Dendritic cells (DCs) are the most potent and specialized antigen-presenting cells (APCs) currently known, which play a crucial role in initiating and amplifying both the innate and adaptive immune responses. During the process of immune function, migration ability of DCs and the number of effector T cells which activated by DCs are closely related to the efficiency of immune function. However, because of the complexity of immune system, in the immune response process caused by the skin chronic inflammatory, much is still unknown about the dynamic changes of cell count with time. Therefore, we created a differential equations model to reflect the initial stages of the immune response process caused by the skin chronic inflammatory via setting the function and initial conditions of parameters. The results showed that the model was able to simulate migration and proliferation of cells in vivo within realistic time scales in accordance with the proliferation and migration efficiency in real terms. In addition, the preliminary model can biologically predict the realistic dynamics of DCs and T cells at different time points. All these results may provide a theoretical reference for studying the immune function of DCs as well as guiding the clinical treatment for immune related diseases further.
树突状细胞（DCs）是目前已知的功能最为强大的专职抗原提呈细胞（APCs），在启动和放大固有免疫以及适应性免疫应答中起到重要的作用。在其发挥免疫功能的过程中，DCs 的迁移能力以及 DCs 活化初始 T 细胞的能力与其发挥免疫功能的效率有着密切关系。然而，由于免疫系统的复杂性，对于皮肤炎症引起 DCs 免疫应答的过程中细胞数量的动态变化依然知之甚少。因此，本研究利用数学模型对该过程进行数值模拟以及动态预测。通过设置函数和参数初始条件并构建常微分方程，模拟炎症引起免疫应答的初始阶段。结果显示，该方程能够较好地模拟 DCs 的迁移以及诱导初始 T 细胞特异性增殖的免疫应答过程，符合实际情况下免疫应答的持续时间、DCs 和 T 细胞的增殖率和迁移率等生理学特性，并且能够对不同时间点 DCs 与 T 细胞的数量进行预测，可为研究 DCs 的免疫学功能提供理论参考，进一步为临床治疗免疫相关疾病提供实践指导。.
Keywords: dendritic cells; mathematical model; ordinary differential equations; skin inflammation.