MATHEMATICAL MODELING OF HEART RHYTHM DISORDERS

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。 心脏是一个复杂的非线性系统，其功能涉及机械收缩和电化学兴奋波之间的相互作用。心跳是这些电和机械功能的非线性行为的结果。在正常心跳期间，兴奋波产生肌肉的协调收缩，称为正常窦性心律。在某些情况下，有序的波会发展成一种复杂的动力学状态，称为纤维性颤动，这会导致肌肉收缩紊乱。心房纤颤虽然不致命，但会使患者感到疲劳，并可能增加中风的风险。另一方面，心室颤动更可怕。在心室纤维性颤动期间，心室的无序收缩不能有效地排出血液，如果不进行治疗，会在几分钟内导致死亡。心室颤动是心源性猝死的主要原因，在美国每年有30 - 40万人死于心源性猝死。要全面了解心脏节律紊乱，需要对生物尺度上的电、化学和机械活动之间的相互作用进行系统水平的研究，范围从离子通道到单细胞到多细胞组织和器官。虽然在实验室中监测和控制所有这些因素是困难的，但数学建模为此提供了有用的工具。对心脏非线性动力学的系统级理解不仅可以提高预测和预防致死性心律的能力，而且还可以推动数学建模技术在模型简化、涌现特性和多尺度建模等领域的发展。

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. The heart is a complex nonlinear system, whose function involves the interaction between mechanical contractions and waves of electrochemical excitation. Heartbeats are the result of the nonlinear behaviors of these electrical and mechanical functions. During normal heartbeats, the waves of excitation generate a coordinated contraction of the muscle, known as normal sinus rhythm. In some situations, the orderly waves develop into a complex dynamical state known as fibrillation, which leads to disorganized muscle contractions. Fibrillation in the atria, although not lethal, leaves a patient feeling tired and may increase the risk of stroke. On the other hand, ventricular fibrillation is more dreadful. During ventricular fibrillation, disorganized contractions of the ventricles fail to eject blood effectively, leading to death within a few minutes if left untreated. Ventricular fibrillation is the main cause of sudden cardiac death, which claims 300,000-400,000 lives a year in the United States. A complete understanding of heart rhythm disorders requires a system-levels investigation on the interaction between electrical, chemical, and mechanical activities on biological scales ranging from ion channels to single cells to multi-cellular tissue and organ. While it is difficult if not impossible to monitor and control all these factors in the lab, mathematical modeling provides a useful tool for this purpose. A systems-level understanding of cardiac nonlinear dynamics will not only improve the ability to predict and prevent lethal heart rhythms but also drives the advance of techniques of mathematical modeling in areas such as model reduction, emergent properties, and multiscale modeling.