Ranjit Kumar Upadhyay , Debasish Pradhan , Rana D. Parshad , Parimita Roy
{"title":"肥胖诱发阿尔茨海默病的反应-扩散模型中全局吸引子的存在及其控制策略","authors":"Ranjit Kumar Upadhyay , Debasish Pradhan , Rana D. Parshad , Parimita Roy","doi":"10.1016/j.cnsns.2024.108396","DOIUrl":null,"url":null,"abstract":"<div><div>Evidence suggests that obesity, diabetes, and aging notably increase susceptibility to dementia-related conditions such as Alzheimer’s disease (AD). This article explores the correlations between obesity, diabetes, and AD. It introduces a diffusion-driven model encompassing variables like glucose dynamics, insulin levels, beta cells, microglia, cytokines, amyloid-<span><math><mi>β</mi></math></span> plaques, neurofibrillary tangles (<span><math><mi>τ</mi></math></span> plaques), neurodegeneration, and cognitive decline. The study includes stability analysis (local and global), examining boundedness and long-time behavior via showing the existence of a global attractor for the diffusion-driven model. A global sensitivity analysis, utilizing the Partial Rank Correlation Coefficient (PRCC), identifies factors sensitively impacting <span><math><msub><mrow><mi>A</mi></mrow><mrow><mi>β</mi></mrow></msub></math></span> plaque growth, <span><math><mi>τ</mi></math></span> plaques, and neurodegeneration. The deterministic model solution illustrates spatiotemporal dynamics, revealing a link between obesity and Alzheimer’s, which is characterized by distinct patchy patterns. While Alzheimer’s has no cure, employing optimal control techniques can help alleviate its effects and enhance affected individuals’ quality of life. An optimal control problem for AD management is developed, optimizing multiple aspects of disease management. The study highlights the efficacy of long-term healthy lifestyle practices and customized anti-amyloid therapy in significantly delaying obesity-induced AD progression. This research sheds light on the connection between obesity and Alzheimer’s, underscoring the negative impact of pro-inflammatory microglia on cognitive decline while proposing control strategies.</div></div>","PeriodicalId":50658,"journal":{"name":"Communications in Nonlinear Science and Numerical Simulation","volume":null,"pages":null},"PeriodicalIF":3.4000,"publicationDate":"2024-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Existence of global attractor in reaction–diffusion model of obesity-induced Alzheimer’s disease and its control strategies\",\"authors\":\"Ranjit Kumar Upadhyay , Debasish Pradhan , Rana D. Parshad , Parimita Roy\",\"doi\":\"10.1016/j.cnsns.2024.108396\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Evidence suggests that obesity, diabetes, and aging notably increase susceptibility to dementia-related conditions such as Alzheimer’s disease (AD). This article explores the correlations between obesity, diabetes, and AD. It introduces a diffusion-driven model encompassing variables like glucose dynamics, insulin levels, beta cells, microglia, cytokines, amyloid-<span><math><mi>β</mi></math></span> plaques, neurofibrillary tangles (<span><math><mi>τ</mi></math></span> plaques), neurodegeneration, and cognitive decline. The study includes stability analysis (local and global), examining boundedness and long-time behavior via showing the existence of a global attractor for the diffusion-driven model. A global sensitivity analysis, utilizing the Partial Rank Correlation Coefficient (PRCC), identifies factors sensitively impacting <span><math><msub><mrow><mi>A</mi></mrow><mrow><mi>β</mi></mrow></msub></math></span> plaque growth, <span><math><mi>τ</mi></math></span> plaques, and neurodegeneration. The deterministic model solution illustrates spatiotemporal dynamics, revealing a link between obesity and Alzheimer’s, which is characterized by distinct patchy patterns. While Alzheimer’s has no cure, employing optimal control techniques can help alleviate its effects and enhance affected individuals’ quality of life. An optimal control problem for AD management is developed, optimizing multiple aspects of disease management. The study highlights the efficacy of long-term healthy lifestyle practices and customized anti-amyloid therapy in significantly delaying obesity-induced AD progression. 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Existence of global attractor in reaction–diffusion model of obesity-induced Alzheimer’s disease and its control strategies
Evidence suggests that obesity, diabetes, and aging notably increase susceptibility to dementia-related conditions such as Alzheimer’s disease (AD). This article explores the correlations between obesity, diabetes, and AD. It introduces a diffusion-driven model encompassing variables like glucose dynamics, insulin levels, beta cells, microglia, cytokines, amyloid- plaques, neurofibrillary tangles ( plaques), neurodegeneration, and cognitive decline. The study includes stability analysis (local and global), examining boundedness and long-time behavior via showing the existence of a global attractor for the diffusion-driven model. A global sensitivity analysis, utilizing the Partial Rank Correlation Coefficient (PRCC), identifies factors sensitively impacting plaque growth, plaques, and neurodegeneration. The deterministic model solution illustrates spatiotemporal dynamics, revealing a link between obesity and Alzheimer’s, which is characterized by distinct patchy patterns. While Alzheimer’s has no cure, employing optimal control techniques can help alleviate its effects and enhance affected individuals’ quality of life. An optimal control problem for AD management is developed, optimizing multiple aspects of disease management. The study highlights the efficacy of long-term healthy lifestyle practices and customized anti-amyloid therapy in significantly delaying obesity-induced AD progression. This research sheds light on the connection between obesity and Alzheimer’s, underscoring the negative impact of pro-inflammatory microglia on cognitive decline while proposing control strategies.
期刊介绍:
The journal publishes original research findings on experimental observation, mathematical modeling, theoretical analysis and numerical simulation, for more accurate description, better prediction or novel application, of nonlinear phenomena in science and engineering. It offers a venue for researchers to make rapid exchange of ideas and techniques in nonlinear science and complexity.
The submission of manuscripts with cross-disciplinary approaches in nonlinear science and complexity is particularly encouraged.
Topics of interest:
Nonlinear differential or delay equations, Lie group analysis and asymptotic methods, Discontinuous systems, Fractals, Fractional calculus and dynamics, Nonlinear effects in quantum mechanics, Nonlinear stochastic processes, Experimental nonlinear science, Time-series and signal analysis, Computational methods and simulations in nonlinear science and engineering, Control of dynamical systems, Synchronization, Lyapunov analysis, High-dimensional chaos and turbulence, Chaos in Hamiltonian systems, Integrable systems and solitons, Collective behavior in many-body systems, Biological physics and networks, Nonlinear mechanical systems, Complex systems and complexity.
No length limitation for contributions is set, but only concisely written manuscripts are published. Brief papers are published on the basis of Rapid Communications. Discussions of previously published papers are welcome.