In Silico Comparison of Phase Maps Based on Action Potential and Extracellular Potential

In this work, a computer simulation of the reentrant ventricular tachycardia (VT) was used to investigate the peculiar properties of phase maps based on transmembrane potentials (TP) and extracellular potentials (EP). The simulation approach included the bidomain model with full myocardium-torso coupling, a realistic ionic model of the human cardiomyocytes and a personalized geometry of the heart and torso. The phase mapping pipeline includes a signal detrending and the Hilbert transform. It was demonstrated that TP-based phase maps correlated well with the propagation of cardiac excitation. In contrast, EP-based phase mapping provides some aberrations which can complicate electrophysiological interpretation of the phase maps in terms of cardiac activation sequence. It was also shown that a modification of the phase computation algorithm, including the sign inversion of signals and a special transformation of the phase plot, can partially eliminate these aberrations and make EP-based phase maps resemble TP-based maps. © 2018 Creative Commons Attribution.Russian Foundation for Basic Research, RFBR: 18-31-00401The reported study was funded by RFBR according to the research project No. 18-31-00401. Development of computer model with personalized geometry was funded by IIP UrB RAS theme No AAAA-A18-118020590031-8, RF Government Act #211 of March 16, 2013 (agreement 02.A03.21.0006), Program of the Presidium RAS #27 (project AAAA-A18-118020590030-1)

Comparison of Depolarization and Depolarization in Mathematical Models of the Left Ventricle and the Longitudinal Ventricular Slice

Myocardial slices are widely used for cardiac electrophysiology research but correspondence of electrophysiological properties between the cardiac slices and the whole heart has not been studied in details. The aim of this study is to investigate the differences in electrophysiological properties between the left ventricle and the longitudinal ventricular slice passing through the apex using mathematical models. ECG signals and the time of activation and repolarization, repolarization dispersion and dispersion of action potential duration were compared. We have shown that the electrophysiological processes in the ventricle and the longitudinal ventricular slice are quite similar, so we believe that cardiac slices can be used to evaluate global electrophysiological properties of the ventricles. The local differences obtained can be explained by differences in geometry and fiber orientation locally affecting depolarization and repolarization in the myocardium. © 2018 Creative Commons Attribution.Russian Foundation for Basic Research, RFBR: 16-31-60015, 18-31-00401This work was supported by IIF UrB RAS theme #AAAA-A18-118020590031-8, RFE Government Act #211 of March 16, 2013, the Program of the Presidium RAS #27 and RFBR (#16-31-60015, 18-31-00401)

Emerging roles of the single EF-hand Ca²⁺ sensor tescalcin in the regulation of gene expression, cell growth and differentiation

© 2016. Published by The Company of Biologists Ltd.Tescalcin (TESC, also known as calcineurin-homologous protein 3, CHP3) is a 24-kDa EF-hand Ca2+-binding protein that has recently emerged as a regulator of cell differentiation and growth. The TESC gene has also been linked to human brain abnormalities, and high expression of tescalcin has been found in several cancers. The expression level of tescalcin changes dramatically during development and upon signal-induced cell differentiation. Recent studies have shown that tescalcin is not only subjected to up- or down-regulation, but also has an active role in pathways that drive cell growth and differentiation programs. At the molecular level, there is compelling experimental evidence showing that tescalcin can directly interact with and regulate the activities of the Na+/H+ exchanger NHE1, subunit 4 of the COP9 signalosome (CSN4) and protein kinase glycogen-synthase kinase 3 (GSK3). In hematopoetic precursor cells, tescalcin has been shown to couple activation of the extracellular signal-regulated kinase (ERK) cascade to the expression of transcription factors that control cell differentiation. The purpose of thisCommentary is to summarize recent efforts that have served to characterize the biochemical, genetic and physiological attributes of tescalcin, and its unique role in the regulation of various cellular functions

The activated charcoal adsorption of phenol

The problems of treatment of the waste water were considered in this work. The main method of the activated charcoal adsorption of phenol was investigated. The adsorption properties of the adsorbent were also considered. Along with it Langmuir's and Friendlich's adsorption isotherm has been studied and analyzed

Role of myocardial properties and pacing lead location on ECG in personalized paced heart models

Personalised cardiac models were built from the computed tomography imaging data for two patients with implanted cardiac resynchronisation therapy devices. The cardiac models comprised a biventricular model of myocardial electrophysiology coupled with a model of the torso to simulate the body surface potential map. The models were verified against electrocardiogams (ECG) recorded in the patients from 240 leads on the body surface under left ventricular pacing. The simulated ECG demonstrated a significant sensitivity to the myocardial anisotropy and location of the pacing electrode tip in the models. An apicobasal cellular heterogeneity was shown to be less significant for the ECG pattern at the paced-ventricle activation than that showed earlier by Keller and co-authors (2012) for the normal activation sequence. © 2017 IEEE Computer Society. All rights reserved.This study was supported by the RAS Presidium Programme I.33Π, and Government of the Russian Federation (agreement 02.A03.21.0006). We used the computational clusters of Ural Federal University and ”URAN” of Institute of Mathematics and Mechanics (Ekaterinburg)

Integrative Modeling of Electrical Properties of Pacemaker Cardiac Cells

This work represents modeling of electrical properties of pacemaker (sinus) cardiac cells. Special attention is paid to electrical potential arising from transmembrane current of Na{+}, K{+} and Ca{2+} ions. This potential is calculated using the NaCaX model. In this respect, molar concentration of ions in the intercellular space which is calculated on the basis of the GENTEX model is essential. Combined use of two different models allows referring this approach to integrative modeling

Effects of Lead Position, Cardiac Rhythm Variation and Drug-induced QT Prolongation on Performance of Machine Learning Methods for ECG Processing

Machine learning shows great performance in various problems of electrocardiography (ECG) signal analysis. However, collecting a dataset for biomedical engineering is a very difficult task. Any dataset for ECG processing contains from 100 to 10,000 times fewer cases than datasets for image or text analysis. This issue is especially important because of physiological phenomena that can significantly change the morphology of heartbeats in ECG signals. In this preliminary study, we analyze the effects of lead choice from the standard ECG recordings, variation of ECG during 24-hours, and the effects of QT-prolongation agents on the performance of machine learning methods for ECG processing. We choose the problem of subject identification for analysis, because this problem may be solved for almost any available dataset of ECG data. In a discussion, we compare our findings with observations from other works that use machine learning for ECG processing with different problem statements. Our results show the importance of training dataset enrichment with ECG signals acquired in specific physiological conditions for obtaining good performance of ECG processing for real applications. © 2020 IEEE.The reported study was supported by RFBR research project No. 19-37-50079 and supported by the IIF UrB RAS theme №AAAA-A18-118020590031-8, RF Government Act #211 of March 16, 2013, the Program of the Presidium RAS

Teaching heart modeling and simulation on parallel computing systems

High Performance Computing (HPC) is an interdisciplinary field of study, which requires learning a number of topics, including not only parallel programming, but also numerical methods and domain science. Stand-alone parallel computing courses are insufficient for thorough HPC education. We present an interdisciplinary track of coherent courses devoted to modeling and simulation of the heart on parallel computing systems for master students at the Ural Federal University. The track consists of three modules: parallel and distributed computing, heart modeling, and numerical methods. Knowledge of numerical methods and heart modeling provides the students with the ability to acquire profound parallel programming skills by working out on the comprehensive programming assignment and complex heart modeling projects. Interdisciplinary approach also increases students’ motivation and involvement. © Springer International Publishing Switzerland 2015.The work is supported by the Programme of Presidium of RAS no. II.4P (PI O.Solovyova). Our study was performed using the “Uran” supercomputer from Institute of Mathematics and Mechanics UrB RAS

Meshless electrophysiological modeling of cardiac resynchronization therapy—benchmark analysis with finite-element methods in experimental data

Computational models of cardiac electrophysiology are promising tools for reducing the rates of non-response patients suitable for cardiac resynchronization therapy (CRT) by optimizing electrode placement. The majority of computational models in the literature are mesh-based, primarily using the finite element method (FEM). The generation of patient-specific cardiac meshes has traditionally been a tedious task requiring manual intervention and hindering the modeling of a large number of cases. Meshless models can be a valid alternative due to their mesh quality independence. The organization of challenges such as the CRT-EPiggy19, providing unique experimental data as open access, enables benchmarking analysis of different cardiac computational modeling solutions with quantitative metrics. We present a benchmark analysis of a meshless-based method with finite-element methods for the prediction of cardiac electrical patterns in CRT, based on a subset of the CRT-EPiggy19 dataset. A data assimilation strategy was designed to personalize the most relevant parameters of the electrophysiological simulations and identify the optimal CRT lead configuration. The simulation results obtained with the meshless model were equivalent to FEM, with the most relevant aspect for accurate CRT predictions being the parameter personalization strategy (e.g., regional conduction velocity distribution, including the Purkinje system and CRT lead distribution). © 2022 by the authors. Licensee MDPI, Basel, Switzerland