Journal of Theoretical Biology最新文献

{"title":"Many-strategy games in groups with relatives and the evolution of coordinated cooperation","authors":"Nadiah P. Kristensen ,&nbsp;Ryan A. Chisholm ,&nbsp;Hisashi Ohtsuki","doi":"10.1016/j.jtbi.2025.112089","DOIUrl":"10.1016/j.jtbi.2025.112089","url":null,"abstract":"<div><div>Humans often cooperate in groups with friends and family members with varying degrees of genetic relatedness. Past kin selection can also be relevant to interactions between strangers, explaining how the cooperation first arose in the ancestral population. However, modelling the effects of relatedness is difficult when the benefits of cooperation scale nonlinearly with the number of cooperators (e.g., economies of scale). Here, we present a direct fitness method for rigorously accounting for kin selection in <span><math><mi>n</mi></math></span>-player interactions with <span><math><mi>m</mi></math></span> discrete strategies, where a genetically homophilic group-formation model is used to calculate the necessary higher-order relatedness coefficients. Our approach allows us to properly account for non-additive fitness effects between relatives (synergy). Analytical expressions for dynamics are obtained, and they can be solved numerically for modestly sized groups and numbers of strategies. We illustrate with an example where group members can verbally agree (cheap talk) to contribute to a public good with a sigmoidal benefit function, and we find that such coordinated cooperation is favoured by kin selection. As interactions switched from family to strangers, in order for coordinated cooperation to persist and for the population to resist invasion by liars, either some level of homophily must be maintained or following through on the agreement must be in the self-interests of contributors. Our approach is useful for scenarios where fitness effects are non-additive and the strategies are best modelled in a discrete way, such as behaviours that require a cognitive ‘leap’ of insight into the situation (e.g., shared intentionality, punishment).</div></div>","PeriodicalId":54763,"journal":{"name":"Journal of Theoretical Biology","volume":"605 ","pages":"Article 112089"},"PeriodicalIF":1.9,"publicationDate":"2025-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143725288","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":"Two-lane track geometry facilitates coordination of collective cell migration.","authors":"Alistair Falconer, Zhiyong Li, Dietmar Oelz","doi":"10.1016/j.jtbi.2025.112105","DOIUrl":"https://doi.org/10.1016/j.jtbi.2025.112105","url":null,"abstract":"<p><p>Collective cell migration is an essential biological process in the formation and maintenance of tissues, yet its regulation is still not well understood. We formulate a 2D particle model for the collective cell migration in a confluent monolayer of epithelial cells within constrained annular geometries. Key elements of the model are directional persistence modelled by a mutual reinforcement between cell polarity and velocity, as well as a process to determine neighbourhoods of cells through adjacency in the associated Voronoi tessellation. We test this model using recently published experimental results concerning the onset of large-scale global migratory behaviour in annular geometries. Our simulations predict that tracks which are narrow enough to prevent the presence of neighbouring cells lateral to the direction of motion lead to less efficient organisation of globally coordinated migration.</p>","PeriodicalId":54763,"journal":{"name":"Journal of Theoretical Biology","volume":" ","pages":"112105"},"PeriodicalIF":1.9,"publicationDate":"2025-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143733230","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":"Plant–pollinator interaction model with separate pollen and nectar dynamics","authors":"Tomás A. Revilla","doi":"10.1016/j.jtbi.2025.112096","DOIUrl":"10.1016/j.jtbi.2025.112096","url":null,"abstract":"<div><div>The mutualism between plants and pollinators involves the exchange between plant resources and pollen dispersal services among con-specific plants. Since many pollinators are generalist foragers, the quality of pollination is compromised by inter-specific pollen transfer (IPT). This article proposes a mechanistic approach to model plant–pollinator interactions that considers the dynamics of pollen pick-up and its delivery to con-specific and hetero-specific targets, in parallel but separated from the consumption dynamics of plant rewards by the pollinators. This mechanism can model the interference effect caused by IPT on plant fitness, and predicts saturating effects on the quantity and efficiency of pollination. By coupling the mechanism with population dynamics, the resulting model demonstrates how plant–pollinator associations can shift between net mutualism and parasitism, depending on the ecological context and species traits.</div></div>","PeriodicalId":54763,"journal":{"name":"Journal of Theoretical Biology","volume":"606 ","pages":"Article 112096"},"PeriodicalIF":1.9,"publicationDate":"2025-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143733229","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":"Interrelating neuronal morphology by coincidence similarity networks","authors":"Alexandre Benatti ,&nbsp;Henrique Ferraz De Arruda ,&nbsp;Luciano Da Fontoura Costa","doi":"10.1016/j.jtbi.2025.112104","DOIUrl":"10.1016/j.jtbi.2025.112104","url":null,"abstract":"<div><div>The study of neuronal morphology presents potential not only for identifying possible relationship with neuronal dynamics, but also as a means to characterize and classify types of neuronal cells and compare them among species, organs, and conditions. In the present work, we approach this problem by using the concept of coincidence similarity index, considering a methodology for mapping datasets into similarity networks. The adopted similarity presents some specific interesting properties, including more strict comparisons. A set of 20 morphological features has been considered, and coincidence similarity networks estimated respectively to 735 considered neuronal cells from 8 groups of Drosophila melanogaster.</div></div>","PeriodicalId":54763,"journal":{"name":"Journal of Theoretical Biology","volume":"606 ","pages":"Article 112104"},"PeriodicalIF":1.9,"publicationDate":"2025-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143733228","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":"Developing cholera outbreak forecasting through qualitative dynamics: Insights into Malawi case study","authors":"Adrita Ghosh ,&nbsp;Parthasakha Das ,&nbsp;Tanujit Chakraborty ,&nbsp;Pritha Das ,&nbsp;Dibakar Ghosh","doi":"10.1016/j.jtbi.2025.112097","DOIUrl":"10.1016/j.jtbi.2025.112097","url":null,"abstract":"<div><div>Cholera, an acute diarrheal disease, is a serious concern in developing and underdeveloped areas. A qualitative understanding of cholera epidemics aims to foresee transmission patterns based on reported data and mechanistic models. The mechanistic model is a crucial tool for capturing the dynamics of disease transmission and population spread. However, using real-time cholera cases is essential for forecasting the transmission trend. This prospective study seeks to furnish insights into transmission trends through qualitative dynamics followed by machine learning-based forecasting. The Monte Carlo Markov Chain approach is employed to calibrate the proposed mechanistic model. We identify critical parameters that illustrate the disease’s dynamics using partial rank correlation coefficient-based sensitivity analysis. The basic reproduction number as a crucial threshold measures asymptotic dynamics. Furthermore, forward bifurcation directs the stability of the infection state, and Hopf bifurcation suggests that trends in transmission may become unpredictable as societal disinfection rates rise. Further, we develop epidemic-informed machine learning models by incorporating mechanistic cholera dynamics into autoregressive integrated moving averages and autoregressive neural networks. We forecast short-term future cholera cases in Malawi by implementing the proposed epidemic-informed machine learning models to support this. We assert that integrating temporal dynamics into the machine learning models can enhance the capabilities of cholera forecasting models. The execution of this mechanism can significantly influence future trends in cholera transmission. This evolving approach can also be beneficial for policymakers to interpret and respond to potential disease systems. Moreover, our methodology is replicable and adaptable, encouraging future research on disease dynamics.</div></div>","PeriodicalId":54763,"journal":{"name":"Journal of Theoretical Biology","volume":"605 ","pages":"Article 112097"},"PeriodicalIF":1.9,"publicationDate":"2025-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143694664","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":"An optimal network that promotes the spread of an advantageous variant in an SIR epidemic","authors":"Samuel Lopez ,&nbsp;Natalia L. Komarova","doi":"10.1016/j.jtbi.2025.112095","DOIUrl":"10.1016/j.jtbi.2025.112095","url":null,"abstract":"<div><div>In the course of epidemics, the pathogen may mutate to acquire a higher fitness. At the same time, such a mutant is automatically in an unfavorable position because the resident virus has a head start in accessing the pool of susceptible individuals. We considered a class of tunable small-world networks, where a parameter, <span><math><mi>p</mi></math></span> (the rewiring probability), characterizes the prevalence of non-local connections, and we asked, whether the underlying network can influence the fate of a mutant virus. Under an SIR model, we considered two measures of mutant success: the expected height of the peak of mutant infected individuals, and the total number of recovered from mutant individuals at the end of the epidemic. Using these measures, we have found the existence of an optimal (for an advantageous mutant virus) rewiring probability that promotes a larger infected maximum and a larger total recovered population corresponding to the advantageous pathogen strain. This optimal rewiring probability decreases as mean degree and the infectivity of the wild type are increased, and it increases with the mutant advantage. The non-monotonic behavior of the advantageous mutant as a function of rewiring probability may shed light into some of the complex patterns in the size of mutant peaks experienced by different countries during the COVID-19 pandemic.</div></div>","PeriodicalId":54763,"journal":{"name":"Journal of Theoretical Biology","volume":"605 ","pages":"Article 112095"},"PeriodicalIF":1.9,"publicationDate":"2025-03-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143665383","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":"A model of tubulin removal and exchange caused by kinesin motor walking on microtubule lattices","authors":"Ping Xie","doi":"10.1016/j.jtbi.2025.112088","DOIUrl":"10.1016/j.jtbi.2025.112088","url":null,"abstract":"<div><div>The kinesin motor walking on microtubule lattices can cause disassembly of GDP-tubulins, generating defects, and repair the defects by incorporating GTP-tubulins. To explore the underlying mechanism, a model is proposed here. On the basis of the model, the dynamics of the defect generation, defect repair and tubulin exchange induced by the kinesin motor is studied theoretically. The theoretical results explain well the available experimental data. Moreover, predicted results are provided.</div></div>","PeriodicalId":54763,"journal":{"name":"Journal of Theoretical Biology","volume":"605 ","pages":"Article 112088"},"PeriodicalIF":1.9,"publicationDate":"2025-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143644146","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":"The spatial aggregation of phytophagous insects driven by the evolution of preference for plant chemicals","authors":"Haruna Ohsaki ,&nbsp;Akira Yamawo ,&nbsp;Yuuya Tachiki","doi":"10.1016/j.jtbi.2025.112094","DOIUrl":"10.1016/j.jtbi.2025.112094","url":null,"abstract":"<div><div>Ecologists have shown considerable interest in the spatial patterns of organism distribution and the processes responsible for their formation and maintenance. The phytophagous insects typically use chemicals in plants as host-finding cues. Because nonvolatile chemicals remain near the source, the spatial structure of plant community determines the local distribution of insects. In addition, the plant chemical accumulation due to plant–plant interaction also influences the distribution of insects. In <em>Rumex obtusifolius</em>, for example, the production of phenolics is mediated by conspecific interaction. <em>Rumex</em> plants with high phenolic concentrations are preferred by the leaf beetle <em>Gastrophysa atrocyanea</em>, resulting in its spatial aggregation. Although this preference of beetles for nonvolatile chemicals should be beneficial in finding host plants, there is also a cost in terms of intraspecific competition among the beetles due to aggregation on certain chemical-rich hosts. To investigate the evolutionary significance of preference for nonvolatile chemicals and the ecological consequence of spatial distribution in leaf beetles, we constructed a mathematical model for the joint evolution of two preferences for plant size and chemical condition. In the model, beetles choose a resource based on the size and chemical concentrations of plants and are exposed to resource competition. Host plants accumulate the chemicals when they interact with neighboring conspecifics, and hence the level of chemical accumulation varies depending on the species composition and spatial distribution of the plant community. As a result, beetles became more sensitive to chemicals when the host species was rare and sparsely distributed in the community. The evolution of high chemical preference caused the aggregation of beetles and hence population size declined. We proposed a potential mechanism that underlies aggregated distribution in phytophagous insects, driven by the evolution of chemical preferences in response to plant community structure.</div></div>","PeriodicalId":54763,"journal":{"name":"Journal of Theoretical Biology","volume":"605 ","pages":"Article 112094"},"PeriodicalIF":1.9,"publicationDate":"2025-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143639853","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":"Absorbing Markov chain model of PrEP drug adherence to estimate adherence decay rate and probability distribution in clinical trials","authors":"Renee Dale ,&nbsp;Hongyu He ,&nbsp;Yingqing Chen","doi":"10.1016/j.jtbi.2025.112086","DOIUrl":"10.1016/j.jtbi.2025.112086","url":null,"abstract":"<div><div>Pre-exposure prophylaxis (PrEP) is increasingly used to prevent the transmission of H.I.V. in at-risk populations. However, PrEP users may discontinue use of the medicine due to side effects, lower perceived risk, or other reasons. The usage metrics of 594 individuals was tracked over 350 days using the Wisepill electronic monitoring system. We model the PrEP drug adherence level using an absorbing Markov chain with a unique absorbing state. The transition matrix <span><math><mi>T</mi></math></span> obtained from the Wisepill data will have a trivial eigenvector (eigendistribution) associated with the first (i.e., largest) eigenvalue 1. The 2nd eigenvalue(s) then become important in determining the asymptotic behavior of the Markov chain, dictating how fast the Markov chain <em>decays</em> to the absorbing state. Under a fairly general assumption, we prove that the second positive eigenvalue is unique and the corresponding eigenvector will have nonnegative entries with exceptions at absorbing states. In addition, we define the asymptotic half life of the absorbing Markov chain directly from the 2nd eigenvalue. We then determine the 2nd eigenvalue of <span><math><mi>T</mi></math></span> and the asymptotic half life of the Markov chain, which turns out to be very close to the real half life of the Markov chain. Finally, we interpret the 2nd eigenvector as the relative probability distribution of <span><math><msub><mi>X</mi><mi>∞</mi></msub></math></span> with respect to the decay rate of the 2nd eigenvalue. By applying these methods to the Wisepill data, we estimate the half-life of population adherence to be 46 weeks. The bi-weekly decay rate observed in these data from 90 to 100 % adherence is 3 %. This work produces an estimate at which adherence falls over time, given no external intervention is applied. These results suggest an eigenvector-based approach to estimate adherence trends, as well as the timing of interventions to improve adherence.</div></div>","PeriodicalId":54763,"journal":{"name":"Journal of Theoretical Biology","volume":"604 ","pages":"Article 112086"},"PeriodicalIF":1.9,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143611685","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":"Branching architecture affects genetic diversity within an individual tree","authors":"Sou Tomimoto ,&nbsp;Yoh Iwasa ,&nbsp;Akiko Satake","doi":"10.1016/j.jtbi.2025.112093","DOIUrl":"10.1016/j.jtbi.2025.112093","url":null,"abstract":"<div><div>While a tree grows over many years, somatic mutations accumulate and form genetic variation among branches within an individual. Trees can transmit such mutations to subsequent generations, potentially enhancing the genetic diversity of the population. We study a mathematical model to understand the relationship between within-individual genetic variation and branching architecture. We generate branching architecture by repeatedly adding two new branches (main and lateral daughter branches) to each terminal branch (mother branch). The architecture is characterized by two key parameters: main-lateral ratio (ML) and daughter-mother ratio (DM). During branch elongation, somatic mutations accumulate in the stem cells of a shoot apical meristem (SAM) at the tip of each branch. In branching, all the stem cells are passed on from the mother to the main daughter branch, but only one stem cell is chosen for the lateral daughter branch. We evaluate genetic variation by <span><math><mover><mrow><mi>Z</mi></mrow><mrow><mo>¯</mo></mrow></mover></math></span>, the mean genetic differences between all pairs of branches of a tree, and examine how <span><math><mover><mrow><mi>Z</mi></mrow><mrow><mo>¯</mo></mrow></mover></math></span> varies with DM and ML while keeping the total branch length constant. As a result, (1) <span><math><mover><mrow><mi>Z</mi></mrow><mrow><mo>¯</mo></mrow></mover></math></span> increases monotonically with ML; (2) <span><math><mover><mrow><mi>Z</mi></mrow><mrow><mo>¯</mo></mrow></mover></math></span> attains the maximum for an intermediate DM, when stem cells in a SAM are genetically homogeneous; (3) <span><math><mover><mrow><mi>Z</mi></mrow><mrow><mo>¯</mo></mrow></mover></math></span> decreases monotonically with DM when stem cells are heterogeneous. The effect of branching architecture varies significantly depending on the genetic heterogeneity within a SAM, which results from the behavior of stem cells during growth. Our study sheds light on the overlooked role of branching architecture in storing genetic diversity.</div></div>","PeriodicalId":54763,"journal":{"name":"Journal of Theoretical Biology","volume":"605 ","pages":"Article 112093"},"PeriodicalIF":1.9,"publicationDate":"2025-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143634975","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}