We present a mathematical study for the development of multiple sclerosis based on a reaction-diffusion system. The model describes interactions among different populations of human cells, motion of immune cells stimulated by cytokines, consumption of myelin sheath due to anomalously activated lymphocytes and its restoration by oligodendrocytes. Successively, we introduce a therapy term representing injection of low-dose IL-2 interleukine. A natural step is then to study the system, investigating the formation of spatial patterns by means of a Turing instability analysis of the problem. In particular, we get spatial patterns oscillating in time that may reproduce brain lesions characteristic of the early stage of the pathology, in both non-treatment and treatment scenarios.
{"title":"A reaction-diffusion model for relapsing-remitting multiple sclerosis with a treatment term","authors":"Romina Travaglini","doi":"arxiv-2407.06802","DOIUrl":"https://doi.org/arxiv-2407.06802","url":null,"abstract":"We present a mathematical study for the development of multiple sclerosis\u0000based on a reaction-diffusion system. The model describes interactions among\u0000different populations of human cells, motion of immune cells stimulated by\u0000cytokines, consumption of myelin sheath due to anomalously activated\u0000lymphocytes and its restoration by oligodendrocytes. Successively, we introduce\u0000a therapy term representing injection of low-dose IL-2 interleukine. A natural\u0000step is then to study the system, investigating the formation of spatial\u0000patterns by means of a Turing instability analysis of the problem. In\u0000particular, we get spatial patterns oscillating in time that may reproduce\u0000brain lesions characteristic of the early stage of the pathology, in both\u0000non-treatment and treatment scenarios.","PeriodicalId":501572,"journal":{"name":"arXiv - QuanBio - Tissues and Organs","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141572062","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Nastassia Pricoupenko, Flavia Marsigliesi, Philippe Marcq, Carles Blanch-Mercader, Isabelle Bonnet
Collective cell migration is key during development, wound healing and metastasis and relies on coordinated cell behaviors at the group level. Src kinase is a signalling enzyme regulating many cellular processes including adhesion and motility and its deregulated activation has been associated to aggressiveness of different cancers. Here, we take advantage of optogenetics to precisely control Src activation in time to study the effect of its over activation on collective rotation of confined monolayers. We show that Src activation slows down collective rotation of epithelial cells confined into circular adhesive patches. We interpret velocity, force and stress data during period of non-activation and period of activation of Src thanks to an hydrodynamic description of the cell assembly as a polar active fluid. Src activation leads to a 2-fold decrease in the ratio of polar angle to friction, which could result from increased adhesive bonds at the cell-substrate interface. Our work reveals the importance of fine-tuning the level of Src activity for coordinated collective behaviors.
{"title":"Src Kinase Slows Collective Rotation of Confined Epithelial Cell Monolayers","authors":"Nastassia Pricoupenko, Flavia Marsigliesi, Philippe Marcq, Carles Blanch-Mercader, Isabelle Bonnet","doi":"arxiv-2407.06920","DOIUrl":"https://doi.org/arxiv-2407.06920","url":null,"abstract":"Collective cell migration is key during development, wound healing and\u0000metastasis and relies on coordinated cell behaviors at the group level. Src\u0000kinase is a signalling enzyme regulating many cellular processes including\u0000adhesion and motility and its deregulated activation has been associated to\u0000aggressiveness of different cancers. Here, we take advantage of optogenetics to\u0000precisely control Src activation in time to study the effect of its over\u0000activation on collective rotation of confined monolayers. We show that Src\u0000activation slows down collective rotation of epithelial cells confined into\u0000circular adhesive patches. We interpret velocity, force and stress data during\u0000period of non-activation and period of activation of Src thanks to an\u0000hydrodynamic description of the cell assembly as a polar active fluid. Src\u0000activation leads to a 2-fold decrease in the ratio of polar angle to friction,\u0000which could result from increased adhesive bonds at the cell-substrate\u0000interface. Our work reveals the importance of fine-tuning the level of Src\u0000activity for coordinated collective behaviors.","PeriodicalId":501572,"journal":{"name":"arXiv - QuanBio - Tissues and Organs","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141572058","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper investigates a model of plant organ placement motivated by the appearance of large Fibonacci numbers in phyllotaxis, and provides the first large-scale empirical validation of this model. Specifically it evaluates the ability of Schwendener disk-stacking models to generate parastichy patterns seen in a large dataset of sunflower seedheads. We find that features of this data that the models can account for include a predominance of Fibonacci counts, usually in a pair of left and right counts on a single seedhead, a smaller but detectable frequency of Lucas and double Fibonacci numbers, a comparable frequency of Fibonacci numbers plus or minus one, and occurrences of pairs of roughly equal but non-Fibonacci counts in a `columnar' structure. A further observation in the dataset was an occasional lack of rotational symmetry in the parastichy spirals, and this paper demonstrates those in the model for the first time. Schwendener disk-stacking models allow Fibonacci structure by ensuring that a parameter of the model corresponding to the speed of plant growth is kept small enough. While many other models can exhibit Fibonacci structure, usually by specifying a rotation parameter to an extremely high precision, no other model has accounted for further, non-Fibonacci, features in the observed data. The Schwendener model produces these naturally in the region of parameter space just beyond where the Fibonacci structure breaks down, without any further parameter fitting. We also introduce stochasticity into the model and show that it while it can be responsible for the appearance of columnar structure, the disordered dynamics of the deterministic system near the critical region can also generate this structure.
{"title":"Disk-stacking models are consistent with Fibonacci and non-Fibonacci structure in sunflowers","authors":"Jonathan Swinton","doi":"arxiv-2407.05857","DOIUrl":"https://doi.org/arxiv-2407.05857","url":null,"abstract":"This paper investigates a model of plant organ placement motivated by the\u0000appearance of large Fibonacci numbers in phyllotaxis, and provides the first\u0000large-scale empirical validation of this model. Specifically it evaluates the\u0000ability of Schwendener disk-stacking models to generate parastichy patterns\u0000seen in a large dataset of sunflower seedheads. We find that features of this\u0000data that the models can account for include a predominance of Fibonacci\u0000counts, usually in a pair of left and right counts on a single seedhead, a\u0000smaller but detectable frequency of Lucas and double Fibonacci numbers, a\u0000comparable frequency of Fibonacci numbers plus or minus one, and occurrences of\u0000pairs of roughly equal but non-Fibonacci counts in a `columnar' structure. A\u0000further observation in the dataset was an occasional lack of rotational\u0000symmetry in the parastichy spirals, and this paper demonstrates those in the\u0000model for the first time. Schwendener disk-stacking models allow Fibonacci structure by ensuring that a\u0000parameter of the model corresponding to the speed of plant growth is kept small\u0000enough. While many other models can exhibit Fibonacci structure, usually by\u0000specifying a rotation parameter to an extremely high precision, no other model\u0000has accounted for further, non-Fibonacci, features in the observed data. The\u0000Schwendener model produces these naturally in the region of parameter space\u0000just beyond where the Fibonacci structure breaks down, without any further\u0000parameter fitting. We also introduce stochasticity into the model and show that\u0000it while it can be responsible for the appearance of columnar structure, the\u0000disordered dynamics of the deterministic system near the critical region can\u0000also generate this structure.","PeriodicalId":501572,"journal":{"name":"arXiv - QuanBio - Tissues and Organs","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141572056","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Alejandro GarzonUniversidad Sergio Arboleda, Roman O. GrigorievGeorgia Institute of Technology
This study investigates ultra-low-energy defibrillation protocols using a simple two-dimensional model of cardiac tissue. We find that, rather counter-intuitively, a single, properly timed, biphasic pulse can be more effective in defibrillating the tissue than low energy antitachycardia pacing (LEAP) which employs a sequence of such pulses, succeeding where the latter approach fails. Furthermore, we show that, with the help of adjoint optimization, it is possible to reduce the energy required for defibrillation even further, making it three orders of magnitude lower than that required by LEAP. Finally, we establish that this dramatic reduction is achieved through exploiting the sensitivity of the dynamics in vulnerable windows to promote annihilation of pairs of nearby phase singularities.
{"title":"Ultra-low-energy defibrillation through adjoint optimization","authors":"Alejandro GarzonUniversidad Sergio Arboleda, Roman O. GrigorievGeorgia Institute of Technology","doi":"arxiv-2407.05115","DOIUrl":"https://doi.org/arxiv-2407.05115","url":null,"abstract":"This study investigates ultra-low-energy defibrillation protocols using a\u0000simple two-dimensional model of cardiac tissue. We find that, rather\u0000counter-intuitively, a single, properly timed, biphasic pulse can be more\u0000effective in defibrillating the tissue than low energy antitachycardia pacing\u0000(LEAP) which employs a sequence of such pulses, succeeding where the latter\u0000approach fails. Furthermore, we show that, with the help of adjoint\u0000optimization, it is possible to reduce the energy required for defibrillation\u0000even further, making it three orders of magnitude lower than that required by\u0000LEAP. Finally, we establish that this dramatic reduction is achieved through\u0000exploiting the sensitivity of the dynamics in vulnerable windows to promote\u0000annihilation of pairs of nearby phase singularities.","PeriodicalId":501572,"journal":{"name":"arXiv - QuanBio - Tissues and Organs","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141572060","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Henrik Finsberg, Verena Charwat, Kevin Healy, Samuel Wall
Human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) are an effective tool for studying cardiac function and disease, and hold promise for screening drug effects on human tissue. Changes to motion patterns in these cells are one of the important features to be characterized to understand how an introduced drug or disease may alter the human heart beat. However, quantifying motion accurately and efficiently from optical measurements using microscopy is currently lacking. In this work, we present a unified framework for performing motion analysis on a sequence of microscopically obtained images of tissues consisting of hiPSC-CMs. We provide validation of our developed software using a synthetic test case and show how it can be used to extract displacements and velocities in hiPSC-CM microtissues. Finally, we show how to apply the framework to quantify the effect of an inotropic compound. The described software system is distributed as a python package that is easy to install, well tested and can be integrated into any python workflow.
{"title":"Automatic motion estimation with applicationsto hiPSC-CMs","authors":"Henrik Finsberg, Verena Charwat, Kevin Healy, Samuel Wall","doi":"arxiv-2407.00799","DOIUrl":"https://doi.org/arxiv-2407.00799","url":null,"abstract":"Human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) are an\u0000effective tool for studying cardiac function and disease, and hold promise for\u0000screening drug effects on human tissue. Changes to motion patterns in these\u0000cells are one of the important features to be characterized to understand how\u0000an introduced drug or disease may alter the human heart beat. However,\u0000quantifying motion accurately and efficiently from optical measurements using\u0000microscopy is currently lacking. In this work, we present a unified framework\u0000for performing motion analysis on a sequence of microscopically obtained images\u0000of tissues consisting of hiPSC-CMs. We provide validation of our developed\u0000software using a synthetic test case and show how it can be used to extract\u0000displacements and velocities in hiPSC-CM microtissues. Finally, we show how to\u0000apply the framework to quantify the effect of an inotropic compound. The\u0000described software system is distributed as a python package that is easy to\u0000install, well tested and can be integrated into any python workflow.","PeriodicalId":501572,"journal":{"name":"arXiv - QuanBio - Tissues and Organs","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141510775","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pascal R. Buenzli, Shahak Kuba, Ryan J. Murphy, Matthew J. Simpson
We propose a simple mathematical model to describe the mechanical relaxation of cells within a curved epithelial tissue layer represented by an arbitrary curve in two-dimensional space. The model represents the mechanics of the cell body either by straight springs between points of the curve, or by curved springs whose shape follows the curve. To understand the collective behaviour of these discrete models of cells at the broader tissue scale, we devise an appropriate continuum limit in which the number of cells is constant but the number of springs tends to infinity. The continuum limit shows that (i)~the straight spring model and the curved spring model converge to the same dynamics; and (ii)~the density of cells becomes governed by a diffusion equation in arc length space with second-order accuracy, where diffusion may be linear or nonlinear depending on the choice of the spring restoring force law. Our derivation of the continuum limit justifies that to reach consistent dynamics as the number of springs increases, the spring restoring force laws must be rescaled appropriately. Despite mechanical relaxation occurring within a curved tissue layer, we find that the curvature of the tissue does not affect tangential stress nor the mechanics-induced redistribution of cells within the layer in the continuum limit. However, the cell's normal stress does depend on curvature due to surface tension induced by the tangential forces. By characterising the full stress state of a cell, these models provide a basis to represent further mechanobiological processes.
{"title":"Mechanical cell interactions on curved interfaces","authors":"Pascal R. Buenzli, Shahak Kuba, Ryan J. Murphy, Matthew J. Simpson","doi":"arxiv-2406.19197","DOIUrl":"https://doi.org/arxiv-2406.19197","url":null,"abstract":"We propose a simple mathematical model to describe the mechanical relaxation\u0000of cells within a curved epithelial tissue layer represented by an arbitrary\u0000curve in two-dimensional space. The model represents the mechanics of the cell\u0000body either by straight springs between points of the curve, or by curved\u0000springs whose shape follows the curve. To understand the collective behaviour\u0000of these discrete models of cells at the broader tissue scale, we devise an\u0000appropriate continuum limit in which the number of cells is constant but the\u0000number of springs tends to infinity. The continuum limit shows that (i)~the\u0000straight spring model and the curved spring model converge to the same\u0000dynamics; and (ii)~the density of cells becomes governed by a diffusion\u0000equation in arc length space with second-order accuracy, where diffusion may be\u0000linear or nonlinear depending on the choice of the spring restoring force law.\u0000Our derivation of the continuum limit justifies that to reach consistent\u0000dynamics as the number of springs increases, the spring restoring force laws\u0000must be rescaled appropriately. Despite mechanical relaxation occurring within\u0000a curved tissue layer, we find that the curvature of the tissue does not affect\u0000tangential stress nor the mechanics-induced redistribution of cells within the\u0000layer in the continuum limit. However, the cell's normal stress does depend on\u0000curvature due to surface tension induced by the tangential forces. By\u0000characterising the full stress state of a cell, these models provide a basis to\u0000represent further mechanobiological processes.","PeriodicalId":501572,"journal":{"name":"arXiv - QuanBio - Tissues and Organs","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141510778","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Marco Ruscone, Andrea Checcoli, Randy Heiland, Emmanuel Barillot, Paul Macklin, Laurence Calzone, Vincent Noël
Multiscale models provide a unique tool for studying complex processes that study events occurring at different scales across space and time. In the context of biological systems, such models can simulate mechanisms happening at the intracellular level such as signaling, and at the extracellular level where cells communicate and coordinate with other cells. They aim to understand the impact of genetic or environmental deregulation observed in complex diseases, describe the interplay between a pathological tissue and the immune system, and suggest strategies to revert the diseased phenotypes. The construction of these multiscale models remains a very complex task, including the choice of the components to consider, the level of details of the processes to simulate, or the fitting of the parameters to the data. One additional difficulty is the expert knowledge needed to program these models in languages such as C++ or Python, which may discourage the participation of non-experts. Simplifying this process through structured description formalisms -- coupled with a graphical interface -- is crucial in making modeling more accessible to the broader scientific community, as well as streamlining the process for advanced users. This article introduces three examples of multiscale models which rely on the framework PhysiBoSS, an add-on of PhysiCell that includes intracellular descriptions as continuous time Boolean models to the agent-based approach. The article demonstrates how to easily construct such models, relying on PhysiCell Studio, the PhysiCell Graphical User Interface. A step-by-step tutorial is provided as a Supplementary Material and all models are provided at: https://physiboss.github.io/tutorial/.
{"title":"Building multiscale models with PhysiBoSS, an agent-based modeling tool","authors":"Marco Ruscone, Andrea Checcoli, Randy Heiland, Emmanuel Barillot, Paul Macklin, Laurence Calzone, Vincent Noël","doi":"arxiv-2406.18371","DOIUrl":"https://doi.org/arxiv-2406.18371","url":null,"abstract":"Multiscale models provide a unique tool for studying complex processes that\u0000study events occurring at different scales across space and time. In the\u0000context of biological systems, such models can simulate mechanisms happening at\u0000the intracellular level such as signaling, and at the extracellular level where\u0000cells communicate and coordinate with other cells. They aim to understand the\u0000impact of genetic or environmental deregulation observed in complex diseases,\u0000describe the interplay between a pathological tissue and the immune system, and\u0000suggest strategies to revert the diseased phenotypes. The construction of these\u0000multiscale models remains a very complex task, including the choice of the\u0000components to consider, the level of details of the processes to simulate, or\u0000the fitting of the parameters to the data. One additional difficulty is the\u0000expert knowledge needed to program these models in languages such as C++ or\u0000Python, which may discourage the participation of non-experts. Simplifying this\u0000process through structured description formalisms -- coupled with a graphical\u0000interface -- is crucial in making modeling more accessible to the broader\u0000scientific community, as well as streamlining the process for advanced users.\u0000This article introduces three examples of multiscale models which rely on the\u0000framework PhysiBoSS, an add-on of PhysiCell that includes intracellular\u0000descriptions as continuous time Boolean models to the agent-based approach. The\u0000article demonstrates how to easily construct such models, relying on PhysiCell\u0000Studio, the PhysiCell Graphical User Interface. A step-by-step tutorial is\u0000provided as a Supplementary Material and all models are provided at:\u0000https://physiboss.github.io/tutorial/.","PeriodicalId":501572,"journal":{"name":"arXiv - QuanBio - Tissues and Organs","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141510780","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Anyu Jiang, Cassandra Acebal, Brook Heyd, Trustin White, Gurleen Kainth, Arunashish Datta, Shreyas Sen, Adam Khalifa, Baibhab Chatterjee
Data transfer using human-body communication (HBC) represents an actively explored alternative solution to address the challenges related to energy-efficiency, tissue absorption, and security of conventional wireless. Although the use of HBC for wearable-to-wearable communication has been well-explored, different configurations for the transmitter (Tx) and receiver (Rx) for implant-to-wearable HBC needs further studies. This paper substantiates the hypothesis that a fully implanted galvanic Tx is more efficient than a capacitive Tx for interaction with a wearable Rx. Given the practical limitations of implanting an ideal capacitive device, we choose a galvanic device with one electrode encapsulated to model the capacitive scenario. We analyze the lumped circuit model for in-body to out-of-body communication, and perform Circuit-based as well as Finite Element Method (FEM) simulations to explore how the encapsulation thickness affects the received signal levels. We demonstrate in-vivo experimental results on live Sprague Dawley rats to validate the hypothesis, and show that compared to the galvanic Tx, the channel loss will be $approx$ 20 dB higher with each additional mm thickness of capacitive encapsulation, eventually going below the noise floor for ideal capacitive Tx.
{"title":"Implant-to-Wearable Communication through the Human Body: Exploring the Effects of Encapsulated Capacitive and Galvanic Transmitters","authors":"Anyu Jiang, Cassandra Acebal, Brook Heyd, Trustin White, Gurleen Kainth, Arunashish Datta, Shreyas Sen, Adam Khalifa, Baibhab Chatterjee","doi":"arxiv-2406.13141","DOIUrl":"https://doi.org/arxiv-2406.13141","url":null,"abstract":"Data transfer using human-body communication (HBC) represents an actively\u0000explored alternative solution to address the challenges related to\u0000energy-efficiency, tissue absorption, and security of conventional wireless.\u0000Although the use of HBC for wearable-to-wearable communication has been\u0000well-explored, different configurations for the transmitter (Tx) and receiver\u0000(Rx) for implant-to-wearable HBC needs further studies. This paper\u0000substantiates the hypothesis that a fully implanted galvanic Tx is more\u0000efficient than a capacitive Tx for interaction with a wearable Rx. Given the\u0000practical limitations of implanting an ideal capacitive device, we choose a\u0000galvanic device with one electrode encapsulated to model the capacitive\u0000scenario. We analyze the lumped circuit model for in-body to out-of-body\u0000communication, and perform Circuit-based as well as Finite Element Method (FEM)\u0000simulations to explore how the encapsulation thickness affects the received\u0000signal levels. We demonstrate in-vivo experimental results on live Sprague\u0000Dawley rats to validate the hypothesis, and show that compared to the galvanic\u0000Tx, the channel loss will be $approx$ 20 dB higher with each additional mm\u0000thickness of capacitive encapsulation, eventually going below the noise floor\u0000for ideal capacitive Tx.","PeriodicalId":501572,"journal":{"name":"arXiv - QuanBio - Tissues and Organs","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141510779","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Kyle Baylous, Brandon Kovarovic, Salwa Anam, Ryan Helbock, Marvin Slepian, Danny Bluestein
Prosthetic heart valve interventions such as TAVR have surged over the past decade, but the associated complication of long-term, life-threatening thrombotic events continues to undermine patient outcomes. Thus, improving thrombogenic risk analysis of TAVR devices is crucial. In vitro studies for thrombogenicity are typically difficult to perform. However, revised ISO testing standards include computational testing for thrombogenic risk assessment of cardiovascular implants. We present a fluid-structure interaction (FSI) approach for assessing thrombogenic risk of prosthetic heart valves. An FSI framework was implemented via the incompressible computational fluid dynamics multi-physics solver of the Ansys LS-DYNA software. The numerical modeling approach for flow analysis was validated by comparing the derived flow rate of the 29-mm CoreValve device from benchtop testing and orifice areas of commercial TAVR valves in the literature to in silico results. Thrombogenic risk was analyzed by computing stress accumulation (SA) on virtual platelets seeded in the flow fields via Ansys EnSight. The integrated FSI-thrombogenicity methodology was subsequently employed to examine hemodynamics and thrombogenic risk of TAVR devices with two approaches: 1) engineering optimization and 2) clinical assessment. Our methodology can be used to improve the thromboresistance of prosthetic valves from the initial design stage to the clinic. It allows for unparalleled optimization of devices, uncovering key TAVR leaflet design parameters that can be used to mitigate thrombogenic risk, in addition to patient-specific modeling to evaluate device performance. This work demonstrates the utility of advanced in silico analysis of TAVR devices that can be utilized for thrombogenic risk assessment of other blood recirculating devices.
{"title":"Thrombogenic Risk Assessment of Transcatheter Prosthetic Heart Valves Using a Fluid-Structure Interaction Approach","authors":"Kyle Baylous, Brandon Kovarovic, Salwa Anam, Ryan Helbock, Marvin Slepian, Danny Bluestein","doi":"arxiv-2406.12156","DOIUrl":"https://doi.org/arxiv-2406.12156","url":null,"abstract":"Prosthetic heart valve interventions such as TAVR have surged over the past\u0000decade, but the associated complication of long-term, life-threatening\u0000thrombotic events continues to undermine patient outcomes. Thus, improving\u0000thrombogenic risk analysis of TAVR devices is crucial. In vitro studies for\u0000thrombogenicity are typically difficult to perform. However, revised ISO\u0000testing standards include computational testing for thrombogenic risk\u0000assessment of cardiovascular implants. We present a fluid-structure interaction\u0000(FSI) approach for assessing thrombogenic risk of prosthetic heart valves. An FSI framework was implemented via the incompressible computational fluid\u0000dynamics multi-physics solver of the Ansys LS-DYNA software. The numerical\u0000modeling approach for flow analysis was validated by comparing the derived flow\u0000rate of the 29-mm CoreValve device from benchtop testing and orifice areas of\u0000commercial TAVR valves in the literature to in silico results. Thrombogenic\u0000risk was analyzed by computing stress accumulation (SA) on virtual platelets\u0000seeded in the flow fields via Ansys EnSight. The integrated FSI-thrombogenicity\u0000methodology was subsequently employed to examine hemodynamics and thrombogenic\u0000risk of TAVR devices with two approaches: 1) engineering optimization and 2)\u0000clinical assessment. Our methodology can be used to improve the thromboresistance of prosthetic\u0000valves from the initial design stage to the clinic. It allows for unparalleled\u0000optimization of devices, uncovering key TAVR leaflet design parameters that can\u0000be used to mitigate thrombogenic risk, in addition to patient-specific modeling\u0000to evaluate device performance. This work demonstrates the utility of advanced\u0000in silico analysis of TAVR devices that can be utilized for thrombogenic risk\u0000assessment of other blood recirculating devices.","PeriodicalId":501572,"journal":{"name":"arXiv - QuanBio - Tissues and Organs","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141530188","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Siemen Brussee, Giorgio Buzzanca, Anne M. R. Schrader, Jesper Kers
Histopathological analysis of Whole Slide Images (WSIs) has seen a surge in the utilization of deep learning methods, particularly Convolutional Neural Networks (CNNs). However, CNNs often fall short in capturing the intricate spatial dependencies inherent in WSIs. Graph Neural Networks (GNNs) present a promising alternative, adept at directly modeling pairwise interactions and effectively discerning the topological tissue and cellular structures within WSIs. Recognizing the pressing need for deep learning techniques that harness the topological structure of WSIs, the application of GNNs in histopathology has experienced rapid growth. In this comprehensive review, we survey GNNs in histopathology, discuss their applications, and exploring emerging trends that pave the way for future advancements in the field. We begin by elucidating the fundamentals of GNNs and their potential applications in histopathology. Leveraging quantitative literature analysis, we identify four emerging trends: Hierarchical GNNs, Adaptive Graph Structure Learning, Multimodal GNNs, and Higher-order GNNs. Through an in-depth exploration of these trends, we offer insights into the evolving landscape of GNNs in histopathological analysis. Based on our findings, we propose future directions to propel the field forward. Our analysis serves to guide researchers and practitioners towards innovative approaches and methodologies, fostering advancements in histopathological analysis through the lens of graph neural networks.
对整张切片图像（WSI）进行组织病理学分析时，深度学习方法，尤其是卷积神经网络（CNN）的使用激增。然而，CNN 通常无法捕捉到 WSI 中固有的错综复杂的局部依赖关系。图神经网络（GNN）是一种很好的替代方案，它善于直接模拟成对的相互作用，并能有效辨别 WSIs 中的拓扑组织和细胞结构。由于认识到对利用 WSI 拓扑结构的深度学习技术的迫切需要，GNN 在组织病理学中的应用经历了快速增长。在这篇综述中，我们对组织病理学中的 GNN 进行了调查，讨论了它们的应用，并探讨了为该领域未来发展铺平道路的新兴趋势。我们首先阐明了 GNN 的基本原理及其在组织病理学中的潜在应用。通过定量文献分析，我们确定了四种新兴趋势：分层 GNN、自适应图结构学习、多模态 GNN 和高阶 GNN。通过对这些趋势的深入探讨，我们深入了解了组织病理学分析中 GNN 的发展状况。我们的分析有助于引导研究人员和从业人员采用创新的方法和手段，通过图神经网络的视角促进组织病理学分析的进步。
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