Ozturk Mustafa Cagdas, Xu Qian, Cinar Ali
Department of Chemical and Biological Engineering, Illinois Institute of Technology, Chicago, IL, United States of America.
Department of Biomedical Engineering, Illinois Institute of Technology, Chicago, IL, United States of America.
PLoS One. 2018 Jan 10;13(1):e0190349. doi: 10.1371/journal.pone.0190349. eCollection 2018.
We propose an agent-based model for the simulation of the autoimmune response in T1D. The model incorporates cell behavior from various rules derived from the current literature and is implemented on a high-performance computing system, which enables the simulation of a significant portion of the islets in the mouse pancreas. Simulation results indicate that the model is able to capture the trends that emerge during the progression of the autoimmunity. The multi-scale nature of the model enables definition of rules or equations that govern cellular or sub-cellular level phenomena and observation of the outcomes at the tissue scale. It is expected that such a model would facilitate in vivo clinical studies through rapid testing of hypotheses and planning of future experiments by providing insight into disease progression at different scales, some of which may not be obtained easily in clinical studies. Furthermore, the modular structure of the model simplifies tasks such as the addition of new cell types, and the definition or modification of different behaviors of the environment and the cells with ease.
我们提出了一种基于代理的模型，用于模拟1型糖尿病中的自身免疫反应。该模型整合了从当前文献中得出的各种规则所描述的细胞行为，并在高性能计算系统上实现，这使得能够模拟小鼠胰腺中相当一部分胰岛。模拟结果表明，该模型能够捕捉自身免疫进展过程中出现的趋势。模型的多尺度性质允许定义支配细胞或亚细胞水平现象的规则或方程，并在组织尺度上观察结果。预计这样的模型将通过快速检验假设和规划未来实验，为不同尺度的疾病进展提供见解，从而促进体内临床研究，其中一些见解可能在临床研究中不容易获得。此外，模型的模块化结构简化了诸如轻松添加新细胞类型以及定义或修改环境和细胞的不同行为等任务。
