Modelling the molecular mechanisms of ageing

This document is the Accepted Manuscript version of a published work that appeared in final form in Bioscience reports. To access the final edited and published work see http://www.bioscirep.org/content/37/1/BSR20160177.The ageing process is driven at the cellular level by random molecular damage which slowly accumulates with age. Although cells possess mechanisms to repair or remove damage, they are not 100% efficient and their efficiency declines with age. There are many molecular mechanisms involved and exogenous factors such as stress also contribute to the ageing process. The complexity of the ageing process has stimulated the use of computational modelling in order to increase our understanding of the system, test hypotheses and make testable predictions. As many different mechanisms are involved, a wide range of models have been developed. This paper gives an overview of the types of models that have been developed, the range of tools used, modelling standards, and discusses many specific examples of models which have been grouped according to the main mechanisms that they address. We conclude by discussing the opportunities and challenges for future modelling in this field

Aging and computational systems biology

This is the peer reviewed version of the following article: Mooney, K. M., Morgan, A. E., & Mc Auley, M. T. (2016). Aging and computational systems biology. Wiley Interdisciplinary Reviews: Systems Biology and Medicine, 8(2), 123-139, which has been published in final form at doi10.1002/wsbm.1328. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-ArchivingAging research is undergoing a paradigm shift, which has led to new and innovative methods of exploring this complex phenomenon. The systems biology approach endeavors to understand biological systems in a holistic manner, by taking account of intrinsic interactions, while also attempting to account for the impact of external inputs, such as diet. A key technique employed in systems biology is computational modeling, which involves mathematically describing and simulating the dynamics of biological systems. Although a large number of computational models have been developed in recent years, these models have focused on various discrete components of the aging process, and to date no model has succeeded in completely representing the full scope of aging. Combining existing models or developing new models may help to address this need and in so doing could help achieve an improved understanding of the intrinsic mechanisms which underpin aging

Unravelling the progression of unfolded protein Rresponse in a model system of familial Alzheimer’s disease

Alzheimer’s disease (AD) is the most common form of dementia disorders and, yet, there is no preventative or curative treatment. It is associated with the progressive loss of memory and cognition and clinically divided into sporadic and familial forms. Familial Alzheimer’s disease (FAD) has predominantly a genetic predisposition with inherited mutations in the amyloid-β precursor protein (APP) and presinilin genes, which promote APP processing through the amyloidogenic pathway. This results in the release of the Aβ peptide, a major neurotoxic agent in AD progression. Accumulation of unfolded and misfolded disease-specific proteins (including Aβ and tau proteins) in neuronal cells perturbs endoplasmic reticulum (ER) homeostasis, leading to the onset of a cellular stress cascade called unfolded protein response (UPR), markers of which are upregulated in AD brain specimens. This suggests a possible role for ER stress in activation and the pathogenesis of AD. The research aimed to investigate the dynamic response of the UPR in an experimental model system of the disease combined with a computational model. For this purpose human neuroblastoma cell lines overexpressing the wild-type (APPWT) and two mutant forms of APP (APPMUT) associated with FAD were generated. Gene expression analysis of UPR markers revealed that overexpression of APP induces preconditioning of ER stress in all cell lines but with a stronger response in FAD-associated mutants. The progression sequence of UPR in APPWT and APPMUT was investigated in a time-course manner following the application of chemical stress. The results revealed that APPMUT exhibited the highest global response to chemically induced stress with a similar pattern. A computational model of the mammalian UPR was then generated and used to understand the dynamics of UPR. The model was able to reproduce our experimental data, which included pre-existing genetic factors (mutations in APP-associated with FAD) and a mimic of environmental triggers (induction of stress) consequently triggering the stress response. It suggested a different protein load and magnitude of transcriptional activation upon stress among the three cell lines. This was followed by in silico case studies exploring the effect of drugs targeting different branches of the UPR. This study proposes a novel multidisciplinary platform that could be further used for the development of therapeutics for AD. As the familial and sporadic form of the disease have similar neuropathological characteristics, drugs efficacious for FAD will also be beneficial for the most common form of AD.Open Acces

Dynamics of the glutathione/glutaredoxin system.

M. Sc. University of KwaZulu-Natal, Pietermaritzburg 2014.The glutathione/glutaredoxin system is made up of glutaredoxins, glutathione (GSH) and glutathione reductase (GLR). Glutaredoxins, which are involved in essential cellular functions such as DNA synthesis, iron metabolism and iron-sulfur cluster assembly, become oxidised during their catalytic cycle and are reduced by GSH and GLR. Glutaredoxins also play a critical role in regulating the glutathionylation/deglutathionylation cycle. Under oxidative stress conditions, protein thiols may be glutathionylated and glutaredoxin activity is important for restoring the functions of these proteins. While the individual components of this system have been studied extensively, the dynamics of the system as a whole has not been described despite its importance in the glutathionylation/deglutathionylation process. Computational systems biology approaches could be used to describe this type of regulation but the kinetic mechanism used by glutaredoxins for deglutathionylation is unclear as a monothiol and a dithiol mechanism have both been proposed for glutaredoxin activity. The in vitro data supporting these mechanisms have been contradictory with a number of discrepancies observed in the literature, including contrasting activities of mutant glutaredoxin Cxx(C→S) and wild-type glutaredoxins. Further, Lineweaver-Burk plots showed a curved line pattern in some studies, while other studies reported a linear pattern in response to GSH. Finally, analyses of the Lineweaver-Burk plots in two substrate kinetics experiments revealed both parallel line and intersecting initial velocity line patterns for deglutathionylation. Computational and mathematical models were used to resolve these discrepancies and we showed that the mono- and di- thiol mechanisms, are in fact identical. Mathematical models of mutant and wild-type glutaredoxin activities revealed that the GSH concentration and the rate constant for GSH oxidation significantly affected these relative activities which explained the contradictory data for wild-type and mutant glutaredoxins. The sigmoidal response to GSH was due to the kinetic order of this reaction and our results demonstrated that the resulting parallel and intersecting kinetic line patterns observed in some studies depended on the reversibility of the deglutathionylation reaction. Finally, fitting experiments showed that our models were able to accurately describe the in vitro data. Collectively, our results showed how deglutathionylation should be described in computational systems biology models and further revealed how the formation of oxidised glutaredoxin may play a vital role in the regulation of glutaredoxin activity

Iron Behaving Badly: Inappropriate Iron Chelation as a Major Contributor to the Aetiology of Vascular and Other Progressive Inflammatory and Degenerative Diseases

The production of peroxide and superoxide is an inevitable consequence of aerobic metabolism, and while these particular "reactive oxygen species" (ROSs) can exhibit a number of biological effects, they are not of themselves excessively reactive and thus they are not especially damaging at physiological concentrations. However, their reactions with poorly liganded iron species can lead to the catalytic production of the very reactive and dangerous hydroxyl radical, which is exceptionally damaging, and a major cause of chronic inflammation. We review the considerable and wide-ranging evidence for the involvement of this combination of (su)peroxide and poorly liganded iron in a large number of physiological and indeed pathological processes and inflammatory disorders, especially those involving the progressive degradation of cellular and organismal performance. These diseases share a great many similarities and thus might be considered to have a common cause (i.e. iron-catalysed free radical and especially hydroxyl radical generation). The studies reviewed include those focused on a series of cardiovascular, metabolic and neurological diseases, where iron can be found at the sites of plaques and lesions, as well as studies showing the significance of iron to aging and longevity. The effective chelation of iron by natural or synthetic ligands is thus of major physiological (and potentially therapeutic) importance. As systems properties, we need to recognise that physiological observables have multiple molecular causes, and studying them in isolation leads to inconsistent patterns of apparent causality when it is the simultaneous combination of multiple factors that is responsible. This explains, for instance, the decidedly mixed effects of antioxidants that have been observed, etc...Comment: 159 pages, including 9 Figs and 2184 reference

Aktiivsete ühendite disain neurodegeneratiivsete haiguste raviks

Väitekirja elektrooniline versioon ei sisalda publikatsiooneNeurodegeneratiivsed haigused on tänapäeval kujunenud keskseks meditsiiniliseks ja sotsiaalseks probleemiks. Ühest küljest on selle põhjuseks haigustega kaasnevad rasked füüsilised ja vaimsed puuded ning mõjusate ravimeetodite puudumine. Teisalt on valdav enamus neurodegeneratiivseid haigusi seotud vananemisega. Oodatava eluea märkimisväärne pikenemine on põhjustanud patsientide arvu olulist kasvu. Üks peamisi takistusi neurodegeneratiivsete häirete jaoks radikaalsete ravimeetodite leidmisel on uute ravimite väljatöötamise protsessi pikkus ja kulukus. Viimase kümnendi jooksul on aga molekulaarse modelleerimise ja tehisintellekti arvutusmeetodite kaasamine võimaldanud märkimisväärselt lühendada nii uute ravimite väljatöötamiseks kuluvat aega kui ka maksumust. Käesolevas väitekirjas rakendati mitmesuguseid arvutipõhiseid ravimite otsimise meetodeid uute potentsiaalsete aktiivsete keemiliste ühendite väljatöötamiseks neurodegeneratiivsete haiguste raviks. Kaasaegsete arvutikeemia molekulaarsildamise ja molekulaardünaamika meetodite abil sõeluti virtuaalselt suuri keemiliste ühendite andmebaase, leidmaks neurodegeneratiivsete haigustega seotud valkudele toimivaid aineid. Nii tehti kindlaks rida uusi looduslikke ühendeid, mis toimivad erinevate ensüümvalkude inhibiitoritena, aga ka uudne ühend, mis toimib efektiivselt samaaegselt kahele Alzheimeri tõvega seotud valgule. Üks peamisi neurodegeneratiivsete haiguste tekke põhjusi on nn närvikasvufaktorite puudulikkus neuronites. Seetõttu on väga huvitavaks ja perspektiivseks suunaks keemiliste ühendite leidmine, mis käituksid analoogselt nende faktoritega ning kaitseks närvirakke suremise eest. Käesoleva töö käigus uuriti erinevate arvutusmeetodite abil põhjalikult ühe taolise närvikasvufaktori (gliia närvikasvufaktor GDNF) toimemehhanismi ning ennustati seda faktorit imiteeriv aktiivne ühend. Kuigi selle eksperimentaalselt mõõdetud neuroneid kaitsev toime ei vasta veel ravimitele esitatavatele nõutele, on siiski tegemist esimese sellelaadse ühendiga maailmas, mille alusel oleks võimalik välja arendada täiesti uut tüüpi ravimeid nii Parkinsoni kui ka Huntingtoni tõve raviksToday, neurodegenerative diseases are one of the most acute medical and social problems. This is due to both severe physical and mental disabilities resulting from the constant progression of the process, and the age-dependent nature of the vast majority of neurodegenerative diseases. The current accelerating increase in life expectancy inevitably leads to a significant increase in the number of such patients. There is currently no radical treatment for neurodegenerative disorders. One of the main obstacles to finding effective drugs is the length and cost of the process of developing a new drug. However, the development of modern molecular modelling and artificial intelligence methods has substantially shortened the time to dispense new medicines and reduced their cost. This dissertation provides examples of the use of various methods of computer-aided drug design such as molecular docking and molecular dynamics to develop new potential candidates against neurodegenerative diseases. The high-throughput virtual screening of large molecular libraries enabled to identify effective compounds against target proteins related to neurodegenerative diseases. In result, a series of natural compounds acting as inhibitors to enzymes related to different diseases was established. Notably, a fully novel compound acting against two proteins related to Alzheimer’s disease was predicted and experimentally verified. One of the main causes of the neurodegeneration is the mostly age-related deficiency of so called neurotrophic factors. Small molecules that can mimic the activity of these factors in cells would be thus very attractive novel drug candidates. In the present thesis, the computational modelling was used for detailed study of the mechanism of action of one of the most important neurotrophic factors (glial cell-derived neurotrophic factor GDNF). The results of this study enabled to develop first time a compound that acted similarly to this factor itself. Whereas the experimentally measured activity of this compound was moderate, it creates a basis for the development of fully new type of drugs against Parkinson’s and Huntington’s diseases.https://www.ester.ee/record=b535990

An integrative workflow to study large-scale biochemical networks

I propose an integrative workflow to study large-scale biochemical networks by combining omics data, network structure and dynamical analysis to unravel disease mechanisms. Using the workflow, I identified core regulatory networks from the E2F1 network underlying EMT in bladder and breast cancer and detected disease signatures and drug targets, which were experimentally validated. Further, I developed a hybrid modeling framework that combines ODE- with logical-models to analyze the dynamics of large-scale non-linear systems. This thesis is a contribution to interdisciplinary cancer research

Development and optimisation of tools for preclinical studies on Parkinson's disease

Successful drug development requires numerous tests to deem a drug safe and efficacious. Before clinical trials, preclinical testing is needed to ensure that the drug can be safely tried out in humans. In preclinical testing, efficacy is also assessed to minimise the risk of a drug failing in clinical trials. Parkinson’s disease (PD) is a common age-associated neurodegenerative disease characterised by distinct debilitating motor symptoms caused by the dysfunction of the dopaminergic nigrostriatal pathway. For PD, a plethora of cellular and animal models have been developed to study the pathophysiology of the disease and to test potential new therapeutic interventions for treating the disease. New models are constantly created. However, methods to study outcomes also need to be developed and refined for reliable and reproducible results, which is pivotal to demonstrating the efficacy of drugs. This dissertation work developed new tools and refined current methods to study PD in preclinical models and studied the characteristics of the cytomegalovirus (CMV) promoter and a primary culture of postnatal dopamine neurons used to model PD. First, we used infrared analysis of optical densities to assess the striatal innervation of tyrosine hydroxylase-positive (TH+) fibres in rat brain sections, a useful alternative to colourimetric optical density analyses. We also developed a novel method based on convolutional neural network algorithms to count dopaminergic neurons from rodent brain sections. The number of neurons counted had a high degree of correlation with results obtained using other counting methods, and counting was substantially faster with the algorithm. Additionally, we developed reporter assays, both reporter plasmids, and cell lines, to measure the activity of a PD-associated drug target, Dicer. These assays, using either exogenous or endogenous fluorescent and bioluminescent indicators, were validated and produced comparable results to previously published similar assays in more physiologically relevant conditions. We also found out that a commonly used promoter in gene therapy, the CMV promoter, could be activated by neurotransmission. We showed in vivo that methamphetamine – a potent dopamine-releasing drug – activated the CMV promoter in the rat brain. Moreover, we observed differences in the distribution of the endoplasmic reticulum between different compartments of cultured mouse TH+ neurons. In summary, the methods and refined tools obtained in these studies expand the toolbox of researchers engaged in studying PD preclinically and may be applicable to other disease areas and human clinical studies as well. Furthermore, our findings on the activation of the CMV promoter are important to consider when designing gene expression systems, reporter assays, or gene therapies for preclinical PD studies utilising amphetamines. And finally, we gained novel insight into the ultrastructural characteristics of cultured postnatal dopamine neurons and provided a valuable resource for the research community.Onnistunut lääkekehitys vaatii useita tutkimuksia, jolla lääkeaine voidaan osoittaa turvalliseksi ja tehokkaaksi. Ennen kliiniisiä kokeita, prekliinissisä kokeissa lääkeaineen turvallisuudesta tulee varmistua voidakseen sitä tutkia potilailla. Prekliinisissä kokeissa myös lääkeaineen tehoa tarkastellaan minimoidakseen riski epäonnistua kliinisissä tutkimuksissa. Parkinsonin tauti on yleinen hermostoa rappeuttava sairaus, joka aiheuttaa haitallisia ja tunnusomaisia liikehäiriöitä, jotka johtuvat keskiaivojen dopamiinijärjestelmän toimintahäiriöstä. Parkinsonin tautiin on kehitetty valtava määrä solu- ja eläinmalleja taudin patofysiologian tutkimiseksi ja uusien lääkkeiden tehon osoittamiseksi. Uusia malleja kehitetään jatkuvasti lisää, mutta myös lopputuloksia määrittäviä menetelmiä tulisi kehittää ja parantaa luotettavien ja toistettavien tulosten aikaansaamiseksi. Tämä on erityisen tärkeää, kun aikeena on osoittaa lääkeaine tehokkaaksi. Tässä väitöskirjatyössä kehitettiin uusia työkaluja ja paranneltiin aiempia menetelmiä Parkinsonin taudin tutkimiseksi prekliinisissä malleissa, ja tutkittiin cytomegalovirus (CMV) promoottorin sekä Parkinsonin taudin mallintamiseen soveltuvan dopaamiinihermosoluviljelmän ominaisuuksia. Ensiksi hyödynsimme rotan striatumin tyrosiinihydroksylaasi positiivisten (TH+) hermosoluyhteyksien optisten tiheyksien mittaamisessa infrapuna-analyysiä, tavallisen väriaineanalyysin sijaan, tarjoten vaihtoehtoisen menetelmän optisten tiheyksien mittaamiseksi. Lisäksi kehitimme uuden hermoverkkoalgoritmeihin perustuvan menetelmän solujen laskemiseksi jyrsijöiden aivoleikkeistä. Solulaskelmat korreloivat voimakkaasti muilla laskentamenetelmillä saatujen tulosten kanssa ja algoritmilla saadut laskelmat olivat huomattavasti nopeampia. Kehitimme myös, sekä plasmidi- että solupohjaisia, reportterikokeita Parkinsonin tautiin liitetyn entsyymin, Dicerin, aktivaation mittaamiseksi. Nämä reportterikokeet, jotka hyödynsivät ekso- ja endogeenisiä fluoresenssi- sekä luminesenssi-indikaattoreita, validoitiin ja tulokset olivat verrattavissa aiempiin julkaistuihin reporttereihin, paranneltujen fysiologisesti suotuisien olosuhteiden myötä. Näiden lisäksi huomasimme, että CMV promoottori, jota käytetään geeniterapioissa, voi aktivoitua neurotransmission myötä. Osoitimme in vivo, että metamfetamiinin – voimakas dopamiinia vapautta aine – annostelun myötä CMV promoottori aktivoitui rottien aivoissa. Viimeiseksi huomasimme eroja solulimakalvoston rakenteissa viljeltyjen hiiren TH+ hermosolujen eri osissa. Yhteenvetona, tässä työssä kehitetyt ja parannellut työkalut laajentavat Parkinsonin taudin prekliinisten tutkijoiden työkalurepertuaaria, mutta ne ovat myös mahdollisesti sovellettavissa muiden tautien, sekä kliinisten tutkimusten, tutkimiseen. Lisäksi löydöksemme CMV-promoottorin aktivaatiosta, on tärkeä tieto ottaa huomioon suunnitellessa ekspressiovektoreita, reportterikokeita, ja geeniterapioita käytettäväksi prekliiniisissä Parkinsonin taudin kokeissa, joissa käytetään amfetamiineja. Ja lopuksi, saimme uusia havaintoja viljeltyjen dopamiinihermosolujen ultrarakenteellisista ominaisuuksista ja tuotimme hyödyllisen resurssin tutkijoiden käytettäväksi

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. 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