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The Biophysical Mechanisms Of Bacterial And Cellular InvasionHarman, Michael William January 2015 (has links)
Advances in genetics and fluorescent protein chemistry have enabled us to fuse fluorescent probes directly to biomolecules in stably growing organisms; making it easier to image the precise position and movement of cells in three dimensions. Fluorescent stains and dyes can be employed in a similar fashion to visualize nano-scale fluctuations in active cellular structures without fixation. While informative and exciting on a qualitatively level, microscopy truly becomes powerful when we can extract meaningful quantitative information. To accomplish this, custom MATLAB (Mathworks, Natick, MA) image analysis algorithms were developed to specifically measure the biophysical parameters related to pathogenesis and function in microbes and mammalian cells. These parameters can then be exploited in the development of biophysical models to validate current measurements, and make critical predictions about the system's behavior, often addressing quantities inaccessible by experimental methods. The following research chapters of this dissertation thoroughly describe how these techniques were developed and applied to study the biophysical mechanisms of bacterial and cellular invasion.
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Use of Larval Connectivity Modeling to Determine Settlement Habitats of Panulirus argus in The Bahamas as a Pre-cursor to Marine Protected Area Network PlanningCallwood, Karlisa A. 01 January 2010 (has links)
Caribbean spiny lobster (Panulirus argus) is a popular and heavily exploited seafood throughout its range. This species supports the primary fishery in many Caribbean countries, especially in the Bahamas, which reports the highest catches and where spiny lobster serves as the number one food export. P. argus possesses one of the longest pelagic larval durations of any marine species, ranging from 6-12 months. This allows for the possibility of long-range dispersal, which would make it difficult to determine if local adult populations originate from areas close-by or within the same countries/jurisdictions, thus presenting implications for conservation and management of the species. This project seeks to explore the policy implications of lobster larval dispersal in the Bahamas by examining the larval connectivity of locally spawned P. argus in order to determine the mean dispersal kernel and to identify hotspots of settlement within the area. A coupled biophysical model was used to simulate larval transport from scaled egg production of 47 release locations within the Bahamas. The model was initialized bi-weekly from April through May, the highest months of larvae production in the Bahamas, with each model run occurring for a maximum of 180 days. The dispersal kernel for the Bahamas was calculated to be an average of 100-300 km, indicating that the larvae released within its boundaries typically settled there as well. Due to the long pelagic larval duration, larval particles were able to travel extensive distances, averaging trajectories covering distances of 4000 km and greater from the source locations. Yet, those same larval particles still settled in locations within the Bahamas, suggesting local retention, which varies from the common perception that lobster in the Bahamas originate elsewhere. This knowledge can be used to assess and perhaps reevaluate conservation and management strategies related to the Bahamian P. argus fishery, including the implementation of MPAs and/or MPA networks, input and output management controls, and other management tools.
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Efficient and Scalable Simulations of Active Hydrodynamics in Three DimensionsSingh, Abhinav 14 February 2024 (has links)
Active matter represents a unique class of non-equilibrium systems, including examples ranging from cellular structures to large-scale biological tissues. These systems exhibit intriguing spatiotemporal dynamics, driven by the constituent particles’ continuous energy expenditure. Such active-matter systems, featuring complex hydrodynamics, are described by sophisticated mathematical models, typically using partial differential equations (PDEs). PDEs modeling hydrodynamics, such as the Navier-Stokes equations, are analytically intractable, and notoriously challenging to study computationally. The challenges include the need for consistent numerical methods along with their efficient and scalable high-performance computer implementation to solve the PDEs numerically. However, when considering new theoretical PDE models, such as active hydrodynamics, conventional approaches often fall short due to the specialization made in the numerical methods to study certain specific models. The inherent complexity and nonlinearity of active-matter PDEs add to the challenge. Hence, the computational study of such active-matter PDE models requires rapidly evolving high-performance computer software that can easily implement new numerical methods to solve these equations in biologically realistic three-dimensional domains. This presents a rich, yet underexplored territory demanding scalable computational frameworks that apply to a large class of PDEs.
In this thesis, we introduce a computational framework that effectively allows for using multiple numerical methods through a context-aware template expression system akin to an embedded domain-specific language. This framework primarily aims at solving lengthy PDEs associated with active hydrodynamics in complex domains, while experimenting with new numerical methods. Existing PDE-solving codes often lack this flexibility, as they are closely tied to a PDE and domain geometry that rely on a specific numerical method. We overcome these limitations by using an object-oriented implementation design, and show experiments with adaptive and numerically consistent particle-based approach called Discretization-Corrected Particle Strength Exchange (DC-PSE). DC-PSE allows for the higher-order discretization of differential operators on arbitrary particle distributions leading to the possibility of solving active hydrodynamic PDEs in complex domains. However, the curse of dimensionality makes it difficult to numerically solve three-dimensional equations on single-core architectures and warrants the use of parallel and distributed computers.
We design a novel template-expression system and implement it in the scalable scientific computing library OpenFPM. Our methodology offers an expression-based embedded language, enabling PDE codes to be written in a form that closely mirrors mathematical notation. Leveraging OpenFPM, this approach also ensures parallel scalability. To further enhance our framework's versatility, we employ a \textit{separation-of-concerns} abstraction, segregating the model equations from numerics, and domain geometry. This allows for the rapid rewriting of codes for agile numerical experiments across different model equations in various geometries. Supplementing this framework, we develop a distributed algebra system compatible with OpenFPM and Boost Odeint. This algebra system opens avenues for a multitude of explicit adaptive time-integration schemes, which can be selected by modifying a single line of code while maintaining parallel scalability.
Motivated by symmetry-preserving theories of active hydrodynamics, and as a first benchmark of our template-expression system, we present a high-order numerically convergent scheme to study active polar fluids in arbitrary three-dimensional domains. We derive analytical solutions in simple Cartesian geometries and use them to show the numerical convergence of our algorithm. Further, we showcase the scalability of the computer code written using our expression system on distributed computing systems. To cater to the need for solving PDEs on curved surfaces, we present a novel meshfree numerical scheme, the Surface DC-PSE method. Upon implementation in our scalable framework, we benchmark Surface DC-PSE for both explicit and implicit Laplace-Beltrami operators and show applications to computing mean and Gauss curvature.
Finally, we apply our computational framework to exploring the three-dimensional active hydrodynamics of biological flowing matter, a prominent model system to study the active dynamics of cytoskeletal networks, celluar migration, and tissue mechanics. Our software framework effectively tackles the challenges associated to numerically solving such non-equilibrium spatiotemporal PDEs. We perform linear perturbation analysis of the three-dimensional Ericksen-Leslie model and find an analytical expression for the critical active potential or, equivalently, a critical length of the system above which a spontaneous flow transition occurs. This spontaneous flow transition is a first realization of a three-dimensional active Fr\'eedericksz transition. With our expression system, we successfully simulate 3D active fluids, finding phases of spontaneous flow transitions, traveling waves, and spatiotemporal chaos with increasing active stress. We numerically find a topological phase transition similar to the Berezinskii–Kosterlitz–Thouless transition (BKT transition) of the two-dimensional XY model that occurs in active polar fluids after the spontaneous flow transition.
We then proceed to non-Cartesian geometries and show the application of our software framework to solve the active polar fluid equations in spherical domains. We find spontaneous flows in agreement with recent experimental observations. We further showcase the framework to solve the equations in 3D annular domains and a `peanut' geometry that resembles a dividing cell. Our simulations further recapitulate the actin flows observed in \textit egg extracts within spherical shell geometries, showcasing our framework's versatility in handling complex geometrical modifications of model equations.
Looking ahead, we hope our framework will serve as a foundation for further advancements in computational morphogenesis, fostering collaboration and using the present techniques in biophysical modeling.
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Modélisation de la connectivité larvaire et implications en terme de gestion de l'environnement / No English title availableCrochelet, Estelle 03 April 2015 (has links)
Intégrer les connaissances sur la connectivité écologique dans la gestion des écosystèmes marins est essentiel, surtout dans un contexte d'appauvrissement des ressources marines et de dégradation des habitats côtiers à l'échelle mondiale. Des outils environnementaux, tels que les Aires Marines Protégées ont été mises en œuvre pour protéger la biodiversité, restaurer les écosystèmes endommagés, soutenir les pêcheries et reconstituer les stocks surexploités. Leur efficacité dépend en partie du maintien de la connectivité entre les populations marines, assurée à travers divers processus écologiques dont la dispersion larvaire. Dans le cadre de ce travail de thèse, un modèle biophysique intégrant des données de courants, issues de mesures d'altimétrie par satellite, a été utilisé pour évaluer la connectivité entre les récifs de l'océan Indien d'une part, et à travers le réseau d'AMP de Méditerranée d'autre part. Différentes méthodes d'analyse ont été utilisées, telles que la théorie des graphes et le clustering. Dans l'océan Indien occidental, l'analyse des connectivités marines montre que le nombre de connexions entre les récifs augmente avec la durée de vie larvaire des poissons. Elle met également en évidence une faible connectivité à l'échelle de la région, mais une forte inter-connectivité au sein de plusieurs sous-régions (Canal du Mozambique, Mascareignes). En Méditerranée, la connectance est globalement faible à l'échelle régionale, bien que plus importante dans le bassin occidental que le bassin oriental. L'analyse des connectivités marines montre également un taux de connectivité élevé à l'échelle d'un même pays. Selon le cas d'étude, une liste de récifs ou de sites prioritaires dans la mise en œuvre des AMP a été proposée. Enfin, les implications de ces résultats en termes de politiques transfrontalières et de coopération régionale sont discutées. / Integrating ecological connectivity into marine ecosystem management and planning is important, especially in a global context of severe fish stocks depletion and growing habitat degradation. Environmental tools such as Marine Protected Areas have been proposed to protect biodiversity, restore damaged ecosystems, sustain fisheries, and rebuild overexploited stocks. The effectiveness of marine protected areas depends in part on the maintenance of connectivity between marine populations, linked by ecological processes such as larval dispersal. In this thesis, we applied a biophysical model driven by ocean currents derived from satellite altimetry to evaluate connectivity between Western Indian Ocean reefs and across the current MPA system in the Mediterranean Sea. We applied different methods of analysis such as graph-theoretic and clustering. In the Western Indian Ocean, marine connectivity analyses show that the number of connections between reefs increases with fish pelagic larval duration. It also highlights a low connectivity across the region and a high interconnectivity within several regions (Mozambique Channel, Mascarene archipelago). In the Mediterranean Sea, connectance is globally low at the regional scale. This connectance is more important in Western than Eastern Mediterranean. Moreover, the marine connectivity analyses revealed high domestic connectivity rates. Depending on the study area, priority reefs or sites for MPA implementation are proposed. Finally, implications for transboundary marine policies and regional cooperation are discussed.
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PREDICTING GENERAL VAGAL NERVE ACTIVITY VIA THE DEVELOPMENT OF BIOPHYSICAL ARTIFICIAL INTELLIGENCELeRayah Michelle Neely-Brown (17593539) 11 December 2023 (has links)
<p dir="ltr">The vagus nerve (VN) is the tenth cranial nerve that mediates most of the parasympathetic functions of the autonomic nervous system. The axons of the human VN comprise a mix of unmyelinated and myelinated axons, where ~80% of the axons are unmyelinated C fibers (Havton et al., 2021). Understanding that most VN axons are unmyelinated, there is a need to map the pathways of these axons to and from organs to understand their function(s) and whether C fiber morphology or signaling characteristics yield insights into their functions. Developing a machine learning model that detects and predicts the morphology of VN single fiber action potentials based on select fiber characteristics, e.g., diameter, myelination, and position within the VN, allows us to more readily categorize the nerve fibers with respect to their function(s). Additionally, the features of this machine learning model could help inform peripheral neuromodulation devices that aim to restore, replace, or augment one or more specific functions of the VN that have been lost due to injury, disease, or developmental abnormalities.</p><p dir="ltr">We designed and trained four types of Multi-layer Perceptron Artificial Deep Neural Networks (MLP-ANN) with 10,000 rat abdominal vagal C-fibers simulated via the peripheral neural interface model ViNERS. We analyze the accuracy of each MLP-ANN’s SFAP predictions by conducting normalized cross-correlation and morphology analyses with the ViNERS C-fiber SFAP counterparts. Our results showed that our best MLP predicted over 94% of the C-fiber SFAPs with strong normalized cross-correlation coefficients of 0.7 through 1 with the ViNERS SFAPs. Overall, this novel tool can use a C-fiber’s biophysical characteristics (i.e., fiber diameter size, fiber position on the x/y axis, etc.) to predict C-fiber SFAP morphology.</p>
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Single Cell Transcriptomic-informed Microcircuit Computer Modelling of Temporal Lobe EpilepsyReddy, Vineet 28 July 2022 (has links)
No description available.
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Amélioration des procédures de cryoconservation de type congélation-lente par simulation et caractérisation des effets de composés chitooligosaccharides / Slow-freezing procedures improvements, by simulation and characterization of the effects of chitooligosaccharides compoundsDesnos, Hugo 05 April 2019 (has links)
Les méthodes d’amélioration des procédures de cryoconservation sont traditionnellement basées sur l’empirisme. Pour s’en démarquer, nous sommes repartis des modèles biophysiques développés pour décrire les procédures en s’appuyant sur 2 méthodes. La 1ère méthode a consisté au développement de techniques de simulation des procédures en caractérisant l’utilisation du Snomax dans l’appareil DSC. Nous avons montré que le contrôle de la température de nucléation (Tn) est possible en choisissant les conditions expérimentales (volume d’échantillon et concentration en Snomax) qui influencent les probabilités de présence de 3 sous-populations d’INA des protéines de P. syringae. La possibilité d’effectuer des simulations a pu être validée pour certaines plages de surfusion dans les solutions de cryoconservation. Ceci a permis la caractérisation des effets physiques influencés par Tn et qui interviennent au cours des procédures et d’alimenter les modèles biophysiques de cryoconservation. La 2ème méthode a consisté à la modification de la composition des solutions afin de réduire le recours au DMSO (cytotoxique) en utilisant des composés de type oligosaccharides : les COS. Après vérification de la biocompatibilité des COS avec des cellules embryonnaires, la caractérisation de l’influence thermodynamique des COS a été effectuée. Il a été montré que les COS sont des cryostabilisateurs qui se lient à une petite quantité de molécule d’eau et n’en affecte pas les propriétés physicochimiques. Les COS peuvent donc être introduits dans le milieu extracellulaire sans risque d’accélérer la déshydratation cellulaire. De plus, il a été montré qu’ils favorisent la gélification du milieu extracellulaire, laquelle est fonction de la proportion massique d’eau en solution résiduelle. Cette gélification fige une partie du système ce qui favorise sa stabilisation au passage des zones de températures à risques de recristallisation / We wished to move aside classical cryopreservation procedure improvements that are based on empiricism and to focus on existing biophysical models in order to describe procedures. We based our study on two methods. The first method consisted in developing the methods for the simulations of procedures, by characterizing the use of Snomax in a DSC device. This study highlighted that the nucleation temperature (Tn) control is possible under precise experimental conditions (sample volume and Snomax concentration) that influence the presence probability of 3 INA subpopulations of the P. syringae protein aggregates. The possibility to simulate the cryopreservation procedures has been achieved for some supercooling ranges within complex cryopreservation solutions. Consequently, it has been possible to characterize the physical effects influenced by Tn and involved within procedures. These results will participate in supplying cryopreservation biophysical models. The second method aimed to modify the composition of cryopreservative solutions in order to reduce the DMSO use (because of its cytotoxicity), using extracellular CPA components: the chitooligosaccharides COS. Subsequent to the biocompatibility verification of the COS with embryonic cells, the thermodynamic influence of the COS has been characterized. Therefore, it has been demonstrated that COS are cryostabilizers that link themselves to a small number of water molecules and does not influence its physicochemical properties. Consequently, COS can be added within the extracellular space without any risk to accelerate the cell dehydration. It has been demonstrated that COS favor the gelation of the extracellular space and that this gelation relies on the mass proportion of water in the residual solution. This gelation immobilizes a part of the system and therefore favor its stabilization when the temperature reaches the risky recrystallization range
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