{"title":"Channel noise induced stochastic effect of Hodgkin–Huxley neurons in a real classification task","authors":"Yasemin Erkan , Erdem Erkan","doi":"10.1016/j.jtbi.2024.112028","DOIUrl":"10.1016/j.jtbi.2024.112028","url":null,"abstract":"<div><div>Noise is generally considered to have negative effects on information processing performance. However, it has also been proven that adding random noise or a certain level of stochastic (random) variability to a nonlinear system can increase its performance or sensitivity to weak signals. Despite the studies on this concept, called stochastic resonance in computational neuroscience, this phenomenon is still among the topics that need detailed research, especially in machine learning. In this study, the effect of noise arising from the intrinsic dynamics of the neurons forming the network in a spiking neural network consisting of Hodgkin–Huxley neurons on the image classification success of the network is investigated. In the first part of this two-part study, a practical neural network model consisting of Hodgkin–Huxley neurons is proposed and the network is tested in a 4-class real classification task. It is observed that the network consisting of Hodgkin–Huxley neurons has a classification performance at least as successful as the artificial neural network. In the second part of the study, the neurons in the network are replaced with stochastic Hodgkin–Huxley neurons, which more realistically represent the biological neuron, and the classification performance of the network at different cell membrane sizes is examined. Findings reveal that a spiking network consisting of stochastic Hodgkin–Huxley neurons, in which intrinsic noise dynamics are incorporated into the system, shows maximum classification performance at an optimal intrinsic noise level. It is called this reflection observed in the classification performance of a spiking network, which is referred to as stochastic resonance in computational neuroscience, as stochastic classification resonance in this study. This study also highlights the importance of bridging the gap between biological neuroscience and artificial neural networks for a better understanding of neurological structure.</div></div>","PeriodicalId":54763,"journal":{"name":"Journal of Theoretical Biology","volume":"599 ","pages":"Article 112028"},"PeriodicalIF":1.9,"publicationDate":"2024-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142857059","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":"Deciphering circulating tumor cells binding in a microfluidic system thanks to a parameterized mathematical model","authors":"Giorgia Ciavolella , Julien Granet , Jacky G. Goetz , Naël Osmani , Christèle Etchegaray , Annabelle Collin","doi":"10.1016/j.jtbi.2024.112029","DOIUrl":"10.1016/j.jtbi.2024.112029","url":null,"abstract":"<div><div>The spread of metastases is a crucial process in which some questions remain unanswered. In this work, we focus on tumor cells circulating in the bloodstream, the so-called Circulating Tumor Cells (CTCs). Our aim is to characterize their trajectories under the influence of hemodynamic and adhesion forces. We focus on already available <em>in vitro</em> measurements performed with a microfluidic device corresponding to the trajectories of CTCs – without or with different protein depletions – interacting with an endothelial layer. A key difficulty is the weak knowledge of the fluid velocity that has to be reconstructed. Our strategy combines a differential equation model – a Poiseuille model for the fluid velocity and an ODE system for the cell adhesion model – and a robust and well-designed calibration procedure. The parameterized model quantifies the strong influence of fluid velocity on adhesion and confirms the expected role of several proteins in the deceleration of CTCs. Finally, it enables the generation of synthetic cells, even for unobserved experimental conditions, opening the way to a digital twin for flowing cells with adhesion.</div></div>","PeriodicalId":54763,"journal":{"name":"Journal of Theoretical Biology","volume":"600 ","pages":"Article 112029"},"PeriodicalIF":1.9,"publicationDate":"2024-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142857060","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}
Xiaodan Sun , Weike Zhou , Yuhua Ruan , Guanghua Lan , Qiuying Zhu , Yanni Xiao
{"title":"Perceived risk induced multiscale model: Coupled within-host and between-host dynamics and behavioral dynamics","authors":"Xiaodan Sun , Weike Zhou , Yuhua Ruan , Guanghua Lan , Qiuying Zhu , Yanni Xiao","doi":"10.1016/j.jtbi.2024.111998","DOIUrl":"10.1016/j.jtbi.2024.111998","url":null,"abstract":"<div><div>A novel multiscale model is formulated to examine the co-evolution among behavioral dynamics, disease transmission dynamics and viral dynamics, in which perceived risk act as a bridge for realizing the bidirectional coupling of between-host dynamics and within-host dynamics. The model is validated by real data and exhibits rich dynamic behaviors including the periodic oscillations of the solutions, the discordance of transmission dynamics and viral dynamics. It is observed that new infections may increase with improving treatment efficacy, which may reveal the hidden mechanisms why it is hard to eliminate HIV/AIDS infection only with the strategy of treatment. If increasing treatment efficacy but without improving diagnosis rate, “nearly elimination” phenomenon may happen when the risk threshold for behavior changes is low, in which the number of new infections may drop to a relatively low level but increase again to a relatively high level after a period of time as people may hardly keep their awareness and increase their high risk behaviors. The findings indicate that the intervention measures should be implemented both at individual level and population level to realize “ending the AIDS”.</div></div>","PeriodicalId":54763,"journal":{"name":"Journal of Theoretical Biology","volume":"599 ","pages":"Article 111998"},"PeriodicalIF":1.9,"publicationDate":"2024-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142820331","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":"Learning to hunt: A data-driven stochastic feedback control model of predator–prey interactions","authors":"Deze Liu, Mohammad Tuqan, Daniel Burbano","doi":"10.1016/j.jtbi.2024.112021","DOIUrl":"10.1016/j.jtbi.2024.112021","url":null,"abstract":"<div><div>The dynamics unfolding during predator–prey interactions encapsulate a critical aspect of the natural world, dictating the survival and evolutionary trajectories of animal species. Underlying these complex dynamics, sensory-motor control strategies orchestrate the locomotory gates essential to guarantee survival or predation. While analytical models have been instrumental in understanding predator–prey interactions, dissecting sensory-motor control strategies remains a great challenge due to the adaptive and stochastic nature of animal behavior and the strong coupling of predator–prey interactions. Here, we propose a data-driven mathematical model describing the adaptive learning response of a dolphin while hunting a fish. Grounded in feedback control systems and stochastic differential equations theory, our model embraces the inherent unpredictability of animal behavior and sheds light on the adaptive learning strategies required to outmaneuver agile prey. The efficacy of our model was validated through numerical experiments mirroring crucial statistical properties of locomotor activity observed in empirical data. Finally, we explored the role of stochasticity in predator–prey dynamics. Interestingly, our findings indicate that varying noise levels can selectively favor either fish survival or dolphin hunting success.</div></div>","PeriodicalId":54763,"journal":{"name":"Journal of Theoretical Biology","volume":"599 ","pages":"Article 112021"},"PeriodicalIF":1.9,"publicationDate":"2024-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142815057","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}
Lachlan Arthur , Vasiliki Voulgaridou , Georgios Papageorgiou , Weiping Lu , Steven R. McDougall , Vassilis Sboros
{"title":"Super-resolution ultrasound imaging of ischaemia flow: An in silico study","authors":"Lachlan Arthur , Vasiliki Voulgaridou , Georgios Papageorgiou , Weiping Lu , Steven R. McDougall , Vassilis Sboros","doi":"10.1016/j.jtbi.2024.112018","DOIUrl":"10.1016/j.jtbi.2024.112018","url":null,"abstract":"<div><div>Super-resolution ultrasound (SRU) is a new ultrasound imaging mode that promises to facilitate the detection of microvascular disease by providing new vascular bio-markers that are directly linked to microvascular pathophysiology, thereby augmenting current knowledge and potentially enabling new treatment. Such a capability can be developed through thorough understanding as articulated by means of mathematical models. In this study, a 2D numerical flow model is adopted for generating flow adaptation in response to ischaemia, in order to determine the ability of SRU to register the resulting flow perturbations. The flow model results demonstrate that variations in flow behaviour in response to locally induced ischaemia can be significant throughout the entire vascular bed. Measured velocities have variations that are dependent on the location of ischaemia, with median values ranging between <span><math><mrow><mn>2</mn><mtext>–</mtext><mn>7</mn></mrow></math></span> mms<sup>−1</sup>. Moreover, the distinction between healthy and ischaemic networks are recorded accurately in the SRU results showing excellent agreement between SRU maps and the model. Up to 7-fold spatial resolution improvement to conventional contrast ultrasound was achieved in microbubble localisation while the detection precision and recall was consistently above 98<span><math><mtext>%</mtext></math></span>. The microbubble tracking precision was of a similar accuracy, whereas the recall was reduced (77<span><math><mtext>%</mtext></math></span>) under varying ischaemic impacted flow. Further, regions with velocities up to 30 mms<sup>−1</sup> are in excellent agreement with SRU maps, while at regions that include a proportion of higher velocities, the median velocity values are within 1.28<span><math><mtext>%</mtext></math></span>–3.32<span><math><mtext>%</mtext></math></span> of the ground-truth. In conclusion, SRU is a highly promising methodology for the direct measurement of microvascular flow dynamics and may provide a valuable tool for the understanding and subsequent modelling of behaviour in the vascular bed.</div></div>","PeriodicalId":54763,"journal":{"name":"Journal of Theoretical Biology","volume":"599 ","pages":"Article 112018"},"PeriodicalIF":1.9,"publicationDate":"2024-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142796455","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":"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":"<div><div>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.</div></div>","PeriodicalId":54763,"journal":{"name":"Journal of Theoretical Biology","volume":"599 ","pages":"Article 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":"OA","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":"<div><div>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.</div></div>","PeriodicalId":54763,"journal":{"name":"Journal of Theoretical Biology","volume":"599 ","pages":"Article 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}
{"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":"<div><div>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.</div></div>","PeriodicalId":54763,"journal":{"name":"Journal of Theoretical Biology","volume":"599 ","pages":"Article 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}