利用基于代理的渐进性肺纤维化弹簧网络模型阐明伸展与僵硬之间的相互作用

Joseph K. Hall, Jason H. T. Bates, Ramaswamy Krishnan, Jae Hun Kim, Yuqing Deng, K. Lutchen, B. Suki
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引用次数: 0

摘要

肺纤维化是一种致命疾病,涉及对机械敏感的成纤维细胞和肌成纤维细胞的失调。以前的计算模型成功地模拟了硬度介导的成纤维细胞行为,但这些模型忽略了拉伸介导的行为,尤其是拉伸敏感通道和拉伸介导的潜伏 TGF-β 释放。在这里,我们开发并探索了一种基于代理的模型和弹簧网络模型的混合模型,该模型能够再现僵硬和拉伸。利用该模型,我们分别评估了自我修复和纤维化过程中机械信号在平衡和疾病进展中的作用。我们建立的模型存在一个纤维化阈值,在该阈值附近,网络趋向于不稳定和纤维化,而在该阈值以下,网络趋向于愈合。自愈反应是由拉伸信号引起的,而纤维化反应则发生在刚度信号超过拉伸信号时,这就形成了一个正反馈回路。我们还发现,通过改变拉伸和僵硬信号的比例权重,我们可以观察到病理网络结构的异质性,这与人类 IPF 组织中的情况类似。该系统还显示出突发性行为和分岔:网络是愈合还是纤维化取决于损伤的初始网络组织,这清楚地表明了结构在整个网络的愈合或纤维化中的关键作用。总之,这些结果有力地表明,肺部存在的机械信号与网络效应相结合,有助于平衡和疾病的发展。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Elucidating the interaction between stretch and stiffness using an agent-based spring network model of progressive pulmonary fibrosis
Pulmonary fibrosis is a deadly disease that involves the dysregulation of fibroblasts and myofibroblasts, which are mechanosensitive. Previous computational models have succeeded in modeling stiffness-mediated fibroblasts behaviors; however, these models have neglected to consider stretch-mediated behaviors, especially stretch-sensitive channels and the stretch-mediated release of latent TGF-β. Here, we develop and explore an agent-based model and spring network model hybrid that is capable of recapitulating both stiffness and stretch. Using the model, we evaluate the role of mechanical signaling in homeostasis and disease progression during self-healing and fibrosis, respectively. We develop the model such that there is a fibrotic threshold near which the network tends towards instability and fibrosis or below which the network tends to heal. The healing response is due to the stretch signal, whereas the fibrotic response occurs when the stiffness signal overpowers the stretch signal, creating a positive feedback loop. We also find that by changing the proportional weights of the stretch and stiffness signals, we observe heterogeneity in pathological network structure similar to that seen in human IPF tissue. The system also shows emergent behavior and bifurcations: whether the network will heal or turn fibrotic depends on the initial network organization of the damage, clearly demonstrating structure’s pivotal role in healing or fibrosis of the overall network. In summary, these results strongly suggest that the mechanical signaling present in the lungs combined with network effects contribute to both homeostasis and disease progression.
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