权益分类	功能权益	普通用户	{{item.name}}会员
{{category.name}}	{{benefitItem.name}}

Multiscale modeling to map cardiac electrophysiology between species

多尺度建模绘制物种间心脏电生理图

基本信息

批准号：
9282978
负责人：
DAVID J. CHRISTINI
金额：
$ 65.42万
依托单位：
ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI
依托单位国家：
美国
项目类别：
财政年份：
2017
资助国家：
美国
起止时间：
2017-04-15 至 2022-01-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9282978
关键词：
Action Potentials Address Arrhythmia Behavior Calcium Calibration Cardiac Cardiac Electrophysiologic Techniques Cardiac Myocytes Cardiac development Cell model Cells Closure by clamp Complement Complex Computer Simulation Computing Methodologies Coupling Development Dimensions Event Exhibits Goals Heart Heterogeneity Human Individual Ion Channel Laboratories Link Maps Membrane Potentials Methodology Methods Modeling Molecular Muscle Cells Oryctolagus cuniculus Participant Pharmaceutical Preparations Physiological Population Population Heterogeneity Prediction of Response to Therapy Process Proteins Protocols documentation Pump Research Risk Sampling System Techniques Testing Tissue Model Tissues United States Variant Ventricular Ventricular Arrhythmia Work base cell type cellular development computer studies experimental study heart cell improved induced pluripotent stem cell innovation insight killings mathematical model method development model development mortality multi-scale modeling novel novel strategies predicting response predictive modeling prevent response simulation sudden cardiac death synergism virtual

项目摘要

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.

项目总结