Mathematical Biosciences最新文献_第3页

A new optimized regularized Stokeslet model reveals the effects of multicellular protozoan colony configuration on hydrodynamic performance 一个新的优化正则化Stokeslet模型揭示了多细胞原生动物群落结构对水动力性能的影响。

IF 1.8 4区数学

Mathematical Biosciences Pub Date : 2025-08-18 DOI: 10.1016/j.mbs.2025.109519

Hongfei Chen , Tom Hata , Ricardo Cortez , Hoa Nguyen , M.A.R. Koehl , Lisa Fauci

{"title":"A new optimized regularized Stokeslet model reveals the effects of multicellular protozoan colony configuration on hydrodynamic performance","authors":"Hongfei Chen , Tom Hata , Ricardo Cortez , Hoa Nguyen , M.A.R. Koehl , Lisa Fauci","doi":"10.1016/j.mbs.2025.109519","DOIUrl":"10.1016/j.mbs.2025.109519","url":null,"abstract":"<div><div>Many microbial eukaryotes have unicellular life stages, but can also form multicellular colonies. We explored hydrodynamic consequences of colony morphology, which affects swimming and flux of prey-carrying water to cells in a colony, using the choanoflagellate, <em>Choanoeca flexa</em>, which forms cup-like colonies that can turn inside-out so flagella line the cup’s interior or cover its outside surface. Detailed hydrodynamic models incorporating cell morphologies are not feasible for colonies with many cells. Therefore, we designed a reduced model of each cell using regularized-force-dipoles with parameters optimized (by selecting the regularized delta function from a given class) to match the flow-field of a detailed model of a cell. Calculated swimming speeds and water flux to flagella-in colonies match those measured for living <em>C. flexa</em>. For a given shape (flat bowls, hemispheres, spherical cups) of flagella-in colony, models showed that swimming speed and water flux towards the colony increases with cell density, although flux per cell is independent of density. Denser packing of cells at the front of flagella-in colonies increases swimming speed and flux to cells at all positions in the colonies. Flagella-in colonies swim more slowly, but produce higher water flux per cell than do flagella-out colonies of the same configuration, suggesting that flagella-out colonies are better swimmers, whereas flagella-in colonies are better feeders. A model flagella-out colony with morphology matched to a real <em>C. flexa</em> requires a flagellar force 5–10 times greater than that for flagella-in colonies to achieve the measured swimming speed, suggesting flagella beat differently on flagella-out colonies.</div></div>","PeriodicalId":51119,"journal":{"name":"Mathematical Biosciences","volume":"389 ","pages":"Article 109519"},"PeriodicalIF":1.8,"publicationDate":"2025-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144984281","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Mathematical model of replication–mutation dynamics in coronaviruses 冠状病毒复制-突变动力学的数学模型

IF 1.8 4区数学

Mathematical Biosciences Pub Date : 2025-08-18 DOI: 10.1016/j.mbs.2025.109518

K.B. Blyuss, Y.N. Kyrychko

{"title":"Mathematical model of replication–mutation dynamics in coronaviruses","authors":"K.B. Blyuss, Y.N. Kyrychko","doi":"10.1016/j.mbs.2025.109518","DOIUrl":"10.1016/j.mbs.2025.109518","url":null,"abstract":"<div><div>RNA viruses are known for their fascinating evolutionary dynamics, characterised by high mutation rates, fast replication, and ability to form quasispecies — clouds of genetically related mutants. Fast replication in RNA viruses is achieved by a very fast but error-prone RNA-dependent RNA polymerase (RdRP). High mutation rates are a double-edged sword: they provide RNA viruses with a mechanism of fast adaptation to a changing environment or host immune system, but at the same time they pose risk to virus survivability in terms of either virus population being dominated by mutants (error catastrophe), or extinction of all viral sequences due to accumulation of mutations (lethal mutagenesis). Coronaviruses, being a subset of RNA viruses, are unique in having a special enzyme, exoribonuclease (ExoN), responsible for proofreading and correcting errors induced by the RdRP. In this paper we consider replication dynamics of coronaviruses with account for mutations that can be neutral, deleterious or lethal. Compared to earlier models of replication of RNA viruses, our model also explicitly includes ExoN and its effects on mediating viral replication. Special attention is paid to different virus replication modes that are known to be crucial for controlling the dynamics of virus populations. We analyse extinction, mutant-only and quasispecies steady states, and study their stability in terms of different parameters, identifying regimes of error catastrophe and lethal mutagenesis. With coronaviruses being responsible for some of the largest pandemics in the last twenty years, we also model the effects of antiviral treatment with various replication inhibitors and mutagenic drugs.</div></div>","PeriodicalId":51119,"journal":{"name":"Mathematical Biosciences","volume":"388 ","pages":"Article 109518"},"PeriodicalIF":1.8,"publicationDate":"2025-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144879013","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Modeling and dynamics of Brucella infection-induced macrophage apoptosis inhibition 布鲁氏菌感染诱导巨噬细胞凋亡抑制的模型和动力学

IF 1.8 4区数学

Mathematical Biosciences Pub Date : 2025-08-11 DOI: 10.1016/j.mbs.2025.109515

Huidi Chu , Meng Fan , Huaiping Zhu

{"title":"Modeling and dynamics of Brucella infection-induced macrophage apoptosis inhibition","authors":"Huidi Chu , Meng Fan , Huaiping Zhu","doi":"10.1016/j.mbs.2025.109515","DOIUrl":"10.1016/j.mbs.2025.109515","url":null,"abstract":"<div><div>Brucella is an intracellular bacterium that causes the widespread zoonotic disease brucellosis. Within their hosts, Brucella has evolved various immune evasion strategies, including the ability to survive and replicate within host cells, especially within macrophages. This leads brucellosis from an acute phase to a chronic phase that is difficult to cure. In order to explore the key factors for the survival of Brucella and the mechanisms of persistent chronic infection, a mathematical model is developed to characterize the interactions between Brucella and macrophages, which incorporates a saturable apoptosis-inhibiting function within an infected host. The dynamics are well investigated in mathematics such as the invariance and boundedness, the existence and stability of equilibria, the bifurcation dynamics, and the threshold criteria for the clearance of Brucella infection. In particular, it is elaborated that the model can undergo forward and backward bifurcation, Hopf bifurcation, and Bogdanov–Takens bifurcation of codimension 2 by applying the central manifold theorem and normal form theory. Numerical analyses indicate that the presence of bistability complicates the clearance processes of Brucella. In addition, the infection rate of Brucella and the baseline apoptosis rate of infected macrophages are identified as key factors in determining Brucella clearance, the persistence of chronic infection, and the occurrence of undulating fever. The main findings highlight that increasing immune clearance capacity and reducing the virulence of Brucella are critical for controlling Brucella infections.</div></div>","PeriodicalId":51119,"journal":{"name":"Mathematical Biosciences","volume":"388 ","pages":"Article 109515"},"PeriodicalIF":1.8,"publicationDate":"2025-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144840862","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Distributions of prevalence and daily new cases in a stochastic linear SEIR model 随机线性SEIR模型中流行率和每日新病例的分布

IF 1.8 4区数学

Mathematical Biosciences Pub Date : 2025-08-11 DOI: 10.1016/j.mbs.2025.109508

Manting Wang, P. van den Driessche, Laura L.E. Cowen, Junling Ma

{"title":"Distributions of prevalence and daily new cases in a stochastic linear SEIR model","authors":"Manting Wang, P. van den Driessche, Laura L.E. Cowen, Junling Ma","doi":"10.1016/j.mbs.2025.109508","DOIUrl":"10.1016/j.mbs.2025.109508","url":null,"abstract":"<div><div>Model parameters are typically estimated by calibrating the model to new case counts. This is important for understanding disease dynamics and guiding control measures. For parameter estimation, it is essential to identify the distribution of new cases and establish an appropriate likelihood function. This study employs a stochastic linear SEIR model to approximate the distributions of the number of infectious individuals and the number of daily new cases. We show that the probability-generating function (PGF) of the number of infectious individuals can be approximated as the product of PGFs of two birth-and-death processes. We theoretically derive formulas for the mean and variance of both the number of infectious individuals and daily new cases. Furthermore, we demonstrate that the distribution of the infectious population size can be approximated by a binomial or negative binomial distribution, depending on the relationship between its mean and variance. The distribution of daily new cases can also be well approximated by a binomial or negative binomial distribution, depending on the distribution of the infectious population. Specifically, if the number of infectious individuals follows a binomial distribution, the number of daily new cases is also binomial; if it follows a negative binomial distribution, the number of daily new cases is negative binomial as well. These findings provide a robust theoretical basis for parameter estimation and epidemic forecasting.</div></div>","PeriodicalId":51119,"journal":{"name":"Mathematical Biosciences","volume":"388 ","pages":"Article 109508"},"PeriodicalIF":1.8,"publicationDate":"2025-08-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144829841","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An ant territory formation model with chemotaxis and alarm pheromones 具有趋化性和报警信息素的蚂蚁领地形成模型

IF 1.8 4区数学

Mathematical Biosciences Pub Date : 2025-07-30 DOI: 10.1016/j.mbs.2025.109498

Paulo Amorim , Rodrigo de Lima , Bruno Telch

{"title":"An ant territory formation model with chemotaxis and alarm pheromones","authors":"Paulo Amorim , Rodrigo de Lima , Bruno Telch","doi":"10.1016/j.mbs.2025.109498","DOIUrl":"10.1016/j.mbs.2025.109498","url":null,"abstract":"<div><div>We present and analyze a PDE model of ant territory formation, consisting of a system of reaction–advection–diffusion PDEs of chemotaxis type in two space dimensions. Following existing literature on rival ant nest interactions, two ant populations are divided into peaceful and aggressive compartments. When encountering members of the other colony, peaceful ants can turn into aggressive ants, which produce an alarm pheromone. This pheromone attracts other aggressive ants, and also turns peaceful ants into aggressive ants. It is belived that these dynamics can help explain the formation of well segregated territories, which are observed in the field. We include these dynamics into a chemotaxis-type model, which we analyze and simulate. We prove that, under a small initial mass condition, weak solutions are globally bounded, and obtain a global well-posedness result (without any mass conditions) under a mild sublinear growth assumption on the pheromone deposition term. Besides the mathematical results, we show through simulations that well-defined, non-overlapping territories emerge from the dynamics, especially in the beginning of territory formation. Our analysis therefore supports the hypothesis that these interaction dynamics are an important part of the observed territorial patterns in ants.</div></div>","PeriodicalId":51119,"journal":{"name":"Mathematical Biosciences","volume":"388 ","pages":"Article 109498"},"PeriodicalIF":1.8,"publicationDate":"2025-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144757907","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Flow-driven dynamics in a mussel-algae system with nonlinear boundary interactions 具有非线性边界相互作用的贻贝-藻类系统的流动驱动动力学

IF 1.8 4区数学

Mathematical Biosciences Pub Date : 2025-07-26 DOI: 10.1016/j.mbs.2025.109507

Chaochao Li , Hao Wang , Shangjiang Guo

引用次数: 0

A stochastic model of prion dynamics with conversion and fragmentation 具有转换和碎裂的朊病毒动力学随机模型

IF 1.9 4区数学

Mathematical Biosciences Pub Date : 2025-07-24 DOI: 10.1016/j.mbs.2025.109505

Arpan Ghosh , Peter Olofsson , Suzanne S. Sindi

引用次数: 0

Optimal control of eggplant pest populations in a Predator–Prey–Parasitoid model with seasonal growth effects 具有季节生长效应的捕食者-被食性-寄生性模型对茄子害虫种群的最优控制

IF 1.9 4区数学

Mathematical Biosciences Pub Date : 2025-07-22 DOI: 10.1016/j.mbs.2025.109506

Mona Zevika, S. Khoirul Himmi

{"title":"Optimal control of eggplant pest populations in a Predator–Prey–Parasitoid model with seasonal growth effects","authors":"Mona Zevika, S. Khoirul Himmi","doi":"10.1016/j.mbs.2025.109506","DOIUrl":"10.1016/j.mbs.2025.109506","url":null,"abstract":"<div><div>This study investigates the population dynamics of the eggplant fruit and shoot borer (EFSB), emphasizing the role of natural enemies — predators and parasitoids — in pest management. A mathematical model, comprising three variables representing each population, is constructed to analyze the interactions. The model exhibits six equilibrium points, with particular focus on the predator-free and coexistence equilibria. Crucially, the model incorporates the seasonal variability of the pest’s growth rate, reflecting the influence of environmental factors such as temperature changes. Optimal control strategies are explored, encompassing both chemical and biological approaches, including the use of parasitoids. For chemical control, Pontryagin’s Minimum Principle is employed to derive optimal strategies under varying seasonal growth conditions. The biological control strategy, centered on parasitoid release, is analyzed using State-Dependent Riccati Equations (SDRE) to determine optimal continuous and impulsive release methods. The findings highlight the importance of considering seasonal variations in pest growth and demonstrate the efficacy of impulsive parasitoid releases for pest management. This research provides valuable insights into sustainable pest management and offers a robust framework for applying mathematical modeling to complex agricultural systems.</div></div>","PeriodicalId":51119,"journal":{"name":"Mathematical Biosciences","volume":"387 ","pages":"Article 109506"},"PeriodicalIF":1.9,"publicationDate":"2025-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144694702","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Persistence index for harvested populations 收获种群的持久性指数。

IF 1.8 4区数学

Mathematical Biosciences Pub Date : 2025-07-18 DOI: 10.1016/j.mbs.2025.109497

Jerzy A. Filar , Matthew H. Holden , Manuela Mendiolar , Sabrina H. Streipert

引用次数: 0

Pattern dynamics analysis and parameter identification of spatiotemporal infectious disease models on complex networks 复杂网络时空传染病模型的模式动力学分析与参数辨识

IF 1.9 4区数学

Mathematical Biosciences Pub Date : 2025-07-16 DOI: 10.1016/j.mbs.2025.109502

Tao Yang , Linhe Zhu , Shuling Shen , Le He

{"title":"Pattern dynamics analysis and parameter identification of spatiotemporal infectious disease models on complex networks","authors":"Tao Yang , Linhe Zhu , Shuling Shen , Le He","doi":"10.1016/j.mbs.2025.109502","DOIUrl":"10.1016/j.mbs.2025.109502","url":null,"abstract":"<div><div>This paper primarily explores the dynamics of reaction–diffusion systems with advection effects on discrete networks and establishes a corresponding infectious disease transmission model incorporating delay effects. Initially, we consider the conditions for the existence of the equilibrium point and linearly approximate the time delay near this equilibrium point. Then we discuss the necessary conditions for Turing instability under various constraints based on the approximate system. We also introduce two types of lower-order network structures. In one of these lower-order networks, we discuss the directional movement of two different populations. To further analyze the dynamic behavior on different networks, we construct a special higher-order network based on another lower-order network. In addition, we use optimal control to solve the problem of parameter identification. We conduct extensive numerical simulations to study the impact of advection effects and higher-order networks on system dynamics, pattern parameter identification under unknown conditions, and model fitting and prediction based on actual data, which validate the model’s effectiveness and practical utility.</div></div>","PeriodicalId":51119,"journal":{"name":"Mathematical Biosciences","volume":"387 ","pages":"Article 109502"},"PeriodicalIF":1.9,"publicationDate":"2025-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144653250","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0