State variables with descriptions.

Radiation combined injury (RCI), resulting from ionizing radiation exposure accompanied by other injuries such as burn, laceration, or fracture, is associated with higher rates of mortality and severe effects. Current available models lack the ability to capture synergistic effects associated with RCI and/or rely on data-driven approaches that are limited in their predictive capabilities. To address this, we developed a mechanistic mathematical model for local radiation exposure combined with burn injury that captures the inflammatory response and early fibroblast activity associated with injury resolution. We utilized sensitivity analysis and parameter sampling methods to leverage limited data. The model was able to reproduce inflammatory and fibroblast behavior consistent with observed thermal injury and combined injury profiles. The formulation of a mechanistic model for combined injury adds increased modeling flexibility allowing for further exploration of the underlying inflammatory mechanisms and provides a framework for leveraging minimal data for improved predictive models of RCI.辐射复合伤（Radiation combined injury, RCI）指由电离辐射暴露合并烧伤、撕裂伤或骨折等其他损伤所引发的病症，其死亡率更高、危害更为严重。现有模型要么无法捕捉辐射复合伤相关的协同效应，要么依赖预测能力受限的数据驱动方法。为解决这一问题，本研究构建了针对局部辐射暴露合并烧伤的机制性数学模型，该模型能够捕捉损伤修复过程中的炎症反应与早期成纤维细胞活性。研究团队采用敏感性分析与参数采样方法，以充分利用有限的实验数据。该模型能够复现与已观测到的热损伤及复合伤特征相符的炎症反应与成纤维细胞行为。构建复合伤机制模型的思路提升了模型的灵活性，可为进一步探究潜在炎症机制提供支撑，同时也为利用少量数据优化辐射复合伤预测模型提供了一套框架。