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一种新的机械生物学模型可以预测生理相关的动态负荷如何导致机械损伤的关节软骨中蛋白聚糖的丢失。

A novel mechanobiological model can predict how physiologically relevant dynamic loading causes proteoglycan loss in mechanically injured articular cartilage.

机构信息

Department of Applied Physics, University of Eastern Finland, Kuopio, Finland.

Departments of Biological Engineering, Electrical Engineering and Computer Science and Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA.

出版信息

Sci Rep. 2018 Oct 22;8(1):15599. doi: 10.1038/s41598-018-33759-3.

Abstract

Cartilage provides low-friction properties and plays an essential role in diarthrodial joints. A hydrated ground substance composed mainly of proteoglycans (PGs) and a fibrillar collagen network are the main constituents of cartilage. Unfortunately, traumatic joint loading can destroy this complex structure and produce lesions in tissue, leading later to changes in tissue composition and, ultimately, to post-traumatic osteoarthritis (PTOA). Consequently, the fixed charge density (FCD) of PGs may decrease near the lesion. However, the underlying mechanisms leading to these tissue changes are unknown. Here, knee cartilage disks from bovine calves were injuriously compressed, followed by a physiologically relevant dynamic compression for twelve days. FCD content at different follow-up time points was assessed using digital densitometry. A novel cartilage degeneration model was developed by implementing deviatoric and maximum shear strain, as well as fluid velocity controlled algorithms to simulate the FCD loss as a function of time. Predicted loss of FCD was quite uniform around the cartilage lesions when the degeneration algorithm was driven by the fluid velocity, while the deviatoric and shear strain driven mechanisms exhibited slightly discontinuous FCD loss around cracks. Our degeneration algorithm predictions fitted well with the FCD content measured from the experiments. The developed model could subsequently be applied for prediction of FCD depletion around different cartilage lesions and for suggesting optimal rehabilitation protocols.

摘要

软骨提供低摩擦特性,在关节中起着重要作用。水合基质主要由糖胺聚糖 (PGs) 和纤维状胶原网络组成,是软骨的主要成分。不幸的是,创伤性关节负荷会破坏这种复杂的结构,并在组织中产生损伤,随后导致组织成分发生变化,最终导致创伤后骨关节炎 (PTOA)。因此,PGs 的固定电荷密度 (FCD) 在病变附近可能会降低。然而,导致这些组织变化的潜在机制尚不清楚。在这里,使用数字密度测定法评估了不同随访时间点的 FCD 含量。通过实施偏应变和最大剪切应变以及控制流速的算法,开发了一种新的软骨退变模型,以模拟 FCD 随时间的损失。当退化算法由流速驱动时,FCD 的损失在软骨病变周围非常均匀,而由偏应变和剪切应变驱动的机制在裂纹周围表现出略微不连续的 FCD 损失。我们的退化算法预测与实验测量的 FCD 含量非常吻合。随后可以将开发的模型应用于预测不同软骨病变周围的 FCD 耗竭,并提出最佳康复方案。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/c20b/6197240/2bce657404ad/41598_2018_33759_Fig1_HTML.jpg

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