Background:The Purkinje network is essential for normal electrical impulse propagation in the heart but has also been implicated in ventricular arrhythmias. Previous experimental work has suggested that not all Purkinje-myocardial junctions (PMJs) are active at rest due to source-sink mismatch at the PMJs. Objective:We hypothesized that pathological conditions that cause gap junction uncoupling (e.g., acute ischaemia), would increase the number of active PMJs, leading to more complex activation patterns. Methods:We investigated this using a whole-heart intact Purkinje system preparation that allowed direct high-resolution endocardial mapping to interrogate PMJ function. Twelve (7 control, five rotigaptide) Langendorff-perfused hearts from New Zealand white rabbits were subjected to an ischaemia-reperfusion protocol and optically mapped. Computational modelling was performed to determine the effects of gap junction coupling on PMJ function, and on the complexity of endocardial activation. Results:During ischaemia, the percentage of right ventricle area activated within the first 5 ms decreased from baseline 62% ± 7% to 52% ± 8% during early ischaemia (p = 0.04), consistent with slowing of conduction. This was followed by a paradoxical increase in late-ischaemia (60% ± 8%) due to extra regions of early activation. Gap junction enhancement with rotigaptide during ischaemia abolished the aforementioned pattern. Parallel computational experiments replicated experimental findings only when the number of functional PMJs was increased during ischaemia. With more active PMJs, there were more breakthrough sites with increased complexity of activation, as also measured in biological preparations. Conclusion:Normally-quiescent PMJs can become active in the context of gap junction uncoupling during acute ischaemia. Pharmacological gap junction modulation may alter propagation patterns across PMJs and may be used as a therapeutic strategy for Purkinje system associated arrhythmias.

The present study aimed to characterize the SCN5A variant I1333V, found in five families with a history of suspected catecholaminergic polymorphic ventricular tachycardia (CPVT). SCN5A encodes the pore-forming subunit of the cardiac voltage-gated sodium channel NaV1.5. Gain of SCN5A function causes long QT syndrome type 3 (LQT3), but its involvement in CPVT is disputed. Nineteen patients harboring the I1333V variant were identified across five families, commonly presenting with exercise-induced arrhythmia, including polymorphic premature ventricular contractions, ventricular bigeminy, couplets, and ventricular tachycardias. Prolonged QT interval was a less consistent finding, and structural myocardial changes were absent. Human NaV1.5/β1 complexes were expressed in Xenopus laevis oocytes, using RNA combinations to emulate homozygous wild-type, heterozygous and homozygous I1333V-mutant conditions. Cells were studied using the cut-open oocyte Vaseline gap voltage-clamp to evaluate effects of I1333V on NaV1.5 function. NaV1.5(I1333V) channels required less depolarization to activate, classifying this variant as gain-of-function. Fast inactivation was unaffected, and action-potential (AP) clamp showed no significant differences in late Na+ current. A computational model of human ventricular myocyte excitability predicted no effect of I1333V on AP duration; instead, it showed stronger Na+ influx during the AP upstroke, concurrent with elevated Ca2+ import via the sodium‑calcium exchanger. Finally, NaV1.5(I1333V) channels exhibited a diminished response to cAMP (emulating adrenergic stimulation), which also likely contributes to arrhythmogenesis. In conclusion, I1333V is a gain-of-function variant of SCN5A with a unique set of functional consequences. It is associated with cardiac arrhythmia disease characterized by overlapping CPVT-like and LQT3 features. Our findings support that SCN5A should be considered in genetic screening of suspected CPVT.

In the calibration process, replicating some cellular properties is the main focus, while the importance of membrane resistance (Rm) that is primal in the tissue-level modeling is often underestimated. Previously, we presented a framework in which Rm in addition to action potential (AP) waveform was considered in the cellular model fitting. In this paper, we test the hypothesis that this approach for tuning cellular model parameters improves the accuracy of simulations at the tissue level. In doing so, two different sets of single-cell models are generated via independent realizations of our multi-objective optimization approach. In the first set of calibration (Model I), root-mean-square error (RMSE) of AP, and absolute error (AE) of maximum upstroke velocity are included as optimization functions; however, in the second set of calibration (Model II), RMSE of Rm curve in the repolarization phase is also added to the optimization functions. The calibrated cell models are then used in several tissue configurations of physiological relevance. We adopt well-defined evaluation metrics to compare tissue models tuned using Models I and II. In the source-sink mismatch configuration, the average absolute relative error (ARE) of the critical transition border, defined as the smallest required window width between source and sink for AP propagation, is less than 4.7 % in Model II, while this error is increased to more than 8.9 % in Model I. In addition, in Model I, the average ARE of total time for activation of tissue is 3.3-6.3 %; however, in Model II, this error is reduced to 0.7-1.6 %. In the Purkinje-myocardium configuration, the average of RMSE of activation time map is reduced approximately 75 % in Model II. Finally, in the transmural APD heterogeneity configuration, the average AREs of AP duration (APD) and APD dispersion (i.e., the difference between maximum and minimum of APD) are about 13.2 % and 17.4 % in Model I and 5.8 % and 6.8 % in Model II, respectively. Overall, our results demonstrate that consideration of Rm in the single-cell optimization procedure yields a substantial improvement in the accuracy of tissue models.

Cardiac cellular models are utilized as the building blocks for tissue simulation. One of the imprecisions of conventional cellular modeling, especially when the models are used in tissue-level modeling, stems from the mere consideration of cellular properties (e.g., action potential shape) in parameter tuning of the model. In our previous work, we put forward an accurate framework in which membrane resistance (R m ) reflecting inter-cellular characteristics, i.e., electrotonic effects, was considered alongside cellular features in cellular model fitting. This paper, for the first time, examines the hypothesis that considering R m as an additional optimization objective improves the accuracy of tissue-level modeling. To study this hypothesis, after cellular-level optimization of a well-known model, source-sink mismatch configurations in a 2-dimensional model are investigated. The results demonstrate that including R m in the optimization protocol yields a substantial improvement in the relative error of the critical transition border which is defined as the minimum window size between source and sink that wave propagates. Model developers can utilize the proposed concept during parameter tuning to increase the accuracy of models.

Mathematical models of cardiac cells have been established to broaden understanding of cardiac function. In the process of developing electrophysiological models for cardiac myocytes, precise parameter tuning is a crucial step. The membrane resistance (Rm) is an essential feature obtained from cardiac myocytes. This feature reflects intercellular coupling and affects important phenomena, such as conduction velocity, and early after-depolarizations, but it is often overlooked during the phase of parameter fitting. Thus, the traditional parameter fitting that only includes action potential (AP) waveform may yield incorrect values for Rm. In this paper, a novel multi-objective parameter fitting formulation is proposed and tested that includes different regions of the Rm profile as additional objective functions for optimization. As Rm depends on the transmembrane voltage (Vm) and exhibits singularities for some specific values of Vm, analyses are conducted to carefully select the regions of interest for the proper characterization of Rm. Non-dominated sorting genetic algorithm II is utilized to solve the proposed multi-objective optimization problem. To verify the efficacy of the proposed problem formulation, case studies and comparisons are carried out using multiple models of human cardiac ventricular cells. Results demonstrate Rm is correctly reproduced by the tuned cell models after considering the curve of Rm obtained from the late phase of repolarization and Rm value calculated in the rest phase as additional objectives. However, relative deterioration of the AP fit is observed, demonstrating trade-off among the objectives. This framework can be useful for a wide range of applications, including the parameters fitting phase of the cardiac cell model development and investigation of normal and pathological scenarios in which reproducing both cellular and intercellular properties are of great importance.

Cardiac models constructed from sets of differential equations provide invaluable information about heart mechanism and disorder of both human and animals. As tuning the parameters is a profoundly important step of modeling, this paper presents a novel parametrization technique based on a bilevel framework that benefits from two solution approaches, namely mixed integer genetic algorithm (MIGA) and linear least squares (LLS). In the upper-level optimization step, the action potential (AP) of the model is fitted to the reference AP using MIGA. In the lower-level optimization step, the mismatch between the total current of the model and reference is minimized via a clamp concept-based linearization and LLS solution approach. Notably, the clamp concept can diminish the nonlinearity of the parameter fitting problem. The issue of dependency on initial parameters in the lower-level problem, as well as the sensitivity of model parameters to linearization, are circumvented by MIGA in the upper-level optimization. For evaluation of MIGA-LLS performance, two complex human ventricular models are employed. The results demonstrate that in comparison to the genetic algorithm (GA)-based approach, the proposed framework significantly reduces the average and variation of normalized root-mean-squared error (NRMSE) in terms of the AP and total current in different trials. Variability in the resulting parameter values is considerably decreased as well.

Amongst the complications of diabetes is arrhythmia, the risk of which depends on multiple factors. This study was designed to investigate several factors, including the effects of ATP-sensitive potassium current, lateralized connexins, and gap junction uncoupling. ATP-sensitive potassium channel (I KATP) opening is caused by ischemia, which can occur in diabetic or non-diabetic hearts. I KATP opening was simulated in this work to determine if the risk of ischemia-induced arrhythmias is affected by diabetes. Simulations were performed using healthy and diabetic models of rat and rabbit ventricle. Results showed that the diabetic rat model is less vulnerable to reentrant arrhythmia than the healthy rat model. The diabetic rabbit model was more vulnerable to reentrant arrhythmia than the healthy rabbit model. In both rabbit models, the vulnerability increased as the gap junctional coupling decreased. Opening of I KATP resulted in larger window of vulnerability. Conduction reserve was simulated based on 1D simulations for both rat and rabbit models. There was no difference between rat and rabbit conduction reserve. Our results showed that the simulation results are model-dependent, i.e., results from the rabbit model are similar to human clinical data, while the results from the rat model contradict human clinical observations, suggesting a significant species-dependence in arrhythmia vulnerability in the diabetic heart.

BackgroundArrhythmogenic cardiomyopathy is an inherited heart muscle disorder leading to ventricular arrhythmias and heart failure, mainly as a result of mutations in cardiac desmosomal genes. Desmosomes are cell-cell junctions mediating adhesion of cardiomyocytes; however, the molecular and cellular mechanisms underlying the disease remain widely unknown. Desmo-collin-2 is a desmosomal cadherin serving as an anchor molecule required to reconstitute homeostatic intercellular adhesion with desmoglein-2. Cardiac specific lack of desmoglein-2 leads to severe cardiomyopathy, whereas overexpression does not. In contrast, the corresponding data for desmocollin-2 are incomplete, in particular from the view of protein overexpression. Therefore, we developed a mouse model overexpressing desmocollin-2 to determine its potential contribution to cardiomyopathy and intercellular adhesion pathology.Methods and resultsWe generated transgenic mice overexpressing DSC2 in cardiac myocytes. Transgenic mice developed a severe cardiac dysfunction over 5 to 13 weeks as indicated by 2D-echocardiography measurements. Corresponding histology and immunohistochemistry demonstrated fibrosis, necrosis and calcification which were mainly localized in patches near the epi- and endocardium of both ventricles. Expressions of endogenous desmosomal proteins were markedly reduced in fibrotic areas but appear to be unchanged in non-fibrotic areas. Furthermore, gene expression data indicate an early up-regulation of inflammatory and fibrotic remodeling pathways between 2 to 3.5 weeks of age.ConclusionCardiac specific overexpression of desmocollin-2 induces necrosis, acute inflammation and patchy cardiac fibrotic remodeling leading to fulminant biventricular cardiomyopathy.

Ca2+ sparks are generated in a voltage-dependent manner to initiate spontaneous transient outward currents (STOCs), events that moderate arterial constriction. In this study, we defined the mechanisms by which membrane depolarization increases Ca2+ sparks and subsequent STOC production. Using perforated patch clamp electrophysiology and rat cerebral arterial myocytes, we monitored STOCs in the presence and absence of agents that modulate Ca2+ entry. Beginning with Ca(V)3.2 channel inhibition, Ni2+ was shown to decrease STOC frequency in cells held at hyperpolarized (-40mV) but not depolarized (-20mV) voltages. In contrast, nifedipine, a Ca(V)1.2 inhibitor, markedly suppressed STOC frequency at -20mV but not -40mV. These findings aligned with the voltage-dependent profiles of L- and T-type Ca2+ channels. Furthermore, computational and experimental observations illustrated that Ca2+ spark production is intimately tied to the activity of both conductances. Intriguingly, this study observed residual STOC production at depolarized voltages that was independent of Ca(V)1.2 and Ca(V)3.2. This residual component was insensitive to TRPV4 channel modulation and was abolished by Na+/Ca2+ exchanger blockade. In summary, our work highlights that the voltage-dependent triggering of Ca2+ sparks/STOCs is not tied to a single conductance but rather reflects an interplay among multiple Ca2+ permeable pores with distinct electrophysiological properties. This integrated orchestration enables smooth muscle to grade Ca2+ spark/STOC production and thus precisely tune negative electrical feedback.

Cardiac optical mapping in whole heart preparations is a research tool that contributes to the understanding of normal and abnormal cardiac electrical activity. The value of the technique is challenged by the presence of motion artifacts in the action potentials retrieved. Motion artifacts appear as a distortion of the action potential and affect the evaluation of electrophysiological parameters of interest such as action potential duration. Dual wavelength optical mapping offers the possibility of correcting motion artifacts by taking advantage of the ratiometric properties of the potentiometric dye used to record the electrical activity. In dual wavelength optical mapping, action potentials are recorded at two wavelengths and a ratio signal is calculated between the signals, removing the artifacts common to both wavelengths. Ratiometry relies on the assumption that motion artifacts in the two channels are similar in direction and shape. However, in practice ratiometry does not completely remove motion artifacts, a fact that has not yet been explained. Differences in signal amplitude between channels have been reported by earlier studies; however, these differences can be dealt with by scaling the signals appropriately. Early data acquired for this study suggest more complex differences exist between motion artifacts acquired in both channels. These differences affect the performance of ratiometry and may explain the inability of the technique to completely remove motion artifacts. This paper presents early examples of how the differences in shape, direction and amplitude between motion artifacts in dual wavelength recordings affect the results of the calculated ratio signal.

Motion artifacts are a major disadvantage of cardiac optical mapping studies. Pixel misalignment due to contraction is a main cause of the presence of gross motion artifacts in action potential recordings. This study is focused on methods for identifying landmarks and tracking the motion of cardiac tissue for preparations in optical mapping recordings. This is a first step toward our long-term goal to implement a landmark-based image registration technique to correct for pixel misalignment in cardiac optical mapping fluorescence videos and, hence, for gross motion artifacts. Preliminary results for the registration step are presented as an initial proof of concept. The characteristics of the optical mapping images are challenging, since their lack of contrast and well-defined features impose a limitation on the techniques than can be used for landmark selection and motion tracking. This paper compares results of motion estimation of the cardiac surface with two approaches that do not rely on high-contrast features: 1) Scale-invariant feature transform (SIFT) detected “keypoints,” to be used as landmarks for motion tracking, as well as 2) a classical global optical flow (OF) algorithm. Both are applied to low-contrast and low-resolution cardiac fluorescence images. We demonstrate that the performance of SIFT is superior to that of OF for pixel motion tracking in cardiac optical mapping images with simulated motion. Results for action potential recovery and action potential duration calculation after landmark-based image registration show that SIFT landmark-based registration yields superior performance in this regard as well.

Introduction:The His-Purkinje system activates ventricular myocardium through Purkinje-Myocardial Junctions (PMJs).It has been suggested that most PMJs are normally non-functional at baseline due to source-sink mismatches at these junctions.We hypothesised that gap junctional uncoupling at the PMJs during acute ischaemia facilitates propagation across a greater number of functional PMJs, thereby leading to accelerated but more complex activation patterns.Methods: In aortic-perfused rabbit hearts (n ¼ 8), the right ventricles (RV) were exposed, preserving the Purkinje system (Figure ), and the endocardium optically mapped.Activation of the RV endocardium during atrial pacing was recorded during 40 minutes of global ischemia followed by 30 minutes reperfusion.A corresponding detailed 3D computer model of rabbit ventricles incorporating the Purkinje system was constructed to test the hypothesis.Results: Optical mapping studies revealed that the percentage of RV area activated within the first 5ms decreased from baseline 53 + 6% to 43 + 8% during early ischemia (,20 min), and paradoxically then increased to 59 + 8%, with more complex activation (p , 0.001).This coincided with more surface breakthroughs at more PMJs during late ischaemia (Figure).Activation normalised after reperfusion.In the computer model, a 6% reduction in conductivity was sufficient to render quiescent PMJs active.Increasing the fraction of functioning PMJs from 5% to 100% accelerated endocardial activation from 27.1 to 15.8 ms, compensating for reduced conduction velocity.Surface breakthroughs increased, as did the complexity of activation, matching the experiments.Conclusion: At baseline, most PMJs are quiescent.Ischaemia-induced closure of gap junction channels reduces conduction velocity, but as the uncoupling progresses, more PMJs become functional due to reduced source-load mismatch.The altered, more complex, activation patterns during ischaemia may be pro-arrhythmic as they increase the pathways for meandering wavefronts and the likelihood of wave collision.

Mathematical models of single cardiac myocytes have a valuable role in driving progress in cardiac physiology and in exploring the electrophysiological mechanisms underlying heart function. Most of these models are used to mimic the results of experimentally observed biological phenomena measured in animal models, and can also provide quantitative insights into natural processes. Adjusting parameters in an ionic model to reproduce experimental behaviour is difficult. Mostly, researchers fit the only the net current to reproduce an action potential (AP) shape. However, even with an excellent AP match in the single cell, tissue behaviour can be vastly different. We hypothesize that this uncertainty can be reduced by additionally fitting Rm.

Fitting parameter sets of non-linear equations in cardiac single cell ionic models to reproduce experimental behavior is a time consuming process. The standard procedure is to adjust maximum channel conductances in ionic models to reproduce action potentials (APs) recorded in isolated cells. However, vastly different sets of parameters can produce similar APs. Furthermore, even with an excellent AP match in case of single cell, tissue behaviour may be very different. We hypothesize that this uncertainty can be reduced by additionally fitting membrane resistance (Rm). To investigate the importance of Rm, we developed a genetic algorithm approach which incorporated Rm data calculated at a few points in the cycle, in addition to AP morphology. Performance was compared to a genetic algorithm using only AP morphology data. The optimal parameter sets and goodness of fit as computed by the different methods were compared. First, we fit an ionic model to itself, starting from a random parameter set. Next, we fit the AP of one ionic model to that of another. Finally, we fit an ionic model to experimentally recorded rabbit action potentials. Adding the extra objective (Rm, at a few voltages) to the AP fit, lead to much better convergence. Typically, a smaller MSE (mean square error, defined as the average of the squared error between the target AP and AP that is to be fitted) was achieved in one fifth of the number of generations compared to using only AP data. Importantly, the variability in fit parameters was also greatly reduced, with many parameters showing an order of magnitude decrease in variability. Adding Rm to the objective function improves the robustness of fitting, better preserving tissue level behavior, and should be incorporated.

Cardiac propagation characteristics such as anisotropy ratio and conduction velocities are often determined experimentally from epicardial measurements. We hypothesize that these measurements have inaccuracies due to intramural fiber rotation and transmural electrotonic interactions. We also hypothesize that optical mapping (OM) recordings compound the error, due to contributions from deeper layers. In this study, we studied propagation in a three-dimensional computer model of a slab of tissue with varying thickness and a 120° fiber rotation. Simulation results were further processed to reconstruct OM signals. As expected, simulation results demonstrated that the direction of wave propagation on the epicardial surface is not aligned with the epicardial fiber orientation. This angle difference was most pronounced for thin tissue, and decreased with decreasing intramural conductivity and increasing tissue thickness. This difference also increased with time elapsed poststimulus, as the contribution from deeper layers increased. Observations were confirmed experimentally with OM measurements from isolated rat hearts. Simulations also predicted that OM causes an additional error in measurements due to activity in deeper layers being less aligned. Several alternative approaches for the estimation of fiber orientation and anisotropy ratio were evaluated. Those based on conduction velocity measurements yielded the most accurate estimates when applied to noise-free simulated data.

The Purkinje system is the fast conduction network of the heart which couples to the myocardium at discrete sites called Purkinje-Myocyte Junctions (PMJs). However, the distribution and number of PMJs remains elusive, as does whether a particular PMJ is functional. We hypothesized that the Purkinje system plays a role during reentry and that the number of functional PMJs affect reentry dynamics. We used a computer finite element model of rabbit ventricles in which we varied the number of PMJs. Sustained, complex reentry was induced by applying an electric shock and the role of the Purkinje system in maintaining the arrhythmia was assessed by analyzing phase singularities, frequency of activation, and bidirectional propagation at PMJs. For larger junctional resistances, increasing PMJ density increased the mean firing rate in the Purkinje system, the percentage of successful retrograde conduction at PMJs, and the incidence of wave break on the epicardium. However, the mean firing of the ventricles was not affected. Furthermore, increasing PMJ density above 13/[Formula: see text] did not alter reentry dynamics. For lower junctional resistances, the trend was not as clear. We conclude that Purkinje system topology affects reentry dynamics and conditions which alter PMJ density can alter reentry dynamics.

It is established that in healthy human pregnancies, there are changes in cardiovascular status, including a significant (≈15%–20%) increase in resting heart rate.1 Although the underlying mechanisms are not well understood, it has been suggested that this pregnancy-related elevation in heart rate may be mediated by increased efferent activity of and/or sensitivity to sympathetic stimulation, concurrent with decreased sensitivity of the heart to parasympathetic activity.2 This increased sympathetic stimulation may be a reflex response to the pregnancy-related decrease in total peripheral resistance and systemic vascular tone, consistent with the need to maintain arterial blood pressure.3 The elevation in resting heart rate is usually benign, although an increase in the incidence of ventricular arrhythmias may result. At present, both intrinsic (pacemaker activity or automaticity) and extrinsic (eg, adrenergic tone) reflex responses are being considered as proarrhythmic factors; however, there is no consensus concerning the underlying ionic mechanisms. Article see p 2009 In this issue of Circulation , researchers in the Fiset laboratory at the Montreal Heart Institute report that in an adult mouse model, pregnancy is associated with a significant and selective upregulation of the so-called funny current ( I f) in the sinoatrial node or primary pacemaker region of the heart.4 The term funny was coined because this current is activated by hyperpolarization, as opposed to depolarization, of membrane potential. I f is modulated, that is, increased or decreased, by the autonomic transmitters norepinephrine and acetylcholine, respectively.5 It is carried mainly by Na+ under physiological conditions.6 El Khoury et al4 report that in pacemaker cells isolated from healthy pregnant adult female mice, I f is increased as a result of enhanced expression of these channels in the sarcolemma. No change in steady-state voltage dependence, that is, the range of membrane potentials for activation, …