{"title":"The impact of contact-network structure on important epidemiological quantities of infectious disease transmission and the identification of the extremes.","authors":"Demetris Avraam, Christoforos Hadjichrysanthou","doi":"10.1016/j.jtbi.2024.112010","DOIUrl":"10.1016/j.jtbi.2024.112010","url":null,"abstract":"<p><p>An individual-based stochastic model was developed to simulate the spread of an infectious disease in an SEIR-type system on all possible contact-networks of size between six and nine nodes. We assessed systematically the impact of the change in the population contact structure on four important epidemiological quantities: i) the epidemic duration, ii) the maximum number of infected individuals at a time point during the epidemic, iii) the time at which the maximum number of infected individuals is reached, and iv) the total number of individuals that have been infected during the epidemic. We considered the potential relationship of these quantities as the network changes and identified the networks that maximise and minimise each of these in the case of an epidemic outbreak. Chain-like networks minimise the peak and final epidemic size, but the disease spread is slow on such contact structures which leads to the maximisation of the epidemic duration. Star-like networks maximise the time to the peak whereas highly connected networks lead to faster disease transmission, and higher peak and final epidemic size. While the pairwise relationship of most of the quantities becomes almost linear, or inverse linear, as the network connectivity increases and approaches the complete network, the relationships are non-linear towards networks of low connectivity. In particular, the pairwise relationship between the final epidemic size and other quantities is changed in a 'bow-shaped' manner. There is a strong inverse linear relationship between epidemic duration and peak epidemic size with increasing network connectivity. The (inverse) linear relationships between quantities are more pronounced in cases of high disease transmissibility. All the values of the quantities change in a non-linear way with the increase of network connectivity and are characterised by high variability between networks of the same degree. The variability decreases as network connectivity increases.</p>","PeriodicalId":54763,"journal":{"name":"Journal of Theoretical Biology","volume":" ","pages":"112010"},"PeriodicalIF":1.9,"publicationDate":"2024-12-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142792936","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":"Kinetics, thresholds, and a comparison of mechanisms underlying systemic infection by Listeria monocytogenes.","authors":"Tristen M Jackson","doi":"10.1016/j.jtbi.2024.112009","DOIUrl":"10.1016/j.jtbi.2024.112009","url":null,"abstract":"<p><p>Studies on the system-scale pathogenesis of Listeria monocytogenes infection have classically focused on its ability to colonize in the intestines following an exposure event. However, despite this, many of the most dangerous complications arising from L. monocytogenes infection are observed days, weeks, or months after exposure, resulting indirectly from bacteria escaping this intestinal colonization hub and invading other organs. Over time, findings of various individual phenomena observed during systemic infection have accumulated, including a shift away from the principal route of intestinal dissemination, delays in bacterial colonization of the central nervous system, differing bacterial flux rates across organs, and multi-stability of bacterial population levels. To further our quantitative understanding of foodborne bacterial infection dynamics, a compartmental model of systemic infection that synthesizes these findings is proposed. Under parameterization to infection in BALB/c mice, the model is used to show a substantial decrease in bacterial populations resulting from dissemination through the mesenteric lymph nodes, as compared to the portal vein, when controlling for the number of bacteria passing through each route. Due to the compartmental nature of this model, we anticipate that this result may be paralleled in other microbes which make use of these pathways to escape the intestinal environment. Additionally, we predict thresholds for intestinal dissemination along each of these routes, which must be surpassed to induce systemic infection, and describe how these thresholds change over time. Supplementarily, logistic curves are fitted to synthetic data as a means of robustly quantifying the dose-response relationship beyond the intestinal barrier.</p>","PeriodicalId":54763,"journal":{"name":"Journal of Theoretical Biology","volume":" ","pages":"112009"},"PeriodicalIF":1.9,"publicationDate":"2024-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142792873","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}
Miranda Harkess, Sudha Kumari, Trilochan Bagarti, Niraj Kumar
{"title":"HIV transactivation: Stochastic modeling for studying the effects of BET inhibitors on the modulation of P-TEFb levels.","authors":"Miranda Harkess, Sudha Kumari, Trilochan Bagarti, Niraj Kumar","doi":"10.1016/j.jtbi.2024.112011","DOIUrl":"10.1016/j.jtbi.2024.112011","url":null,"abstract":"<p><p>Latency is the major obstacle in eradicating HIV from infected patients. Recent studies have shown that BET protein inhibitors can successfully reverse this latency by inhibiting the binding of BET proteins with positive cellular cofactor P-TEFb. Thus, availability of P-TEFbs plays an important role in HIV transactivation. However, in cells of our immune system which are primarily infected by the virus, number of P-TEFb is very low and is considered as one of the factors in inducing viral latency. At such small numbers of P-TEFb, the internal fluctuations can have a decisive role in the cell fate decision and fluctuations in the P-TEFb levels can switch the HIV to either a state of active replication or to a state of latency. Aimed at quantitative understanding of how BET inhibitors affect the statistics of P-TEFb level, we develop a coarse-grained stochastic model. However, the interaction between P-TEFb and BET proteins makes the problem analytically challenging. To address the nonlinearity arising due to such interactions, we use Langevin equation based approach to study the statistics of steady-state P-TEFb levels and explore the variations of some of the important quantities such as noise and fano factor associated with P-TEFb as well as correlations between BET and P-TEFb levels with model parameters. The analytic results derived exhibit that these quantities, in general, show non-monotonic response with respect to the parameters of the model. The results derived will be helpful in estimating the model parameters as well in identifying the pathways that can be intervened for effective HIV transactivation.</p>","PeriodicalId":54763,"journal":{"name":"Journal of Theoretical Biology","volume":" ","pages":"112011"},"PeriodicalIF":1.9,"publicationDate":"2024-12-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142792912","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 hybrid approach to study and forecast climate-sensitive norovirus infections in the USA","authors":"Juping Ji , Shohel Ahmed , Hao Wang","doi":"10.1016/j.jtbi.2024.112007","DOIUrl":"10.1016/j.jtbi.2024.112007","url":null,"abstract":"<div><div>Norovirus, responsible for acute gastroenteritis and foodborne diseases in the United States, is influenced significantly by environmental factors. This study employs a hybrid approach to develop a foodborne disease model that incorporates indirect incidence to examine the correlation between norovirus outbreaks and environmental conditions, specifically focusing on the impact of temperature and humidity on virus transmission. By analyzing weekly average climate data and confirmed case data from four United States regions (Southern, Northeastern, Midwestern, and Western), we assess the mortality rates and estimate transmission rates using the inverse method. Our numerical results confirm that norovirus outbreaks predominantly occur in colder months. However, higher temperatures or increased humidity during warmer months appear to mitigate the spread of the virus. Utilizing climate data, this study also forecasts transmission rates and infection cases up to eight weeks in advance using a generalized boosting machine learning model.</div></div>","PeriodicalId":54763,"journal":{"name":"Journal of Theoretical Biology","volume":"598 ","pages":"Article 112007"},"PeriodicalIF":1.9,"publicationDate":"2024-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142747094","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}
Li Li , Na Zheng , Chen Liu , Zhen Wang , Zhen Jin
{"title":"Optimal control of vaccination for an epidemic model with standard incidence rate","authors":"Li Li , Na Zheng , Chen Liu , Zhen Wang , Zhen Jin","doi":"10.1016/j.jtbi.2024.111993","DOIUrl":"10.1016/j.jtbi.2024.111993","url":null,"abstract":"<div><div>A critical challenge for diseases spread is the development of effective prevention and control measures while minimizing costs, representing the foremost priority. Unfortunately, research in this crucial area remains inadequately explored. Consequently, this paper addresses the issue by leveraging an SI reaction–diffusion epidemic model incorporating a logistic birth rate and standard incidence rate. Employing vaccination as a control variable and integrating sparse optimal control theory, the study elucidates the achievement of epidemic prevention and control through the optimization of resource allocation, emphasizing a perspective rooted in pattern structure transformation. On the one hand, we theoretically prove the existence of the optimal solutions, first-order necessary optimality conditions, and the sparsity properties. On the other hand, we use numerical simulations to verify the rationality of the control method and the effectiveness of the control strategy from three aspects of control effect, control error and control cost. In addition, tailored targeting options are proposed based on the economic status of each region, specifying the required inoculum amount for each moment. Ultimately, the study demonstrates the effectiveness of input vaccination in controlling epidemics in a majority of areas. In summary, this work offers crucial insights into the prevention and control of a non-quasimonotonic reaction–diffusion epidemic model.</div></div>","PeriodicalId":54763,"journal":{"name":"Journal of Theoretical Biology","volume":"598 ","pages":"Article 111993"},"PeriodicalIF":1.9,"publicationDate":"2024-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142741484","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":"Optimisation of gene expression noise for cellular persistence against lethal events","authors":"Pavol Bokes , Abhyudai Singh","doi":"10.1016/j.jtbi.2024.111996","DOIUrl":"10.1016/j.jtbi.2024.111996","url":null,"abstract":"<div><div>Bacterial cell persistence, crucial for survival under adverse conditions like antibiotic exposure, is intrinsically linked to stochastic fluctuations in gene expression. Certain genes, while inhibiting growth under normal circumstances, confer tolerance to antibiotics at elevated expression levels. The occurrence of antibiotic events lead to instantaneous cellular responses with varied survival probabilities correlated with gene expression levels. Notably, cells with lower protein concentrations face higher mortality rates. This study aims to elucidate an optimal strategy for protein expression conducive to cellular survival. Through comprehensive mathematical analysis, we determine the optimal burst size and frequency that maximise cell proliferation. Furthermore, we explore how the optimal expression distribution changes as the cost of protein expression to growth escalates. Our model reveals a hysteresis phenomenon, characterised by discontinuous transitions between deterministic and stochastic optima. Intriguingly, stochastic optima possess a noise floor, representing the minimal level of fluctuations essential for optimal cellular resilience.</div></div>","PeriodicalId":54763,"journal":{"name":"Journal of Theoretical Biology","volume":"598 ","pages":"Article 111996"},"PeriodicalIF":1.9,"publicationDate":"2024-11-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142741485","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}
Matthew Nicol , Julian D.J. Sng , Yanshan Zhu , Sissy Therese Sonnleitner , Kirsty R. Short , Meagan Carney
{"title":"An analytical, numerical and experimental study of in-vitro SARS-CoV-2 evolution in Vero B4 cells","authors":"Matthew Nicol , Julian D.J. Sng , Yanshan Zhu , Sissy Therese Sonnleitner , Kirsty R. Short , Meagan Carney","doi":"10.1016/j.jtbi.2024.112000","DOIUrl":"10.1016/j.jtbi.2024.112000","url":null,"abstract":"<div><div>We derive a numerical model representing the emergence and evolution of SARS-CoV-2 variants, informed by data from in-vitro passaging experiments in Vero B4 cells. We compare our numerical simulation results against probabilistic derivations of the expected probability of and time until the fittest variant becomes fixed in the population. Contrary to literature surrounding DNA viruses and eukaryotes where probabilities of fitness extremes are often modelled by exponential decaying tail, we show that above wildtype fitness differences for SARS-CoV-2 are actually best modelled by a heavy-tailed Fréchet distribution. Furthermore, we find that SARS-CoV-2 variants evolve through an essentially deterministic process rather than a diffusional one, with the dynamics driven by the fitness difference between the top variants rather than by the sampling/dilution process. An interesting consequence of this setting is that the number of variant virions, rather than their proportion, is a better predictor of the probability of fixation for a given variant.</div></div>","PeriodicalId":54763,"journal":{"name":"Journal of Theoretical Biology","volume":"598 ","pages":"Article 112000"},"PeriodicalIF":1.9,"publicationDate":"2024-11-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142717695","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}
Ting Huang , Hengmin Lv , Yiting Shu , Jian Luo , Linxuan Yu , Bing Chen , Xin Sun , Xilin Hou , Xiong You , Tonghua Zhang
{"title":"Noise-induced entrainment of the circadian clock by thermoperiods in tomato: A computational approach","authors":"Ting Huang , Hengmin Lv , Yiting Shu , Jian Luo , Linxuan Yu , Bing Chen , Xin Sun , Xilin Hou , Xiong You , Tonghua Zhang","doi":"10.1016/j.jtbi.2024.111999","DOIUrl":"10.1016/j.jtbi.2024.111999","url":null,"abstract":"<div><div>The endogenous circadian rhythm (approximately 24 h) allows plants to adapt to daily light and temperature variations. Although the mechanism of photoperiod entrainment has been studied extensively, entrainment to diurnal temperature rhythms remains poorly understood. Here we investigate the stochastic entrainment of the circadian clock in the model crop tomato, subject to different thermoperiods. We first proposed the deterministic model of the thermoresponsive circadian clock. The expressions of the circadian clock genes under constant warm temperature (29 ℃) were quantified by RT-qPCR for basal parameters estimation through minimizing the cost function. Model simulations by the stochastic simulation algorithm showed warm temperatures resulting in an advanced phase for approximately 3–4 h. A few hundred molecules for the system size of the stochastic model were sufficient to engage the robust oscillations. Multiple temperature inputs and abnormal temperature cycles similarly showed the invariant robustness of the oscillations. In addition, phases of the core circadian elements were remarkably correlated linearly with periods under temperature cycles. Whereas, the phases were correlated with the duration of daily warm temperature stimuli in a polynomial mode.</div></div>","PeriodicalId":54763,"journal":{"name":"Journal of Theoretical Biology","volume":"598 ","pages":"Article 111999"},"PeriodicalIF":1.9,"publicationDate":"2024-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142712030","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":"Phase synchronization analysis of EEG functional connectivity in Parkinson’s disease","authors":"Karthikeyan Rajagopal , Nafise Naseri , Fatemeh Parastesh , Farnaz Ghassemi , Sajad Jafari","doi":"10.1016/j.jtbi.2024.111997","DOIUrl":"10.1016/j.jtbi.2024.111997","url":null,"abstract":"<div><div>There is a growing need for research on Parkinson’s disease (PD), a neurological condition that often affects the elderly. By examining brain network connectivity, researchers are able to discover how different brain regions interact during various cognitive and behavioral tasks. They can also understand how changes in nonlinear connections may be linked to neurological and mental illnesses. In this paper, the synchrony levels of 59 EEG channels from 26 Parkinson’s patients and 13 healthy subjects is examined by utilizing Phase-Lag Index (PLI) during a motor task and resting-state conditions. Examining different EEG frequency bands shows that whole-brain synchronization in the delta band is significantly lower in PD patients compared to healthy subjects during the task. PD patients also exhibit a lower clustering coefficient and a higher shortest path length in this band during the task, which shows the higher small-worldness in Parkinson’s patients compared to healthy individuals. Moreover, the global efficiency in the delta band is significantly reduced in PD patients during the task. An analysis of local efficiency shows that PD and control groups differ in 57 channels. These results reveal that Parkinson’s patients appear to have considerable pathological abnormalities in their delta band connectivity and its characteristic features.</div></div>","PeriodicalId":54763,"journal":{"name":"Journal of Theoretical Biology","volume":"598 ","pages":"Article 111997"},"PeriodicalIF":1.9,"publicationDate":"2024-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142689767","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}
Jochen Blath , Anna Kraut , Tobias Paul , András Tóbiás
{"title":"A stochastic population model for the impact of cancer cell dormancy on therapy success","authors":"Jochen Blath , Anna Kraut , Tobias Paul , András Tóbiás","doi":"10.1016/j.jtbi.2024.111995","DOIUrl":"10.1016/j.jtbi.2024.111995","url":null,"abstract":"<div><div>Therapy evasion – and subsequent disease progression – is a major challenge in current oncology. An important role in this context seems to be played by various forms of cancer cell dormancy. For example, therapy-induced dormancy, over short timescales, can create serious obstacles to aggressive treatment approaches such as chemotherapy, and long-term dormancy may lead to relapses and metastases even many years after an initially successful treatment.</div><div>In this paper, we focus on individual cancer cells switching into and out of a dormant state both spontaneously as well as in response to treatment. We introduce an idealized mathematical model, based on stochastic agent-based interactions, for the dynamics of cancer cell populations involving individual short-term dormancy, and allow for a range of (multi-drug) therapy protocols. Our analysis – based on simulations of the many-particle limit – shows that in our model, depending on the specific underlying dormancy mechanism, even a small initial population (of explicitly quantifiable size) of dormant cells can lead to therapy failure under classical single-drug treatments that would successfully eradicate the tumour in the absence of dormancy. We further investigate and quantify the effectiveness of several multi-drug regimes (manipulating dormant cancer cells in specific ways, including increasing or decreasing resuscitation rates or targeting dormant cells directly). Relying on quantitative results for concrete simulation parameters, we provide some general basic rules for the design of (multi-)drug treatment protocols depending on the types and processes of dormancy mechanisms present in the population.</div></div>","PeriodicalId":54763,"journal":{"name":"Journal of Theoretical Biology","volume":"597 ","pages":"Article 111995"},"PeriodicalIF":1.9,"publicationDate":"2024-11-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142683610","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}