From ionic to cellular variability in human atrial myocytes: an integrative computational and experimental study.

Variability refers to differences in physiological function between individuals, which may translate into different disease susceptibility and treatment efficacy. Experiments in human cardiomyocytes face wide variability and restricted tissue access; under these conditions, computational models are a useful complementary tool. We conducted a computational and experimental investigation in cardiomyocytes isolated from samples of the right atrial appendage of patients undergoing cardiac surgery to evaluate the impact of variability in action potentials (APs) and subcellular ionic densities on Ca transient dynamics.

Up-regulation of miR-31 in human atrial fibrillation begets the arrhythmia by depleting dystrophin and neuronal nitric oxide synthase.

Atrial fibrillation (AF) is a growing public health burden, and its treatment remains a challenge. AF leads to electrical remodeling of the atria, which in turn promotes AF maintenance and resistance to treatment. Although remodeling has long been a therapeutic target in AF, its causes remain poorly understood.

Variability in cardiac electrophysiology: Using experimentally-calibrated populations of models to move beyond the single virtual physiological human paradigm.

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.

Human-based approaches to pharmacology and cardiology: an interdisciplinary and intersectorial workshop.

Both biomedical research and clinical practice rely on complex datasets for the physiological and genetic characterization of human hearts in health and disease. Given the complexity and variety of approaches and recordings, there is now growing recognition of the need to embed computational methods in cardiovascular medicine and science for analysis, integration and prediction. This paper describes a Workshop on Computational Cardiovascular Science that created an international, interdisciplinary and inter-sectorial forum to define the next steps for a human-based approach to disease supported by computational methodologies.