A note on stress-driven anisotropic diffusion and its role in active deformable media

We propose a new model to describe diffusion processes within active deformable media. Our general theoretical framework is based on physical and mathematical considerations, and it suggests to use diffusion tensors directly coupled to mechanical stress. A proof-of-concept experiment and the proposed generalised reaction-diffusion-mechanics model reveal that initially isotropic and homogeneous diffusion tensors turn into inhomogeneous and anisotropic quantities due to the intrinsic structure of the nonlinear coupling. We study the physical properties leading to these effects, and investigate mathematical conditions for its occurrence. Together, the experiment, the model, and the numerical results obtained using a mixed-primal finite element method, clearly support relevant consequences of stress-assisted diffusion into anisotropy patterns, drifting, and conduction velocity of the resulting excitation waves. Our findings also indicate the applicability of this novel approach in the description of mechano-electrical feedback in actively deforming bio-materials such as the heart

Review of Journal of Cardiovascular Magnetic Resonance 2014

There were 102 articles published in the Journal of Cardiovascular Magnetic Resonance (JCMR) in 2014, which is a 6 % decrease on the 109 articles published in 2013. The quality of the submissions continues to increase. The 2013 JCMR Impact Factor (which is published in June 2014) fell to 4.72 from 5.11 for 2012 (as published in June 2013). The 2013 impact factor means that the JCMR papers that were published in 2011 and 2012 were cited on average 4.72 times in 2013. The impact factor undergoes natural variation according to citation rates of papers in the 2 years following publication, and is significantly influenced by highly cited papers such as official reports. However, the progress of the journal’s impact over the last 5 years has been impressive. Our acceptance rate is <25 % and has been falling because the number of articles being submitted has been increasing. In accordance with Open-Access publishing, the JCMR articles go on-line as they are accepted with no collating of the articles into sections or special thematic issues. For this reason, the Editors have felt that it is useful once per calendar year to summarize the papers for the readership into broad areas of interest or theme, so that areas of interest can be reviewed in a single article in relation to each other and other recent JCMR articles. The papers are presented in broad themes and set in context with related literature and previously published JCMR papers to guide continuity of thought in the journal. We hope that you find the open-access system increases wider reading and citation of your papers, and that you will continue to send your quality papers to JCMR for publication

Nonlinear diffusion & thermo-electric coupling in a two-variable model of cardiac action potential

This work reports the results of the theoretical investigation of nonlinear dynamics and spiral wave breakup in a generalized two-variable model of cardiac action potential accounting for thermo-electric coupling and diffusion nonlinearities. As customary in excitable media, the common Q10 and Moore factors are used to describe thermo-electric feedback in a 10-degrees range. Motivated by the porous nature of the cardiac tissue, in this study we also propose a nonlinear Fickian flux formulated by Taylor expanding the voltage dependent diffusion coefficient up to quadratic terms. A fine tuning of the diffusive parameters is performed a priori to match the conduction velocity of the equivalent cable model. The resulting combined effects are then studied by numerically simulating different stimulation protocols on a one-dimensional cable. Model features are compared in terms of action potential morphology, restitution curves, frequency spectra and spatio-temporal phase differences. Two-dimensional long-run simulations are finally performed to characterize spiral breakup during sustained fibrillation at different thermal states. Temperature and nonlinear diffusion effects are found to impact the repolarization phase of the action potential wave with non-monotone patterns and to increase the propensity of arrhythmogenesis

On the analysis of mixed-index time fractional differential equation systems

In this paper we study the class of mixed-index time fractional differential equations in which different components of the problem have different time fractional derivatives on the left hand side. We prove a theorem on the solution of the linear system of equations, which collapses to the well-known Mittag-Leffler solution in the case the indices are the same, and also generalises the solution of the so-called linear sequential class of time fractional problems. We also investigate the asymptotic stability properties of this class of problems using Laplace transforms and show how Laplace transforms can be used to write solutions as linear combinations of generalised Mittag-Leffler functions in some cases. Finally we illustrate our results with some numerical simulations.Comment: 21 pages, 6 figures (some are made up of sub-figures - there are 15 figures or sub-figures

Evaluation of non‐Gaussian diffusion in cardiac MRI

Purpose: The diffusion tensor model assumes Gaussian diffusion and is widely applied in cardiac diffusion MRI. However, diffusion in biological tissue deviates from a Gaussian profile as a result of hindrance and restriction from cell and tissue microstructure, and may be quantified better by non‐Gaussian modeling. The aim of this study was to investigate non‐Gaussian diffusion in healthy and hypertrophic hearts. Methods: Thirteen rat hearts (five healthy, four sham, four hypertrophic) were imaged ex vivo. Diffusion‐weighted images were acquired at b‐values up to 10,000 s/mm2. Models of diffusion were fit to the data and ranked based on the Akaike information criterion. Results: The diffusion tensor was ranked best at b‐values up to 2000 s/mm2 but reflected the signal poorly in the high b‐value regime, in which the best model was a non‐Gaussian “beta distribution” model. Although there was considerable overlap in apparent diffusivities between the healthy, sham, and hypertrophic hearts, diffusion kurtosis and skewness in the hypertrophic hearts were more than 20% higher in the sheetlet and sheetlet‐normal directions. Conclusion: Non‐Gaussian diffusion models have a higher sensitivity for the detection of hypertrophy compared with the Gaussian model. In particular, diffusion kurtosis may serve as a useful biomarker for characterization of disease and remodeling in the heart

Experimental and computational biomedicine : Russian Conference with International Participation in memory of Professor Vladimir S. Markhasin : abstract book

Toward 100 Anniversary of I. P. Pavlov's Physiological Society.The volume contains the presentations that were made during Russian conference with international participation "Experimental and Computational Biomedicine" dedicated to corresponding member of RAS V.S. Markhasin (Ekaterinburg, April 10‒12, 2016). The main purpose of the conference is the discussion of the current state of experimental and theoretical research in biomedicine. For a wide range of scientists, as well as for lecturers, students of the biological and medical high schools.Сборник содержит тезисы докладов, представленных на российской конференции с международным участием «Экспериментальная и компьютерная биомедицина», посвященной памяти члена‐корреспондента РАН В. С. Мархасина (г. Екатеринбург, 10‒12 апреля 2016 г.). Основной целью конференции является обсуждение современного состояния экспериментальных и теоретических исследований в области биомедицины. Сборник предназначен для ученых, преподавателей, студентов и аспирантов биологического и медицинского профиля.МАРХАСИН ВЛАДИМИР СЕМЕНОВИЧ (1941-2015)/ MARKHASIN VLADIMIR SEMENOVICH (1941-2015). [3] PROGRAMM COMMITTEE. [5] ORGANIZING COMMITTEE. [6] KEYNOTE SPEAKERS. [7] CONTENTS. [9] PLENARY LECTURES. [10] Fedotov S. Non-Markovian random walks and anomalous transport in biology. [10] Hoekstra A. Multiscale modelling in vascular disease. [10] Kohl P. Systems biology of the heart: why bother? [10] Meyerhans A. On the regulation of virus infection fates. [11] Panfilov A.V., Dierckx H., Kazbanov I., Vandersickel N. Systems approach to studying mechanisms of ventricular fibrillationusing anatomically accurate modeling. [11] Revishvili A.S. Atrial fibrillation. Noninvasive diagnostic and treatment:from fundamental studies to clinical practice. [12] Rice J. Life sciences research at IBM. [12] Roshchevskaya I.M., Smirnova S., Roshchevsky M.P. Regularities of the depolarization of an atria:an experimental comparative-physiological study. [12] Rusinov V.L., Chupahin O.N., Charushin V.N Scientific basis for development of antiviral drugs. [13] Solovyova O.E. Tribute Lecture. Mechano-electric heterogeneity of the myocardiumas a paradigm of its function. [13] Veksler V. Myocardial energy starvation in chronic heart failure:perspectives for metabolic therapy. [13] Wladimiroff J.W. Fetal cardiac assessment using new methodsof ultrasound examination. [14] Yushkov B.G., Chereshnev V.A. The important questions of regeneration theory. [14] EXPERIMENTAL AND COMPUTATIONAL MODELS IN CARDIOVASCULARPHYSIOLOGY AND CARDIOLOGY. [15] EXPERIMENTAL AND COMPUTATIONAL MODELS IN CARDIOVASCULARPHYSIOLOGY AND CARDIOLOGY. [15] Arteyeva N. T-wave area along with Tpeak-Tend interval is the most accurateindex of the dispersion of repolarization. [15] Borodin N., Iaparov B.Y., Moskvin A. Mathematical modeling of the calmodulin effect on the RyR2 gating. [15] Dokuchaev A., Katsnelson L.B., Sulman T.B., Shikhaleva E.V., Vikulova N.A. Contribution of cooperativity to the mechano-calcium feedbacksin myocardium. Experimental discrepancy and mathematicalapproach to overcome it. [16] Elman K.A., Filatova D.Y., Bashkatova Y.V., Beloschenko D.V. The stochastic and chaotic estimation of parametersof cardiorespiratory system of students of Ugra. [16] Erkudov V.O., Pugovkin A.P., Verlov N.A., Sergeev I.V., Ievkov S.A., Mashood S., Bagrina J.V. Characteristics of the accuracy of calculation of values of systemic blood pressure using transfer functions in experimental blood loss and its compensation. [16] Ermolaev P., Khramykh T.Mechanisms of cardiodepression after 80% liver resection in rats. [17] Filatova O.E., Rusak S.N., Maystrenko E.V., Dobrynina I.Y. Aging dynamics of cardio-vascular parameters аboriginal systemand alien population of the Russian North. [17] Frolova S., Agladze K.I., Tsvelaya V., Gaiko O. Photocontrol of voltage-gated ion channel activity by azobenzenetrimethylammonium bromide in neonatal rat cardiomyocytes. [18] Gorbunov V.S., Agladze K.I., Erofeev I.S. The application of C-TAB for excitation propagation photocontrolin cardiac tissue. [18] Iribe G. Localization of TRPC3 channels estimated by in-silicoand cellular functional experiments. [19] Kachalov V.N., Tsvelaya V., Agladze K.I. Conditions of the spiral wave unpinning from the heterogeneitywith different boundary conditions in a model of cardiac tissue. [19] Kalita I., Nizamieva A.A., Tsvelaya V., Kudryashova N., Agladze K.I. The influence of anisotropy on excitation wave propagationin neonatal rat cardiomyocytes monolayer. [19] Kamalova Y. The designing of vectorcardiograph prototype. [20] Kapelko V., Shirinsky V.P., Lakomkin V., Lukoshkova E., Gramovich V.,Vyborov O., Abramov A., Undrovinas N., Ermishkin V. Models of chronic heart failure with acute and gradual onset. [20] Khassanov I., Lomidze N.N., Revishvili A.S. Remote Patient Monitoring and Integration of Medical Data. [20] Kislukhin V. Markov chain for an indicator passing throughoutcardio-vascular system (CVS). [21] Konovalov P.V., Pravdin S., Solovyova O.E., Panfilov A.V. Influence of myocardial heterogeneity on scroll wave dynamicsin an axisymmetrical anatomical model of the left ventricle of thehuman heart. [21] Koshelev A., Pravdin S., Ushenin K.S., Bazhutina A.E. An improved analytical model of the cardiac left ventricle. [22] Lookin O., Protsenko Y.L. Sex-related effects of stretch on isometric twitch and Ca2+ transientin healthy and failing right ventricular myocardiumof adult and impuberal rats. [22] Moskvin A. Electron-conformational model of the ligand-activated ion channels. [22] Nezlobinsky T., Pravdin S., Katsnelson L.B. In silico comparison of the electrical propagation wave alongmyocardium fibers in the left ventricle wall vs. isolation. 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Dynamics of scroll wave filaments in personalized modelsof the left ventricle of the human heart. [28] Vasserman I.N., Shardakov I.N., Shestakov A.P. Deriving of macroscopic intracellular conductivity of deformedmyocardium based on its microstructure. [28] Vassilevski Y.V., Pryamonosov R., Gamilov T. Personalized 3D models and applications. [29] Zun P.S., Hoekstra A., Anikina T.S. First results of fully coupled 3D models of in-stent restenosis. [29] BIOMECHANICS. EXPERIMENTAL AND MATHEMATICAL MODELSSBIOMECHANICS. EXPERIMENTAL AND MATHEMATICAL MODELS. EXPERIMENTAL AND MATHEMATICAL MODELS. [30] Balakin A., Kuznetsov D., Protsenko Y.L. The ‘length-tension’ loop in isolated myocardial preparations of theright ventricle of normal and hypertrophied hearts of male rats. [30] Belousova M.D., Kruchinina A.P., Chertopolokhov V.A. Automatic control model of the three-tier arm type manipulatorin the aimed-movement task. [30] Berestin D.K., Bazhenova A.E., Chernikov N.A., Vokhmina Y.V. Mathematical modeling of dynamics of development of Parkinson'sdisease on the tremor parameters. [31] Dubinin A.L., Nyashin Y.I., Osipenko M.A. Development of the biomechanical approach to tooth movementunder the orthodontic treatment. [31] Galochkina T., Volpert V. Reaction-diffusion waves in mathematical model of bloodcoagulation. [31] Golov A.V., Simakov S., Timme E.A. Mathematical modeling of alveolar ventilationand gas exchange during treadmill stress tests. [32] Gurev V., Rice J. Strain prediction in 3D finite element models of cardiac mechanics. [32] Kamaltdinov M.R. Simulation of digestion processes in antroduodenum:food particles dissolution in consideration of functional disorders. [33] Khamzin S., Kursanov A., Solovyova O.E. Load-dependence of the electromechanical function of myocardiumin a 1D tissue model. [33] Khokhlova A., Iribe G., Solovyova O.E Transmural gradient in mechanical properties of isolatedsubendocardial and subepicardial cardiomyocytes. [33] Kruchinin P.A. Optimal control problem and indexesof stabilometric "test with the visual step input". [34] Kruchinina A.P., Yakushev A.G. A study of the edge segments of saccadic eye trajectory. [34] Kursanov A., Khamzin S., Solovyova O.E. Load-dependence of intramyocardial slow force responsein heterogeneous myocardium. [35] Lisin R.V., Balakin A., Protsenko Y.L. Experimental study of the intramyocardial slow force response. [35] Melnikova N.B., Hoekstra A. The mechanics of a discrete multi-cellular model of arterial in‐stent restenosis. [35] Murashova D.S., Murashov S.A., Bogdan O.P., Muravieva O.V., Yugova S.O. Modelling of soft tissue deformation for static elastometry. [36] Nikitin V.N., Tverier V.M., Krotkikh A.A. Occlusion correction based on biomechanical modelling. [36] Nyashin Y.I., Lokhov V.A. Development of the “Virtual physiological human” concept. [37] Shulyatev A.F., Akulich Y.V., Akulich A.Y., Denisov A.S. 3D FEA simulation of the proximal human femur. [37] Smoluk A.T., Smoluk L.T., Balakin A., Protsenko Y.L., Lisin R.V. Modelling viscoelastic hysteresis of passive myocardial sample. [37] Svirepov P.I. Mathematical modeling of the left atria mechanical actionwith mitral regurgitation. [38] Svitenkov A., Rekin O., Hoekstra A. Accuracy of 1D blood flow simulations in relation to level of detailof the arterial tree model. [38] Tsinker M. Mathematical modelling of airflow in human respiratory tract. [39] Wilde M.V. Influence of artificial initial and boundary conditionsin biomechanical models of blood vessels. [39] ELECTROPHYSIOLOGY. EXPERIMENTAL AND COMPUTATIONAL MODELS. CLINICAL STUDIES. [40] Agladze K.I., Agladze N.N. Arrhythmia modelling in tissue culture. [40] Golovko V., Gonotkov M.A. Pharmacological analysis of transmembrane action potential'smorphology of myoepitelial cells in the spontaneously beating heartof ascidia Styela rustica. [40] Gonotkov M.A., Golovko V. The crucial role of the rapidly activating component of outwarddelayed rectifier K-current (IKr) in pig sinoauricular node (SAN). [40] Danilov A.A. Numerical methods for electrocardiography modelling. [41] Kolomeyets N.L., Roshchevskaya I.M. The electrical resistivity of a segment of the tail, lungs, liver,intercostal muscles of grass snakes during cooling. [41] Kharkovskaia E., Zhidkova N., Mukhina I.V., Osipov G.V. Role of TRPC1 channels in the propagation of electrical excitationin the isolated rat heart. [42] Lubimceva T.A., Lebedeva V.K., Trukshina M.A., Lyasnikova E.A., Lebedev D.S. Ventricular lead position and mechanical dyssynchronyin response to cardiac resynchronization therapy. [42] Poskina T.Y., Shakirova L.S., Klyus L.G., Eskov V.V. Stochastics and chaotic analysis of electromyogramand electroencefalogramm. [42] Prosheva V.I. New insights into the pacemaker and conduction systemcells organization in the adult avian heart. 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A mathematical model of the functioning and mutual regulation ofthe immune and neuroendocrine systems in response to viralexposure under the impact of environmental factors, taking intoaccount the evolution of synthetic function impairment. [46] Khramtsova Y. The role of mast cells in the regulation of repair testicles. [46] Novikov M.Y., Kim A.V. Simulation of immune processes using Bio-Medical Software Package. [47] Polevshchikov A.V., Bondar A.V., Gumovskaya J.P. Modelling of t cell extravasation into a lymph node:from morphological basics towards clonal selection theory. [47] Tuzankina I.A., Sarkisyan N., Bolkov M., Tihomirov L.B., Bass E.A. Oral and maxillofacial manifestationsof primary immunodeficiency syndroms. [47] Zaitsev S.V., Polevshchikov A.V. Evaluation of probabilities of antigen recognition by T-lymphocytesin the lymph node: a mathematical model. [48] MOLECULAR BASIS OF BIOLOGICAL MOTILITY. [49] Bershitsky S.Y., Nabiev S., Kopylova G., Shchepkin D., Matyushenko A.M., Koubassova N.A., Levitsky D.I., Tsaturyan A. Mutations in the central part of tropomyosin molecule affectthe actomyosin interaction. [49] Borovkov D.I., Kopylova G., Shchepkin D., Nabiev S., Matyushenko A.M., Levitsky D.I. Functional studies of tropomyosin mutations associatedwith dilated and hypertrophic cardiomyopathy. [49] Fatkhrakhmanova M.R., Mukhutdinova K.A., Kasimov M.R., Petrov A.M. The role of glutamate NMDA-receptor-NO synthase axis in the effectof 24-hydroxycholesterolon synaptic vesicle exocytosis at the mouseneuromuscular junctions. [50] Gritsyna Y., Vikhlyantsev I.M., Salmov N., Bobylev A.G., Podlubnaya Z.A. Increasing μ-calpain activity in striated muscles of alcohol-fed rats. [50] Kochubey P.V., Bershitsky S.Y. Study of biphasic tension rise in contracting muscle fiberduring ramp stretch. [51] Kopylova G., Shchepkin D., Nabiev S., Nikitina L., Bershitsky S.Y. 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State of the Art and New Advances: Cardiac MRI

Cardiac Magnetic Resonance Imaging (CMR) is an advanced imaging modality for better assessment of cardiac structure, function and tissue characterization. This is an essential imaging modality when indicated for assessment of a variety of cardiomyopathies, cardiac ischemia, myocardial viability, arrhythmias, cardiac masses, congenital heart disease, shunts, acute and constrictive pericardial diseases among others. CMR is sometimes referred to as the non-invasive biopsy given the significant information it provides. This chapter discusses the current state of the art of CMR with discussion about the indications, common sequences used, and the role of CMR in evaluation of ischemic and non-ischemic cardiac disease. This chapter also discusses new advances and the future of the field of CMR

Monte Carlo Simulations of Diffusion Weighted MRI in Myocardium: Validation and Sensitivity Analysis

A model of cardiac microstructure and diffusion MRI is presented, and compared with experimental data from ex vivo rat hearts. The model includes a simplified representation of individual cells, with physiologically correct cell size and orientation, as well as intra- to extracellular volume ratio. Diffusion MRI is simulated using a Monte Carlo model and realistic MRI sequences. The results show good correspondence between the simulated and experimental MRI signals. Similar patterns are observed in the eigenvalues of the diffusion tensor, the mean diffusivity (MD), and the fractional anisotropy (FA). A sensitivity analysis shows that the diffusivity is the dominant influence on all three eigenvalues of the diffusion tensor, the MD, and the FA. The area and aspect ratio of the cell cross-section affect the secondary and tertiary eigenvalues, and hence the FA. Within biological norms, the cell length, volume fraction of cells, and rate of change of helix angle play a relatively small role in influencing tissue diffusion. Results suggest that the model could be used to improve understanding of the relationship between cardiac microstructure and diffusion MRI measurements, as well as in testing and refinement of cardiac diffusion MRI protocols