Coordinating Center

协调中心

基本信息

批准号：
10210420
负责人：
Fabrisia Ambrosio
金额：
$ 12.33万
依托单位：
UNIVERSITY OF PITTSBURGH AT PITTSBURGH
依托单位国家：
美国
项目类别：
财政年份：
2020
资助国家：
美国
起止时间：
2020-07-06 至 2025-06-30
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10210420
关键词：
3-Dimensional Activities of Daily Living Acute Address Algorithms Animals Biocompatible Materials Biological Models Cell Lineage Characteristics Communities Computer software Consumption Data Development Disease Effectiveness Event Exercise Feedback Fibrosis Future Gait Generations Goals Grant Heart Histologic In Situ In Vitro Individual Injury Intervention Investigation Lead Lesion Machine Learning Maps Measurement Measures Mechanics Modeling Mus Muscle Muscle function Muscle satellite cell Natural History Natural regeneration Nerve Newsletter Pathologic Pattern Peripheral nerve injury Physical Function Physiological Pre-Clinical Model Protocols documentation Recovery Recovery of Function Regenerative Medicine Regenerative capacity Rehabilitation therapy Research Personnel Research Training Running Science Skeletal Muscle Skin Stem cell transplant Stimulus Surveys Systems Analysis Techniques Technology Testing Therapeutic Intervention Time Tissues Training Translations Ultrasonography Work automated analysis bone clinical application clinical practice efficacy testing electric field functional disability gait examination healing improved injury recovery kinematics machine learning algorithm mechanical load migration mouse model muscle regeneration new technology next generation novel pre-clinical pre-clinical assessment predictive modeling primary outcome regenerative rehabilitation regenerative tissue rehabilitation research rehabilitation strategy response restoration scaffold stem cell migration stem cell proliferation stem cells symposium technology development tissue injury tissue regeneration tool treadmill uptake volumetric muscle loss

项目摘要

TECHNOLOGY DEVELOPMENT: ABSTRACT To further support Regenerative Rehabilitation research, we will develop novel technologies that expand the armamentarium of Regenerative Rehabilitation investigations. The technologies to be developed will focus on functional assessment (Aim 1) and interventional strategies (Aim 2). A major impediment to the translation of Regenerative Rehabilitation protocols into meaningful clinical applications is arguably the lack of meaningful, sensitive, and reliable pre-clinical assessments of function. The bulk of pre-clinical measures of regeneration involve histological analyses and/or ex vivo/in situ mechanical testing paradigms. However, these terminal and time-consuming analyses preclude the assessment of changes in physical functioning over time. The studies in Aim 1 will improve the analysis of functional recovery in a murine model using machine learning approaches to automate gait kinematics. Algorithms derived will describe normative values as well as patterns of pathologic gait after injury. Ultimately, we will employ predictive modeling to identify a function that maps input data obtained from the gait analysis software to make predictions about long-term restoration of skeletal muscle function. Regenerative Rehabilitation was borne on the premise that stem cells are responsive to extrinsic mechanical, electrical, and thermal stimuli. The application of these stimuli represents a pillar of rehabilitation clinical practice. We propose that next generation Regenerative Rehabilitation studies will implement stimuli- responsive biomaterials that modulate the local microenvironment to improve tissue regeneration. Piezoelectric materials convert mechanical stimuli, such as by exercise or ultrasound, into a local electric field that may modulate resident stem cell proliferation, migration, and differentiation. Aim 2 studies will develop and optimize a piezoelectric biomaterial scaffold used in combination with mechanical loading to promote functional skeletal muscle regeneration after an acute injury. In future years, we will work with external investigators to evaluate the use of piezoelectric materials for other indications, such as peripheral nerve injury. So as to make sure that we are highly responsive to the needs of our community, in years 2-5, we will distribute polls through our monthly newsletter and at AR3T 2.0 events (i.e. advanced training courses, conference sessions, and the Symposium) in order to gauge the number of potential users of the technology whose development we have supported. Finally, we will survey our community to identify technologies that will maximally impact the quality and scope of Regenerative Rehabilitation investigations. The results of this survey will be used to guide next generation technology development efforts in the latter years of the grant.

技术发展：摘要为了进一步支持再生康复研究，我们将开发出扩展的新技术再生康复调查的武术。要开发的技术将重点放在功能评估（目标1）和介入策略（AIM 2）。将再生康复方案转化为有意义的临床的主要障碍应用可以说是缺乏有意义的，敏感和可靠的功能前临床评估。这大部分再生前临床前测量涉及组织学分析和/或原位机械的机械分析测试范例。但是，这些终端和耗时的分析排除了评估的评估随着时间的流逝，身体功能。 AIM 1中的研究将改善A中功能恢复的分析使用机器学习方法自动化步态运动学的鼠模型。得出的算法将描述损伤后的规范值以及病理步态的模式。最终，我们将采用预测建模以识别映射从步态分析软件获得的输入数据的函数，以使关于骨骼肌功能的长期恢复的预测。再生康复的前提是干细胞对外部机械的反应，电气和热刺激。这些刺激的应用代表了康复临床的支柱实践。我们建议下一代再生康复研究将实施刺激反应迅速的生物材料，可调节局部微环境改善组织再生。压电材料将机械刺激（例如通过锻炼或超声波）转换为可能的当地电场调节常驻干细胞增殖，迁移和分化。 AIM 2研究将发展和优化与机械载荷结合使用的压电生物材料支架以促进急性损伤后功能性骨骼肌再生。在未来的几年中，我们将与外部合作研究人员评估使用压电材料来用于其他适应症，例如外周神经损伤。为了确保我们对社区的需求有很高的反应，在2 - 5年内，我们将通过我们的每月新闻通讯和AR3T 2.0活动（即高级培训课程，会议会议和研讨会），以评估该技术的潜在用户数量我们支持谁的发展。最后，我们将调查我们的社区，以确定将对质量产生最大影响和的技术再生康复调查的范围。该调查的结果将用于指导下一步赠款后期的一代技术开发工作。