Journal of Theoretical Biology最新文献

{"title":"Design, optimization, and inference of biphasic decay of infectious virus particles","authors":"Jérémy Seurat ,&nbsp;Krista R. Gerbino ,&nbsp;Justin R. Meyer ,&nbsp;Joshua M. Borin ,&nbsp;Joshua S. Weitz","doi":"10.1016/j.jtbi.2025.112042","DOIUrl":"10.1016/j.jtbi.2025.112042","url":null,"abstract":"<div><div>Virus population dynamics are driven by counter-balancing forces of production and loss. Whereas viral production arises from complex interactions with susceptible hosts, the loss of infectious virus particles is often approximated as a first-order kinetic process. As such, experimental protocols to measure infectious virus loss are not typically designed to identify non-exponential decay processes. Here, we propose methods to evaluate if an experimental design is adequate to identify multiphasic virus particle decay and to optimize the sampling times of decay experiments, accounting for uncertainties in viral kinetics. First, we evaluate synthetic scenarios of biphasic decays, with varying decay rates and initial proportions of subpopulations. We show that robust inference of multiphasic decay is more likely when the faster decaying subpopulation predominates insofar as early samples are taken to resolve the faster decay rate. Moreover, design optimization involving non-equal spacing between observations increases the precision of estimation while reducing the number of samples. We then apply these methods to infer multiple decay rates associated with the decay of bacteriophage (‘phage’) <span><math><mi>Φ</mi></math></span>D9, an evolved isolate derived from phage <span><math><mi>Φ</mi></math></span>21. A pilot experiment confirmed that <span><math><mi>Φ</mi></math></span>D9 decay is multiphasic, but was unable to resolve the rate or proportion of the fast decaying subpopulation(s). We then applied a Fisher information matrix-based design optimization method to propose non-equally spaced sampling times. Using this strategy, we were able to robustly estimate multiple decay rates and the size of the respective subpopulations. Notably, we conclude that the vast majority (94%) of the phage <span><math><mi>Φ</mi></math></span>D9 population decays at a rate 16-fold higher than the slow decaying population. Altogether, these results provide both a rationale and a practical approach to quantitatively estimate heterogeneity in viral decay.</div></div>","PeriodicalId":54763,"journal":{"name":"Journal of Theoretical Biology","volume":"600 ","pages":"Article 112042"},"PeriodicalIF":1.9,"publicationDate":"2025-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142973382","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":"Quantifying the impact of metronomic chemotherapy chemo-switch regimen and the sequencing of chemotherapy and radiotherapy on pancreatic ductal adenocarcinoma treatment","authors":"Xu Wang ,&nbsp;Xi Chen ,&nbsp;Jinhui Zhu ,&nbsp;Sheng Li","doi":"10.1016/j.jtbi.2024.112033","DOIUrl":"10.1016/j.jtbi.2024.112033","url":null,"abstract":"<div><div>Metronomic chemotherapy (MCT) is a novel chemotherapy approach characterized by a high-frequency, low-dose administration strategy. The “chemo-switch” regimen involves the sequential use of two dosing strategies: maximum tolerated dose (MTD) chemotherapy and MCT. For patients with pancreatic ductal adenocarcinoma (PDAC), selecting novel chemotherapy regimens appropriately according to their physical conditions may help address the challenges associated with MTD chemotherapy, such as excessive toxicity, prolonged tumor recovery, and suboptimal efficacy. There is currently limited research on mathematical models related to novel chemotherapy regimens and PDAC, as well as on the impact of different drug administration strategies and the sequence of chemoradiotherapy in combined treatment. To address these gaps, we propose a two-dimensional multiscale mathematical model. Initially, we model the individual effects of MTD chemotherapy, antiangiogenic therapy, and radiotherapy. Subsequently, we analyze the anti-tumor effects of various chemotherapy regimens and their underlying mechanisms. Furthermore, we assess how different drug administration regimens and the sequencing of chemotherapy and radiotherapy affect treatment outcomes. Simulation results indicate that, compared to standard MTD chemotherapy, using the MCT regimen or introducing MCT during MTD chemotherapy (chemo-switch regimen) demonstrates better anti-tumor efficacy and sustained tumor perfusion, enhancing drug accumulation within tumor regions. Combined therapy exhibits superior efficacy compared to monotherapy. Placing radiotherapy after anti-angiogenic therapy and chemotherapy suggests more effective in suppressing tumor growth and sustaining tumor perfusion. It is noteworthy that while this study focuses on PDAC treatment, its findings can be extrapolated to other fibrotic tumors, thereby facilitating similar analyses across different tumor types.</div></div>","PeriodicalId":54763,"journal":{"name":"Journal of Theoretical Biology","volume":"599 ","pages":"Article 112033"},"PeriodicalIF":1.9,"publicationDate":"2024-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142899272","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":"From Bayes to Darwin: Evolutionary search as an exaptation from sampling-based Bayesian inference","authors":"Márton Csillag ,&nbsp;Hamza Giaffar ,&nbsp;Eörs Szathmáry ,&nbsp;Mauro Santos ,&nbsp;Dániel Czégel","doi":"10.1016/j.jtbi.2024.112032","DOIUrl":"10.1016/j.jtbi.2024.112032","url":null,"abstract":"<div><div>Building on the algorithmic equivalence between finite population replicator dynamics and particle filtering based approximation of Bayesian inference, we design a computational model to demonstrate the emergence of Darwinian evolution over representational units when collectives of units are selected to infer statistics of high-dimensional combinatorial environments. The non-Darwinian starting point is two units undergoing a few cycles of noisy, selection-dependent information transmission, corresponding to a serial (one comparison per cycle), non-cumulative process without heredity. Selection for accurate Bayesian inference at the collective level induces an adaptive path to the emergence of Darwinian evolution within the collectives, capable of maintaining and iteratively improving upon complex combinatorial information. When collectives are themselves Darwinian, this mechanism amounts to a top-down (filial) transition in individuality. We suggest that such a selection mechanism can explain the hypothesized emergence of fast timescale Darwinian dynamics over a population of neural representations within animal and human brains, endowing them with combinatorial planning capabilities. Further possible physical implementations include prebiotic collectives of non-replicating molecules and reinforcement learning agents with parallel policy search.</div></div>","PeriodicalId":54763,"journal":{"name":"Journal of Theoretical Biology","volume":"599 ","pages":"Article 112032"},"PeriodicalIF":1.9,"publicationDate":"2024-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142873144","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":"Bridging Wright–Fisher and Moran models","authors":"Arthur Alexandre ,&nbsp;Alia Abbara ,&nbsp;Cecilia Fruet ,&nbsp;Claude Loverdo ,&nbsp;Anne-Florence Bitbol","doi":"10.1016/j.jtbi.2024.112030","DOIUrl":"10.1016/j.jtbi.2024.112030","url":null,"abstract":"<div><div>The Wright–Fisher model and the Moran model are both widely used in population genetics. They describe the time evolution of the frequency of an allele in a well-mixed population with fixed size. We propose a simple and tractable model which bridges the Wright–Fisher and the Moran descriptions. We assume that a fixed fraction of the population is updated at each discrete time step. In this model, we determine the fixation probability of a mutant and its average fixation and extinction times, under the diffusion approximation. We further study the associated coalescent process, which converges to Kingman’s coalescent, and we calculate effective population sizes. We generalize our model, first by taking into account fluctuating updated fractions or individual lifetimes, and then by incorporating selection on the lifetime as well as on the reproductive fitness.</div></div>","PeriodicalId":54763,"journal":{"name":"Journal of Theoretical Biology","volume":"599 ","pages":"Article 112030"},"PeriodicalIF":1.9,"publicationDate":"2024-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142873105","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":"Beyond predation: Fish–coral interactions can tip the scales of coral disease","authors":"Buddhadev Ranjit ,&nbsp;Arnab Chattopadhyay ,&nbsp;Arindam Mandal ,&nbsp;Santosh Biswas ,&nbsp;Joydev Chattopadhyay","doi":"10.1016/j.jtbi.2024.112031","DOIUrl":"10.1016/j.jtbi.2024.112031","url":null,"abstract":"<div><div>Coral reefs are critical ecosystems, fostering biodiversity and sustaining the livelihoods of millions globally. Nonetheless, they confront escalating threats, with infectious diseases emerging as primary catalysts for extensive damage, surpassing the impacts of other human-induced stressors. Disease transmission via biotic factors, particularly during fish predation, is a crucial yet often overlooked pathway. While their feeding can spread infectious diseases through spores, it also controls the growth of macroalgae, a major competitor for space on the reef. Given this dual effect, the precise impact of fish on coral disease remains ambiguous and requires additional investigation. In this study, we addressed this gap for the first time by employing a mathematical model. Our analyses unveil intricate interactions between fish predation and coral health, revealing potential benefits and drawbacks for coral reef ecosystems. Coral survival hinges on a delicate balance of fish predation, with extremes (both low and high) offering some protection against disease outbreaks compared to moderate predation, which can cause sudden die-offs. More specifically, as fish predation intensifies, the ecosystem undergoes a tipping point, transitioning from a disease-dominated state to a healthier one. Moreover, the interplay between transmission rate and virulence in coral populations is significantly shaped by fish predation rates. Specifically, the threshold ratio of transmission to virulence, signalling a regime shift from a healthy to a disease-dominated state, exhibits a linear increase with fish predation rate. Overall, our findings emphasize the importance of considering biotic interactions in coral disease ecology and offer insights essential for effective reef conservation strategies.</div></div>","PeriodicalId":54763,"journal":{"name":"Journal of Theoretical Biology","volume":"599 ","pages":"Article 112031"},"PeriodicalIF":1.9,"publicationDate":"2024-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142872620","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":"Analysis of electrical activities in a functional neuron with dual memristors","authors":"Xinlin Song ,&nbsp;Feifei Yang","doi":"10.1016/j.jtbi.2024.112034","DOIUrl":"10.1016/j.jtbi.2024.112034","url":null,"abstract":"<div><div>Neuron as a charged body, it is easily disturbed by the external electromagnetic field, which changes the electrical activities of the neurons. In fact, the interference of external electric or magnetic field is the process of energy injection of neurons, the injection of energy will redistribute the field energy inside the neurons, and the redistribution of energy will change the electrical activities of the neurons. Therefore, we design a neuron model with double memristors to explore the external electromagnetic field on the regulation of neural electrical activity. The dimensionless equations of the model with double memristors and its energy function are obtained based on the Kirchhoff’s and the Helmholtz’s theorems. The electrical activities of the neuron model under the external electromagnetic field distribution are researched by applying the nonlinear analysis methods, and the coherence resonance of the neuron is explored under the external noise electromagnetic field. The results indicate that the electrical activities of the model are controlled by the external electromagnetic field. This neuron model can be used to study the synchronization between magnetic field coupled or electric field coupled neurons.</div></div>","PeriodicalId":54763,"journal":{"name":"Journal of Theoretical Biology","volume":"599 ","pages":"Article 112034"},"PeriodicalIF":1.9,"publicationDate":"2024-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142871989","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":"Channel noise induced stochastic effect of Hodgkin–Huxley neurons in a real classification task","authors":"Yasemin Erkan ,&nbsp;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 ,&nbsp;Julien Granet ,&nbsp;Jacky G. Goetz ,&nbsp;Naël Osmani ,&nbsp;Christèle Etchegaray ,&nbsp;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}

{"title":"Perceived risk induced multiscale model: Coupled within-host and between-host dynamics and behavioral dynamics","authors":"Xiaodan Sun ,&nbsp;Weike Zhou ,&nbsp;Yuhua Ruan ,&nbsp;Guanghua Lan ,&nbsp;Qiuying Zhu ,&nbsp;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,&nbsp;Mohammad Tuqan,&nbsp;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}