Atrial Myopathy

This paper discusses the evolving concept of atrial myopathy by presenting how it develops and how it affects the properties of the atria. It also reviews the complex relationships among atrial myopathy, atrial fibrillation (AF), and stroke. Finally, it discusses how to apply the concept of atrial myopathy in the clinical setting—to identify patients with atrial myopathy and to be more selective in anticoagulation in a subset of patients with AF. An apparent lack of a temporal relationship between episodes of paroxysmal AF and stroke in patients with cardiac implantable electronic devices has led investigators to search for additional factors that are responsible for AF-related strokes. Multiple animal models and human studies have revealed a close interplay of atrial myopathy, AF, and stroke via various mechanisms (e.g., aging, inflammation, oxidative stress, and stretch), which, in turn, lead to fibrosis, electrical and autonomic remodeling, and a pro-thrombotic state. The complex interplay among these mechanisms creates a vicious cycle of everworsening atrial myopathy and a higher risk of more sustained AF and strokes. By highlighting the importance of atrial myopathy and the risk of strokes independent of AF, this paper reviews the methods to identify patients with atrial myopathy and proposes a way to incorporate the concept of atrial myopathy to guide anticoagulation in patients with AF.S

Response to sub-threshold stimulus is enhanced by spatially heterogeneous activity

Sub-threshold stimuli cannot initiate excitations in active media, but surprisingly as we show in this paper, they can alter the time-evolution of spatially heterogeneous activity by modifying the recovery dynamics. This results in significant reduction of waveback velocity which may lead to spatial coherence, terminating all activity in the medium including spatiotemporal chaos. We analytically derive model-independent conditions for which such behavior can be observed.Comment: 5 pages, 5 figure

Spatial patterns of desynchronization bursts in networks

We adapt a previous model and analysis method (the {\it master stability function}), extensively used for studying the stability of the synchronous state of networks of identical chaotic oscillators, to the case of oscillators that are similar but not exactly identical. We find that bubbling induced desynchronization bursts occur for some parameter values. These bursts have spatial patterns, which can be predicted from the network connectivity matrix and the unstable periodic orbits embedded in the attractor. We test the analysis of bursts by comparison with numerical experiments. In the case that no bursting occurs, we discuss the deviations from the exactly synchronous state caused by the mismatch between oscillators

Spatial gradients in action potential duration created by regional magnetofection of hERG are a substrate for wavebreak and turbulent propagation in cardiomyocyte monolayers

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/95178/1/jphysiol.2012.238758.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/95178/2/TJP_5439_sm_SuppMat.pd

Spatial gradients in action potential duration created by regional magnetofection of hERG are a substrate for wavebreak and turbulent propagation in cardiomyocyte monolayers

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/95178/1/jphysiol.2012.238758.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/95178/2/TJP_5439_sm_SuppMat.pd

Anti-phase synchronization of phase-reduced oscillators using open-loop control

In this letter, we present an elegant method to build and maintain an anti-phase configuration of two nonlinear oscillators with different natural frequencies and dynamics described by the sinusoidal phase-reduced model. The anti-phase synchronization is achieved using a common input that couples the oscillators and consists of a sequence of square pulses of appropriate amplitude and duration. This example provides a proof of principle that open-loop control can be used to create desired synchronization patterns for nonlinear oscillators, when feedback is expensive or impossible to obtain

Phase transitions towards frequency entrainment in large oscillator lattices

We investigate phase transitions towards frequency entrainment in large, locally coupled networks of limit cycle oscillators. Specifically, we simulate two-dimensional lattices of pulse-coupled oscillators with random natural frequencies, resembling pacemaker cells in the heart. As coupling increases, the system seems to undergo two phasetransitions in the thermodynamic limit. At the first, the largest cluster of frequency entrained oscillators becomes macroscopic. At the second, global entrainment settles. Between the two transitions, the system has features indicating self-organized criticality.Comment: 4 pages, 5 figures, submitted to PR

A computational model of induced pluripotent stem-cell derived cardiomyocytes incorporating experimental variability from multiple data sources

KEY POINTS: Induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs) capture patient-specific genotype-phenotype relationships, as well as cell-to-cell variability of cardiac electrical activity Computational modelling and simulation provide a high throughput approach to reconcile multiple datasets describing physiological variability, and also identify vulnerable parameter regimes We have developed a whole-cell model of iPSC-CMs, composed of single exponential voltage-dependent gating variable rate constants, parameterized to fit experimental iPSC-CM outputs We have utilized experimental data across multiple laboratories to model experimental variability and investigate subcellular phenotypic mechanisms in iPSC-CMs This framework links molecular mechanisms to cellular-level outputs by revealing unique subsets of model parameters linked to known iPSC-CM phenotypes ABSTRACT: There is a profound need to develop a strategy for predicting patient-to-patient vulnerability in the emergence of cardiac arrhythmia. A promising in vitro method to address patient-specific proclivity to cardiac disease utilizes induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs). A major strength of this approach is that iPSC-CMs contain donor genetic information and therefore capture patient-specific genotype-phenotype relationships. A cited detriment of iPSC-CMs is the cell-to-cell variability observed in electrical activity. We postulated, however, that cell-to-cell variability may constitute a strength when appropriately utilized in a computational framework to build cell populations that can be employed to identify phenotypic mechanisms and pinpoint key sensitive parameters. Thus, we have exploited variation in experimental data across multiple laboratories to develop a computational framework for investigating subcellular phenotypic mechanisms. We have developed a whole-cell model of iPSC-CMs composed of simple model components comprising ion channel models with single exponential voltage-dependent gating variable rate constants, parameterized to fit experimental iPSC-CM data for all major ionic currents. By optimizing ionic current model parameters to multiple experimental datasets, we incorporate experimentally-observed variability in the ionic currents. The resulting population of cellular models predicts robust inter-subject variability in iPSC-CMs. This approach links molecular mechanisms to known cellular-level iPSC-CM phenotypes, as shown by comparing immature and mature subpopulations of models to analyse the contributing factors underlying each phenotype. In the future, the presented models can be readily expanded to include genetic mutations and pharmacological interventions for studying the mechanisms of rare events, such as arrhythmia triggers.S