BULLETIN OF MATHEMATICAL BIOLOGY数学生物学通报
BULLETIN OF MATHEMATICAL BIOLOGY(英文缩写 B MATH BIOL),ISSN 0092-8240,eISSN 1522-9602,中文译名:数学生物学通报 是一本学术期刊。本页汇总该期刊的最新影响因子、分区信息以及最新收录于 PubMed 的文献,帮助您快速了解期刊全貌。
发文量统计区间：2025-10-01 至 2026-09-30，按本站收录文献的发表日期统计。
期刊介绍
历年影响因子趋势
| JCR 数据年份 | 影响因子 | JCR 分区 |
|---|---|---|
| 2021 | 3.871 | Q2 |
| 2022 | 3.500 | Q2 |
| 2023 | 2.000 | Q2 |
| 2024 | 2.200 | Q2 |
| 2025 | 2.300 | Q2 |
BULLETIN OF MATHEMATICAL BIOLOGY 最新收录文献
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1. Oxygenation and Spatial Heterogeneity Shape Radiotherapy Protocol Ranking Through Phenotypic Adaptation.
PMID:日期:2026-10-03Tumor response to radiotherapy is strongly influenced by oxygen availability and phenotypic heterogeneity, yet their combined impact on the relative performance of fractionation schedules remains unclear. Here, we develop a mathematical model that integrates spatial oxygen dynamics with continuous phenotypic adaptation to hypoxia and radiation, and use it to systematically compare radiotherapy protocols under a common normal-tissue toxicity constraint. Under spatially uniform oxygenation, we find that alternative fractionation schedules provide little improvement over standard-of-care protocols in normoxic conditions. Under moderate hypoxia, however, a distinct class of protracted schedules with longer inter-fraction intervals substantially increases time-to-progression, in some cases by up to twofold. This regime-dependent benefit is consistent with a shift in the balance between reoxygenation and selection for resistant phenotypes. When oxygen delivery is spatially heterogeneous, treatment outcomes depend strongly on the geometric organization of oxygen sources. Even with identical total oxygen supply, different spatial configurations lead to large variability in time-to-progression and can alter the relative ranking of radiotherapy protocols. These results show that radiotherapy effectiveness is not an intrinsic property of a treatment schedule alone, but emerges from its interaction with tumor microenvironmental structure and evolutionary dynamics. Incorporating both spatial heterogeneity and phenotypic adaptation may therefore be important for the consistent evaluation and design of fractionation strategies in heterogeneous tumors.
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2. Stacked Waves and Qualitative Analysis of an Oncolytic Virus-Immune Model.
PMID:日期:2026-10-03Oncolytic virotherapy (OVT) represents a promising therapeutic method for cancer treatment. It involves the introduction of oncolytic viruses into the patient, which are engineered to selectively target and lyse tumor cells. Based on previous mathematical modeling of oncolytic viruses, we consider a mathematical model that describes the intricate interactions between the oncolytic virus, cancer cell populations, and the immune system. Our study includes a detailed qualitative and quantitative analysis of the model to explain why, despite their promise, oncolytic viruses alone rarely lead to complete and lasting regression of established tumors in vivo. We use parameter sensitivity analysis to support our findings. Furthermore, we consider the spatial version of the model in the form of a system of reaction-diffusion equations. A travelling wave analysis shows an unexpected phenomenon. The solution components do not necessarily evolve into a single traveling front; rather, they develop into stacked fronts, where each front propagates at a different speed. We give explicit formulas for these different invasion speeds, confirm those through numerical simulations, and discuss their significance for OVT.
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3. An Immuno-Epidemiological Model of Foot-and-Mouth Disease (FMD) in the African Buffalo Population with Carrier Transmission.
PMID:日期:2026-10-01In this paper, we present a novel immuno-epidemiological model, linking host-pathogen interactions at within-host and population scales for foot-and-mouth disease virus (FMDV) in its natural host, African buffalo. Endemic persistence of FMD in buffalo populations is facilitated by chronic infections in carrier hosts: Upon exposure to the virus, buffalo become acutely infected, followed by either viral clearance and recovery with immunity, or persistent infection for several months. In our model, we divide the infectious population based upon these two stages, acute and carrier infection, so that we can dynamically capture the immunological characteristics of both phases of the disease to better understand the carriers' role in disease transmission. We first define the epidemiological basic reproduction number, , depending on the viral-immune kinetics from acute and carrier infected hosts. Then, we show that is a threshold condition for the local stability of the disease free equilibrium and for the existence of the endemic equilibrium. We also analytically establish that the system always displays forward bifurcation with respect to between-host epidemic parameters. Later, by using a sensitivity analysis (SA) approach developed for multi-scale models, we assess the impact of the acute infection and carrier phase immunological parameters on . Interestingly, our numerical results show that the viral and immunological parameters from a carrier infected host and the susceptible individual recruitment rates play significant roles in disease persistence, which are consistent with experimental and field studies.
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4. Mathematical Modeling of the Complement System: a Scoping Review.
PMID:日期:2026-10-01The complement system is a potent arm of the immune system, linking the adaptive and innate immune systems, and affecting many facets of human pathophysiology. Recent advances in the development of complement-specific drugs in several rare diseases have opened the gateways to apply complement interventions toward a broader array of pathologies. However, this goal remains elusive due to the complexity and the multifaceted roles of the complement system. Mechanistic mathematical models can provide an effective tool to integrate the different mechanisms, features, and feedback loops into a framework that allows the simulation of complement dynamics under different conditions and the prediction of the effect of interventions. In this scoping review, we provide an overview of current mathematical models of the complement system, open problems related to complement biology, and discuss future work on how mechanistic mathematical modeling of the complement system can potentially alleviate some of the challenges in complement biology.
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5. Intestinal Alkaline Phosphatase Interaction Gut Model.
PMID:日期:2026-09-28High fat Western diet (WD) is known to alter the composition of gut microbiota causing the release of lipopolysaccharide (LPS) (Cani et al. 2007). LPS is a TLR4 ligand, produced by Gram-negative bacteria, and is a potent inducer of various inflammatory cytokines. Inflammation in the gut can promote leaky gut syndrome which results in the translocation of LPS from the gut to circulation. The resulting leakage activates pro-inflammatory cytokines and alters macrophage polarization (Pelegrin and Surprenant 2009). This systemic inflammation can aggravate various diseases such as diabetes, atherosclerosis and chronic liver disease. Intestinal Alkaline Phosphatase (IAP) dephosphorylates LPS and renders it inactive, subsequently reducing leaky gut phenomenon. Informed by mouse model data, we developed an ordinary differential equation model to dynamically model the effect of diet on circulating LPS levels. The model allows for better understanding of systemic risk factors and for exploration of potential treatment using IAP-based interventions.
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6. Impulsive Release Strategies for Wolbachia-Infected Mosquitoes Under Temperature-Induced Infection Loss.
PMID:日期:2026-09-28The release of Wolbachia-infected mosquitoes is a promising strategy for controlling Aedes aegypti populations, although high-temperature exposure may temporarily reduce infection levels and compromise long-term persistence. We propose a population-dynamics model based on impulsive differential equations that incorporates cytoplasmic incompatibility, periodic mosquito releases, and temperature-driven infection loss. Analytical results establish fundamental qualitative properties of the continuous and impulsive models, derive conditions for the existence and stability of periodic solutions, and provide an explicit release threshold for the successful establishment and long-term persistence of the infected population. Numerical simulations validate the theoretical results and compare the performance of the wMelPop, wMel, and wAlbB strains under different thermal scenarios, highlighting the influence of strain-specific fitness costs and thermal tolerance. Additional simulations investigate temperature-dependent demographic variation and imperfect maternal transmission, extending the analysis beyond the assumptions of the analytical framework. The proposed approach provides a tractable mathematical framework for analyzing and designing impulsive Wolbachia release strategies under environmentally driven infection loss.
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7. Modelling Between-Cell-Type Heterogeneity in Within-Host Influenza Virus Infection.
PMID:日期:2026-09-28Cell tropism, or the preference of a virus for particular cell types, has major implications for viral transmission, pathogenesis, and evolution. Historically, changes in cell tropism for particular viruses have been observed to correlate to changes in viral fitness, in the form of increased within-host replication and increased transmission between hosts. This is illustrated in the context of influenza, where adaptation to infect cells expressing 2-6 linked sialic acid receptors enhances human-to-human transmissibility. Target cell populations differ not only in abundance but also in intrinsic properties such as susceptibility, viral production, and interferon responses, rendering the relationship between tropism and viral fitness multi-faceted and complex. Understanding how different cell tropisms quantitatively change fitness remains an important open question in virology and quantitative biology. Here, we present a within-host mathematical model that incorporates distinct target cell types differing in key properties, and examine how cell tropism affects fitness-related summary statistics such as peak viral load, infection duration, or total virus produced. Our analysis reveals that tradeoffs may arise when cell types differ by multiple characteristics. We further demonstrate that model parameters describing heterogeneity between cell types can be more accurately inferred when cell type proportions are measured alongside viral load. Our findings provide a framework for assessing the links between viral evolution, cell tropism, and within-host fitness, and motivate the design of experiments to collect quantitative data on between-cell-type heterogeneity.
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8. New Game-Theoretical Approach to Marketing Cooperatives in Fisheries.
PMID:日期:2026-09-26While most game-theoretical models in fisheries deal with the conflict of exploitation of the same resource, unlike these models, the present paper is dedicated to marketing conflicts, always accounting for the underlying population dynamics. In the context of marketing cooperatives in fisheries, three models are combined: the classical fishing effort model based on logistic population dynamics, a game-theoretical model of the conflict between a marketing cooperative and its members, and a Cournot-type oligopoly market model. The latter, in particular, means that the market price is determined by the total supply on the market. The fishers selling fish outside the marketing cooperative are punished. In the present paper, within this complex model, based on Pareto optimality, a particular cooperative solution, the so-called nearly ideal solution, is introduced and compared with the previously studied, special non-cooperative solution, also called attractive solution. In fact, for the respective repeated games, counting with the underlying fishing effort dynamics, the two solution types are compared. Results show that the cooperative solution yields higher total payoffs if at least one member fishes, one member is unfaithful, and a specific pricing condition holds. Additionally, increasing the punishment parameter stabilizes the cooperative by ensuring members contribute their catch, while higher fishing efforts increase catches without depleting stocks but require stricter penalties to prevent free-market diversion.
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9. {"_":"Multiple Disease-Free Equilibria: Toward a Vector Structure of .","mml:math":[{"xmlns:mml":["http://www.w3.org/1998/Math/MathML"],"mml:msub":[{"mml:mi":["R"],"mml:mn":["0"]}]}]}
PMID:日期:2026-09-25Traditional epidemiological models rely on the basic reproductive number, , as a single threshold quantity to determine whether a disease will persist or die out. However, increased structural complexity in models can lead to the emergence of multiple disease-free equilibria (DFEs). To illustrate this dynamic diversity, we analyze a compartmental model based on the Health Belief Model, where risk perception, social imitation, and behavioral fatigue among susceptible individuals generate the coexistence of multiple DFEs. This case study exposes the limitations of a single scalar threshold and motivates the introduction of a methodological approach: a vector-valued reproductive number and three-dimensional bifurcation diagrams. The analysis reveals complex scenarios including multistability, regions with specific dynamic behaviors, and outcomes conditioned by the initial population distribution. This heuristic approach suggests an extension of the classical concept of and offers a new analytical perspective that lays the groundwork for studying disease dynamics in populations with complex structure.
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10. Bayesian Parameter Estimation and Stochastic Extinction Analysis in a Seasonal Bubonic Plague Transmission Model.
PMID:日期:2026-09-24Mathematical models of plague dynamics provide insight into zoonotic transmission processes and epidemic persistence but often neglect stochastic effects and seasonal variability. In this study, we examine how seasonal variability influences zoonotic disease transmission through a rat-flea-human plague model. Periodic environmental forcing modulates rat abundance, flea survival, and biting activity, generating time-dependent rates that capture realistic ecological seasonality. To represent demographic randomness, we formulate a continuous-time Markov chain (CTMC) model and apply a multi-type branching process approximation near the disease-free equilibrium (DFE) to derive approximate disease extinction probabilities using probability generating functions (PGFs) and the backward Kolmogorov differential equation (BKDE). Our results show that random fluctuations can prevent an epidemic outbreak even when the seasonal reproduction number satisfies . We also quantify the spillover probability arising from a single infectious flea, demonstrating that seasonal forcing significantly alters outbreak risk. Along with this, an expression for time to extinction is also derived. To ensure biological understanding, we estimate model parameters from historical data using a Bayesian Markov chain Monte Carlo (MCMC) approach implemented via the Delayed Rejection Adaptive Metropolis (DRAM) algorithm. Through this analysis, we highlight the critical role of seasonality in shaping outbreak risk and demonstrate the limitations of relying solely on deterministic models.