UCL Mechanical Engineering, London, UK.
UCL Centre for Nerve Engineering, UK.
J R Soc Interface. 2022 Mar;19(188):20210824. doi: 10.1098/rsif.2021.0824. Epub 2022 Mar 2.
Peripheral nerve injuries affect millions of people per year and cause loss of sensation and muscle control alongside chronic pain. The most severe injuries are treated through a nerve autograft; however, donor site morbidity and poor outcomes mean alternatives are required. One option is to engineer nerve replacement tissues to provide a supportive microenvironment to encourage nerve regeneration as an alternative to nerve grafts. Currently, progress is hampered due to a lack of consensus on how to arrange materials and cells in space to maximize rate of regeneration. This is compounded by a reliance on experimental testing, which precludes extensive investigations of multiple parameters due to time and cost limitations. Here, a computational framework is proposed to simulate the growth of repairing neurites, captured using a random walk approach and parameterized against literature data. The framework is applied to a specific scenario where the engineered tissue comprises a collagen hydrogel with embedded biomaterial fibres. The size and number of fibres are optimized to maximize neurite regrowth, and the robustness of model predictions is tested through sensitivity analyses. The approach provides an tool to inform the design of engineered replacement tissues, with the opportunity for further development to multi-cue environments.
周围神经损伤每年影响数百万人，导致感觉和肌肉控制丧失以及慢性疼痛。最严重的损伤通过神经自体移植物治疗；然而，供体部位发病率和不良结果意味着需要替代方案。一种选择是工程化神经替代组织，以提供支持性的微环境，作为神经移植物的替代物来促进神经再生。目前，由于缺乏如何在空间中安排材料和细胞以最大程度地提高再生率的共识，进展受到阻碍。这是由于对实验测试的依赖造成的，由于时间和成本的限制，实验测试排除了对多个参数的广泛研究。在这里，提出了一个计算框架来模拟修复神经突的生长，使用随机游走方法捕获，并根据文献数据进行参数化。该框架应用于一个特定的场景，其中工程化组织由嵌入生物材料纤维的胶原水凝胶组成。优化纤维的大小和数量以最大程度地促进神经突再生，并通过敏感性分析测试模型预测的稳健性。该方法提供了一种工具，可以为工程化替代组织的设计提供信息，并为多线索环境提供进一步发展的机会。
