Ensemble Density Analysis for Stochastic Models of Cardiac Excitation-Contraction Coupling

心脏兴奋-收缩耦合随机模型的集合密度分析

• 批准号: 0443843
• 负责人: Mohsin Jafri
• 金额: $ 200万
• 依托单位: George Mason University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-03-15 至 2011-02-28
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0443843&HistoricalAwards=false
• 关键词: Ensemble; Density; Analysis; Stochastic; Models

Many cellular processes are governed by discrete molecular events that are intrinsically stochastic, e.g., single channel gating, the binding and unbinding of ligand and receptor, and the collective activity of intracellular calcium channels giving rise to "calcium sparks." These subcellular phenomena are typically modeled using Monte Carlo simulation methods. The proposed work begins with the observation that realistic models of cardiac myocytes are required to strategically investigate the generation of cardiac arrhythmias and to develop medical device or drug interventions that can prevent this pathophysiology. Unfortunately, widely used deterministic cardiac myocyte models do not reproduce certain cellular phenomenon in which discrete molecular events and local signaling within subcellular compartments play an essential role. An important example is pathological excitation-contraction (EC) coupling during heart failure that is due in part to aberrant local signaling between small numbers of voltage-gated calcium channels and ryanodine receptors co-localized at the same dyadic cleft, so-called "stochastic functional units" (SFUs). Another example is the phenomenon of "graded release" where the amount of calcium released by internal stores is a gradually increasing function of calcium entry through voltage-gated calcium channels. In these cases deterministic models provide only limited mechanistic insight and stochastic cellular models only include a compact representation of subcellular events that are required to assist experimental design and interpretation. Moreover, Monte Carlo simulations of SFUs are computationally expensive and difficult to apply at the cellular scale. To address those issues, the development of an "ensemble density" approach is proposed where coupled Fokker-Planck-like equations are used to accurately represent SFU activity and the resulting independent probability density of subsarcolemmal calcium concentrations in mathematical models of normal and pathophysiological EC coupling in cardiac myocytes. The ensemble density method will be validated using traditional Monte Carlo techniques and the computational advantage of the method explored. A hierarchy of models will be developed and tested in the context of a joint experimental/theoretical investigation of the stochastic aspects of normal and pathological EC coupling in cardiac myocytes.To summarize, many cellular processes are involved in single events that occur with a certain probability. These seemingly random events combined determine cellular function. The proposed research will develop methods and representations for the cardiac muscle cell incorporating discrete random events in efficient cellular models. The modeling efforts will be guided and confirmed by experimental work. The development of computationally efficient whole cell models of cardiac myocytes is a step toward realistic tissue and organ level models of the heart.

许多细胞过程由本质上随机的离散分子事件控制，例如，单通道门控、配体和受体的结合和非结合以及引起“钙火花”的细胞内钙通道的集体活性。“这些亚细胞现象通常使用蒙特卡罗模拟方法建模。 拟议的工作开始于观察到需要心肌细胞的现实模型来战略性地研究心律失常的产生，并开发可以预防这种病理生理学的医疗设备或药物干预。 不幸的是，广泛使用的确定性心肌细胞模型不能再现某些细胞现象，其中亚细胞区室内的离散分子事件和局部信号传导起着至关重要的作用。 一个重要的例子是心力衰竭期间的病理性兴奋-收缩（EC）偶联，其部分原因是由于少量电压门控钙通道和兰尼碱受体之间的异常局部信号传导，所述少数电压门控钙通道和兰尼碱受体共定位于相同的二元裂隙，即所谓的“随机功能单位”（SFU）。 另一个例子是“分级释放”现象，其中由内部储存释放的钙的量是通过电压门控钙通道进入的钙的逐渐增加的函数。 在这些情况下，确定性模型只提供有限的机制洞察力和随机细胞模型只包括一个紧凑的表示亚细胞事件，需要协助实验设计和解释。 此外，SFU的Monte Carlo模拟在计算上是昂贵的，并且难以在细胞尺度上应用。 为了解决这些问题，提出了一个“合奏密度”的方法，耦合福克-普朗克方程被用来准确地表示SFU活动和由此产生的独立概率密度的肌膜下钙浓度的数学模型中的正常和病理生理EC耦合在心肌细胞的发展。 系综密度方法将使用传统的蒙特卡罗技术进行验证，并探讨该方法的计算优势。 一个层次的模型将被开发和测试的背景下，联合实验/理论研究的随机方面的正常和病理EC耦合在cardiac myocytes.To总结，许多细胞过程中涉及的单个事件发生一定的概率。 这些看似随机的事件结合在一起决定了细胞的功能。 拟议的研究将开发心肌细胞的方法和表示，将离散随机事件纳入有效的细胞模型。 建模工作将由实验工作指导和确认。 心肌细胞的计算效率的全细胞模型的发展是迈向真实的心脏组织和器官水平模型的一步。