Once myocardium dies during a heart attack, it is replaced by scar tissue over the course of several weeks. The size, location, composition, structure and mechanical properties of the healing scar are all critical determinants of the fate of patients who survive the initial infarction. While the central importance of scar structure in determining pump function and remodeling has long been recognized, it has proven remarkably difficult to design therapies that improve heart function or limit remodeling by modifying scar structure. Many exciting new therapies are under development, but predicting their long-term effects requires a detailed understanding of how infarct scar forms, how its properties impact left ventricular function and remodeling, and how changes in scar structure and properties feed back to affect not only heart mechanics but also electrical conduction, reflex hemodynamic compensations, and the ongoing process of scar formation itself. In this article, we outline the scar formation process following an MI, discuss interpretation of standard measures of heart function in the setting of a healing infarct, then present implications of infarct scar geometry and structure for both mechanical and electrical function of the heart and summarize experiences to date with therapeutic interventions that aim to modify scar geometry and structure. One important conclusion that emerges from the studies reviewed here is that computational modeling is an essential tool for integrating the wealth of information required to understand this complex system and predict the impact of novel therapies on scar healing, heart function, and remodeling following myocardial infarction.

Electrophysiological studies of excitable organs usually focus on action potential (AP)-generating cells, whereas nonexcitable cells are generally considered as barriers to electrical conduction. Whether nonexcitable cells may modulate excitable cell function or even contribute to AP conduction via direct electrotonic coupling to AP-generating cells is unresolved in the heart: such coupling is present in vitro, but conclusive evidence in situ is lacking. We used genetically encoded voltage-sensitive fluorescent protein 2.3 (VSFP2.3) to monitor transmembrane potential in either myocytes or nonmyocytes of murine hearts. We confirm that VSFP2.3 allows measurement of cell type-specific electrical activity. We show that VSFP2.3, expressed solely in nonmyocytes, can report cardiomyocyte AP-like signals at the border of healed cryoinjuries. Using EM-based tomographic reconstruction, we further discovered tunneling nanotube connections between myocytes and nonmyocytes in cardiac scar border tissue. Our results provide direct electrophysiological evidence of heterocellular electrotonic coupling in native myocardium and identify tunneling nanotubes as a possible substrate for electrical cell coupling that may be in addition to previously discovered connexins at sites of myocyte-nonmyocyte contact in the heart. These findings call for reevaluation of cardiac nonmyocyte roles in electrical connectivity of the heterocellular heart.

Physiological variability manifests itself via differences in physiological function between individuals of the same species, and has crucial implications in disease progression and treatment. Despite its importance, physiological variability has traditionally been ignored in experimental and computational investigations due to averaging over samples from multiple individuals. Recently, modelling frameworks have been devised for studying mechanisms underlying physiological variability in cardiac electrophysiology and pro-arrhythmic risk under a variety of conditions and for several animal species as well as human. One such methodology exploits populations of cardiac cell models constrained with experimental data, or experimentally-calibrated populations of models. In this review, we outline the considerations behind constructing an experimentally-calibrated population of models and review the studies that have employed this approach to investigate variability in cardiac electrophysiology in physiological and pathological conditions, as well as under drug action. We also describe the methodology and compare it with alternative approaches for studying variability in cardiac electrophysiology, including cell-specific modelling approaches, sensitivity-analysis based methods, and populations-of-models frameworks that do not consider the experimental calibration step. We conclude with an outlook for the future, predicting the potential of new methodologies for patient-specific modelling extending beyond the single virtual physiological human paradigm.

In just over a decade, Systems Biology has moved from being an idea, or rather a disparate set of ideas, to a mainstream feature of research and funding priorities. Institutes, departments, and centers of various flavors of Systems Biology have sprung up all over the world. An Internet search now produces more than 2 million hits. Of the 2,800 entries in PubMed with "Systems Biology" in either the title or the abstract, only two papers were published before 2000, and >90% were published in the past five years. In this article, we interpret Systems Biology as an approach rather than as a field or a destination of research. We illustrate that this approach is productive for the exploration of systems behavior, or "phenotypes," at all levels of structural and functional complexity, explicitly including the supracellular domain, and suggest how this may be related conceptually to genomes and biochemical networks. We discuss the role of models in Systems Biology and conclude with a consideration of their utility in biomedical research and development.

The heart is vital for biological function in almost all chordates, including human. It beats continually throughout our life, supplying the body with oxygen and nutrients while removing waste products. If it stops - so does life. The heartbeat involves precise coordination of the activity of billions of individual cells, as well as their swift and well-coordinated adaption to changes in physiological demand. Much of the vital control of cardiac function occurs at the level of individual cardiac muscle cells, including acute beat-by-beat feedback from the local mechanical environment to electrical activity (as opposed to longer-term changes in gene expression, and functional or structural remodelling). This process is known as Mechano-Electric Coupling (MEC). In the current review, we: present evidence for, and implications of, MEC in health and disease in human; summarise our understanding of MEC effects gained from whole animal, organ, tissue, and cell studies; identify potential molecular mediators of MEC responses; and demonstrate the power of computational modelling in developing a more comprehensive understanding of 'what makes the heart tick'.