Predicting collagen turnover for tendon repair across diverse loading environments

总结 数百万的美国人目前有一定程度的肌腱撕裂，留下的组织与异常胶原蛋白 数量和排列，以及降低的机械性能。胶原蛋白重塑依赖于机械 因此，恢复正常肌腱结构的治疗干预措施在不同的国家和地区可能具有不同的效果。 不同的加载环境，即患者特定的几何形状、运动或损伤严重程度。我们最终的，长久的- 长期目标是设计专门针对不同负荷环境下肌腱的治疗方法。 胶原蛋白重塑是由基质蛋白、基质蛋白和胶原之间的相互作用的复杂系统控制的。 金属蛋白酶（MMPs）、金属蛋白酶组织抑制剂（TIMPs）、降解产物和生长 这些因素，机械负荷影响许多这些相互作用。在此，我们建议通过实验 阐明胶原-MMP-生长因子网络的未知机械敏感性，并开发一种 整合多方面网络交互作为筛选潜力工具的计算模型 治疗干预。具体来说，我们的目标是1）测试拉伸负荷对MMP特异性降解的影响 通过使胶原蛋白I和III凝胶经受不同水平的应变，加入或不加入腱， 2）测试拉伸负荷可以通过以下方式从胶原基质中释放活性TGFβ的假设： 使胶原I和III凝胶经受各种水平的应变，并测量胶原I和III凝胶中潜在和活性TGFβ的水平。 凝胶和介质，以及3）构建和测试（离体和体内）负荷依赖性肌腱的计算模型 基质周转，捕获胶原蛋白，MMPs，TIMPs，降解产物和TGFβ相互作用， 常微分方程组总的来说，这些目标将立即影响该领域的基本 负载对基质周转的影响的知识，也产生了第一个大规模的胶原蛋白模型- MMP-生长因子网络，立即影响该领域的能力，前瞻性地设计治疗 干预（例如，物理治疗方案、MMP-或TIMP-靶向药物等）控制肌腱基质 内容和对齐给定任何特定的负载和几何形状。这种预测能力将极大地支持 建议的COBRE重点是虚拟人体试验的患者特定建模。

SUMMARY Millions of Americans currently have some degree of tendon tear that leaves the tissue with abnormal collagen quantity and alignment, and reduced mechanical properties. Collagen remodeling depends on mechanical loading, and therefore therapeutic interventions to restore normal tendon structure can have varied effects across diverse loading environments, i.e. patient-specific geometries, motions, or injury severities. Our ultimate, long- term objective is to design therapies tailored specifically for tendons across different loading environments. Collagen remodeling is governed by a complex system of interactions between matrix proteins, matrix metalloproteinases (MMPs), tissue inhibitors of metalloproteinases (TIMPs), degradation products, and growth factors, with mechanical loading affecting many of these interactions. Herein, we propose to experimentally elucidate unknown mechano-sensitivities of the collagen-MMP-growth factor network, and develop a computational model that integrates the multi-faceted network interactions as a tool for screening potential therapeutic interventions. Specifically, we aim to 1) test the effect of tensile loading on MMP-specific degradation of collagens by subjecting collagen I and III gels to various levels of strain with or without the addition of tendon- relevant MMPs, 2) test the hypothesis that tensile loading can release active TGFβ from collagenous matrix by subjecting collagen I and III gels to various levels of strain and measuring levels of latent and active TGFβ in the gels and media, and 3) build and test (ex vivo and in vivo) a computational model of load-dependent tendon matrix turnover that captures collagens, MMPs, TIMPs, degradation products, and TGFβ interactions as a system of ordinary differential equations. Collectively, these aims will immediately impact the field's basic knowledge of loading effects on matrix turnover and also produce the first large-scale model of the collagen- MMP-growth factor network, immediately impacting the field's ability to prospectively design therapeutic interventions (e.g., physical therapy regimens, MMP- or TIMP-targeting drugs, etc.) to control tendon matrix content and alignment given any specific loading and geometry. Such predictive capability will greatly support the proposed COBRE focus of patient-specific modeling for virtual human trials.