Mehdizadeh Arash, Gardiner Bruce S, Lavagnino Michael, Smith David W
Faculty of Engineering, Computing and Mathematics, University of Western Australia, Crawley, WA, Australia.
School of Engineering, Australian College of Kuwait, West Mishref, Kuwait.
Biomech Model Mechanobiol. 2017 Aug;16(4):1329-1348. doi: 10.1007/s10237-017-0890-x. Epub 2017 Mar 13.
In this study, we propose a method for quantitative prediction of changes in concentrations of a number of key signaling, structural and effector molecules within the extracellular matrix of tendon. To achieve this, we introduce the notion of elementary cell responses (ECRs). An ECR defines a normal reference secretion profile of a molecule by a tenocyte in response to the tenocyte's local strain. ECRs are then coupled with a model for mechanical damage of tendon collagen fibers at different straining conditions of tendon and then scaled up to the tendon tissue level for comparison with experimental observations. Specifically, our model predicts relative changes in ECM concentrations of transforming growth factor beta, interleukin 1 beta, collagen type I, glycosaminoglycan, matrix metalloproteinase 1 and a disintegrin and metalloproteinase with thrombospondin motifs 5, with respect to tendon straining conditions that are consistent with the observations in the literature. In good agreement with a number of in vivo and in vitro observations, the model provides a logical and parsimonious explanation for how excessive mechanical loading of tendon can lead to under-stimulation of tenocytes and a degenerative tissue profile, which may well have bearing on a better understanding of tendon homeostasis and the origin of some tendinopathies.
在本研究中，我们提出了一种定量预测肌腱细胞外基质中多种关键信号分子、结构分子和效应分子浓度变化的方法。为实现这一目标，我们引入了基本细胞反应（ECR）的概念。一个ECR定义了肌腱细胞对其局部应变做出反应时分子的正常参考分泌谱。然后，将ECR与肌腱在不同应变条件下胶原纤维机械损伤的模型相结合，并放大到肌腱组织水平，以便与实验观察结果进行比较。具体而言，我们的模型预测了转化生长因子β、白细胞介素1β、I型胶原、糖胺聚糖、基质金属蛋白酶1以及含血小板反应蛋白基序的解聚素和金属蛋白酶5在细胞外基质中的浓度相对于肌腱应变条件的相对变化，这些应变条件与文献中的观察结果一致。与许多体内和体外观察结果高度吻合，该模型为肌腱过度机械负荷如何导致肌腱细胞刺激不足和组织退变提供了合理且简洁的解释，这可能有助于更好地理解肌腱稳态以及某些肌腱病的发病机制。
