808
  • 项目类别:
  • 资助金额:
    $136.33万
  • 财政年份:
    2010
  • 负责人:
    KRISTA H VANDENBORNE
  • 依托单位:
Magnetic Resonance Imaging and Biomarkers for Muscular Dystrophy
  • 批准号:
    8666519
  • 项目类别:
  • 资助金额:
    $134.29万
  • 财政年份:
    2010
  • 负责人:
    KRISTA H VANDENBORNE
  • 依托单位:
国内基金
海外基金
Scalable Learning and Optimization: High-dimensional Models and Online Decision-Making Strategies for Big Data Analysis