Uncertainty assessment of proarrhythmia predictions derived from multi-level in silico models.

In silico methods can be used for an early assessment of arrhythmogenic properties of drug candidates. However, their use for decision-making is conditioned by the possibility to estimate the predictions' uncertainty. This work describes our efforts to develop uncertainty quantification methods for the predictions produced by multi-level proarrhythmia models. In silico models used in this field usually start with experimental or predicted IC50 values that describe drug-induced ion channel blockade. Using such inputs, an electrophysiological model computes how the ion channel inhibition, exerted by a drug in a certain concentration, translates to an altered shape and duration of the action potential in cardiac cells, which can be represented as arrhythmogenic risk biomarkers such as the APD90. Using this framework, we identify the main sources of aleatory and epistemic uncertainties and propose a method based on probabilistic simulations that replaces single-point estimates predicted using multiple input values, including the IC50s and the electrophysiological parameters, by distributions of values. Two selected variability types associated with these inputs are then propagated through the multi-level model to estimate their impact on the uncertainty levels in the output, expressed by means of intervals. The proposed approach yields single predictions of arrhythmogenic risk biomarkers together with value intervals, providing a more comprehensive and realistic description of drug effects on a human population. The methodology was tested by predicting arrhythmogenic biomarkers on a series of twelve well-characterised marketed drugs, belonging to different arrhythmogenic risk classes.

Effect of Lead Position and Polarity on Paresthesia Coverage in Spinal Cord Stimulation Therapy: A Computational Study.

OBJECTIVES: The effect of lead placement and programming strategies on spinal cord stimulation (SCS) therapy has been widely studied; however, there is a need to optimize these parameters to favor dorsal column (DC) over dorsal root (DR) stimulation in complex pain treatment. This study aimed to determine the optimal lateral distance between two leads and the effect of transverse stimulation using a mathematical model. MATERIALS AND METHODS: A three-dimensional computational SCS and a nerve fiber model were used to determine the effect of the lateral distance between two leads at the same vertebral level T8 and the effect of the addition of anodes with two parallel leads at T8 and three different lateral distances on the model-based results (perception thresholds, activated DC fiber area and depth, and position of the first stimulated fiber). RESULTS: With two parallel leads programmed with symmetrical polarities, the maximal DC fiber area stimulated was found for a lateral distance of 5 mm. The results also show a higher preference for DR stimulation as the lateral distance increased. The addition of positive contacts at the same level of active contacts in the second lead produces a displacement of the first stimulated fiber laterally. CONCLUSIONS: A lateral distance of 5 mm shows a DC stimulated fiber area greater than when leads are placed contiguously. The addition of anodes creates an effect whereby the area of paresthesia is not displaced to the midline, but in the opposite direction. This may be useful when the leads are too close and stimulation of one of the sides is compromised.

In vitro and in vivo cardiac toxicity of flavored electronic nicotine delivery systems.

The usage of flavored electronic nicotine delivery systems (ENDS) is popular, specifically in the teen and young adult age-groups. The possible cardiac toxicity of the flavoring aspect of ENDS is largely unknown. Vaping, a form of electronic nicotine delivery, uses "e-liquid" to generate "e-vapor," an aerosolized mixture of nicotine and/or flavors. We report our investigation into the cardiotoxic effects of flavored e-liquids. E-vapors containing flavoring aldehydes such as vanillin and cinnamaldehyde, as indicated by mass spectrometry, were more toxic in HL-1 cardiomyocytes than fruit-flavored e-vapor. Exposure of human induced pluripotent stem cell-derived cardiomyocytes to cinnamaldehyde or vanillin-flavored e-vapor affected the beating frequency and prolonged the field potential duration of these cells more than fruit-flavored e-vapor. In addition, vanillin aldehyde-flavored e-vapor reduced the human ether-à-go-go-related gene (hERG)-encoded potassium current in transfected human embryonic kidney cells. In mice, inhalation exposure to vanillin aldehyde-flavored e-vapor for 10 wk caused increased sympathetic predominance in heart rate variability measurements. In vivo inducible ventricular tachycardia was significantly longer, and in optical mapping, the magnitude of ventricular action potential duration alternans was significantly larger in the vanillin aldehyde-flavored e-vapor-exposed mice than in controls. We conclude that the widely popular flavored ENDS are not harm free, and they have a potential for cardiac harm. More studies are needed to further assess their cardiac safety profile and long-term health effects.NEW & NOTEWORTHY The use of electronic nicotine delivery systems (ENDS) is not harm free. It is not known whether ENDS negatively affect cardiac electrophysiological function. Our study in cell lines and in mice shows that ENDS can compromise cardiac electrophysiology, leading to action potential instability and inducible ventricular arrhythmias. Further investigations are necessary to assess the long-term cardiac safety profile of ENDS products in humans and to better understand how individual components of ENDS affect cardiac toxicity.

Macrophage-Dependent Interleukin-6-Production and Inhibition of IK Contributes to Acquired QT Prolongation in Lipotoxic Guinea Pig Heart.

In the heart, the delayed rectifier K current, IK, composed of the rapid (IKr) and slow (IKs) components contributes prominently to normal cardiac repolarization. In lipotoxicity, chronic elevation of pro-inflammatory cytokines may remodel IK, elevating the risk for ventricular arrythmias and sudden cardiac death. We investigated whether and how the pro-inflammatory interleukin-6 altered IK in the heart, using electrophysiology to evaluate changes in IK in adult guinea pig ventricular myocytes. We found that palmitic acid (a potent inducer of lipotoxicity), induced a rapid (~24 h) and significant increase in IL-6 in RAW264.7 cells. PA-diet fed guinea pigs displayed a severely prolonged QT interval when compared to low-fat diet fed controls. Exposure to isoproterenol induced torsade de pointes, and ventricular fibrillation in lipotoxic guinea pigs. Pre-exposure to IL-6 with the soluble IL-6 receptor produced a profound depression of IKr and IKs densities, prolonged action potential duration, and impaired mitochondrial ATP production. Only with the inhibition of IKr did a proarrhythmic phenotype of IKs depression emerge, manifested as a further prolongation of action potential duration and QT interval. Our data offer unique mechanistic insights with implications for pathological QT interval in patients and vulnerability to fatal arrhythmias.

In Silico Classifiers for the Assessment of Drug Proarrhythmicity.

Drug-induced torsade de pointes (TdP) is a life-threatening ventricular arrhythmia responsible for the withdrawal of many drugs from the market. Although currently used TdP risk-assessment methods are effective, they are expensive and prone to produce false positives. In recent years, in silico cardiac simulations have proven to be a valuable tool for the prediction of drug effects. The objective of this work is to evaluate different biomarkers of drug-induced proarrhythmic risk and to develop an in silico risk classifier. Cellular simulations were performed using a modified version of the O'Hara et al. ventricular action potential model and existing pharmacological data (IC50 and effective free therapeutic plasma concentration, EFTPC) for 109 drugs of known torsadogenic risk (51 positive). For each compound, four biomarkers were tested: Tx (drug concentration leading to a 10% prolongation of the action potential over the EFTPC), TqNet (net charge carried by ionic currents when exposed to 10 times the EFTPC with respect to the net charge in control), Ttriang (triangulation for a drug concentration of 10 times the EFTPC over triangulation in control), and TEAD (drug concentration originating early afterdepolarizations over EFTPC). Receiver operating characteristic (ROC) curves were built for each biomarker to evaluate their individual predictive quality. At the optimal cutoff point, accuracies for Tx, TqNet, Ttriang, and TEAD were 89.9, 91.7, 90.8, and 78.9% respectively. The resulting accuracy of the hERG IC50 test (current biomarker) was 78.9%. When combining Tx, TqNet and Ttriang into a classifier based on decision trees, the prediction improves, achieving an accuracy of 94.5%. The sensitivity analysis revealed that most of the effects on the action potential are mainly due to changes in IKr, ICaL, INaL and IKs. In fact, considering that drugs affect only these four currents, TdP risk classification can be as accurate as when considering effects on the seven main currents proposed by the CiPA initiative. Finally, we built a ready-to-use tool (based on more than 450 000 simulations), which can be used to quickly assess the proarrhythmic risk of a compound. In conclusion, our in silico tool can be useful for the preclinical assessment of TdP-risk and to reduce costs related with new drug development. The TdP risk-assessment tool and the software used in this work are available at https://riunet.upv.es/handle/10251/136919.

When Does the IC50 Accurately Assess the Blocking Potency of a Drug?

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

Factors affecting basket catheter detection of real and phantom rotors in the atria: A computational study.

Anatomically based procedures to ablate atrial fibrillation (AF) are often successful in terminating paroxysmal AF. However, the ability to terminate persistent AF remains disappointing. New mechanistic approaches use multiple-electrode basket catheter mapping to localize and target AF drivers in the form of rotors but significant concerns remain about their accuracy. We aimed to evaluate how electrode-endocardium distance, far-field sources and inter-electrode distance affect the accuracy of localizing rotors. Sustained rotor activation of the atria was simulated numerically and mapped using a virtual basket catheter with varying electrode densities placed at different positions within the atrial cavity. Unipolar electrograms were calculated on the entire endocardial surface and at each of the electrodes. Rotors were tracked on the interpolated basket phase maps and compared with the respective atrial voltage and endocardial phase maps, which served as references. Rotor detection by the basket maps varied between 35-94% of the simulation time, depending on the basket's position and the electrode-to-endocardial wall distance. However, two different types of phantom rotors appeared also on the basket maps. The first type was due to the far-field sources and the second type was due to interpolation between the electrodes; increasing electrode density decreased the incidence of the second but not the first type of phantom rotors. In the simulations study, basket catheter-based phase mapping detected rotors even when the basket was not in full contact with the endocardial wall, but always generated a number of phantom rotors in the presence of only a single real rotor, which would be the desired ablation target. Phantom rotors may mislead and contribute to failure in AF ablation procedures.

Computational Study of the Effect of Electrode Polarity on Neural Activation Related to Paresthesia Coverage in Spinal Cord Stimulation Therapy.

OBJECTIVE: Using computer simulation, we investigated the effect of electrode polarity on neural activation in spinal cord stimulation and propose a new strategy to maximize the activating area in the dorsal column (DC) and, thus, paresthesia coverage in clinical practice. MATERIALS AND METHODS: A new three-dimensional spinal cord model at the T10 vertebral level was developed to simulate neural activation induced by the electric field distribution produced by different typical four-contact electrode polarities in single- and dual-lead stimulation. Our approach consisted of the combination of a finite element model of the spinal cord developed in COMSOL Multiphysics and a nerve fiber model implemented in MATLAB. Five evaluation parameters were evaluated, namely, the recruitment ratio, the perception and discomfort thresholds, and the activating area and depth. The results were compared quantitatively. RESULTS: The dual-guarded cathode presents the maximum activating area and depth in single- and dual-lead stimulation. However, the lowest value of the ratio between the perception threshold in DC and the perception threshold in the dorsal root (DR) is achieved when the guarded cathode is programmed. Although the two versions of bipolar polarity (namely bipolar 1 and bipolar 2) produce higher activating area and depth than the guarded cathode, they are suitable for producing DR stimulation. Similarly, dual-lead stimulation is likely to activate DR fibers because the electrodes are closer to these fibers. CONCLUSIONS: The results suggest that the activating area in the DC is maximized by using the dual-guarded cathode both in single- and dual-lead stimulation modes. However, DC nerve fibers are preferentially stimulated when the guarded cathode is used. According to these results, the new electrode programming strategy that we propose for clinical practice first uses the dual-guarded cathode, but, if the DR nerve fibers are activated, it then uses guarded cathode polarity.

In Silico QT and APD Prolongation Assay for Early Screening of Drug-Induced Proarrhythmic Risk.

Drug-induced proarrhythmicity is a major concern for regulators and pharmaceutical companies. For novel drug candidates, the standard assessment involves the evaluation of the potassium hERG channels block and the in vivo prolongation of the QT interval. However, this method is known to be too restrictive and to stop the development of potentially valuable therapeutic drugs. The aim of this work is to create an in silico tool for early detection of drug-induced proarrhythmic risk. The system is based on simulations of how different compounds affect the action potential duration (APD) of isolated endocardial, midmyocardial, and epicardial cells as well as the QT prolongation in a virtual tissue. Multiple channel-drug interactions and state-of-the-art human ventricular action potential models ( O'Hara , T. , PLos Comput. Biol. 2011 , 7 , e1002061 ) were used in our simulations. Specifically, 206.766 cellular and 7072 tissue simulations were performed by blocking the slow and the fast components of the delayed rectifier current ( IKs and IKr, respectively) and the L-type calcium current ( ICaL) at different levels. The performance of our system was validated by classifying the proarrhythmic risk of 84 compounds, 40 of which present torsadogenic properties. On the basis of these results, we propose the use of a new index (Tx) for discriminating torsadogenic compounds, defined as the ratio of the drug concentrations producing 10% prolongation of the cellular endocardial, midmyocardial, and epicardial APDs and the QT interval, over the maximum effective free therapeutic plasma concentration (EFTPC). Our results show that the Tx index outperforms standard methods for early identification of torsadogenic compounds. Indeed, for the analyzed compounds, the Tx tests accuracy was in the range of 87-88% compared with a 73% accuracy of the hERG IC50 based test.

Cardiac action potential repolarization revisited: early repolarization shows all-or-none behaviour.

In healthy mammalian hearts the action potential (AP) waveform initiates and modulates each contraction, or heartbeat. As a result, AP height and duration are key physiological variables. In addition, rate-dependent changes in ventricular AP duration (APD), and variations in APD at a fixed heart rate are both reliable biomarkers of electrophysiological stability. Present guidelines for the likelihood that candidate drugs will increase arrhythmias rely on small changes in APD and Q-T intervals as criteria for safety pharmacology decisions. However, both of these measurements correspond to the final repolarization of the AP. Emerging clinical evidence draws attention to the early repolarization phase of the action potential (and the J-wave of the ECG) as an additional important biomarker for arrhythmogenesis. Here we provide a mechanistic background to this early repolarization syndrome by summarizing the evidence that both the initial depolarization and repolarization phases of the cardiac action potential can exhibit distinct time- and voltage-dependent thresholds, and also demonstrating that both can show regenerative all-or-none behaviour. An important consequence of this is that not all of the dynamics of action potential repolarization in human ventricle can be captured by data from single myocytes when these results are expressed as 'repolarization reserve'. For example, the complex pattern of cell-to-cell current flow that is responsible for AP conduction (propagation) within the mammalian myocardium can change APD and the Q-T interval of the electrocardiogram alter APD stability, and modulate responsiveness to pharmacological agents (such as Class III anti-arrhythmic drugs).

In silico screening of the impact of hERG channel kinetic abnormalities on channel block and susceptibility to acquired long QT syndrome.

Accurate diagnosis of predisposition to long QT syndrome is crucial for reducing the risk of cardiac arrhythmias. In recent years, drug-induced provocative tests have proved useful to unmask some latent mutations linked to cardiac arrhythmias. In this study we expanded this concept by developing a prototype for a computational provocative screening test to reveal genetic predisposition to acquired long-QT syndrome (aLQTS). We developed a computational approach to reveal the pharmacological properties of I(Kr) blocking drugs that are most likely to cause aLQTS in the setting of subtle alterations in I(Kr) channel gating that would be expected to result from benign genetic variants.Weused themodel to predict themost potentially lethal combinations of kinetic anomalies and drug properties. In doing so, we also implicitly predicted ideal inverse therapeutic properties of K channel openers that would be expected to remedy a specific defect. We systematically performed "in silico mutagenesis" by altering discrete kinetic transition rates of the Fink et al. Markov model of human I(Kr) channels, corresponding to activation, inactivation, deactivation and recovery from inactivation of I(Kr) channels. We then screened and identified the properties of I(Kr) blockers that caused acquired long QT and therefore unmasked mutant phenotypes formild,moderate and severe variants. Mutant I(Kr) channels were incorporated into the O'Hara et al. human ventricular action potential (AP) model and subjected to simulated application of a wide variety of I(Kr)-drug interactions in order to identify the characteristics that selectively exacerbate the AP duration (APD) differences between wild-type and I(Kr) mutated cells. Our results show that drugs with disparate affinities to conformation states of the I(Kr) channel are key to amplify variants underlying susceptibility to acquired long QT syndrome, an effect that is especially pronounced at slow frequencies. Finally, we developed a mathematical formulation of the M54T MiRP1 latent mutation and simulated a provocative test. In this setting, application of dofetilide dramatically amplified the predicted QT interval duration in the M54T hMiRP1 mutation compared to wild-type.

The surgical experience of general surgery residents: an analysis of the applicability of the specialty program in General and Digestive Surgery.

UNLABELLED: Residents in our country have achieved a homogenous surgical training by following a structured residency program. This is due to the existence of specific training programs for each specialty. The current program, approved in 2007, has a detailed list of procedures that a surgeon should have performed in order to complete training. The aim of this study is to analyze the applicability of the program with regard to the number of procedures performed during the residency period. MATERIAL AND METHODS: A data collection form was designed that included the list of procedures from the program of the specialty; it was sent in April 2014 to all hospitals with accredited residency programs. In September 2014 the forms were analysed, and a general descriptive study was performed; a subanalysis according to the resident's sex and Autonomous region was also performed. The number of procedures performed according to the number of residents in the different centers was also analyzed. RESULTS: The survey was sent to 117 hospitals with accredited programs, which included 190 resident places. A total of 91 hospitals responded (53%). The training offered adapts in general to the specialty program. The total number of procedures performed in the different sub-areas, in laparoscopic and emergency surgery is correct or above the number recommended by the program, with the exception of esophageal-gastric and hepatobiliary surgery. The sub-analysis according to Autonomous region did not show any significant differences in the total number of procedures, however, there were significant differences in endocrine surgery (P=.001) and breast surgery (P=.042). A total of 55% of residents are female, with no significant differences in distribution in Autonomous regions. However, female surgeons operate more than their male counterparts during the residency period (512±226 vs. 625±244; P<.01). The number of residents in the hospital correlates with the number of procedures performed; the residents with more procedures trained in hospitals where there were less residents (669±237 vs. 527±209; P=.004). CONCLUSION: The surgical activity performed by spanish surgeons is adequate to the specialty program, except in hepatobiliary and esophageal-gastric surgery. The distribution is homogeneous in the different autonomous regions, although there are differences that depend on the number and sex the of residents in each hospital. This information is essential to evaluate the quality of the specialty program and to design new training programs.

In silico screening of the impact of hERG channel kinetic abnormalities on channel block and susceptibility to acquired long QT syndrome.

Accurate diagnosis of predisposition to long QT syndrome is crucial for reducing the risk of cardiac arrhythmias. In recent years, drug-induced provocative tests have proved useful to unmask some latent mutations linked to cardiac arrhythmias. In this study we expanded this concept by developing a prototype for a computational provocative screening test to reveal genetic predisposition to acquired long-QT syndrome (aLQTS). We developed a computational approach to reveal the pharmacological properties of IKr blocking drugs that are most likely to cause aLQTS in the setting of subtle alterations in IKr channel gating that would be expected to result from benign genetic variants. We used the model to predict the most potentially lethal combinations of kinetic anomalies and drug properties. In doing so, we also implicitly predicted ideal inverse therapeutic properties of K channel openers that would be expected to remedy a specific defect. We systematically performed "in silico mutagenesis" by altering discrete kinetic transition rates of the Fink et al. Markov model of human IKr channels, corresponding to activation, inactivation, deactivation and recovery from inactivation of IKr channels. We then screened and identified the properties of IKr blockers that caused acquired long QT and therefore unmasked mutant phenotypes for mild, moderate and severe variants. Mutant IKr channels were incorporated into the O'Hara et al. human ventricular action potential (AP) model and subjected to simulated application of a wide variety of IKr-drug interactions in order to identify the characteristics that selectively exacerbate the AP duration (APD) differences between wild-type and IKr mutated cells. Our results show that drugs with disparate affinities to conformation states of the IKr channel are key to amplify variants underlying susceptibility to acquired long QT syndrome, an effect that is especially pronounced at slow frequencies. Finally, we developed a mathematical formulation of the M54T MiRP1 latent mutation and simulated a provocative test. In this setting, application of dofetilide dramatically amplified the predicted QT interval duration in the M54T hMiRP1 mutation compared to wild-type.

In silico ischaemia-induced reentry at the Purkinje-ventricle interface.

AIMS: This computational modelling work illustrates the influence of hyperkalaemia and electrical uncoupling induced by defined ischaemia on action potential (AP) propagation and the incidence of reentry at the Purkinje-ventricle interface in mammalian hearts. METHODS AND RESULTS: Unidimensional and bidimensional models of the Purkinje-ventricle subsystem, including ischaemic conditions (defined as phase 1B) in the ventricle and an ischaemic border zone, were developed by altering several important electrophysiological parameters of the Luo-Rudy AP model of the ventricular myocyte. Purkinje electrical activity was modelled using the equations of DiFrancesco and Noble. Our study suggests that an extracellular potassium concentration [K(+)]o >14 mM and a slight decrease in intercellular coupling induced by ischaemia in ventricle can cause conduction block from Purkinje to ventricle. Under these conditions, propagation from ventricle to Purkinje is possible. Thus, unidirectional block (UDB) and reentry can result. When conditions of UDB are met, retrograde propagation with a long delay (320 ms) may re-excite Purkinje cells, and give rise to a reentrant pathway. This induced reentry may be the origin of arrhythmias observed in phase 1B ischaemia. CONCLUSION: In a defined setting of ischaemia (phase 1B), a small amount of uncoupling between ventricular cells, as well as between Purkinje and ventricular tissue, may induce UDBs and reentry. Hyperkalaemia is also confirmed to be an important factor in the genesis of reentrant rhythms, since it regulates the range of coupling in which UDBs may be induced.

Experimentally validated modeling of dynamic drug-hERG channel interactions reproducing the binding mechanisms and its importance in action potential duration.

BACKGROUND AND OBJECTIVE: Assessment of drug cardiotoxicity is critical in the development of new compounds and modeling of drug-binding dynamics to hERG can improve early cardiotoxicity assessment. We previously developed a methodology to generate Markovian models reproducing preferential state-dependent binding properties, trapping dynamics and the onset of IKr block using simple voltage clamp protocols. Here, we test this methodology with real IKr blockers and investigate the impact of drug dynamics on action potential prolongation. METHODS: Experiments were performed on HEK cells stably transfected with hERG and using the Nanion SyncroPatch 384i. Three protocols, P-80, P0 and P 40, were applied to obtain the experimental data from the drugs and the Markovian models were generated using our pipeline. The corresponding static models were also generated and a modified version of the O´Hara-Rudy action potential model was used to simulate the action potential duration. RESULTS: The experimental Hill plots and the onset of IKr block of ten compounds were obtained using our voltage clamp protocols and the models generated successfully mimicked these experimental data, unlike the CiPA dynamic models. Marked differences in APD prolongation were observed when drug effects were simulated using the dynamic models and the static models. CONCLUSIONS: These new dynamic models of ten well-known IKr blockers constitute a validation of our methodology to model dynamic drug-hERG channel interactions and highlight the importance of state-dependent binding, trapping dynamics and the time-course of IKr block to assess drug effects even at the steady-state.

Application of machine learning to improve the efficiency of electrophysiological simulations used for the prediction of drug-induced ventricular arrhythmia.

BACKGROUND AND OBJECTIVE: In silico prediction of drug-induced ventricular arrhythmia often requires computationally intensive simulations, making its application tedious and non-interactive. This inconvenience can be mitigated using matrices of precomputed simulation results, allowing instantaneous computation of biomarkers such as action potential duration at 90% of the repolarisation (APD90). However, preparing such matrices can be computationally intensive for the method developers, limiting the range of simulated conditions. In this work, we aim to optimise the generation of these matrices so that they can be obtained with less effort and for a broader range of input values. METHODS: Machine learning methods were applied, building models trained with only a small fraction of the originally simulated results. The predictive performances of the models were assessed by comparing their predicted values with the actual simulation results, using percentual mean absolute error and mean relative error, as well as the percentage of data with a relative error below 5%. RESULTS: Our method obtained highly accurate estimations of the original values, leading to a nearly one hundred-fold decrease in computation time. This method also allows precomputing more complex matrices, describing the effect of more ion channels on the APD90. The best results were obtained by applying Support Vector Machine models, which yielded errors below 1% in most cases. This approach was further validated by predicting the APD90 of a set of 12 CiPA compounds and exporting the optimal settings for predicting APD90 using a different set of ion channels, always with satisfactory results. CONCLUSIONS: The proposed method effectively reduces the computational effort required to generate matrices of precomputed electrophysiological simulation values. The same approach can be applied in other fields where computationally costly simulations are applied repeatedly using slightly different input values.

Air Pollution and Cardiac Diseases: A Review of Experimental Studies.

Air pollution is associated with around 6.5 million premature deaths annually, which are directly related to cardiovascular diseases, and the most dangerous atmospheric pollutants to health are as follows: NO2, SO2, CO, and PM. The mechanisms underlying the observed effects have not yet been clearly defined. This work aims to conduct a narrative review of experimental studies to provide a more comprehensive and multiperspective assessment of how the effect of atmospheric pollutants on cardiac activity can result in the development of cardiac diseases. For this purpose, a review was carried out in databases of experimental studies, excluding clinical trials, and epidemiological and simulation studies. After analyzing the available information, the existence of pathophysiological effects of the different pollutants on cardiac activity from exposure during both short-term and long-term is evident. This narrative review based on experimental studies is a basis for the development of recommendations for public health.

Characterization of airborne particulate matter and its toxic and proarrhythmic effects: A case study in Aburrá Valley, Colombia.

Particle matter (PM) is a complex mixture of particles suspended in the air, mainly caused by fuel combustion from vehicles and industry, and has been related to pulmonary and cardiovascular diseases. The Metropolitan Area of Aburrá Valley in Colombia is the second most populous urban agglomeration in the country and the third densest in the world, composed of ten municipalities. Examining the physicochemical properties of PM is crucial in comprehending its composition and its effects on human health, as it varies based on the socioeconomic dynamics specific to each city. This study characterized the PM collected from the north, south, and central zones to evaluate its chemical composition and morphology. Different elements such as silicon, carbon, aluminum, potassium, calcium, sodium, iron, magnesium, and copper and the presence of unburned fuel, motor oil, and silicon fibers were identified. In vitro and in silico studies were conducted to evaluate the toxicity of the PM, and it was found that the PM collected from the central zone had the greatest impact on cell viability and caused DNA damage. The in silico study demonstrated that PM has concentration-dependent proarrhythmic effects, reflected in an action potential duration shortening and an increased number of reentries, which may contribute to the development of cardiac arrhythmias. Overall, the results suggest that the size and chemical composition of ambient PM can induce toxicity and play an important role in the generation of arrhythmias.

Combining pharmacokinetic and electrophysiological models for early prediction of drug-induced arrhythmogenicity.

BACKGROUND AND OBJECTIVE: In silico methods are gaining attention for predicting drug-induced Torsade de Pointes (TdP) in different stages of drug development. However, many computational models tended not to account for inter-individual response variability due to demographic covariates, such as sex, or physiologic covariates, such as renal function, which may be crucial when predicting TdP. This study aims to compare the effects of drugs in male and female populations with normal and impaired renal function using in silico methods. METHODS: Pharmacokinetic models considering sex and renal function as covariates were implemented from data published in pharmacokinetic studies. Drug effects were simulated using an electrophysiologically calibrated population of cellular models of 300 males and 300 females. The population of models was built by modifying the endocardial action potential model published by O'Hara et al. (2011) according to the experimentally measured gene expression levels of 12 ion channels. RESULTS: Fifteen pharmacokinetic models for CiPA drugs were implemented and validated in this study. Eight pharmacokinetic models included the effect of renal function and four the effect of sex. The mean difference in action potential duration (APD) between male and female populations was 24.9 ms (p<0.05). Our simulations indicated that women with impaired renal function were particularly susceptible to drug-induced arrhythmias, whereas healthy men were less prone to TdP. Differences between patient groups were more pronounced for high TdP-risk drugs. The proposed in silico tool also revealed that individuals with impaired renal function, electrophysiologically simulated with hyperkalemia (extracellular potassium concentration [K+]o = 7 mM) exhibited less pronounced APD prolongation than individuals with normal potassium levels. The pharmacokinetic/electrophysiological framework was used to determine the maximum safe dose of dofetilide in different patient groups. As a proof of concept, 3D simulations were also run for dofetilide obtaining QT prolongation in accordance with previously reported clinical values. CONCLUSIONS: This study presents a novel methodology that combines pharmacokinetic and electrophysiological models to incorporate the effects of sex and renal function into in silico drug simulations and highlights their impact on TdP-risk assessment. Furthermore, it may also help inform maximum dose regimens that ensure TdP-related safety in a specific sub-population of patients.

Manifold analysis of the P-wave changes induced by pulmonary vein isolation during cryoballoon procedure.

BACKGROUND/AIM: In atrial fibrillation (AF) ablation procedures, it is desirable to know whether a proper disconnection of the pulmonary veins (PVs) was achieved. We hypothesize that information about their isolation could be provided by analyzing changes in P-wave after ablation. Thus, we present a method to detect PV disconnection using P-wave signal analysis. METHODS: Conventional P-wave feature extraction was compared to an automatic feature extraction procedure based on creating low-dimensional latent spaces for cardiac signals with the Uniform Manifold Approximation and Projection (UMAP) method. A database of patients (19 controls and 16 AF individuals who underwent a PV ablation procedure) was collected. Standard 12-lead ECG was recorded, and P-waves were segmented and averaged to extract conventional features (duration, amplitude, and area) and their manifold representations provided by UMAP on a 3-dimensional latent space. A virtual patient was used to validate these results further and study the spatial distribution of the extracted characteristics over the whole torso surface. RESULTS: Both methods showed differences between P-wave before and after ablation. Conventional methods were more prone to noise, P-wave delineation errors, and inter-patient variability. P-wave differences were observed in the standard leads recordings. However, higher differences appeared in the torso region over the precordial leads. Recordings near the left scapula also yielded noticeable differences. CONCLUSIONS: P-wave analysis based on UMAP parameters detects PV disconnection after ablation in AF patients and is more robust than heuristic parameterization. Moreover, additional leads different from the standard 12-lead ECG should be used to detect PV isolation and possible future reconnections better.