Enhanced piezoelectric fibered extracellular matrix to promote cardiomyocyte maturation and tissue formation: a 3d computational model

Mechanical and electrical stimuli play a key role in tissue formation, guiding cell processes such as cell migration, differentiation, maturation, and apoptosis. Monitoring and controlling these stimuli on in vitro experiments is not straightforward due to the coupling of these different stimuli. In addition, active and reciprocal cell–cell and cell–extracellular matrix interactions are essential to be considered during formation of complex tissue such as myocardial tissue. In this sense, computational models can offer new perspectives and key information on the cell microenvironment. Thus, we present a new computational 3D model, based on the Finite Element Method, where a complex extracellular matrix with piezoelectric properties interacts with cardiac muscle cells during the first steps of tissue formation. This model includes collective behavior and cell processes such as cell migration, maturation, differentiation, proliferation, and apoptosis. The model has employed to study the initial stages of in vitro cardiac aggregate formation, considering cell–cell junctions, under different extracellular matrix configurations. Three different cases have been purposed to evaluate cell behavior in fibered, mechanically stimulated fibered, and mechanically stimulated piezoelectric fibered extra-cellular matrix. In this last case, the cells are guided by the coupling of mechanical and electrical stimuli. Accordingly, the obtained results show the formation of more elongated groups and enhancement in cell proliferation

Mechanical stimulation of cell microenvironment for cardiac muscle tissue regeneration: a 3D in-silico model

The processes in which cardiac cells are reorganized for tissue regeneration is still unclear. It is a complicated process that is orchestrated by many factors such as mechanical, chemical, thermal, and/or electrical cues. Studying and optimizing these conditions in-vitro is complicated and time costly. In such cases, in-silico numerical simulations can offer a reliable solution to predict and optimize the considered conditions for the cell culture process. For this aim, a 3D novel and enhanced numerical model has been developed to study the effect of the mechanical properties of the extracellular matrix (ECM) as well as the applied external forces in the process of the cell differentiation and proliferation for cardiac muscle tissue regeneration. The model has into account the essential cellular processes such as migration, cell–cell interaction, cell–ECM interaction, differentiation, proliferation and/or apoptosis. It has employed to study the initial stages of cardiac muscle tissue formation within a wide range of ECM stiffness (8–50 kPa). The results show that, after cell culture within a free surface ECM, cells tend to form elongated aggregations in the ECM center. The formation rate, as well as the aggregation morphology, have been found to be a function of the ECM stiffness and the applied external force. Besides, it has been found that the optimum ECM stiffness for cardiovascular tissue regeneration is in the range of 29–39 kPa, combined with the application of a mechanical stimulus equivalent to deformations of 20–25%

Experimentally-guided in silico design of engineered heart tissues to improve cardiac electrical function after myocardial infarction

Engineered heart tissues (EHTs) built from human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) showed promising results for cardiac function restoration following myocardial infarction. Nevertheless, human iPSC-CMs have longer action potential and lower cell-to-cell coupling than adult-like CMs. These immature electrophysiological properties favor arrhythmias due to the generation of electrophysiological gradients when hiPSC-CMs are injected in the cardiac tissue. Culturing hiPSC-CMs on three-dimensional (3D) scaffolds can promote their maturation and influence their alignment. However, it is still uncertain how on-scaffold culturing influences the overall electrophysiology of the in vitro and implanted EHTs, as it requires expensive and time consuming experimentation. Here, we computationally investigated the impact of the scaffold design on the EHT electrical depolarization and repolarization before and after engraftment on infarcted tissue. We first acquired and processed electrical recordings from in vitro EHTs, which we used to calibrate the modeling and simulation of in silico EHTs to replicate experimental outcomes. Next, we built in silico EHT models for a range of scaffold pore sizes, shapes (square, rectangular, auxetic, hexagonal) and thicknesses. In this setup, we found that scaffolds made of small (0.2 mm2), elongated (30° half-angle) hexagons led to faster EHT activation and better mimicked the cardiac anisotropy. The scaffold thickness had a marginal role on the not engrafted EHT electrophysiology. Moreover, EHT engraftment on infarcted tissue showed that the EHT conductivity should be at least 5% of that in healthy tissue for bidirectional EHT-myocardium electrical propagation. For conductivities above such threshold, the scaffold made of small elongated hexagons led to the lowest activation time (AT) in the coupled EHT-myocardium. If the EHT conductivity was further increased and the hiPSC-CMs were uniformly oriented parallel to the epicardial cells, the total AT and the repolarization time gradient decreased substantially, thus minimizing the likelihood for arrhythmias after EHT transplantation

Experimentally-guided in silico design of engineered heart tissues to improve cardiac electrical function after myocardial infarction

Engineered heart tissues (EHTs) built from human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) showed promising results for cardiac function restoration following myocardial infarction. Nevertheless, human iPSC-CMs have longer action potential and lower cell-to-cell coupling than adult-like CMs. These immature electrophysiological properties favor arrhythmias due to the generation of electrophysiological gradients when hiPSC-CMs are injected in the cardiac tissue. Culturing hiPSC-CMs on three-dimensional (3D) scaffolds can promote their maturation and influence their alignment. However, it is still uncertain how on-scaffold culturing influences the overall electrophysiology of the in vitro and implanted EHTs, as it requires expensive and time consuming experimentation. Here, we computationally investigated the impact of the scaffold design on the EHT electrical depolarization and repolarization before and after engraftment on infarcted tissue. We first acquired and processed electrical recordings from in vitro EHTs, which we used to calibrate the modeling and simulation of in silico EHTs to replicate experimental outcomes. Next, we built in silico EHT models for a range of scaffold pore sizes, shapes (square, rectangular, auxetic, hexagonal) and thicknesses. In this setup, we found that scaffolds made of small (0.2 mm 2), elongated (30° half-angle) hexagons led to faster EHT activation and better mimicked the cardiac anisotropy. The scaffold thickness had a marginal role on the not engrafted EHT electrophysiology. Moreover, EHT engraftment on infarcted tissue showed that the EHT conductivity should be at least 5% of that in healthy tissue for bidirectional EHT-myocardium electrical propagation. For conductivities above such threshold, the scaffold made of small elongated hexagons led to the lowest activation time (AT) in the coupled EHT-myocardium. If the EHT conductivity was further increased and the hiPSC-CMs were uniformly oriented parallel to the epicardial cells, the total AT and the repolarization time gradient decreased substantially, thus minimizing the likelihood for arrhythmias after EHT transplantation

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. [23] Nigmatullina R.R., Zemskova S.N., Bilalova D.F., Mustafin A.A., Kuzmina O.I., Chibireva M.D., Nedorezova R.S. Valid method for estimation of pulmonary hypertention degreein children. [23] Parfenov A. Mathematical modeling of the cardiovascular systemunder the influence of environmental factors. [24] Pimenov V.G., Hendy A. Adaptivity of the alternating direction method for fractional reactiondiffusion equation with delay effects in electrocardiology. [24] Podgurskaya A.D., Krasheninnikova A., Tsvelaya V., Kudryashova N., Agladze K.I. Influence of alcohols on excitation wave propagationin neonatal rat ventricular cardiomyocyte monolayer. [24] Pravdin S. A mathematical model of the cardiac left ventricle anatomy and morphology. [24] Seemann G. Cause and effects of cardiac heterogeneity:insights from experimental and computational models. [25] Seryapina A.A., Shevelev O.B. Basic metabolomic patterns in early hypertensive rats: MRI study. [25] Shestakov A.P., Vasserman I.N., Shardakov I.N. Modeling of cardiac arrhythmia generation caused bypathological distribution of myocardial conductivity. [26] Shutko A.V., Gorbunov V.S., Nizamieva A.A., Guriya K.G., Agladze K.I. Contractile micro-constructs from cardiac tissue culturefor the research of autowave propagation in excitable systems. [26] Simakov S., Gamilov T., Kopylov Ph. Computational study of the haemodynamic significanceof the stenosis during multivessel coronary disease. [27] Syomin F., Zberiya M.V. A numerical simulation of changes in the performance of the leftventricle of the heart under various hemodynamic conditions. [27] Tsaturyan A. A simple model of cardiac muscle:mechanics, actin-myosin interaction and Ca-activation. [27] Tsvelaya V., Krasheninnikova A., Kudryashova N., Agladze K.I. Calcium-current dominated upstroke in severe hyperkalemia. [28] Ushenin K.S., Pravdin S., Chumarnaya T.V., Alueva Y.S., Solovyova O.E. 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. [43] Suslonova O., Smirnova S., Roshchevskaya I.M. Cardioelectric field in rats with experimental pulmonaryhypertension during ventricular depolarization. [43] Syunyaev R.A., Karpaev A.A., Aliev R.R. Simulation of the fibroblasts effect on synchronizationand rhythmogenesis in the sinoatrial node. [44] Zorin N.M., Ryvkin A.М., Moskvin A. Cooperation of membrane and calcium oscillatorsin sinoatrial node cells. [44] EXPERIMENTAL AND COMPUTATIONAL MODELS IN IMMUNOLOGY. [45] Bocharov G. Systems approach to modelling the "virus-host organism" interactionin infectious diseases. [45] Brilliant S.A. Impact of immobilization stress on change of protein fractionshemoglobin of bone marrow in rats. [45] Bykova M. The features of biochemical properties of extracellular matrix of bonemarrow in rats in conditions which stimulate granulocytopoiesis. [45] Chigvintsev V.M. 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. The Ca2+ regulation of actin-myosin interactionin atrium and ventricle. [51] Nabiev S., Bershitsky S.Y., Tsaturyan A. Measurements of the bending stiffnessof reconstructed thin filament with the optical trap. [51] Shchepkin D., Kopylova G., Matyushenko A.M., Popruga K.E., Pivovarova A.V., Levitsky D.I. Structural and functional studies of tropomyosin species withcardiomyopathic mutations in the areaof tropomyosin-troponin contact. [52] Shenkman B., Nemirovskaya T.L., Lomonosova Y.N., Lyubimova K.A., Ptitsyn K.G. Nitric oxide in uloaded muscle: powerless guard of stability. [52] Shirinsky V.P., Kazakova O.A., Samsonov M.V., Khalisov M.M., Khapchaev A.Yu., Penniyaynen V.A., Ankudinov A.V., Krylov B.V.Spatiotemporal activity profiling of key myosin regulators inendothelial cells with regard to control of cell stiffnessand barrier dysfunction. [53] Yakupova E.I., Bobylev A.G., Vikhlyantsev I.M., Podlubnaya Z.A. Smooth muscle titin forms aggregates with amyloid-likedye-binding properties. 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Modelado computacional avanzado del comportamiento celular para el estudio y optimización de los procesos de reorganización celular en la regeneración de tejidos y la creación de órganos

Los procesos celulares de diferenciación, migración, proliferación y apoptosis juegan un papel clave en el desarrollo de los tejidos, así como en diferentes enfermedades como el cáncer. Estos procesos dependen de las condiciones mecánicas de la célula y su entorno. A su vez, las células alteran dinámicamente las condiciones de la matriz extracelular, generando y degradando matriz para promover la migración celular o la regeneración de tejidos. Analizar estos procesos en detalle mediante modelos \textit{in-vitro} puede ser complejo y costoso. Abordar estos procesos desde una perspectiva mecánica, mediante el desarrollo de modelos computacionales, puede ser útil para estudiar comportamientos celulares complejos.En esta tesis se han desarrollado dos modelos computacionales diferentes para analizar el comportamiento celular en entornos 3D. El primer modelo, un modelo mecánico que define el equilibrio tensión-deformación de la célula con su entorno, se ha aplicado para estudiar las interacciones entre células. El segundo modelo, un modelo de fluido, basándose en una formulación híbrida (discreta y continua), se ha aplicado para el análisis del crecimiento de tumores no-sólidos en entornos líquidos.Mediante el modelo mecánico, se ha analizado el crecimiento y la diferenciación de células óseas, cardíacas y tumorales, bajo diferentes condiciones mecánicas, eléctricas y químicas. En primer lugar, se ha estudiado el efecto de la concentración de oxígeno en la diferenciación de células madre mesenquimales en osteoblastos, así como en la migración y proliferación de ambos tipos celulares. Posteriormente, se ha estudiado la formación de tejidos cardíacos estructurados mediante la aplicación de estímulos mecánicos y eléctricos direccionados. En este caso, se ha considerado el comportamiento celular colectivo a través de la formación de adhesiones celulares estrechas.En el modelo de fluido, se ha estudiado la formación y el crecimiento de agregados de tumores de mieloma múltiple. En condiciones líquidas, la concentración y distribución de las células juegan un papel clave en el crecimiento de las células tumorales. Además, se ha estudiado la interacción de las células tumorales con las células madre mesenquimales a través de la expresión de diferentes factores que promueven la migración, el crecimiento y la diferenciación de los fibroblastos asociados al cáncer.Los modelos desarrollados han demostrado ser válidos para el estudio del comportamiento celular en una amplia variedad de condiciones. Con estos modelos ha sido posible estudiar los procesos de diferenciación, migración y proliferación bajo los efectos de diferentes estímulos. La aplicación de modelos híbridos para el análisis de entornos líquidos, ha supuesto una enorme reducción del coste computacional, lo que ha permitido aumentar significativamente el número de células consideradas en los cálculos, así como mejorar la definición del entorno celular.<br /

A versatile platform for three-dimensional dynamic suspension culture applications

In the last decades, the rapid upgrading in cell biological knowledge has bumped the interest in using cell-based therapeutic approaches as well as cell-based model systems for the treatment of diseases. Given the rapid translation towards cell-based clinical treatments and the consequent increasing demand of cell sources, three-dimensional (3D) suspension cultures have demonstrated to be an advantageous alternative to monolayer techniques for large scale expansion of cells and for the generation of three-dimensional model systems in a scale-up perspective. In this scenario, a versatile bioreactor platform suitable for 3D dynamic suspension cell culture under tuneable shear stress conditions is developed and preliminarily tested in two different biotechnological applications. By adopting simple technological solutions and avoiding rotating components, the bioreactor exploits a laminar hydrodynamics, enabling dynamic cell suspension in an environment favourable to mass transport. Technically, the bioreactor is conceived to produce dynamic suspension cell culture under tuneable shear stress conditions without the use of moving components (from ultralow to moderate shear stress). A multiphysics computational modelling strategy is applied for the development and optimization of the suspension bioreactor platform. The in silico modelling is used to support the design and optimization phase of the bioreactor platform, providing a comprehensive analysis of its operating principles, also supporting the development/optimization of culture protocols directly in silico, and thus minimizing preliminary laboratory tests. After the technical assessment of the functionality of the device and a massive number of in silico simulations for its characterization, the bioreactor platform has been employed for two preliminary experimental applications, in order to determine the suitability of the device for culturing human cells under dynamic suspension. In detail, the bioreactor platform has been used to culture lung cancer cells for spheroid formation (Calu-3 cell line) under ultralow shear stress conditions, and for human induced pluripotent stem cell (hiPSC) dynamic suspension culture. The use of the bioreactor platform for the formation of cancer cell spheroids under low shear stress conditions confirms the suitability of the device for its use as dynamic suspension bioreactor. In fact, compared to static cell suspension, after 5 days of dynamic suspension culture the bioreactor platform preserves morphological features, promotes intercellular connection, increases the number of cycling cells, and reduces double strand DNA damage. Calu-3 cells form functional 3D spheroids characterized by more functional adherence junctions between cells. Moreover, the computational model has been used as a tool for assisting the setup of the experimental framework with the extraction of the fluid dynamic features establishing inside the bioreactor culture chamber. As second proof of concept application, the bioreactor platform has been tested for the dynamic suspension of hiPSCs. Starting from the ‘a priori’ knowledge gained by the development of the in silico culture protocol, the agglomeration of human induced pluripotent stem cells has been modulated by means of the combination of moderate intermittent shear stress and free-fall transport within the bioreactor culture chamber. The inoculation of single cells suspensions inside the bioreactor chamber promotes cell-cell interaction and consequently the formation of human induced pluripotent stem cell aggregates. In conclusion, the impeller-free functioning principle characterizing the proposed bioreactor platform demonstrates to be promising for human cell dynamic suspension culture. In the future, this bioreactor platform will be further optimized for the realization of impeller-free dynamic suspension bioreactors dedicated and optimized to specific applications in stem cell and cancer cell culture

Fabrication of human myocardium using multidimensional modelling of engineered tissues

Biofabrication of human tissues has seen a meteoric growth triggered by recent technical advancements such as human induced pluripotent stem cells (hiPSCs) and additive manufacturing. However, generation of cardiac tissue is still hampered by lack of adequate mechanical properties and crucially by the often unpredictable post-fabrication evolution of biological components. In this study we employ melt electrowriting (MEW) and hiPSC-derived cardiac cells to generate fibre-reinforced human cardiac minitissues. These are thoroughly characterized in order to build computational models and simulations able to predict their post-fabrication evolution. Our results show that MEW-based human minitissues display advanced maturation 28 post-generation, with a significant increase in the expression of cardiac genes such as MYL2, GJA5, SCN5A and the MYH7/MYH6 and MYL2/MYL7 ratios. Human iPSC-cardiomyocytes are significantly more aligned within the MEW-based 3D tissues, as compared to conventional 2D controls, and also display greater expression of C ×43. These are also correlated with a more mature functionality in the form of faster conduction velocity. We used these data to develop simulations capable of accurately reproducing the experimental performance. In-depth gauging of the structural disposition (cellular alignment) and intercellular connectivity (C ×43) allowed us to develop an improved computational model able to predict the relationship between cardiac cell alignment and functional performance. This study lays down the path for advancing in the development of in silico tools to predict cardiac biofabricated tissue evolution after generation, and maps the route towards more accurate and biomimetic tissue manufacture

Unravelling cell migration: defining movement from the cell surface

Cell motility is essential for life and development. Unfortunately, cell migration is also linked to several pathological processes, such as cancer metastasis. Cells’ ability to migrate relies on many actors. Cells change their migratory strategy based on their phenotype and the properties of the surrounding microenvironment. Cell migration is, therefore, an extremely complex phenomenon. Researchers have investigated cell motility for more than a century. Recent discoveries have uncovered some of the mysteries associated with the mechanisms involved in cell migration, such as intracellular signaling and cell mechanics. These findings involve different players, including transmembrane receptors, adhesive complexes, cytoskeletal components , the nucleus, and the extracellular matrix. This review aims to give a global overview of our current understanding of cell migration