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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 electrical 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.

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.

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 QA on Clinical and Nonclinical Evaluation of QT/QTc Interval Prolongation and Proarrhythmic Potential promotes human

Cardiomyopathies have unresolved genotype-phenotype relationships and lack disease-specific treatments. Here we identify genotype-specific pathomechanisms and therapeutic targets combining experimental hiPSC-CM modelling and human-based cardiac electromechanical in-silico modelling and simulation bridging from specific mutations to clinical biomarkers. We select hypertrophic cardiomyopathy as a challenge for this approach and study genetic variations that mutate proteins of the thick (MYH7R403Q/+) and thin filaments (TNNT2R92Q/+, TNNI3R21C/+) of the cardiac sarcomere. We show that destabilisation of myosin super relaxation drives disease in MYH7R403Q/+ with secondary effects on thin filament activation, which are corrected by Mavacamten. Thin filament variants TNNT2R92Q/+ and TNNI3R21C/+ share calcium regulation-related pathomechanisms, for which Mavacamten provides incomplete salvage. 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.

Highlights • Regulators now consider also evidences produced in silico. • We need accepted methods to evaluate the credibility of models. • In this paper we describe the use of the ASME V&V-40 technical standard. • We also discuss its application to various types of modelling methods., Historically, the evidences of safety and efficacy that companies provide to regulatory agencies as support to the request for marketing authorization of a new medical product have been produced experimentally, either in vitro or in vivo. More recently, regulatory agencies started receiving and accepting evidences obtained in silico, i.e. through modelling and simulation. However, before any method (experimental or computational) can be acceptable for regulatory submission, the method itself must be considered “qualified” by the regulatory agency. This involves the assessment of the overall “credibility” that such a method has in providing specific evidence for a given regulatory procedure. In this paper, we describe a methodological framework for the credibility assessment of computational models built using mechanistic knowledge of physical and chemical phenomena, in addition to available biological and physiological knowledge; these are sometimes referred to as “biophysical” models. Using guiding examples, we explore the definition of the context of use, the risk analysis for the definition of the acceptability thresholds, and the various steps of a comprehensive verification, validation and uncertainty quantification process, to conclude with considerations on the credibility of a prediction for a specific context of use. While this paper does not provide a guideline for the formal qualification process, which only the regulatory agencies can provide, we expect it to help researchers to better appreciate the extent of scrutiny required, which should be considered early on in the development/use of any (new) in silico evidence.

AimsSudden death after myocardial infarction (MI) is associated with electrophysiological heterogeneities and ionic remodelling, which are reflected as variable phenotypes. Low ejection fraction (EF) is used in risk stratification, but its mechanistic links with the post-MI electrophysiological heterogeneities are unknown. We aim to unravel how phenotypic ECG and EF variability in post-MI may be explained by the impact of ionic remodelling on spatio-temporal dispersion of repolarization using human biventricular electromechanical modelling and simulation.Methods and ResultsMultiple post-MI ECG phenotypes observed clinically were investigated using multi-scale modelling and simulation, calibrated and evaluated using experimental and clinical data. Acute stage T-wave inversion was caused by delayed repolarization in the epicardial border zone (BZ), and Brugada phenocopy was generated by repolarization delay and activation failure in the BZ. Upright tall T-waves in chronic MI represented large repolarisation dispersion between BZ and surrounding tissue, which promoted ectopic propagation at fast pacing. T-wave morphology alternans were present at fast-pacing due to prolonged refractoriness in the mid-myocardium. Post-MI ionic remodelling reduced EF through inhibition of calcium transient amplitude, but the EF at resting heart rate was not sensitive to the extent of repolarisation heterogeneity and the risk of repolarisation abnormalities at fast pacing.ConclusionsIn acute post-MI, ionic remodelling and its effect on refractoriness and propagation failure in the BZ have a strong impact on phenotypic ECG variability, whereas in chronic post-MI, the repolarisation dispersion across the BZ is crucial. T-wave and QT abnormalities are better indicators of repolarisation heterogeneities than EF in post-MI.

Human-based computational modelling and simulation are powerful tools to accelerate the mechanistic understanding of cardiac patho-physiology, and to develop and evaluate therapeutic interventions. The aim of this study is to calibrate and evaluate human ventricular electro-mechanical models for investigations on the effect of the electro-mechanical coupling and pharmacological action on human ventricular electrophysiology, calcium dynamics, and active contraction. The most recent models of human ventricular electrophysiology, excitation-contraction coupling, and active contraction were integrated, and the coupled models were calibrated using human experimental data. Simulations were then conducted using the coupled models to quantify the effects of electro-mechanical coupling and drug exposure on electrophysiology and force generation in virtual human ventricular cardiomyocytes and tissue. The resulting calibrated human electro-mechanical models yielded active tension, action potential, and calcium transient metrics that are in agreement with experiments for endocardial, epicardial, and mid-myocardial human samples. Simulation results correctly predicted the inotropic response of different multichannel action reference compounds and demonstrated that the electro-mechanical coupling improves the robustness of repolarisation under drug exposure compared to electrophysiology-only models. They also generated additional evidence to explain the partial mismatch between in-silico and in-vitro experiments on drug-induced electrophysiology changes. The human calibrated and evaluated modelling and simulation framework constructed in this study opens new avenues for future investigations into the complex interplay between the electrical and mechanical cardiac substrates, its modulation by pharmacological action, and its translation to tissue and organ models of cardiac patho-physiology.

This white paper presents principles for validating proarrhythmia risk prediction models for regulatory use as discussed at the In Silico Breakout Session of a Cardiac Safety Research Consortium/Health and Environmental Sciences Institute/US Food and Drug Administration–sponsored Think Tank Meeting on May 22, 2018. The meeting was convened to evaluate the progress in the development of a new cardiac safety paradigm, the Comprehensive in Vitro Proarrhythmia Assay (CiPA). The opinions regarding these principles reflect the collective views of those who participated in the discussion of this topic both at and after the breakout session. Although primarily discussed in the context of in silico models, these principles describe the interface between experimental input and model‐based interpretation and are intended to be general enough to be applied to other types of nonclinical models for proarrhythmia assessment. This document was developed with the intention of providing a foundation for more consistency and harmonization in developing and validating different models for proarrhythmia risk prediction using the example of the CiPA paradigm.

The electrocardiogram is the most widely used diagnostic tool that records the electrical activity of the heart and, therefore, its use for identifying markers for early diagnosis and detection is of paramount importance. In the last years, the huge increase of electronic health records containing a systematised collection of different type of digitalised medical data, together with new tools to analyse this large amount of data in an efficient way have re-emerged the field of machine learning in healthcare innovation. This review describes the most recent machine learning-based systems applied to the electrocardiogram as well as pros and cons in the use of these techniques. Machine learning, including deep learning, have shown to be powerful tools for aiding clinicians in patient screening and risk stratification tasks. However, they do not provide the physiological basis of classification outcomes. Computational modelling and simulation can help in the interpretation and understanding of key physiologically meaningful ECG biomarkers extracted from machine learning techniques.

Safety and efficacy testing is a crucial part of the drug development process, and several different methods are used to obtain the necessary data (e.g. in vitro testing, animal trials and clinical trials). Our group has been investigating the potential of modelling and simulation as an alternative approach to some of the methods used for testing drugs for cardiac effects. To achieve our goal of developing and promoting novel approaches in drug development, we formed multidisciplinary collaborations that included clinicians, computer scientists and biologists. Our in silico models are based on human data (e.g. magnetic resonance images, electrocardiogram) and on current knowledge of human electrophysiology, thus generating predictions that are directly applicable to humans. Such models are a particularly powerful tool because they encompass different sources of population heterogeneity, which is crucial for drug testing and for assessing how interindividual variability might affect clinical endpoints. Our group has shown that computer modelling can be used to predict the effects of a test drug in a virtual population or in combination with machine learning to predict different phenotypes when a drug is given to a diseased population. Furthermore, our user-friendly drug testing software is freely available and is being adopted by industry in their drug development process. We have been engaging with industry and regulators to show that our models can contribute to the replacement of animals in drug development. Our ambition is to generate models for simulation of different diseases and therapies for investigations from subcellular to whole organ.

Hypertrophic cardiomyopathy (HCM) affects as many as ~1 in 500 individuals, and is often typified by hyperdynamic contraction and poor cellular relaxation. HCM can be caused by mutations in a variety of key contractile proteins of the sarcomere. A large proportion of these variants are found in MYBPC3, MYH7, TNNT2, and TNNI3. These genes encode proteins that control cardiac muscle contraction at the thick (MYBPC3 and MYH7) and thin filaments (TNNT2 and TNNI3) of the sarcomere. In this study we use human induced pluripotent stem cell derived cardiomyocytes to model HCM across all of these genes. We do this to define key mechanistic differences between thick and thin filament HCM. We define sarcomeric contractility (SarcTrack) calcium transients (CalTrack) and myosin states using the mant-ATP assay. We use the parametric data from these experimental studies in iPSC-CMs to model possible disease mechanisms in silico. Our experimental analysis highlights that both thick and thin filament HCM variants cause cellular hypercontractility, with slowed cellular relaxation. We find that thick filament HCM variants drive cellular HCM phenotypes by destabilising the myosin interacting heads motif (IHM), showing a marked reduction in the super relaxed state of myosin. Counterintuitively thin filament based HCM variants show a reduction in DRX myosin. When applying Mavacamten the allosteric myosin ATPase inhibitor to our thin and thick filament HCM variant iPSC-CMs we find a dichotomy of cellular responses. The thick filament variants studied all show a clear resolution of cellular HCM. However, not all cellular phenotypes of thin filament HCM are corrected by Mavacamten treatment, although there is benefit. We conclude that causal mechanisms of thick filament HCM are well corrected at the molecular and cellular level by Mavacamten, but these causal mechanisms in thin filament based HCM are not suitably corrected. We highlight key mechanistic pharmacological targets for thin filament variants that could add cellular benefit to HCM phenotype resolution.

Supplemental Digital Content is available in the text., Rationale: Calcium transient analysis is central to understanding inherited and acquired cardiac physiology and disease. Although the development of novel calcium reporters enables assays of CRISPR/Cas-9 genome-edited induced pluripotent stem cell–derived cardiomyocytes and primary adult cardiomyocytes, existing calcium-detection technologies are often proprietary and require specialist equipment, whereas open-source workflows necessitate considerable user expertise and manual input. Objective: We aimed to develop an easy to use open-source, adaptable, and automated analysis pipeline for measuring cellular calcium transients, from image stack to data output, inclusive of cellular identification, background subtraction, photobleaching correction, calcium transient averaging, calcium transient fitting, data collation, and aberrant behavior recognition. Methods and Results: We developed CalTrack, a MatLab-based algorithm, to monitor fluorescent calcium transients in living cardiomyocytes, including isolated single cells or those contained in 3-dimensional tissues or organoids, and to analyze data acquired using photomultiplier tubes or employing line scans. CalTrack uses masks to segment cells allowing multiple cardiomyocyte transients to be measured from a single field of view. After automatically correcting for photobleaching, CalTrack averages and fits a string of transients and provides parameters that measure time to peak, time of decay, tau, peak fluorescence/baseline fluorescence (Fmax/F0), and others. We demonstrate the utility of CalTrack in primary and induced pluripotent stem cell–derived cell lines in response to pharmacological compounds and in phenotyping cells carrying hypertrophic cardiomyopathy variants. Conclusions: CalTrack, an open-source tool that runs on a local computer, provides automated high-throughput analysis of calcium transients in response to development, genetic or pharmacological manipulations, and pathological conditions. We expect that CalTrack analyses will accelerate insights into physiological and abnormal calcium homeostasis that influence diverse aspects of cardiomyocyte biology.

INTRODUCTION AND OBJECTIVEPost-COVID syndrome (PCS) is a poorly-known entity. Underlying low-grade inflammation (LGI) has been theorized as one of its pathophysiological mechanisms. We aimed to investigate a possible relationship between PCS and an increase in inflammation markers, in a sex-stratified analysis.PARTICIPANTS AND METHODSMild cases of COVID-19 according to the WHO classification followed-up in a Primary Care Center, were included. We collected epidemiological data (age, sex, body mass index -BMI-, smoking, and comorbidities -Charlson index-), variables of the acute COVID-19 episode, and data at 3 months of follow-up (clinical manifestations and inflammatory markers). Serum C-reactive protein (CRP), neutrophil and lymphocyte counts, neutrophil/lymphocyte ratio (NLR), lactate dehydrogenase (LDH), ferritin, fibrinogen, and D-dimer levels were analyzed. Low-grade inflammation (LGI) was defined as serum CRP between >0.3 and RESULTSWe analyzed 121 subjects with mild COVID-19 (56.2% women; mean age 46 years). The most common symptom in the acute episode was fever (60.3%), while it was fatigue in PCS (42.8%). Prevalence of PCS was 35.8% in women and 20.8% in men (p = 0.07).In women, after controlling for age, BMI, smoking, and comorbidities, the D1, D3, and D4 indices were consistently associated with PCS, with ORs of 5.14 (95% CI, 1.6-16.4), 4.20 (95% CI, 1.3-13.3), and 4.12 (95% CI, 1.3-13.1), respectively; in patients with post-COVID anosmia and ageusia, neutrophils were significantly elevated (3.43±0.3 vs 2.58±0.1; p = 0.014, and 3.89±0.3 vs 2.59±0.1; p = 0.002,respectively), after adjusting for confounders.In men, the D2 and D5 indices were associated with PCS, with adjusted ORs of 10.1 (95% CI, 1.2-85) and 17.5 (95% CI, 2-153), respectively. Furthermore, serum CRP in the LGI range was associated with PCS [adjusted OR=12.9 (95% CI, 1.3-121)], and in post-COVID persistent fatigue, the neutrophil count was significantly elevated (4.68±0.6 vs 3.37±0.1; p = 0.041), after controlling for confounders.CONCLUSIONSConsistent associations among PCS, anosmia, ageusia, and fatigue, with slight -but significant-elevated levels of inflammatory markers, have been observed. The neutrophil count was the most frequently involved marker. Sex-stratified analyses showed relevant differences between women and men concerning PCS and serum inflammatory markers.

Funding Acknowledgements Type of funding sources: Public grant(s) – National budget only. Main funding source(s): NC3Rs Infrastructure for Impart Award (NC/P001076/1) Wellcome Trust Senior Research Fellowship in Basic Biomedical Sciences (214290/Z/18/Z) Background Human-based computer modelling and simulations have been widely used in cardiac electrophysiology, to provide a better understanding of the ionic mechanisms underlying risk of arrhythmias, and their modulation by drugs and diseased conditions. More recently, multiscale computer models of human cardiac electro-mechanics have been developed. These models provide the means for a comprehensive investigation of action potential, calcium transient, active force, and their variability in the population, and can predict drug-induced contractility changes in humans. Purpose This study aims to perform a computational investigation of variability in human cardiac contractility biomarkers and their modulation by well-known drugs. Methods We considered the most recent model of human ventricular electro-mechanics (Margara et al. 2020). We constructed a population of 300 cells by randomly varying the main ionic currents in the model, to represent the biological variability observed in human experimental data. We then simulated the effect of 10 reference compounds, 6 of which with known pro-arrhythmic risk. Simulations were performed at 1 Hz for multiple drug concentrations, using the Virtual Assay software. A set of action potential, calcium transient and active force biomarkers were computed, as well as the electro-mechanical window, and the occurrence of early after-depolarisations and after-contractions in the virtual population. Simulation results were compared against clinical risk of drug-induced arrhythmias and experimental recording from human ventricular myocytes from literature. Results Overall, biomarker variability in the virtual population increased following drug application compared to control conditions. All compounds had a negative inotropic effect in simulation, with a marked decrease of the active tension peak, e.g. -80% for nifedipine 8 nM. This is in agreement with human experimental data for all compounds except Dofetilide, for which no inotropic effect was observed in vitro. Compounds with known risk of arrhythmias provoked early after-depolarisations, which in turn caused after-contractions. Their occurrence in the population increased together with the drug concentration, e.g. 3.6% at 0.16 µM and 48% at 0.48 µM for droperidol. In addition, these compounds also displayed prolonged action potential and calcium transient, and a shortening of the electro-mechanical window, all known biomarkers of pro-arrhythmia. Conclusions We evaluated the effect and the cardiac safety of 10 reference compounds in a population of 300 human ventricular electro-mechanical models. Simulation results were in good agreement with experimental data in human ventricular cardiomyocytes, and they allowed to identify the compounds with a known pro-arrhythmic risk based on drug-induced early after-depolarisations and after-contractions. This methodology provides new insights into variability in human cardiac contractility and its modulation by drugs.

Funding Acknowledgements Type of funding sources: Public grant(s) – National budget only. Main funding source(s): Wellcome Trust Background Sudden cardiac death (SCD) occurs in both acute and chronic stages post myocardial infarction (MI), and the left ventricular ejection fraction (LVEF) and electrocardiogram (ECG) characteristics are important biomarkers for clinical decision making. While various ionic remodelling has been reported in literature at various stages post-MI, the effect of them on clinical biomarkers have not been fully explored. Purpose Evaluate the effects of cellular ionic remodelling in acute and chronic post myocardial infarction on ECG and LVEF biomarkers through computational modelling and simulations of human biventricular electromechanics. Methods An electromechanical coupled biventricular model with ToR-ORd (Tomek 2019) human electrophysiology coupled with human excitation-contraction machinery (Land 2017) and orthotropic passive mechanics (Holzapfel 2009) was used as baseline model. The 12-lead ECG were simulated at standard body-surface electrode locations, and the biventricular pressure volume loop was simulated to quantify the simulated LVEF. A cardiac magnetic resonance (CMR) derived human biventricular geometry (Strocchi 2020) was used in combination with rigidly aligned torso geometry (Minchole 2019). An anterior sub-endocardial infarction was delineated with infarct, border zone (BZ) and remote zone (RZ) regions. For acute infarction, three types of BZ ionic remodelling from literature, and their effects on simulated LVEF and ECG characteristics were quantified. For chronic infarction, a single chronic BZ ionic remodelling was combine with two different models of RZ ionic remodelling from literature, and the effects of these remodelling on the simulated LVEF and ECG were quantified. The electromechanical properties of the sub-endocardial infarct region did not significantly affect simulated ECG or LVEF biomarkers. Results For the acute phase, simulations showed pre-cordial ECG abnormalities for all three BZ models, with T-wave inversion and QT prolongation (80 ms) in BZ1, ST-segment elevation with T-wave inversion in BZ2, and decreased T-wave amplitude in BZ3. Activation maps showed conduction block in BZ2 simulations, leading to ST-segment elevation. Repolarisation maps showed high dispersion in BZ1 simulations, leading to T-wave inversion. LVEF for BZ2 decreased by 4% (from 57% in control) due to conduction block in BZ and lack of contraction in that region, LVEF remained constant for BZ1 and BZ3 simulations. For the chronic phase, there was QT prolongation in both RZ1 (80 ms) and RZ2 (170 ms) as well as decreased T-wave amplitude, reflected by elevated repolarisation dispersion. LVEF was not significantly altered for either simulations. Conclusions Post-MI ionic remodelling at the acute and chronic stages cause varying degrees of dispersion of repolarisation and T-wave and ST-segment abnormalities, with minimal effect on mechanical function, except in the case of severe conduction abnormality. Abstract Figure.

Funding Acknowledgements Type of funding sources: Public grant(s) – EU funding. Main funding source(s): European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement 764738. British Heart Foundation Intermediate Basic Science Fellowship (FS/17/22/32644). Background The pathogenic TNNI3R21C/+ variant causes malignant hypertrophic cardiomyopathy (HCM) with high incidence of sudden cardiac death, even in individuals absent of hypertrophy. There is evidence to support a known biophysical defect in the protein, yet the cellular mechanisms that precipitate adverse clinical outcomes remain unclear. Purpose We aim to computationally model and map the TNNI3R21C/+ cellular phenotype observed in induced pluripotent stem cell derived cardiomyocytes (iPSC-CMs) to human disease, thereby explaining the key mechanisms driving HCM in TNNI3R21C/+ variant carriers. Methods Wild-type (WT) and TNNI3R21C/+ iPSC-CMs were characterised by calcium transient analysis and direct sarcomere tracking to assess cellular contraction and relaxation. In-vitro data was used to inform the in-silico modelling of human cardiomyocytes. We constructed an in-silico population of WT adult cardiomyocytes and used it to transform the in-vitro data into corresponding adult phenotypes by means of a novel iPSC-to-adult data mapping. We tested the hypothesis that the abnormal TNNI3R21C/+ phenotype observed in iPSC-CMs would be explained by alterations in calcium affinity of troponin and increased myofilament calcium sensitivity. Results Analysis of in-vitro iPSC-CM data showed that TNNI3R21C/+ cells exhibit increased contractility with slowed relaxation when compared to WT. They also exhibited a faster rise in the calcium transient with a slowed calcium decay in comparison to WT. The in-silico adult TNNI3R21C/+ phenotype from the iPSC-to-adult mapping replicated the abnormalities observed in iPSC-CMs. The WT in-silico population accurately covered the ranges of electromechanical biomarkers providing a representative cohort of physiological variability. The TNNI3R21C/+ calcium phenotype could be recovered by our in-silico mutant models. Simulation results suggest that calcium abnormalities in TNNI3R21C/+ are a direct consequence of abnormal calcium buffering by thin filaments, mediated by increases in calcium affinity of troponin and myofilament calcium sensitivity. The TNNI3R21C/+ phenotype could not be recovered if these two factors were considered in isolation. Corresponding contractility analyses of in-silico models showed that the calcium level changes caused by the TNNI3R21C/+ phenotype are associated with hypercontractility and diastolic dysfunction, well-known hallmarks of HCM, which were also observed in the iPSC-CM model of disease. Conclusions This study showcases human-based computational and experimental methodologies that unearth direct mechanistic explanations of phenotypes driven by the TNNI3R21C/+ HCM variant. We show that the TNNI3R21C/+ HCM-causing mutation exhibits multifactorial remodelling of troponin calcium affinity and myofilament calcium sensitivity. Unearthing mechanistic pathways in mutation-specific HCM will be key to develop effective pharmacological interventions for a wide variety of understudied variants.

Conclusions The project highlighted considerations for working with Latino communities, demonstrated the importance of community partners to conduct effective community-engaged research, and explored effectiveness of a unique partnership that relied on clinical expertise and nonclinical community-engaged research expertise. Findings illuminate effort required to implement clinical telemedicine interventions in community settings. Background Diabetes prevalence is increasing rapidly and disproportionately affects Latinos, who face greater risk for complications such as diabetic neuropathy. Objectives This project partnered a Latino community center with clinical and community-engaged researchers to test the feasibility of telemedicine to provide retinal screenings to urban Latinos. Further, researchers aimed to understand cultural implications of using telemedicine with this population. Methods Pre- and post-study focus groups identified study participants' perceptions of screening process. Results The research team concluded that telemedicine is feasible for providing early detection and care to urban Latino populations, and identified processes for conducting clinical trials within community settings.

Background: Perivascular spaces (PVS) have an important role in the elimination of metabolic waste from the brain. It has been hypothesized that the enlargement of PVS (ePVS) could be affected by pathophysiological mechanisms involved in Alzheimer's disease (AD), such as abnormal levels of CSF biomarkers. However, the relationship between ePVS and these pathophysiological mechanisms remains unknown. Objective: We aimed to investigate the association between ePVS and CSF biomarkers of several pathophysiological mechanisms for AD. We hypothesized that ePVS will be associated to CSF biomarkers early in the AD continuum (i.e., amyloid positive cognitively unimpaired individuals). Besides, we explored associations between ePVS and demographic and cardiovascular risk factors. Methods: The study included 322 middle-aged cognitively unimpaired participants from the ALFA + study, many within the Alzheimer's continuum. NeuroToolKit and Elecsys® immunoassays were used to measure CSF Aβ42, Aβ40, p-tau and t-tau, NfL, neurogranin, TREM2, YKL40, GFAP, IL6, S100, and α-synuclein. PVS in the basal ganglia (BG) and centrum semiovale (CS) were assessed based on a validated 4-point visual rating scale. Odds ratios were calculated for associations of cardiovascular and AD risk factors with ePVS using logistic and multinomial models adjusted for relevant confounders. Models were stratified by Aβ status (positivity defined as Aβ42/40 < 0.071). Results: The degree of PVS significantly increased with age in both, BG and CS regions independently of cardiovascular risk factors. Higher levels of p-tau, t-tau, and neurogranin were significantly associated with ePVS in the CS of Aβ positive individuals, after accounting for relevant confounders. No associations were detected in the BG neither in Aβ negative participants. Conclusions: Our results support that ePVS in the CS are specifically associated with tau pathophysiology, neurodegeneration, and synaptic dysfunction in asymptomatic stages of the Alzheimer's continuum. The project leading to these results has received funding from “la Caixa” Foundation (ID 100010434), under agreement LCF/PR/GN17/50300004 and the Alzheimer’s Association and an international anonymous charity foundation through the TriBEKa Imaging Platform project (TriBEKa-17–519007). Additional support has been received from the Health Department of the Catalan Government (Health Research and Innovation Strategic Plan (PERIS) 2016–2020 grant# SLT002/16/00201) and the Universities and Research Secretariat, Ministry of Business and Knowledge of the Catalan Government under the grant no. 2017-SGR-892. All CRG authors acknowledge the support of the Spanish Ministry of Science, Innovation and Universities to the EMBL partnership, the Centro de Excelencia Severo Ochoa, and the CERCA Programme/Generalitat de Catalunya. NV-T is funded by a post-doctoral grant, Juan de la Cierva Programme (FJC2018-038085-I), Ministry of Science and Innovation– Spanish State Research Agency. MS-C received funding from the European Union’s Horizon 2020 Research and Innovation Program under the Marie Sklodowska-Curie action grant agreement No 752310, and currently receives funding from Instituto de Salud Carlos III (PI19/00155) and from the Spanish Ministry of Science, Innovation and Universities (Juan de la Cierva Programme grant IJC2018-037478-I). EMAU is supported by the Spanish Ministry of Science, Innovation and Universities—Spanish State Research Agency (RYC2018-026053-I). OGR is supported by the Spanish Ministry of Science, Innovation and Universities (FJCI-2017–33437). JDG is supported by the Spanish Ministry of Science and Innovation (RYC-2013–13054). KB is supported by the Swedish Research Council (#2017–00915), the Alzheimer Drug Discovery Foundation (ADDF), USA (#RDAPB-201809–2016615), the Swedish Alzheimer Foundation (#AF-742881), Hjärnfonden, Sweden (#FO2017-0243), the Swedish state under the agreement between the Swedish government and the County Councils, the ALF-agreement (#ALFGBG-715986), and European Union Joint Program for Neurodegenerative Disorders (JPND2019-466–236). HZ is a Wallenberg Scholar supported by grants from the Swedish Research Council (#2018–02532), the European Research Council (#681712), the Swedish state under the agreement between the Swedish government and the County Councils, the ALF-agreement (#ALFGBG-720931), the ADDF, USA (#201809–2016862), and the UK Dementia Research Institute at UCL.

The helix orientated fibres in the ventricular wall modulate the cardiac electromechanical functions. Experimental data of the helix angle through the ventricular wall have been reported from histological and image-based methods, exhibiting large variability. It is, however, still unclear how this variability influences electrocardiographic characteristics and mechanical functions of human hearts, as characterized through computer simulations. This paper investigates the effects of the range and transmural gradient of the helix angle on electrocardiogram, pressure-volume loops, circumferential contraction, wall thickening, longitudinal shortening and twist, by using state-of-the-art computational human biventricular modelling and simulation. Five models of the helix angle are considered based on in vivo diffusion tensor magnetic resonance imaging data. We found that both electrocardiographic and mechanical biomarkers are influenced by these two factors, through the mechanism of regulating the proportion of circumferentially-orientated fibres. With the increase in this proportion, the T-wave amplitude decreases, circumferential contraction and twist increase while longitudinal shortening decreases.

Sudden cardiac death was reported in both the acute stage and the chronic heart failure (HF) stage after myocardial infarction (MI). The goal of this study is to investigate the pro-arrhythmic cellular effects of post-MI electrophysiological remodelling for both the acute stage and the chronic stage, using human-based computer modelling and simulation. The ToR-ORd human ventricular cellular model was used as baseline, and a new formulation of the calcium activated potassium current was also included in order to reflect its enhanced expression in the HF stage. We constructed and calibrated populations of human ventricular cell models to represent electrophysiological variability of normal zone (NZ) myocytes. For the acute post-MI stage, three types of border zone (BZ) ionic remodelling were considered based on canine experimental data. For the chronic phase with the development of HF, ionic remodelling in BZ and the remote zone (RZ) were introduced based on minipig and human experiments. For both the acute stage and the chronic stage post-MI, simulations showed that both large and small pro-arrhythmic dispersion in action potential duration can be present between BZ and non-infarcted NZ or RZ, and the post-MI ionic remodelling led to weak calcium transient in the BZ.

In silico trials using multiscale and biophysically-detailed human models have proven to be a new powerful tool for proarrhythmic risk prediction. Our goal is to evaluate the consistency between in silico results using a novel human Purkinje model and experimental data obtained from rabbit Purkinje fibres. The effects of Diltiazem, Dofetilide, Risperidone, and Verapamil were evaluated through AP biomarkers, at 1 and 0.2 Hz. Drug-induced effects on the ion channels were simulated through a simple pore-block model using IC 50 values and Hill coefficients. Simulation results quantitatively reproduced the drug-induced effects experimentally observed for both Dofetilide and Risperidone. Simulations of Diltiazem and Verapamil correctly reproduced drug-induced effects observed experimentally in the early phase of repolarisation, but they showed AP prolongation instead of shortening. The interplay between Ca2+ and K+ current inhibition was identified as the leading cause of the discrepancy. The experimentally observed AP shortening was quantitively matched when not considering the effects on K+ current. In silico trials are a powerful tool for drug safety and efficacy assessment, and their performance requires careful evaluation of data describing drug-ionic current interactions since they critically affect the simulation results.

Sudden cardiac death (SCD) from ventricular arrhythmias is a leading cause of mortality. Accurate arrhythmic risk stratification is vital for preventative clinical interventions. Ejection fraction (EF) is the primary metric used, but its accuracy is under debate, as many SCD cases exhibit preserved EF. Thus, identifying clear links between EF and arrhythmic risk is critical. Here, as a step forward, we investigate the ionic processes determining cellular pro-arrhythmic mechanisms and their relationship with active tension. A population of 2500 human ventricular electromechanical cellular models was created, and stimulated to produce pro-arrhythmic behaviour. We quantified their susceptibility to develop early afterdepolarizations (EADs) and action potential duration (APD) shortening, as key arrhythmic markers. The relationship between both arrhythmic markers and tension amplitude was found to be highly dependent on ionic mechanism. Variability in L-type calcium current was the primary determinant of active tension and arrhythmia susceptibility, alongside SERCA and hERG expression. Models with low tension could exhibit both high and low EAD susceptibility. APD shortening, however, displayed a weak positive correlation with active tension amplitude.

Aims Develop, calibrate and evaluate with clinical data a human electromechanical modelling and simulation framework for multiscale, mechanistic investigations in healthy and post-myocardial infarction (MI) conditions, from ionic to clinical biomarkers. Methods and results Human healthy and post-MI electromechanical simulations were conducted with a novel biventricular model, calibrated and evaluated with experimental and clinical data, including torso/biventricular anatomy from clinical magnetic resonance, state-of-the-art human-based membrane kinetics, excitation–contraction and active tension models, and orthotropic electromechanical coupling. Electromechanical remodelling of the infarct/ischaemic region and the border zone were simulated for ischaemic, acute, and chronic states in a fully transmural anterior infarct and a subendocardial anterior infarct. The results were compared with clinical electrocardiogram and left ventricular ejection fraction (LVEF) data at similar states. Healthy model simulations show LVEF 63%, with 11% peak systolic wall thickening, QRS duration and QT interval of 100 ms and 330 ms. LVEF in ischaemic, acute, and chronic post-MI states were 56%, 51%, and 52%, respectively. In linking the three post-MI simulations, it was apparent that elevated resting potential due to hyperkalaemia in the infarcted region led to ST-segment elevation, while a large repolarization gradient corresponded to T-wave inversion. Mechanically, the chronic stiffening of the infarct region had the benefit of improving systolic function by reducing infarct bulging at the expense of reducing diastolic function by inhibiting inflation. Conclusion Our human-based multiscale modelling and simulation framework enables mechanistic investigations into patho-physiological electrophysiological and mechanical behaviour and can serve as testbed to guide the optimization of pharmacological and electrical therapies. This work was funded by a Wellcome Trust Fellowship in Basic Biomedical Sciences to B.R. (214290/Z/18/Z), Personalised In-Silico Cardiology (PIC) project, European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement 764738, the CompBioMed 1 and 2 Centre of Excellence in Computational Biomedicine (European Commission Horizon 2020 research and innovation programme, grant agreements No. 675451 and No. 823712), an NC3Rs Infrastructure for Impact Award (NC/P001076/1), the TransQST project (Innovative Medicines Initiative 2 Joint Undertaking under grant agreement No 116030, receiving support from the European Union’s Horizon 2020 research and innovation programme and EFPIA), and the Oxford BHF Centre of Research Excellence (RE/13/1/30181). This paper is part of a supplement supported by an unrestricted grant from the Theo-Rossi di Montelera (TRM) foundation.

Recently, our group published a new model of human ventricular cardiomyocyte named ToR-ORd (Tomek et al., 2019). Its development, calibration, and validation, were performed using a broad range of human experimental data and brought general insights into modelling of ionic channels. Model calibration ensured the reproduction of key physiological cellular features, with independent multiscale validation demonstrating a correct response to channel blocking drugs and pathophysiological remodelling.However, for very long simulations (several hours rather than minutes), the ToR-ORd simulations display a drift in its behaviour, caused by modelling chloride concentrations as constant values. This may be a limitation for simulations considering extremely long protocols, or for studies on model stability. To remedy this, we present here an updated version, termed ToR-ORd-dynCl, with dynamic representation of intracellular chloride. This model behaves very similarly to the original ToR-ORd, but with stable properties over long simulations and only a small increase in model complexity.

Funding: UK Engineering and Physical Sciences Research Council [grant number EP/N509711/1 (J.K.)]. Chaste (Cancer, Heart And Soft Tissue Environment) is an open source simulation package for the numerical solution of mathematical models arising in physiology and biology. To date, Chaste development has been driven primarily by applications that include continuum modelling of cardiac electrophysiology (‘Cardiac Chaste’), discrete cell-based modelling of soft tissues (‘Cell-based Chaste’), and modelling of ventilation in lungs (‘Lung Chaste’). Cardiac Chaste addresses the need for a high-performance, generic, and verified simulation framewor kfor cardiac electrophysiology that is freely available to the scientific community. Cardiac chaste provides a software package capable of realistic heart simulations that is efficient, rigorously tested, and runs on HPC platforms. Cell-based Chaste addresses the need for efficient and verified implementations of cell-based modelling frameworks, providing a set of extensible tools for simulating biological tissues. Computational modelling, along with live imaging techniques, plays an important role in understanding the processes of tissue growth and repair. A wide range of cell-based modelling frameworks have been developed that have each been successfully applied in a range of biological applications. Cell-based Chaste includes implementations of the cellular automaton model, the cellular Potts model, cell-centre models with cell representations as overlapping spheres or Voronoi tessellations, and the vertex model. Lung Chaste addresses the need for a novel, generic and efficient lung modelling software package that is both tested and verified. It aims to couple biophysically-detailed models of airway mechanics with organ-scale ventilation models in a package that is freely available to the scientific community. Publisher PDF

Safety and efficacy testing is a crucial part of the drug development process, and several different methods are used to obtain the necessary data (e.g.

The Arctic is rapidly transforming due to sea ice loss, increasing shipping activity, and oil and gas development. Associated marine and combustion emissions influence atmospheric aerosol composition, impacting complex aerosol–cloud–climate feedbacks. To improve understanding of the sources and processes determining Arctic aerosol composition, atmospheric particles were collected aboard the Korean icebreaker R/V Araon cruising within the Bering Strait and Chukchi Sea during August 2016. Offline analyses of individual particles by microspectroscopic techniques, including scanning electron microscopy with energy dispersive X-ray spectroscopy and atomic force microscopy with infrared spectroscopy, provided information on particle size, morphology, and chemical composition. The most commonly observed particle types were sea spray aerosol (SSA), comprising ∼60–90%, by number, of supermicron particles, and organic aerosol (OA), comprising ∼50–90%, by number, of submicron particles. Sulfate and nitrate were internally mixed within both SSA and OA particles, consistent with particle multiphase reactions during atmospheric transport. Within the Bering Strait, SSA and OA particles were more aged, with greater number fractions of particles containing sulfate and/or nitrate, compared to particles collected over the Chukchi Sea. This is indicative of greater pollution influence within the Bering Strait from coastal and inland sources, while the Chukchi Sea is primarily influenced by marine sources.

Cardiotoxicity, defined as toxicity that affects the heart, is one of the most common adverse drug effects. Numerous drugs have been shown to have the potential to induce lethal arrhythmias by impacting cardiac electrophysiology, for which current preclinical testing is largely focused on the detection of such interactions. However, a substantial number of drugs can also affect cardiac function beyond electrophysiology. In this much broader sense of cardiotoxicity, this review discusses the key drug-protein interactions known to be involved in cardiotoxic drug response, expanding from adverse drug effects in electrophysiology to contractility, mitochondrial function and cellular signalling. We cover adverse effects and cardiotoxic mechanisms of anti-cancer, central nervous, genitourinary, gastrointestinal, anti-histamines, anti-inflammatory, and anti-infective agents, demonstrating they have common modes of action on cardiac function and on adverse cardiac events.

The human heart beats as a result of multiscale nonlinear dynamics coupling subcellular to whole organ processes, achieving electrophysiologically-driven mechanical contraction. Computational cardiac modelling and simulation have achieved a great degree of maturity, both in terms of mathematical models of underlying biophysical processes and the development of simulation software. In this study, we present the detailed description of a human-based physiologically-based, and fully-coupled ventricular electromechanical modelling and simulation framework, and a sensitivity analysis focused on its mechanical properties. The biophysical detail of the model, from ionic to whole-organ, is crucial to enable future simulations of disease and drug action. Key novelties include the coupling of state-of-the-art human-based electrophysiology membrane kinetics, excitation–contraction and active contraction models, and the incorporation of a pre-stress model to allow for pre-stressing and pre-loading the ventricles in a dynamical regime. Through high performance computing simulations, we demonstrate that 50% to 200%−1000% variations in key parameters result in changes in clinically-relevant mechanical biomarkers ranging from diseased to healthy values in clinical studies. Furthermore mechanical biomarkers are primarily affected by only one or two parameters. Specifically, ejection fraction is dominated by the scaling parameter of the active tension model and its scaling parameter in the normal direction (kort2); the end systolic pressure is dominated by the pressure at which the ejection phase is triggered (Pej) and the compliance of the Windkessel fluid model (C); and the longitudinal fractional shortening is dominated by the fibre angle (ϕ) and kort2. The wall thickening does not seem to be clearly dominated by any of the considered input parameters. In summary, this study presents in detail the description and implementation of a human-based coupled electromechanical modelling and simulation framework, and a high performance computing study on the sensitivity of mechanical biomarkers to key model parameters. The tools and knowledge generated enable future investigations into disease and drug action on human ventricles., Highlights • Detailed description of human fully-coupled ventricular electromechanical model. • Sensitivity analysis reveals parameter variations effects on mechanical biomarkers. • Simulations yield biomarker values ranging from healthy to diseased conditions. • Each biomarkers is primarily affected by one or two of the parameters tested. • Tools and knowledge generated enable investigations into disease and drug action.

Prediction of drug effects on the heart still represents a challenge in drug development, given potential adverse outcomes. Computer modelling and simulations of the human heart offer a powerful technology to augment existing animal and clinical methodologies. Here we describe the translation process that led to the development and uptake of Virtual Assay, a user-friendly software to perform in silico drug trials in population of human cardiac models. Through this work, we contributed to the uptake of in silico modelling and simulations in industry and regulatory paradigms, and demonstrated accurate and mechanistic predictions of drug-induced cardiac pro-arrhythmic toxicity.

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.

Glucagon, the body's principal hyperglycaemic hormone, is released from the α-cells of the pancreatic islet. The secretion of this hormone is dysregulated in type 2 diabetes mellitus but the mechanisms controlling secretion are not well understood. Regulation of glucagon secretion by factors secreted by neighbouring β- and δ-cells (paracrine regulation) have been proposed to be important. In this study, we explored the importance of paracrine regulation by using an optogenetic strategy. Specific light-induced activation of β-cells in mouse islets expressing the light-gated channelrhodopsin-2 resulted in stimulation of electrical activity in δ-cells but suppression of α-cell activity. The activation of the δ-cells was rapid and sensitive to the gap junction inhibitor carbenoxolone, whereas the effect on electrical activity in α-cells was blocked by CYN 154806, an antagonist of the somatostatin-2 receptor. These observations indicate that optogenetic activation of the β-cells propagates to the δ-cells via gap junctions, and the consequential stimulation of somatostatin secretion inhibits α-cell electrical activity by a paracrine mechanism. To explore whether this pathway is important for regulating α-cell activity and glucagon secretion in human islets, we constructed computational models of human islets. These models had detailed architectures based on human islets and consisted of a collection of >500 α-, β- and δ-cells. Simulations of these models revealed that this gap junctional/paracrine mechanism accounts for up to 23% of the suppression of glucagon secretion by high glucose. This article is protected by copyright. All rights reserved

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