Mathematical Biosciences最新文献_第3页

Threshold dynamics of a Wolbachia-driven mosquito suppression model on two patches 沃尔巴克氏体驱动的两个斑块上蚊虫抑制模型的阈值动态。

IF 1.9 4区数学

Mathematical Biosciences Pub Date : 2025-06-29 DOI: 10.1016/j.mbs.2025.109495

Xiaoke Ma, Ying Su

{"title":"Threshold dynamics of a Wolbachia-driven mosquito suppression model on two patches","authors":"Xiaoke Ma, Ying Su","doi":"10.1016/j.mbs.2025.109495","DOIUrl":"10.1016/j.mbs.2025.109495","url":null,"abstract":"<div><div>The release of <em>Wolbachia</em>-infected mosquitoes is a promising and biologically safe measure for controlling wild mosquitoes. Numerous studies have been devoted to finding optimal control strategies using mathematical tools. However, the effects of dispersal of uninfected and infected mosquitoes remain poorly understood. To characterize the spatial discretization of release sites, we investigate a two-patch mosquito suppression model with time delay and impulsive release. Specifically, we assume that the waiting period between two consecutive releases is equal to the sexual lifespan of infected males. We confirm the well-posedness and monotonicity of the solution and explore the existence and stability of equilibria. By some technical skills, sufficient conditions for the bistable dynamics are provided. Then, the existence of the unstable separatrix is established by some sharp estimates when choosing constant functions as initial values. More interestingly, the monotonicity of this separatrix in the release number is proved, implying the existence of an optimal release strategy. We further find that uniform release on two patches is more effective than single-patch release. Additionally, the higher the cytoplasmic incompatibility intensity, the more likely wild mosquitoes are to be suppressed.</div></div>","PeriodicalId":51119,"journal":{"name":"Mathematical Biosciences","volume":"387 ","pages":"Article 109495"},"PeriodicalIF":1.9,"publicationDate":"2025-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144532102","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

Assessing the influence of HIV on the spread of Mpox disease 评估艾滋病毒对痘病传播的影响

IF 1.9 4区数学

Mathematical Biosciences Pub Date : 2025-06-29 DOI: 10.1016/j.mbs.2025.109499

Arsène Jaurès Ouemba Tassé , Yibetal Terefe , Jean Lubuma

{"title":"Assessing the influence of HIV on the spread of Mpox disease","authors":"Arsène Jaurès Ouemba Tassé , Yibetal Terefe , Jean Lubuma","doi":"10.1016/j.mbs.2025.109499","DOIUrl":"10.1016/j.mbs.2025.109499","url":null,"abstract":"<div><div>Mpox, originating primarily in African rodents, has led to human outbreaks over recent years. This study presents a mathematical model for Mpox, distinguishing between individuals with and without HIV who are susceptible. We explore scenarios involving both rodent-to-human transmission and those without it. In the absence of this transmission route, the model undergoes a backward bifurcation, suggesting that reducing the basic reproduction number below one would not eliminate the disease unless further control strategies are used. With the account of rodent-to-human transmission, if Mpox is endemic in the rodent population, a unique interior equilibrium, globally asymptotically stable, exists, requiring targeted interventions like quarantine or vaccination for people with HIV (PWH) for disease control. Model validation using USA case data (May 2022–July 2024) shows that both human-to-human and rodent-to-human transmissions prevail in the population, but the disease is not endemic. Projections indicate that the outbreak will be overcome by May 2027, with a total of 35,811 cases. We design a nonstandard finite difference (NSFD) scheme which is dynamically consistent with respect to the qualitative properties of the continuous model. Numerical simulations demonstrate that reducing the recruitment rate of PWH is essential, and rodent-to-human transmission is identified as highly influential in increasing the number of Mpox cases.</div></div>","PeriodicalId":51119,"journal":{"name":"Mathematical Biosciences","volume":"387 ","pages":"Article 109499"},"PeriodicalIF":1.9,"publicationDate":"2025-06-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144517846","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

GMFOLD: Subgraph matching for high-throughput DNA-aptamer secondary structure classification and machine learning interpretability GMFOLD：用于高通量dna适体二级结构分类和机器学习可解释性的子图匹配。

IF 1.9 4区数学

Mathematical Biosciences Pub Date : 2025-06-27 DOI: 10.1016/j.mbs.2025.109485

Paolo Climaco , Noelle M. Mitchell , Matthew J. Tyler , Kyungae Yang , Anne M. Andrews , Andrea L. Bertozzi

{"title":"GMFOLD: Subgraph matching for high-throughput DNA-aptamer secondary structure classification and machine learning interpretability","authors":"Paolo Climaco , Noelle M. Mitchell , Matthew J. Tyler , Kyungae Yang , Anne M. Andrews , Andrea L. Bertozzi","doi":"10.1016/j.mbs.2025.109485","DOIUrl":"10.1016/j.mbs.2025.109485","url":null,"abstract":"<div><div>Aptamers are oligonucleotide receptors that bind to their targets with high affinity. Here, we consider aptamers comprised of single-stranded DNA that undergo target-binding-induced conformational changes, giving rise to unique secondary and tertiary structures. Given a specific aptamer primary sequence, there are well-established computational tools (notably mfold) to predict the secondary structure via free energy minimization algorithms. While mfold generates secondary structures for individual sequences, there is a need for a high-throughput process whereby thousands of DNA structures can be predicted in real-time for use in an interactive setting, when combined with aptamer selections that generate candidate pools that are too large to be experimentally interrogated. We developed a new Python code for high-throughput aptamer secondary structure determination (GMfold). GMfold uses subgraph matching methods to group aptamer candidates by secondary structure similarities. We also improve an open-source code, SeqFold, to incorporate subgraph matching concepts. We represent each secondary structure as a lowest-energy bipartite subgraph matching of the DNA graph to itself. These new tools enable thousands of DNA sequences to be compared based on their secondary structures, using machine-learning algorithms. This process is advantageous when analyzing sequences that arise from aptamer selections via systematic evolution of ligands by exponential enrichment (SELEX). This work is a building block for future machine-learning-informed DNA-aptamer selection processes to identify aptamers with improved target affinity and selectivity and advance aptamer biosensors and therapeutics.</div></div>","PeriodicalId":51119,"journal":{"name":"Mathematical Biosciences","volume":"387 ","pages":"Article 109485"},"PeriodicalIF":1.9,"publicationDate":"2025-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144532101","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

Bifurcation analysis of tumor-immune dynamics under the dual Allee effects 双Allee效应下肿瘤免疫动力学的分岔分析。

IF 1.9 4区数学

Mathematical Biosciences Pub Date : 2025-06-23 DOI: 10.1016/j.mbs.2025.109483

Eymard Hernandez-Lopez, Xiunan Wang

引用次数: 0

Recurrent patterns of disease spread post the acute phase of a pandemic: Insights from a coupled system of a differential equation for disease transmission and a delayed algebraic equation for behavioral adaptation 大流行急性期后疾病传播的复发模式：来自疾病传播微分方程和行为适应延迟代数方程耦合系统的见解

IF 1.9 4区数学

Mathematical Biosciences Pub Date : 2025-06-21 DOI: 10.1016/j.mbs.2025.109480

Tianyu Cheng, Jianhong Wu

{"title":"Recurrent patterns of disease spread post the acute phase of a pandemic: Insights from a coupled system of a differential equation for disease transmission and a delayed algebraic equation for behavioral adaptation","authors":"Tianyu Cheng, Jianhong Wu","doi":"10.1016/j.mbs.2025.109480","DOIUrl":"10.1016/j.mbs.2025.109480","url":null,"abstract":"<div><div>We introduce a coupled system of a disease transmission differential equation and a behavioral adaptation algebraic renewal equation to understand the mechanisms of nonlinear oscillations post-acute phase of a pandemic. This extends the Zhang–Scarabel–Murty–Wu model, which was formulated and analyzed to describe multi-wave patterns observed at the early stage during the acute phase of the COVID-19 pandemic. Our extension involves the depletion of susceptible population due to infection and contains a nonlinear disease transmission term to reflect the recovery and temporal immunity in the infected population past the acute phase of the pandemic. Examining whether and how incorporating this depletion of susceptible population impacts interwoven disease transmission dynamics and behavioral adaptation is the objective of our current research. We introduce some prototypical risk aversion functions to characterize behavioral responses to perceived risks and show how the risk aversion behaviors and the logistic delay in implementation of behavioral adaptation combined contribute to a dynamic equilibrium state described by a periodic oscillatory wave. We also link the period between two consecutive peaks to basic epidemic parameters, the community flexibility to behavioral change, and the population’s tolerance to perceived risks.</div></div>","PeriodicalId":51119,"journal":{"name":"Mathematical Biosciences","volume":"387 ","pages":"Article 109480"},"PeriodicalIF":1.9,"publicationDate":"2025-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144478349","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

Dynamic properties of Lotka–Volterra systems corresponding to the colonization model Lotka-Volterra系统对应殖民化模型的动态特性。

IF 1.9 4区数学

Mathematical Biosciences Pub Date : 2025-06-21 DOI: 10.1016/j.mbs.2025.109500

Atsushi Yamauchi

{"title":"Dynamic properties of Lotka–Volterra systems corresponding to the colonization model","authors":"Atsushi Yamauchi","doi":"10.1016/j.mbs.2025.109500","DOIUrl":"10.1016/j.mbs.2025.109500","url":null,"abstract":"<div><div>The colonization model, also known as the Levins model, has been developed to understand the mechanisms that drive species coexistence under interspecific competition. Previous simulation studies have shown that the dynamic properties of the model significantly depend on the encounter mode between propagules and colonization sites. Perfect mass action encounters result in convergence towards equilibrium, while perfect ratio-dependent encounters lead to multiple continuously transient trajectories that depend on the initial condition. In the present study, I investigate the properties of the dynamics by transforming the colonization model into a Lotka-Volterra model. I show that the eigenvalues of the Jacobian matrix indicate stability of the equilibrium under perfect mass action encounters, while the Lyapunov function shows the existence of an infinite number of continuously transient trajectories under perfect ratio-dependent encounters. These results highlight new properties of Lotka-Volterra systems and the colonization model, and provide new insights into the mechanisms and dynamic processes involved in the coexistence of multiple species.</div></div>","PeriodicalId":51119,"journal":{"name":"Mathematical Biosciences","volume":"387 ","pages":"Article 109500"},"PeriodicalIF":1.9,"publicationDate":"2025-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144478348","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

Estimation of time-varying recovery and death rates from epidemiological data: A new approach 从流行病学数据估计时变的恢复率和死亡率：一种新方法。

IF 1.9 4区数学

Mathematical Biosciences Pub Date : 2025-06-09 DOI: 10.1016/j.mbs.2025.109479

Samiran Ghosh , Malay Banerjee , Subhra Sankar Dhar , Siuli Mukhopadhyay

{"title":"Estimation of time-varying recovery and death rates from epidemiological data: A new approach","authors":"Samiran Ghosh , Malay Banerjee , Subhra Sankar Dhar , Siuli Mukhopadhyay","doi":"10.1016/j.mbs.2025.109479","DOIUrl":"10.1016/j.mbs.2025.109479","url":null,"abstract":"<div><div>The time-to-recovery or time-to-death for various infectious diseases can vary significantly among individuals, influenced by several factors such as demographic differences, immune strength, medical history, age, pre-existing conditions, and infection severity. To capture these variations, time-since-infection dependent recovery and death rates offer a detailed description of the epidemic. However, obtaining individual-level data to estimate these rates is challenging, while aggregate epidemiological data (such as the number of new infections, number of active cases, number of new recoveries, and number of new deaths) are more readily available. In this article, a new methodology is proposed to estimate time-since-infection dependent recovery and death rates using easily available data sources, accommodating irregular data collection timings reflective of real-world reporting practices. The Nadaraya–Watson estimator is utilized to derive the number of new infections. This model improves the accuracy of epidemic progression descriptions and provides clear insights into recovery and death distributions. The proposed methodology is validated using COVID-19 data and its general applicability is demonstrated by applying it to some other diseases like measles and typhoid.</div></div>","PeriodicalId":51119,"journal":{"name":"Mathematical Biosciences","volume":"387 ","pages":"Article 109479"},"PeriodicalIF":1.9,"publicationDate":"2025-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144277096","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 study of the spread and blocking in inflammatory bowel disease 炎症性肠病扩散和阻塞的数学研究。

IF 1.9 4区数学

Mathematical Biosciences Pub Date : 2025-06-07 DOI: 10.1016/j.mbs.2025.109481

Saoussen Latrach , Eric Ogier-Denis , Nicolas Vauchelet , Hatem Zaag

引用次数: 0

Stochastic model of siRNA endosomal escape mediated by fusogenic peptides 融合肽介导siRNA内体逃逸的随机模型。

IF 1.9 4区数学

Mathematical Biosciences Pub Date : 2025-06-05 DOI: 10.1016/j.mbs.2025.109476

Nisha Yadav , Jessica Boulos , Angela Alexander-Bryant , Keisha Cook

{"title":"Stochastic model of siRNA endosomal escape mediated by fusogenic peptides","authors":"Nisha Yadav , Jessica Boulos , Angela Alexander-Bryant , Keisha Cook","doi":"10.1016/j.mbs.2025.109476","DOIUrl":"10.1016/j.mbs.2025.109476","url":null,"abstract":"<div><div>Gene silencing via small interfering RNA (siRNA) represents a transformative tool in cancer therapy, offering specificity and reduced off-target effects compared to conventional treatments. A crucial step in siRNA-based therapies is endosomal escape, the release of siRNA from endosomes into the cytoplasm. Quantifying endosomal escape is challenging due to the dynamic nature of the process and limitations in imaging and analytical techniques. Traditional methods often rely on fluorescence intensity measurements or manual image processing, which are time-intensive and fail to capture continuous dynamics. This paper presents a novel computational framework that integrates automated image processing to analyze time-lapse fluorescent microscopy data of endosomal escape, hierarchical Bayesian inference, and stochastic simulations. Our method employs image segmentation techniques such as binary masks, Gaussian filters, and multichannel color quantification to extract precise spatial and temporal data from microscopy images. Using a hierarchical Bayesian approach, we estimate the parameters of a compartmental model that describes endosomal escape dynamics, accounting for variability over time. These parameters inform a Gillespie stochastic simulation algorithm, ensuring realistic simulations of siRNA release events over time. By combining these techniques, our framework provides a scalable and reproducible method for quantifying endosomal escape. The model captures uncertainty and variability in parameter estimation, and endosomal escape dynamics. Additionally, synthetic data generation allows researchers to validate experimental findings and explore alternative conditions without extensive laboratory work. This integrated approach not only improves the accuracy of endosomal escape quantification but also provides predictive insights for optimizing siRNA delivery systems and advancing gene therapy research.</div></div>","PeriodicalId":51119,"journal":{"name":"Mathematical Biosciences","volume":"387 ","pages":"Article 109476"},"PeriodicalIF":1.9,"publicationDate":"2025-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144251660","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

Patient-specific prediction of glioblastoma growth via reduced order modeling and neural networks 通过降阶模型和神经网络对胶质母细胞瘤生长的患者特异性预测

IF 1.9 4区数学

Mathematical Biosciences Pub Date : 2025-06-03 DOI: 10.1016/j.mbs.2025.109468

D. Cerrone , D. Riccobelli , S. Gazzoni , P. Vitullo , F. Ballarin , J. Falco , F. Acerbi , A. Manzoni , P. Zunino , P. Ciarletta

{"title":"Patient-specific prediction of glioblastoma growth via reduced order modeling and neural networks","authors":"D. Cerrone , D. Riccobelli , S. Gazzoni , P. Vitullo , F. Ballarin , J. Falco , F. Acerbi , A. Manzoni , P. Zunino , P. Ciarletta","doi":"10.1016/j.mbs.2025.109468","DOIUrl":"10.1016/j.mbs.2025.109468","url":null,"abstract":"<div><div>Glioblastoma is among the most aggressive brain tumors in adults, characterized by patient-specific invasion patterns driven by the underlying brain microstructure. In this work, we present a proof-of-concept for a mathematical model of GBL growth, enabling real-time prediction and patient-specific parameter identification from longitudinal neuroimaging data.</div><div>The framework exploits a diffuse-interface mathematical model to describe the tumor evolution and a reduced-order modeling strategy, relying on proper orthogonal decomposition, trained on synthetic data derived from patient-specific brain anatomies reconstructed from magnetic resonance imaging and diffusion tensor imaging. A neural network surrogate learns the inverse mapping from tumor evolution to model parameters, achieving significant computational speed-up while preserving high accuracy.</div><div>To ensure robustness and interpretability, we perform both global and local sensitivity analyses, identifying the key biophysical parameters governing tumor dynamics and assessing the stability of the inverse problem solution. These results establish a methodological foundation for future clinical deployment of patient-specific digital twins in neuro-oncology.</div></div>","PeriodicalId":51119,"journal":{"name":"Mathematical Biosciences","volume":"387 ","pages":"Article 109468"},"PeriodicalIF":1.9,"publicationDate":"2025-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144223529","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