Journal of Theoretical Biology最新文献

{"title":"Estimating the contribution of age-structure to the COVID-19 epidemic in England","authors":"Robert Hinch ,&nbsp;Jasmina Panovska-Griffiths ,&nbsp;Christophe Fraser","doi":"10.1016/j.jtbi.2025.112177","DOIUrl":"10.1016/j.jtbi.2025.112177","url":null,"abstract":"<div><div>The spread of epidemics in populations is often inhomogeneous, consequently infection incidence varies between sub-populations. Age-structure is often particularly important in the dynamics of epidemics, due to the contact patterns between individuals of different ages. Public health interventions are often targeted at specific age-groups, therefore analysing the age-structure of transmission patterns is essential to evaluate the efficacy of these interventions. We develop a Bayesian model to estimate the contribution of different age-groups to the reproduction number (R) and to new infections for COVID-19 in England throughout 2021, using the ONS Infection Survey. We model a dynamic next-generation matrix in a novel way by splitting it into a static survey-derived social-contact matrix, multiplied by a low-rank dynamic matrix. We show that whilst R was typically highest for school-age children (5–11y and 12–17y) and lowest for the elderly (60y+), the former typically rose during term-time and fell during the school-holidays. The dynamics for young adults (18–29y) were particularly interesting, which increased relative to older adults in late-spring 2021 following the re-opening of entertainment venues. The R peaked for young adults in July 2021 coinciding with the period of the Euros football tournament, before rapidly dropping as the national vaccination program reached this group in August 2021. Our model is an important tool that can estimate R and attribute new infections by the infector’s age, thus identifying core groups which sustain the epidemic and informing the design of targeted interventions.</div></div>","PeriodicalId":54763,"journal":{"name":"Journal of Theoretical Biology","volume":"611 ","pages":"Article 112177"},"PeriodicalIF":1.9,"publicationDate":"2025-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144259336","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":"Development of a mathematical model of the innate immune response to inhaled toxicants","authors":"Aamy Bakry ,&nbsp;Emma Brashear ,&nbsp;Jacob Brashear ,&nbsp;Shannon Z. Jones ,&nbsp;Marcella M. Torres","doi":"10.1016/j.jtbi.2025.112159","DOIUrl":"10.1016/j.jtbi.2025.112159","url":null,"abstract":"<div><div>Lung inflammation due to inhalation of toxicants such as wood smoke is a feature of many respiratory diseases, including asthma, chronic obstructive pulmonary disease (COPD), interstitial lung diseases, and respiratory infections. We present a mathematical model of immune cell and cytokine interactions in the presence of inhaled toxicants. The model, focusing on interactions between epithelial cells, macrophages, and pro- and anti-inflammatory cytokines, is constructed by developing several submodels calibrated to fit both experimental in vitro data and our understanding of the transition from type I to type II immune responses. The model’s predictions align with experimental observations, showing an initial pro-inflammatory (type I) response dominated by M1 macrophages transitioning to an anti-inflammatory/repair (type II) response characterized by M2 macrophages. Simulations of different exposure scenarios demonstrate that although a single exposure elicits a self-limiting inflammatory response, repeated exposures lead to persistent inflammation and elevated M2:M1 ratios consistent with chronic lung conditions. The model provides a novel mathematical framework that captures complex immune system transitions through a minimal set of equations, demonstrating how relatively simple mathematical structures can effectively represent sophisticated biological behavior while maintaining analytical tractability. Through stability analysis and careful parameter selection, we show that the model exhibits biologically relevant steady states that align with experimental observations. This framework enables the exploration of various exposure patterns and potential interventions on inflammatory dynamics, serving as a foundation for the future development of a virtual tissue model of macrophage–epithelial cell interactions.</div></div>","PeriodicalId":54763,"journal":{"name":"Journal of Theoretical Biology","volume":"611 ","pages":"Article 112159"},"PeriodicalIF":1.9,"publicationDate":"2025-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144250935","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":"Scalable inference of transcriptional variability with BASiCS","authors":"Alan O'Callaghan ,&nbsp;Catalina A. Vallejos","doi":"10.1016/j.jtbi.2025.112157","DOIUrl":"10.1016/j.jtbi.2025.112157","url":null,"abstract":"<div><div>BASiCS (Bayesian Analysis of Single-Cell Sequencing data) is an integrated Bayesian hierarchical model for the analysis of single-cell RNA sequencing data. BASiCS performs simultaneous data normalization and quantification of technical noise, and enables analysis of mean expression and expression variability within or across cell populations. We extend BASiCS with a divide and conquer inference scheme to enable scalable Bayesian inference for large datasets. We compare the performance of the divide and conquer approach to standard Markov Chain Monte Carlo (MCMC) and variational inference methods (ADVI) in terms of accuracy and scalability. Our results demonstrate that the divide and conquer approach enables large-scale scRNA-seq analysis, providing accurate and efficient inference while maintaining the interpretability and flexibility of the BASiCS framework.</div></div>","PeriodicalId":54763,"journal":{"name":"Journal of Theoretical Biology","volume":"611 ","pages":"Article 112157"},"PeriodicalIF":1.9,"publicationDate":"2025-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144220801","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":"Rankings of tuberculosis antibiotic treatment regimens are sensitive to spatial scale, detection limit, and initial host bacterial burden","authors":"Christian T. Michael ,&nbsp;Maral Budak ,&nbsp;Pauline Maiello ,&nbsp;Kara Kracinovsky ,&nbsp;Mark Rodgers ,&nbsp;Jaime Tomko ,&nbsp;Philana Ling Lin ,&nbsp;JoAnne Flynn ,&nbsp;Jennifer J. Linderman ,&nbsp;Denise Kirschner","doi":"10.1016/j.jtbi.2025.112176","DOIUrl":"10.1016/j.jtbi.2025.112176","url":null,"abstract":"<div><div>Pulmonary infection after inhalation of Mycobacterium tuberculosis (Mtb) causes tuberculosis (TB). TB presents with lung granulomas − complex spheroidal structures composed of immune cells and bacteria. Granulomas often have centralized caseum (necrotic tissue) where mycobacteria are quarantined, complicating and prolonging multi-antibiotic regimens. Determining which antibiotic regimens are optimal for reducing treatment time and toxicity is a goal of recent TB eradication campaigns. Clinical trials are expensive and challenging, making it difficult to untangle which host-pathogen interactions drive heterogeneous infection and treatment outcomes observed both within and between hosts. To determine responses to antibiotic regimens, we simulate treatments in <em>HostSim</em>, our whole-host mechanistic, multi-scale computational model of Mtb-infection. <em>HostSim</em> tracks dynamics of pulmonary Mtb-infection over molecular, cellular, tissue, organ, and whole-host scales. We create a heterogenous virtual cohort, comprising distinct hosts, for virtual clinical trials. We represent drug treatments by newly-integrating pharmacokinetics / pharmacodynamics into <em>HostSim</em>, simulating treatment with commonly-prescribed TB antibiotic regimens (e.g., HRZE or BPaL). Our approach allows us to identify both (1) which hosts/granulomas improve with treatment, and (2) which mechanisms influence outcome heterogeneity. By tracking experimental and clinical measurements, we virtually recreate several drug rankings from literature. We find that many methods of ranking treatment efficacy are strongly influenced by the ‘definition of improvement’ used and, in some cases, the detection threshold of CFU. Our work suggests that a study’s reported optimal treatment may depend on its experimental design, including initial disease state and bacterial burden measures, possibly explaining seemingly-contradictory findings from prior studies.</div></div>","PeriodicalId":54763,"journal":{"name":"Journal of Theoretical Biology","volume":"611 ","pages":"Article 112176"},"PeriodicalIF":1.9,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144217548","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":"Data-informed model reduction for inference and prediction from non-identifiable models","authors":"Matthew J. Simpson","doi":"10.1016/j.jtbi.2025.112155","DOIUrl":"10.1016/j.jtbi.2025.112155","url":null,"abstract":"<div><div>Many mathematical models in the field of theoretical biology involve challenges relating to parameter identifiability. Non-identifiability implies that different combinations of parameter values lead to indistinguishable solutions of the mathematical model. This means that it is difficult, and sometimes impossible, to explain the mechanistic origin of observations using a non-identifiable mathematical model. A standard approach to deal with structurally non-identifiable models is to use reparameterisation, which typically focuses on the structure of the mathematical model without accounting for the impact of noisy, finite data. We present and explore a simple computational approach for model reduction, via likelihood reparameterisation, that can be applied to both structurally non-identifiable and practically non-identifiable problems. We construct simplified, identifiable mathematical models that enable model-based predictions for a range of continuum models based on different classes of commonly-used differential equations. Through a series of computational experiments, we illustrate how to deal with a range of noise models that relate the solution of the mathematical model with noisy observations. A key focus is to illustrate how computationally efficient model-based predictions can be made from reduced models.</div></div>","PeriodicalId":54763,"journal":{"name":"Journal of Theoretical Biology","volume":"611 ","pages":"Article 112155"},"PeriodicalIF":1.9,"publicationDate":"2025-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144210282","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 effect of outcome choice on vaccine dose allocation: a modelling study","authors":"Eleanor Burch,&nbsp;Hannah Christensen,&nbsp;Ellen Brooks-Pollock","doi":"10.1016/j.jtbi.2025.112156","DOIUrl":"10.1016/j.jtbi.2025.112156","url":null,"abstract":"<div><h3>Background</h3><div>In the early stages of a pandemic, vaccine rollout strategies are generally based on reducing the burden on healthcare services and/or deaths. Quality-adjusted life-years are often not taken into account. With COVID-19 as an example, we used mathematical modelling to investigate how the optimal strategy for allocating vaccines is affected when life-years are the focus rather than deaths, specifically whether single-dose or two-dose prioritisation is more effective.</div></div><div><h3>Methods</h3><div>We extended a previously published model to estimate the number of life-years saved and deaths averted following a one-dose or two-dose COVID-19 vaccination schedule in England at the beginning of the vaccine rollout. We included updated estimates for the risk of mortality due to COVID-19 and vaccine uptake levels for different population groups.</div></div><div><h3>Results</h3><div>The vaccine dose allocation strategy considered optimal changed depending on the outcome of interest. For lower numbers of available doses (between three and ten million), it was more beneficial to prioritise the one-dose strategy, regardless of the outcome. As the number of available doses increased above ten million, the two-dose strategy became optimal at a point determined by the vaccine effectiveness and the chosen outcome measure.</div></div><div><h3>Conclusions</h3><div>Rather than focussing on deaths, which is the approach taken in many existing COVID-19 models, targeting life-years can lead to different vaccination policies being considered optimal. We argue that – alongside infections, hospitalisations and deaths – life-years lost should be regarded as a primary measure of disease impact in the development of future vaccine programmes.</div></div>","PeriodicalId":54763,"journal":{"name":"Journal of Theoretical Biology","volume":"610 ","pages":"Article 112156"},"PeriodicalIF":1.9,"publicationDate":"2025-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144180615","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":"Contact data and SARS-CoV-2: Retrospective analysis of the estimated impact of the first UK lockdown","authors":"Joel Kandiah ,&nbsp;Edwin van Leeuwen ,&nbsp;Paul J. Birrell ,&nbsp;Daniela De Angelis","doi":"10.1016/j.jtbi.2025.112158","DOIUrl":"10.1016/j.jtbi.2025.112158","url":null,"abstract":"<div><div>To combat the spread of SARS-CoV-2 in March 2020 the United Kingdom (UK) announced a series of restrictions on social interaction, culminating with the introduction of lockdown measures. Estimation of lockdown effectiveness using pandemic models relied on the availability of contact data and choices on how to structure models accordingly.</div><div>We revisit the Cambridge/Public Health England real-time model (RTM), which was routinely implemented during the pandemic to monitor its development and produce short-term projections. To derive contact matrices, Google Mobility weekly contact data and school attendance data from the Department for Education were combined with information from the POLYMOD study and the UK Time Use Survey. These matrices were combined with susceptibility and transmissibility parameters to estimate effective reproduction numbers, which were taken as indicators of transmission trends.</div><div>We explore alternative formulations of the RTM, which make fuller use of the available contact data, and assess the impact of each formulation on the conclusions of lockdown effectiveness. Results show that the estimated impact of the lockdown remains unchanged, but also uncover previously uncaptured early epidemic dynamics. This highlights the importance of the timely availability of contact data in understanding transmission dynamics during the early stages of an epidemic and assessing the effectiveness of interventions.</div></div>","PeriodicalId":54763,"journal":{"name":"Journal of Theoretical Biology","volume":"610 ","pages":"Article 112158"},"PeriodicalIF":1.9,"publicationDate":"2025-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144151804","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":"Heat delivery accompanying pulsed field ablation","authors":"Angiolo Farina ,&nbsp;Antonio Fasano ,&nbsp;Massimo Grimaldi ,&nbsp;Fabio Rosso","doi":"10.1016/j.jtbi.2025.112145","DOIUrl":"10.1016/j.jtbi.2025.112145","url":null,"abstract":"<div><div>Pulsed Field Ablation (PFA) is a technique to achieve pulmonary vein isolation, alternative to the traditional thermal ablation procedures. Instead of delivering or subtracting heat, PFA uses rapid pulses of a high intensity electric field, inducing cells electroporation. PFA is usually claimed not to influence the temperature in the surroundings of the ablation site. Nevertheless, in some case a non-negligible increase of the patient’s luminal esophageal temperature has been observed. Here we set up a mathematical model to provide a theoretical basis to the latter observation, considering a worst case scenario.</div></div>","PeriodicalId":54763,"journal":{"name":"Journal of Theoretical Biology","volume":"610 ","pages":"Article 112145"},"PeriodicalIF":1.9,"publicationDate":"2025-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144144428","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":"Hybrid of glioma growth model and deformable image registration for longitudinal brain MRIs synthesis","authors":"Fulian Zhong ,&nbsp;Yujian Liu ,&nbsp;Jianquan Zhong ,&nbsp;Ling He ,&nbsp;Zhonglan Tang ,&nbsp;Jing Zhang","doi":"10.1016/j.jtbi.2025.112147","DOIUrl":"10.1016/j.jtbi.2025.112147","url":null,"abstract":"<div><div>Modeling and visualization of glioma growth could assist in cancer diagnosis, tumor progression prediction, and clinical treatment outcome improvement. However, most studies either failed to make patient-specific predictions or could only display information about tumor size and shape, lacking the capability to characterize the impact of tumor growth on surrounding tissues. In this study, a method (HybrSyn) combining tumor growth model and deformable image registration technique for synthesizing MRIs at arbitrary time point after the detection time has been proposed. Through the tumor growth model, tumor growth process for consecutive time point has been predicted according to the characteristics of tumor cell diffusion and proliferation within the brain. The glioma deformable image registration model was employed to obtain the deformation fields between the tumors at detection time and simulations at subsequent time points. These fields were then mapped to the patient’s initial MRI scans to generate the synthetic MRIs corresponding to that time points. To validate the HybrSyn, various experiments were conducted on the BraTS19 and the internal dataset collected from Zigong First People’s Hospital. The quantitative results demonstrated a structural similarity of 80.93% between the synthesized MRIs and the patients’ MRI scans. The qualitative results indicated that the HybrSyn could effectively capture changes during tumor progression and provide a global view. From the clinical point of view, synthesized longitudinal brain MRIs could potentially aid in presenting the impact of glioma growth on surrounding functional areas, and identifying target regions for personalized treatment planning.</div></div>","PeriodicalId":54763,"journal":{"name":"Journal of Theoretical Biology","volume":"610 ","pages":"Article 112147"},"PeriodicalIF":1.9,"publicationDate":"2025-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144103245","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":"Crick’s “Frozen accident theory” of the genetic code explored by Ising models","authors":"Reijer Lenstra ,&nbsp;Antonia Claudio Lenstra ,&nbsp;Marco V. José","doi":"10.1016/j.jtbi.2025.112146","DOIUrl":"10.1016/j.jtbi.2025.112146","url":null,"abstract":"<div><div>Francis Crick proposed that the almost universal genetic code could be nothing more than a ‘frozen accident’. The Ising model, widely used in statistical mechanics, is used to explore patterns which could achieve a phase transition mimicking the frozen accident. Codons are considered as nodes and amino acids as spins. Monte Carlo simulations of the 64-node genetic code models are carried out. Anti-ferromagnetic interactions or a combination of ferro and anti-ferromagnetic interactions can lead to stable, regular patterns resembling the genetic code. It is indeed found that the 64-node Ising system exhibits critical slowing down dynamics, compatible with a freezing process. These models aim to simulate the formation of patterns similar to the genetic code through physical freezing processes, providing insights into potential mechanisms and processes that may have contributed to the formation and evolution of the genetic code.</div></div>","PeriodicalId":54763,"journal":{"name":"Journal of Theoretical Biology","volume":"609 ","pages":"Article 112146"},"PeriodicalIF":1.9,"publicationDate":"2025-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144103243","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}