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一种理解烧伤后免疫反应动态的计算建模方法。

An in silico modeling approach to understanding the dynamics of the post-burn immune response.

机构信息

Department of Plastic, Reconstructive and Hand Surgery, Amsterdam Movement Sciences (AMS) Institute, Amsterdam University Medical Center (UMC), Location VUmc, Amsterdam, Netherlands.

Department of Molecular Cell Biology and Immunology, Amsterdam Infection and Immunity (AII) Institute, Amsterdam University Medical Center (UMC), Location VUmc, Amsterdam, Netherlands.

出版信息

Front Immunol. 2024 Jan 29;15:1303776. doi: 10.3389/fimmu.2024.1303776. eCollection 2024.


DOI:10.3389/fimmu.2024.1303776
PMID:38348032
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10859697/
Abstract

INTRODUCTION: Burns are characterized by a massive and prolonged acute inflammation, which persists for up to months after the initial trauma. Due to the complexity of the inflammatory process, Predicting the dynamics of wound healing process can be challenging for burn injuries. The aim of this study was to develop simulation models for the post-burn immune response based on (pre)clinical data. METHODS: The simulation domain was separated into blood and tissue compartments. Each of these compartments contained solutes and cell agents. Solutes comprise pro-inflammatory cytokines, anti-inflammatory cytokines and inflammation triggering factors. The solutes diffuse around the domain based on their concentration profiles. The cells include mast cells, neutrophils, and macrophages, and were modeled as independent agents. The cells are motile and exhibit chemotaxis based on concentrations gradients of the solutes. In addition, the cells secrete various solutes that in turn alter the dynamics and responses of the burn wound system. RESULTS: We developed an Glazier-Graner-Hogeweg method-based model (GGH) to capture the complexities associated with the dynamics of inflammation after burn injuries, including changes in cell counts and cytokine levels. Through simulations from day 0 - 4 post-burn, we successfully identified key factors influencing the acute inflammatory response, i.e., the initial number of endothelial cells, the chemotaxis threshold, and the level of chemoattractants. CONCLUSION: Our findings highlight the pivotal role of the initial endothelial cell count as a key parameter for intensity of inflammation and progression of acute inflammation, 0 - 4 days post-burn.

摘要

简介:烧伤的特点是剧烈且持久的急性炎症,这种炎症在初始创伤后可持续长达数月。由于炎症过程的复杂性,预测烧伤伤口愈合过程的动态可能具有挑战性。本研究旨在基于(临床前)数据为烧伤后的免疫反应开发模拟模型。

方法:模拟域分为血液和组织隔室。这些隔室中的每一个都包含溶质和细胞剂。溶质包括促炎细胞因子、抗炎细胞因子和炎症触发因子。溶质根据其浓度分布在整个区域内扩散。细胞包括肥大细胞、中性粒细胞和巨噬细胞,并且被建模为独立的剂。细胞是运动的,并根据溶质的浓度梯度表现出趋化性。此外,细胞分泌各种溶质,这些溶质反过来又改变烧伤伤口系统的动态和反应。

结果:我们开发了一种基于 Glazier-Graner-Hogeweg 方法的模型(GGH),以捕获与烧伤后炎症动态相关的复杂性,包括细胞计数和细胞因子水平的变化。通过对烧伤后 0-4 天的模拟,我们成功确定了影响急性炎症反应的关键因素,即内皮细胞的初始数量、趋化阈值和趋化因子水平。

结论:我们的研究结果强调了初始内皮细胞计数作为炎症强度和急性炎症进展的关键参数的重要作用,这发生在烧伤后 0-4 天。

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[1]
An agent-based modeling approach for lung fibrosis in response to COVID-19.

PLoS Comput Biol. 2023-12

[2]
The Complexity of the Post-Burn Immune Response: An Overview of the Associated Local and Systemic Complications.

Cells. 2023-1-17

[3]
Burn-injured skin is marked by a prolonged local acute inflammatory response of innate immune cells and pro-inflammatory cytokines.

Front Immunol. 2022

[4]
What good is maths in studies of wound healing?

iScience. 2022-7-19

[5]
Burn-Induced Local and Systemic Immune Response: Systematic Review and Meta-Analysis of Animal Studies.

J Invest Dermatol. 2022-11

[6]
The Future of Burn Care From a Complexity Science Perspective.

J Burn Care Res. 2022-11-2

[7]
Scar formation from the perspective of complexity science: a new look at the biological system as a whole.

J Wound Care. 2022-2-2

[8]
Universal activation function for machine learning.

Sci Rep. 2021-9-21

[9]
A systematic review of machine learning and automation in burn wound evaluation: A promising but developing frontier.

Burns. 2021-12

[10]
Severe Altered Immune Status After Burn Injury Is Associated With Bacterial Infection and Septic Shock.

Front Immunol. 2021-3-2

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