02831nas a2200349 4500000000100000000000100001008004100002260001500043653001100058653002800069653002100097653001800118653001900136100002300155700002200178700002100200700001500221700001600236700002500252700002700277700002000304700002800324700001600352700002200368700002200390700002700412245009800439856009300537490000700630520183000637022001402467 2024 d c2024-01-2910aBurns110aComputational Modeling510aImmune Response410ainflammation310awound healing21 aH. Ibrahim Korkmaz1 aVivek M. Sheraton1 aRoland V. Bumbuc1 aMeifang Li1 aAnouk Pijpe1 aPatrick P. G. Mulder1 aBouke K. H. L. Boekema1 aEvelien de Jong1 aStephan G. F. Papendorp1 aRuud Brands1 aEsther Middelkoop1 aPeter M. A. Sloot1 aPaul P. M. van Zuijlen00aAn in silico modeling approach to understanding the dynamics of the post-burn immune response uhttps://www.frontiersin.org/journals/immunology/articles/10.3389/fimmu.2024.1303776/full0 v153 aIntroduction

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.

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