Mathematical Biosciences最新文献

{"title":"Trophic flow of contamination: A nontrivial weapon for species coexistence","authors":"Amit Samadder ,&nbsp;Arnab Chattopadhyay ,&nbsp;Arindam Mandal ,&nbsp;Yun Kang ,&nbsp;Sabyasachi Bhattacharya","doi":"10.1016/j.mbs.2025.109443","DOIUrl":"10.1016/j.mbs.2025.109443","url":null,"abstract":"<div><div>In the modern age of human-induced environmental changes, ecologists are increasingly alarmed about the potential disruption of ecosystems through toxicological processes. As humanity’s footprint on the natural world expands, understanding these dynamics becomes crucial. While recent ecotoxicology research has mainly focused on entirely contaminated ecosystems, overlooking the effects of aquatic contamination on terrestrial predators with access to uncontaminated prey, our study addresses this gap. We present a prey–predator model for partially contaminated communities, where predators face a trade-off in prey preference between contaminated and uncontaminated sources. Through mathematical analysis and numerical simulations, we uncover some interpretable findings: (1) In uncontaminated environments, predation pressure may cause the extinction of one prey species. However, when even a small contamination level exists in alternative prey, endangered prey species can coexist with others. (2) Survival under high contamination depends on the predator’s preference. A very low preference for contaminated prey trivially allows the predator to persist, while low or high preferences lead to the predator’s exclusion. Surprisingly, intermediate preference leads to bi-stability between contaminated prey and predator extinction equilibrium, resulting in a trade-off between the presence of contaminated prey or the predator. (3) Our results confirm the abrupt extinction of predators due to contamination, driven by bistability between predator-free and coexisting states. However, our observation reveals that the likelihood of sudden predator extinction increases with a higher preference for contaminated prey. Additionally, we explore the robustness of these outcomes by considering flexible model assumptions and alternative parameter sets. In summary, our study offers valuable insights into the ecotoxicological processes within partially contaminated communities, shedding light on direct and indirect species interactions.</div></div>","PeriodicalId":51119,"journal":{"name":"Mathematical Biosciences","volume":"384 ","pages":"Article 109443"},"PeriodicalIF":1.9,"publicationDate":"2025-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143842540","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}

{"title":"Homeostasis in input-output networks: Structure, Classification and Applications","authors":"Fernando Antoneli ,&nbsp;Martin Golubitsky ,&nbsp;Jiaxin Jin ,&nbsp;Ian Stewart","doi":"10.1016/j.mbs.2025.109435","DOIUrl":"10.1016/j.mbs.2025.109435","url":null,"abstract":"<div><div>Homeostasis is concerned with regulatory mechanisms, present in biological systems, where some specific variable is kept close to a set value as some external disturbance affects the system. Many biological systems, from gene networks to signaling pathways to whole tissue/organism physiology, exhibit homeostatic mechanisms. In all these cases there are homeostatic regions where the variable is relatively to insensitive external stimulus, flanked by regions where it is sensitive. Mathematically, the notion of homeostasis can be formalized in terms of an input–output function that maps the parameter representing the external disturbance to the output variable that must be kept within a fairly narrow range. This observation inspired the introduction of the notion of infinitesimal homeostasis, namely, the derivative of the input–output function is zero at an isolated point. This point of view allows for the application of methods from singularity theory to characterize infinitesimal homeostasis points (i.e. critical points of the input–output function). In this paper we review the infinitesimal approach to the study of homeostasis in input–output networks. An input–output network is a network with two distinguished nodes ‘input’ and ‘output’, and the dynamics of the network determines the corresponding input–output function of the system. This class of dynamical systems provides an appropriate framework to study homeostasis and several important biological systems can be formulated in this context. Moreover, this approach, coupled to graph-theoretic ideas from combinatorial matrix theory, provides a systematic way for classifying different types of homeostasis (homeostatic mechanisms) in input–output networks, in terms of the network topology. In turn, this leads to new mathematical concepts, such as, homeostasis subnetworks, homeostasis patterns, homeostasis mode interaction. We illustrate the usefulness of this theory with several biological examples: biochemical networks, chemical reaction networks (CRN), gene regulatory networks (GRN), Intracellular metal ion regulation and so on.</div></div>","PeriodicalId":51119,"journal":{"name":"Mathematical Biosciences","volume":"384 ","pages":"Article 109435"},"PeriodicalIF":1.9,"publicationDate":"2025-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143830343","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}

{"title":"Deciphering Akt activation: Insights from a mean-field model","authors":"Catheryn W. Gray,&nbsp;Adelle C.F. Coster","doi":"10.1016/j.mbs.2025.109434","DOIUrl":"10.1016/j.mbs.2025.109434","url":null,"abstract":"<div><div>Being at the right place at the right time is vital for any signalling system component. Akt/PKB is a well-known low-threshold switch in the mammalian insulin signalling pathway. The activation of Akt is essential for the uptake of glucose, however, data concerning this vital system is very sparse, particularly with regards to cellular location and activation state. Here we present a parsimonious mathematical model that captures the current experimental understanding of Akt dynamics. The system operates on two distinct timescales (signalling and physical transport), with the transportation of Akt constituting the rate-limiting step in most circumstances. The model outputs are consistent with observations of the steady state behaviour of the system and display the transient overshoot behaviour which is a necessary characteristic of the activation of Akt.</div></div>","PeriodicalId":51119,"journal":{"name":"Mathematical Biosciences","volume":"384 ","pages":"Article 109434"},"PeriodicalIF":1.9,"publicationDate":"2025-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143834243","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}

{"title":"Foraging dynamics in social insect colonies: Mechanisms of backward bifurcations and impacts of stochasticity","authors":"Tao Feng ,&nbsp;Yun Kang","doi":"10.1016/j.mbs.2025.109436","DOIUrl":"10.1016/j.mbs.2025.109436","url":null,"abstract":"<div><div>This investigation presents a two-dimensional collective foraging model alongside its stochastic counterpart, simplifying the previous more complex three-dimensional framework utilized to examine foraging behaviors within social insect colonies. We first conduct a thorough examination of the global dynamics of the deterministic model. The results show that the two-dimensional model exhibits equilibrium dynamics, with the possibility of coexistence between non-foraging and foraging equilibrium states. This finding highlights the parallelism between the two-dimensional model and the traditional three-dimensional framework. Following this, an extensive exploration into the long-term collective foraging dynamics within a stochastic environment is conducted, elucidating the interplay between stochasticity and the transitions across distinct stable foraging states. Additionally, the investigation assesses the risk of foraging cessation across varying initial worker populations, subsequently delineating foraging termination warning thresholds. The findings illuminate the multifaceted influence of environmental stochasticity on the collective foraging dynamics observed in harvester ant colonies. Grasping these dynamics furnishes valuable understanding of ecological resilience and the adaptive strategies deployed by collective entities in navigating environmental fluctuations.</div></div>","PeriodicalId":51119,"journal":{"name":"Mathematical Biosciences","volume":"384 ","pages":"Article 109436"},"PeriodicalIF":1.9,"publicationDate":"2025-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143830342","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}

{"title":"Adipocyte size distribution: Mathematical model of a tissue property","authors":"Aloïs Dauger ,&nbsp;Hedi Soula ,&nbsp;Chloe Audebert","doi":"10.1016/j.mbs.2025.109433","DOIUrl":"10.1016/j.mbs.2025.109433","url":null,"abstract":"<div><div>White adipose tissue is in charge of storing excess of energy in form of lipids. The main cells involved in the process – the adipocytes – adapt their sizes up to <span><math><mrow><mn>200</mn><mspace></mspace><mi>μ</mi><mi>m</mi></mrow></math></span> of diameter to accommodate the storage. In addition, their size distribution is bimodal. A previous mathematical model based on lipid fluxes provided size distribution bimodality. However, the variability within cell population was not fully explored. In the previous model, bimodality was considered a consequence of a bistable distribution of cell sizes at equilibrium: meaning that adipocytes had to have two stable sizes. In this study, we first provide a computational method to evaluate equilibria taking into account cells variability. Our results suggest that this variability is key to provide realistic distributions. In addition, we show that size distributions with a proportion of cell with bi-stable profile are not in good agreement with the measurements. We find that mono-stable (i.e. one equilibrium size) profile within the adipose tissue is enough to explain bimodality and to reproduce qualitatively size distribution data. We thus show that bimodality of adipose tissue size distribution does not arise directly from cellular bi-stability but rather from a tissue property.</div></div>","PeriodicalId":51119,"journal":{"name":"Mathematical Biosciences","volume":"384 ","pages":"Article 109433"},"PeriodicalIF":1.9,"publicationDate":"2025-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143842538","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}

{"title":"Characterizing symmetry transitions in systems with dynamic morphology","authors":"Maria-Veronica Ciocanel ,&nbsp;Punit Gandhi ,&nbsp;Karl Niklas ,&nbsp;Adriana T. Dawes","doi":"10.1016/j.mbs.2025.109431","DOIUrl":"10.1016/j.mbs.2025.109431","url":null,"abstract":"<div><div>The accurate quantification of symmetry is a key goal in biological inquiries because symmetry can affect biological performance and can reveal insights into development and evolutionary history. Recently, we proposed a versatile measure of symmetry, transformation information (<span><math><mi>TI</mi></math></span>), which provides an entropy-based measure of deviations from exact symmetry with respect to a parameterized family of transformations. Here we develop this measure further to quantify approximate symmetries and maximal symmetries represented by critical points in <span><math><mi>TI</mi></math></span> as a function of a transformation parameter. This framework allows us to characterize the evolution of symmetry by tracking qualitative changes with respect to these critical points. We apply <span><math><mi>TI</mi></math></span> to increasingly complex settings, from mathematically tractable probability distributions to differential equation models with emergent behaviors that are inspired by developmental biology and formulated in both static and growing domains. Our analysis of the qualitative changes in symmetry properties indicates a potential pathway toward a general mathematical framework for characterizing symmetry transitions akin to bifurcation theory for dynamical systems. The results reveal deep connections between observed symmetry transitions, subtle changes in morphology, and the underlying mechanisms that govern the dynamics of the system.</div></div>","PeriodicalId":51119,"journal":{"name":"Mathematical Biosciences","volume":"384 ","pages":"Article 109431"},"PeriodicalIF":1.9,"publicationDate":"2025-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143756705","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Testing-isolation interventions will likely be insufficient to contain future novel disease outbreaks","authors":"Jeffery Demers ,&nbsp;William F. Fagan ,&nbsp;Sriya Potluri ,&nbsp;Justin M. Calabrese","doi":"10.1016/j.mbs.2025.109432","DOIUrl":"10.1016/j.mbs.2025.109432","url":null,"abstract":"<div><div>Rapid identification and isolation of infected individuals with diagnostic testing plays a critical role in combating invasions of novel human pathogens. Unfortunately, unprepared health agencies may struggle to meet the massive testing capacity demands imposed by an outbreaking novel pathogen, potentially resulting in a failure of epidemic containment as occurred with COVID-19. Despite the critical importance of understanding the likelihood of such an outcome, it remains unclear how the particular characteristics of a novel disease will impact the magnitude of resource constraints on controllability. Specifically, is the failure of testing-isolation unique to COVID-19, or is this a likely outcome across the spectrum of disease traits that may constitute future epidemics? Here, using a generalized mathematical model parameterized for seven different human diseases and variants, we show that testing-isolation strategies will typically fail to contain epidemic outbreaks at practicably achievable testing capacities. From this analysis, we identify three key disease characteristics that govern controllability under resource constraints; the basic reproduction number, mean latent period, and non-symptomatic transmission index. Interactions among these characteristics play prominent roles in both explaining controllability differences among diseases and enhancing the efficacy of testing-isolation in combination with transmission-reduction measures. This study provides broad guidelines for managing controllability expectations during future novel disease invasions, describing which classes of diseases are most amenable to testing-isolation strategies alone and which will necessitate additional transmission-reduction measures like social distancing.</div></div>","PeriodicalId":51119,"journal":{"name":"Mathematical Biosciences","volume":"384 ","pages":"Article 109432"},"PeriodicalIF":1.9,"publicationDate":"2025-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143756729","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}

{"title":"Analyzing time activity curves from spatio-temporal tracer data to determine tracer transport velocity in plants","authors":"Hannah Lanzrath ,&nbsp;Eric von Lieres ,&nbsp;Ralf Metzner ,&nbsp;Gregor Huber","doi":"10.1016/j.mbs.2025.109430","DOIUrl":"10.1016/j.mbs.2025.109430","url":null,"abstract":"<div><div>Non-invasive methods utilizing tracers have a great potential to investigate carbon allocation in plants. Specifically, radioactive tracers, such as <span><math><mrow><msup><mrow></mrow><mrow><mn>11</mn></mrow></msup><mtext>C</mtext></mrow></math></span>, enable the monitoring of spatially localized transport processes on short time scales in living plants. Typically, such tracer transport experiments yield time activity curves (TACs) of tracer activity over time at various locations along a transport pathway. These TACs can exhibit different characteristic shapes that strongly depend on tracer transport dynamics, reflecting properties such as transport velocity, exchange with surrounding tissue, and tracer storage along the pathway. Various methods, either data-driven or model-based, exist to determine transport velocities from TACs. However, for some TAC shapes, the inferred carbon tracer velocity values can be inconsistent and greatly vary between analysis methods. In the present study, we review and evaluate different analysis methods for their suitability to reliably determine tracer transport velocities from typical TAC shapes. For this evaluation, we use both <em>in silico</em> generated and experimentally acquired TACs from positron emission tomography measurements on tomato, barley, and bean. We demonstrate that each of the compared methods can be suitable for specific TAC shapes while being less or not appropriate for others. In conclusion, we present a case-specific evaluation of methods as a reference for analyzing TACs from tracer transport experiments, which allows to ensure a robust and globally comparable determination of transport velocities.</div></div>","PeriodicalId":51119,"journal":{"name":"Mathematical Biosciences","volume":"383 ","pages":"Article 109430"},"PeriodicalIF":1.9,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143674702","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Random evolutionary dynamics in predator–prey systems yields large, clustered ecosystems","authors":"Christian H.S. Hamster ,&nbsp;Jorik Schaap ,&nbsp;Peter van Heijster ,&nbsp;Joshua A. Dijksman","doi":"10.1016/j.mbs.2025.109417","DOIUrl":"10.1016/j.mbs.2025.109417","url":null,"abstract":"<div><div>We study the effect of introducing new species through evolution into communities. We use the setting of predator–prey systems. Predator–prey dynamics is classically well modeled by Lotka–Volterra (LV) equations, also when multiple predator and prey species co-exist. We use a stochastic method to introduce new species in a two-trophic LV system. We find that introducing random evolving species leads to robust ecosystems in which large numbers of species coexist. Crucially, in these large ecosystems an emergent clustering of species is observed, tying functional differences to phylogenetic history.</div></div>","PeriodicalId":51119,"journal":{"name":"Mathematical Biosciences","volume":"383 ","pages":"Article 109417"},"PeriodicalIF":1.9,"publicationDate":"2025-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143672182","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Epidemic spreading on biological evolution networks","authors":"Zhong-Pan Cao,&nbsp;Jin-Xuan Yang,&nbsp;Ying Tan","doi":"10.1016/j.mbs.2025.109416","DOIUrl":"10.1016/j.mbs.2025.109416","url":null,"abstract":"<div><div>The spread of epidemics is closely related to network structure. In reality, network structure will change over time with the departure or employment of many individuals. Mathematical models can not only be used to simulate the evolution of networks, but also to better analyze the changes in the spread of epidemics. In the present work, we propose two mathematical models of evolution networks with the addition and deletion of nodes to analyze epidemic spread on homogeneous and heterogeneous networks. We discuss various factors affecting the spread of epidemics when the evolution network reaches a steady state, including the number of new nodes and their initial degree, the deletion rate of nodes, and so on. The results show that in homogeneous networks, the epidemic threshold first increases and then decreases, while in heterogeneous networks, the epidemic threshold increases or decreases under certain conditions. It provides many measures to improve the epidemic threshold and slow down the spread of epidemics.</div></div>","PeriodicalId":51119,"journal":{"name":"Mathematical Biosciences","volume":"383 ","pages":"Article 109416"},"PeriodicalIF":1.9,"publicationDate":"2025-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143672156","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}