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Abstract Cardiac arrhythmias are the leading cause of death and pose a huge health and economic burden globally. Electrocardiography (ECG) is an effective technique for the diagnosis of cardiovascular diseases because of its noninvasive and cost-effective advantages. However, traditional ECG analysis relies heavily on the clinical experience of physicians, which can be challenging and time-consuming to produce valid diagnostic results. This work proposes a new hybrid deep learning model that combines convolutional neural network (CNN) and bidirectional gated recurrent unit (BiGRU) with multi-head attention (CBGM model). Specifically, the model consists of seven convolutional layers with varying filter sizes (4, 16, 32, and 64) and three pooling layers, respectively, while the BiGRU module includes two layers with 64 units each followed by multi-head attention (8-heads). The combination of CNN and BiGRU effectively captures spatio-temporal features of ECG signals, with multi-head attention comprehensively extracted global correlations among multiple segments of ECG signals. The validation in the MIT-BIH arrhythmia database achieved an accuracy of 99.41%, a precision of 99.15%, a specificity of 99.68%, and an F1-Score of 99.21%, indicating its robust performance across different evaluation metrics. Additionally, the model’s performance was evaluated on the PTB Diagnostic ECG Database, where it achieved an accuracy of 98.82%, demonstrating its generalization capability. Comparative analysis against previous methods revealed that our proposed CBGM model exhibits more higher performance in automatic classification of arrhythmia and can be helpful for assisting clinicians by enabling real-time detection of cardiac arrhythmias during routine ECG screenings.

Abstract Background Global longitudinal active strain energy density (GLASED) is an innovative method for assessing myocardial function and quantifies the work performed per unit volume of the left ventricular myocardium. The GLASED, measured using MRI, is the best prognostic marker currently available. This study aimed to evaluate the feasibility of measuring the GLASED using echocardiography and to investigate potential differences in the GLASED among athletes based on age and sex. Methods An echocardiographic study was conducted with male controls, male and female young athletes, and male and female veteran athletes. GLASED was calculated from the myocardial stress and strain. Results The mean age (in years) of the young athletes was 21.6 for males and 21.4 for females, while the mean age of the veteran athletes was 53.5 for males and 54.2 for females. GLASED was found to be highest in young male athletes (2.40 kJ/m3) and lowest in female veterans (1.96 kJ/m3). Veteran males exhibited lower values (1.96 kJ/m3) than young male athletes did (P

The growing use of nitazene synthetic opioids heralds a new phase of the opioid crisis. However, limited information exists on the toxic effects of these drugs, aside from a propensity for respiratory depression. With restricted research availability of nitazenes, we used machine-learning-based tools to evaluate five nitazene compounds' interaction potential with the hERG potassium channel, a key drug antitarget in the heart. All nitazenes were predicted to inhibit hERG with low μM IC50 values. These findings indicate a potential for proarrhythmic hERG block by nitazene opioids, warranting detailed cardiac safety evaluations of these drugs.

Remdesivir (RDV) is the first drug approved by the FDA for clinical treatment of hospitalized patients infected with COVID-19 because it has been shown to have good antiviral activity against a variety of viruses, including Arenaviridae and Coronaviridae viral families. However, it has been reported that its clinical treatment leads to the symptoms of sick sinus syndrome such as sinus bradycardia, conduction block, and sinus arrest, but the electrophysiological mechanism of its specific cardiac adverse events is still unclear. We report complementary, experimental, studies of its electrophysiological effects. In wireless cardiac telemetry experiments in vivo and electrocardiographic studies in ex vivo cardiac preparations, RDV significantly caused sinus bradycardia, sinus atrial block, and prolongation of the QT interval in guinea pigs. Dose-dependent effects of RDV on the electrical activities of sinoatrial node (SA node) preparations of guinea pigs were characterised by multielectrode, optical RH237 voltage mapping. These revealed reversibly reduced sinoatrial conduction time (SACT), increased AP durations (APDs), and decreased the pacemaking rate of the SA node. Patch-clamp experiments showed that RDV significantly inhibited the If current of HCN4 channels, resulting in a significant decrease in the spontaneous firing rate of SA node cells, which may underlie the development of sick sinus node syndrome. In addition, RDV significantly inhibits IKr currents in hERG channels, leading to prolongation of the QT interval and playing a role in bradycardia. Therefore, these findings provide insights into the understanding the bradycardia effect of RDV, which may be used as basic theoretical guidance for the intervention of its adverse events, and prompt safety investigations of RDV’s cardiac safety in the future.

Abstract The heterogeneity of functional cardiomyocytes arises during heart development, which is essential to the complex and highly coordinated cardiac physiological function. Yet the biological and physiological identities and the origin of the specialized cardiomyocyte populations have not been fully comprehended. Here we report a previously unrecognised population of cardiomyocytes expressing Dbhgene encoding dopamine beta-hydroxylase in murine heart. We determined how these myocytes are distributed across the heart by utilising advanced single-cell and spatial transcriptomic analyses, genetic fate mapping and molecular imaging with computational reconstruction. We demonstrated that they form the key functional components of the cardiac conduction system by using optogenetic electrophysiology and conditional cardiomyocyte Dbh gene deletion models. We revealed their close relationship with sympathetic innervation during cardiac conduction system formation. Our study thus provides new insights into the development and heterogeneity of the mammalian cardiac conduction system by revealing a new cardiomyocyte population with potential catecholaminergic endocrine function.

Abstract The left ventricular ejection fraction does not accurately predict exercise capacity or symptom severity and has a limited role in predicting prognosis in heart failure. A better method of assessing ventricular performance is needed to aid understanding of the pathophysiological mechanisms and guide management in conditions such as heart failure. In this study, we propose two novel measures to quantify myocardial performance, the global longitudinal active strain energy (GLASE) and its density (GLASED) and compare them to existing measures in normal and diseased left ventricles. GLASED calculates the work done per unit volume of muscle (energy density) by combining information from myocardial strain and wall stress (contractile force per unit cross sectional area). Magnetic resonance images were obtained from 183 individuals forming four cohorts (normal, hypertension, dilated cardiomyopathy, and cardiac amyloidosis). GLASE and GLASED were compared with the standard ejection fraction, the corrected ejection fraction, myocardial strains, stroke work and myocardial forces. Myocardial shortening was decreased in all disease cohorts. Longitudinal stress was normal in hypertension, increased in dilated cardiomyopathy and severely decreased in amyloid heart disease. GLASE was increased in hypertension. GLASED was mildly reduced in hypertension (1.39 ± 0.65 kJ/m3), moderately reduced in dilated cardiomyopathy (0.86 ± 0.45 kJ/m3) and severely reduced in amyloid heart disease (0.42 ± 0.28 kJ/m3) compared to the control cohort (1.94 ± 0.49 kJ/m3). GLASED progressively decreased in the hypertension, dilated cardiomyopathy and cardiac amyloid cohorts indicating that mechanical work done and systolic performance is severely reduced in cardiac amyloid despite the relatively preserved ejection fraction. GLASED provides a new technique for assessing left ventricular myocardial health and contractile function.

Abstract T‐wave alternans (TWA) has been used for predicting the risk of malignant cardiac arrhythmias and sudden cardiac death (SCD) in multiple clinical settings; however, possible mechanism(s) underlying the spontaneous transition from cellular alternans reflected by TWA to arrhythmias in impaired repolarization remains unclear. The healthy guinea pig ventricular myocytes under E‐4031 blocking IKr (0.1 μM, N = 12; 0.3 μM, N = 10; 1 μM, N = 10) were evaluated using whole‐cell patch‐clamp. The electrophysiological properties of isolated perfused guinea pig hearts under E‐4031 (0.1 μM, N = 5; 0.3 μM, N = 5; 1 μM, N = 5) were evaluated using dual‐ optical mapping. The amplitude/threshold/restitution curves of action potential duration (APD) alternans and potential mechanism(s) underlying the spontaneous transition of cellular alternans to ventricular fibrillation (VF) were examined. There were longer APD80 and increased amplitude and threshold of APD alternans in E‐4031 group compared with baseline group, which was reflected by more pronounced arrhythmogenesis at the tissue level, and were associated with steep restitution curves of the APD and the conduction velocity (CV). Conduction of AP alternans augmented tissue's functional spatiotemporal heterogeneity of regional AP/Ca alternans, as well as the AP/Ca dispersion, leading to localized uni‐directional conduction block that spontaneous facilitated the formation of reentrant excitation waves without the need for additional premature stimulus. Our results provide a possible mechanism for the spontaneous transition from cardiac electrical alternans in cellular action potentials and intercellular conduction without the involvement of premature excitations, and explain the increased susceptibility to ventricular arrhythmias in impaired repolarization. In this study, we implemented voltage‐clamp and dual‐optical mapping approaches to investigate the underlying mechanism(s) for the arrhythmogenesis of cardiac alternans in the guinea pig heart at cellular and tissue levels. Our results demonstrated a spontaneous development of reentry from cellular alternans, arising from a combined actions of restitution properties of action potential duration, conduction velocity of excitation wave and interplay between alternants of action potential and the intracellular Ca handling. We believe this study provides new insights into underlying the mechanism, by which cellular cardiac alternans spontaneously evolves into cardiac arrhythmias.

Background: Electrocardiogram (ECG) provides a straightforward and non-invasive approach for various applications, such as disease classification, biometric identification, emotion recognition, and so on. In recent years, artificial intelligence (AI) shows excellent performance and plays an increasingly important role in electrocardiogram research as well.Objective: This study mainly adopts the literature on the applications of artificial intelligence in electrocardiogram research to focus on the development process through bibliometric and visual knowledge graph methods.Methods: The 2,229 publications collected from the Web of Science Core Collection (WoSCC) database until 2021 are employed as the research objects, and a comprehensive metrology and visualization analysis based on CiteSpace (version 6.1. R3) and VOSviewer (version 1.6.18) platform, which were conducted to explore the co-authorship, co-occurrence and co-citation of countries/regions, institutions, authors, journals, categories, references and keywords regarding artificial intelligence applied in electrocardiogram.Results: In the recent 4 years, both the annual publications and citations of artificial intelligence in electrocardiogram sharply increased. China published the most articles while Singapore had the highest ACP (average citations per article). The most productive institution and authors were Ngee Ann Polytech from Singapore and Acharya U. Rajendra from the University of Technology Sydney. The journal Computers in Biology and Medicine published the most influential publications, and the subject with the most published articles are distributed in Engineering Electrical Electronic. The evolution of research hotspots was analyzed by co-citation references’ cluster knowledge visualization domain map. In addition, deep learning, attention mechanism, data augmentation, and so on were the focuses of recent research through the co-occurrence of keywords.

It has been found that arsenic trioxide (ATO) is effective in treating acute promyelocytic leukemia (APL). However, long QT syndrome was reported in patients receiving therapy using ATO, which even led to sudden cardiac death. The underlying mechanisms of ATO-induced cardiotoxicity have been investigated in some biological experiments, showing that ATO affects human ether-à-go-go-related gene (hERG) channels, coding rapid delayed rectifier potassium current (IKr), as well as L-type calcium (ICaL) channels. Nevertheless, the mechanism by which these channel reconstitutions induced the arrhythmia in ventricular tissue remains unsolved. In this study, a mathematical model was developed to simulate the effect of ATO on ventricular electrical excitation at cellular and tissue levels by considering ATO’s effects on IKr and ICaL. The ATO-dose-dependent pore block model was incorporated into the IKr model, and the enhanced degree of ATO to ICaL was based on experimental data. Simulation results indicated that ATO extended the action potential duration of three types of ventricular myocytes (VMs), including endocardial cells (ENDO), midmyocardial cells (MCELL), and epicardial cells (EPI), and exacerbated the heterogeneity among them. ATO could also induce alternans in all three kinds of VMs. In a cable model of the intramural ventricular strand, the effects of ATO are reflected in a prolonged QT interval of simulated pseudo-ECG and a wide vulnerable window, thus increasing the possibility of spiral wave formation in ventricular tissue. In addition to showing that ATO prolonged QT, we revealed that the heterogeneity caused by ATO is also an essential hazard factor. Based on this, a pharmacological intervention of ATO toxicity by resveratrol was undertaken. This study provides a further understanding of ATO-induced cardiotoxicity, which may help to improve the treatment for APL patients.

Background: Analysis of electrocardiogram (ECG) provides a straightforward and non-invasive approach for cardiologists to diagnose and classify the nature and severity of variant cardiac diseases including cardiac arrhythmia. However, the interpretation and analysis of ECG are highly working-load demanding, and the subjective may lead to false diagnoses and heartbeats classification. In recent years, many deep learning works showed an excellent role in accurate heartbeats classification. However, the imbalance of heartbeat classes is universal in most of the available ECG databases since abnormal heartbeats are always relatively rare in real life scenarios. In addition, many existing approaches achieved prominent results by removing noise and extracting features in data preprocessing, which relies heavily on powerful computers. It is a pressing need to develop efficient and automatic light weighted algorithms for accurate heartbeats classification that can be used in portable ECG sensors.Objective: This study aims at developing a robust and efficient deep learning method, which can be embedded into wearable or portable ECG monitors for classifying heartbeats.Methods: We proposed a novel and light weighted deep learning architecture with weight-based loss based on a convolutional neural network (CNN) and bidirectional long short-term memory (Bi-LSTM) that can automatically identify five types of ECG heartbeats according to the AAMI EC57 standard. It was also true that the raw ECG signals were simply segmented without noise removal and other feature extraction processing. Moreover, to tackle the challenge of classification bias due to imbalanced ECG datasets for different types of arrhythmias, we introduced a weight-based loss function to reduce the influence of over-weighted categories in the ECG dataset. For avoiding the influence of the division of validation dataset, k-fold method was adopted to improve the reliability of the model.Results: The proposed algorithm is trained and tested on MIT-BIH Arrhythmia Database, and achieves an average of 99.33% accuracy, 93.67% sensitivity, 99.18% specificity, 89.85% positive prediction, and 91.65% F1 score.

Roughly 75% of normal myocardial tissue volume is comprised of myocytes, however, fibroblasts by number are the most predominant cells in cardiac tissue. Previous studies have shown distinctive differences in cellular electrophysiology and excitability between myocytes and fibroblasts. However, it is still unclear how the electrical coupling between the two and the increased population of fibroblasts affects the electromechanical dynamics of cardiac tissue. This paper focuses on investigating effects of fibroblast-myocyte electrical coupling (FMEC) and fibroblast population on atrial electrical conduction and mechanical contractility by using a two-dimensional Discrete Element Method (DEM) model of cardiac tissue that is different to finite element method (FEM). In the model, the electro-mechanics of atrial cells are modelled by a biophysically detailed model for atrial electrical action potentials and myofilament kinetics, and the atrial fibroblasts are modelled by an active model that considers four active membrane ionic channel currents. Our simulation results show that the FMEC impairs myocytes’ electrical action potential and mechanical contractibility, manifested by reduced upstroke velocity, amplitude and duration of action potentials, as well as cell length shortening. At the tissue level, the FMEC slows down the conduction of excitation waves, and reduces strain of the tissue produced during a contraction course. These findings provide new insights into understandings of how FMEC impairs cardiac electrical and mechanical dynamics of the heart.

Electrocardiogram (ECG) is a physiological signal widely used in monitoring heart health, which is of great significance to the detection and diagnosis of heart diseases. Because abnormal heart rhythms are very rare, most ECG datasets have data imbalance problems. At present, many algorithms for ECG anomaly automatic recognition are affected by data imbalance. Conventional data augmentation methods are not suitable for the augmentation of the ECG signal, because the ECG signal is one-dimensional and their morphology has physiological significances. In this paper, we propose a ProGAN based ECG sample generation model, called ProEGAN-MS, to solve the problem of data imbalance. The model can stably generate realistic ECG samples. We evaluate the fidelity and diversity of the data generated by the model and compare the data distribution of the original and generated data. In addition, in order to show the diversity of the generated ECG data more intuitively, we manually checked the diversity and calculate the statistics of the data. The results show that compared with other ECG augmentation methods based on GANs, the ECG data generated by our model has higher fidelity and diversity, and the distribution of generated samples is closer to the distribution of original data. Finally, we established neural network models for arrhythmia classification, and used them to evaluate the improvement of the classification model performance by ProEGAN-MS. The results show that augmented data by ProEGAN-MS can effectively improve the insufficient sensitivity and precision of the classification model.

Heart failure is associated with electrical remodeling of the electrical properties and kinetics of the ion channels and transporters that are responsible for cardiac action potentials. However, it is still unclear whether heart failure-induced ionic remodeling can affect the conduction of excitation waves at the Purkinje fiber-ventricle junction contributing to pro-arrhythmic effects of heart failure, as the complexity of the heart impedes a detailed experimental analysis. The aim of this study was to employ computational models to investigate the pro-arrhythmic effects of heart failure-induced ionic remodeling on the cardiac action potentials and excitation wave conduction at the Purkinje fiber-ventricle junction. Single cell models of canine Purkinje fiber and ventricular myocytes were developed for control and heart failure. These single cell models were then incorporated into one-dimensional strand and three-dimensional wedge models to investigate the effects of heart failure-induced remodeling on propagation of action potentials in Purkinje fiber and ventricular tissue and at the Purkinje fiber-ventricle junction. This revealed that heart failure-induced ionic remodeling of Purkinje fiber and ventricular tissue reduced conduction safety and increased tissue vulnerability to the genesis of the unidirectional conduction block. This was marked at the Purkinje fiber-ventricle junction, forming a potential substrate for the genesis of conduction failure that led to re-entry. This study provides new insights into proarrhythmic consequences of heart failure-induced ionic remodeling.

Myocardial ischemia, injury and infarction (MI) are the three stages of acute coronary syndrome (ACS). In the past two decades, a great number of studies focused on myocardial ischemia and MI individually, and showed that the occurrence of reentrant arrhythmias is often associated with myocardial ischemia or MI. However, arrhythmogenic mechanisms in the tissue with various degrees of remodeling in the ischemic heart have not been fully understood. In this study, biophysical detailed single-cell models of ischemia 1a, 1b, and MI were developed to mimic the electrophysiological remodeling at different stages of ACS. 2D tissue models with different distributions of ischemia and MI areas were constructed to investigate the mechanisms of the initiation of reentrant waves during the progression of ischemia. Simulation results in 2D tissues showed that the vulnerable windows (VWs) in simultaneous presence of multiple ischemic conditions were associated with the dynamics of wave propagation in the tissues with each single pathological condition. In the tissue with multiple pathological conditions, reentrant waves were mainly induced by two different mechanisms: one is the heterogeneity along the excitation wavefront, especially the abrupt variation in conduction velocity (CV) across the border of ischemia 1b and MI, and the other is the decreased safe factor (SF) for conduction at the edge of the tissue in MI region which is attributed to the increased excitation threshold of MI region. Finally, the reentrant wave was observed in a 3D model with a scar reconstructed from MRI images of a MI patient. These comprehensive findings provide novel insights for understanding the arrhythmic risk during the progression of myocardial ischemia and highlight the importance of the multiple pathological stages in designing medical therapies for arrhythmias in ischemia.

Beat-by-beat arrhythmia detection in ambulatory electrocardiogram (ECG) monitoring is critical for the evaluation and prognosis of cardiac arrhythmias, however, it is a highly professional demanding and time-consuming task. Current methods for automatic beat-by-beat arrhythmia detection suffer from poor generalization ability due to the lack of large-sample and finely-annotated (labels are given to each beat) ECG data for model training. In this work, we propose a weakly supervised deep learning framework for arrhythmia detection (WSDL-AD), which permits training a fine-grained (beat-by-beat) arrhythmia detector with the use of large amounts of coarsely annotated ECG data (labels are given to each recording) to improve the generalization ability. In this framework, heartbeat classification and recording classification are integrated into a deep neural network for end-to-end training with only recording labels. Several techniques, including knowledge-based features, masked aggregation, and supervised pre-training, are proposed to improve the accuracy and stability of the heartbeat classification under weak supervision. The developed WSDL-AD model is trained for the detection of ventricular ectopic beats (VEB) and supraventricular ectopic beats (SVEB) on five large-sample and coarsely-annotated datasets and the model performance is evaluated on three independent benchmarks according to the recommendations from the Association for the Advancement of Medical Instrumentation (AAMI). The experimental results show that our method improves the F1 score of supraventricular ectopic beats detection by 8%–290% and the F1 of ventricular ectopic beats detection by 4%–11% on the benchmarks compared with the state-of-the-art methods of supervised learning. It demonstrates that the WSDL-AD framework can leverage the abundant coarsely-labeled data to achieve a better generalization ability than previous methods while retaining fine detection granularity. Therefore, this framework has a great potential to be used in clinical and telehealth applications. The source code is available at https://github.com/sdnjly/WSDL-AD.

The involvement of cAMP-dependent regulation of HCN4 in the chronotropic heart rate response is a matter of debate. Here the authors use a knockin mouse model expressing cAMP-insensitive HCN4 channels to discover an inhibitory nonfiring cell pool in the sinoatrial node and a tonic and mutual interaction between firing and nonfiring pacemaker cells that is controlled by cAMP-dependent regulation of HCN4, with implications in chronotropic heart rate responses.

Deep neural networks (DNNs) are currently the best-performing method for many classification problems. For training DNNs, the learning rate is the most important hyper-parameter, choice of which affects the performance of the model greatly. In recent years, some learning rate schedulers, such as HTD, CLR, and SGDR, have been proposed. These methods, some of which make use of the cycling mechanism to improve the convergence speed and accuracy of DNN, but performance degradation occurs in the convergence process. Others have good accuracy, but their convergence speed is too slow. This paper proposed a new learning rate schedule called piecewise arc cotangent decay learning rate (PACL), which can not only improve the convergence speed and accuracy of DNN but also significantly reduce performance degradation zone caused by the cycling mechanism. It is easy to implement, but almost at no extra computing expense. Finally, we demonstrate the effectiveness of PACL, on training CIFAR-10, CIFAR-100, and Tiny ImageNet with ResNet, DenseNet, WRN, SEResNet, and MobileNet.

Cardiac alternans is a dynamical phenomenon in cardiomyocytes, which is linked to the genesis of cardiac mechanical dysfunction and lethal arrhythmias. The beat-to-beat alteration may occur in the amplitude of Ca2+ transients (CaT) or the action potential duration (APD). Typically, APD alternans is a secondary consequence of the CaT alternans and the generation of CaT alternans is relevant to the imbalance of the sarcoplasmic reticulum (SR) Ca2+ release and uptake. However, the effect of cell-cell coupling and $\beta $ -adrenergic receptor ($\beta $ -AdR) stimulation on the initiation and inhibition of CaT alternans is not fully understood. Here, we used a biophysically detailed mathematical model of the mouse atrial myocyte to study the mechanism underlying alternans and the effects of $\beta $ -AdR stimulation. The cell exhibited obvious CaT alternans under fast pacing due to sarcolemmal Ca2+ flux imbalance leaded SR Ca2+ flux imbalance, while no noticeable APD alternans was seen. The $\beta $ -AdR agonist isoproterenol (ISO) inhibited CaT alternans by its regulatory role on amplifying the L-type Ca2+ current. On a one-dimensional strand, cell-cell coupling indirectly alleviated CaT alternans by affecting the overshoot and APD, reducing the triggered SR Ca2+ release. Variation in the cell-cell coupling did not change the pattern of CaT alternans or interfere with the alternans inhibitory effect of $\beta $ -AdR stimulation. Taken together, our results imply a potentially anti-arrhythmic effect of $\beta $ -AdR stimulation and shed new light on the mechanisms behind the cardiac alternans.

Medical imaging provides a powerful tool for medical diagnosis. In the process of computer-aided diagnosis and treatment of liver cancer based on medical imaging, accurate segmentation of liver region from abdominal CT images is an important step. However, due to defects of liver tissue and limitations of CT imaging procession, the gray level of liver region in CT image is heterogeneous, and the boundary between the liver and those of adjacent tissues and organs is blurred, which makes the liver segmentation an extremely difficult task. In this study, aiming at solving the problem of low segmentation accuracy of the original 3D U-Net network, an improved network based on the three-dimensional (3D) U-Net, is proposed. Moreover, in order to solve the problem of insufficient training data caused by the difficulty of acquiring labeled 3D data, an improved 3D U-Net network is embedded into the framework of generative adversarial networks (GAN), which establishes a semi-supervised 3D liver segmentation optimization algorithm. Finally, considering the problem of poor quality of 3D abdominal fake images generated by utilizing random noise as input, deep convolutional neural networks (DCNN) based on feature restoration method is designed to generate more realistic fake images. By testing the proposed algorithm on the LiTS-2017 and KiTS19 dataset, experimental results show that the proposed semi-supervised 3D liver segmentation method can greatly improve the segmentation performance of liver, with a Dice score of 0.9424 outperforming other methods.

The congenital short QT syndrome (SQTS) is a cardiac condition that leads to abbreviated ventricular repolarization and an increased susceptibility to arrhythmia and sudden death. The SQT3 form of the syndrome is due to mutations to the KCNJ2 gene that encodes Kir2.1, a critical component of channels underlying cardiac inwardly rectifying K+ current, IK1. The first reported SQT3 KCNJ2 mutation gives rise to the D172N Kir2.1 mutation, the consequences of which have been studied on recombinant channels in vitro and in ventricular cell and tissue simulations. The aim of this study was to establish the effects of the D172N mutation on ventricular repolarization through real-time replacement of IK1 using the dynamic clamp technique. Whole-cell patch-clamp recordings were made from adult guinea-pig left ventricular myocytes at physiological temperature. Action potentials (APs) were elicited at 1 Hz. Intrinsic IK1 was inhibited with a low concentration (50 µM) of Ba2+ ions, which led to AP prolongation and triangulation, accompanied by a ∼6 mV depolarization of resting membrane potential. Application of synthetic IK1 through dynamic clamp restored AP duration, shape and resting potential. Replacement of wild-type (WT) IK1 with heterozygotic (WT-D172N) or homozygotic (D172N) mutant formulations under dynamic clamp significantly abbreviated AP duration (APD90) and accelerated maximal AP repolarization velocity, with no significant hyperpolarization of resting potential. Across stimulation frequencies from 0.5 to 3 Hz, the relationship between APD90 and cycle length was downward shifted, reflecting AP abbreviation at all stimulation frequencies tested. In further AP measurements at 1 Hz from hiPSC cardiomyocytes, the D172N mutation produced similar effects on APD and repolarization velocity; however, resting potential was moderately hyperpolarized by application of mutant IK1 to these cells. Overall, the results of this study support the major changes in ventricular cell AP repolarization with the D172N predicted from prior AP modelling and highlight the potential utility of using adult ventricular cardiomyocytes for dynamic clamp exploration of functional consequences of Kir2.1 mutations.

Cardiovascular disease is the leading cause of death worldwide and kills over 17 million people per year. In the recent decade, growing epidemiological evidence links air pollution and cardiac arrhythmias, suggesting a detrimental influence of air pollution on cardiac electrophysiological functionality. However, the proarrhythmic mechanisms underlying the air pollution-induced cardiac arrhythmias are not fully understood. The purpose of this work is to provide recent advances in air pollution-induced arrhythmias with a comprehensive review of the literature on the common air pollutants and arrhythmias. Six common air pollutants of widespread concern are discussed, namely particulate matter, carbon monoxide, hydrogen sulfide, sulfur dioxide, nitrogen dioxide, and ozone. The epidemiological and clinical reports in recent years are reviewed by pollutant type, and the recently identified mechanisms including both the general pathways and the direct influences of air pollutants on the cellular electrophysiology are summarized. Particularly, this review focuses on the impaired ion channel functionality underlying the air pollution-induced arrhythmias. Alterations of ionic currents directly by the air pollutants, as well as the alterations mediated by intracellular signaling or other more general pathways are reviewed in this work. Finally, areas for future research are suggested to address several remaining scientific questions.

The macrolide antibiotic azithromycin (AZM) is widely used for respiratory infections and has been suggested to be a possible treatment for the Coronavirus Disease of 2019 (COVID-19). However, AZM-associated QT interval prolongation and arrhythmias have been reported. Integrated mechanistic information on AZM actions on human ventricular excitation and conduction is lacking. Therefore, this study was undertaken to investigate the actions of AZM on ventricular cell and tissue electrical activity. The O'Hara- Virag-Varro-Rudy dynamic (ORd) model of human ventricular cells was modified to incorporate experimental data on the concentration-dependent actions of AZM on multiple ion channels, including INa, ICaL, IKr, IKs, IK1 and INaL in both acute and chronic exposure conditions. In the single cell model, AZM prolonged the action potential duration (APD) in a concentration-dependent manner, which was predominantly attributable to IKr reduction in the acute condition and potentiated INaL in the chronic condition. High concentrations of AZM also increased action potential (AP) triangulation (determined as an increased difference between APD30 and APD90) which is a marker of arrhythmia risk. In the chronic condition, the potentiated INaL caused a modest intracellular Na + concentration accumulation at fast pacing rates. At the 1D tissue level, the AZM-prolonged APD at the cellular level was reflected by an increased QT interval in the simulated pseudo-ECG, consistent with clinical observations. Additionally, AZM reduced the conduction velocity (CV) of APs in the acute condition due to a reduced INa, and it augmented the transmural APD dispersion of the ventricular tissue, which is also pro-arrhythmic. Such actions were markedly augmented when the effects of chronic exposure of AZM were also considered, or with additional IKr block, as may occur with concurrent use of other medications. This study provides insights into the ionic mechanisms by which high concentrations of AZM may modulate ventricular electrophysiology and susceptibility to arrhythmia.

The cardiac hyperpolarization-activated “funny” current (If), which contributes to sinoatrial node (SAN) pacemaking, has a more negative half-maximal activation voltage and smaller fully-activated macroscopic conductance in human than in rabbit SAN cells. The consequences of these differences for the relative roles of If in the two species, and for their responses to the specific bradycardic agent ivabradine at clinical doses have not been systematically explored. This study aims to address these issues, through incorporating rabbit and human If formulations developed by Fabbri et al. into the Severi et al. model of rabbit SAN cells. A theory was developed to correlate the effect of If reduction with the total inward depolarising current (Itotal) during diastolic depolarization. Replacing the rabbit If formulation with the human one increased the pacemaking cycle length (CL) from 355 to 1,139 ms. With up to 20% If reduction (a level close to the inhibition of If by ivabradine at clinical concentrations), a modest increase (~5%) in the pacemaking CL was observed with the rabbit If formulation; however, the effect was doubled (~12.4%) for the human If formulation, even though the latter has smaller If density. When the action of acetylcholine (ACh, 0.1 nM) was considered, a 20% If reduction markedly increased the pacemaking CL by 37.5% (~27.3% reduction in the pacing rate), which is similar to the ivabradine effect at clinical concentrations. Theoretical analysis showed that the resultant increase of the pacemaking CL is inversely proportional to the magnitude of Itotal during diastolic depolarization phase: a smaller If in the model resulted in a smaller Itotal amplitude, resulting in a slower pacemaking rate; and the same reduction in If resulted in a more significant change of CL in the cell model with a smaller Itotal. This explained the mechanism by which a low dose of ivabradine slows pacemaking rate more in humans than in the rabbit. Similar results were seen in the Fabbri et al. model of human SAN cells, suggesting our observations are model-independent. Collectively, the results of study explain why low dose ivabradine at clinically relevant concentrations acts as an effective bradycardic agent in modulating human SAN pacemaking.

The sinus node generates rhythmic heartbeat but the molecular basis of pacemaking is still under debate. Here, the authors combine quantitative proteomics and single-nucleus transcriptomics to characterize the molecular composition of the sinus node and provide insights into the underpinnings of pacemaking.

Cardiac arrhythmia is associated with abnormal electrical activities of the heart, which can be reflected by altered characteristics of electrocardiogram (ECG). Due to the simplicity and non-invasive nature, the ECG has been widely used for detecting arrhythmias and there is an urgent need for automatic ECG detection. Up to date, some algorithms have been proposed for automatic classification of cardiac arrhythmias based on the features of the ECG; however, their stratification rate is still poor due to unreliable features of signal characteristics or limited generalization capability of the classifier, and therefore, it remains a challenge for automatic diagnosis of arrhythmias. In this paper, we propose a new method for automatic classification of arrhythmias based on deep neural networks (DNNs). The two DNN models constitutive of residual convolutional modules and bidirectional long short-term memory (LSTM) layers are trained to extract features from raw ECG signals. The extracted features are concatenated to form a feature vector which is trained to do the final classification. The algorithm is evaluated based on the test set of China Physiological Signal Challenge (CPSC) dataset with F1 measure regarded as the harmonic mean between the precision and recall. The resulting overall F1 score is 0.806, FAF score is 0.914 for atrial fibrillation (AF), FBlock score is 0.879 for block, FPC and FST scores are 0.801 and 0.742 for premature contraction and ST-segment change, which demonstrates a good performance that may have potential practical applications.

T-wave alternans (TWA) reflects every-other-beat alterations in the morphology of the electrocardiogram ST segment or T wave in the setting of a constant heart rate, hence, in the absence of heart rate variability. It is believed to be associated with the dispersion of repolarization and has been used as a non-invasive marker for predicting the risk of malignant cardiac arrhythmias and sudden cardiac death as numerous studies have shown. This review aims to provide up-to-date review on both experimental and simulation studies in elucidating possible mechanisms underlying the genesis of TWA at the cellular level, as well as the genesis of spatially concordant/discordant alternans at the tissue level, and their transition to cardiac arrhythmia. Recent progress and future perspectives in antiarrhythmic therapies associated with TWA are also discussed.

Introduction: Electrocardiograms (ECG) provide information about the electrical activity of the heart, which is useful for diagnosing abnormal cardiac functions such as arrhythmias. Recently, several algorithms based on advanced structures of neural networks have been proposed for auto-detecting cardiac arrhythmias, but their performance still needs to be further improved. This study aimed to develop an auto-detection algorithm, which extracts valid features from 12-lead ECG for classifying multiple types of cardiac states.Method: The proposed algorithm consists of the following components: (i) a preprocessing component that utilizes the frame blocking method to split an ECG recording into frames with a uniform length for all considered ECG recordings; and (ii) a binary classifier based on ResNet, which is combined with the attention-based bidirectional long-short term memory model.Result: The developed algorithm was trained and tested on ECG data of nine types of cardiac states, fulfilling a task of multi-label classification. It achieved an averaged F1-score and area under the curve at 0.908 and 0.974, respectively.Conclusion: The frame blocking and bidirectional long-short term memory model represented an improved algorithm compared with others in the literature for auto-detecting and classifying multi-types of cardiac abnormalities.

Pacemaking dysfunction (PD) may result in heart rhythm disorders, syncope or even death. Current treatment of PD using implanted electronic pacemakers has some limitations, such as finite battery life and the risk of repeated surgery. As such, the biological pacemaker has been proposed as a potential alternative to the electronic pacemaker for PD treatment. Experimentally and computationally, it has been shown that bio-engineered pacemaker cells can be generated from non-rhythmic ventricular myocytes (VMs) by knocking out genes related to the inward rectifier potassium channel current (IK1) or by overexpressing hyperpolarization-activated cyclic nucleotide gated channel genes responsible for the "funny" current (If). However, it is unclear if a bio-engineered pacemaker based on the modification of IK1- and If-related channels simultaneously would enhance the ability and stability of bio-engineered pacemaking action potentials. In this study, the possible mechanism(s) responsible for VMs to generate spontaneous pacemaking activity by regulating IK1 and If density were investigated by a computational approach. Our results showed that there was a reciprocal interaction between IK1 and If in ventricular pacemaker model. The effect of IK1 depression on generating ventricular pacemaker was mono-phasic while that of If augmentation was bi-phasic. A moderate increase of If promoted pacemaking activity but excessive increase of If resulted in a slowdown in the pacemaking rate and even an unstable pacemaking state. The dedicated interplay between IK1 and If in generating stable pacemaking and dysrhythmias was evaluated. Finally, a theoretical analysis in the IK1/If parameter space for generating pacemaking action potentials in different states was provided. In conclusion, to the best of our knowledge, this study provides a wide theoretical insight into understandings for generating stable and robust pacemaker cells from non-pacemaking VMs by the interplay of IK1 and If, which may be helpful in designing engineered biological pacemakers for application purposes.

Potassium is the predominant intracellular cation, with its extracellular concentrations maintained between 3. 5 and 5 mM. Among the different potassium disorders, hypokalaemia is a common clinical condition that increases the risk of life-threatening ventricular arrhythmias. This review aims to consolidate pre-clinical findings on the electrophysiological mechanisms underlying hypokalaemia-induced arrhythmogenicity. Both triggers and substrates are required for the induction and maintenance of ventricular arrhythmias. Triggered activity can arise from either early afterdepolarizations (EADs) or delayed afterdepolarizations (DADs). Action potential duration (APD) prolongation can predispose to EADs, whereas intracellular Ca2+ overload can cause both EADs and DADs. Substrates on the other hand can either be static or dynamic. Static substrates include action potential triangulation, non-uniform APD prolongation, abnormal transmural repolarization gradients, reduced conduction velocity (CV), shortened effective refractory period (ERP), reduced excitation wavelength (CV × ERP) and increased critical intervals for re-excitation (APD–ERP). In contrast, dynamic substrates comprise increased amplitude of APD alternans, steeper APD restitution gradients, transient reversal of transmural repolarization gradients and impaired depolarization-repolarization coupling. The following review article will summarize the molecular mechanisms that generate these electrophysiological abnormalities and subsequent arrhythmogenesis.

The function of the sinoatrial node (SAN), the pacemaker of the heart, declines with age, resulting in increased incidence of sinoatrial node dysfunction (SND) in older adults. The present study assesses potential ionic mechanisms underlying age associated SND. Two group studies have identified complex and various changes in some of membrane ion channels in aged rat SAN, the first group (Aging Study-1) indicates a considerable changes of gene expression with up-regulation of mRNA in ion channels of Cav1.2, Cav1.3 and KvLQT1, Kv4.2, and the Ca2+ handling proteins of SERCA2a, and down-regulation of Cav3.1, NCX, and HCN1 and the Ca2+-clock proteins of RYR2. The second group (Aging Study-2) suggests a different pattern of changes, including down regulation of Cav1.2, Cav1.3 and HCN4, and RYR2, and an increase of NCX and SERCA densities and proteins. Although both data sets shared a similar finding for some specific ion channels, such as down regulation of HCN4, NCX, and RYR2, there are contradictory changes for some other membrane ion channels, such as either up-regulation or down-regulation of Cav1.2, NCX and SERCA2a in aged rat SAN. The present study aims to test a hypothesis that age-related SND may arise from different ionic and molecular remodeling patterns. To test this hypothesis, a mathematical model of the electrical action potential of rat SAN myocytes was modified to simulate the functional impact of age-induced changes on membrane ion channels and intracellular Ca2+ handling as observed in Aging Study-1 and Aging Study-2. The role and relative importance of each individually remodeled ion channels and Ca2+-handling in the two datasets were evaluated. It was shown that the age-induced changes in ion channels and Ca2+-handling, based on either Aging Study-1 or Aging Study-2, produced similar bradycardic effects as manifested by a marked reduction in the heart rate (HR) that matched experimental observations. Further analysis showed that although the SND arose from an integrated action of all remodeling of ion channels and Ca2+-handling in both studies, it was the change to ICaL that played the most important influence.

This simulation study aims to investigate how the Calcium/calmodulin-dependent protein kinase II (CaMKII) overexpression and oxidation would influence the cardiac electrophysiological behavior and its arrhythmogenic mechanism in atria. A new-built CaMKII oxidation module and a refitted CaMKII overexpression module were integrated into a mouse atrial cell model for analyzing cardiac electrophysiological variations in action potential (AP) characteristics and intracellular Ca2+ cycling under different conditions. Simulation results showed that CaMKII overexpression significantly increased the phosphorylation level of its downstream target proteins, resulting in prolonged AP and smaller calcium transient amplitude, and impaired the Ca2+ cycling stability. These effects were exacerbated by extra reactive oxygen species, which oxidized CaMKII and led to continuous high CaMKII activation in both systolic and diastolic phases. Intracellular Ca2+ depletion and sustained delayed afterdepolarizations (DADs) were observed under co-existing CaMKII overexpression and oxidation, which could be effectively reversed by clamping the phosphorylation level of ryanodine receptor (RyR). We also found that the stability of RyR release highly depended on a delicate balance between the level of RyR phosphorylation and sarcoplasmic reticulum Ca2+ concentration, which was closely related to the genesis of DADs. We concluded that the CaMKII overexpression and oxidation have a synergistic role in increasing the activity of CaMKII, and the unstable RyR may be the key downstream target in the CaMKII arrhythmogenic mechanism. Our simulation provides detailed mechanistic insights into the arrhythmogenic effect of CaMKII overexpression and oxidation, which suggests CaMKII as a promising target in the therapy of atrial fibrillation.

A number of distinct electrophysiological mechanisms that modulate the myogenic spontaneous pacemaker activity in the sinoatrial node (SAN) of the mammalian heart have been investigated extensively. There is agreement that several (3 or 4) different transmembrane ionic current changes (referred to as the voltage clock) are involved; and that the resulting net current interacts with direct and indirect effects of changes in intracellular Ca2+ (the calcium clock). However, significant uncertainties, and important knowledge gaps, remain concerning the functional roles in SAN spontaneous pacing of many of the individual ion channel- or exchanger-mediated transmembrane current changes. We report results from patch clamp studies and mathematical modeling of the hyperpolarization-activated current, If, in the generation/modulation of the diastolic depolarization, or pacemaker potential, produced by individual myocytes that were enzymatically isolated from the adult mouse sinoatrial node (SAN). Amphotericin-mediated patch microelectrode recordings at 35 °C were made under control conditions and in the presence of 5 or 10 nM isoproterenol (ISO). These sets of results were complemented and integrated with mathematical modeling of the current changes that take place in the range of membrane potentials (−70 to −50 mV), which corresponds to the ‘pacemaker depolarization’ in the adult mouse SAN. Our results reveal a very small, but functionally important, approximately steady-state or time-independent current generated by residual activation of If channels that are expressed in these pacemaker myocytes. Recordings of the pacemaker depolarization and action potential, combined with measurements of changes in If, and the well-known increases in the L-type Ca2+ current, ICaL, demonstrated that ICaL activation, is essential for myogenic pacing. Moreover, after being enhanced (approximately 3-fold) by 5 or 10 nM ISO, ICaL contributes significantly to the positive chronotropic effect. Our mathematical model has been developed in an attempt to better understand the underlying mechanisms for the pacemaker depolarization and action potential in adult mouse SAN myocytes. After being updated with our new experimental data describing If, our simulations reveal a novel functional component of If in adult mouse SAN. Computational work carried out with this model also confirms that in the presence of ISO the residual activation of If and opening of ICaL channels combine to generate a net current change during the slow diastolic depolarization phase that is essential for the observed accelerated pacemaking rate of these SAN myocytes.

Marked age- and development- related differences have been observed in morphology and characteristics of action potentials (AP) of neonatal and adult sinoatrial node (SAN) cells. These may be attributable to a different set of ion channel interactions between the different ages. However, the underlying mechanism(s) have yet to be elucidated. The objective of this study was to determine the mechanisms underlying different spontaneous APs and heart rate between neonatal and adult SAN cells of the rabbit heart by biophysical modeling approaches. A mathematical model of neonatal rabbit SAN cells was developed by modifying the current densities and/or kinetics of ion channels and transporters in an adult cell model based on available experimental data obtained from neonatal SAN cells. The single cell models were then incorporated into a multi-cellular, two-dimensional model of the intact SAN-atrium to investigate the functional impact of altered ion channels during maturation on pacemaking electrical activities and their conduction at the tissue level. Effects of the neurotransmitter acetylcholine on the pacemaking activities in neonatal cells were also investigated and compared to those in the adult. Our results showed: (1) the differences in ion channel properties between neonatal and adult SAN cells are able to account for differences in their APs and the heart rate, providing mechanistic insight into understanding the reduced pacemaking rate of the rabbit sinoatrial node during postnatal development; (2) in the 2D model of the intact SAN-atria, it was shown that cellular changes during postnatal development impaired pacemaking activity through increasing the activation time and reducing the conduction velocity across the SAN; (3) the neonatal SAN model, with its faster beating rates, showed a greater sensitivity to parasympathetic modulation in response to acetylcholine than did the adult model. These results provide novel insights into the understanding of the cellular mechanisms underlying the differences in the cardiac pacemaking activities of the neonatal and adult SAN.

Biophysically detailed mathematical models of cardiac electrophysiology provide an alternative to experimental approaches for investigating possible ionic mechanisms underlying the genesis of electrical action potentials and their propagation through the heart. The aim of this study was to develop a biophysically detailed mathematical model of the action potentials of mouse atrial myocytes, a popular experimental model for elucidating molecular and cellular mechanisms of arrhythmogenesis. Based on experimental data from isolated mouse atrial cardiomyocytes, a set of mathematical equations for describing the biophysical properties of membrane ion channel currents, intracellular Ca2+ handling, and Ca2+-calmodulin activated protein kinase II and β-adrenergic signaling pathways were developed. Wherever possible, membrane ion channel currents were modeled using Markov chain formalisms, allowing detailed representation of channel kinetics. The model also considered heterogeneous electrophysiological properties between the left and the right atrial cardiomyocytes. The developed model was validated by its ability to reproduce the characteristics of action potentials and Ca2+ transients, matching quantitatively to experimental data. Using the model, the functional roles of four K+ channel currents in atrial action potential were evaluated by channel block simulations, results of which were quantitatively in agreement with existent experimental data. To conclude, this newly developed model of mouse atrial cardiomyocytes provides a powerful tool for investigating possible ion channel mechanisms of atrial electrical activity at the cellular level and can be further used to investigate mechanisms underlying atrial arrhythmogenesis.

Heart failure (HF) is associated with an increased propensity for atrial fibrillation (AF), causing higher mortality than AF or HF alone. It is hypothesized that HF-induced remodelling of atrial cellular and tissue properties promotes the genesis of atrial action potential (AP) alternans and conduction alternans that perpetuate AF. However, the mechanism underlying the increased susceptibility to atrial alternans in HF remains incompletely elucidated. In this study, we investigated the effects of how HF-induced atrial cellular electrophysiological (with prolonged AP duration) and tissue structural (reduced cell-to-cell coupling caused by atrial fibrosis) remodelling can have an effect on the generation of atrial AP alternans and their conduction at the cellular and one-dimensional (1D) tissue levels. Simulation results showed that HF-induced atrial electrical remodelling prolonged AP duration, which was accompanied by an increased sarcoplasmic reticulum (SR) Ca2+ content and Ca2+ transient amplitude. Further analysis demonstrated that HF-induced atrial electrical remodelling increased susceptibility to atrial alternans mainly due to the increased sarcoplasmic reticulum Ca2+-ATPase (SERCA) Ca2+ reuptake, modulated by increased phospholamban (PLB) phosphorylation, and the decreased transient outward K+ current (Ito). The underlying mechanism has been suggested that the increased SR Ca2+ content and prolonged AP did not fully recover to their previous levels at the end of diastole, resulting in a smaller SR Ca2+ release and AP in the next beat. These produced Ca2+ transient alternans and AP alternans, and further caused AP alternans and Ca2+ transient alternans through Ca2+→AP coupling and AP→Ca2+ coupling, respectively. Simulation of a 1D tissue model showed that the combined action of HF-induced ion channel remodelling and a decrease in cell-to-cell coupling due to fibrosis increased the heart tissue's susceptibility to the formation of spatially discordant alternans, resulting in an increased functional AP propagation dispersion, which is pro-arrhythmic. These findings provide insights into how HF promotes atrial arrhythmia in association with atrial alternans.

Hydrogen sulfide (H2S), an ambient air pollutant, has been reported to increase cardiac events in patients with cardiovascular diseases, but the underlying mechanisms remain not elucidated. This study investigated the pro-arrhythmic effects of H2S in healthy and ischemic conditions. Experimental data of H2S effects on ionic channels (including the L-type Ca2+ channel and ATP-sensitive K+ channel) were incorporated into a virtual heart model to evaluate their integral action on cardiac arrhythmogenesis. It was shown that H2S depressed cellular excitability, abbreviated action potential duration, and augmented tissue’s transmural dispersion of repolarization, resulting in an increase in tissue susceptibility to initiation and maintenance of reentry. The observed effects of H2S on cardiac excitation are more remarkable in the ischemic condition than in the healthy condition. This study provides mechanistic insights into the pro-arrhythmic effects of air pollution (H2S), especially in the case with extant ischemic conditions.

Abstract Cardiovascular diseases are associated with high morbidity and mortality. However, it is still a challenge to diagnose them accurately and efficiently. Electrocardiogram (ECG), a bioelectrical signal of the heart, provides crucial information about the dynamical functions of the heart, playing an important role in cardiac diagnosis. As the QRS complex in ECG is associated with ventricular depolarization, therefore, accurate QRS detection is vital for interpreting ECG features. In this paper, we proposed a real-time, accurate, and effective algorithm for QRS detection. In the algorithm, a proposed preprocessor with a band-pass filter was first applied to remove baseline wander and power-line interference from the signal. After denoising, a method combining K-Nearest Neighbor (KNN) and Particle Swarm Optimization (PSO) was used for accurate QRS detection in ECGs with different morphologies. The proposed algorithm was tested and validated using 48 ECG records from MIT-BIH arrhythmia database (MITDB), achieved a high averaged detection accuracy, sensitivity and positive predictivity of 99.43, 99.69, and 99.72%, respectively, indicating a notable improvement to extant algorithms as reported in literatures.

Automatic electrocardiogram (ECG) classification is a promising technology for the early screening and follow-up management of cardiovascular diseases. It is, by nature, a multi-label classification task owing to the coexistence of different kinds of diseases, and is challenging due to the large number of possible label combinations and the imbalance among categories. Furthermore, the task of multi-label ECG classification is cost-sensitive, a fact that has usually been ignored in previous studies on the development of the model. To address these problems, in this work, we propose a novel deep learning model–based learning framework and a thresholding method, namely category imbalance and cost-sensitive thresholding (CICST), to incorporate prior knowledge about classification costs and the characteristic of category imbalance in designing a multi-label ECG classifier. The learning framework combines a residual convolutional network with a class-wise attention mechanism. We evaluate our method with a cost-sensitive metric on multiple realistic datasets. The results show that CICST achieved a cost-sensitive metric score of 0.641 ± 0.009 in a 5-fold cross-validation, outperforming other commonly used thresholding methods, including rank-based thresholding, proportion-based thresholding, and fixed thresholding. This demonstrates that, by taking into account the category imbalance and predefined cost information, our approach is effective in improving the performance and practicability of multi-label ECG classification models.

Atrial fibrillation (AF) is a common arrhythmia. Better prevention and treatment of AF are needed to reduce AF-associated morbidity and mortality. Several major mechanisms cause AF in patients, including genetic predispositions to AF development. Genome-wide association studies have identified a number of genetic variants in association with AF populations, with the strongest hits clustering on chromosome 4q25, close to the gene for the homeobox transcription PITX2. Because of the inherent complexity of the human heart, experimental and basic research is insufficient for understanding the functional impacts of PITX2 variants on AF. Linking PITX2 properties to ion channels, cells, tissues, atriums and the whole heart, computational models provide a supplementary tool for achieving a quantitative understanding of the functional role of PITX2 in remodelling atrial structure and function to predispose to AF. It is hoped that computational approaches incorporating all we know about PITX2-related structural and electrical remodelling would provide better understanding into its proarrhythmic effects leading to development of improved anti-AF therapies. In the present review, we discuss advances in atrial modelling and focus on the mechanistic links between PITX2 and AF. Challenges in applying models for improving patient health are described, as well as a summary of future perspectives.

Abstract Short QT syndrome (SQTS) is a rare condition characterized by abnormally ‘short’ QT intervals on the ECG and increased susceptibility to cardiac arrhythmias and sudden death. This simulation study investigated arrhythmia dynamics in multi-scale human ventricle models associated with the SQT2-related V307L KCNQ1 ‘gain-of-function’ mutation, which increases slow-delayed rectifier potassium current (IKs). A Markov chain (MC) model recapitulating wild type (WT) and V307L mutant IKs kinetics was incorporated into a model of the human ventricular action potential (AP) for investigation of QT interval changes and arrhythmia substrates. In addition, the degree of simulated IKs inhibition necessary to normalize the QT interval and terminate re-entry in SQT2 conditions was quantified. The developed MC model accurately reproduced AP shortening and reduced effective refractory period associated with altered IKs kinetics in homozygous (V307L) and heterozygous (WT-V307L) mutation conditions, which increased the lifespan and dominant frequency of re-entry in 3D human ventricle models. IKs reductions of 58% and 65% were sufficient to terminate re-entry in WT-V307L and V307L conditions, respectively. This study further substantiates a causal link between the V307L KCNQ1 mutation and pro-arrhythmia in human ventricles, and establishes partial inhibition of IKs as a potential anti-arrhythmic strategy in SQT2.

Abstract Cardiac arrhythmias and conduction disturbances are accompanied by structural remodelling of the specialised cardiomyocytes known collectively as the cardiac conduction system. Here, using contrast enhanced micro-computed tomography, we present, in attitudinally appropriate fashion, the first 3-dimensional representations of the cardiac conduction system within the intact human heart. We show that cardiomyocyte orientation can be extracted from these datasets at spatial resolutions approaching the single cell. These data show that commonly accepted anatomical representations are oversimplified. We have incorporated the high-resolution anatomical data into mathematical simulations of cardiac electrical depolarisation. The data presented should have multidisciplinary impact. Since the rate of depolarisation is dictated by cardiac microstructure, and the precise orientation of the cardiomyocytes, our data should improve the fidelity of mathematical models. By showing the precise 3-dimensional relationships between the cardiac conduction system and surrounding structures, we provide new insights relevant to valvar replacement surgery and ablation therapies. We also offer a practical method for investigation of remodelling in disease, and thus, virtual pathology and archiving. Such data presented as 3D images or 3D printed models, will inform discussions between medical teams and their patients, and aid the education of medical and surgical trainees.

Abstract Background Short QT syndrome (SQTS) is a newly identified clinical disorder associated with atrial and/or ventricular arrhythmias and increased risk of sudden cardiac death (SCD). The SQTS variant 3 is linked to D172N mutation to the KCNJ2 gene that causes a gain-of-function to the inward rectifier potassium channel current (I K1), which shortens the ventricular action potential duration (APD) and effective refractory period (ERP). Pro-arrhythmogenic effects of SQTS have been characterized, but less is known about the possible pharmacological treatment of SQTS. Therefore, in this study, we used computational modeling to assess the effects of amiodarone, class III anti-arrhythmic agent, on human ventricular electrophysiology in SQT3. Methods The ten Tusscher et al. model for the human ventricular action potentials (APs) was modified to incorporate I K1 formulations based on experimental data of Kir2.1 channels (including WT, WT-D172N and D172N conditions). The modified cell model was then implemented to construct one-dimensional (1D) and 2D tissue models. The blocking effects of amiodarone on ionic currents were modeled using IC50 and Hill coefficient values from literatures. Effects of amiodarone on APD, ERP and pseudo-ECG traces were computed. Effects of the drug on the temporal and spatial vulnerability of ventricular tissue to genesis and maintenance of re-entry were measured, as well as on the dynamic behavior of re-entry. Results Amiodarone prolonged the ventricular cell APD and decreased the maximal voltage heterogeneity (δV) among three difference cells types across transmural ventricular wall, leading to a decreased transmural heterogeneity of APD along a 1D model of ventricular transmural strand. Amiodarone increased cellular ERP, prolonged QT interval and decreased the T-wave amplitude. It reduced tissue’s temporal susceptibility to the initiation of re-entry and increased the minimum substrate size necessary to sustain re-entry in the 2D tissue. Conclusions At the therapeutic-relevant concentration of amiodarone, the APD and ERP at the single cell level were increased significantly. The QT interval in pseudo-ECG was prolonged and the re-entry in tissue was prevented. This study provides further evidence that amiodarone may be a potential pharmacological agent for preventing arrhythmogenesis for SQT3 patients.

Abstract Background Electrophysiological behavior is of great importance for analyzing the cardiac functional mechanism under cardiac physiological and pathological condition. Due to the complexity of cardiac structure and biophysiological function, visualization of a cardiac electrophysiological model compositively is still a challenge. The lack of either modality of the whole organ structure or cardiac electrophysiological behaviors makes analysis of the intricate mechanisms of cardiac dynamic function a difficult task. This study aims at exploring 3D conduction of stimulus and electrical excitation reactivity on the level of organ with the authentic fine cardiac anatomy structure. Methods In this paper, a cardiac electrical excitation propagation model is established based on the human cardiac cross-sectional data to explore detailed cardiac electrical activities. A novel biophysical merging visualization method is then presented for biophysical integration of cardiac anatomy and electrophysiological properties in the form of the merging optical model, which provides the corresponding position, spatial relationship and the whole process in 3D space with the context of anatomical structure for representing the biophysical detailed electrophysiological activity. Results The visualization result present the action potential propagation of the left ventricle within the excitation cycle with the authentic fine cardiac organ anatomy. In the visualized images, all vital organs are identified and distinguished without ambiguity. The three dimensional spatial position, relation and the process of cardiac excitation conduction and re-entry propagation in the anatomical structure during the phase of depolarization and repolarization is also shown in the result images, which exhibits the performance of a more detailed biophysical understanding of the electrophysiological kinetics of human heart in vivo. Conclusions Results suggest that the proposed merging optical model can merge cardiac electrophysiological activity with the anatomy structure. By specifying the respective opacity for the cardiac anatomy structure and the electrophysiological model in the merging attenuation function, the visualized images can provide an in-depth insight into the biophysical detailed cardiac functioning phenomena and the corresponding electrophysiological behavior mechanism, which is helpful for further speculating cardiac physiological and pathological responses and is fundamental to the cardiac research and clinical diagnoses.

Functional analysis has shown that the p.Met207Val mutation was linked to atrial fibrillation and caused an increase in transactivation activity of PITX2c, which caused changes in mRNA synthesis related to ionic channels and intercellular electrical coupling. We assumed that these changes were quantitatively translated to the functional level. This study aimed to investigate the potential impact of the PITX2c p.Met207Val mutation on atrial electrical activity through multiscale computational models. The well-known Courtemanche-Ramirez-Nattel (CRN) model of human atrial cell action potentials (APs) was modified to incorporate experimental data on the expected p.Met207Val mutation-induced changes in ionic channel currents (INaL, IKs, and IKr) and intercellular electrical coupling. The cell models for wild-type (WT), heterozygous (Mutant/Wild type, MT/WT), and homozygous (Mutant, MT) PITX2c cases were incorporated into homogeneous multicellular 1D and 2D tissue models. Effects of this mutation-induced remodeling were quantified as changes in AP profile, AP duration (APD) restitution, conduction velocity (CV) restitution and wavelength (WL). Temporal and spatial vulnerabilities of atrial tissue to the genesis of reentry were computed. Dynamic behaviors of re-entrant excitation waves (Life span, tip trajectory and dominant frequency) in a homogeneous 2D tissue model were characterized. Our results suggest that the PITX2c p.Met207Val mutation abbreviated atrial APD and flattened APD restitution curves. It reduced atrial CV and WL that facilitated the conduction of high rate atrial excitation waves. It increased the tissue's temporal vulnerability by increasing the vulnerable window for initiating reentry and increased the tissue spatial vulnerability by reducing the substrate size necessary to sustain reentry. In the 2D models, the mutation also stabilized and accelerated re-entrant excitation waves, leading to rapid and sustained reentry. In conclusion, electrical and structural remodeling arising from the PITX2c p.Met207Val mutation may increase atrial susceptibility to arrhythmia due to shortened APD, reduced CV and increased tissue vulnerability, which, in combination, facilitate initiation and maintenance of re-entrant excitation waves.

Electrocardiography provides some information useful for ischemic diagnosis. However, more recently there has been substantial growth in the area of ECG imaging, which by solving the inverse problem of electrocardiography aims to produce high-resolution mapping of the electrical and magnetic dynamics of the heart. Most inverse studies use the full resolution of the body surface potential (BSP) to reconstruct the epicardial potentials, however using a limited number of torso electrodes to interpolate the BSP is more clinically relevant and has an important effect on the reconstruction which must be quantified. A circular ischemic lesion on the right ventricle lateral wall 27 mm in radius is reconstructed using three Tikhonov methods along with 6 different electrode configurations ranging from 32 leads to 1,024 leads. The 2nd order Tikhonov solution performed the most accurately (~80% lesion identified) followed by the 1st (~50% lesion identified) and then the 0 order Tikhonov solution performed the worst with a maximum of ~30% lesion identified regardless of how many leads were used. With an increasing number of leads the solution produces less error, and the error becomes more localised around the lesion for all three regularisation methods. In noisy conditions, the relative performance gap of the 1st and 2nd order Tikhonov solutions was reduced, and determining an accurate regularisation parameter became relatively more difficult. Lesions located on the left ventricle walls were also able to be identified but comparatively to the right ventricle lateral wall performed marginally worse with lesions located on the interventricular septum being able to be indicated by the reconstructions but not successfully identified against the error. The quality of reconstruction was found to decrease as the lesion radius decreased, with a lesion radius of 512 torso electrodes.

Short QT syndrome variant 1 (SQT1) arises due to gain-of-function mutations to the human Ether-à-go-go-Related Gene (hERG), which encodes the α subunit of channels carrying rapid delayed rectifier potassium current, IKr. In addition to QT interval shortening and ventricular arrhythmias, SQT1 is associated with increased risk of atrial fibrillation (AF), which is often the only clinical presentation. However, the underlying basis of AF and its pharmacological treatment remain incompletely understood in the context of SQT1. In this study, computational modeling was used to investigate mechanisms of human atrial arrhythmogenesis consequent to a SQT1 mutation, as well as pharmacotherapeutic effects of selected class I drugs–disopyramide, quinidine, and propafenone. A Markov chain formulation describing wild type (WT) and N588K-hERG mutant IKr was incorporated into a contemporary human atrial action potential (AP) model, which was integrated into one-dimensional (1D) tissue strands, idealized 2D sheets, and a 3D heterogeneous, anatomical human atria model. Multi-channel pharmacological effects of disopyramide, quinidine, and propafenone, including binding kinetics for IKr/hERG and sodium current, INa, were considered. Heterozygous and homozygous formulations of the N588K-hERG mutation shortened the AP duration (APD) by 53 and 86 ms, respectively, which abbreviated the effective refractory period (ERP) and excitation wavelength in tissue, increasing the lifespan and dominant frequency (DF) of scroll waves in the 3D anatomical human atria. At the concentrations tested in this study, quinidine most effectively prolonged the APD and ERP in the setting of SQT1, followed by disopyramide and propafenone. In 2D simulations, disopyramide and quinidine promoted re-entry termination by increasing the re-entry wavelength, whereas propafenone induced secondary waves which destabilized the re-entrant circuit. In 3D simulations, the DF of re-entry was reduced in a dose-dependent manner for disopyramide and quinidine, and propafenone to a lesser extent. All of the anti-arrhythmic agents promoted pharmacological conversion, most frequently terminating re-entry in the order quinidine > propafenone = disopyramide. Our findings provide further insight into mechanisms of SQT1-related AF and a rational basis for the pursuit of combined IKr and INa block based pharmacological strategies in the treatment of SQT1-linked AF.

Robust, spontaneous pacemaker activity originating in the sinoatrial node (SAN) of the heart is essential for cardiovascular function. Anatomical, electrophysiological, and molecular methods as well as mathematical modeling approaches have quite thoroughly characterized the transmembrane fluxes of Na+, K+ and Ca2+ that produce SAN action potentials (AP) and ‘pacemaker depolarizations’ in a number of different in vitro adult mammalian heart preparations. Possible ionic mechanisms that are responsible for SAN primary pacemaker activity are described in terms of: (i) a Ca2+-regulated mechanism based on a requirement for phasic release of Ca2+ from intracellular stores and activation of an inward current-mediated by Na+/Ca2+ exchange; (ii) time- and voltage-dependent activation of Na+ or Ca2+ currents, as well as a cyclic nucleotide-activated current, If; and/or (iii) a combination of (i) and (ii). Electrophysiological studies of single spontaneously active SAN myocytes in both adult mouse and rabbit hearts consistently reveal significant expression of a rapidly activating time- and voltage-dependent K+ current, often denoted IKr, that is selectively expressed in the leading or primary pacemaker region of the adult mouse SAN. The main goal of the present study was to examine by combined experimental and simulation approaches the functional or physiological roles of this K+ current in the pacemaker activity. Our patch clamp data of mouse SAN myocytes on the effects of a pharmacological blocker, E4031, revealed that a rapidly activating K+ current is essential for action potential (AP) repolarization, and its deactivation during the pacemaker potential contributes a small but significant component to the pacemaker depolarization. Mathematical simulations using a murine SAN AP model confirm that well known biophysical properties of a delayed rectifier K+ current can contribute to its role in generating spontaneous myogenic activity.

Electrical remodelling as a result of homeodomain transcription factor 2 (Pitx2)-dependent gene regulation was linked to atrial fibrillation (AF) and AF patients with single nucleotide polymorphisms at chromosome 4q25 responded favorably to class I antiarrhythmic drugs (AADs). The possible reasons behind this remain elusive. The purpose of this study was to assess the efficacy of the AADs disopyramide, quinidine, and propafenone on human atrial arrhythmias mediated by Pitx2-induced remodelling, from a single cell to the tissue level, using drug binding models with multi-channel pharmacology. Experimentally calibrated populations of human atrial action po-tential (AP) models in both sinus rhythm (SR) and Pitx2-induced AF conditions were constructed by using two distinct models to represent morphological subtypes of AP. Multi-channel pharmaco-logical effects of disopyramide, quinidine, and propafenone on ionic currents were considered. Simulated results showed that Pitx2-induced remodelling increased maximum upstroke velocity (dVdtmax), and decreased AP duration (APD), conduction velocity (CV), and wavelength (WL). At the concentrations tested in this study, these AADs decreased dVdtmax and CV and prolonged APD in the setting of Pitx2-induced AF. Our findings of alterations in WL indicated that disopyramide may be more effective against Pitx2-induced AF than propafenone and quinidine by prolonging WL.