THREE-DIMENSIONAL RECONSTRUCTION OF CARDIAC CELLS

这个子项目是许多研究子项目中的一个 由NIH/NCRR资助的中心赠款提供的资源。子项目和 研究者（PI）可能从另一个NIH来源获得了主要资金， 因此可以在其他CRISP条目中表示。所列机构为 研究中心，而研究中心不一定是研究者所在的机构。 心脏建模已经进行了超过45年，从牛津大学名誉教授Denis Noble，CBE（Noble，1960）的第一个基于实验的心肌细胞电生理模型开始。随着20世纪90年代早期实验技术的改进，包括膜电流、单通道门控特性和细胞内离子浓度的记录，细胞模型变得越来越复杂，预测性也越来越强。然而，对细胞活动的了解还不足以研究心脏等复杂器官内复杂的电传导模式。随着20世纪90年代初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。这些模型已经说明了结构细节对于功能预测的巨大重要性，并且极大地帮助形成了我们对细胞兴奋、复极化和收缩的基础过程的理解，并且日益成为实验研究的组成部分，有助于假设形成、分析和预测（Kohl等人，2000年）。在这种情况下，数学模型已经开始对实验工作的改进，干预措施的严重性的降低以及“湿”生物研究的部分替代做出重大贡献（Garny & Kohl，2004）。这些模型进一步突出了考虑多尺度性质的必要性  在空间和时间上  心脏功能。相关的空间尺度从纳米（亚细胞）到微观（细胞）和宏观（器官）水平不等。上述发展得益于“微观到宏观”领域日益准确的数据，但“纳米到微观”层面迄今在很大程度上被忽视。然而，为了理解亚细胞机制，必须解决心肌细胞的区室化，这是从信号传导到离子处理和收缩的综合行为的基础。为此，所面临的挑战是获得单个心肌细胞的细胞解剖结构的准确表示。ET是理想的结构，其尺寸变化显着在一个小的体积。它允许计算机生成比物理切割薄得多的“虚拟切片”。因此，ET对于具有复杂3D几何形状的结构是理想的，例如细胞骨架阵列或心室肌细胞中的T-小管、肌浆网和微管的卷曲膜系统。通过这种方法，可以开始重建单个心脏细胞，以超越将细胞视为电活动的“点源”或机械机构的统一“构建块”的方式来模拟心肌细胞活动的结构。 参考文献： Garny A & Kohl P.心脏研究在工程和计算的界面。化学工程师9月：31-32（2004）。 Kohl P，Noble D，温斯洛RL & Hunter PJ.生物系统的计算建模：工具和愿景。PhilTrans R Soc A 358：579-610（2000）。 诺布尔湾基于Hodgkin-Huxley方程的心脏动作和起搏器电位Nature 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).