Pub Date : 2025-01-30DOI: 10.1016/j.jtbi.2025.112050
Zhuojun Yu , Yangyang Wang , Peter J. Thomas , Hillel J. Chiel
Rhythmic motor behaviors controlled by neuromechanical systems, consisting of central neural circuitry, biomechanics, and sensory feedback, show efficiency in energy expenditure. The biomechanical elements (e.g., muscles) are modulated by peripheral neuromodulation which may improve their strength and speed properties. However, there are relatively few studies on neuromodulatory control of muscle function and metabolic mechanical efficiency in neuromechanical systems. To investigate the role of neuromodulation on the system’s mechanical efficiency, we consider a neuromuscular model of motor patterns for feeding in the marine mollusk Aplysia californica. By incorporating muscle energetics and neuromodulatory effects into the model, we demonstrate tradeoffs in the energy efficiency of Aplysia’s rhythmic swallowing behavior as a function of the level of neuromodulation. A robust efficiency optimum arises from an intermediate level of neuromodulation, and excessive neuromodulation may be inefficient and disadvantageous to an animal’s metabolism. This optimum emerges from physiological constraints imposed upon serotonergic modulation trajectories on the energy efficiency landscape. Our results may lead to experimentally testable hypotheses of the role of neuromodulation in rhythmic motor control.
{"title":"Tradeoffs in the energetic value of neuromodulation in a closed-loop neuromechanical system","authors":"Zhuojun Yu , Yangyang Wang , Peter J. Thomas , Hillel J. Chiel","doi":"10.1016/j.jtbi.2025.112050","DOIUrl":"10.1016/j.jtbi.2025.112050","url":null,"abstract":"<div><div>Rhythmic motor behaviors controlled by neuromechanical systems, consisting of central neural circuitry, biomechanics, and sensory feedback, show efficiency in energy expenditure. The biomechanical elements (e.g., muscles) are modulated by peripheral neuromodulation which may improve their strength and speed properties. However, there are relatively few studies on neuromodulatory control of muscle function and metabolic mechanical efficiency in neuromechanical systems. To investigate the role of neuromodulation on the system’s mechanical efficiency, we consider a neuromuscular model of motor patterns for feeding in the marine mollusk <em>Aplysia californica</em>. By incorporating muscle energetics and neuromodulatory effects into the model, we demonstrate tradeoffs in the energy efficiency of <em>Aplysia</em>’s rhythmic swallowing behavior as a function of the level of neuromodulation. A robust efficiency optimum arises from an intermediate level of neuromodulation, and excessive neuromodulation may be inefficient and disadvantageous to an animal’s metabolism. This optimum emerges from physiological constraints imposed upon serotonergic modulation trajectories on the energy efficiency landscape. Our results may lead to experimentally testable hypotheses of the role of neuromodulation in rhythmic motor control.</div></div>","PeriodicalId":54763,"journal":{"name":"Journal of Theoretical Biology","volume":"604 ","pages":"Article 112050"},"PeriodicalIF":1.9,"publicationDate":"2025-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143076495","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}
Pub Date : 2025-01-27DOI: 10.1016/j.jtbi.2025.112046
Xin Zhao , Shiyang Yu , Meng Fan
Coral reef ecosystem is a crucial component of marine ecosystems and is undergoing severe degradation due to the combined dural impact of environmental changes and human activities. Soundscape technology is an innovative coral reef restoration approach that attracts fish to degraded reefs. Inspired by such technique, a five-dimensional mathematical dynamical model incorporating the asymmetric dispersal of parrotfish is formulated to characterize the dynamic interaction among macroalgae, coral, algal turf, and parrotfish in coral reef ecosystem. Theoretical analyses are conducted and the impact of dispersal on the stability of coral reef ecosystems is systematically studied. The global sensitivity analysis is presented by using PRCC method and the impact of dispersal coefficients on the dynamic behavior of the model is explored through numerical simulations, which provide deeper insights into the influence of key parameters on the stability of the model. The main findings indicate that, adopting soundscape technology facilitates the recovery of coral reefs, make it easier to maintain a coral-dominated state, and reduce the possibility of phase shifts, thereby enhance the stability, biodiversity, and recovery of coral reef ecosystem.
{"title":"White lies for coral reefs: Dynamics of two-patch coral reefs model with asymmetric dispersal","authors":"Xin Zhao , Shiyang Yu , Meng Fan","doi":"10.1016/j.jtbi.2025.112046","DOIUrl":"10.1016/j.jtbi.2025.112046","url":null,"abstract":"<div><div>Coral reef ecosystem is a crucial component of marine ecosystems and is undergoing severe degradation due to the combined dural impact of environmental changes and human activities. Soundscape technology is an innovative coral reef restoration approach that attracts fish to degraded reefs. Inspired by such technique, a five-dimensional mathematical dynamical model incorporating the asymmetric dispersal of parrotfish is formulated to characterize the dynamic interaction among macroalgae, coral, algal turf, and parrotfish in coral reef ecosystem. Theoretical analyses are conducted and the impact of dispersal on the stability of coral reef ecosystems is systematically studied. The global sensitivity analysis is presented by using PRCC method and the impact of dispersal coefficients on the dynamic behavior of the model is explored through numerical simulations, which provide deeper insights into the influence of key parameters on the stability of the model. The main findings indicate that, adopting soundscape technology facilitates the recovery of coral reefs, make it easier to maintain a coral-dominated state, and reduce the possibility of phase shifts, thereby enhance the stability, biodiversity, and recovery of coral reef ecosystem.</div></div>","PeriodicalId":54763,"journal":{"name":"Journal of Theoretical Biology","volume":"601 ","pages":"Article 112046"},"PeriodicalIF":1.9,"publicationDate":"2025-01-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143069795","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}
Pub Date : 2025-01-25DOI: 10.1016/j.jtbi.2025.112047
Jintao Wang, Yanni Xiao, Pengfei Song
There are evidence showing that meteorological factors, such as temperature and humidity, have critical effects on transmission of some infectious diseases, while quantifying the influence is challenging. In this study we develop a learning-explaining framework to discover the particular dependence of transmission mechanisms on meteorological factors based on multiple source data. The incidence rate based on the epidemic data and epidemic model is theoretically identified, and meanwhile the practical discovery of particular formula is feasible through deep neural networks (DNN), symbolic regression (SR) and sparse identification of nonlinear dynamics (SINDy). In particular, we initially learn the incidence rate in an SIRS model based on epidemic data, then use mechanism discovery methods to explore the possible explicit forms of the incidence rate, and consequently explore the possible relationship between transmission rate and meteorological factors. We finally use information criteria and a definition of evaluation score to make model selection, and hence suggest the optimal explicit formula. We illustrate the idea by derive the incidence rate and transmission rate of respiratory infectious diseases based on the case data on influenza-like illness (ILI) in Xi’an, Shaanxi Province of China and meteorological data from 1st January 2010 to 10th November 2016. The finding reveals that the influence of meteorological factors on transmission exhibits very strong nonlinearity, and modeling the effect should be of great care.
{"title":"Discovering the climate dependent disease transmission mechanism through learning-explaining framework","authors":"Jintao Wang, Yanni Xiao, Pengfei Song","doi":"10.1016/j.jtbi.2025.112047","DOIUrl":"10.1016/j.jtbi.2025.112047","url":null,"abstract":"<div><div>There are evidence showing that meteorological factors, such as temperature and humidity, have critical effects on transmission of some infectious diseases, while quantifying the influence is challenging. In this study we develop a learning-explaining framework to discover the particular dependence of transmission mechanisms on meteorological factors based on multiple source data. The incidence rate based on the epidemic data and epidemic model is theoretically identified, and meanwhile the practical discovery of particular formula is feasible through deep neural networks (DNN), symbolic regression (SR) and sparse identification of nonlinear dynamics (SINDy). In particular, we initially learn the incidence rate in an SIRS model based on epidemic data, then use mechanism discovery methods to explore the possible explicit forms of the incidence rate, and consequently explore the possible relationship between transmission rate and meteorological factors. We finally use information criteria and a definition of evaluation score to make model selection, and hence suggest the optimal explicit formula. We illustrate the idea by derive the incidence rate and transmission rate of respiratory infectious diseases based on the case data on influenza-like illness (ILI) in Xi’an, Shaanxi Province of China and meteorological data from 1st January 2010 to 10th November 2016. The finding reveals that the influence of meteorological factors on transmission exhibits very strong nonlinearity, and modeling the effect should be of great care.</div></div>","PeriodicalId":54763,"journal":{"name":"Journal of Theoretical Biology","volume":"601 ","pages":"Article 112047"},"PeriodicalIF":1.9,"publicationDate":"2025-01-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143054287","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}
Pub Date : 2025-01-21DOI: 10.1016/j.jtbi.2025.112045
Nir Gavish
The competitive exclusion principle in epidemiology implies that when competing strains of a pathogen provide complete protection for each other, the strain with the largest reproduction number outcompetes the other strains and drives them to extinction. The introduction of various trade-off mechanisms may facilitate the coexistence of competing strains, especially when their respective basic reproduction numbers are close so that the competition between the strains is weak. Yet, one may expect that a substantial competitive advantage of one of the strains will eventually outbalance trade-off mechanisms driving less competitive strains to extinction. The literature, however, lacks a rigorous validation of this statement.
In this work, we challenge the validity of the exclusion principle at a limit in which one strain has a vast competitive advantage over the other strains. We show that when one strain is significantly more transmissible than the others, and under broad conditions, an epidemic system with two strains has a stable endemic equilibrium in which both strains coexist with comparable prevalence. Thus, the competitive exclusion principle does not unconditionally hold beyond the established case of complete immunity.
{"title":"Revisiting the exclusion principle in epidemiology at the limit of a large competitive advantage","authors":"Nir Gavish","doi":"10.1016/j.jtbi.2025.112045","DOIUrl":"10.1016/j.jtbi.2025.112045","url":null,"abstract":"<div><div>The competitive exclusion principle in epidemiology implies that when competing strains of a pathogen provide complete protection for each other, the strain with the largest reproduction number outcompetes the other strains and drives them to extinction. The introduction of various trade-off mechanisms may facilitate the coexistence of competing strains, especially when their respective basic reproduction numbers are close so that the competition between the strains is weak. Yet, one may expect that a substantial competitive advantage of one of the strains will eventually outbalance trade-off mechanisms driving less competitive strains to extinction. The literature, however, lacks a rigorous validation of this statement.</div><div>In this work, we challenge the validity of the exclusion principle at a limit in which one strain has a vast competitive advantage over the other strains. We show that when one strain is significantly more transmissible than the others, and under broad conditions, an epidemic system with two strains has a stable endemic equilibrium in which both strains coexist with comparable prevalence. Thus, the competitive exclusion principle does not unconditionally hold beyond the established case of complete immunity.</div></div>","PeriodicalId":54763,"journal":{"name":"Journal of Theoretical Biology","volume":"600 ","pages":"Article 112045"},"PeriodicalIF":1.9,"publicationDate":"2025-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143030059","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}
Pub Date : 2025-01-11DOI: 10.1016/j.jtbi.2025.112043
Yohsuke Murase
Cooperation is fundamental to human societies, and indirect reciprocity, where individuals cooperate to build a positive reputation for future benefits, plays a key role in promoting it. Previous theoretical and experimental studies have explored both the effectiveness and limitations of costly punishment in sustaining cooperation. While empirical observations show that costly punishment by third parties is common, some theoretical models suggest it may not be effective in the context of indirect reciprocity, raising doubts about its potential to enhance cooperation. In this study, we theoretically investigate the conditions under which costly punishment is effective. Building on a previous model, we introduce a new type of error in perceiving actions, where defection may be mistakenly perceived as cooperation. This extension models a realistic scenario where defectors have a strong incentive to disguise their defection as cooperation. Our analysis reveals that when defection is difficult to detect, norms involving costly punishment can emerge as the most efficient evolutionarily stable strategies. These findings demonstrate that costly punishment can play a crucial role in promoting cooperation within indirect reciprocity.
{"title":"Costly punishment sustains indirect reciprocity under low defection detectability","authors":"Yohsuke Murase","doi":"10.1016/j.jtbi.2025.112043","DOIUrl":"10.1016/j.jtbi.2025.112043","url":null,"abstract":"<div><div>Cooperation is fundamental to human societies, and indirect reciprocity, where individuals cooperate to build a positive reputation for future benefits, plays a key role in promoting it. Previous theoretical and experimental studies have explored both the effectiveness and limitations of costly punishment in sustaining cooperation. While empirical observations show that costly punishment by third parties is common, some theoretical models suggest it may not be effective in the context of indirect reciprocity, raising doubts about its potential to enhance cooperation. In this study, we theoretically investigate the conditions under which costly punishment is effective. Building on a previous model, we introduce a new type of error in perceiving actions, where defection may be mistakenly perceived as cooperation. This extension models a realistic scenario where defectors have a strong incentive to disguise their defection as cooperation. Our analysis reveals that when defection is difficult to detect, norms involving costly punishment can emerge as the most efficient evolutionarily stable strategies. These findings demonstrate that costly punishment can play a crucial role in promoting cooperation within indirect reciprocity.</div></div>","PeriodicalId":54763,"journal":{"name":"Journal of Theoretical Biology","volume":"600 ","pages":"Article 112043"},"PeriodicalIF":1.9,"publicationDate":"2025-01-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142980722","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}
Pub Date : 2025-01-10DOI: 10.1016/j.jtbi.2025.112044
Małgorzata Fic , Frank Bastian , Jacek Miȩkisz , Chaitanya S. Gokhale
Real-world processes often exhibit temporal separation between actions and reactions - a characteristic frequently ignored in many modelling frameworks. Adding temporal aspects, like time delays, introduces a higher complexity of problems and leads to models that are challenging to analyse and computationally expensive to solve. In this work, we propose an intermediate solution to resolve the issue in the framework of evolutionary game theory. Our compartment-based model includes time delays while remaining relatively simple and straightforward to analyse. We show that this model yields qualitatively comparable results with models incorporating explicit delays. Particularly, we focus on the case of delays between parents’ interaction and an offspring joining the population, with the magnitude of the delay depending on the parents’ strategy. We analyse Stag-Hunt, Snowdrift, and the Prisoner’s Dilemma game and show that strategy-dependent delays are detrimental to affected strategies. Additionally, we present how including delays may change the effective games played in the population, subsequently emphasising the importance of considering the studied systems’ temporal aspects to model them accurately.
{"title":"Compartment model of strategy-dependent time delays in replicator dynamics","authors":"Małgorzata Fic , Frank Bastian , Jacek Miȩkisz , Chaitanya S. Gokhale","doi":"10.1016/j.jtbi.2025.112044","DOIUrl":"10.1016/j.jtbi.2025.112044","url":null,"abstract":"<div><div>Real-world processes often exhibit temporal separation between actions and reactions - a characteristic frequently ignored in many modelling frameworks. Adding temporal aspects, like time delays, introduces a higher complexity of problems and leads to models that are challenging to analyse and computationally expensive to solve. In this work, we propose an intermediate solution to resolve the issue in the framework of evolutionary game theory. Our compartment-based model includes time delays while remaining relatively simple and straightforward to analyse. We show that this model yields qualitatively comparable results with models incorporating explicit delays. Particularly, we focus on the case of delays between parents’ interaction and an offspring joining the population, with the magnitude of the delay depending on the parents’ strategy. We analyse Stag-Hunt, Snowdrift, and the Prisoner’s Dilemma game and show that strategy-dependent delays are detrimental to affected strategies. Additionally, we present how including delays may change the effective games played in the population, subsequently emphasising the importance of considering the studied systems’ temporal aspects to model them accurately.</div></div>","PeriodicalId":54763,"journal":{"name":"Journal of Theoretical Biology","volume":"601 ","pages":"Article 112044"},"PeriodicalIF":1.9,"publicationDate":"2025-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142973381","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}
Pub Date : 2025-01-10DOI: 10.1016/j.jtbi.2025.112042
Jérémy Seurat , Krista R. Gerbino , Justin R. Meyer , Joshua M. Borin , Joshua S. Weitz
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’) D9, an evolved isolate derived from phage 21. A pilot experiment confirmed that 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 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.
{"title":"Design, optimization, and inference of biphasic decay of infectious virus particles","authors":"Jérémy Seurat , Krista R. Gerbino , Justin R. Meyer , Joshua M. Borin , 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}
Pub Date : 2024-12-24DOI: 10.1016/j.jtbi.2024.112033
Xu Wang , Xi Chen , Jinhui Zhu , Sheng Li
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.
{"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 , Xi Chen , Jinhui Zhu , 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}
Pub Date : 2024-12-19DOI: 10.1016/j.jtbi.2024.112032
Márton Csillag , Hamza Giaffar , Eörs Szathmáry , Mauro Santos , Dániel Czégel
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.
{"title":"From Bayes to Darwin: Evolutionary search as an exaptation from sampling-based Bayesian inference","authors":"Márton Csillag , Hamza Giaffar , Eörs Szathmáry , Mauro Santos , 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}
Pub Date : 2024-12-19DOI: 10.1016/j.jtbi.2024.112030
Arthur Alexandre , Alia Abbara , Cecilia Fruet , Claude Loverdo , Anne-Florence Bitbol
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.
{"title":"Bridging Wright–Fisher and Moran models","authors":"Arthur Alexandre , Alia Abbara , Cecilia Fruet , Claude Loverdo , 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}
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