Mathematical modeling of local perfusion in large distensible microvascular networks

Microvessels -blood vessels with diameter less than 200 microns- form large, intricate networks organized into arterioles, capillaries and venules. In these networks, the distribution of flow and pressure drop is a highly interlaced function of single vessel resistances and mutual vessel interactions. In this paper we propose a mathematical and computational model to study the behavior of microcirculatory networks subjected to different conditions. The network geometry is composed of a graph of connected straight cylinders, each one representing a vessel. The blood flow and pressure drop across the single vessel, further split into smaller elements, are related through a generalized Ohm's law featuring a conductivity parameter, function of the vessel cross section area and geometry, which undergo deformations under pressure loads. The membrane theory is used to describe the deformation of vessel lumina, tailored to the structure of thick-walled arterioles and thin-walled venules. In addition, since venules can possibly experience negative transmural pressures, a buckling model is also included to represent vessel collapse. The complete model including arterioles, capillaries and venules represents a nonlinear system of PDEs, which is approached numerically by finite element discretization and linearization techniques. We use the model to simulate flow in the microcirculation of the human eye retina, a terminal system with a single inlet and outlet. After a phase of validation against experimental measurements, we simulate the network response to different interstitial pressure values. Such a study is carried out both for global and localized variations of the interstitial pressure. In both cases, significant redistributions of the blood flow in the network arise, highlighting the importance of considering the single vessel behavior along with its position and connectivity in the network

Mathematical methods for modeling the microcirculation

The microcirculation plays a major role in maintaining homeostasis in the body. Alterations or dysfunctions of the microcirculation can lead to several types of serious diseases. It is not surprising, then, that the microcirculation has been an object of intense theoretical and experimental study over the past few decades. Mathematical approaches offer a valuable method for quantifying the relationships between various mechanical, hemodynamic, and regulatory factors of the microcirculation and the pathophysiology of numerous diseases. This work provides an overview of several mathematical models that describe and investigate the many different aspects of the microcirculation, including geometry of the vascular bed, blood flow in the vascular networks, solute transport and delivery to the surrounding tissue, and vessel wall mechanics under passive and active stimuli. Representing relevant phenomena across multiple spatial scales remains a major challenge in modeling the microcirculation. Nevertheless, the depth and breadth of mathematical modeling with applications in the microcirculation is demonstrated in this work. A special emphasis is placed on models of the retinal circulation, including models that predict the influence of ocular hemodynamic alterations with the progression of ocular diseases such as glaucoma

Biofluid modeling of the coupled eye-brain system and insights into simulated microgravity conditions

This work aims at investigating the interactions between the flow of fluids in the eyes and the brain and their potential implications in structural and functional changes in the eyes of astronauts, a condition also known as spaceflight associated neuro-ocular syndrome (SANS). To this end, we propose a reduced (0-dimensional) mathematical model of fluid flow in the eyes and brain, which is embedded into a simplified whole-body circulation model. In particular, the model accounts for: (i) the flows of blood and aqueous humor in the eyes; (ii) the flows of blood, cerebrospinal fluid and interstitial fluid in the brain; and (iii) their interactions. The model is used to simulate variations in intraocular pressure, intracranial pressure and blood flow due to microgravity conditions, which are thought to be critical factors in SANS. Specifically, the model predicts that both intracranial and intraocular pressures increase in microgravity, even though their respective trends may be different. In such conditions, ocular blood flow is predicted to decrease in the choroid and ciliary body circulations, whereas retinal circulation is found to be less susceptible to microgravity-induced alterations, owing to a purely mechanical component in perfusion control associated with the venous segments. These findings indicate that the particular anatomical architecture of venous drainage in the retina may be one of the reasons why most of the SANS alterations are not observed in the retina but, rather, in other vascular beds, particularly the choroid. Thus, clinical assessment of ocular venous function may be considered as a determinant SANS factor, for which astronauts could be screened on earth and in-flight

An Analytical Solution for Diffusion and Nonlinear Uptake

Abstract. A simple mathematical model of steady state oxygen distribution subject to diffusive transport and non-linear uptake in a retinal cylinder has been developed. The approximate analytical solution to a reaction-diffusion equation are obtained by using series expansions. The computational results for the scaled variables are presented through graphs. The effect of the important parameters (1) diffusion coefficient (2) metabolic rate constant (3) retinal capillary concentration are examined and discusse

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. 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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. 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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Probabilistic theory of ions binding to RYR-channelwithin the improved electron-conformational model. [56] Shadrin K.V., Pakhomova V., Rupenko A. Stoichiometric modeling of oxygen transport through the surfaceof the isolated perfused rat liver at various oxygenation conditions. [57] Zubarev A.Y. Theoretical modelling of magnetic hyperthermia. [57] TRANSLATIONAL MEDICINE. FROM BASIC SCIENCE TO CLINICAL PRACTICE. [58] Blinkova N.B., Danilova I.G., Gette I.F., Abidov M.T., Pozdina V.A. Features of the regenerative processesin the rat liver exposed to alloxan diabetes with stimulationof macrophages functional activity. [58] Bulavintseva T.S., Danilova I.G., Brilliant S.A. The response of macrophage to chronic hyperglycemiabefore and after modulation of macrophage functional phenotype. [58] Chumarnaya T.V., Alueva Y.S., Kochmasheva V.V., Mikhailov S.P., Ostern O.V., Sopov O.V., Solovyova O.E. Specific features of the functional geometryof the left ventricle in myocardial diseases. 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A hybrid discrete–continuum approach for modelling microcirculatory blood flow

In recent years, biological imaging techniques have advanced significantly and it is now possible to digitally reconstruct microvascular network structures in detail, identifying the smallest capillaries at sub-micron resolution and generating large 3D structural data sets of size >106 vessel segments. However, this relies on ex vivo imaging; corresponding in vivo measures of microvascular structure and flow are limited to larger branching vessels and are not achievable in three dimensions for the smallest vessels. This suggests the use of computational modelling to combine in vivo measures of branching vessel architecture and flows with ex vivo data on complete microvascular structures to predict effective flow and pressures distributions. In this paper, a hybrid discrete–continuum model to predict microcirculatory blood flow based on structural information is developed and compared with existing models for flow and pressure in individual vessels. A continuum-based Darcy model for transport in the capillary bed is coupled via point sources of flux to flows in individual arteriolar vessels, which are described explicitly using Poiseuille’s law. The venular drainage is represented as a spatially uniform flow sink. The resulting discrete–continuum framework is parameterized using structural data from the capillary network and compared with a fully discrete flow and pressure solution in three networks derived from observations of the rat mesentery. The discrete–continuum approach is feasible and effective, providing a promising tool for extracting functional transport properties in situations where vascular branching structures are well defined

Mathematical and computational models of the retina in health, development and disease

The retina confers upon us the gift of vision, enabling us to perceive the world in a manner unparalleled by any other tissue. Experimental and clinical studies have provided great insight into the physiology and biochemistry of the retina; however, there are questions which cannot be answered using these methods alone. Mathematical and computational techniques can provide complementary insight into this inherently complex and nonlinear system. They allow us to characterise and predict the behaviour of the retina, as well as to test hypotheses which are experimentally intractable. In this review, we survey some of the key theoretical models of the retina in the healthy, developmental and diseased states. The main insights derived from each of these modelling studies are highlighted, as are model predictions which have yet to be tested, and data which need to be gathered to inform future modelling work. Possible directions for future research are also discussed. Whilst the present modelling studies have achieved great success in unravelling the workings of the retina, they have yet to achieve their full potential. For this to happen, greater involvement with the modelling community is required, and stronger collaborations forged between experimentalists, clinicians and theoreticians. It is hoped that, in addition to bringing the fruits of current modelling studies to the attention of the ophthalmological community, this review will encourage many such future collaborations

Variability in Retinal Neuron Populations and Associated Variations in Mass Transport Systems of the Retina in Health and Aging

Aging is associated with a broad range of visual impairments that can have dramatic consequences on the quality of life of those impacted. These changes are driven by a complex series of alterations affecting interactions between multiple cellular and extracellular elements. The resilience of many of these interactions may be key to minimal loss of visual function in aging; yet many of them remain poorly understood. In this review, we focus on the relation between retinal neurons and their respective mass transport systems. These metabolite delivery systems include the retinal vasculature, which lies within the inner portion of the retina, and the choroidal vasculature located externally to the retinal tissue. A framework for investigation is proposed and applied to identify the structures and processes determining retinal mass transport at the cellular and tissue levels. Spatial variability in the structure of the retina and changes observed in aging are then harnessed to explore the relation between variations in neuron populations and those seen among retinal metabolite delivery systems. Existing data demonstrate that the relation between inner retinal neurons and their mass transport systems is different in nature from that observed between the outer retina and choroid. The most prominent structural changes observed across the eye and in aging are seen in Bruch’s membrane, which forms a selective barrier to mass transfers at the interface between the choroidal vasculature and the outer retina

Aerospace Medicine and Biology: A continuing supplement 180, May 1978

This special bibliography lists 201 reports, articles, and other documents introduced into the NASA scientific and technical information system in April 1978

Cell migration and capillary plexus formation in wounds and retinae

Cell migration is a fundamental biological phenomenon that is critical to the development and maintenance of tissues in multi-cellular organisms. This thesis presents a series of discrete mathematical models designed to study the migratory response of such cells when exposed to a variety of environmental stimuli. By applying these models to pertinent biological scenarios and benchmarking results against experimental data, novel insights are gained into the underlying cell behaviour. The process of angiogenesis is investigated first and models are developed for simulating capillary plexus expansion during both wound healing and retinal vascular development. The simulated cell migration is coupled to a detailed model of blood perfusion that allows prediction of dynamic flow-induced evolution of the nascent vascular architectures – the network topologies generated in each case are found to successfully reproduce a number of longitudinal experimental metrics. Moreover, in the case of retinal development, the resultant distributions of haematocrit and oxygen are found to be essential in generating vasculatures that resemble those observed in vivo. An alternative cell migration model is then derived that is capable of more accurately describing both individual and collective cell movement. The general model framework, which allows for biophysical cell-cell interactions and adaptive cell morphologies, is seen to have the potential for a range of applications. The value of the modelling approach is well demonstrated by benchmarking in silico cell movement against experimental data from an in vitro fibroblast scrape wound assay. The results subsequently reveal an unexplained discrepancy that provides an intriguing challenge for future studies