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基于Agent 的肺部颗粒暴露后炎症和纤维化模型。

An agent-based model of inflammation and fibrosis following particulate exposure in the lung.

机构信息

Center for Inflammation and Regenerative Modeling, McGowan Institute for Regenerative Medicine, University of Pittsburgh, Pittsburgh, PA 15219, USA.

出版信息

Math Biosci. 2011 Jun;231(2):186-96. doi: 10.1016/j.mbs.2011.03.005. Epub 2011 Mar 6.

Abstract

Inflammation and airway remodeling occur in a variety of airway diseases. Modeling aspects of the inflammatory and fibrotic processes following repeated exposure to particulate matter may provide insights into a spectrum of airway diseases, as well as prevention/treatment strategies. An agent-based model (ABM) was created to examine the response of an abstracted population of inflammatory cells (nominally macrophages, but possibly including other inflammatory cells such as lymphocytes) and cells involved in remodeling (nominally fibroblasts) to particulate exposure. The model focused on a limited number of relevant interactions, specifically those among macrophages, fibroblasts, a pro-inflammatory cytokine (TNF-α), an anti-inflammatory cytokine (TGF-β1), collagen deposition, and tissue damage. The model yielded three distinct states that were equated with (1) self-resolving inflammation and a return to baseline, (2) a pro-inflammatory process of localized tissue damage and fibrosis, and (3) elevated pro- and anti-inflammatory cytokines, persistent tissue damage, and fibrosis outcomes. Experimental results consistent with these predicted states were observed in histology sections of lung tissue from mice exposed to particulate matter. Systematic in silico studies suggested that the development of each state depended primarily upon the degree and duration of exposure. Thus, a relatively simple ABM resulted in several, biologically feasible, emergent states, suggesting that the model captures certain salient features of inflammation following exposure of the lung to particulate matter. This ABM may hold future utility in the setting of airway disease resulting from inflammation and fibrosis following particulate exposure.

摘要

在各种气道疾病中都会发生炎症和气道重塑。对反复暴露于颗粒物后炎症和纤维化过程的建模可以深入了解一系列气道疾病以及预防/治疗策略。创建了一个基于代理的模型 (ABM) 来研究炎症细胞(名义上是巨噬细胞,但可能包括其他炎症细胞,如淋巴细胞)和参与重塑的细胞(名义上是成纤维细胞)对颗粒物暴露的反应。该模型侧重于少数相关的相互作用,特别是巨噬细胞、成纤维细胞、促炎细胞因子 (TNF-α)、抗炎细胞因子 (TGF-β1)、胶原蛋白沉积和组织损伤之间的相互作用。该模型产生了三种不同的状态,分别与 (1) 自我缓解的炎症和恢复到基线、(2) 局部组织损伤和纤维化的促炎过程以及 (3) 升高的促炎和抗炎细胞因子、持续的组织损伤和纤维化结果相对应。在暴露于颗粒物的小鼠肺组织的组织学切片中观察到与这些预测状态一致的实验结果。系统的计算机模拟研究表明,每种状态的发展主要取决于暴露的程度和持续时间。因此,一个相对简单的 ABM 产生了几种具有生物学可行性的突发状态,这表明该模型捕获了肺部暴露于颗粒物后炎症的某些显著特征。这种 ABM 可能在炎症和纤维化导致气道疾病的情况下具有未来的应用价值。

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5
TH17 cells in asthma and COPD.哮喘和 COPD 中的 TH17 细胞。
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6
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Allergy. 2010 May;65(5):537-53. doi: 10.1111/j.1398-9995.2009.02305.x. Epub 2010 Feb 1.
7
Differences of inflammatory mechanisms in asthma and COPD.哮喘和 COPD 中炎症机制的差异。
Allergol Int. 2009 Sep;58(3):307-13. doi: 10.2332/allergolint.09-RAI-0106. Epub 2009 Jul 25.
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Mechanistic simulations of inflammation: current state and future prospects.炎症的机制模拟:现状与未来展望
Math Biosci. 2009 Jan;217(1):1-10. doi: 10.1016/j.mbs.2008.07.013. Epub 2008 Aug 26.

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