Self-organization of conducting pathways explains electrical wave propagation in cardiac tissues with high fraction of nonconducting cells

Cardiac fibrosis occurs in many forms of heart disease and is considered to be one of the main arrhythmogenic factors. Regions with a high density of fibroblasts are likely to cause blocks of wave propagation that give rise to dangerous cardiac arrhythmias. Therefore, studies of the wave propagation through these regions are very important, yet the precise mechanisms leading to arrhythmia formation in fibrotic cardiac tissue remain poorly understood. Particularly, it is not clear how wave propagation is organized at the cellular level, as experiments show that the regions with a high percentage of fibroblasts (65-75%) are still conducting electrical signals, whereas geometric analysis of randomly distributed conducting and non-conducting cells predicts connectivity loss at 40% at the most (percolation threshold). To address this question, we used a joint in vitro-in silico approach, which combined experiments in neonatal rat cardiac monolayers with morphological and electrophysiological computer simulations. We have shown that the main reason for sustainable wave propagation in highly fibrotic samples is the formation of a branching network of cardiomyocytes. We have successfully reproduced the morphology of conductive pathways in computer modelling, assuming that cardiomyocytes align their cytoskeletons to fuse into cardiac syncytium. The electrophysiological properties of the monolayers, such as conduction velocity, conduction blocks and wave fractionation, were reproduced as well. In a virtual cardiac tissue, we have also examined the wave propagation at the subcellular level, detected wavebreaks formation and its relation to the structure of fibrosis and, thus, analysed the processes leading to the onset of arrhythmias. © 2019 Kudryashova et al

The study of the functionality of cardiomyocytes obtained from induced pluripotent stem cells for the modeling of cardiac arrhythmias based on long QT syndrome

There are risk factors that lead the normal conduction of excitation in the heart into a chaotic one. These factors include hereditary and acquired channelopathies. Many dangerous changes in the work of the heart can be identified using the patient’s electrocardiogram. Such relatively easily detectable changes include the long QT interval syndrome (LQTS). Despite a relatively high prevalence of hereditary LQTS, to which it is necessary to add both hereditary and induced LQTS as well as the ease of detection on the ECG, the mechanism of reentry formation in this syndrome is still un­known. What should be noted is a high variability of the hereditary syndrome and the fact of the connection between the increase in the heart rate and the risk of cardiac arrest. After an electrophysiological study on individual cardiac cells from patients with the LQT syndrome, it became apparent that the search for a mechanism for the transition of the normal heart rhythm to chaotic and fibrillation cannot be limited to recording ion currents in single cells. To solve this problem, we need a model of the behavior of cardiac tissue which reflects the relationship of various factors and the risk of reentry. In order to create an experimental model of LQTS in our work, the iPSC of a pati­ent-specific line from a healthy patient was differentiated into a monolayer of cardiac cells and the parameters of the excitation propagation were studied depending on the stage of differentiation. It was shown that a stable value of the propagation velocity and the response to periodic stimulation in the range of physiological values, are reached after the 30th day of dif­ferentiation