Kapitanov Georgi I, Ayati Bruce P, Martin James A
Department of Mathematics, University of Iowa, Iowa City, IA, United States of America.
Program in Applied Mathematical & Computational Sciences, University of Iowa, Iowa City, IA, United States of America.
PeerJ. 2017 Jul 17;5:e3468. doi: 10.7717/peerj.3468. eCollection 2017.
Osteoarthritis (OA) is a disease characterized by degeneration of joint cartilage. It is associated with pain and disability and is the result of either age and activity related joint wear or an injury. Non-invasive treatment options are scarce and prevention and early intervention methods are practically non-existent. The modeling effort presented in this article is constructed based on an emerging biological hypothesis-post-impact oxidative stress leads to cartilage cell apoptosis and hence the degeneration observed with the disease. The objective is to quantitatively describe the loss of cell viability and function in cartilage after an injurious impact and identify the key parameters and variables that contribute to this phenomenon.
We constructed a system of differential equations that tracks cell viability, mitochondrial function, and concentrations of reactive oxygen species (ROS), adenosine triphosphate (ATP), and glycosaminoglycans (GAG). The system was solved using MATLAB and the equations' parameters were fit to existing data using a particle swarm algorithm.
The model fits well the available data for cell viability, ATP production, and GAG content. Local sensitivity analysis shows that the initial amount of ROS is the most important parameter.
The model we constructed is a viable method for producing in silico studies and with a few modifications, and data calibration and validation, may be a powerful predictive tool in the search for a non-invasive treatment for post-traumatic osteoarthritis.
骨关节炎（OA）是一种以关节软骨退变为特征的疾病。它与疼痛和残疾相关，是年龄和活动相关的关节磨损或损伤的结果。非侵入性治疗选择稀缺，预防和早期干预方法实际上不存在。本文提出的建模工作基于一种新出现的生物学假说构建——撞击后氧化应激导致软骨细胞凋亡，进而导致该疾病中观察到的退变。目的是定量描述损伤性撞击后软骨细胞活力和功能的丧失，并确定导致这种现象的关键参数和变量。
我们构建了一个微分方程组，用于跟踪细胞活力、线粒体功能以及活性氧（ROS）、三磷酸腺苷（ATP）和糖胺聚糖（GAG）的浓度。该系统使用MATLAB求解，并使用粒子群算法将方程参数拟合到现有数据。
该模型很好地拟合了细胞活力、ATP产生和GAG含量的现有数据。局部敏感性分析表明，ROS的初始量是最重要的参数。
我们构建的模型是进行计算机模拟研究的一种可行方法，经过一些修改以及数据校准和验证后，可能成为寻找创伤后骨关节炎非侵入性治疗方法的强大预测工具。
