Multiscale modeling to map cardiac electrophysiology between species

项目总结 U01应用程序的总体目标是开发用于心脏多尺度建模的新方法 电生理学和心律失常研究。为了实现这一目标，我们将使用创新的组合 在多个空间尺度和跨多个概念尺度的实验和计算研究。 因为心肌细胞是涉及数十个相互作用的分子实体的复杂系统，数学上 长期以来，建模一直是揭示心律失常机制的有价值的技术。然而，已经建立了 将建模和实验相结合的方法有重要的局限性，包括：(1)大多数研究测试 只有有限数量的模型预测；(2)模型通常预测所考虑的样本的反应 代表一个群体，从而忽略个体之间的差异；以及(3)组织水平 模拟可能包含不同区域之间的生理差异，但没有考虑到以下事实 组织中的每个细胞都是不同的。 我们将使用创新和协同的计算和实验来解决这些限制 由绩效指标制定的方法。这些方法允许严格的参数估计，系统和 定量预测，并在每个实验样本中测试多个扰动，以及定量 不同单元格类型之间的映射。为了达到我们的总体目标，我们建议： 1.通过严格的实验测试和数学发展来改进心脏细胞模型 特定于每个研究细胞的模型。 2.对异质细胞群体的模型进行了校准，并对有关离子的预测进行了实验验证。 跨种群的当前变异和协变 3.根据一个物种的记录，建立模型，以预测某一物种受到干扰的影响 不同的物种 4.预测单个细胞之间的变异性如何影响组织层面的心律失常风险。 这项研究可能会展示改进的、广泛适用的方法，以严格和系统地 多空间尺度下实验与模拟的耦合。通过这样做，联合研究 将对细胞和组织水平上的可变性的后果提供重要的洞察。

PROJECT SUMMARY The overall goal of this U01 application is to develop novel approaches for multiscale modeling in cardiac electrophysiology and arrhythmia research. To accomplish this goal, we will use innovative combinations of experimental and computational studies at multiple spatial scales and across multiple conceptual scales. Because cardiac cells are complex systems involving dozens of interacting molecular entities, mathematical modeling has long been a valuable technique for uncovering arrhythmia mechanisms. However, established methods for combining modeling with experiments have important limitations, including: (1) most studies test only a limited number of model predictions; (2) models usually predict the response of a sample considered representative of a population, thereby ignoring differences between individuals; and (3) tissue-level simulations may incorporate physiological differences between regions but do not account for the fact that each cell in the tissue is different. We will address these limitations using innovative and synergistic computational and experimental methodologies developed by the PIs. These methods allow for rigorous parameter estimation, systematic and quantitative predictions, and testing multiple perturbations in each experimental sample, and quantitative mappings between different cell types. To achieve our overall goals, we propose to: 1. improve heart cell models through rigorous experimental testing and the development of mathematical models specific to each cell studied. 2. calibrate models of heterogeneous cell populations and experimentally test predictions regarding ionic current variation and co-variation across populations 3. develop models to predict the effects of perturbations in one species based on recordings made in a different species 4. predict how variability between individual cells influences arrhythmia risk at the tissue level. The research is likely to demonstrate improved, broadly applicable methods for rigorous and systematic coupling between experiments and simulations at multiple spatial scales. By so doing, the combined studies will provide important insight into the consequences of variability at both the cellular and tissue levels.