The Resting Potential and K+ Currents in Primary Human Articular Chondrocytes

Human transplant programs provide significant opportunities for detailed in vitro assessments of physiological properties of selected tissues and cell types. We present a semi-quantitative study of the fundamental electrophysiological/biophysical characteristics of human chondrocytes, focused on K+ transport mechanisms, and their ability to regulate to the resting membrane potential, Em. Patch clamp studies on these enzymatically isolated human chondrocytes reveal consistent expression of at least three functionally distinct K+ currents, as well as transient receptor potential (TRP) currents. The small size of these cells and their exceptionally low current densities present significant technical challenges for electrophysiological recordings. These limitations have been addressed by parallel development of a mathematical model of these K+ and TRP channel ion transfer mechanisms in an attempt to reveal their contributions to Em. In combination, these experimental results and simulations yield new insights into: (i) the ionic basis for Em and its expected range of values; (ii) modulation of Em by the unique articular joint extracellular milieu; (iii) some aspects of TRP channel mediated depolarization-secretion coupling; (iv) some of the essential biophysical principles that regulate K+ channel function in “chondrons.” The chondron denotes the chondrocyte and its immediate extracellular compartment. The presence of discrete localized surface charges and associated zeta potentials at the chondrocyte surface are regulated by cell metabolism and can modulate interactions of chondrocytes with the extracellular matrix. Semi-quantitative analysis of these factors in chondrocyte/chondron function may yield insights into progressive osteoarthritis

Abnormal Tissue Zone Detection and Average Active Stress Estimation in Patients with LV Dysfunction

Detection of regional ventricular dysfunction is a challenging problem. This study presents an efficient method based on ultrasound (US) imaging and finite element (FE) analysis, for detecting akinetic and dyskinetic regions in the left ventricle (LV). The underlying hypothesis is that the contraction of a healthy LV is approximately homogeneous. Therefore, any deviations between the image-based measured deformation and a homogeneous contraction FE model should correspond to a pathological region. The method was first successfully applied to synthetic data simulating an acute ischemia; it demonstrated that the pathological areas were revealed with a higher contrast than those observed directly in the deformation maps. The technique was then applied to a cohort of eight left bundle branch block (LBBB) patients. For this group, the heterogeneities were significantly less pronounced than those revealed for the synthetic cases but the method was still able to identify the abnormal regions of the LV. This study indicated the potential clinical utility of the method by its simplicity in a patient-specific context and its ability to quickly identify various heterogeneities in LV function. Further studies are required to determine the model accuracy in other pathologies and to investigate its robustness to noise and image artifacts

Na+ current expression in human atrial myofibroblasts: identity and functional roles

In the mammalian heart fibroblasts have important functional roles in both healthy conditions and diseased states. During pathophysiological challenges, a closely related myofibroblast cell population emerges, and can have distinct and significant roles.Recently, it has been reported that human atrial myofibroblasts can express a Na+ current, INa. Some of the biophysical properties and molecular features suggest that this INa is due to expression of Nav 1.5, the same Na+ channel α subunit that generates the predominant INa in myocytes from adult mammalian heart. In principle, expression of Nav 1.5 could give rise to regenerative action potentials in the fibroblasts/myofibroblasts. This would suggest an active as opposed to passive role for fibroblasts/myofibroblasts in both the ‘trigger’ and the ‘substrate’ components of cardiac rhythm disturbances.Our goals in this preliminary study were: (i) to confirm and extend the electrophysiological characterization of INa in a human atrial fibroblast/myofibroblast cell population maintained in conventional 2-D tissue culture; (ii) to identify key molecular properties of the α and β subunits of these Na+ channel(s); (iii) to define the biophysical and pharmacological properties of this INa ; (iv) to integrate the available multi-disciplinary data, and attempt to illustrate its functional consequences, using a mathematical model in which the human atrial myocyte is coupled via connexins to fixed numbers of fibroblasts/myofibroblasts in a syncytial arrangement.Our experimental findings confirm that a significant fraction (~40-50%) of these human atrial myofibroblasts can express INa. However, our results suggest that INa may be generated by Nav 1.9, Nav 1.2, and Nav 1.5. Our findings, when complemented with mathematical modeling, provide a background for re-evaluating pharmacological management of supraventricular rhythm disorders, e.g. persistent atrial fibrillation

Unstable eigenmodes are possible drivers for cardiac arrhythmias

The well-organized contraction of each heartbeat is enabled by an electrical wave traversing and exciting the myocardium in a regular manner. Perturbations to this wave, referred to as arrhythmias, can lead to lethal fibrillation if not treated within minutes. One manner in which arrhythmias originate is an ill-fated interaction of the regular electrical signal controlling the heartbeat, the sinus wave, with an ectopic stimulus. It is not fully understood how and when ectopic waves are generated. Based on mathematical models, we show that ectopic beats can be characterized in terms of unstable eigenmodes of the resting state

Atrial Fibrosis Hampers Non-invasive Localization of Atrial Ectopic Foci From Multi-Electrode Signals: A 3D Simulation Study

[EN] Introduction: Focal atrial tachycardia is commonly treated by radio frequency ablation with an acceptable long-term success. Although the location of ectopic foci tends to appear in specific hot-spots, they can be located virtually in any atrial region. Multi-electrode surface ECG systems allow acquiring dense body surface potential maps (BSPM) for non-invasive therapy planning of cardiac arrhythmia. However, the activation of the atria could be affected by fibrosis and therefore biomarkers based on BSPM need to take these effects into account. We aim to analyze the effect of fibrosis on a BSPM derived index, and its potential application to predict the location of ectopic foci in the atria. Methodology: We have developed a 3D atrial model that includes 5 distributions of patchy fibrosis in the left atrium at 5 different stages. Each stage corresponds to a different amount of fibrosis that ranges from 2 to 40%. The 25 resulting 3D models were used for simulation of Focal Atrial Tachycardia (FAT), triggered from 19 different locations described in clinical studies. BSPM were obtained for all simulations, and the body surface potential integral maps (BSPiM) were calculated to describe atrial activations. A machine learning (ML) pipeline using a supervised learning model and support vector machine was developed to learn the BSPM patterns of each of the 475 activation sequences and relate them to the origin of the FAT source. Results: Activation maps for stages with more than 15% of fibrosis were greatly affected, producing conduction blocks and delays in propagation. BSPiMs did not always cluster into non-overlapped groups since BSPiMs were highly altered by the conduction blocks. From stage 3 (15% fibrosis) the BSPiMs showed differences for ectopic beats placed around the area of the pulmonary veins. Classification results were mostly above 84% for all the configurations studied when a large enough number of electrodes were used to map the torso. However, the presence of fibrosis increases the area of the ectopic focus location and therefore decreases the utility for the electrophysiologist. Conclusions: The results indicate that the proposed ML pipeline is a promising methodology for non-invasive ectopic foci localization from BSPM signal even when fibrosis is present.This work was partially supported by Ministerio de Economia y Competitividad and Fondo Europeo de Desarrollo Regional (FEDER) DPI2015-69125-R and TIN2014-59932-JIN (MINECO/FEDER, UE).Godoy, EJ.; Lozano, M.; García-Fernández, I.; Ferrer-Albero, A.; Macleod, R.; Saiz, J.; Sebastián, R. (2018). Atrial Fibrosis Hampers Non-invasive Localization of Atrial Ectopic Foci From Multi-Electrode Signals: A 3D Simulation Study. Frontiers in Physiology. 9:1-18. https://doi.org/10.3389/fphys.2018.00404S1189Boyle, P. 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Sensitivity and uncertainty analysis of two human atrial cardiac cell models using gaussian process emulators

Biophysically detailed cardiac cell models reconstruct the action potential and calcium dynamics of cardiac myocytes. They aim to capture the biophysics of current flow through ion channels, pumps, and exchangers in the cell membrane, and are highly detailed. However, the relationship between model parameters and model outputs is difficult to establish because the models are both complex and non-linear. The consequences of uncertainty and variability in model parameters are therefore difficult to determine without undertaking large numbers of model evaluations. The aim of the present study was to demonstrate how sensitivity and uncertainty analysis using Gaussian process emulators can be used for a systematic and quantitive analysis of biophysically detailed cardiac cell models. We selected the Courtemanche and Maleckar models of the human atrial action potential for analysis because these models describe a similar set of currents, with different formulations. In our approach Gaussian processes emulate the main features of the action potential and calcium transient. The emulators were trained with a set of design data comprising samples from parameter space and corresponding model outputs, initially obtained from 300 model evaluations. Variance based sensitivity indices were calculated using the emulators, and first order and total effect indices were calculated for each combination of parameter and output. The differences between the first order and total effect indices indicated that the effect of interactions between parameters was small. A second set of emulators were then trained using a new set of design data with a subset of the model parameters with a sensitivity index of more than 0.1 (10%). This second stage analysis enabled comparison of mechanisms in the two models. The second stage sensitivity indices enabled the relationship between the L-type Ca2+ current and the action potential plateau to be quantified in each model. Our quantitative analysis predicted that changes in maximum conductance of the ultra-rapid K+ channel IKur would have opposite effects on action potential duration in the two models, and this prediction was confirmed by additional simulations. This study has demonstrated that Gaussian process emulators are an effective tool for sensitivity and uncertainty analysis of biophysically detailed cardiac cell models