Minimum Information about a Cardiac Electrophysiology Experiment (MICEE): standardised reporting for model reproducibility, interoperability, and data sharing

The challenges of research data management in cardiovascular science: a DGK and DZHK position paper-executive summary

The sharing and documentation of cardiovascular research data are essential for efficient use and reuse of data, thereby aiding scientific transparency, accelerating the progress of cardiovascular research and healthcare, and contributing to the reproducibility of research results. However, challenges remain. This position paper, written on behalf of and approved by the German Cardiac Society and German Centre for Cardiovascular Research, summarizes our current understanding of the challenges in cardiovascular research data management (RDM). These challenges include lack of time, awareness, incentives, and funding for implementing effective RDM; lack of standardization in RDM processes; a need to better identify meaningful and actionable data among the increasing volume and complexity of data being acquired; and a lack of understanding of the legal aspects of data sharing. While several tools exist to increase the degree to which data are findable, accessible, interoperable, and reusable (FAIR), more work is needed to lower the threshold for effective RDM not just in cardiovascular research but in all biomedical research, with data sharing and reuse being factored in at every stage of the scientific process. A culture of open science with FAIR research data should be fostered through education and training of early-career and established research professionals. Ultimately, FAIR RDM requires permanent, long-term effort at all levels. If outcomes can be shown to be superior and to promote better (and better value) science, modern RDM will make a positive difference to cardiovascular science and practice. The full position paper is available in the supplementary materials.

The in vivo study of cardiac mechano-electric and mechano-mechanical coupling during heart development in zebrafish

In the adult heart, acute adaptation of electrical and mechanical activity to changes in mechanical load occurs via feedback processes known as “mechano-electric coupling” and “mechano-mechanical coupling.” Whether this occurs during cardiac development is ill-defined, as acutely altering the heart’s mechanical load while measuring functional responses in traditional experimental models is difficult, as embryogenesis occurs in utero, making the heart inaccessible. These limitations can be overcome with zebrafish, as larvae develop in a dish and are nearly transparent, allowing for in vivo manipulation and measurement of cardiac structure and function. Here we present a novel approach for the in vivo study of mechano-electric and mechano-mechanical coupling in the developing zebrafish heart. This innovative methodology involves acute in vivo atrial dilation (i.e., increased atrial preload) in larval zebrafish by injection of a controlled volume into the venous circulation immediately upstream of the heart, combined with optical measurement of the acute electrical (change in heart rate) and mechanical (change in stroke area) response. In proof-of-concept experiments, we applied our new method to 48 h post-fertilisation zebrafish, which revealed differences between the electrical and mechanical response to atrial dilation. In response to an acute increase in atrial preload there is a large increase in atrial stroke area but no change in heart rate, demonstrating that in contrast to the fully developed heart, during early cardiac development mechano-mechanical coupling alone drives the adaptive increase in atrial output. Overall, in this methodological paper we present our new experimental approach for the study of mechano-electric and mechano-mechanical coupling during cardiac development and demonstrate its potential for understanding the essential adaptation of heart function to acute changes in mechanical load.

Tipping the scales of understanding: An engineering approach to design and implement whole-body cardiac electrophysiology experimental models

The study of cardiac electrophysiology is built on experimental models that span all scales, from ion channels to whole-body preparations. Novel discoveries made at each scale have contributed to our fundamental understanding of human cardiac electrophysiology, which informs clinicians as they detect, diagnose, and treat complex cardiac pathologies. This expert review describes an engineering approach to developing experimental models that is applicable across scales. The review also outlines how we applied the approach to create a set of multiscale whole-body experimental models of cardiac electrophysiology, models that are driving new insights into the response of the myocardium to acute ischemia. Specifically, we propose that researchers must address three critical requirements to develop an effective experimental model: 1) how the experimental model replicates and maintains human physiological conditions, 2) how the interventions possible with the experimental model capture human pathophysiology, and 3) what signals need to be measured, at which levels of resolution and fidelity, and what are the resulting requirements of the measurement system and the access to the organs of interest. We will discuss these requirements in the context of two examples of whole-body experimental models, a closed chest in situ model of cardiac ischemia and an isolated-heart, torso-tank preparation, both of which we have developed over decades and used to gather valuable insights from hundreds of experiments.

Portable low-cost macroscopic mapping system for all-optical cardiac electrophysiology

SIGNIFICANCE

All-optical cardiac electrophysiology enables the visualization and control of key parameters relevant to the detection of cardiac arrhythmias. Mapping such responses in human induced pluripotent stem-cell-derived cardiomyocytes (hiPSC-CMs) is of great interest for cardiotoxicity and personalized medicine applications.

AIM

We introduce and validate a very low-cost compact mapping system for macroscopic all-optical electrophysiology in layers of hiPSC-CMs.

APPROACH

The system uses oblique transillumination, low-cost cameras, light-emitting diodes, and off-the-shelf components (total < $ 15 , 000 ) to capture voltage, calcium, and mechanical waves under electrical or optical stimulation.

RESULTS

Our results corroborate the equivalency of electrical and optogenetic stimulation of hiPSC-CMs, and V m - [ Ca 2 + ] i similarity in conduction under pacing. Green-excitable optical sensors are combinable with blue optogenetic actuators (chanelrhodopsin2) only under very low green light ( < 0.05    mW / mm 2 ). Measurements in warmer culture medium yield larger spread of action potential duration and higher conduction velocities compared to Tyrode's solution at room temperature.

CONCLUSIONS

As multiple optical sensors and actuators are combined, our results can help handle the "spectral congestion" and avoid parameter distortion. We illustrate the utility of the system for uncovering the action of cellular uncoupling agents and show extensibility to an epi-illumination mode for future imaging of thicker native or engineered tissues.

Models of the cardiac L-type calcium current: A quantitative review

The L-type calcium current (I CaL ) plays a critical role in cardiac electrophysiology, and models ofI CaL are vital tools to predict arrhythmogenicity of drugs and mutations. Five decades of measuring and modelingI CaL have resulted in several competing theories (encoded in mathematical equations). However, the introduction of new models has not typically been accompanied by a data-driven critical comparison with previous work, so that it is unclear which model is best suited for any particular application. In this review, we describe and compare 73 published mammalianI CaL models and use simulated experiments to show that there is a large variability in their predictions, which is not substantially diminished when grouping by species or other categories. We provide model code for 60 models, list major data sources, and discuss experimental and modeling work that will be required to reduce this huge list of competing theories and ultimately develop a community consensus model ofI CaL . This article is categorized under: Cardiovascular Diseases > Computational Models Cardiovascular Diseases > Molecular and Cellular Physiology.

Guidelines for assessment of cardiac electrophysiology and arrhythmias in small animals

Cardiac arrhythmias are a major cause of morbidity and mortality worldwide. Although recent advances in cell-based models, including human-induced pluripotent stem cell-derived cardiomyocytes (iPSC-CM), are contributing to our understanding of electrophysiology and arrhythmia mechanisms, preclinical animal studies of cardiovascular disease remain a mainstay. Over the past several decades, animal models of cardiovascular disease have advanced our understanding of pathological remodeling, arrhythmia mechanisms, and drug effects and have led to major improvements in pacing and defibrillation therapies. There exist a variety of methodological approaches for the assessment of cardiac electrophysiology and a plethora of parameters may be assessed with each approach. This guidelines article will provide an overview of the strengths and limitations of several common techniques used to assess electrophysiology and arrhythmia mechanisms at the whole animal, whole heart, and tissue level with a focus on small animal models. We also define key electrophysiological parameters that should be assessed, along with their physiological underpinnings, and the best methods with which to assess these parameters.

Re-evaluating methods reporting practices to improve reproducibility: an analysis of methodological rigor for the Langendorff whole-heart technique

In recent decades, the scientific community has seen an increased interest in rigor and reproducibility. In 2017, concerns of methodological thoroughness and reporting practices were implicated as significant barriers to reproducibility within the preclinical cardiovascular literature, particularly in studies employing animal research. The Langendorff, whole-heart technique has proven to be an invaluable research tool, being modified in a myriad of ways to probe questions across the spectrum of physio- and pathophysiologic function of the heart. As a result, significant variability in the application of the Langendorff technique exists. This literature review quantifies the different methods employed in the implementation of the Langendorff technique and provides brief examples of how individual parametric differences can impact the outcomes and interpretation of studies. From 2017-2020, significant variability of animal models, anesthesia, cannulation time, and perfusate composition, pH, and temperature demonstrate that the technique has diversified to meet new challenges and answer different scientific questions. The review also reveals which individual methods are most frequently reported, even if there is no explicit agreement upon which parameters should be reported. The analysis of methods related to the Langendorff technique suggests a framework for considering methodological approach when interpreting seemingly contradictory results, rather than concluding that results are irreproducible.

Demographic and Methodological Heterogeneity in Electrocardiogram Signals From Guinea Pigs

Electrocardiograms (ECG) are universally used to measure the electrical activity of the heart; however, variations in recording techniques and/or subject demographics can affect ECG interpretation. In this study, we investigated variables that are likely to influence ECG metric measurements in cardiovascular research, including recording technique, use of anesthesia, and animal model characteristics. Awake limb lead ECG recordings were collected in vivo from adult guinea pigs using a platform ECG system, while recordings in anesthetized animals were performed using both a platform and needle ECG system. We report significant heterogeneities in ECG metric values that are attributed to methodological differences (e.g., ECG lead configuration, ECG recording platform, presence or absence of anesthesia) that persist even within the same cohort of animals. Further, we report that variability in animal demographics is preserved in vivo ECG recordings—with animal age serving as a significant contributor, while sex-specific influences were less pronounced. Methodological approaches and subject demographics should be fully considered when interpreting ECG values in animal models, comparing datasets between studies, or developing artificial intelligence algorithms that utilize an ECG database.

Drivers of Sinoatrial Node Automaticity in Zebrafish: Comparison With Mechanisms of Mammalian Pacemaker Function

Cardiac excitation originates in the sinoatrial node (SAN), due to the automaticity of this distinct region of the heart. SAN automaticity is the result of a gradual depolarisation of the membrane potential in diastole, driven by a coupled system of transarcolemmal ion currents and intracellular Ca²⁺ cycling. The frequency of SAN excitation determines heart rate and is under the control of extra- and intracardiac (extrinsic and intrinsic) factors, including neural inputs and responses to tissue stretch. While the structure, function, and control of the SAN have been extensively studied in mammals, and some critical aspects have been shown to be similar in zebrafish, the specific drivers of zebrafish SAN automaticity and the response of its excitation to vagal nerve stimulation and mechanical preload remain incompletely understood. As the zebrafish represents an important alternative experimental model for the study of cardiac (patho-) physiology, we sought to determine its drivers of SAN automaticity and the response to nerve stimulation and baseline stretch. Using a pharmacological approach mirroring classic mammalian experiments, along with electrical stimulation of intact cardiac vagal nerves and the application of mechanical preload to the SAN, we demonstrate that the principal components of the coupled membrane- Ca²⁺ pacemaker system that drives automaticity in mammals are also active in the zebrafish, and that the effects of extra- and intracardiac control of heart rate seen in mammals are also present. Overall, these results, combined with previously published work, support the utility of the zebrafish as a novel experimental model for studies of SAN (patho-) physiological function.

Data integration in cardiac electrophysiology ablation toward achieving proper interoperability in health information systems

INTRODUCTION

Providing information exchange and collaboration between isolated information systems (ISs) is essential in the health-care environments. In this context, we aimed to develop a communication protocol to facilitate better interoperability among electrophysiology study (EPS)-related ISs in order to allow exchange unified reporting in EPS ablation.

MATERIALS AND METHODS

This study was an applied-descriptive research that was conducted in 2019. To determine the information content of agreed cardiac EPS Minimum Data Set (MDS) in Iran, the medical record of patients undergoing EPS ablation procedure in the Tehran Heart Center (THC) hospital was reviewed by a checklist. Then, an information model based on Health Level Seven, Clinical Document Architecture (HL7 CDA) standard framework for structural interoperability has been developed. In this framework, using NPEX online browser and MindMaple software, a set of terminology mapping rules was used for consistent transfer of data between various ISs.

RESULTS

The information content of each data field was introduced into the heading and body sections of HL7 CDA document using Systematized Nomenclature of Medicine - Clinical Terminology names and codes. Then, the ontology alignment was designed in the form of thesaurus mapping routes.

CONCLUSION

The sensitive, complex, and multidimensional nature of cardiovascular conditions requires special attention to the interoperability of ISs. Designing customized communication protocols plays an important role in improving the interoperability, and they are compatible with the needs of future Iranian health information exchange.

Sinoatrial Node Structure, Mechanics, Electrophysiology and the Chronotropic Response to Stretch in Rabbit and Mouse

The rhythmic electrical activity of the heart's natural pacemaker, the sinoatrial node (SAN), determines cardiac beating rate (BR). SAN electrical activity is tightly controlled by multiple factors, including tissue stretch, which may contribute to adaptation of BR to changes in venous return. In most animals, including human, there is a robust increase in BR when the SAN is stretched. However, the chronotropic response to sustained stretch differs in mouse SAN, where it causes variable responses, including decreased BR. The reasons for this species difference are unclear. They are thought to relate to dissimilarities in SAN electrophysiology (particularly action potential morphology) between mouse and other species and to how these interact with subcellular stretch-activated mechanisms. Furthermore, species-related differences in structural and mechanical properties of the SAN may influence the chronotropic response to SAN stretch. Here we assess (i) how the BR response to sustained stretch of rabbit and mouse isolated SAN relates to tissue stiffness, (ii) whether structural differences could account for observed differences in BR responsiveness to stretch, and (iii) whether pharmacological modification of mouse SAN electrophysiology alters stretch-induced chronotropy. We found disparities in the relationship between SAN stiffness and the magnitude of the chronotropic response to stretch between rabbit and mouse along with differences in SAN collagen structure, alignment, and changes with stretch. We further observed that pharmacological modification to prolong mouse SAN action potential plateau duration rectified the direction of BR changes during sustained stretch, resulting in a positive chronotropic response akin to that of other species. Overall, our results suggest that structural, mechanical, and background electrophysiological properties of the SAN influence the chronotropic response to stretch. Improved insight into the biophysical determinants of stretch effects on SAN pacemaking is essential for a comprehensive understanding of SAN regulation with important implications for studies of SAN physiology and its dysfunction, such as in the aging and fibrotic heart.

Calibration of ionic and cellular cardiac electrophysiology models

Cardiac electrophysiology models are among the most mature and well-studied mathematical models of biological systems. This maturity is bringing new challenges as models are being used increasingly to make quantitative rather than qualitative predictions. As such, calibrating the parameters within ion current and action potential (AP) models to experimental data sets is a crucial step in constructing a predictive model. This review highlights some of the fundamental concepts in cardiac model calibration and is intended to be readily understood by computational and mathematical modelers working in other fields of biology. We discuss the classic and latest approaches to calibration in the electrophysiology field, at both the ion channel and cellular AP scales. We end with a discussion of the many challenges that work to date has raised and the need for reproducible descriptions of the calibration process to enable models to be recalibrated to new data sets and built upon for new studies. This article is categorized under: Analytical and Computational Methods > Computational Methods Physiology > Mammalian Physiology in Health and Disease Models of Systems Properties and Processes > Cellular Models.

Cardiac Mechano-Electric Coupling: Acute Effects of Mechanical Stimulation on Heart Rate and Rhythm

The heart is vital for biological function in almost all chordates, including humans. It beats continually throughout our life, supplying the body with oxygen and nutrients while removing waste products. If it stops, so does life. The heartbeat involves precise coordination of the activity of billions of individual cells, as well as their swift and well-coordinated adaption to changes in physiological demand. Much of the vital control of cardiac function occurs at the level of individual cardiac muscle cells, including acute beat-by-beat feedback from the local mechanical environment to electrical activity (as opposed to longer term changes in gene expression and functional or structural remodeling). This process is known as mechano-electric coupling (MEC). In the current review, we present evidence for, and implications of, MEC in health and disease in human; summarize our understanding of MEC effects gained from whole animal, organ, tissue, and cell studies; identify potential molecular mediators of MEC responses; and demonstrate the power of computational modeling in developing a more comprehensive understanding of ‟what makes the heart tick.ˮ.

Ischemia Enhances the Acute Stretch-Induced Increase in Calcium Spark Rate in Ventricular Myocytes

Introduction: In ventricular myocytes, spontaneous release of calcium (Ca²⁺) from the sarcoplasmic reticulum via ryanodine receptors (“Ca²⁺ sparks”) is acutely increased by stretch, due to a stretch-induced increase of reactive oxygen species (ROS). In acute regional ischemia there is stretch of ischemic tissue, along with an increase in Ca²⁺ spark rate and ROS production, each of which has been implicated in arrhythmogenesis. Yet, whether there is an impact of ischemia on the stretch-induced increase in Ca²⁺ sparks and ROS has not been investigated. We hypothesized that ischemia would enhance the increase of Ca²⁺ sparks and ROS that occurs with stretch.

Methods: Isolated ventricular myocytes from mice (male, C57BL/6J) were loaded with fluorescent dye to detect Ca²⁺ sparks (4.6 μM Fluo-4, 10 min) or ROS (1 μM DCF, 20 min), exposed to normal Tyrode (NT) or simulated ischemia (SI) solution (hyperkalemia [15 mM potassium], acidosis [6.5 pH], and metabolic inhibition [1 mM sodium cyanide, 20 mM 2-deoxyglucose]), and subjected to sustained stretch by the carbon fiber technique (~10% increase in sarcomere length, 15 s). Ca²⁺ spark rate and rate of ROS production were measured by confocal microscopy.

Results: Baseline Ca²⁺ spark rate was greater in SI (2.54 ± 0.11 sparks·s⁻¹·100 μm⁻²; n = 103 cells, N = 10 mice) than NT (0.29 ± 0.05 sparks·s⁻¹·100 μm⁻²; n = 33 cells, N = 9 mice; p < 0.0001). Stretch resulted in an acute increase in Ca²⁺ spark rate in both SI (3.03 ± 0.13 sparks·s⁻¹·100 μm⁻²; p < 0.0001) and NT (0.49 ± 0.07 sparks·s⁻¹·100 μm⁻²; p < 0.0001), with the increase in SI being greater than NT (+0.49 ± 0.04 vs. +0.20 ± 0.04 sparks·s⁻¹·100 μm⁻²; p < 0.0001). Baseline rate of ROS production was also greater in SI (1.01 ± 0.01 normalized slope; n = 11, N = 8 mice) than NT (0.98 ± 0.01 normalized slope; n = 12, N = 4 mice; p < 0.05), but there was an acute increase with stretch only in SI (+12.5 ± 2.6%; p < 0.001).

Conclusion: Ischemia enhances the stretch-induced increase of Ca²⁺ sparks in ventricular myocytes, with an associated enhancement of stretch-induced ROS production. This effect may be important for premature excitation and/or in the development of an arrhythmogenic substrate in acute regional ischemia.

Scientist and data architect collaborate to curate and archive an inner ear electrophysiology data collection

In the past scientists reported summaries of their findings; they did not provide their original data collections. Many stakeholders (e.g., funding agencies) are now requesting that such data be made publicly available. This mandate is being adopted to facilitate further discovery, and to mitigate waste and deficits in the research process. At the same time, the necessary infrastructure for data curation (e.g., repositories) has been evolving. The current target is to make research products FAIR (Findable, Accessible, Interoperable, Reusable), resulting in data that are curated and archived to be both human and machine compatible. However, most scientists have little training in data curation. Specifically, they are ill-equipped to annotate their data collections at a level that facilitates discoverability, aggregation, and broad reuse in a context separate from their creation or sub-field. To circumvent these deficits data architects may collaborate with scientists to transform and curate data. This paper’s example of a data collection describes the electrical properties of outer hair cells isolated from the mammalian cochlea. The data is expressed with a variant of The Ontology for Biomedical Investigations (OBI), mirrored to provide the metadata and nested data architecture used within the Hierarchical Data Format version 5 (HDF5) format. Each digital specimen is displayed in a tree configuration (like directories in a computer) and consists of six main branches based on the ontology classes. The data collections, scripts, and ontological OWL file (OBI based Inner Ear Electrophysiology (OBI_IEE)) are deposited in three repositories. We discuss the impediments to producing such data collections for public use, and the tools and processes required for effective implementation. This work illustrates the impact that small collaborations can have on the curation of our publicly-funded collections, and is particularly salient for fields where data is sparse, throughput is low, and sacrifice of animals is required for discovery.

Data Management in Computational Systems Biology: Exploring Standards, Tools, Databases, and Packaging Best Practices

Computational systems biology involves integrating heterogeneous datasets in order to generate models. These models can assist with understanding and prediction of biological phenomena. Generating datasets and integrating them into models involves a wide range of scientific expertise. As a result these datasets are often collected by one set of researchers, and exchanged with others researchers for constructing the models. For this process to run smoothly the data and models must be FAIR-findable, accessible, interoperable, and reusable. In order for data and models to be FAIR they must be structured in consistent and predictable ways, and described sufficiently for other researchers to understand them. Furthermore, these data and models must be shared with other researchers, with appropriately controlled sharing permissions, before and after publication. In this chapter we explore the different data and model standards that assist with structuring, describing, and sharing. We also highlight the popular standards and sharing databases within computational systems biology.

Cardiac Electrophysiological Effects of Light-Activated Chloride Channels

During the last decade, optogenetics has emerged as a paradigm-shifting technique to monitor and steer the behavior of specific cell types in excitable tissues, including the heart. Activation of cation-conducting channelrhodopsins (ChR) leads to membrane depolarization, allowing one to effectively trigger action potentials (AP) in cardiomyocytes. In contrast, the quest for optogenetic tools for hyperpolarization-induced inhibition of AP generation has remained challenging. The green-light activated ChR from Guillardia theta (GtACR1) mediates Cl^--driven photocurrents that have been shown to silence AP generation in different types of neurons. It has been suggested, therefore, to be a suitable tool for inhibition of cardiomyocyte activity. Using single-cell electrophysiological recordings and contraction tracking, as well as intracellular microelectrode recordings and in vivo optical recordings of whole hearts, we find that GtACR1 activation by prolonged illumination arrests cardiac cells in a depolarized state, thus inhibiting re-excitation. In line with this, GtACR1 activation by transient light pulses elicits AP in rabbit isolated cardiomyocytes and in spontaneously beating intact hearts of zebrafish. Our results show that GtACR1 inhibition of AP generation is caused by cell depolarization. While this does not address the need for optogenetic silencing through physiological means (i.e., hyperpolarization), GtACR1 is a potentially attractive tool for activating cardiomyocytes by transient light-induced depolarization.

Predicting changes to INa from missense mutations in human SCN5A

Mutations in SCN5A can alter the cardiac sodium current I_Na and increase the risk of potentially lethal conditions such as Brugada and long-QT syndromes. The relation between mutations and their clinical phenotypes is complex, and systems to predict clinical severity of unclassified SCN5A variants perform poorly. We investigated if instead we could predict changes to I_Na, leaving the link from I_Na to clinical phenotype for mechanistic simulation studies. An exhaustive list of nonsynonymous missense mutations and resulting changes to I_Na was compiled. We then applied machine-learning methods to this dataset, and found that changes to I_Na could be predicted with higher sensitivity and specificity than most existing predictors of clinical significance. The substituted residues’ location on the protein correlated with channel function and strongly contributed to predictions, while conservedness and physico-chemical properties did not. However, predictions were not sufficiently accurate to form a basis for mechanistic studies. These results show that changes to I_Na, the mechanism through which SCN5A mutations create cardiac risk, are already difficult to predict using purely in-silico methods. This partly explains the limited success of systems to predict clinical significance of SCN5A variants, and underscores the need for functional studies of I_Na in risk assessment.

Reproducible model development in the cardiac electrophysiology Web Lab

The modelling of the electrophysiology of cardiac cells is one of the most mature areas of systems biology. This extended concentration of research effort brings with it new challenges, foremost among which is that of choosing which of these models is most suitable for addressing a particular scientific question. In a previous paper, we presented our initial work in developing an online resource for the characterisation and comparison of electrophysiological cell models in a wide range of experimental scenarios. In that work, we described how we had developed a novel protocol language that allowed us to separate the details of the mathematical model (the majority of cardiac cell models take the form of ordinary differential equations) from the experimental protocol being simulated. We developed a fully-open online repository (which we termed the Cardiac Electrophysiology Web Lab) which allows users to store and compare the results of applying the same experimental protocol to competing models. In the current paper we describe the most recent and planned extensions of this work, focused on supporting the process of model building from experimental data. We outline the necessary work to develop a machine-readable language to describe the process of inferring parameters from wet lab datasets, and illustrate our approach through a detailed example of fitting a model of the hERG channel using experimental data. We conclude by discussing the future challenges in making further progress in this domain towards our goal of facilitating a fully reproducible approach to the development of cardiac cell models.

Mechanically Induced Ectopy via Stretch-Activated Cation-Nonselective Channels Is Caused by Local Tissue Deformation and Results in Ventricular Fibrillation if Triggered on the Repolarization Wave Edge (Commotio Cordis)

Supplemental Digital Content is available in the text.

Background—

External chest impacts (commotio cordis) can cause mechanically induced premature ventricular excitation (PVE_M) and, rarely, ventricular fibrillation (VF). Because block of stretch-sensitive ATP-inactivated potassium channels curtailed VF occurrence in a porcine model of commotio cordis, VF has been suggested to arise from abnormal repolarization caused by stretch activation of potassium channels. Alternatively, VF could result from abnormal excitation by PVE_M, overlapping with normal repolarization-related electric heterogeneity. Here, we investigate mechanisms and determinants of PVE_M induction and its potential role in commotio cordis–induced VF.

Methods and Results—

Subcontusional mechanical stimuli were applied to isolated rabbit hearts during optical voltage mapping, combined with pharmacological block of ATP-inactivated potassium or stretch-activated cation-nonselective channels. We demonstrate that local mechanical stimulation reliably triggers PVE_M at the contact site, with inducibility predicted by local tissue indentation. PVE_M induction is diminished by pharmacological block of stretch-activated cation-nonselective channels. In hearts where electrocardiogram T waves involve a well-defined repolarization edge traversing the epicardium, PVE_M can reliably provoke VF if, and only if, the mechanical stimulation site overlaps the repolarization wave edge. In contrast, application of short-lived intraventricular pressure surges neither triggers PVE_M nor changes repolarization. ATP-inactivated potassium channel block has no effect on PVE_M inducibility per se, but shifts it to later time points by delaying repolarization and prolonging refractoriness.

Conclusions—

Local mechanical tissue deformation determines PVE_M induction via stretch-activation of cation-nonselective channels, with VF induction requiring PVE_M overlap with the trailing edge of a normal repolarization wave. This defines a narrow, subject-specific vulnerable window for commotio cordis–induced VF that exists both in time and in space.

Comparing maximum rate and sustainability of pacing by mechanical vs. electrical stimulation in the Langendorff-perfused rabbit heart

Aims

Mechanical stimulation (MS) represents a readily available, non-invasive means of pacing the asystolic or bradycardic heart in patients, but benefits of MS at higher heart rates are unclear. Our aim was to assess the maximum rate and sustainability of excitation by MS vs. electrical stimulation (ES) in the isolated heart under normal physiological conditions.

Methods and results

Trains of local MS or ES at rates exceeding intrinsic sinus rhythm (overdrive pacing; lowest pacing rates 2.5±0.5 Hz) were applied to the same mid-left ventricular free-wall site on the epicardium of Langendorff-perfused rabbit hearts. Stimulation rates were progressively increased, with a recovery period of normal sinus rhythm between each stimulation period. Trains of MS caused repeated focal ventricular excitation from the site of stimulation. The maximum rate at which MS achieved 1:1 capture was lower than during ES (4.2±0.2 vs. 5.9±0.2 Hz, respectively). At all overdrive pacing rates for which repetitive MS was possible, 1:1 capture was reversibly lost after a finite number of cycles, even though same-site capture by ES remained possible. The number of MS cycles until loss of capture decreased with rising stimulation rate. If interspersed with ES, the number of MS to failure of capture was lower than for MS only.

Conclusion

In this study, we demonstrate that the maximum pacing rate at which MS can be sustained is lower than that for same-site ES in isolated heart, and that, in contrast to ES, the sustainability of successful 1:1 capture by MS is limited. The mechanism(s) of differences in MS vs. ES pacing ability, potentially important for emergency heart rhythm management, are currently unknown, thus warranting further investigation.

Intrinsic regulation of sinoatrial node function and the zebrafish as a model of stretch effects on pacemaking

Excitation of the heart occurs in a specialised region known as the sinoatrial node (SAN). Tight regulation of SAN function is essential for the maintenance of normal heart rhythm and the response to (patho-)physiological changes. The SAN is regulated by extrinsic (central nervous system) and intrinsic (neurons, peptides, mechanics) factors. The positive chronotropic response to stretch in particular is essential for beat-by-beat adaptation to changes in hemodynamic load. Yet, the mechanism of this stretch response is unknown, due in part to the lack of an appropriate experimental model for targeted investigations. We have been investigating the zebrafish as a model for the study of intrinsic regulation of SAN function. In this paper, we first briefly review current knowledge of the principal components of extrinsic and intrinsic SAN regulation, derived primarily from experiments in mammals, followed by a description of the zebrafish as a novel experimental model for studies of intrinsic SAN regulation. This mini-review is followed by an original investigation of the response of the zebrafish isolated SAN to controlled stretch. Stretch causes an immediate and continuous increase in beating rate in the zebrafish isolated SAN. This increase reaches a maximum part way through a period of sustained stretch, with the total change dependent on the magnitude and direction of stretch. This is comparable to what occurs in isolated SAN from most mammals (including human), suggesting that the zebrafish is a novel experimental model for the study of mechanisms involved in the intrinsic regulation of SAN function by mechanical effects.

Electrotonic coupling of excitable and nonexcitable cells in the heart revealed by optogenetics

Electrophysiological studies of excitable organs usually focus on action potential (AP)-generating cells, whereas nonexcitable cells are generally considered as barriers to electrical conduction. Whether nonexcitable cells may modulate excitable cell function or even contribute to AP conduction via direct electrotonic coupling to AP-generating cells is unresolved in the heart: such coupling is present in vitro, but conclusive evidence in situ is lacking. We used genetically encoded voltage-sensitive fluorescent protein 2.3 (VSFP2.3) to monitor transmembrane potential in either myocytes or nonmyocytes of murine hearts. We confirm that VSFP2.3 allows measurement of cell type-specific electrical activity. We show that VSFP2.3, expressed solely in nonmyocytes, can report cardiomyocyte AP-like signals at the border of healed cryoinjuries. Using EM-based tomographic reconstruction, we further discovered tunneling nanotube connections between myocytes and nonmyocytes in cardiac scar border tissue. Our results provide direct electrophysiological evidence of heterocellular electrotonic coupling in native myocardium and identify tunneling nanotubes as a possible substrate for electrical cell coupling that may be in addition to previously discovered connexins at sites of myocyte-nonmyocyte contact in the heart. These findings call for reevaluation of cardiac nonmyocyte roles in electrical connectivity of the heterocellular heart.

The Cardiac Electrophysiology Web Lab

Computational modeling of cardiac cellular electrophysiology has a long history, and many models are now available for different species, cell types, and experimental preparations. This success brings with it a challenge: how do we assess and compare the underlying hypotheses and emergent behaviors so that we can choose a model as a suitable basis for a new study or to characterize how a particular model behaves in different scenarios? We have created an online resource for the characterization and comparison of electrophysiological cell models in a wide range of experimental scenarios. The details of the mathematical model (quantitative assumptions and hypotheses formulated as ordinary differential equations) are separated from the experimental protocol being simulated. Each model and protocol is then encoded in computer-readable formats. A simulation tool runs virtual experiments on models encoded in CellML, and a website (https://chaste.cs.ox.ac.uk/WebLab) provides a friendly interface, allowing users to store and compare results. The system currently contains a sample of 36 models and 23 protocols, including current-voltage curve generation, action potential properties under steady pacing at different rates, restitution properties, block of particular channels, and hypo-/hyperkalemia. This resource is publicly available, open source, and free, and we invite the community to use it and become involved in future developments. Investigators interested in comparing competing hypotheses using models can make a more informed decision, and those developing new models can upload them for easy evaluation under the existing protocols, and even add their own protocols.

Minimum information required for a DMET experiment reporting

AIM

To provide pharmacogenomics reporting guidelines, the information and tools required for reporting to public omic databases.

MATERIAL & METHODS

For effective DMET data interpretation, sharing, interoperability, reproducibility and reporting, we propose the Minimum Information required for a DMET Experiment (MIDE) reporting.

RESULTS

MIDE provides reporting guidelines and describes the information required for reporting, data storage and data sharing in the form of XML.

CONCLUSION

The MIDE guidelines will benefit the scientific community with pharmacogenomics experiments, including reporting pharmacogenomics data from other technology platforms, with the tools that will ease and automate the generation of such reports using the standardized MIDE XML schema, facilitating the sharing, dissemination, reanalysis of datasets through accessible and transparent pharmacogenomics data reporting.

Myokit: A simple interface to cardiac cellular electrophysiology

Myokit is a new powerful and versatile software tool for modeling and simulation of cardiac cellular electrophysiology. Myokit consists of an easy-to-read modeling language, a graphical user interface, single and multi-cell simulation engines and a library of advanced analysis tools accessible through a Python interface. Models can be loaded from Myokit's native file format or imported from CellML. Model export is provided to C, MATLAB, CellML, CUDA and OpenCL. Patch-clamp data can be imported and used to estimate model parameters. In this paper, we review existing tools to simulate the cardiac cellular action potential to find that current tools do not cater specifically to model development and that there is a gap between easy-to-use but limited software and powerful tools that require strong programming skills from their users. We then describe Myokit's capabilities, focusing on its model description language, simulation engines and import/export facilities in detail. Using three examples, we show how Myokit can be used for clinically relevant investigations, multi-model testing and parameter estimation in Markov models, all with minimal programming effort from the user. This way, Myokit bridges a gap between performance, versatility and user-friendliness.

Deranged sodium to sudden death

In February 2014, a group of scientists convened as part of the University of California Davis Cardiovascular Symposium to bring together experimental and mathematical modelling perspectives and discuss points of consensus and controversy on the topic of sodium in the heart. This paper summarizes the topics of presentation and discussion from the symposium, with a focus on the role of aberrant sodium channels and abnormal sodium homeostasis in cardiac arrhythmias and pharmacotherapy from the subcellular scale to the whole heart. Two following papers focus on Na(+) channel structure, function and regulation, and Na(+)/Ca(2+) exchange and Na(+)/K(+) ATPase. The UC Davis Cardiovascular Symposium is a biannual event that aims to bring together leading experts in subfields of cardiovascular biomedicine to focus on topics of importance to the field. The focus on Na(+) in the 2014 symposium stemmed from the multitude of recent studies that point to the importance of maintaining Na(+) homeostasis in the heart, as disruption of homeostatic processes are increasingly identified in cardiac disease states. Understanding how disruption in cardiac Na(+)-based processes leads to derangement in multiple cardiac components at the level of the cell and to then connect these perturbations to emergent behaviour in the heart to cause disease is a critical area of research. The ubiquity of disruption of Na(+) channels and Na(+) homeostasis in cardiac disorders of excitability and mechanics emphasizes the importance of a fundamental understanding of the associated mechanisms and disease processes to ultimately reveal new targets for human therapy.

Human cardiac systems electrophysiology and arrhythmogenesis: iteration of experiment and computation

Human cardiac electrophysiology (EP) is a unique system for computational modelling at multiple scales. Due to the complexity of the cardiac excitation sequence, coordinated activity must occur from the single channel to the entire myocardial syncytium. Thus, sophisticated computational algorithms have been developed to investigate cardiac EP at the level of ion channels, cardiomyocytes, multicellular tissues, and the whole heart. Although understanding of each functional level will ultimately be important to thoroughly understand mechanisms of physiology and disease, cardiac arrhythmias are expressly the product of cardiac tissue-containing enough cardiomyocytes to sustain a reentrant loop of activation. In addition, several properties of cardiac cellular EP, that are critical for arrhythmogenesis, are significantly altered by cell-to-cell coupling. However, relevant human cardiac EP data, upon which to develop or validate models at all scales, has been lacking. Thus, over several years, we have developed a paradigm for multiscale human heart physiology investigation and have recovered and studied over 300 human hearts. We have generated a rich experimental dataset, from which we better understand mechanisms of arrhythmia in human and can improve models of human cardiac EP. In addition, in collaboration with computational physiologists, we are developing a database for the deposition of human heart experimental data, including thorough experimental documentation. We anticipate that accessibility to this human heart dataset will further human EP computational investigations, as well as encourage greater data transparency within the field of cardiac EP.

In silico assessment of drug safety in human heart applied to late sodium current blockers

Drug-induced action potential (AP) prolongation leading to Torsade de Pointes is a major concern for the development of anti-arrhythmic drugs. Nevertheless the development of improved anti-arrhythmic agents, some of which may block different channels, remains an important opportunity. Partial block of the late sodium current (I(NaL)) has emerged as a novel anti-arrhythmic mechanism. It can be effective in the settings of free radical challenge or hypoxia. In addition, this approach can attenuate pro-arrhythmic effects of blocking the rapid delayed rectifying K(+) current (I(Kr)). The main goal of our computational work was to develop an in-silico tool for preclinical anti-arrhythmic drug safety assessment, by illustrating the impact of I(Kr)/I(NaL) ratio of steady-state block of drug candidates on "torsadogenic" biomarkers. The O'Hara et al. AP model for human ventricular myocytes was used. Biomarkers for arrhythmic risk, i.e., AP duration, triangulation, reverse rate-dependence, transmural dispersion of repolarization and electrocardiogram QT intervals, were calculated using single myocyte and one-dimensional strand simulations. Predetermined amounts of block of I(NaL) and I(Kr) were evaluated. "Safety plots" were developed to illustrate the value of the specific biomarker for selected combinations of IC(50)s for I(Kr) and I(NaL) of potential drugs. The reference biomarkers at baseline changed depending on the "drug" specificity for these two ion channel targets. Ranolazine and GS967 (a novel potent inhibitor of I(NaL)) yielded a biomarker data set that is considered safe by standard regulatory criteria. This novel in-silico approach is useful for evaluating pro-arrhythmic potential of drugs and drug candidates in the human ventricle.

Computer-based prediction of the drug proarrhythmic effect: problems, issues, known and suspected challenges

It is likely that computer modelling and simulations will become an element of comprehensive cardiac safety testing. Their role would be primarily the integration and the interpretation of previously gathered data. There are still unanswered questions and issues which we list and describe below. They include sources of data used for the development of the models as well as data utilized as input information, which can come from the in vitro studies and the quantitative structure-activity relationship models. The pharmacokinetics of the drugs in question play a crucial role as their active concentration should be considered, yet the question remains where is the right place to assess it. The pharmacodynamic angle includes complications coming from multiple drugs (i.e. active metabolites) acting in parallel as well as the type of interaction with (potentially) multiple affected channels. Once established, the model and the methodology of its use should be further validated, optimistically against individual data reported at the clinical level as the physiological, anatomical, and genetic parameters play a crucial role in the drug-triggered arrhythmia induction. All the abovementioned issues should be at least considered and-hopefully-resolved, to properly utilize the mathematical models for a cardiac safety assessment.

In Silico Organ Modelling in Predicting Efficacy and Safety of New Medicines

The development of new medicines faces important challenges due to difficulties in the assessment of their efficacy and their safety in the targeted human population. In silico approaches through the use of mathematical modelling and computer simulations are increasingly being used to overcome some of the limitations of current experimental methods used in the development of new medicines. This chapter describes state-of-the-art in silico approaches for the evaluation of the safety and efficacy of medicines targeting important causes of mortality such as cardiovascular disease. Firstly, we describe the in silico multi-scale mathematical models and simulation techniques required to describe drug-induced effects on physiological systems such as the heart from the subcellular to the whole organ level. Then we illustrate the power of in silico approaches used to augment experimental and clinical investigations, by providing the framework to unravel multi-scale mechanisms underlying variability in the response to medicines and to focus on effects in human rather than animal models. We devote the last part of the chapter to discussing the process of validation of in silico models and simulations, which is key in building up their credibility.

Prediction of Thorough QT study results using action potential simulations based on ion channel screens

INTRODUCTION

Detection of drug-induced pro-arrhythmic risk is a primary concern for pharmaceutical companies and regulators. Increased risk is linked to prolongation of the QT interval on the body surface ECG. Recent studies have shown that multiple ion channel interactions can be required to predict changes in ventricular repolarisation and therefore QT intervals. In this study we attempt to predict the result of the human clinical Thorough QT (TQT) study, using multiple ion channel screening which is available early in drug development.

METHODS

Ion current reduction was measured, in the presence of marketed drugs which have had a TQT study, for channels encoded by hERG, CaV1.2, NaV1.5, KCNQ1/MinK, and Kv4.3/KChIP2.2. The screen was performed on two platforms - IonWorks Quattro (all 5 channels, 34 compounds), and IonWorks Barracuda (hERG & CaV1.2, 26 compounds). Concentration-effect curves were fitted to the resulting data, and used to calculate a percentage reduction in each current at a given concentration. Action potential simulations were then performed using the ten Tusscher and Panfilov (2006), Grandi et al. (2010) and O'Hara et al. (2011) human ventricular action potential models, pacing at 1Hz and running to steady state, for a range of concentrations.

RESULTS

We compared simulated action potential duration predictions with the QT prolongation observed in the TQT studies. At the estimated concentrations, simulations tended to underestimate any observed QT prolongation. When considering a wider range of concentrations, and conventional patch clamp rather than screening data for hERG, prolongation of ≥5ms was predicted with up to 79% sensitivity and 100% specificity.

DISCUSSION

This study provides a proof-of-principle for the prediction of human TQT study results using data available early in drug development. We highlight a number of areas that need refinement to improve the method's predictive power, but the results suggest that such approaches will provide a useful tool in cardiac safety assessment.

Images as drivers of progress in cardiac computational modelling

Computational models have become a fundamental tool in cardiac research. Models are evolving to cover multiple scales and physical mechanisms. They are moving towards mechanistic descriptions of personalised structure and function, including effects of natural variability. These developments are underpinned to a large extent by advances in imaging technologies. This article reviews how novel imaging technologies, or the innovative use and extension of established ones, integrate with computational models and drive novel insights into cardiac biophysics. In terms of structural characterization, we discuss how imaging is allowing a wide range of scales to be considered, from cellular levels to whole organs. We analyse how the evolution from structural to functional imaging is opening new avenues for computational models, and in this respect we review methods for measurement of electrical activity, mechanics and flow. Finally, we consider ways in which combined imaging and modelling research is likely to continue advancing cardiac research, and identify some of the main challenges that remain to be solved.

Population of computational rabbit-specific ventricular action potential models for investigating sources of variability in cellular repolarisation

Variability is observed at all levels of cardiac electrophysiology. Yet, the underlying causes and importance of this variability are generally unknown, and difficult to investigate with current experimental techniques. The aim of the present study was to generate populations of computational ventricular action potential models that reproduce experimentally observed intercellular variability of repolarisation (represented by action potential duration) and to identify its potential causes. A systematic exploration of the effects of simultaneously varying the magnitude of six transmembrane current conductances (transient outward, rapid and slow delayed rectifier K⁺, inward rectifying K⁺, L-type Ca²⁺, and Na⁺/K⁺ pump currents) in two rabbit-specific ventricular action potential models (Shannon et al. and Mahajan et al.) at multiple cycle lengths (400, 600, 1,000 ms) was performed. This was accomplished with distributed computing software specialised for multi-dimensional parameter sweeps and grid execution. An initial population of 15,625 parameter sets was generated for both models at each cycle length. Action potential durations of these populations were compared to experimentally derived ranges for rabbit ventricular myocytes. 1,352 parameter sets for the Shannon model and 779 parameter sets for the Mahajan model yielded action potential duration within the experimental range, demonstrating that a wide array of ionic conductance values can be used to simulate a physiological rabbit ventricular action potential. Furthermore, by using clutter-based dimension reordering, a technique that allows visualisation of multi-dimensional spaces in two dimensions, the interaction of current conductances and their relative importance to the ventricular action potential at different cycle lengths were revealed. Overall, this work represents an important step towards a better understanding of the role that variability in current conductances may play in experimentally observed intercellular variability of rabbit ventricular action potential repolarisation.

Combining wet and dry research: experience with model development for cardiac mechano-electric structure-function studies

Since the development of the first mathematical cardiac cell model 50 years ago, computational modelling has become an increasingly powerful tool for the analysis of data and for the integration of information related to complex cardiac behaviour. Current models build on decades of iteration between experiment and theory, representing a collective understanding of cardiac function. All models, whether computational, experimental, or conceptual, are simplified representations of reality and, like tools in a toolbox, suitable for specific applications. Their range of applicability can be explored (and expanded) by iterative combination of 'wet' and 'dry' investigation, where experimental or clinical data are used to first build and then validate computational models (allowing integration of previous findings, quantitative assessment of conceptual models, and projection across relevant spatial and temporal scales), while computational simulations are utilized for plausibility assessment, hypotheses-generation, and prediction (thereby defining further experimental research targets). When implemented effectively, this combined wet/dry research approach can support the development of a more complete and cohesive understanding of integrated biological function. This review illustrates the utility of such an approach, based on recent examples of multi-scale studies of cardiac structure and mechano-electric function.

mRNA expression levels in failing human hearts predict cellular electrophysiological remodeling: a population-based simulation study

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

Application of cardiac electrophysiology simulations to pro-arrhythmic safety testing

Concerns over cardiac side effects are the largest single cause of compound attrition during pharmaceutical drug development. For a number of years, biophysically detailed mathematical models of cardiac electrical activity have been used to explore how a compound, interfering with specific ion-channel function, may explain effects at the cell-, tissue- and organ-scales. With the advent of high-throughput screening of multiple ion channels in the wet-lab, and improvements in computational modelling of their effects on cardiac cell activity, more reliable prediction of pro-arrhythmic risk is becoming possible at the earliest stages of drug development. In this paper, we review the current use of biophysically detailed mathematical models of cardiac myocyte electrical activity in drug safety testing, and suggest future directions to employ the full potential of this approach.

Computational approaches to understand cardiac electrophysiology and arrhythmias

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

Bridging experiments, models and simulations: an integrative approach to validation in computational cardiac electrophysiology

Computational models in physiology often integrate functional and structural information from a large range of spatiotemporal scales from the ionic to the whole organ level. Their sophistication raises both expectations and skepticism concerning how computational methods can improve our understanding of living organisms and also how they can reduce, replace, and refine animal experiments. A fundamental requirement to fulfill these expectations and achieve the full potential of computational physiology is a clear understanding of what models represent and how they can be validated. The present study aims at informing strategies for validation by elucidating the complex interrelations among experiments, models, and simulations in cardiac electrophysiology. We describe the processes, data, and knowledge involved in the construction of whole ventricular multiscale models of cardiac electrophysiology. Our analysis reveals that models, simulations, and experiments are intertwined, in an assemblage that is a system itself, namely the model-simulation-experiment (MSE) system. We argue that validation is part of the whole MSE system and is contingent upon 1) understanding and coping with sources of biovariability; 2) testing and developing robust techniques and tools as a prerequisite to conducting physiological investigations; 3) defining and adopting standards to facilitate the interoperability of experiments, models, and simulations; 4) and understanding physiological validation as an iterative process that contributes to defining the specific aspects of cardiac electrophysiology the MSE system targets, rather than being only an external test, and that this is driven by advances in experimental and computational methods and the combination of both.

Systems biology of the heart: hype or hope?

Systems biology, the approach that combines reduction and integration to explore dynamic structure-function interrelations across biomedically relevant spatio-temporal scales, is applied to heart research.

Inter-model consistency and complementarity: learning from ex-vivo imaging and electrophysiological data towards an integrated understanding of cardiac physiology

Computational models of the heart at various scales and levels of complexity have been independently developed, parameterised and validated using a wide range of experimental data for over four decades. However, despite remarkable progress, the lack of coordinated efforts to compare and combine these computational models has limited their impact on the numerous open questions in cardiac physiology. To address this issue, a comprehensive dataset has previously been made available to the community that contains the cardiac anatomy and fibre orientations from magnetic resonance imaging as well as epicardial transmembrane potentials from optical mapping measured on a perfused ex-vivo porcine heart. This data was used to develop and customize four models of cardiac electrophysiology with different level of details, including a personalized fast conduction Purkinje system, a maximum a posteriori estimation of the 3D distribution of transmembrane potential, the personalization of a simplified reaction-diffusion model, and a detailed biophysical model with generic conduction parameters. This study proposes the integration of these four models into a single modelling and simulation pipeline, after analyzing their common features and discrepancies. The proposed integrated pipeline demonstrates an increase prediction power of depolarization isochrones in different pacing conditions.

Considerations for the use of cellular electrophysiology models within cardiac tissue simulations

The use of mathematical models to study cardiac electrophysiology has a long history, and numerous cellular scale models are now available, covering a range of species and cell types. Their use to study emergent properties in tissue is also widespread, typically using the monodomain or bidomain equations coupled to one or more cell models. Despite the relative maturity of this field, little has been written looking in detail at the interface between the cellular and tissue-level models. Mathematically this is relatively straightforward and well-defined. There are however many details and potential inconsistencies that need to be addressed, in order to ensure correct operation of a cellular model within a tissue simulation. This paper will describe these issues and how to address them. Simply having models available in a common format such as CellML is still of limited utility, with significant manual effort being required to integrate these models within a tissue simulation. We will thus also discuss the facilities available for automating this in a consistent fashion within Chaste, our robust and high-performance cardiac electrophysiology simulator. It will be seen that a common theme arising is the need to go beyond a representation of the model mathematics in a standard language, to include additional semantic information required in determining the model's interface, and hence to enhance interoperability. Such information can be added as metadata, but agreement is needed on the terms to use, including development of appropriate ontologies, if reliable automated use of CellML models is to become common.

A framework for the study of multiple realizations: the importance of levels of analysis

The brain may undergo functional reorganizations. Selective loss of sensory input or training within a restricted part of a modality cause "shifts" within for instance somatotopic or tonotopic maps. Cross-modal plasticity occurs when input within a modality is absent - e.g., in the congenitally blind. Reorganizations are also found in functional recovery after brain injury. Focusing on such reorganizations, it may be studied whether a cognitive or conscious process can exclusively be mediated by one neural substrate - or may be associated with multiple neural representations. This is typically known as the problem of multiple realization - an essentially empirical issue with wide theoretical implications. This issue may appear to have a simple solution. When, for instance, the symptoms associated with brain injury disappear and the recovery is associated with increased activities within spared regions of the brain, it is tempting to conclude that the processes originally associated with the injured part of the brain are now mediated by an alternative neural substrate. Such a conclusion is, however, not a simple matter. Without a more thorough analysis, it cannot be concluded that a functional recovery of for instance language or attention is necessarily associated with a novel representation of the processes lost to injury. Alternatively, for instance, the recovery may reflect that apparently similar surface phenomena are obtained via dissimilar cognitive mechanisms. In this paper we propose a theoretical framework, which we believe can guide the design and interpretations of studies of post-traumatic recovery. It is essential to distinguish between a number of levels of analysis - including a differentiation between the surface phenomena and the underlying information processing - when addressing, for instance, whether a pre-traumatic and post-traumatically recovered cognitive or conscious process are actually the same. We propose a (somewhat preliminary) system of levels of analysis, which can be applied to such studies.

A framework for the study of multiple realizations: the importance of levels of analysis

The brain may undergo functional reorganizations. Selective loss of sensory input or training within a restricted part of a modality cause "shifts" within for instance somatotopic or tonotopic maps. Cross-modal plasticity occurs when input within a modality is absent - e.g., in the congenitally blind. Reorganizations are also found in functional recovery after brain injury. Focusing on such reorganizations, it may be studied whether a cognitive or conscious process can exclusively be mediated by one neural substrate - or may be associated with multiple neural representations. This is typically known as the problem of multiple realization - an essentially empirical issue with wide theoretical implications. This issue may appear to have a simple solution. When, for instance, the symptoms associated with brain injury disappear and the recovery is associated with increased activities within spared regions of the brain, it is tempting to conclude that the processes originally associated with the injured part of the brain are now mediated by an alternative neural substrate. Such a conclusion is, however, not a simple matter. Without a more thorough analysis, it cannot be concluded that a functional recovery of for instance language or attention is necessarily associated with a novel representation of the processes lost to injury. Alternatively, for instance, the recovery may reflect that apparently similar surface phenomena are obtained via dissimilar cognitive mechanisms. In this paper we propose a theoretical framework, which we believe can guide the design and interpretations of studies of post-traumatic recovery. It is essential to distinguish between a number of levels of analysis - including a differentiation between the surface phenomena and the underlying information processing - when addressing, for instance, whether a pre-traumatic and post-traumatically recovered cognitive or conscious process are actually the same. We propose a (somewhat preliminary) system of levels of analysis, which can be applied to such studies.

Single-sensor system for spatially resolved, continuous, and multiparametric optical mapping of cardiac tissue

Background

Simultaneous optical mapping of multiple electrophysiologically relevant parameters in living myocardium is desirable for integrative exploration of mechanisms underlying heart rhythm generation under normal and pathophysiologic conditions. Current multiparametric methods are technically challenging, usually involving multiple sensors and moving parts, which contributes to high logistic and economic thresholds that prevent easy application of the technique.

Objective

The purpose of this study was to develop a simple, affordable, and effective method for spatially resolved, continuous, simultaneous, and multiparametric optical mapping of the heart, using a single camera.

Methods

We present a new method to simultaneously monitor multiple parameters using inexpensive off-the-shelf electronic components and no moving parts. The system comprises a single camera, commercially available optical filters, and light-emitting diodes (LEDs), integrated via microcontroller-based electronics for frame-accurate illumination of the tissue. For proof of principle, we illustrate measurement of four parameters, suitable for ratiometric mapping of membrane potential (di-4-ANBDQPQ) and intracellular free calcium (fura-2), in an isolated Langendorff-perfused rat heart during sinus rhythm and ectopy, induced by local electrical or mechanical stimulation.

Results

The pilot application demonstrates suitability of this imaging approach for heart rhythm research in the isolated heart. In addition, locally induced excitation, whether stimulated electrically or mechanically, gives rise to similar ventricular propagation patterns.

Conclusion

Combining an affordable camera with suitable optical filters and microprocessor-controlled LEDs, single-sensor multiparametric optical mapping can be practically implemented in a simple yet powerful configuration and applied to heart rhythm research. The moderate system complexity and component cost is destined to lower the threshold to broader application of functional imaging and to ease implementation of more complex optical mapping approaches, such as multiparametric panoramic imaging. A proof-of-principle application confirmed that although electrically and mechanically induced excitation occur by different mechanisms, their electrophysiologic consequences downstream from the point of activation are not dissimilar.