Pub Date : 2026-01-19DOI: 10.1016/j.jtbi.2025.112365
Stéphane Urcun , Yasmin El Mahi , Raluca Eftimie , Zélie Dirand , Gwenaël Rolin , Stéphane P.A. Bordas
In this study, we propose and validate a simple agent-based model to study cell-cell interactions and cell migration during in vitro scratch assays in the context of cutaneous fibrosis (keloid). For model parametrization, we collect data from in vitro experiments performed with healthy or keloid fibroblasts treated (or not) with type 1 or 2 macrophages secretome to mimic specific in vivo environments. All experiments were performed with mitomycin to inhibit cell proliferation, and subsequently isolate the sole contribution of migration to wound filling over time. The scratch assays are modeled within the cellular Potts model framework. The calibration process, via Levenberg-Maquart algorithm, gives a mean error of 4.53 ± 0.77% across the four modalities (healthy, control, M1 and M2 secretum) and the evaluation dataset gives a mean error of 10.55 ± 0.77%. With the help of this model, we test whether the hypothesis of contact inhibition of locomotion (CIL) can explain the movement of keloid fibroblasts. The simulation results and their comparison with the experimental data suggest that CIL might not characterize the movement of keloid fibroblasts, which is in contrast to the importance of CIL for the movement of healthy fibroblasts.
{"title":"Simple cellular potts model of scratch assays on healthy and keloid fibroblasts driven by contact inhibition of locomotion","authors":"Stéphane Urcun , Yasmin El Mahi , Raluca Eftimie , Zélie Dirand , Gwenaël Rolin , Stéphane P.A. Bordas","doi":"10.1016/j.jtbi.2025.112365","DOIUrl":"10.1016/j.jtbi.2025.112365","url":null,"abstract":"<div><div>In this study, we propose and validate a simple agent-based model to study cell-cell interactions and cell migration during in vitro scratch assays in the context of cutaneous fibrosis (keloid). For model parametrization, we collect data from in vitro experiments performed with healthy or keloid fibroblasts treated (or not) with type 1 or 2 macrophages secretome to mimic specific in vivo environments. All experiments were performed with mitomycin to inhibit cell proliferation, and subsequently isolate the sole contribution of migration to wound filling over time. The scratch assays are modeled within the cellular Potts model framework. The calibration process, via Levenberg-Maquart algorithm, gives a mean error of 4.53 ± 0.77% across the four modalities (healthy, control, M1 and M2 secretum) and the evaluation dataset gives a mean error of 10.55 ± 0.77%. With the help of this model, we test whether the hypothesis of contact inhibition of locomotion (CIL) can explain the movement of keloid fibroblasts. The simulation results and their comparison with the experimental data suggest that CIL might not characterize the movement of keloid fibroblasts, which is in contrast to the importance of CIL for the movement of healthy fibroblasts.</div></div>","PeriodicalId":54763,"journal":{"name":"Journal of Theoretical Biology","volume":"622 ","pages":"Article 112365"},"PeriodicalIF":2.0,"publicationDate":"2026-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146020818","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 : 2026-01-17DOI: 10.1016/j.jtbi.2026.112375
Heiko Enderling
{"title":"Mathematical modeling of tumor-immune interactions in breast cancer must model tumor-immune interactions in breast cancer","authors":"Heiko Enderling","doi":"10.1016/j.jtbi.2026.112375","DOIUrl":"10.1016/j.jtbi.2026.112375","url":null,"abstract":"","PeriodicalId":54763,"journal":{"name":"Journal of Theoretical Biology","volume":"622 ","pages":"Article 112375"},"PeriodicalIF":2.0,"publicationDate":"2026-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146004805","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 : 2026-01-17DOI: 10.1016/j.jtbi.2026.112378
Srikant Venkitachalam , Amitabh Joshi
The study of larval competition in laboratory populations of Drosophila, implemented via the crowding of larval cultures, has contributed greatly to the understanding of the ecology of competition, the evolution of larval competitive ability, and formed the basis of rigorous testing of the theory of density-dependent selection. Earlier studies led to the view that the outcomes of larval competition, and resulting evolutionary consequences of crowding-adaptation, could largely be understood by varying the starting density of individuals in a crowded culture. However, recent studies have shown that the results of adaptation to larval crowding may not be well predicted by the overall larval density (i.e., total starting individuals/total volume of food). Cultures raised at the same overall density but at different egg number and food volume combinations were shown to have different underlying density-specific fitness functions, and crowding-adaptation in each of these cultures was attained through different evolutionary trajectories as well. A recent study showed that cultures with not just the same density, but the same egg and food volume combination, achieved through food columns of differing diameter and height, could also differ greatly in fitness-related trait outcomes. In that study, the density of larvae in the feeding band (volume of food close to the surface in contact with air, to which larval feeding is largely restricted) was a very important factor in predicting the outcomes of larval competition. Given these recent findings, it is important to understand the overall role of feeding band density, and how it influences density-specific fitness functions in different kinds of crowded cultures. As the older models of larval competition are now insufficient to capture current empirical data, we constructed an individual-based simulation framework informed in part by these more recent findings, in order to better understand the evolutionary ecology and mechanistic underpinnings of larval competition, and predict robust experiments for expanding our understanding of the process of larval competition in Drosophila.
{"title":"An individual-based simulation framework exploring the ecology and mechanistic underpinnings of larval crowding in laboratory populations of Drosophila","authors":"Srikant Venkitachalam , Amitabh Joshi","doi":"10.1016/j.jtbi.2026.112378","DOIUrl":"10.1016/j.jtbi.2026.112378","url":null,"abstract":"<div><div>The study of larval competition in laboratory populations of <em>Drosophila</em>, implemented via the crowding of larval cultures, has contributed greatly to the understanding of the ecology of competition, the evolution of larval competitive ability, and formed the basis of rigorous testing of the theory of density-dependent selection. Earlier studies led to the view that the outcomes of larval competition, and resulting evolutionary consequences of crowding-adaptation, could largely be understood by varying the starting density of individuals in a crowded culture. However, recent studies have shown that the results of adaptation to larval crowding may not be well predicted by the overall larval density (i.e., total starting individuals/total volume of food). Cultures raised at the same overall density but at different egg number and food volume combinations were shown to have different underlying density-specific fitness functions, and crowding-adaptation in each of these cultures was attained through different evolutionary trajectories as well. A recent study showed that cultures with not just the same density, but the same egg and food volume combination, achieved through food columns of differing diameter and height, could also differ greatly in fitness-related trait outcomes. In that study, the density of larvae in the feeding band (volume of food close to the surface in contact with air, to which larval feeding is largely restricted) was a very important factor in predicting the outcomes of larval competition. Given these recent findings, it is important to understand the overall role of feeding band density, and how it influences density-specific fitness functions in different kinds of crowded cultures. As the older models of larval competition are now insufficient to capture current empirical data, we constructed an individual-based simulation framework informed in part by these more recent findings, in order to better understand the evolutionary ecology and mechanistic underpinnings of larval competition, and predict robust experiments for expanding our understanding of the process of larval competition in <em>Drosophila</em>.</div></div>","PeriodicalId":54763,"journal":{"name":"Journal of Theoretical Biology","volume":"622 ","pages":"Article 112378"},"PeriodicalIF":2.0,"publicationDate":"2026-01-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146004789","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 : 2026-01-15DOI: 10.1016/j.jtbi.2026.112376
Verdiana Mustaro , Vincenzo Casolaro , Antonio Di Crescenzo
B cells are important components of the adaptive immune system, responsible for antibody production and working as antigen-presenting cells. B cells display protein receptors on their membrane, which bind with foreign antigens and process them before presenting them to T cells. In this work, we present a stochastic process modeling the dynamics of such receptors on the B cell. The model consists of a two-dimensional birth-death process having linear transition rates, where X(t) and Y(t) represent the number of free and occupied receptors, respectively. After determining the partial differential equation for the probability generating function of the process, we compute the main moments of the process, including the covariance. The transient and asymptotic behavior of the means of X(t) and Y(t) is also studied. Throughout the paper, we provide insights into the biological significance of each parameter on the system’s dynamics. In addition, we conduct a sensitivity analysis to assess how variations in the model parameters affect the first-order moments. Such analysis shows that minimal variations of the parameters representing the binding frequency of antigens and B-cell receptors, when happening in the initial instants of the process, result in noticeable alterations of the number of occupied receptors.
{"title":"On the dynamics of antigen receptors on the B-cell membrane through a two-dimensional stochastic process","authors":"Verdiana Mustaro , Vincenzo Casolaro , Antonio Di Crescenzo","doi":"10.1016/j.jtbi.2026.112376","DOIUrl":"10.1016/j.jtbi.2026.112376","url":null,"abstract":"<div><div>B cells are important components of the adaptive immune system, responsible for antibody production and working as antigen-presenting cells. B cells display protein receptors on their membrane, which bind with foreign antigens and process them before presenting them to T cells. In this work, we present a stochastic process modeling the dynamics of such receptors on the B cell. The model consists of a two-dimensional birth-death process <span><math><mstyle><mrow><mo>{</mo><mo>(</mo><mi>X</mi><mo>(</mo><mi>t</mi><mo>)</mo><mo>,</mo><mi>Y</mi><mo>(</mo><mi>t</mi><mo>)</mo><mo>)</mo><mo>,</mo><mspace></mspace><mi>t</mi><mo>≥</mo><mn>0</mn><mo>}</mo></mrow></mstyle></math></span> having linear transition rates, where <em>X</em>(<em>t</em>) and <em>Y</em>(<em>t</em>) represent the number of free and occupied receptors, respectively. After determining the partial differential equation for the probability generating function of the process, we compute the main moments of the process, including the covariance. The transient and asymptotic behavior of the means of <em>X</em>(<em>t</em>) and <em>Y</em>(<em>t</em>) is also studied. Throughout the paper, we provide insights into the biological significance of each parameter on the system’s dynamics. In addition, we conduct a sensitivity analysis to assess how variations in the model parameters affect the first-order moments. Such analysis shows that minimal variations of the parameters representing the binding frequency of antigens and B-cell receptors, when happening in the initial instants of the process, result in noticeable alterations of the number of occupied receptors.</div></div>","PeriodicalId":54763,"journal":{"name":"Journal of Theoretical Biology","volume":"622 ","pages":"Article 112376"},"PeriodicalIF":2.0,"publicationDate":"2026-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145994734","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 : 2026-01-06DOI: 10.1016/j.jtbi.2025.112349
Edwin van Leeuwen , Frank G. Sandmann , Rosalind M. Eggo , Peter J. White
Susceptibility in children is a key driver of heterogeneity in the transmission of different respiratory viruses. For example, SARS-CoV-2 is associated with low susceptibility in children, while for the influenza and respiratory syncytial viruses it is thought that children have higher susceptibility, because adults will have built up natural immunity. We modelled seasonal changes in time use and social mixing based on age-stratified contact rates using historical nationally-representative surveys. We explored changes in the reproduction number and the age distribution of infections of respiratory diseases during the early phase of an epidemic, for different assumptions of susceptibility in children aged 0-15. Across ages, the estimated R0 and the age distribution of incidence fluctuated due to changes in time use. For the scenarios where adults have acquired natural immunity through past infection R0 fell and relative incidence decreased in children aged 0-15 but increased in other ages during holiday periods. If children were less susceptible than adults these changes were less pronounced. Our modelling findings suggest that changing contacts during the holiday periods may shift the age distribution of cases from children towards adults. Given that severity and deaths rise with age for many diseases, more intergenerational mixing risks the disease moving into the more vulnerable following the holidays even if the absolute number of infections did not increase.
{"title":"Social mixing and time use throughout the year: Potential changes in disease transmission and age distribution of cases","authors":"Edwin van Leeuwen , Frank G. Sandmann , Rosalind M. Eggo , Peter J. White","doi":"10.1016/j.jtbi.2025.112349","DOIUrl":"10.1016/j.jtbi.2025.112349","url":null,"abstract":"<div><div>Susceptibility in children is a key driver of heterogeneity in the transmission of different respiratory viruses. For example, SARS-CoV-2 is associated with low susceptibility in children, while for the influenza and respiratory syncytial viruses it is thought that children have higher susceptibility, because adults will have built up natural immunity. We modelled seasonal changes in time use and social mixing based on age-stratified contact rates using historical nationally-representative surveys. We explored changes in the reproduction number and the age distribution of infections of respiratory diseases during the early phase of an epidemic, for different assumptions of susceptibility in children aged 0-15. Across ages, the estimated <em>R</em><sub>0</sub> and the age distribution of incidence fluctuated due to changes in time use. For the scenarios where adults have acquired natural immunity through past infection <em>R</em><sub>0</sub> fell and relative incidence decreased in children aged 0-15 but increased in other ages during holiday periods. If children were less susceptible than adults these changes were less pronounced. Our modelling findings suggest that changing contacts during the holiday periods may shift the age distribution of cases from children towards adults. Given that severity and deaths rise with age for many diseases, more intergenerational mixing risks the disease moving into the more vulnerable following the holidays even if the absolute number of infections did not increase.</div></div>","PeriodicalId":54763,"journal":{"name":"Journal of Theoretical Biology","volume":"622 ","pages":"Article 112349"},"PeriodicalIF":2.0,"publicationDate":"2026-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145936505","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}
A detailed understanding of biochemical networks at the molecular level is essential for studying complex cellular processes. In this paper, we provide a structural description of biochemical networks by considering individual atoms and chemical bonds. To address combinatorial complexity, we introduce a well-established approach to group similar types of information within biochemical networks. A conserved moiety is a set of atoms whose association is invariant across all reactions in a network and arises from the decomposition of the reaction network. A reacting moiety is a set of bonds that are either broken, formed, or undergo a change in bond order in at least one reaction in the network and arises from the decomposition of the molecular network. By mathematically identifying these moieties, and by developing the link between these two decompositions, we establish the biological significance of conserved and reacting moieties according to the mathematical properties of the stoichiometric matrix. We also present a novel decomposition of the stoichiometric matrix based on conserved moieties. This approach establishes a clear connection between graph theory, linear algebra, and biological interpretation, thus offering new perspectives for the study of chemical reaction networks.
{"title":"Characterisation of conserved and reacting moieties in chemical reaction networks","authors":"Hadjar Rahou , Hulda S. Haraldsdóttir , Filippo Martinelli , Ines Thiele , Ronan M.T. Fleming","doi":"10.1016/j.jtbi.2025.112348","DOIUrl":"10.1016/j.jtbi.2025.112348","url":null,"abstract":"<div><div>A detailed understanding of biochemical networks at the molecular level is essential for studying complex cellular processes. In this paper, we provide a structural description of biochemical networks by considering individual atoms and chemical bonds. To address combinatorial complexity, we introduce a well-established approach to group similar types of information within biochemical networks. A conserved moiety is a set of atoms whose association is invariant across all reactions in a network and arises from the decomposition of the reaction network. A reacting moiety is a set of bonds that are either broken, formed, or undergo a change in bond order in at least one reaction in the network and arises from the decomposition of the molecular network. By mathematically identifying these moieties, and by developing the link between these two decompositions, we establish the biological significance of conserved and reacting moieties according to the mathematical properties of the stoichiometric matrix. We also present a novel decomposition of the stoichiometric matrix based on conserved moieties. This approach establishes a clear connection between graph theory, linear algebra, and biological interpretation, thus offering new perspectives for the study of chemical reaction networks.</div></div>","PeriodicalId":54763,"journal":{"name":"Journal of Theoretical Biology","volume":"621 ","pages":"Article 112348"},"PeriodicalIF":2.0,"publicationDate":"2026-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145907268","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 : 2025-12-31DOI: 10.1016/j.jtbi.2025.112355
Tobias Dieselhorst, Johannes Berg
Phylogenetic trees represent the evolutionary relationships between extant lineages, where extinct or non-sampled lineages are omitted. Extending the work of Stadler and collaborators, this paper focuses on the branch lengths in phylogenetic trees arising under a constant-rate birth-death model. We derive branch length distributions of phylogenetic branches with and without random sampling of individuals of the extant population under two distinct statistical scenarios: a fixed age of the birth-death process and a fixed number of individuals at the time of observation. We find that branches connected to the tree leaves (pendant branches) and branches in the interior of the tree behave very differently under sampling; pendant branches grow longer without limit as the sampling probability is decreased, whereas the interior branch lengths quickly reach an asymptotic distribution that does not depend on the sampling probability.
{"title":"Branch length statistics in phylogenetic trees under constant-rate birth-death dynamics","authors":"Tobias Dieselhorst, Johannes Berg","doi":"10.1016/j.jtbi.2025.112355","DOIUrl":"10.1016/j.jtbi.2025.112355","url":null,"abstract":"<div><div>Phylogenetic trees represent the evolutionary relationships between extant lineages, where extinct or non-sampled lineages are omitted. Extending the work of Stadler and collaborators, this paper focuses on the branch lengths in phylogenetic trees arising under a constant-rate birth-death model. We derive branch length distributions of phylogenetic branches with and without random sampling of individuals of the extant population under two distinct statistical scenarios: a fixed age of the birth-death process and a fixed number of individuals at the time of observation. We find that branches connected to the tree leaves (pendant branches) and branches in the interior of the tree behave very differently under sampling; pendant branches grow longer without limit as the sampling probability is decreased, whereas the interior branch lengths quickly reach an asymptotic distribution that does not depend on the sampling probability.</div></div>","PeriodicalId":54763,"journal":{"name":"Journal of Theoretical Biology","volume":"621 ","pages":"Article 112355"},"PeriodicalIF":2.0,"publicationDate":"2025-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145893478","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 : 2025-12-30DOI: 10.1016/j.jtbi.2025.112367
James Austin Orgeron, Malbor Asllani
Habitat fragmentation, often driven by human activities, alters ecological landscapes by disrupting connectivity and reshaping species interactions. In such fragmented environments, habitats can be modeled as networks, where individuals disperse across interconnected patches. We consider an intraspecific competition model, where individuals compete for space while dispersing according to a nonlinear random walk, capturing the heterogeneity of the network. The interplay between asymmetric competition, dispersal dynamics, and spatial heterogeneity leads to nonuniform species distribution: individuals with stronger competitive traits accumulate in central (hub) habitat patches, while those with weaker traits are displaced toward the periphery. We provide analytical insights into this mechanism, supported by numerical simulations, demonstrating how competition and spatial structure jointly influence species segregation. In the large-network limit, this effect becomes extreme, with dominant individuals disappearing from peripheral patches and subordinate ones from central regions, establishing spatial segregation. This pattern may act as a potential precursor to both speciation and diversity, as physical separation can reinforce divergence within the population over time and potentially support coexistence at the landscape scale.
{"title":"Habitat fragmentation promotes spatial scale separation under resource competition","authors":"James Austin Orgeron, Malbor Asllani","doi":"10.1016/j.jtbi.2025.112367","DOIUrl":"10.1016/j.jtbi.2025.112367","url":null,"abstract":"<div><div>Habitat fragmentation, often driven by human activities, alters ecological landscapes by disrupting connectivity and reshaping species interactions. In such fragmented environments, habitats can be modeled as networks, where individuals disperse across interconnected patches. We consider an intraspecific competition model, where individuals compete for space while dispersing according to a nonlinear random walk, capturing the heterogeneity of the network. The interplay between asymmetric competition, dispersal dynamics, and spatial heterogeneity leads to nonuniform species distribution: individuals with stronger competitive traits accumulate in central (hub) habitat patches, while those with weaker traits are displaced toward the periphery. We provide analytical insights into this mechanism, supported by numerical simulations, demonstrating how competition and spatial structure jointly influence species segregation. In the large-network limit, this effect becomes extreme, with dominant individuals disappearing from peripheral patches and subordinate ones from central regions, establishing spatial segregation. This pattern may act as a potential precursor to both speciation and diversity, as physical separation can reinforce divergence within the population over time and potentially support coexistence at the landscape scale.</div></div>","PeriodicalId":54763,"journal":{"name":"Journal of Theoretical Biology","volume":"621 ","pages":"Article 112367"},"PeriodicalIF":2.0,"publicationDate":"2025-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145890173","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}
Pedunculopontine nucleus (PPN) has extensive projections with numerous brain tissues, and it has become an important target for clinical intervention in neurological diseases. In this study, we integrate the PPN into a typical corticothalamic-basal ganglia dynamical model to systematically investigate the mechanisms by which PPN-related projections regulate spike-and-wave discharges (SWDs) in absence seizures. We find that the glutamatergic (GLU) cortical-PPN projection can significantly control SWDs, through signal transmission via two GLU PPN-thalamic pathways. The coupling weights in PPN-thalamic pathways have a critical impact on the control pattern. We observe that bidirectional suppression of SWDs may be achieved by modulating the coupling strength in the GLU PPN-cortical projection. Furthermore, we analyze that, although from a computational perspective, the GLU PPN-substantia nigra pars reticulata (SNr) projection can potentially achieve control over SWDs through the SNr-thalamic pathways, this control method might be biologically challenging to implement. Finally, we observe that the reciprocal GLU projections between the PPN and the subthalamic nucleus (STN) play a regulatory role in the activity of basal ganglia, yet they do not exhibit a significant suppressive effect on SWDs. For the first time, we emphasize from a computational perspective that is the direct communication between the PPN and the cerebral cortex, rather than the communication between the PPN and the basal ganglia, might have a significant effect on the regulation of absence seizures. As a crucial component of the brainstem, the findings in this paper further elucidate the potential functions of the PPN in regulating brain activity.
{"title":"Deciphering the modulatory role of direct pedunculopontine nucleus-cortical circuitry in absence seizure dynamics: A computational study","authors":"Bing Hu, Jiaqin Peng, Wencan Li, Yuhan Xiao, Ningmin Zhu","doi":"10.1016/j.jtbi.2025.112366","DOIUrl":"10.1016/j.jtbi.2025.112366","url":null,"abstract":"<div><div>Pedunculopontine nucleus (PPN) has extensive projections with numerous brain tissues, and it has become an important target for clinical intervention in neurological diseases. In this study, we integrate the PPN into a typical corticothalamic-basal ganglia dynamical model to systematically investigate the mechanisms by which PPN-related projections regulate spike-and-wave discharges (SWDs) in absence seizures. We find that the glutamatergic (GLU) cortical-PPN projection can significantly control SWDs, through signal transmission via two GLU PPN-thalamic pathways. The coupling weights in PPN-thalamic pathways have a critical impact on the control pattern. We observe that bidirectional suppression of SWDs may be achieved by modulating the coupling strength in the GLU PPN-cortical projection. Furthermore, we analyze that, although from a computational perspective, the GLU PPN-substantia nigra pars reticulata (SNr) projection can potentially achieve control over SWDs through the SNr-thalamic pathways, this control method might be biologically challenging to implement. Finally, we observe that the reciprocal GLU projections between the PPN and the subthalamic nucleus (STN) play a regulatory role in the activity of basal ganglia, yet they do not exhibit a significant suppressive effect on SWDs. For the first time, we emphasize from a computational perspective that is the direct communication between the PPN and the cerebral cortex, rather than the communication between the PPN and the basal ganglia, might have a significant effect on the regulation of absence seizures. As a crucial component of the brainstem, the findings in this paper further elucidate the potential functions of the PPN in regulating brain activity.</div></div>","PeriodicalId":54763,"journal":{"name":"Journal of Theoretical Biology","volume":"621 ","pages":"Article 112366"},"PeriodicalIF":2.0,"publicationDate":"2025-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145879582","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 : 2025-12-27DOI: 10.1016/j.jtbi.2025.112347
Yihan Liu , David J. Warne , Matthew J. Simpson
Sensitivity analysis characterises input–output relationships for mathematical models, and has been widely applied to deterministic models across many applications in the life sciences. In contrast, sensitivity analysis for stochastic models has received less attention, with most previous work focusing on well-mixed, non-spatial problems. For explicit spatio-temporal stochastic models, such as random walk models (RWMs), sensitivity analysis has received far less attention. Here we present a new type of sensitivity analysis, called parameter-wise prediction, for two types of biologically-motivated and computationally expensive RWMs. To overcome the limitations of directly analysing stochastic simulations, we employ continuum-limit partial differential equation (PDE) descriptions as surrogate models, and we link these efficient surrogate descriptions to the RWMs using a range of biophysically-motivated measurement error models. Our approach is likelihood-based, which means that we also consider likelihood-based parameter estimation and identifiability analysis along with parameter sensitivity. The new approach is presented for two important classes of lattice-based RWM including a classical model where crowding effects are neglected, and an exclusion process model that explicitly incorporates crowding. Our workflow illustrates how different process models can be combined with different measurement error models to reveal how each parameter impacts the outcome of the expensive stochastic simulation. Open-access software to replicate all results is available on GitHub (Liu, 2025).
{"title":"Parameter-wise predictions and sensitivity analysis for random walk models in the life sciences","authors":"Yihan Liu , David J. Warne , Matthew J. Simpson","doi":"10.1016/j.jtbi.2025.112347","DOIUrl":"10.1016/j.jtbi.2025.112347","url":null,"abstract":"<div><div>Sensitivity analysis characterises input–output relationships for mathematical models, and has been widely applied to deterministic models across many applications in the life sciences. In contrast, sensitivity analysis for stochastic models has received less attention, with most previous work focusing on well-mixed, non-spatial problems. For explicit spatio-temporal stochastic models, such as random walk models (RWMs), sensitivity analysis has received far less attention. Here we present a new type of sensitivity analysis, called <em>parameter-wise prediction</em>, for two types of biologically-motivated and computationally expensive RWMs. To overcome the limitations of directly analysing stochastic simulations, we employ continuum-limit partial differential equation (PDE) descriptions as surrogate models, and we link these efficient surrogate descriptions to the RWMs using a range of biophysically-motivated <em>measurement error models</em>. Our approach is likelihood-based, which means that we also consider likelihood-based parameter estimation and identifiability analysis along with parameter sensitivity. The new approach is presented for two important classes of lattice-based RWM including a classical model where crowding effects are neglected, and an exclusion process model that explicitly incorporates crowding. Our workflow illustrates how different process models can be combined with different measurement error models to reveal how each parameter impacts the outcome of the expensive stochastic simulation. Open-access software to replicate all results is available on <span><span>GitHub</span><svg><path></path></svg></span> (Liu, 2025).</div></div>","PeriodicalId":54763,"journal":{"name":"Journal of Theoretical Biology","volume":"621 ","pages":"Article 112347"},"PeriodicalIF":2.0,"publicationDate":"2025-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145859279","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}
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