Regenerative Rehabilitation of Complex Musculoskeletal Injuries

摘要 复杂的肌肉骨骼创伤在战斗和高能民用事故中都很常见，并且常常导致 导致长期残疾或骨骼不愈合。再生康复是一个新兴领域，具有潜力 改善下肢肌肉骨骼创伤患者的功能结果。我们的总体目标是 (i) 研究康复负荷作为严重复杂情况的再生康复治疗策略 肌肉骨骼创伤和（ii）了解康复负荷、局部再生之间的关系 生态位机制和生物反应。我们将通过以下具体目标来实现这些目标。 具体目标 1：确定康复负荷、损伤严重程度和性别对再生的影响 利基机械信号和功能再生。在股骨缺损的大鼠模型中，我们将采用 析因实验设计，以确定针对严重损伤的有效康复负荷方案， 并确定康复对局部和全身生物反应和功能再生的影响 作为性别和损伤大小的函数。具体目标 2：将传感器支持的实时反馈集成到 康复方案并测试加速骨骼和肌肉功能恢复的能力 严重的肢体损伤。该目标将使用无线植入式应变传感器来提供无创监测 在康复负荷下的整个愈合过程中再生生态位中的力学。传感器 机械数据将用于确定应变范围，作为愈合状态的早期指标，并且 作为针对特定主题动态调整康复方案的标准，以加速 肌肉骨骼组织的功能再生。具体目标 3：建立基于预测的多元模型 局部再生生态位机械参数之间的相互依赖关系，系统 生物标志物和功能再生。有限元建模将用于生成模拟应变 使用植入式传感器测量显示再生利基机械信号的局部变化的地图 作为时变边界条件。线性多变量分析将用于绘制空间和时间图 康复环境下生物反应与局部再生生态位力学之间的关系 负荷方案。整合先前目标的早期机械数据和系统生物标志物数据， 非线性符号回归将用于开发骨骼和肌肉功能结果的预测模型 对于男女受试者。这些模型将在一项前瞻性研究中使用额外的队列进行测试 验证在一种性别中开发的模型是否可以预测两种性别的治愈结果 和异性。

SUMMARY Complex musculoskeletal trauma is common both in combat and high energy civilian accidents and often leads to prolonged disability or skeletal nonunion. Regenerative rehabilitation is an emerging field with the potential to improve functional outcomes for lower limb musculoskeletal trauma patients. Our overall objectives are to (i) investigate rehabilitative loading as a regenerative rehabilitation treatment strategy for severe complex musculoskeletal trauma and (ii) understand the relationship between rehabilitative loading, local regenerative niche mechanics, and the biological response. We will meet these objectives through the following specific aims. Specific Aim 1: Determine the effects of rehabilitative loading, injury severity and sex on regenerative niche mechanical signals and functional regeneration. In a rat model of a femoral bone defect, we will employ a factorial experimental design to determine effective rehabilitative loading protocols in critically sized injuries, and determine the effects of rehabilitation on local and systemic biological responses and functional regeneration as a function of sex and injury size. Specific Aim 2: Integrate sensor-enabled real-time feedback into rehabilitation protocols and test the ability to accelerate bone and muscle functional recovery following severe extremity injury. This aim will use wireless implantable strain sensors to provide noninvasive monitoring of mechanics in the regenerative niche throughout the progression of healing under rehabilitative loading. Sensor mechanical data will be used to identify strain ranges that serve as early indicators of healing status and are used as a criterion for dynamically adjusting the rehabilitation regimen on a subject-specific basis to accelerate functional regeneration of musculoskeletal tissue. Specific Aim 3: Build predictive multivariate models based on co-dependent relationships among local regenerative niche mechanical parameters, systemic biomarkers, and functional regeneration. Finite element modeling will be used to generate simulated strain maps showing local variations in regenerative niche mechanical signals using implantable sensor measurements as time-varying boundary conditions. Linear multivariate analyses will be used to map spatial and temporal relationships between the biological responses and local regenerative niche mechanics under rehabilitative loading regimens. Integrating early mechanical data and systemic biomarker data from the previous aims, nonlinear symbolic regression will be used to develop predictive models of bone and muscle functional outcomes for subjects of both sexes. These models will be tested in a prospective study using an additional cohort of both sexes to validate whether models developed in one sex can be predictive of healing outcomes in both the same and the opposite sexes.