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白细胞介素-17 作为急性到慢性炎症的时空桥梁:计算建模的新见解。

Interleukin-17 as a spatiotemporal bridge from acute to chronic inflammation: Novel insights from computational modeling.

机构信息

Physician Scientist Training Program, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA.

Department of Surgery, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.

出版信息

WIREs Mech Dis. 2023 May-Jun;15(3):e1599. doi: 10.1002/wsbm.1599. Epub 2023 Jan 29.

Abstract

A systematic review of several acute inflammatory diseases ranging from sepsis and trauma/hemorrhagic shock to the relevant pathology of the decade, COVID-19, points to the cytokine interleukin (IL)-17A as being centrally involved in the propagation of inflammation. We summarize the role of IL-17A in acute inflammation, leveraging insights made possible by biological network analysis and novel computational methodologies aimed at defining the spatiotemporal spread of inflammation in both experimental animal models and humans. These studies implicate IL-17A in the cross-tissue spread of inflammation, a process that appears to be in part regulated through neural mechanisms. Although acute inflammatory diseases are currently considered distinct from chronic inflammatory pathologies, we suggest that chronic inflammation may represent repeated, cyclical episodes of acute inflammation driven by mechanisms involving IL-17A. Thus, insights from computational modeling of acute inflammatory diseases may improve diagnosis and treatment of chronic inflammation; in turn, therapeutics developed for chronic/autoimmune disease may be of benefit in acute inflammation. This article is categorized under: Immune System Diseases > Computational Models.

摘要

对几种急性炎症性疾病(从败血症和创伤/失血性休克到 COVID-19 的相关病理学)进行的系统评价指出,细胞因子白细胞介素 (IL)-17A 是炎症传播的核心介质。我们总结了 IL-17A 在急性炎症中的作用,利用生物网络分析和新型计算方法学的见解,这些方法学旨在定义实验动物模型和人类中炎症的时空传播。这些研究表明,IL-17A 参与了炎症的跨组织传播,这一过程似乎部分受到神经机制的调节。尽管急性炎症性疾病目前被认为与慢性炎症性疾病不同,但我们认为慢性炎症可能代表由涉及 IL-17A 的机制驱动的反复、周期性急性炎症发作。因此,对急性炎症性疾病的计算模型的深入研究可能会改善慢性炎症的诊断和治疗;反过来,为慢性/自身免疫性疾病开发的治疗方法可能对急性炎症有益。本文属于以下分类:免疫系统疾病 > 计算模型。

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