Unraveling the forces shaping foraging dynamics in harvester ant colonies: Recruitment efficiency and environmental variability
Math Biosci. 2024 Mar 22;371:109182. doi: 10.1016/j.mbs.2024.109182. Online ahead of print.ABSTRACTThe collective foraging behavior of ant colonies is a central focus in behavioral ecology. This paper enhances the classical model of foraging dynamics in harvester ant colonies by introducing a nonlinear recruitment rate and considering environmental variability. Initially, we analyze the existence and stability of steady states in the deterministic model. The results suggest that an increase in mean recruitment time can reduce the foraging threshold, leading to both forward and backward bifurcations. Furthermore, both avera...
Source: Mathematical Biosciences - March 23, 2024 Category: Statistics Authors: Chenbo Liu Tao Feng Source Type: research
Mathematical generation of data-driven hippocampal CA1 pyramidal neurons and interneurons copies via A-GLIF models for large-scale networks covering the experimental variability range
Math Biosci. 2024 Mar 21:109179. doi: 10.1016/j.mbs.2024.109179. Online ahead of print.ABSTRACTEfficient and accurate large-scale networks are a fundamental tool in modelling brain areas, to advance our understanding of neuronal dynamics. However, their implementation faces two key issues: computational efficiency and heterogeneity. Computational efficiency is achieved using simplified neurons, whereas there are no practical solutions available to solve the problem of reproducing in a large-scale network the experimentally observed heterogeneity of the intrinsic properties of neurons. This is important, because the use of ...
Source: Mathematical Biosciences - March 23, 2024 Category: Statistics Authors: A Marasco C Tribuzi A Iuorio M Migliore Source Type: research
Unraveling the forces shaping foraging dynamics in harvester ant colonies: Recruitment efficiency and environmental variability
Math Biosci. 2024 Mar 21:109182. doi: 10.1016/j.mbs.2024.109182. Online ahead of print.ABSTRACTThe collective foraging behavior of ant colonies is a central focus in behavioral ecology. This paper enhances the classical model of foraging dynamics in harvester ant colonies by introducing a nonlinear recruitment rate and considering environmental variability. Initially, we analyze the existence and stability of steady states in the deterministic model. The results suggest that an increase in mean recruitment time can reduce the foraging threshold, leading to both forward and backward bifurcations. Furthermore, both average r...
Source: Mathematical Biosciences - March 23, 2024 Category: Statistics Authors: Chenbo Liu Tao Feng Source Type: research
Modelling remission from overweight type 2 diabetes reveals how altering advice may counter relapse
This study leads to the suggestion that type 2 diabetes remission guidelines be given in terms of model parameters, not variables; that is, the patient should adhere to a given nutrition and exercise plan, rather than achieve a certain subset of variable values. The model predicts that calorie restriction, not weight loss, initiates remission from type 2 diabetes; and that advice of the form 'adhere to the diet and exercise plan' rather than 'achieve a certain weight loss' may help counter relapse.PMID:38518862 | DOI:10.1016/j.mbs.2024.109180 (Source: Mathematical Biosciences)
Source: Mathematical Biosciences - March 22, 2024 Category: Statistics Authors: Catherine Z W Hassell Sweatman Source Type: research
A mathematical model for the within-host (re)infection dynamics of SARS-CoV-2
We present a mathematical model, which not only describes the SARS-CoV-2 infection dynamics during the acute infection phase, but extends current approaches by also recapitulating clinically observed long-term post-acute infection effects, such as the recovery of the number of susceptible epithelial cells to an initial pre-infection homeostatic level, a permanent and full clearance of the infection within the individual, immune waning, and the formation of long-term immune capacity levels after infection. Finally, we used our model and its description of the long-term post-acute infection dynamics to explore reinfection sc...
Source: Mathematical Biosciences - March 15, 2024 Category: Statistics Authors: Lea Schuh Peter V Markov Vladimir M Veliov Nikolaos I Stilianakis Source Type: research
A mathematical model for the within-host (re)infection dynamics of SARS-CoV-2
We present a mathematical model, which not only describes the SARS-CoV-2 infection dynamics during the acute infection phase, but extends current approaches by also recapitulating clinically observed long-term post-acute infection effects, such as the recovery of the number of susceptible epithelial cells to an initial pre-infection homeostatic level, a permanent and full clearance of the infection within the individual, immune waning, and the formation of long-term immune capacity levels after infection. Finally, we used our model and its description of the long-term post-acute infection dynamics to explore reinfection sc...
Source: Mathematical Biosciences - March 15, 2024 Category: Statistics Authors: Lea Schuh Peter V Markov Vladimir M Veliov Nikolaos I Stilianakis Source Type: research
A mathematical model for the within-host (re)infection dynamics of SARS-CoV-2
We present a mathematical model, which not only describes the SARS-CoV-2 infection dynamics during the acute infection phase, but extends current approaches by also recapitulating clinically observed long-term post-acute infection effects, such as the recovery of the number of susceptible epithelial cells to an initial pre-infection homeostatic level, a permanent and full clearance of the infection within the individual, immune waning, and the formation of long-term immune capacity levels after infection. Finally, we used our model and its description of the long-term post-acute infection dynamics to explore reinfection sc...
Source: Mathematical Biosciences - March 15, 2024 Category: Statistics Authors: Lea Schuh Peter V Markov Vladimir M Veliov Nikolaos I Stilianakis Source Type: research
A mathematical model for the within-host (re)infection dynamics of SARS-CoV-2
We present a mathematical model, which not only describes the SARS-CoV-2 infection dynamics during the acute infection phase, but extends current approaches by also recapitulating clinically observed long-term post-acute infection effects, such as the recovery of the number of susceptible epithelial cells to an initial pre-infection homeostatic level, a permanent and full clearance of the infection within the individual, immune waning, and the formation of long-term immune capacity levels after infection. Finally, we used our model and its description of the long-term post-acute infection dynamics to explore reinfection sc...
Source: Mathematical Biosciences - March 15, 2024 Category: Statistics Authors: Lea Schuh Peter V Markov Vladimir M Veliov Nikolaos I Stilianakis Source Type: research
A mathematical model for the within-host (re)infection dynamics of SARS-CoV-2
We present a mathematical model, which not only describes the SARS-CoV-2 infection dynamics during the acute infection phase, but extends current approaches by also recapitulating clinically observed long-term post-acute infection effects, such as the recovery of the number of susceptible epithelial cells to an initial pre-infection homeostatic level, a permanent and full clearance of the infection within the individual, immune waning, and the formation of long-term immune capacity levels after infection. Finally, we used our model and its description of the long-term post-acute infection dynamics to explore reinfection sc...
Source: Mathematical Biosciences - March 15, 2024 Category: Statistics Authors: Lea Schuh Peter V Markov Vladimir M Veliov Nikolaos I Stilianakis Source Type: research
A mathematical model for the within-host (re)infection dynamics of SARS-CoV-2
We present a mathematical model, which not only describes the SARS-CoV-2 infection dynamics during the acute infection phase, but extends current approaches by also recapitulating clinically observed long-term post-acute infection effects, such as the recovery of the number of susceptible epithelial cells to an initial pre-infection homeostatic level, a permanent and full clearance of the infection within the individual, immune waning, and the formation of long-term immune capacity levels after infection. Finally, we used our model and its description of the long-term post-acute infection dynamics to explore reinfection sc...
Source: Mathematical Biosciences - March 15, 2024 Category: Statistics Authors: Lea Schuh Peter V Markov Vladimir M Veliov Nikolaos I Stilianakis Source Type: research
Mathematical modeling of combined therapies for treating tumor drug resistance
Math Biosci. 2024 Mar 11;371:109170. doi: 10.1016/j.mbs.2024.109170. Online ahead of print.ABSTRACTDrug resistance is one of the most intractable issues to the targeted therapy for cancer diseases. To explore effective combination therapy schemes, we propose a mathematical model to study the effects of different treatment schemes on the dynamics of cancer cells. Then we characterize the dynamical behavior of the model by finding the equilibrium points and exploring their local stability. Lyapunov functions are constructed to investigate the global asymptotic stability of the model equilibria. Numerical simulations are carr...
Source: Mathematical Biosciences - March 11, 2024 Category: Statistics Authors: Kangbo Bao Guizhen Liang Tianhai Tian Xinan Zhang Source Type: research
Mathematical modeling of combined therapies for treating tumor drug resistance
Math Biosci. 2024 Mar 11;371:109170. doi: 10.1016/j.mbs.2024.109170. Online ahead of print.ABSTRACTDrug resistance is one of the most intractable issues to the targeted therapy for cancer diseases. To explore effective combination therapy schemes, we propose a mathematical model to study the effects of different treatment schemes on the dynamics of cancer cells. Then we characterize the dynamical behavior of the model by finding the equilibrium points and exploring their local stability. Lyapunov functions are constructed to investigate the global asymptotic stability of the model equilibria. Numerical simulations are carr...
Source: Mathematical Biosciences - March 11, 2024 Category: Statistics Authors: Kangbo Bao Guizhen Liang Tianhai Tian Xinan Zhang Source Type: research
Mathematical modeling of combined therapies for treating tumor drug resistance
Math Biosci. 2024 Mar 9:109170. doi: 10.1016/j.mbs.2024.109170. Online ahead of print.ABSTRACTDrug resistance is one of the most intractable issues to the targeted therapy for cancer diseases. To explore effective combination therapy schemes, we propose a mathematical model to study the effects of different treatment schemes on the dynamics of cancer cells. Then we characterize the dynamical behavior of the model by finding the equilibrium points and exploring their local stability. Lyapunov functions are constructed to investigate the global asymptotic stability of the model equilibria. Numerical simulations are carried o...
Source: Mathematical Biosciences - March 11, 2024 Category: Statistics Authors: Kangbo Bao Guizhen Liang Tianhai Tian Xinan Zhang Source Type: research
Mathematical modeling of combined therapies for treating tumor drug resistance
Math Biosci. 2024 Mar 9:109170. doi: 10.1016/j.mbs.2024.109170. Online ahead of print.ABSTRACTDrug resistance is one of the most intractable issues to the targeted therapy for cancer diseases. To explore effective combination therapy schemes, we propose a mathematical model to study the effects of different treatment schemes on the dynamics of cancer cells. Then we characterize the dynamical behavior of the model by finding the equilibrium points and exploring their local stability. Lyapunov functions are constructed to investigate the global asymptotic stability of the model equilibria. Numerical simulations are carried o...
Source: Mathematical Biosciences - March 11, 2024 Category: Statistics Authors: Kangbo Bao Guizhen Liang Tianhai Tian Xinan Zhang Source Type: research
Structural instability and linear allocation control in generalized models of substance use disorder
Math Biosci. 2024 Mar 2;371:109169. doi: 10.1016/j.mbs.2024.109169. Online ahead of print.ABSTRACTSubstance use disorder (SUD) is a complex disease involving nontrivial biological, psychological, environmental, and social factors. While many mathematical studies have proposed compartmental models for SUD, almost all of these exclusively model new cases as the result of an infectious process, neglecting any SUD that was primarily developed in social isolation. While these decisions were likely made to facilitate mathematical analysis, isolated SUD development is critical for the most common substances of abuse today, includ...
Source: Mathematical Biosciences - March 4, 2024 Category: Statistics Authors: Leigh B Pearcy Suzanne Lenhart W Christopher Strickland Source Type: research
