THREE-DIMENSIONAL RECONSTRUCTION OF CARDIAC CELLS

这个子项目是许多研究子项目中利用 资源由NIH/NCRR资助的中心拨款提供。子项目和 调查员(PI)可能从NIH的另一个来源获得了主要资金， 并因此可以在其他清晰的条目中表示。列出的机构是 该中心不一定是调查人员的机构。 心脏模型已经进行了超过45年，从牛津大学名誉教授Denis Noble，CBE(Noble，1960)建立的第一个基于实验的心肌细胞电生理模型开始。20世纪90年代初，随着改进的实验技术的出现，包括记录膜电流、单通道门控特性和细胞内离子浓度，细胞模型变得更加复杂，并且越来越具有预测性。然而，仅有细胞活动的知识还不足以研究心脏等复杂器官内复杂的导电模式。20世纪90年代初，随着民用超级计算机的出现，开发和使用心脏组织模型成为可能。这些模型说明了结构细节对于功能预测的巨大重要性，并极大地帮助我们形成了对细胞兴奋、复极化和收缩潜在过程的理解，并日益成为实验研究的组成部分，有助于假说的形成、分析和预测(Kohl等人，2000年)。在此背景下，数学模型已开始对改进实验工作、降低干预措施的严重性以及部分取代“湿”生物学研究作出重大贡献(Garny&Kohl，2004)。这些模型进一步强调了考虑心脏功能在空间和时间上的多尺度性质的必要性。相关的空间尺度从纳米(亚细胞)到微观(细胞)和宏观(器官)。上述发展得益于“微观到宏观”领域日益准确的数据，然而，“纳米到微观”的水平迄今在很大程度上被忽视了。然而，为了了解亚细胞机制，必须解决心脏细胞的区隔，这是从信号到离子处理和收缩的综合行为的基础。为此，挑战是获得单个心肌细胞的细胞解剖结构的准确表示。对于尺寸在小体积内变化很大的结构来说，ET是理想的。它允许计算机生成比物理切割薄得多的“虚拟切片”。因此，ET非常适合于具有复杂3D几何结构的结构，如细胞骨架阵列或T管、肌浆网和微管的卷曲膜系统。有了这种方法，就有可能开始重建单个的心肌细胞，对它们的结构进行建模，以模拟心肌细胞的活动，而不仅仅是将细胞视为电活动的“点源”，或机械机械的统一“积木”。 参考资料： 加尼·A和科尔·P：工程与计算交界处的心脏研究。《化学工程师》，2004年9月31-32期。 科尔·P，诺布尔·D，温斯洛·RL和亨特·PJ。生物系统的计算模型：工具与愿景。PhilTrans R Soc A 358：579-610(2000)。 基于Hodgkin-Huxley方程的心脏动作和起搏器电位。《自然》188：495-497(1960)。

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. Cardiac modelling has been conducted for over 45 years, starting with the first experimentally based electrophysiological model of a cardiac myocyte by Oxford Emeritus Prof. Denis Noble, CBE (Noble, 1960). With the availability, in the early 1990s, of improved experimental techniques, including the recording of membrane currents, single-channel gating properties and intracellular ion concentrations, cellular models have grown in complexity and are increasingly predictive. Knowledge of cell activity is not sufficient, however, to study complex patterns of electrical conduction within a complex organ such as the heart. With the advent, in the early 1990s, of civil-use supercomputers, it became possible to develop and use cardiac tissue models. These models have illustrated the tremendous importance of structural detail for functional prediction and have greatly helped in shaping our understanding of processes underlying cellular excitation, repolarisation, and contraction, and are increasingly becoming an integrated part of experimental research, helping in hypothesis formation, analysis, and prediction (Kohl et al., 2000). In this context, mathematical models have begun to make significant contributions to the refinement of experimental work, reduction in severity of interventions, and partial replacement of 'wet' biological research (Garny & Kohl, 2004). These models have further highlighted the need to account for the multi-scale nature  both in space and time  of cardiac function. Relevant spatial scales range from nano (sub-cellular) to micro (cellular) and macro (organ) levels. The above development has benefited from increasingly accurate data in the 'micro-to-macro' domain However, the 'nano-to-micro' level has thus far largely been neglected. Yet in order to understand sub-cellular mechanisms it is imperative to address compartmentalisation of cardiac cells which underlies integrated behaviour, from signalling to ion handling and contraction. To this end, the challenge is to acquire an accurate representation of the cyto-anatomical structure of individual cardiac myocytes. ET is ideal for structures whose dimensions vary significantly within a small volume. It allows for computer-generation of 'virtual slices' that are much thinner than could be cut physically. ET is ideal, therefore, for structures with a complex 3D geometry, such as cytoskeletal arrays or convoluted membrane systems of the T-tubules, sarcoplasmic reticulum and micro-tubules in ventricular myocytes. With this approach, it is possible to begin reconstruction of individual cardiac cells, to model their structure for the simulation of cardiomyocyte activity in a way that goes beyond treating cells as a 'point source' of electrical activity, or a uniform 'building block' of the mechanical machinery. References: Garny A & Kohl P. Cardiac Research at the Interface of Engineering and Computing. The Chemical Engineer September: 31-32 (2004). Kohl P, Noble D, Winslow RL & Hunter PJ. Computational Modelling of Biological Systems: Tools and Visions. PhilTrans R Soc A 358: 579-610 (2000). Noble D. Cardiac Action and Pacemaker Potentials Based on the Hodgkin-Huxley Equations. Nature 188: 495-497 (1960).