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A computerized tool and interdisciplinary care were implemented to develop a novel model for older patients with delirium in the emergency department (ED).We developed a computerized tool using a delirium triage screen and brief confusion assessment in the hospital information system, performed education for the healthcare providers, and developed a continuous care protocol. Comparisons for outcomes between pre- and post-intervention periods were performed.Compared with the pre-intervention period, patients in the post-intervention period had shorter hospitalization stay, lower expenditure of hospitalization, more likely to return home, lower ED revisits of ≤ 3 days, re-hospitalization of ≤ 14 days, and mortality of ≤ 1 month. All mentioned differences were not statistically significant.A novel model was successfully developed for delirium management in older patients in the ED. Outcome differences were not significant; however, the result is promising, which gives us an important reference in the future.

Drug isomers may differ in their proarrhythmia risk. An interesting example is the drug sotalol, an antiarrhythmic drug comprising d- and l- enantiomers that both block the hERG cardiac potassium channel and confer differing degrees of proarrhythmic risk. We developed a multi-scale in silico pipeline focusing on hERG channel - drug interactions and used it to probe and predict the mechanisms of pro-arrhythmia risks of the two enantiomers of sotalol. Molecular dynamics (MD) simulations predicted comparable hERG channel binding affinities for d- and l-sotalol, which were validated with electrophysiology experiments. MD derived thermodynamic and kinetic parameters were used to build multi-scale functional computational models of cardiac electrophysiology at the cell and tissue scales. Functional models were used to predict inactivated state binding affinities to recapitulate electrocardiogram (ECG) QT interval prolongation observed in clinical data. Our study demonstrates how modeling and simulation can be applied to predict drug effects from the atom to the rhythm for dl-sotalol and also increased proarrhythmia proclivity of d- vs. l-sotalol when accounting for stereospecific beta-adrenergic receptor blocking.

Home healthcare (HHC) provides continuous care for disabled patients. However, HHC referral after the emergency department (ED) discharge remains unclear. Thus, this study aimed its clarification.A computer-assisted HHC referral by interdisciplinary collaboration among emergency physicians, case managers, nurse practitioners, geriatricians, and HHC nurses was built in a tertiary medical center in Taiwan. Patients who had HHC referrals after ED discharge between February 1, 2020 and September 31, 2020, were recruited into the study. A non-ED HHC cohort who had HHC referrals after hospitalization from the ED was also identified. Comparison for clinical characteristics and uses of medical resources was performed between ED HHC and non-ED HHC cohorts.The model was successfully implemented. In total, 34 patients with ED HHC and 40 patients with non-ED HHC were recruited into the study. The female proportion was 61.8% and 67.5%, and the mean age was 81.5 and 83.7 years in ED HHC and non-ED HHC cohorts, respectively. No significant difference was found in sex, age, underlying comorbidities, and ED diagnoses between the two cohorts. The ED HHC cohort had a lower median total medical expenditure within 3 months (34,030.0 vs. 56,624.0 New Taiwan Dollars, p = 0.021) compared with the non-ED HHC cohort. Compared to the non-ED HHC cohort, the ED HHC cohort had a lower ≤ 1 month ED visit, ≤ 6 months ED visit, and ≤ 3 months hospitalization; however, differences were not significant.An innovative ED HHC model was successfully implemented. Further studies with more patients are warranted to investigate the impact.

It is imperative to develop better approaches to predict how antiarrhythmic drugs with multiple interactions and targets may alter the overall electrical and/or mechanical function of the heart. Safety Pharmacology studies have provided new insights into the multi-target effects of many different classes of drugs and have been aided by the addition of robust new in vitro and in silico technology. The primary focus of Safety Pharmacology studies has been to determine the risk profile of drugs and drug candidates by assessing their effects on repolarization of the cardiac action potential. However, for decades experimental and clinical studies have described substantial and potentially detrimental effects of Na+ channel blockers in addition to their well-known conduction slowing effects. One such side effect, associated with administration of some Na+ channel blocking drugs is negative inotropy. This reduces the pumping function of the heart, thereby resulting in hypotension. Flecainide is a well-known example of a Na+ channel blocking drug, that exhibits strong rate-dependent block of INa and may cause negative cardiac inotropy. While the phenomenon of Na+ channel suppression and resulting negative inotropy is well described, the mechanism(s) underlying this effect are not. Here, we set out to use a modeling and simulation approach to reveal plausible mechanisms that could explain the negative inotropic effect of flecainide. We utilized the Grandi-Bers model [1] of the cardiac ventricular myocyte because of its robust descriptions of ion homeostasis in order to characterize and resolve the relative effects of QRS widening, flecainide off-target effects and changes in intracellular Ca2+ and Na+ homeostasis. The results of our investigations and predictions reconcile multiple data sets and illustrate how multiple mechanisms may play a contributing role in the flecainide induced negative cardiac inotropic effect.

Torsade de Pointes (TdP), a rare but lethal ventricular arrhythmia, is a toxic side effect of many drugs. To assess TdP risk, safety regulatory guidelines require quantification of hERG channel block in vitro and QT interval prolongation in vivo for all new therapeutic compounds. Unfortunately, these have proven to be poor predictors of torsadogenic risk, and are likely to have prevented safe compounds from reaching clinical phases. While this has stimulated numerous efforts to define new paradigms for cardiac safety, none of the recently developed strategies accounts for patient conditions. In particular, despite being a well-established independent risk factor for TdP, female sex is vastly underrepresented in both basic research and clinical studies, and thus current TdP metrics are likely biased toward the male sex. Here, we apply statistical learning to synthetic data, generated by simulating drug effects on cardiac myocyte models capturing male and female electrophysiology, to develop new sex-specific classification frameworks for TdP risk. We show that (1) TdP classifiers require different features in females vs. males; (2) malebased classifiers perform more poorly when applied to female data; (3) female-based classifier performance is largely unaffected by acute effects of hormones (i.e., during various phases of the menstrual cycle). Notably, when predicting TdP risk of intermediate drugs on female simulated data, male-biased predictive models consistently underestimate TdP risk in women. Therefore, we conclude that pipelines for preclinical cardiotoxicity risk assessment should consider sex as a key variable to avoid potentially lifethreatening consequences for the female population.

The development of induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs) has been a critical in vitro advance in the study of patient-specific physiology, pathophysiology, and pharmacology. We designed a new deep learning multitask network approach intended to address the low throughput, high variability, and immature phenotype of the iPSC-CM platform. The rationale for combining translation and classification tasks is because the most likely application of the deep learning technology we describe here is to translate iPSC-CMs following application of a perturbation. The deep learning network was trained using simulated action potential (AP) data and applied to classify cells into the drug-free and drugged categories and to predict the impact of electrophysiological perturbation across the continuum of aging from the immature iPSC-CMs to the adult ventricular myocytes. The phase of the AP extremely sensitive to perturbation due to a steep rise of the membrane resistance was found to contain the key information required for successful network multitasking. We also demonstrated successful translation of both experimental and simulated iPSC-CM AP data validating our network by prediction of experimental drug-induced effects on adult cardiomyocyte APs by the latter.

The development of induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs) has been a critical in vitro advance in the study of patient-specific physiology, pathophysiology and pharmacology. We designed a new deep learning multitask network approach intended to address the low throughput, high variability and immature phenotype of the iPSC-CM platform. It was trained using simulated action potential (AP) data and applied to classify cells into the drug-free and drugged categories and to predict the impact of electrophysiological perturbation across the continuum of aging from the immature iPSC-CMs to the adult ventricular myocytes. The phase of the AP extremely sensitive to perturbation due to a steep rise of the membrane resistance was found to contain the key information required for successful network multitasking. We also demonstrated successful translation of both experimental and simulated iPSC-CM AP data validating our network by prediction of experimental drug-induced effects on adult cardiomyocyte APs by the latter.

[EN] Preclinical assessment of drug-induced proarrhythmicity is typically evaluated by the potency of the drug to block the potassium human ether-a-go-go-related gene (hERG) channels, which is currently quantified by the IC50. However, channel block depends on the experimental conditions. Our aim is to improve the evaluation of the blocking potency of drugs by designing experimental stimulation protocols to measure the IC50 that will help to decide whether the IC50 is representative enough. We used the state-of-the-art mathematical models of the cardiac electrophysiological activity to design three stimulation protocols that enhance the differences in the probabilities to occupy a certain conformational state of the channel and, therefore, the potential differences in the blocking effects of a compound. We simulated an extensive set of 144 in silico IKr blockers with different kinetics and affinities to conformational states of the channel and we also experimentally validated our key predictions. Our results show that the IC50 protocol dependency relied on the tested compounds. Some of them showed no differences or small differences on the IC50 value, which suggests that the IC50 could be a good indicator of the blocking potency in these cases. However, others provided highly protocol dependent IC50 values, which could differ by even 2 orders of magnitude. Moreover, the protocols yielding the maximum IC50 and minimum IC50 depended on the drug, which complicates the definition of a "standard" protocol to minimize the influence of the stimulation protocol on the IC50 measurement in safety pharmacology. As a conclusion, we propose the adoption of our threeprotocol IC50 assay to estimate the potency to block hERG in vitro. If the IC50 values obtained for a compound are similar, then the IC50 could be used as an indicator of its blocking potency, otherwise kinetics and state-dependent binding properties should be accounted., This work was partially supported by the Direccion General de Polit ' ica Cientifica de la Generalitat Valenciana (PROMETEU2016/088), Ministerio de Economia y Competitividad, and Fondo Europeo de Desarrollo Regional (FEDER) DPI2015-69125-R (MINECO/FEDER, UE) as well as Ayuda a Primeros Proyectos de Investigacion (PAID-06-18), Vicerrectorado de Investigacion. Innovacion y Transferencia de la Universitat Politecnica de Valencia (UPV), Valencia, Spain. The research was also supported by the National Institutes of Health 1R01HL128537-01A1

T cell receptor stimulation initiates a cascade of reactions that cause an increase in intracellular calcium (Ca2+) concentration mediated through inositol 1,4,5-trisphosphate (IP3). To understand the basic mechanisms by which the immune response in T cells is activated, it is useful to understand the signaling pathways that contain important targets for drugs in a quantitative fashion. A computational model helps us to understand how the selected elements in the pathways interact with each other, and which component plays the crucial role in systems. We have developed a mathematical model to explore the mechanism for controlling transcription factor activity, which regulates gene expression, by the modulation of calcium signaling triggered during T cell activation. The model simulates the activation and modulation of Ca2+ release-activated Ca2+ (CRAC) channels by mitochondrial dynamics and depletion of endoplasmic reticulum (ER) store, and also includes membrane potential in T-cells. The model simulates the experimental finding that increases in Ca2+ current enhances the activation of transcription factors and the Ca2+ influx through CRAC is also essential for the NFAT and NFκB activation. The model also suggests that plasma membrane Ca2+-ATPase (PMCA) controls a majority of the extrusion of Ca2+ and modulates the activation of CRAC channels. Furthermore, the model simulations explain how the complex interaction of the endoplasmic reticulum, membrane potential, mitochondria, and ion channels such as CRAC channels control T cell activation., Biochemistry; Bioinformatics; Immunology; Mathematical Biology; Biophysics; Systems Biology; Immune Response; Immune System; calcium signaling; Mathematical Modeling; T cell activation; NFAT; JNK; NFkappaB

Preclinical assessment of drug-induced proarrhythmicity is typically evaluated by the potency of the drug to block the potassium human ether-à-go-go-related gene (hERG) channels, which is currently quantified by the IC50. However, channel block depends on the experimental conditions. Our aim is to improve the evaluation of the blocking potency of drugs by designing experimental stimulation protocols to measure the IC50 that will help to decide whether the IC50 is representative enough. We used the state-of-the-art mathematical models of the cardiac electrophysiological activity to design three stimulation protocols that enhance the differences in the probabilities to occupy a certain conformational state of the channel and, therefore, the potential differences in the blocking effects of a compound. We simulated an extensive set of 144 in silico IKr blockers with different kinetics and affinities to conformational states of the channel and we also experimentally validated our key predictions. Our results show that the IC50 protocol dependency relied on the tested compounds. Some of them showed no differences or small differences on the IC50 value, which suggests that the IC50 could be a good indicator of the blocking potency in these cases. However, others provided highly protocol dependent IC50 values, which could differ by even 2 orders of magnitude. Moreover, the protocols yielding the maximum IC50 and minimum IC50 depended on the drug, which complicates the definition of a “standard” protocol to minimize the influence of the stimulation protocol on the IC50 measurement in safety pharmacology. As a conclusion, we propose the adoption of our three-protocol IC50 assay to estimate the potency to block hERG in vitro. If the IC50 values obtained for a compound are similar, then the IC50 could be used as an indicator of its blocking potency, otherwise kinetics and state-dependent binding properties should be accounted.

Rationale: Drug-induced proarrhythmia is so tightly associated with prolongation of the QT interval that QT prolongation is an accepted surrogate marker for arrhythmia. But QT interval is too sensitive a marker and not selective, resulting in many useful drugs eliminated in drug discovery. Objective: To predict the impact of a drug from the drug chemistry on the cardiac rhythm. Methods and Results: In a new linkage, we connected atomistic scale information to protein, cell, and tissue scales by predicting drug-binding affinities and rates from simulation of ion channel and drug structure interactions and then used these values to model drug effects on the hERG channel. Model components were integrated into predictive models at the cell and tissue scales to expose fundamental arrhythmia vulnerability mechanisms and complex interactions underlying emergent behaviors. Human clinical data were used for model framework validation and showed excellent agreement, demonstrating feasibility of a new approach for cardiotoxicity prediction. Conclusions: We present a multiscale model framework to predict electrotoxicity in the heart from the atom to the rhythm. Novel mechanistic insights emerged at all scales of the system, from the specific nature of proarrhythmic drug interaction with the hERG channel, to the fundamental cellular and tissue-level arrhythmia mechanisms. Applications of machine learning indicate necessary and sufficient parameters that predict arrhythmia vulnerability. We expect that the model framework may be expanded to make an impact in drug discovery, drug safety screening for a variety of compounds and targets, and in a variety of regulatory processes.

Author(s): Yang, Pei-Chi; Perissinotti, Laura L; Lopez-Redondo, Fernando; Wang, Yibo; DeMarco, Kevin R; Jeng, Mao-Tsuen; Vorobyov, Igor; Harvey, Robert D; Kurokawa, Junko; Noskov, Sergei Y; Clancy, Colleen E | Abstract: KEY POINTS:This study represents a first step toward predicting mechanisms of sex-based arrhythmias that may lead to important developments in risk stratification and may inform future drug design and screening. We undertook simulations to reveal the conditions (i.e. pacing, drugs, sympathetic stimulation) required for triggering and sustaining reentrant arrhythmias. Using the recently solved cryo-EM structure for the Eag-family channel as a template, we revealed potential interactions of oestrogen with the pore loop hERG mutation (G604S). Molecular models suggest that oestrogen and dofetilide blockade can concur simultaneously in the hERG channel pore. ABSTRACT:Female sex is a risk factor for inherited and acquired long-QT associated torsade de pointes (TdP) arrhythmias, and sympathetic discharge is a major factor in triggering TdP in female long-QT syndrome patients. We used a combined experimental and computational approach to predict 'the perfect storm' of hormone concentration, IKr block and sympathetic stimulation that induces arrhythmia in females with inherited and acquired long-QT. More specifically, we developed mathematical models of acquired and inherited long-QT syndrome in male and female ventricular human myocytes by combining effects of a hormone and a hERG blocker, dofetilide, or hERG mutations. These 'male' and 'female' model myocytes and tissues then were used to predict how various sex-based differences underlie arrhythmia risk in the setting of acute sympathetic nervous system discharge. The model predicted increased risk for arrhythmia in females when acute sympathetic nervous system discharge was applied in the settings of both inherited and acquired long-QT syndrome. Females were predicted to have protection from arrhythmia induction when progesterone is high. Males were protected by the presence of testosterone. Structural modelling points towards two plausible and distinct mechanisms of oestrogen action enhancing torsadogenic effects: oestradiol interaction with hERG mutations in the pore loop containing G604 or with common TdP-related blockers in the intra-cavity binding site. Our study presents findings that constitute the first evidence linking structure to function mechanisms underlying female dominance of arousal-induced arrhythmias.

Current methods for assessing safety pharmacology in the context of cardiac arrhythmia risk are unable to distinguish between drugs that cause cardiac rhythm disturbances and benign drugs. Drugs deemed likely to be unsafe share the common property of blocking the human Ether-à-go-go-Related Gene (hERG) encoded cardiac potassium channel and consequent prolongation of QT interval on the ECG. However, hERG block and QT prolongation alone are not selective indicators for cardiac arrhythmia. Here we present a prototype computational framework to distinguish between safe and unsafe hERG blockers. We used recent cryo-EM hERG structure to build and validate an atomistic structural model of the channel open conducting state. We also developed structural atomistic models of dofetilide, a hERG blocking drug with high pro-arrhythmia risk, in both charged and neutral ionization states. Next, we employed unbiased and enhanced sampling all-atom molecular dynamics (MD) simulations to probe atomic-scale mechanisms of dofetilide interaction with open-state hERG. Multi-microsecond drug “flooding” simulations revealed spontaneous dofetilide binding to the channel pore through the intracellular gate. Umbrella sampling MD was used to compute dofetilide affinity to hERG, in good agreement with experiment, as well as ingress and egress rates, which in a novel linkage between the atomistic and functional scale are utilized in our companion paper (Yang P-Cet al.2019bioRxiv:635433) to parameterize functional kinetic models of dofetilide - hERG interactions used to predict emergent drug effects on the cardiac rhythm. This study represents the first necessary components of a computational framework for virtual cardiac safety pharmacology screening from the atom to the rhythm.

SUMMARYWe simulate and predict cardiotoxicity over multiple temporal and spatial scales from the drug chemistry to the cardiac rhythm.ABSTRACTDrug-induced proarrhythmia is so tightly associated with prolongation of the QT interval that QT prolongation has become widely accepted as a surrogate marker for arrhythmia. The problem is that QT interval as an arrhythmia indicator is too sensitive and not selective, resulting in many potentially useful drugs eliminated early in the drug discovery process. We first set out to predict the fundamental mode of binding for the proarrhythmic drug dofetilide with the promiscuous cardiac drug target, the hERG potassium channel. In a novel linkage between the atomistic and functional scales, computed binding affinities and rates from atomistic simulation are utilized here to parameterize function scale kinetic models of dofetilide interactions with the hERG channel. The kinetic model components are then integrated into predictive models at the cell and tissue scales to expose fundamental arrhythmia vulnerability mechanisms and complex interactions underlying emergent behaviors. Human clinical data from published studies were used to validate model framework and showed excellent agreement, demonstrating feasibility of the approach. The model predictions show that a clinically relevant dose of dofetilide increased arrhythmia vulnerability in all emergent TRIaD-linked parameters including Triangulation, Reverse use-dependence, beat-to-beat Instability and temporal and spatial action potential duration Dispersion. Application of machine learning demonstrated redundancy in the TRIaD linked parameters and suggested that changes in beat-to-beat instability were highly predictive of arrhythmia vulnerability in this setting. Here, we demonstrate the development and validation of a prototype multiscale model framework to predict electro-toxicity in the heart for the proarrhythmic drug dofetilide from the atom to the rhythm.SIGNIFICANCE STATEMENTCardiotoxicity in the form of deadly abnormal rhythms is one of the most common and dangerous risks for drugs in development and clinical use. There is an urgent need for new approaches to screen and predict the effects of chemically similar drugs on the cardiac rhythm and to move beyond the QT interval as a diagnostic indicator for arrhythmia. To this end, we present a computational pipeline to predict cardiotoxicity over multiple temporal and spatial scales from the drug chemistry to the cardiac rhythm. We utilize predicted quantitative estimates of ion channel-drug interactions from our companion paper to simulate cardiotoxicity over multiple temporal and spatial scales from the drug chemistry to the cardiac rhythm.

Multi-scale computational modeling is a major branch of computational biology as evidenced by the US federal interagency Multi-Scale Modeling Consortium and major international projects. It invariably involves specific and detailed sequences of data analysis and simulation, often with multiple tools and datasets, and the community recognizes improved modularity, reuse, reproducibility, portability and scalability as critical unmet needs in this area. Scientific workflows are a well-recognized strategy for addressing these needs in scientific computing. While there are good examples if the use of scientific workflows in bioinformatics, medical informatics, biomedical imaging and data analysis, there are fewer examples in multi-scale computational modeling in general and cardiac electrophysiology in particular. Cardiac electrophysiology simulation is a mature area of multi-scale computational biology that serves as an excellent use case for developing and testing new scientific workflows. In this article, we develop, describe and test a computational workflow that serves as a proof of concept of a platform for the robust integration and implementation of a reusable and reproducible multi-scale cardiac cell and tissue model that is expandable, modular and portable. The workflow described leverages Python and Kepler-Python actor for plotting and pre/post-processing. During all stages of the workflow design, we rely on freely available open-source tools, to make our workflow freely usable by scientists., Author summary We present a computational workflow as a proof of concept for integration and implementation of a reusable and reproducible cardiac multi-scale electrophysiology model that is expandable, modular and portable. This framework enables scientists to create intuitive, user-friendly and flexible end-to-end automated scientific workflows using a graphical user interface. Kepler is an advanced open-source platform that supports multiple models of computation. The underlying workflow engine handles scalability, provenance, reproducibility aspects of the code, performs orchestration of data flow, and automates execution on heterogeneous computing resources. One of the main advantages of workflow utilization is the integration of code written in multiple languages Standardization occurs at the interfaces of the workflow elements and allows for general applications and easy comparison and integration of code from different research groups or even multiple programmers coding in different languages for various purposes from the same group. A workflow driven problem-solving approach enables domain scientists to focus on resolving the core science questions, and delegates the computational and process management burden to the underlying Workflow. The workflow driven approach allows scaling the computational experiment with distributed data-parallel execution on multiple computing platforms, such as, HPC resources, GPU clusters, Cloud etc. The workflow framework tracks software version information along with hardware information to allow users an opportunity to trace any variation in workflow outcome to the system configurations.

We have created a prototype Cardiac use-case package for modeling and simulation of autonomic effects on the cardiovascular system. The Cardiac use-case package consists of a single-cell model, 1D and 2D tissues models with documentation.

Background Catecholaminergic polymorphic ventricular tachycardia (CPVT) is a lethal inherited arrhythmia syndrome characterized by adrenergically stimulated ventricular tachycardia. Mutations in the cardiac ryanodine receptor gene ( RYR2 ) cause an autosomal dominant form of CPVT, while mutations in the cardiac calsequestrin 2 gene ( CASQ2 ) cause an autosomal recessive form. Objective The aim of this study was to clinically and genetically evaluate a large family with severe autosomal dominant CPVT. Methods Clinical evaluation of family members was performed, including detailed history, physical examination, electrocardiogram, exercise stress test, and autopsy review of decedents. We performed genome-wide linkage analysis in 12 family members and exome sequencing in 2 affected family members. In silico models of mouse and rabbit myocyte electrophysiology were used to predict potential disease mechanisms. Results Severe CPVT with dominant inheritance in 6 members was diagnosed in a large family with 2 sudden deaths, 2 resuscitated cardiac arrests, and multiple appropriate implantable cardioverter-defibrillator shocks. A comprehensive analysis of cardiac arrhythmia genes did not reveal a pathogenic variant. Exome sequencing identified a novel heterozygous missense variant in CASQ2 (Lys180Arg) affecting a highly conserved residue, which cosegregated with disease and was absent in unaffected family members. Genome-wide linkage analysis confirmed a single linkage peak at the CASQ2 locus (logarithm of odds ratio score 3.01; θ = 0). Computer simulations predicted that haploinsufficiency was unlikely to cause the severe CPVT phenotype and suggested a dominant negative mechanism. Conclusion We show for the first time that a variant in CASQ2 causes autosomal dominant CPVT. Genetic testing in dominant CPVT should include screening for heterozygous CASQ2 variants.

In the last decade, there has been tremendous progress in identifying genetic anomalies linked to clinical disease. New experimental platforms have connected genetic variants to mechanisms underlying disruption of cellular and organ behavior and the emergence of proarrhythmic cardiac phenotypes. The development of induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs) signifies an important advance in the study of genetic disease in a patient-specific context. However, considerable limitations of iPSC-CM technologies have not been addressed: 1) phenotypic variability in apparently identical genotype perturbations, 2) low-throughput electrophysiological measurements, and 3) an immature phenotype which may impact translation to adult cardiac response. We have developed a computational approach intended to address these problems. We applied our recent iPSC-CM computational model to predict the proarrhythmic risk of 40 KCNQ1 genetic variants. An IKs computational model was fit to experimental data for each mutation, and the impact of each mutation was simulated in a population of iPSC-CM models. Using a test set of 15 KCNQ1 mutations with known clinical long QT phenotypes, we developed a method to stratify the effects of KCNQ1 mutations based on proarrhythmic markers. We utilized this method to predict the severity of the remaining 25 KCNQ1 mutations with unknown clinical significance. Tremendous phenotypic variability was observed in the iPSC-CM model population following mutant perturbations. A key novelty is our reporting of the impact of individual KCNQ1 mutant models on adult ventricular cardiomyocyte electrophysiology, allowing for prediction of mutant impact across the continuum of aging. This serves as a first step toward translating predicted response in the iPSC-CM model to predicted response of the adult ventricular myocyte given the same genetic mutation. As a whole, this study presents a new computational framework that serves as a high throughput method to evaluate risk of genetic mutations based-on proarrhythmic behavior in phenotypically variable populations., Author summary In the last decade, there has been tremendous progress in identifying genetic mutations linked to clinical diseases, such as cardiac arrhythmia. Many experimental platforms have been developed to study this link, including induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs). IPSC-CMs are patient-derived cardiac cells which allow for the study of genetic variants within a patient-specific context. However, experimentally iPSC-CMs have certain limitations, including: (1) they exhibit variability in behavior within cells that are apparently genetically identical, and (2) they are immature compared to adult cardiac cells. In our study, we have developed a computational approach to model 40 genetic variants in the KCNQ1 gene and predict the proarrhythmic risk of each variant. To do this, we modeled the ionic current determined by KCNQ1, IKs, to fit experimental data for each mutation. We then simulated the impact of each mutation in a population of iPSC-CMs, incorporating variability across the population. We also simulated each variant in an adult cardiac cell model, providing a link between iPSC-CM response to mutants and adult cardiac cell response to the same mutants. Overall, this study provides a new computational framework to evaluate risk of genetic mutations based-on proarrhythmic behavior diverse populations of iPSC-CM models.

Aim: Confining cAMP production to discrete subcellular locations makes it possible for this ubiquitous second messenger to elicit unique functional responses. Yet, factors that determine how and where the production of this diffusible signaling molecule occurs are incompletely understood. The fluid mosaic model originally proposed that signal transduction occurs through random interactions between proteins diffusing freely throughout the plasma membrane. However, it is now known that the movement of membrane proteins is restricted, suggesting that the plasma membrane is segregated into distinct microdomains where different signaling proteins can be concentrated. In this study, we examined what role lipid raft and non-raft membrane domains play in compartmentation of cAMP signaling in adult ventricular myocytes. Methods and Results: The freely diffusible fluorescence resonance energy transfer-based biosensor Epac2-camps was used to measure global cytosolic cAMP responses, while versions of the probe targeted to lipid raft (Epac2-MyrPalm) and non-raft (Epac2-CAAX) domains were used to monitor local cAMP production near the plasma membrane. We found that β-adrenergic receptors, which are expressed in lipid raft and non-raft domains, produce cAMP responses near the plasma membrane that are distinctly different from those produced by E-type prostaglandin receptors, which are expressed exclusively in non-raft domains. We also found that there are differences in basal cAMP levels associated with lipid raft and non-raft domains, and that this can be explained by differences in basal adenylyl cyclase activity associated with each of these membrane environments. In addition, we found evidence that phosphodiesterases 2, 3, and 4 work together in regulating cAMP activity associated with both lipid raft and non-raft domains, while phosphodiesterase 3 plays a more prominent role in the bulk cytoplasmic compartment. Conclusion: These results suggest that different membrane domains contribute to the formation of distinct pools of cAMP under basal conditions as well as following receptor stimulation in adult ventricular myocytes.

IKr is the rapidly activating component of the delayed rectifier potassium current, the ion current largely responsible for the repolarization of the cardiac action potential. Inherited forms of long QT syndrome (LQTS) (Lees-Miller et al., 1997) in humans are linked to functional modifications in the Kv11.1 (hERG) ion channel and potentially life threatening arrhythmias. There is little doubt now that hERG-related component of IKr in the heart depends on the tetrameric (homo- or hetero-) channels formed by two alternatively processed isoforms of hERG, termed hERG1a and hERG1b. Isoform composition (hERG1a- vs. the b-isoform) has recently been reported to alter pharmacologic responses to some hERG blockers and was proposed to be an essential factor pre-disposing patients for drug-induced QT prolongation. Very little is known about the gating and pharmacological properties of two isoforms in heart membranes. For example, how gating mechanisms of the hERG1a channels differ from that of hERG1b is still unknown. The mechanisms by which hERG 1a/1b hetero-tetramers contribute to function in the heart, or what role hERG1b might play in disease are all questions to be answered. Structurally, the two isoforms differ only in the N-terminal region located in the cytoplasm: hERG1b is 340 residues shorter than hERG1a and the initial 36 residues of hERG1b are unique to this isoform. In this study, we combined electrophysiological measurements for HEK cells, kinetics and structural modeling to tease out the individual contributions of each isoform to Action Potential formation and then make predictions about the effects of having various mixture ratios of the two isoforms. By coupling electrophysiological data with computational kinetic modeling, two proposed mechanisms of hERG gating in two homo-tetramers were examined. Sets of data from various experimental stimulation protocols (HEK cells) were analyzed simultaneously and fitted to Markov-chain models (M-models). The minimization procedure presented here, allowed assessment of suitability of different Markov model topologies and the corresponding parameters that describe the channel kinetics. The kinetics modeling pointed to key differences in the gating kinetics that were linked to the full channel structure. Interactions between soluble domains and the transmembrane part of the channel appeared to be critical determinants of the gating kinetics. The structures of the full channel in the open and closed states were compared for the first time using the recent Cryo-EM resolved structure for full open hERG channel and an homology model for the closed state, based on the highly homolog EAG1 channel. Key potential interactions which emphasize the importance of electrostatic interactions between N-PAS cap, S4-S5, and C-linker are suggested based on the structural analysis. The derived kinetic parameters were later used in higher order models of cells and tissue to track down the effect of varying the ratios of hERG1a and hERG1b on cardiac action potentials and computed electrocardiograms. Simulations suggest that the recovery from inactivation of hERG1b may contribute to its physiologic role of this isoform in the action potential. Finally, the results presented here contribute to the growing body of evidence that hERG1b significantly affects the generation of the cardiac Ikr and plays an important role in cardiac electrophysiology. We highlight the importance of carefully revisiting the Markov models previously proposed in order to properly account for the relative abundance of the hERG1 a- and b- isoforms.

Key points The ventricular action potential plateau is a phase of high resistance, which makes ventricular myocytes vulnerable to small electrical perturbations. We developed a computationally based model of GS-458967 interaction with the cardiac Na+ channel, informed by experimental data recorded from guinea pig isolated single ventricular myocytes. The model predicts that the therapeutic potential of GS-458967 derives largely from the designed property of significant potent selectivity for INaL. Abstract Selective inhibition of the slowly inactivating or late Na+ current (INaL) in patients with inherited or acquired arrhythmia syndrome may confer therapeutic benefit by reducing the incidence of triggers for arrhythmia and suppressing one component of arrhythmia-promoting cardiac substrates (e.g. prolonged refractoriness and spatiotemporal dispersion of action potential duration). Recently, a novel compound that preferentially and potently reduces INaL, GS-458967 (IC50 for block of INaL = 130 nm) has been studied. Experimental measurements of the effects of GS-458967 on endogenous INaL in guinea pig ventricular myocytes demonstrate a robust concentration-dependent reduction in action potential duration (APD). Using experimental data to calibrate INaL and the rapidly activating delayed rectifier K+ current, IKr, in the Faber–Rudy computationally based model of the guinea pig ventricular action potential, we simulated effects of GS-458967 on guinea pig ventricular APD. GS-458967 (0.1 μm) caused a 28.67% block of INaL and 12.57% APD shortening in experiments, while the model predicted 10.06% APD shortening with 29.33% block of INaL. An additional effect of INaL block is to reduce the time during which the membrane potential is in a high resistance state (i.e. the action potential plateau). To test the hypothesis that targeted block of INaL would make ventricular myocytes less susceptible to small electrical perturbations, we used the computational model to test the degree of APD prolongation induced by small electrical perturbations in normal cells and in cells with simulated long QT syndrome. The model predicted a substantial dose-dependent reduction in sensitivity to small electrical perturbations as evidenced by action potential duration at 90% repolarization variability in the presence of GS-458967-induced INaL block. This effect was especially potent in the ‘disease setting’ of inherited long QT syndrome. Using a combined experimental and theoretical approach, our results suggest that INaL block is a potent therapeutic strategy. This is because reduction of INaL stabilizes the action potential waveform by reducing depolarizing current during the plateau phase of the action potential. This reduces the most vulnerable phase of the action potential with high membrane resistance. In summary, by reducing the sensitivity of the myocardial substrate to small electrical perturbations that promote arrhythmia triggers, agents such as GS-458967 may constitute an effective antiarrhythmic pharmacological strategy.

The mechanism of therapeutic efficacy of flecainide for catecholaminergic polymorphic ventricular tachycardia (CPVT) is unclear. Model predictions suggest that Na(+) channel effects are insufficient to explain flecainide efficacy in CPVT. This study represents a first step toward predicting therapeutic mechanisms of drug efficacy in the setting of CPVT and then using these mechanisms to guide modelling and simulation to predict alternative drug therapies. Catecholaminergic polymorphic ventricular tachycardia (CPVT) is an inherited arrhythmia syndrome characterized by fatal ventricular arrhythmias in structurally normal hearts during β-adrenergic stimulation. Current treatment strategies include β-blockade, flecainide and ICD implementation--none of which is fully effective and each comes with associated risk. Recently, flecainide has gained considerable interest in CPVT treatment, but its mechanism of action for therapeutic efficacy is unclear. In this study, we performed in silico mutagenesis to construct a CPVT model and then used a computational modelling and simulation approach to make predictions of drug mechanisms and efficacy in the setting of CPVT. Experiments were carried out to validate model results. Our simulations revealed that Na(+) channel effects are insufficient to explain flecainide efficacy in CPVT. The pure Na(+) channel blocker lidocaine and the antianginal ranolazine were additionally tested and also found to be ineffective. When we tested lower dose combination therapy with flecainide, β-blockade and CaMKII inhibition, our model predicted superior therapeutic efficacy than with flecainide monotherapy. Simulations indicate a polytherapeutic approach may mitigate side-effects and proarrhythmic potential plaguing CPVT pharmacological management today. Importantly, our prediction of a novel polytherapy for CPVT was confirmed experimentally. Our simulations suggest that flecainide therapeutic efficacy in CPVT is unlikely to derive from primary interactions with the Na(+) channel, and benefit may be gained from an alternative multi-drug regimen.

Key points This study represents a first step toward predicting mechanisms of sex‐based arrhythmias that may lead to important developments in risk stratification and may inform future drug design and screening.We undertook simulations to reveal the conditions (i.e. pacing, drugs, sympathetic stimulation) required for triggering and sustaining reentrant arrhythmias.Using the recently solved cryo‐EM structure for the Eag‐family channel as a template, we revealed potential interactions of oestrogen with the pore loop hERG mutation (G604S).Molecular models suggest that oestrogen and dofetilide blockade can concur simultaneously in the hERG channel pore. Abstract Female sex is a risk factor for inherited and acquired long‐QT associated torsade de pointes (TdP) arrhythmias, and sympathetic discharge is a major factor in triggering TdP in female long‐QT syndrome patients. We used a combined experimental and computational approach to predict ‘the perfect storm’ of hormone concentration, I Kr block and sympathetic stimulation that induces arrhythmia in females with inherited and acquired long‐QT. More specifically, we developed mathematical models of acquired and inherited long‐QT syndrome in male and female ventricular human myocytes by combining effects of a hormone and a hERG blocker, dofetilide, or hERG mutations. These ‘male’ and ‘female’ model myocytes and tissues then were used to predict how various sex‐based differences underlie arrhythmia risk in the setting of acute sympathetic nervous system discharge. The model predicted increased risk for arrhythmia in females when acute sympathetic nervous system discharge was applied in the settings of both inherited and acquired long‐QT syndrome. Females were predicted to have protection from arrhythmia induction when progesterone is high. Males were protected by the presence of testosterone. Structural modelling points towards two plausible and distinct mechanisms of oestrogen action enhancing torsadogenic effects: oestradiol interaction with hERG mutations in the pore loop containing G604 or with common TdP‐related blockers in the intra‐cavity binding site. Our study presents findings that constitute the first evidence linking structure to function mechanisms underlying female dominance of arousal‐induced arrhythmias., Key points This study represents a first step toward predicting mechanisms of sex‐based arrhythmias that may lead to important developments in risk stratification and may inform future drug design and screening.We undertook simulations to reveal the conditions (i.e. pacing, drugs, sympathetic stimulation) required for triggering and sustaining reentrant arrhythmias.Using the recently solved cryo‐EM structure for the Eag‐family channel as a template, we revealed potential interactions of oestrogen with the pore loop hERG mutation (G604S).Molecular models suggest that oestrogen and dofetilide blockade can concur simultaneously in the hERG channel pore.

We examine the inter-relationships among internal governance, firm attributes, and the listing choices of American Depositary Receipts (ADRs) for Chinese firms. We find that Chinese ADRs exhibit better performance, higher growth opportunities, and stronger internal governance than domestic firms prior to and after ADR listings. Furthermore, we find that the listing choices are influenced by Chinese firms' growth opportunities and internal governance. Those with lower growth opportunities tend to choose a Level 1 listing that restricts capital-raising but does not require U.S. regulatory compliance. In contrast, those with higher growth opportunities prefer a Level 3 listing that permits public offerings but requires full regulatory compliance. As a result, the improvement in the internal governance of Level 3 ADRs is more pronounced than that of Level 1 ADRs in the post-listing period. This suggests that the extent of improvement in governance is related to the firm attributes and the motivations behind cross-listings.

[EN] Background: The QT interval is a phase of the cardiac cycle that corresponds to action potential duration (APD) including cellular repolarization (T-wave). In both clinical and experimental settings, prolongation of the QT interval of the electrocardiogram (ECG) and related proarrhythmia have been so strongly associated that a prolonged QT interval is largely accepted as surrogate marker for proarrhythmia. Accordingly, drugs that prolong the QT interval are not considered for further preclinical development resulting in removal of many promising drugs from development. While reduction of drug interactions with hERG is an important goal, there are promising means to mitigate hERG block. Here, we examine one possibility and test the hypothesis that selective inhibition of the cardiac late Na current (I-NaL) by the novel compound GS-458967 can suppress proarrhythmic markers. Methods and results: New experimental data has been used to calibrate INaL in the Soltis-Saucerman computationally based model of the rabbit ventricular action potential to study effects of GS-458967 on INaL during the rabbit ventricular AP. We have also carried out systematic in silico tests to determine if targeted block of INaL would suppress proarrhythmia markers in ventricular myocytes described by TRIaD: Triangulation, Reverse use dependence, beat-to-beat Instability of action potential duration, and temporal and spatial action potential duration Dispersion. Conclusions: Our computer modeling approach based on experimental data, yields results that suggest that selective inhibition of INaL modifies all TRIaD related parameters arising from acquired Long-QT Syndrome, and thereby reduced arrhythmia risk. This study reveals the potential for adjunctive pharmacotherapy via targeted block of INaL to mitigate proarrhythmia risk for drugs with significant but unintended off-target hERG blocking effects., The National Institutes of Health R01 HL128537-01 (CEC), U01 HL126273-01 (CEC) and R01HL128170-02 (CEC).

Activated phospholipase C (PLC*) generates 1,4,5-triphosphate (IP3) and diacylglycerol (DAG) from phosphatidyl inositol (PIP2). The DAG remains in the plasma membrane and co-activates conventional protein kinase C (PKC) with Ca2+. We have developed a mathematical model for the activation of the Ca2+-dependent PKC and its negative feedback on phospholipase C (PLC) and coupled it to the De Young-Keizer model for IP3 mediated Ca2+ oscillations. The model describes the cascade of reactions for the translocation of PKC to plasma membrane, and simulates activation of Ca2+ and diacylglycerol (DAG) oscillations. The model demonstrates that oscillations in Ca2+ and DAG are possible with or without a positive Ca2+ feedback on phospholipase C consistent with experiment. In many experimental studies, the timing of the peaks of the Ca2+ and IP3 oscillations have been used to suggest causality, i.e. that the IP3 oscillations cause the Ca2+ oscillations. The model is used to explore this question. To this end, the positive and negative feedback between Ca2+ and IP3 production are modulated, resulting in changes to the phase lag between the peaks in [Ca2+]cyt and [IP]cyt. The model simulates a possible experimental protocol that can be used to differentiate whether or not the positive feedback of Ca2+ on PLC is needed for the oscillations.

Cardiac rhythms arise from electrical activity generated by precisely timed opening and closing of ion channels in individual cardiac myocytes. These impulses spread throughout the cardiac muscle to manifest as electrical waves in the whole heart. Regularity of electrical waves is critically important since they signal the heart muscle to contract, driving the primary function of the heart to act as a pump and deliver blood to the brain and vital organs. When electrical activity goes awry during a cardiac arrhythmia, the pump does not function, the brain does not receive oxygenated blood, and death ensues. For more than 50 years, mathematically based models of cardiac electrical activity have been used to improve understanding of basic mechanisms of normal and abnormal cardiac electrical function. Computer-based modeling approaches to understand cardiac activity are uniquely helpful because they allow for distillation of complex emergent behaviors into the key contributing components underlying them. Here we review the latest advances and novel concepts in the field as they relate to understanding the complex interplay between electrical, mechanical, structural, and genetic mechanisms during arrhythmia development at the level of ion channels, cells, and tissues. We also discuss the latest computational approaches to guiding arrhythmia therapy.

The Internet has played a pivotal role in transforming banking services into e-services. While several studies have examined the effective measurement of e-banking service quality, their lack of a holistic view has hindered the accumulation of past knowledge. To address this issue, this study first reviews and summarizes the methodology, service quality dimensions, suggestions and limitations of seven e-banking service quality studies conducted in seven countries. An empirical study is then conducted to derive the first robust and comprehensive measure of e-banking service quality in Taiwanese context by compensating three shortcomings of a prior Taiwanese study. To improve our understanding of e-banking service quality, a comprehensive scheme is proposed that has managerial implications. The primary contribution of this study is to present a holistic view of e-service quality for e-banking with embedded cultural factors and to provide a rigorous measurement scale development procedure applicable to areas...