Stochastic Simulation Of Excitation-contraction Coupling

我们已经开始将更多的注意力投入到所谓的自发钙释放事件中，这些事件在形态上从单个火花到局部小波再到全局钙波。 这些事件已被证明在控制起搏细胞的频率以及在病理条件下触发心律失常中起关键的“时钟”作用。 为了模拟这一过程，我们正在构建一个基于簇的三维随机反应扩散模型，描述嵌入在有限元网络中的钙释放通道簇的动力学，在该网络中钙可以扩散并进行缓冲反应。 专门的beyowulf集群（48个处理器）的硬件刚刚交付，正在安装。 与此同时，我们已成功将之前的蒙特卡罗兴奋-收缩模拟代码移植到NIH Biowulf计算集群，并在多达160个处理器上并行化。 这使得有可能探索局部控制模型的参数依赖性，这导致了新的见解增益调节的机制。 并行模型将形成广泛的软件开发所需的基础，包括钙释放的三维传播。 即使有了新的硬件，在易于处理的时间内进行这种计算也需要特殊的编程方法。 我们已经开发了一种专门的方法，用于集成reacdtion扩散方程，利用生物物理方程的结构，运行速度比传统的偏微分方程包快100倍。 我们最近发明了一种分层积分方案，其中微分方程求解器递归地调用自己，以便在更接近钙源的区域中使用较小的时间步长，同时在构成胞质溶胶的大部分体积的开放空间中采取大的步骤。 目前正在为这两个集群编写Fortran语言的这些方法。 与此同时，我们正在收集有关心肌细胞钙释放事件统计特性的大量实验数据，以便与3D随机模拟模型的输出进行比较。

SUMMARY OF WORK We have begun devoting more attention to so-called spontaneous calcium release events, which vary morphologically from single sparks to localized wavelets to global calcium waves. These events have been shown to play a critical "clock" role in controlling rate in pacemaker cells, as well as triggering arhythmias under pathological condition. In order to model this process, we are constructing a cluster-based thre dimensional stochastic reaction diffusion model describing the dynamics of calcium release channel clusters embedded in a finite-element network in which calcium can diffuse and undergo buffering reactions. Hardware for a dedicated beyowulf cluster (48 processors) has just been delivered and is being installed. Simultaneously, we have successfully ported our previous Monte Carlo excitation-contraction simulation code to the NIH Biowulf computing cluster, parallelized on up to 160 processors. This makes it possible to explore the parameter dependence of the local control model, which is leading to new insights about the mechanism of gain regulation. The parallelized model will form the basis for the extensive software development required to include the three dimensional propagation of calcium release. Even with the new hardware, doing this computation in tractable time will require special progamming methods. We have developed a specialized method for integrating reacdtion diffusion equations that takes advantage of the structure of the biophysical equations to run 100 times faster than a conventional partial-differential equation package. We have recently invented a hierarchical integration scheme in which the differential equation solver calls itself recursively in order to use smaller time steps in regions closer to the calcium sources while taking large steps in the open spaces that constitute most of the volume of the cytosol. These methods are now being coded in Fortran for the two clusters. At the same time, we are collecting extensive experimental data on the statistical properties of calcium release events in cardiac myocytes, for comparison with the output of the 3D stochastic simulation model when the latter is ready to run.