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.

技术开发：摘要为了进一步支持再生康复研究，我们将开发新技术来扩大再生康复研究的范围。再生康复研究的设备。待开发的技术将集中于功能评估（目标 1）和干预策略（目标 2）。将再生康复方案转化为有意义的临床的主要障碍应用的问题可以说是缺乏有意义、敏感和可靠的临床前功能评估。这再生的大部分临床前测量涉及组织学分析和/或离体/原位机械分析测试范例。然而，这些最终且耗时的分析排除了对变化的评估。随着时间的推移身体机能。目标 1 中的研究将改进对功能恢复的分析使用机器学习方法来自动化步态运动学的小鼠模型。导出的算法将描述损伤后的正常值和病理步态模式。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关于骨骼肌功能长期恢复的预测。再生康复的前提是干细胞对外在机械、电刺激和热刺激。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调节局部微环境以改善组织再生的响应性生物材料。压电式材料将机械刺激（例如运动或超声波）转化为局部电场，调节驻留干细胞的增殖、迁移和分化。目标 2 研究将发展并优化与机械加载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。未来几年，我们将与外部合作研究人员评估压电材料在其他适应症中的应用，例如周围神经损伤。为了确保我们能够高度响应社区的需求，在第 2-5 年中，我们将通过我们的每月通讯和 AR3T 2.0 活动（即高级培训课程、会议和研讨会），以衡量该技术的潜在用户数量我们支持其发展。最后，我们将调查我们的社区，以确定将最大限度地影响质量和再生康复研究的范围。本次调查结果将用于指导下一步发电技术开发工作在后几年得到了补助。