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Agent-based computational model investigates muscle-specific responses to disuse-induced atrophy

机译:基于代理的计算模型研究针对废用性萎缩的肌肉特异性反应

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摘要

Skeletal muscle is highly responsive to use. In particular, muscle atrophy attributable to decreased activity is a common problem among the elderly and injured/immobile. However, each muscle does not respond the same way. We developed an agent-based model that generates a tissue-level skeletal muscle response to disuse/immobilization. The model incorporates tissue-specific muscle fiber architecture parameters and simulates changes in muscle fiber size as a result of disuse-induced atrophy that are consistent with published experiments. We created simulations of 49 forelimb and hindlimb muscles of the rat by incorporating eight fiber-type and size parameters to explore how these parameters, which vary widely across muscles, influence sensitivity to disuse-induced atrophy. Of the 49 muscles modeled, the soleus exhibited the greatest atrophy after 14 days of simulated immobilization (51% decrease in fiber size), whereas the extensor digitorum communis atrophied the least (32%). Analysis of these simulations revealed that both fiber-type distribution and fiber-size distribution influence the sensitivity to disuse atrophy even though no single tissue architecture parameter correlated with atrophy rate. Additionally, software agents representing fibroblasts were incorporated into the model to investigate cellular interactions during atrophy. Sensitivity analyses revealed that fibroblast agents have the potential to affect disuse-induced atrophy, albeit with a lesser effect than fiber type and size. In particular, muscle atrophy elevated slightly with increased initial fibroblast population and increased production of TNF-α. Overall, the agent-based model provides a novel framework for investigating both tissue adaptations and cellular interactions in skeletal muscle during atrophy.
机译:骨骼肌对使用反应灵敏。特别地,归因于活动减少的肌肉萎缩是老年人和受伤/不活动者的普遍问题。但是,每个肌肉的反应方式都不相同。我们开发了一种基于代理的模型,该模型生成对停用/固定化的组织级骨骼肌反应。该模型结合了组织特有的肌纤维结构参数,并模拟了由于废弃引起的萎缩而导致的肌纤维大小变化,这与已发表的实验一致。我们通过结合八个纤维类型和大小参数来研究大鼠49条前肢和后肢肌肉的模拟,以探索这些参数如何在不同的肌肉之间广泛变化,从而影响对废用性萎缩的敏感性。在模拟的49块肌肉中,比目鱼比目鱼肌表现出最大的萎缩程度(经过14天的模拟固定)(纤维大小减少了51%),而指趾伸肌的萎缩最少(32%)。对这些模拟的分析表明,即使没有单个组织结构参数与萎缩率相关,纤维类型的分布和纤维大小的分布也会影响停用萎缩的敏感性。另外,代表成纤维细胞的软件代理被合并到模型中以研究萎缩过程中的细胞相互作用。敏感性分析表明,成纤维细胞因子可能会影响废品引起的萎缩,尽管其作用远小于纤维类型和大小。尤其是,肌肉萎缩随着初始成纤维细胞数量的增加和TNF-α产量的增加而略有升高。总体而言,基于代理的模型为研究萎缩过程中骨骼肌的组织适应性和细胞相互作用提供了新颖的框架。

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