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Abstract Background Type 2 diabetes mellitus (T2DM) is a major risk factor for heart failure with preserved ejection fraction and cardiac arrhythmias. Precursors of these complications, such as diabetic cardiomyopathy, remain incompletely understood and underdiagnosed. Detection of early signs of cardiac deterioration in T2DM patients is critical for prevention. Our goal is to quantify T2DM-driven abnormalities in ECG and cardiac imaging biomarkers leading to cardiovascular disease. Methods We quantified ECG and cardiac magnetic resonance imaging biomarkers in two matched cohorts of 1781 UK Biobank participants, with and without T2DM, and no diagnosed cardiovascular disease at the time of assessment. We performed a pair-matched cross-sectional study to compare cardiac biomarkers in both cohorts, and examined the association between T2DM and these biomarkers. We built multivariate multiple linear regression models sequentially adjusted for socio-demographic, lifestyle, and clinical covariates. Results Participants with T2DM had a higher resting heart rate (66 vs. 61 beats per minute, p

Abstract Human-based modelling and simulation offer an ideal testbed for novel medical therapies to guide experimental and clinical studies. Myocardial infarction (MI) is a common cause of heart failure and mortality, for which novel therapies are urgently needed. Although cell therapy offers promise, electrophysiological heterogeneity raises pro-arrhythmic safety concerns, where underlying complex spatio-temporal dynamics cannot be investigated experimentally. Here, after demonstrating credibility of the modelling and simulation framework, we investigate cell therapy in acute versus chronic MI and the role of cell heterogeneity, scar size and the Purkinje system. Simulations agreed with experimental and clinical recordings from ionic to ECG dynamics in acute and chronic infarction. Following cell delivery, spontaneous beats were facilitated by heterogeneity in cell populations, chronic MI due to tissue depolarisation and slow sinus rhythm. Subsequent re-entrant arrhythmias occurred, in some instances with Purkinje involvement and their susceptibility was enhanced by impaired Purkinje-myocardium coupling, large scars and acute infarction. We conclude that homogeneity in injected ventricular-like cell populations minimises their spontaneous beating, which is enhanced by chronic MI, whereas a healthy Purkinje-myocardium coupling is key to prevent subsequent re-entrant arrhythmias, particularly for large scars.

Abstract Chronic heart failure is one of the most common reasons for hospitalization. Current risk stratification is based on ejection fraction, whereas many arrhythmic events occur in patients with relatively preserved ejection fraction. We aim to investigate the mechanistic link between proarrhythmic abnormalities, reduced contractility and diastolic dysfunction in heart failure, using electromechanical modelling and simulations of human failing cardiomyocytes. We constructed, calibrated and validated populations of human electromechanical models of failing cardiomyocytes, that were able to reproduce the prolonged action potential, reduced contractility and diastolic dysfunction as observed in human data, as well as increased propensity to proarrhythmic incidents such as early afterdepolarization and beat-to-beat alternans. Our simulation data reveal that proarrhythmic incidents tend to occur in failing myocytes with lower diastolic tension, rather than with lower contractility, due to the relative preserved SERCA and sodium calcium exchanger current. These results support the inclusion of end-diastolic volume to be potentially beneficial in the risk stratifications of heart failure patients.

Sudden death after myocardial infarction (MI) is associated with electrophysiological heterogeneities and ionic current remodelling. Low ejection fraction (EF) is used in risk stratification, but its mechanistic links with pro-arrhythmic heterogeneities are unknown. We aim to provide mechanistic explanations of clinical phenotypes in acute and chronic MI, from ionic current remodelling to ECG and EF, using human electromechanical modelling and simulation to augment experimental and clinical investigations. A human ventricular electromechanical modelling and simulation framework is constructed and validated with rich experimental and clinical datasets, incorporating varying degrees of ionic current remodelling as reported in literature. In acute MI, T-wave inversion and Brugada phenocopy were explained by conduction abnormality and local action potential prolongation in the border zone. In chronic MI, upright tall T-waves highlight large repolarisation dispersion between the border and remote zones, which promoted ectopic propagation at fast pacing. Post-MI EF at resting heart rate was not sensitive to the extent of repolarisation heterogeneity and the risk of repolarisation abnormalities at fast pacing. T-wave and QT abnormalities are better indicators of repolarisation heterogeneities than EF in post-MI.

BackgroundVentricular fibrillation (VF) is the deadliest arrhythmia, often caused by myocardial ischaemia. VF patients require urgent intervention planned quickly and non-invasively. However, the accuracy with which electrocardiographic (ECG) markers reflect the underlying arrhythmic substrate is unknown.MethodsWe analysed how ECG metrics reflect the fibrillatory dynamics of electrical excitation and ischaemic substrate. For this, we developed a human-based computational modelling and simulation framework for the quantification of ECG metrics, namely, frequency, slope, and amplitude spectrum area (AMSA) during VF in acute ischaemia for several electrode configurations. Simulations reproduced experimental and clinical findings in 21 scenarios presenting variability in the location and transmural extent of regional ischaemia, and severity of ischaemia in the remote myocardium secondary to VF.ResultsRegional acute myocardial ischaemia facilitated re-entries, potentially breaking up into VF. Ischaemia in the remote myocardium modulated fibrillation dynamics. Cases presenting a mildly ischaemic remote myocardium yielded sustained VF, enabled by the high proliferation of phase singularities (PS, 11–22) causing remarkably disorganised activation patterns. Conversely, global acute ischaemia induced stable rotors (3–12 PS). Changes in frequency and morphology of the ECG during VF reproduced clinical findings but did not show a direct correlation with the underlying wave dynamics. AMSA allowed the precise stratification of VF according to ischaemic severity in the remote myocardium (healthy: 23.62–24.45 mV Hz; mild ischaemia: 10.58–21.47 mV Hz; moderate ischaemia: 4.82–11.12 mV Hz). Within the context of clinical reference values, apex-anterior and apex-posterior electrode configurations were the most discriminatory in stratifying VF based on the underlying ischaemic substrate.ConclusionThis in silico study provides further insights into non-invasive patient-specific strategies for assessing acute ventricular arrhythmias. The use of reliable ECG markers to characterise VF is critical for developing tailored resuscitation strategies.

ABSTRACT Quorum sensing (QS) is a cell-cell signaling system that enables bacteria to coordinate population density-dependent changes in behavior. This chemical communication pathway is mediated by diffusible N-acyl L-homoserine lactone signals and cytoplasmic signal-responsive LuxR-type receptors in Gram-negative bacteria. As many common pathogenic bacteria use QS to regulate virulence, there is significant interest in disrupting QS as a potential therapeutic strategy. Prior studies have implicated the natural products salicylic acid, cinnamaldehyde, and other related benzaldehyde derivatives as inhibitors of QS in the opportunistic pathogen Pseudomonas aeruginosa, yet we lack an understanding of the mechanisms by which these compounds function. Herein, we evaluate the activity of a set of benzaldehyde derivatives using heterologous reporters of the P. aeruginosa LasR and RhlR QS signal receptors. We find that most tested benzaldehyde derivatives can antagonize LasR or RhlR reporter activation at micromolar concentrations, although certain molecules also cause mild growth defects and nonspecific reporter antagonism. Notably, several compounds showed promising RhlR or LasR-specific inhibitory activities over a range of concentrations below that causing toxicity. ortho-Vanillin, a previously untested compound, was the most promising within this set. Competition experiments against the native ligands for LasR and RhlR revealed that ortho-vanillin can interact competitively with RhlR but not with LasR. Overall, these studies expand our understanding of benzaldehyde activities in the LasR and RhlR receptors and reveal potentially promising effects of ortho-vanillin as a small molecule QS modulator against RhlR.IMPORTANCEQuorum sensing (QS) regulates many aspects of bacterial pathogenesis and has attracted much interest as a target for anti-virulence therapies over the past 30 years, for example, antagonists of the LasR and RhlR QS receptors in Pseudomonas aeruginosa. Potent and selective QS inhibitors remain relatively scarce. However, natural products have provided a bounty of chemical scaffolds with anti-QS activities, but their molecular mechanisms are poorly characterized. The current study serves to fill this void by examining the activity of an important and wide-spread class of natural product QS modulators, benzaldehydes, and related derivatives, in LasR and RhlR. We demonstrate that ortho-vanillin can act as a competitive inhibitor of RhlR, a receptor that has emerged and may supplant LasR in certain settings as a target for P. aeruginosa QS control. The results and insights provided herein will advance the design of chemical tools to study QS with improved activities and selectivities.

Abstract Cardiac Purkinje networks are a fundamental part of the conduction system and are known to initiate a variety of cardiac arrhythmias. However, patient-specific modeling of Purkinje networks remains a challenge due to their high morphological complexity. This work presents a novel method based on optimization principles for the generation of Purkinje networks that combines geometric and activation accuracy in branch size, bifurcation angles, and Purkinje-ventricular-junction activation times. Three biventricular meshes with increasing levels of complexity are used to evaluate the performance of our approach. Purkinje-tissue coupled monodomain simulations are executed to evaluate the generated networks in a realistic scenario using the most recent Purkinje/ventricular human cellular models and physiological values for the Purkinje-ventricular-junction characteristic delay. The results demonstrate that the new method can generate patient-specific Purkinje networks with controlled morphological metrics and specified local activation times at the Purkinje-ventricular junctions.

In the field of knee imaging, the incorporation of MR-based pseudo-CT synthesis holds the potential to mitigate the need for separate CT scans, simplifying workflows, enhancing patient comfort, and reducing radiation exposure. In this work, we present a novel DL framework, grounded in the development of the Cycle-Consistent Generative Adversarial Network (CycleGAN) method, tailored specifically for the synthesis of pseudo-CT images in knee imaging to surmount the limitations of current methods. Upon visually examining the outcomes, it is evident that the synthesized pseudo-CTs show an excellent quality and high robustness. Despite the limited dataset employed, the method is able to capture the particularities of the bone contours in the resulting image. The experimental Mean Absolute Error (MAE), Peak Signal-to-Noise Ratio (PSNR), Structural Similarity Index Measure (SSIM), Zero-Normalized Cross Correlation (ZNCC), Mutual Information (MI), Relative Change (RC), and absolute Relative Change (|RC|) report values of 30.4638 ± 7.4770, 28.1168 ± 1.5245, 0.9230 ± 0.0217, 0.9807 ± 0.0071, 0.8548 ± 0.1019, 0.0055 ± 0.0265, and 0.0302 ± 0.0218 (median ± median absolute deviation), respectively. The voxel-by-voxel correlation plot shows an excellent correlation between pseudo-CT and ground-truth CT Hounsfield units (m = 0.9785; adjusted R2 = 0.9988; ρ = 0.9849; p < 0.001). The Bland–Altman plot shows that the average of the differences is low ((HUCT−HUpseudo−CT = 0.7199 ± 35.2490; 95% confidence interval [−68.3681, 69.8079]). This study represents the first reported effort in the field of MR-based knee pseudo-CT synthesis, shedding light to significantly advance the field of knee imaging.

Abstract Cardiomyopathies have unresolved genotype–phenotype relationships and lack disease-specific treatments. Here we provide a framework to identify genotype-specific pathomechanisms and therapeutic targets to accelerate the development of precision medicine. We use human cardiac electromechanical in-silico modelling and simulation which we validate with experimental hiPSC-CM data and modelling in combination with clinical biomarkers. We select hypertrophic cardiomyopathy as a challenge for this approach and study genetic variations that mutate proteins of the thick (MYH7 R403Q/+) and thin filaments (TNNT2 R92Q/+, TNNI3 R21C/+) of the cardiac sarcomere. Using in-silico techniques we show that the destabilisation of myosin super relaxation observed in hiPSC-CMs drives disease in virtual cells and ventricles carrying the MYH7R403Q/+ variant, and that secondary effects on thin filament activation are necessary to precipitate slowed relaxation of the cell and diastolic insufficiency in the chamber. In-silico modelling shows that Mavacamten corrects the MYH7R403Q/+ phenotype in agreement with hiPSC-CM experiments. Our in-silico model predicts that the thin filament variants TNNT2R92Q/+ and TNNI3R21C/+ display altered calcium regulation as central pathomechanism, for which Mavacamten provides incomplete salvage, which we have corroborated in TNNT2R92Q/+ and TNNI3R21C/+ hiPSC-CMs. We define the ideal characteristics of a novel thin filament-targeting compound and show its efficacy in-silico. We demonstrate that hybrid human-based hiPSC-CM and in-silico studies accelerate pathomechanism discovery and classification testing, improving clinical interpretation of genetic variants, and directing rational therapeutic targeting and design.

Digital health technologies have been in use for many years in a wide spectrum of healthcare scenarios. This narrative review outlines the current use and the future strategies and significance of digital health technologies in modern healthcare applications. It covers the current state of the scientific field (delineating major strengths, limitations, and applications) and envisions the future impact of relevant emerging key technologies. Furthermore, we attempt to provide recommendations for innovative approaches that would accelerate and benefit the research, translation and utilization of digital health technologies.

Abstract Levetiracetam (LEV), a well‐established anti‐seizure medication (ASM), was launched before the original ICH S7B nonclinical guidance assessing QT prolongation potential and the introduction of the Comprehensive In Vitro Proarrhythmia Assay (CiPA) paradigm. No information was available on its effects on cardiac channels. The goal of this work was to “pressure test” the CiPA approach with LEV and check the concordance of nonclinical core and follow‐up S7B assays with clinical and post‐marketing data. The following experiments were conducted with LEV (0.25–7.5 mM): patch clamp assays on hERG (acute or trafficking effects), NaV1.5, CaV1.2, Kir2.1, KV7.1/mink, KV1.5, KV4.3, and HCN4; in silico electrophysiology modeling (Virtual Assay® software) in control, large‐variability, and high‐risk human ventricular cell populations; electrophysiology measurements in human induced pluripotent stem cell (hiPSC)‐derived cardiomyocytes and dog Purkinje fibers; ECG measurements in conscious telemetered dogs after single oral administration (150, 300, and 600 mg/kg). Except a slight inhibition (

The preclinical identification of drug-induced cardiotoxicity and its translation into human risk are still major challenges in pharmaceutical drug discovery. The ICH S7B Guideline and Q&A on Clinical and Nonclinical Evaluation of QT/QTc Interval Prolongation and Proarrhythmic Potential promotes human in silico drug trials as a novel tool for proarrhythmia risk assessment. To facilitate the use of in silico data in regulatory submissions, explanatory control compounds should be tested and documented to demonstrate consistency between predictions and the historic validation data. This study aims to quantify drug-induced electrophysiological effects on in silico cardiac human Purkinje cells, to compare them with existing in vitro rabbit data, and to assess their accuracy for clinical pro-arrhythmic risk predictions. The effects of 14 reference compounds were quantified in simulations with a population of in silico human cardiac Purkinje models. For each drug dose, five electrophysiological biomarkers were quantified at three pacing frequencies, and results compared with available in vitro experiments and clinical proarrhythmia reports. Three key results were obtained: 1) In silico, repolarization abnormalities in human Purkinje simulations predicted drug-induced arrhythmia for all risky compounds, showing higher predicted accuracy than rabbit experiments; 2) Drug-induced electrophysiological changes observed in human-based simulations showed a high degree of consistency with in vitro rabbit recordings at all pacing frequencies, and depolarization velocity and action potential duration were the most consistent biomarkers; 3) discrepancies observed for dofetilide, sotalol and terfenadine are mainly caused by species differences between humans and rabbit. Taken together, this study demonstrates higher accuracy of in silico methods compared to in vitro animal models for pro-arrhythmic risk prediction, as well as a high degree of consistency with in vitro experiments commonly used in safety pharmacology, supporting the potential for industrial and regulatory adoption of in silico trials for proarrhythmia prediction.

Abstract The value of in silico methods in drug development and evaluation has been demonstrated repeatedly and convincingly. While their benefits are now unanimously recognized, international standards for their evaluation, accepted by all stakeholders involved, are still to be established. In this white paper, we propose a risk‐informed evaluation framework for mechanistic model credibility evaluation. To properly frame the proposed verification and validation activities, concepts such as context of use, regulatory impact and risk‐based analysis are discussed. To ensure common understanding between all stakeholders, an overview is provided of relevant in silico terminology used throughout this paper. To illustrate the feasibility of the proposed approach, we have applied it to three real case examples in the context of drug development, using a credibility matrix currently being tested as a quick‐start tool by regulators. Altogether, this white paper provides a practical approach to model evaluation, applicable in both scientific and regulatory evaluation contexts.

Abstract We applied a set of in silico and in vitro assays, compliant with the Comprehensive In Vitro Proarrhythmia Assay (CiPA) paradigm, to assess the risk of chloroquine (CLQ) or hydroxychloroquine (OH‐CLQ)‐mediated QT prolongation and Torsades de Pointes (TdP), alone and combined with erythromycin (ERT) and azithromycin (AZI), drugs repurposed during the first wave of coronavirus disease 2019 (COVID‐19). Each drug or drug combination was tested in patch clamp assays on seven cardiac ion channels, in in silico models of human ventricular electrophysiology (Virtual Assay) using control (healthy) or high‐risk cell populations, and in human‐induced pluripotent stem cell (hiPSC)‐derived cardiomyocytes. In each assay, concentration‐response curves encompassing and exceeding therapeutic free plasma levels were generated. Both CLQ and OH‐CLQ showed blocking activity against some potassium, sodium, and calcium currents. CLQ and OH‐CLQ inhibited IKr (half‐maximal inhibitory concentration [IC50]: 1 µM and 3–7 µM, respectively) and IK1 currents (IC50: 5 and 44 µM, respectively). When combining OH‐CLQ with AZI, no synergistic effects were observed. The two macrolides had no or very weak effects on the ion currents (IC50 > 300–1000 µM). Using Virtual Assay, both antimalarials affected several TdP indicators, CLQ being more potent than OH‐CLQ. Effects were more pronounced in the high‐risk cell population. In hiPSC‐derived cardiomyocytes, all drugs showed early after‐depolarizations, except AZI. Combining CLQ or OH‐CLQ with a macrolide did not aggravate their effects. In conclusion, our integrated nonclinical CiPA dataset confirmed that, at therapeutic plasma concentrations relevant for malaria or off‐label use in COVID‐19, CLQ and OH‐CLQ use is associated with a proarrhythmia risk, which is higher in populations carrying predisposing factors but not worsened with macrolide combination.

Atrial fibrillation (AF) inducibility, sustainability and response to pharmacological treatment of individual patients are expected to be determined by their ionic current properties, especially in structurally-healthy atria. Mechanisms underlying AF and optimal cardioversion are however still unclear. In this study, in-silico drug trials were conducted using a population of human structurally-healthy atria models to 1) identify key ionic current properties determining AF inducibility, maintenance and pharmacological cardioversion, and 2) compare the prognostic value for predicting individual AF cardioversion of ionic current properties and electrocardiogram (ECG) metrics. In the population of structurally-healthy atria, 477 AF episodes were induced in ionic current profiles with both steep action potential duration (APD) restitution (eliciting APD alternans), and high excitability (enabling propagation at fast rates that transformed alternans into discordant). High excitability also favored 211 sustained AF episodes, so its decrease, through prolonged refractoriness, explained pharmacological cardioversion. In-silico trials over 200 AF episodes, 100 ionic profiles and 10 antiarrhythmic compounds were consistent with previous clinical trials, and identified optimal treatments for individual electrophysiological properties of the atria. Algorithms trained on 211 simulated AF episodes exhibited >70% accuracy in predictions of cardioversion for individual treatments using either ionic current profiles or ECG metrics. In structurally-healthy atria, AF inducibility and sustainability are enabled by discordant alternans, under high excitability and steep restitution conditions. Successful pharmacological cardioversion is predicted with 70% accuracy from either ionic or ECG properties, and it is optimal for treatments maximizing refractoriness (thus reducing excitability) for the given ionic current profile of the atria.

Imaging genetic studies aim to test how genetic information influences brain structure and function by combining neuroimaging-based brain features and genetic data from the same individual.Most studies focus on individual correlation and association tests between genetic variants and a single measurement of the brain. Despite the great success of univariate approaches, given the capacity of neuroimaging methods to provide a multiplicity of cerebral phenotypes, the development and application of multivariate methods become crucial.In this article, we review novel methods and strategies focused on the analysis of multiple phenotypes and genetic data. We also discuss relevant aspects of multi-trait modelling in the context of neuroimaging data.

We present reactive VOC observations over the North Pacific and the Arctic Ocean from airborne and shipborne measurements, investigating, in particular, distributions of biogenic volatile organic compounds that may be emitted from phytoplankton. In contrast to terrestrial observations, isoprene (C5H8), the most dominant BVOC emission from the terrestrial ecosystem, was mostly present under the lower detection limit along with monoterpenes (C10H16), the second largest emission from the terrestrial ecosystem. However, we consistently detected sesquiterpenes (C15H24) over the Arctic Ocean for the two Arctic cruises. The results of the analysis of sorbent cartridge samplings conducted over the Arctic Ocean on Korean icebreaker R/V Araon in 2016 and 2017 illustrate that few tens ppt levels of sesquiterpenes were present over the Arctic Ocean. Moreover, the concentration variation was positively correlated with the quantitative indicators of ocean biological activities, such as chlorophyll-a, dissolved DMS, and the ratio of dissolved O2 and Ar. This suggests that further investigations on sesquiterpene’s emission and atmospheric transformation processes over the marine boundary layer are required.

Patients with heart failure often develop cardiac arrhythmias. The mechanisms and interrelations linking heart failure and arrhythmias are not fully understood. Historically, research into arrhythmias has been performed on affected individuals or in vivo (animal) models. The latter however is constrained by interspecies variation, demands to reduce animal experiments and cost. Recent developments in in vitro induced pluripotent stem cell technology and in silico modelling have expanded the number of models available for the evaluation of heart failure and arrhythmia. An agnostic approach, combining the modalities discussed here, has the potential to improve our understanding for appraising the pathology and interactions between heart failure and arrhythmia and can provide robust and validated outcomes in a variety of research settings. This review discusses the state of the art models, methodologies and techniques used in the evaluation of heart failure and arrhythmia and will highlight the benefits of using them in combination. Special consideration is paid to assessing the pivotal role calcium handling has in the development of heart failure and arrhythmia.

Background: The Nav 1.8 sodium channel has a key role in generating repetitive action potentials in nociceptive human dorsal root ganglion neurons. Nav 1.8 is differentiated from other voltage-gated sodium channels by its unusually slow inactivation kinetics and depolarised voltage-dependence of activation. These features are particularly pronounced in the human Nav 1.8 channel and allow the channel to remain active during repolarisation. Gain-of-function mutations in Nav 1.8 have been linked to neuropathic pain and selective blockers of Nav 1.8 have been developed as potential new analgesics. However, it is not well understood how modulating the Nav 1.8 conductance alters neuronal excitability and how this depends on the balance of other ion channels expressed by nociceptive neurons. Methods: To investigate this, we developed a novel computational model of the human dorsal root ganglion neuron and used it to construct a population of models that mimicked inter-neuronal heterogeneity in ionic conductances and action potential morphology Results: By simulating changes to the Nav 1.8 conductance in the population of models, we found that moderately increasing the Nav 1.8 conductance led to increased firing rate, as expected, but increasing Nav 1.8 conductance beyond an inflection point caused firing rate to decrease. We found that the delayed rectifier and M-type potassium conductances were also critical for determining neuronal excitability. In particular, altering the delayed rectifier potassium conductance shifted the position of the Nav 1.8 inflection point and therefore the relationship between Nav 1.8 conductance and firing rate. Conclusions: Our results suggest that the effects of modulating Nav 1.8 in a nociceptive neuron can depend significantly on other conductances, particularly potassium conductances.

El objetivo general de esta investigación se dirige a conocer la circulación de los materiales tradicionales en las bibliotecas de la ULe, para observar la evolución del préstamo en el momento de auge de la colección electrónica, indagar sobre los principales usuarios de la colección y averiguar qué tipos documentales son los más prestados. En especial interesa saber el posicionamiento del libro como fuente de información en la comunidad universitaria. De los resultados obtenidos se desprende que el volumen de la colección se adecua al número de usuario, que el movimiento de la colección no es muy elevado, aunque existen notables diferencias entre centros, y que el préstamo, al igual que la colección, está dominado por los libros impresos.

Objectives: Improvements in human stem cell-derived cardiomyocyte (hSC-CM) technology have promoted their use for drug testing and disease investigations. Several in silico hSC-CM models have been proposed to augment interpretation of experimental findings through simulations. This work aims to assess the response of three hSC-CM in silico models (Koivumäki2018, Kernik2019, and Paci2020) to simulated drug action, and compare simulation results against in vitro data for 15 drugs.Methods: First, simulations were conducted considering 15 drugs, using a simple pore-block model and experimental data for seven ion channels. Similarities and differences were analyzed in the in silico responses of the three models to drugs, in terms of Ca2+ transient duration (CTD90) and occurrence of arrhythmic events. Then, the sensitivity of each model to different degrees of blockage of Na+ (INa), L-type Ca2+ (ICaL), and rapid delayed rectifying K+ (IKr) currents was quantified. Finally, we compared the drug-induced effects on CTD90 against the corresponding in vitro experiments.Results: The observed CTD90 changes were overall consistent among the in silico models, all three showing changes of smaller magnitudes compared to the ones measured in vitro. For example, sparfloxacin 10 µM induced +42% CTD90 prolongation in vitro, and +17% (Koivumäki2018), +6% (Kernik2019), and +9% (Paci2020) in silico. Different arrhythmic events were observed following drug application, mainly for drugs affecting IKr. Paci2020 and Kernik2019 showed only repolarization failure, while Koivumäki2018 also displayed early and delayed afterdepolarizations. The spontaneous activity was suppressed by Na+ blockers and by drugs with similar effects on ICaL and IKr in Koivumäki2018 and Paci2020, while only by strong ICaL blockers, e.g. nisoldipine, in Kernik2019. These results were confirmed by the sensitivity analysis.Conclusion: To conclude, The CTD90 changes observed in silico are qualitatively consistent with our in vitro data, although our simulations show differences in drug responses across the hSC-CM models, which could stem from variability in the experimental data used in their construction.

Computational methods can increase productivity of drug discovery pipelines, through overcoming challenges such as cardiotoxicity identification. We demonstrate prediction and preservation of cardiotoxic relationships for six drug-induced cardiotoxicity types using a machine learning approach on a large collected and curated dataset of transcriptional and molecular profiles (1,131 drugs, 35% with known cardiotoxicities, and 9,933 samples). The algorithm generality is demonstrated through validation in an independent drug dataset, in addition to cross-validation. The best prediction attains an average accuracy of 79% in area under the curve (AUC) for safe versus risky drugs, across all six cardiotoxicity types on validation and 66% on the unseen set of drugs. Individual cardiotoxicities for specific drug types are also predicted with high accuracy, including cardiac disorder signs and symptoms for a previously unseen set of anti-inflammatory agents (AUC = 80%) and heart failures for an unseen set of anti-neoplastic agents (AUC = 76%). Besides, independent testing on transcriptional data from the Drug Toxicity Signature Generation Center (DToxS) produces similar results in terms of accuracy and shows an average AUC of 72% for previously seen drugs and 60% for unseen respectively. Given the ubiquitous manifestation of multiple drug adverse effects in every human organ, the methodology is expected to be applicable to additional tissue-specific side effects beyond cardiotoxicity.

Torsades de Pointes (TdP) is a type of ventricular arrhythmia which could be observed as an unwanted drug-induced cardiac side effect, and it is associated with repolarization abnormalities in single cells. The pharmacological evaluations of TdP risk in previous years mainly focused on the hERG channel due to its vital role in the repolarization of cardiomyocytes. However, only considering drug effects on hERG led to false positive predictions since the drug action on other ion channels can also have crucial regulatory effects on repolarization. To address the limitation of only evaluating hERG, the Comprehensive in Vitro Proarrhythmia Assay initiative has proposed to systematically integrate drug effects on multiple ion channels into in silico drug trial to improve TdP risk assessment. It is not clear how many ion channels are sufficient for reliable TdP risk predictions, and whether differences in IC50 and Hill coefficient values from independent sources can lead to divergent in silico prediction outcomes. The rationale of this work is to investigate the above two questions using a computationally efficient population of human ventricular cells optimized to favor repolarization abnormality. Our blinded results based on two independent data sources confirm that simulations with the optimized population of human ventricular cell models enable efficient in silico drug screening, and also provide direct observation and mechanistic analysis of repolarization abnormality. Our results show that 1) the minimum set of ion channels required for reliable TdP risk predictions are Nav1.5 (peak), Cav1.2, and hERG; 2) for drugs with multiple ion channel blockage effects, moderate IC50 variations combined with variable Hill coefficients can affect the accuracy of in silico predictions.

Human-based modelling and simulations are becoming ubiquitous in biomedical science due to their ability to augment experimental and clinical investigations. Cardiac electrophysiology is one of the most advanced areas, with cardiac modelling and simulation being considered for virtual testing of pharmacological therapies and medical devices. Current models present inconsistencies with experimental data, which limit further progress. In this study, we present the design, development, calibration and independent validation of a human-based ventricular model (ToR-ORd) for simulations of electrophysiology and excitation-contraction coupling, from ionic to whole-organ dynamics, including the electrocardiogram. Validation based on substantial multiscale simulations supports the credibility of the ToR-ORd model under healthy and key disease conditions, as well as drug blockade. In addition, the process uncovers new theoretical insights into the biophysical properties of the L-type calcium current, which are critical for sodium and calcium dynamics. These insights enable the reformulation of L-type calcium current, as well as replacement of the hERG current model.

AimsPatient-to-patient anatomical differences are an important source of variability in the electrocardiogram, and they may compromise the identification of pathological electrophysiological abnormalities. This study aims at quantifying the contribution of variability in ventricular and torso anatomies to differences in QRS complexes of the 12-lead ECG using computer simulations.MethodsA computational pipeline is presented that enables computer simulations using human torso/biventricular anatomically based electrophysiological models from clinically standard magnetic resonance imaging (MRI). The ventricular model includes membrane kinetics represented by the biophysically detailed O’Hara Rudy model modified for tissue heterogeneity and includes fiber orientation based on the Streeter rule. A population of 265 torso/biventricular models was generated by combining ventricular and torso anatomies obtained from clinically standard MRIs, augmented with a statistical shape model of the body. 12-lead ECGs were simulated on the 265 human torso/biventricular electrophysiology models, and QRS morphology, duration and amplitude were quantified in each ECG lead for each of the human torso-biventricular models.ResultsQRS morphologies in limb leads are mainly determined by ventricular anatomy, while in the precordial leads, and especially V1 to V4, they are determined by heart position within the torso. Differences in ventricular orientation within the torso can explain morphological variability from monophasic to biphasic QRS complexes. QRS duration is mainly influenced by myocardial volume, while it is hardly affected by the torso anatomy or position. An average increase of 0.12 ± 0.05 ms in QRS duration is obtained for each cm3 of myocardial volume across all the leads while it hardly changed due to changes in torso volume.ConclusionComputer simulations using populations of human torso/biventricular models based on clinical MRI enable quantification of anatomical causes of variability in the QRS complex of the 12-lead ECG. The human models presented also pave the way toward their use as testbeds in silico clinical trials.

The congenital long QT syndrome (LQTS) is a cardiac electrophysiological disorder that can cause sudden cardiac death. LQT1 is a subtype of LQTS caused by mutations in KCNQ1, affecting the slow delayed-rectifier potassium current (IKs), which is essential for cardiac repolarization. Paradoxically, gain-of-function mutations in KCNQ1 have been reported to cause borderline QT prolongation, atrial fibrillation (AF), sinus bradycardia, and sudden death, however, the mechanisms are not well understood. The goal of the study is to investigate the ionic, cellular and tissue mechanisms underlying the complex phenotype of a gain-of-function mutation in KCNQ1, c.686G > A (p.G229D) using computer modeling and simulations informed by in vitro measurements. Previous studies have shown this mutation to cause AF and borderline QT prolongation. We report a clinical description of a family that carry this mutation and that a member of the family died suddenly during sleep at 21 years old. Using patch-clamp experiments, we confirm that KCNQ1-G229D causes a significant gain in channel function. We introduce the effect of the mutation in populations of atrial, ventricular and sinus node (SN) cell models to investigate mechanisms underlying phenotypic variability. In a population of human atrial and ventricular cell models and tissue, the presence of KCNQ1-G229D predominantly shortens atrial action potential duration (APD). However, in a subset of models, KCNQ1-G229D can act to prolong ventricular APD by up to 7% (19 ms) and underlie depolarization abnormalities, which could promote QT prolongation and conduction delays. Interestingly, APD prolongations were predominantly seen at slow pacing cycle lengths (CL > 1,000 ms), which suggests a greater arrhythmic risk during bradycardia, and is consistent with the observed sudden death during sleep. In a population of human SN cell models, the KCNQ1-G229D mutation results in slow/abnormal sinus rhythm, and we identify that a stronger L-type calcium current enables the SN to be more robust to the mutation. In conclusion, our computational modeling experiments provide novel mechanistic explanations for the observed borderline QT prolongation, and predict that KCNQ1-G229D could underlie SN dysfunction and conduction delays. The mechanisms revealed in the study can potentially inform management and treatment of KCNQ1 gain-of-function mutation carriers.

Background: Following myocardial infarction (MI), the myocardium is prone to calcium-driven alternans, which typically precedes ventricular tachycardia and fibrillation. MI is also associated with remodeling of the sympathetic innervation in the infarct border zone, although how this influences arrhythmogenesis is controversial. We hypothesize that the border zone is most vulnerable to alternans, that β-adrenergic receptor stimulation can suppresses this, and investigate the consequences in terms of arrhythmogenic mechanisms.Methods and Results: Anterior MI was induced in Sprague-Dawley rats (n = 8) and allowed to heal over 2 months. This resulted in scar formation, significant (p < 0.05) dilation of the left ventricle, and reduction in ejection fraction compared to sham operated rats (n = 4) on 7 T cardiac magnetic resonance imaging. Dual voltage/calcium optical mapping of post-MI Langendorff perfused hearts (using RH-237 and Rhod2) demonstrated that the border zone was significantly more prone to alternans than the surrounding myocardium at longer cycle lengths, predisposing to spatially heterogeneous alternans. β-Adrenergic receptor stimulation with norepinephrine (1 μmol/L) attenuated alternans by 60 [52–65]% [interquartile range] and this was reversed with metoprolol (10 μmol/L, p = 0.008). These results could be reproduced by computer modeling of the border zone based on our knowledge of β-adrenergic receptor signaling pathways and their influence on intracellular calcium handling and ion channels. Simulations also demonstrated that β-adrenergic receptor stimulation in this specific region reduced the formation of conduction block and the probability of premature ventricular activation propagation.Conclusion: While high levels of overall cardiac sympathetic drive are a negative prognostic indicator of mortality following MI and during heart failure, β-adrenergic receptor stimulation in the infarct border zone reduced spatially heterogeneous alternans, and prevented conduction block and propagation of extrasystoles. This may help explain recent clinical imaging studies using meta-iodobenzylguanidine (MIBG) and 11C-meta-hydroxyephedrine positron emission tomography (PET) which demonstrate that border zone denervation is strongly associated with a high risk of future arrhythmia.

Background: Cardiac alternans is an important precursor to arrhythmia, facilitating formation of conduction block, and re-entry. Diseased hearts were observed to be particularly vulnerable to alternans, mainly in heart failure or after myocardial infarction. Alternans is typically linked to oscillation of calcium cycling, particularly in the sarcoplasmic reticulum (SR). While the role of SR calcium reuptake in alternans is well established, the role of altered calcium release by ryanodine receptors has not yet been studied extensively. At the same time, there is strong evidence that calcium release is abnormal in heart failure and other heart diseases, suggesting that these changes might play a pro-alternans role.Aims: To demonstrate how changes to intracellular calcium release dynamics and magnitude affect alternans vulnerability.Methods: We used the state-of-the-art Heijman–Rudy and O’Hara–Rudy computer models of ventricular myocyte, given their detailed representation of calcium handling and their previous utility in alternans research. We modified the models to obtain precise control over SR release dynamics and magnitude, allowing for the evaluation of these properties in alternans formation and suppression.Results: Shorter time to peak SR release and shorter release duration decrease alternans vulnerability by improved refilling of releasable calcium within junctional SR; conversely, slow release promotes alternans. Modulating the total amount of calcium released, we show that sufficiently increased calcium release may surprisingly prevent alternans via a mechanism linked to the functional depletion of junctional SR during release. We show that this mechanism underlies differences between “eye-type” and “fork-type” alternans, which were observed in human in vivo and in silico. We also provide a detailed explanation of alternans formation in the given computer models, termed “sarcoplasmic reticulum calcium cycling refractoriness.” The mechanism relies on the steep SR load–release relationship, combined with relatively limited rate of junctional SR refilling.Conclusion: Both altered dynamics and magnitude of SR calcium release modulate alternans vulnerability. In particular, slow dynamics of SR release, such as those observed in heart failure, promote alternans. Therefore, acceleration of intracellular calcium release, e.g., via synchronization of calcium sparks, may inhibit alternans in failing hearts and reduce arrhythmia occurrence.

Aims: Ventricular arrhythmia triggers sudden cardiac death (SCD) in hypertrophic cardiomyopathy (HCM), yet electrophysiological biomarkers are not used for risk stratification. Our aim was to identify distinct HCM phenotypes based on ECG computational analysis, and characterize differences in clinical risk factors and anatomical differences using cardiac magnetic resonance (CMR) imaging.Methods: High-fidelity 12-lead Holter ECGs from 85 HCM patients and 38 healthy volunteers were analyzed using mathematical modeling and computational clustering to identify phenotypic subgroups. Clinical features and the extent and distribution of hypertrophy assessed by CMR were evaluated in the subgroups.Results: QRS morphology alone was crucial to identify three HCM phenotypes with very distinct QRS patterns. Group 1 (n = 44) showed normal QRS morphology, Group 2 (n = 19) showed short R and deep S waves in V4, and Group 3 (n = 22) exhibited short R and long S waves in V4-6, and left QRS axis deviation. However, no differences in arrhythmic risk or distribution of hypertrophy were observed between these groups. Including T wave biomarkers in the clustering, four HCM phenotypes were identified: Group 1A (n = 20), with primary repolarization abnormalities showing normal QRS yet inverted T waves, Group 1B (n = 24), with normal QRS morphology and upright T waves, and Group 2 and Group 3 remaining as before, with upright T waves. Group 1A patients, with normal QRS and inverted T wave, showed increased HCM Risk-SCD scores (1A: 4.0%, 1B: 1.8%, 2: 2.1%, 3: 2.5%, p = 0.0001), and a predominance of coexisting septal and apical hypertrophy (p < 0.0001). HCM patients in Groups 2 and 3 exhibited predominantly septal hypertrophy (85 and 90%, respectively).Conclusion: HCM patients were classified in four subgroups with distinct ECG features. Patients with primary T wave inversion not secondary to QRS abnormalities had increased HCM Risk-SCD scores and coexisting septal and apical hypertrophy, suggesting that primary T wave inversion may increase SCD risk in HCM, rather than T wave inversion secondary to depolarization abnormalities. Computational ECG phenotyping provides insight into the underlying processes captured by the ECG and has the potential to be a novel and independent factor for risk stratification.

Input-output (I/O) optimization at the low-level design of data layout on disk drastically impacts the efficiency of high performance computing (HPC) applications. However, such a low-level optimization is in general challenging, especially when using popular scientific file formats designed with an emphasis on portability and flexibility. To reconcile these two aspects, we present a novel low-level data layout for HPC applications, fully independent of the number of dimensions in the dataset. The new data layout improves reading and writing efficiency in large HPC applications using many processors, and in particular during parallel post-processing. Furthermore, its combination with a cached write mode, in order to aggregate multiple writes into larger ones, substantially decreased the writing times of the proposed strategy. When applied to our simulation framework for the forward calculation of the human electrocardiogram, the combined strategy resulted in drastic improvements in I/O performance, of up to 40% in writing and 93-98% in reading for post-processing tasks. Given the generality of the proposed strategies and scientific file formats used, our results may represent significant improvements in I/O performance of HPC applications across multiple disciplines, reducing execution and post-processing times and leading to a more efficient use of HPC resource envelopes.

Early prediction of cardiotoxicity is critical for drug development. Current animal models raise ethical and translational questions, and have limited accuracy in clinical risk prediction. Human-based computer models constitute a fast, cheap and potentially effective alternative to experimental assays, also facilitating translation to human. Key challenges include consideration of inter-cellular variability in drug responses and integration of computational and experimental methods in safety pharmacology. Our aim is to evaluate the ability of in silico drug trials in populations of human action potential (AP) models to predict clinical risk of drug-induced arrhythmias based on ion channel information, and to compare simulation results against experimental assays commonly used for drug testing. A control population of 1,213 human ventricular AP models in agreement with experimental recordings was constructed. In silico drug trials were performed for 62 reference compounds at multiple concentrations, using pore-block drug models (IC50/Hill coefficient). Drug-induced changes in AP biomarkers were quantified, together with occurrence of repolarization/depolarization abnormalities. Simulation results were used to predict clinical risk based on reports of Torsade de Pointes arrhythmias, and further evaluated in a subset of compounds through comparison with electrocardiograms from rabbit wedge preparations and Ca2+-transient recordings in human induced pluripotent stem cell-derived cardiomyocytes (hiPS-CMs). Drug-induced changes in silico vary in magnitude depending on the specific ionic profile of each model in the population, thus allowing to identify cell sub-populations at higher risk of developing abnormal AP phenotypes. Models with low repolarization reserve (increased Ca2+/late Na+ currents and Na+/Ca2+-exchanger, reduced Na+/K+-pump) are highly vulnerable to drug-induced repolarization abnormalities, while those with reduced inward current density (fast/late Na+ and Ca2+ currents) exhibit high susceptibility to depolarization abnormalities. Repolarization abnormalities in silico predict clinical risk for all compounds with 89% accuracy. Drug-induced changes in biomarkers are in overall agreement across different assays: in silico AP duration changes reflect the ones observed in rabbit QT interval and hiPS-CMs Ca2+-transient, and simulated upstroke velocity captures variations in rabbit QRS complex. Our results demonstrate that human in silico drug trials constitute a powerful methodology for prediction of clinical pro-arrhythmic cardiotoxicity, ready for integration in the existing drug safety assessment pipelines.

Background:In silico modeling could soon become a mainstream method of pro-arrhythmic risk assessment in drug development. However, a lack of human-specific data and appropriate modeling techniques has previously prevented quantitative comparison of drug effects between in silico models and recordings from human cardiac preparations. Here, we directly compare changes in repolarization biomarkers caused by dofetilide, dl-sotalol, quinidine, and verapamil, between in silico populations of human ventricular cell models and ex vivo human ventricular trabeculae.Methods and Results:Ex vivo recordings from human ventricular trabeculae in control conditions were used to develop populations of in silico human ventricular cell models that integrated intra- and inter-individual variability in action potential (AP) biomarker values. Models were based on the O'Hara-Rudy ventricular cardiomyocyte model, but integrated experimental AP variability through variation in underlying ionic conductances. Changes to AP duration, triangulation and early after-depolarization occurrence from application of the four drugs at multiple concentrations and pacing frequencies were compared between simulations and experiments. To assess the impact of variability in IC50 measurements, and the effects of including state-dependent drug binding dynamics, each drug simulation was repeated with two different IC50 datasets, and with both the original O'Hara-Rudy hERG model and a recently published state-dependent model of hERG and hERG block. For the selective hERG blockers dofetilide and sotalol, simulation predictions of AP prolongation and repolarization abnormality occurrence showed overall good agreement with experiments. However, for multichannel blockers quinidine and verapamil, simulations were not in agreement with experiments across all IC50 datasets and IKr block models tested. Quinidine simulations resulted in overprolonged APs and high incidence of repolarization abnormalities, which were not observed in experiments. Verapamil simulations showed substantial AP prolongation while experiments showed mild AP shortening.Conclusions: Results for dofetilide and sotalol show good agreement between experiments and simulations for selective compounds, however lack of agreement from simulations of quinidine and verapamil suggest further work is needed to understand the more complex electrophysiological effects of these multichannel blocking drugs.

Background: Cellular repolarization abnormalities occur unpredictably due to disease and drug effects, and can occur even in cardiomyocytes that exhibit normal action potentials (AP) under control conditions. Variability in ion channel densities may explain differences in this susceptibility to repolarization abnormalities. Here, we quantify the importance of key ionic mechanisms determining repolarization abnormalities following ionic block in human cardiomyocytes yielding normal APs under control conditions.Methods and Results: Sixty two AP recordings from non-diseased human heart preparations were used to construct a population of human ventricular models with normal APs and a wide range of ion channel densities. Multichannel ionic block was applied to investigate susceptibility to repolarization abnormalities. IKr block was necessary for the development of repolarization abnormalities. Models that developed repolarization abnormalities over the widest range of blocks possessed low Na+/K+ pump conductance below 50% of baseline, and ICaL conductance above 70% of baseline. Furthermore, INaK made the second largest contribution to repolarizing current in control simulations and the largest contribution under 75% IKr block. Reversing intracellular Na+ overload caused by reduced INaK was not sufficient to prevent abnormalities in models with low Na+/K+ pump conductance, while returning Na+/K+ pump conductance to normal substantially reduced abnormality occurrence, indicating INaK is an important repolarization current.Conclusions: INaK is an important determinant of repolarization abnormality susceptibility in human ventricular cardiomyocytes, through its contribution to repolarization current rather than homeostasis. While we found IKr block to be necessary for repolarization abnormalities to occur, INaK decrease, as in disease, may amplify the pro-arrhythmic risk of drug-induced IKr block in humans.

To estimate dry deposition flux of atmospheric water-soluble nitrogen (N), including ammonium (NH4+), nitrate (NO3−), and water-soluble organic nitrogen (WSON), aerosol samples were collected over the subarctic western North Pacific Ocean in the summer of 2016 aboard the Korean icebreaker IBR/V Araon. During the cruise, concentrations of NH4+, NO3−, and WSON in bulk (fine + coarse) aerosols ranged from 0.768 to 25.3, 0.199 to 5.94, and 0.116 to 14.7 nmol m−3, respectively. Contributions of NH4+, NO3−, and WSON to total water-soluble N represented ~74%, ~17%, and ~9%, respectively. Water-soluble N concentrations showed a strong gradient from the East Asian continent to the subarctic western North Pacific Ocean, indicating that water-soluble N species were mainly derived from anthropogenic or terrestrial sources. During sea fog events, coarse mode NO3− was likely to be scavenged more efficiently by fog droplets than fine mode NO3−; besides, WSON was detected only in fine mode, suggesting that there may have been a significant influence of sea fog on WSON, such as the photochemical conversion of WSON into inorganic N. Mean dry deposition flux for water-soluble total N (6.3 ± 9.4 µmol m−2 d−1) over the subarctic western North Pacific Ocean was estimated to support a minimum carbon uptake of 42 ± 62 µmol C m−2d−1 by using the Redfield C/N ratio of 6.625.

AIMS:Human atrial electrophysiology exhibits high inter-subject variability in both sinus rhythm (SR) and chronic atrial fibrillation (cAF) patients. Variability is however rarely investigated in experimental and theoretical electrophysiological studies, thus hampering the understanding of its underlying causes but also its implications in explaining differences in the response to disease and treatment. In our study, we aim at investigating the ability of populations of human atrial cell models to capture the inter-subject variability in action potential (AP) recorded in 363 patients both under SR and cAF conditions. METHODS AND RESULTS:Human AP recordings in atrial trabeculae (n = 469) from SR and cAF patients were used to calibrate populations of computational SR and cAF atrial AP models. Three populations of over 2000 sampled models were generated, based on three different human atrial AP models. Experimental calibration selected populations of AP models yielding AP with morphology and duration in range with experimental recordings. Populations using the three original models can mimic variability in experimental AP in both SR and cAF, with median conductance values in SR for most ionic currents deviating less than 30% from their original peak values. All cAF populations show similar variations in G(K1), G(Kur) and G(to), consistent with AF-related remodeling as reported in experiments. In all SR and cAF model populations, inter-subject variability in I(K1) and I(NaK) underlies variability in APD90, variability in I(Kur), I(CaL) and I(NaK) modulates variability in APD50 and combined variability in Ito and I(Kur) determines variability in APD20. The large variability in human atrial AP triangulation is mostly determined by I(K1) and either I(NaK) or I(NaCa) depending on the model. CONCLUSION:Experimentally-calibrated human atrial AP models populations mimic AP variability in SR and cAF patient recordings, and identify potential ionic determinants of inter-subject variability in human atrial AP duration and morphology in SR versus cAF.

Variability is observed at all levels of cardiac electrophysiology. Yet, the underlying causes and importance of this variability are generally unknown, and difficult to investigate with current experimental techniques. The aim of the present study was to generate populations of computational ventricular action potential models that reproduce experimentally observed intercellular variability of repolarisation (represented by action potential duration) and to identify its potential causes. A systematic exploration of the effects of simultaneously varying the magnitude of six transmembrane current conductances (transient outward, rapid and slow delayed rectifier K(+), inward rectifying K(+), L-type Ca(2+), and Na(+)/K(+) pump currents) in two rabbit-specific ventricular action potential models (Shannon et al. and Mahajan et al.) at multiple cycle lengths (400, 600, 1,000 ms) was performed. This was accomplished with distributed computing software specialised for multi-dimensional parameter sweeps and grid execution. An initial population of 15,625 parameter sets was generated for both models at each cycle length. Action potential durations of these populations were compared to experimentally derived ranges for rabbit ventricular myocytes. 1,352 parameter sets for the Shannon model and 779 parameter sets for the Mahajan model yielded action potential duration within the experimental range, demonstrating that a wide array of ionic conductance values can be used to simulate a physiological rabbit ventricular action potential. Furthermore, by using clutter-based dimension reordering, a technique that allows visualisation of multi-dimensional spaces in two dimensions, the interaction of current conductances and their relative importance to the ventricular action potential at different cycle lengths were revealed. Overall, this work represents an important step towards a better understanding of the role that variability in current conductances may play in experimentally observed intercellular variability of rabbit ventricular action potential repolarisation.

Differences in mRNA expression levels have been observed in failing versus non-failing human hearts for several membrane channel proteins and accessory subunits. These differences may play a causal role in electrophysiological changes observed in human heart failure and atrial fibrillation, such as action potential (AP) prolongation, increased AP triangulation, decreased intracellular calcium transient (CaT) magnitude and decreased CaT triangulation. Our goal is to investigate whether the information contained in mRNA measurements can be used to predict cardiac electrophysiological remodeling in heart failure using computational modeling. Using mRNA data recently obtained from failing and non-failing human hearts, we construct failing and non-failing cell populations incorporating natural variability and up/down regulation of channel conductivities. Six biomarkers are calculated for each cell in each population, at cycle lengths between 1500 ms and 300 ms. Regression analysis is performed to determine which ion channels drive biomarker variability in failing versus non-failing cardiomyocytes. Our models suggest that reported mRNA expression changes are consistent with AP prolongation, increased AP triangulation, increased CaT duration, decreased CaT triangulation and amplitude, and increased delay between AP and CaT upstrokes in the failing population. Regression analysis reveals that changes in AP biomarkers are driven primarily by reduction in I[Formula: see text], and changes in CaT biomarkers are driven predominantly by reduction in I(Kr) and SERCA. In particular, the role of I(CaL) is pacing rate dependent. Additionally, alternans developed at fast pacing rates for both failing and non-failing cardiomyocytes, but the underlying mechanisms are different in control and heart failure.

Left-to-right ventricular (LV/RV) differences in repolarization have been implicated in lethal arrhythmias in animal models. Our goal is to quantify LV/RV differences in action potential duration (APD) and APD rate adaptation and their contribution to arrhythmogenic substrates in the in vivo human heart using combined in vivo and in silico studies. Electrograms were acquired from 10 LV and 10 RV endocardial sites in 15 patients with normal ventricles. APD and APD adaptation were measured during an increase in heart rate. Analysis of in vivo electrograms revealed longer APD in LV than RV (207.8 ± 21.5 vs 196.7 ± 20.1 ms; P

"Hagamos visible la dirección de personas" es un proyecto de innovación que fue llevado a la práctica en todos los grupos de 2 º año de grado de los cursos de Dirección de Personas, en la Facultad de Ciencias Sociales. El proyecto involucró a todos los profesores que imparten este curso, y se organizó en torno al aprendizaje cooperativo. El objetivo de este proyecto fue que los estudiantes entendieran y aprendieran, de una manera lúdica, los fundamentos de la Gestión de Personas. Con este fin, los estudiantes organizados en equipos, crearon un video documental y un caso que debían reflejar una de las siguientes áreas de conocimiento contenida en el plan de estudios: diseño de puestos de trabajo, reclutamiento y selección, formación, evaluación del desempeño y motivación. Para preparar el contenido del video, los estudiantes utilizaron recursos bibliográficos y audiovisuales y se trabajó con la técnica de rol. Una vez que los videos se terminaron, los estudiantes compartieron sus conocimientos adquiridos mediante la puesta en común de su trabajo y resolvieron los casos desarrollados por los otros grupos. Las competencias desarrolladas fueron: el trabajo en equipo, la empatía, la tolerancia, la toma de decisiones, la responsabilidad y la creatividad. Treinta videos fueron presentados a concurso y publicado en el V Seminario de Recursos Humanos "Talentum".ABSTRACTLet´s Make People Management Visible.“Let’s make people management visible” is an innovation project that was run in all 2nd year groups for the Managing People courses, within the Social Science Faculty. The project involved all the teachers who taught this course, and was organized around cooperative learning. The objective of this project was the students to understand and learn, in a playful way, the basics of People Management. To this end, students organized in teams, created a video documentary and a business case that should reflect one of the following areas of knowledge contained in the syllabus: job design, recruitment and selection, training, performance appraisal and motivation. To prepare the content for the video, students used bibliographic and audiovisual resources and they worked with the role- playing technique. After the videos were finished, students shared their acquired knowledge by putting in common their work and by solving the business cases developed by the other groups. The competencies developed were: teamwork, empathy, tolerance, decision making, responsibility and creativity. Thirty videos were submitted to the contest and published in the V Seminar on Human Resources, "Talentum."

Background: The Nav 1.8 sodium channel has a key role in generating repetitive action potentials in nociceptive human dorsal root ganglion neurons. Nav 1.8 is differentiated from other voltage-gated sodium channels by its unusually slow inactivation kinetics and depolarised voltage-dependence of activation. These features are particularly pronounced in the human Nav 1.8 channel and allow the channel to remain active during repolarisation. Gain-of-function mutations in Nav 1.8 have been linked to neuropathic pain and selective blockers of Nav 1.8 have been developed as potential new analgesics. However, it is not well understood how modulating the Nav 1.8 conductance alters neuronal excitability and how this depends on the balance of other ion channels expressed by nociceptive neurons. Methods: To investigate this, we developed a novel computational model of the human dorsal root ganglion neuron and used it to construct a population of models that mimicked inter-neuronal heterogeneity in ionic conductances and action potential morphology Results: By simulating changes to the Nav 1.8 conductance in the population of models, we found that moderately increasing the Nav 1.8 conductance led to increased firing rate, as expected, but increasing Nav 1.8 conductance beyond an inflection point caused firing rate to decrease. We found that the delayed rectifier and M-type potassium conductances were also critical for determining neuronal excitability. In particular, altering the delayed rectifier potassium conductance shifted the position of the Nav 1.8 inflection point and therefore the relationship between Nav 1.8 conductance and firing rate. Conclusions: Our results suggest that the effects of modulating Nav 1.8 in a nociceptive neuron can depend significantly on other conductances, particularly potassium conductances.