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新型冠状病毒2019感染期间细胞因子风暴诱导的新冠病毒分子机制建模与模拟

Modeling and simulations of CoViD-19 molecular mechanism induced by cytokines storm during SARS-CoV2 infection.

作者信息

Yu Zhenhua, Ellahi R, Nutini Alessandro, Sohail Ayesha, Sait Sadiq M

机构信息

Institute of Systems Security and Control, College of Computer Science and Technology, Xi'an University of Science and Technology, Xi'an 710054, China.

Department of Mathematics, International Islamic University, Islamabad 44000, Pakistan.

出版信息

J Mol Liq. 2021 Apr 1;327:114863. doi: 10.1016/j.molliq.2020.114863. Epub 2020 Nov 28.

Abstract

It is highly desired to explore the interventions of COVID-19 for early treatment strategies. Such interventions are still under consideration. A model is benchmarked research and comprises target cells, virus infected cells, immune cells, pro-inflammatory cytokines, and, anti-inflammatory cytokine. The interaction of the drug with the inflammatory sub-system is analyzed with the aid of kinetic modeling. The impact of drug therapy on the immune cells is modelled and the computational framework is verified with the aid of numerical simulations. The work includes a significant hypothesis that quantifies the complex dynamics of the infection, by relating it to the effect of the inflammatory syndrome generated by IL-6. In this paper we use the cancer immunoediting process: a dynamic process initiated by cancer cells in response to immune surveillance of the immune system that it can be conceptualized by an alternating movement that balances immune protection with immune evasion. The mechanisms of resistance to immunotherapy seem to broadly overlap with those used by cancers as they undergo immunoediting to evade detection by the immune system. In this process the immune system can both constrain and promote tumour development, which proceeds through three phases termed: (i) Elimination, (ii) Equilibrium, and, (iii) Escape [1]. We can also apply these concepts to viral infection, which, although it is not exactly "immunoediting", has many points in common and helps to understand how it expands into an "untreated" host and can help in understanding the SARS-CoV2 virus infection and treatment model.

摘要

迫切需要探索针对 COVID-19 的早期治疗策略干预措施。此类干预措施仍在考虑之中。一个模型以研究为基准,包括靶细胞、病毒感染细胞、免疫细胞、促炎细胞因子和抗炎细胞因子。借助动力学模型分析药物与炎症子系统的相互作用。对药物治疗对免疫细胞的影响进行建模,并借助数值模拟验证计算框架。这项工作包含一个重要假设,即通过将感染的复杂动态与 IL-6 产生的炎症综合征的影响相关联来对其进行量化。在本文中,我们使用癌症免疫编辑过程:这是一个由癌细胞响应免疫系统的免疫监视而启动的动态过程,可以通过在免疫保护和免疫逃逸之间取得平衡的交替运动来概念化。免疫疗法的耐药机制似乎与癌症在进行免疫编辑以逃避免疫系统检测时所使用的机制广泛重叠。在这个过程中,免疫系统既可以抑制也可以促进肿瘤发展,肿瘤发展经历三个阶段,即:(i) 消除,(ii) 平衡,以及 (iii) 逃逸 [1]。我们也可以将这些概念应用于病毒感染,虽然它不完全是“免疫编辑”,但有许多共同点,有助于理解它如何在“未治疗”的宿主中扩散,并有助于理解 SARS-CoV2 病毒感染和治疗模型。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a136/7698669/76e07203e00b/ga1_lrg.jpg

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