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成纤维细胞力学转导网络预测机械适应性梗死治疗的靶点。

Fibroblast mechanotransduction network predicts targets for mechano-adaptive infarct therapies.

机构信息

Department of Bioengineering; Clemson University, Clemson, United States.

出版信息

Elife. 2022 Feb 9;11:e62856. doi: 10.7554/eLife.62856.

Abstract

Regional control of fibrosis after myocardial infarction is critical for maintaining structural integrity in the infarct while preventing collagen accumulation in non-infarcted areas. Cardiac fibroblasts modulate matrix turnover in response to biochemical and biomechanical cues, but the complex interactions between signaling pathways confound efforts to develop therapies for regional scar formation. We employed a logic-based ordinary differential equation model of fibroblast mechano-chemo signal transduction to predict matrix protein expression in response to canonical biochemical stimuli and mechanical tension. Functional analysis of mechano-chemo interactions showed extensive pathway crosstalk with tension amplifying, dampening, or reversing responses to biochemical stimuli. Comprehensive drug target screens identified 13 mechano-adaptive therapies that promote matrix accumulation in regions where it is needed and reduce matrix levels in regions where it is not needed. Our predictions suggest that mechano-chemo interactions likely mediate cell behavior across many tissues and demonstrate the utility of multi-pathway signaling networks in discovering therapies for context-specific disease states.

摘要

心肌梗死后的区域性纤维化控制对于维持梗死区的结构完整性,同时防止非梗死区胶原积累至关重要。心肌成纤维细胞响应生化和生物力学线索调节基质周转,但信号通路之间的复杂相互作用使开发针对区域性瘢痕形成的治疗方法变得复杂。我们采用基于逻辑的成纤维细胞机械化学信号转导的常微分方程模型,预测基质蛋白表达对经典生化刺激和机械张力的反应。机械化学相互作用的功能分析显示,与张力放大、阻尼或逆转生化刺激反应的途径广泛相互作用。全面的药物靶点筛选确定了 13 种机械适应性治疗方法,这些方法可促进需要的区域中的基质积累,并降低不需要的区域中的基质水平。我们的预测表明,机械化学相互作用可能介导许多组织中的细胞行为,并证明多途径信号网络在发现针对特定疾病状态的治疗方法方面的实用性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/11ce/8849334/75b244e932dc/elife-62856-fig1.jpg

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