Predicting collagen turnover for tendon repair across diverse loading environments

摘要 数以百万计的美国人目前有不同程度的肌腱撕裂，使组织中的胶原蛋白异常 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 负荷，因此恢复正常肌腱结构的治疗干预可以有不同的影响 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。我们终极的，长久的- 学期目标是设计专门针对不同负荷环境下的肌腱的治疗方法。 胶原蛋白重塑是由基质蛋白、基质之间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物(TIMPs)、降解产物和生长 影响这些相互作用的因素很多，其中机械载荷影响很大。在此，我们建议在实验中 阐明胶原-基质金属蛋白酶-生长因子网络未知的机械敏感性，并开发一种 集成多方面网络交互作为筛选潜力的工具的计算模型 治疗性干预。具体地说，我们的目标是1)测试拉伸载荷对基质金属蛋白酶特异性降解的影响 通过使I型和III型胶原凝胶在添加或不添加肌腱的情况下承受不同程度的应变而产生的胶原蛋白- 相关的基质金属蛋白酶，2)检验拉伸负荷可以通过以下方式从胶原基质中释放活性转化生长因子β的假设 将I型和III型胶原凝胶置于不同水平的应变中，并测定细胞中潜伏和活性转化生长因子β的水平 凝胶和介质，以及3)建立和测试(体外和体内)负荷依赖肌腱的计算模型 基质周转率捕获胶原蛋白、MMP、TIMP、降解产物和转化生长因子β相互作用 常微分方程组。总而言之，这些目标将立即影响该领域的基本 了解负荷对基质周转的影响，并制作了第一个大规模的胶原模型- 基质金属蛋白酶-生长因子网络，立即影响该领域前瞻性设计治疗的能力 干预措施(例如，理疗方案、基质金属蛋白酶或TIMP靶向药物等)控制肌腱基质 给定任何特定载荷和几何图形的内容和对齐方式。这种预测能力将极大地支持 Cobre提出的针对特定患者的虚拟人试验建模重点。

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.