Second-Order Effects of Chemotherapy Pharmacodynamics and Pharmacokinetics on Tumor Regression and Cachexia
Bull Math Biol. 2024 Mar 28;86(5):47. doi: 10.1007/s11538-024-01278-0.ABSTRACTDrug dose response curves are ubiquitous in cancer biology, but these curves are often used to measure differential response in first-order effects: the effectiveness of increasing the cumulative dose delivered. In contrast, second-order effects (the variance of drug dose) are often ignored. Knowledge of second-order effects may improve the design of chemotherapy scheduling protocols, leading to improvements in tumor response without changing the total dose delivered. By considering treatment schedules with identical cumulative dose delivered, we...
Source: Bulletin of Mathematical Biology - March 28, 2024 Category: Bioinformatics Authors: Luke Pierik Patricia McDonald Alexander R A Anderson Jeffrey West Source Type: research
Second-Order Effects of Chemotherapy Pharmacodynamics and Pharmacokinetics on Tumor Regression and Cachexia
Bull Math Biol. 2024 Mar 28;86(5):47. doi: 10.1007/s11538-024-01278-0.ABSTRACTDrug dose response curves are ubiquitous in cancer biology, but these curves are often used to measure differential response in first-order effects: the effectiveness of increasing the cumulative dose delivered. In contrast, second-order effects (the variance of drug dose) are often ignored. Knowledge of second-order effects may improve the design of chemotherapy scheduling protocols, leading to improvements in tumor response without changing the total dose delivered. By considering treatment schedules with identical cumulative dose delivered, we...
Source: Bulletin of Mathematical Biology - March 28, 2024 Category: Bioinformatics Authors: Luke Pierik Patricia McDonald Alexander R A Anderson Jeffrey West Source Type: research
Second-Order Effects of Chemotherapy Pharmacodynamics and Pharmacokinetics on Tumor Regression and Cachexia
Bull Math Biol. 2024 Mar 28;86(5):47. doi: 10.1007/s11538-024-01278-0.ABSTRACTDrug dose response curves are ubiquitous in cancer biology, but these curves are often used to measure differential response in first-order effects: the effectiveness of increasing the cumulative dose delivered. In contrast, second-order effects (the variance of drug dose) are often ignored. Knowledge of second-order effects may improve the design of chemotherapy scheduling protocols, leading to improvements in tumor response without changing the total dose delivered. By considering treatment schedules with identical cumulative dose delivered, we...
Source: Bulletin of Mathematical Biology - March 28, 2024 Category: Bioinformatics Authors: Luke Pierik Patricia McDonald Alexander R A Anderson Jeffrey West Source Type: research
Inferring Parameters of Pyramidal Neuron Excitability in Mouse Models of Alzheimer's Disease Using Biophysical Modeling and Deep Learning
Bull Math Biol. 2024 Mar 25;86(5):46. doi: 10.1007/s11538-024-01273-5.ABSTRACTAlzheimer's disease (AD) is believed to occur when abnormal amounts of the proteins amyloid beta and tau aggregate in the brain, resulting in a progressive loss of neuronal function. Hippocampal neurons in transgenic mice with amyloidopathy or tauopathy exhibit altered intrinsic excitability properties. We used deep hybrid modeling (DeepHM), a recently developed parameter inference technique that combines deep learning with biophysical modeling, to map experimental data recorded from hippocampal CA1 neurons in transgenic AD mice and age-matched w...
Source: Bulletin of Mathematical Biology - March 26, 2024 Category: Bioinformatics Authors: Soheil Saghafi Timothy Rumbell Viatcheslav Gurev James Kozloski Francesco Tamagnini Kyle C A Wedgwood Casey O Diekman Source Type: research
Inferring Parameters of Pyramidal Neuron Excitability in Mouse Models of Alzheimer's Disease Using Biophysical Modeling and Deep Learning
Bull Math Biol. 2024 Mar 25;86(5):46. doi: 10.1007/s11538-024-01273-5.ABSTRACTAlzheimer's disease (AD) is believed to occur when abnormal amounts of the proteins amyloid beta and tau aggregate in the brain, resulting in a progressive loss of neuronal function. Hippocampal neurons in transgenic mice with amyloidopathy or tauopathy exhibit altered intrinsic excitability properties. We used deep hybrid modeling (DeepHM), a recently developed parameter inference technique that combines deep learning with biophysical modeling, to map experimental data recorded from hippocampal CA1 neurons in transgenic AD mice and age-matched w...
Source: Bulletin of Mathematical Biology - March 26, 2024 Category: Bioinformatics Authors: Soheil Saghafi Timothy Rumbell Viatcheslav Gurev James Kozloski Francesco Tamagnini Kyle C A Wedgwood Casey O Diekman Source Type: research
Enumeration of Rooted Binary Unlabeled Galled Trees
Bull Math Biol. 2024 Mar 22;86(5):45. doi: 10.1007/s11538-024-01270-8.ABSTRACTRooted binary galled trees generalize rooted binary trees to allow a restricted class of cycles, known as galls. We build upon the Wedderburn-Etherington enumeration of rooted binary unlabeled trees with n leaves to enumerate rooted binary unlabeled galled trees with n leaves, also enumerating rooted binary unlabeled galled trees with n leaves and g galls, 0 ⩽ g ⩽ ⌊ n - 1 2 ⌋ . The enumerations rely on a recursive decomposition that considers subtrees descended from the nodes of a gall, adopting a restriction on galls that amounts to con...
Source: Bulletin of Mathematical Biology - March 23, 2024 Category: Bioinformatics Authors: Lily Agranat-Tamir Shaili Mathur Noah A Rosenberg Source Type: research
Enumeration of Rooted Binary Unlabeled Galled Trees
Bull Math Biol. 2024 Mar 22;86(5):45. doi: 10.1007/s11538-024-01270-8.ABSTRACTRooted binary galled trees generalize rooted binary trees to allow a restricted class of cycles, known as galls. We build upon the Wedderburn-Etherington enumeration of rooted binary unlabeled trees with n leaves to enumerate rooted binary unlabeled galled trees with n leaves, also enumerating rooted binary unlabeled galled trees with n leaves and g galls, 0 ⩽ g ⩽ ⌊ n - 1 2 ⌋ . The enumerations rely on a recursive decomposition that considers subtrees descended from the nodes of a gall, adopting a restriction on galls that amounts to con...
Source: Bulletin of Mathematical Biology - March 23, 2024 Category: Bioinformatics Authors: Lily Agranat-Tamir Shaili Mathur Noah A Rosenberg Source Type: research
Enumeration of Rooted Binary Unlabeled Galled Trees
Bull Math Biol. 2024 Mar 22;86(5):45. doi: 10.1007/s11538-024-01270-8.ABSTRACTRooted binary galled trees generalize rooted binary trees to allow a restricted class of cycles, known as galls. We build upon the Wedderburn-Etherington enumeration of rooted binary unlabeled trees with n leaves to enumerate rooted binary unlabeled galled trees with n leaves, also enumerating rooted binary unlabeled galled trees with n leaves and g galls, 0 ⩽ g ⩽ ⌊ n - 1 2 ⌋ . The enumerations rely on a recursive decomposition that considers subtrees descended from the nodes of a gall, adopting a restriction on galls that amounts to con...
Source: Bulletin of Mathematical Biology - March 23, 2024 Category: Bioinformatics Authors: Lily Agranat-Tamir Shaili Mathur Noah A Rosenberg Source Type: research
NIAID/SMB Workshop on Multiscale Modeling of Infectious and Immune-Mediated Diseases
Bull Math Biol. 2024 Mar 21;86(5):44. doi: 10.1007/s11538-024-01276-2.ABSTRACTOn July 19th, 2023, the National Institute of Allergy and Infectious Diseases co-organized a workshop with the Society of Mathematical Biology, with the authors of this paper as the organizing committee. The workshop, "Bridging multiscale modeling and practical clinical applications in infectious diseases" sought to create an environment for mathematical modelers, statisticians, and infectious disease researchers and clinicians to exchange ideas and perspectives.PMID:38512541 | PMC:PMC10957590 | DOI:10.1007/s11538-024-01276-2 (Source: Bulletin of...
Source: Bulletin of Mathematical Biology - March 21, 2024 Category: Bioinformatics Authors: Reed S Shabman Morgan Craig Reinhard Laubenbacher Daniel Reeves Liliana L Brown Source Type: research
NIAID/SMB Workshop on Multiscale Modeling of Infectious and Immune-Mediated Diseases
Bull Math Biol. 2024 Mar 21;86(5):44. doi: 10.1007/s11538-024-01276-2.ABSTRACTOn July 19th, 2023, the National Institute of Allergy and Infectious Diseases co-organized a workshop with the Society of Mathematical Biology, with the authors of this paper as the organizing committee. The workshop, "Bridging multiscale modeling and practical clinical applications in infectious diseases" sought to create an environment for mathematical modelers, statisticians, and infectious disease researchers and clinicians to exchange ideas and perspectives.PMID:38512541 | DOI:10.1007/s11538-024-01276-2 (Source: Bulletin of Mathematical Biology)
Source: Bulletin of Mathematical Biology - March 21, 2024 Category: Bioinformatics Authors: Reed S Shabman Morgan Craig Reinhard Laubenbacher Daniel Reeves Liliana L Brown Source Type: research
Impact of Resistance on Therapeutic Design: A Moran Model of Cancer Growth
In this study, a Moran process is used to capture stochastic mutations arising in cancer cells, inferring treatment resistance. The model is used to predict the probability of cancer recurrence given varying treatment modalities. The simulations predict that sustained-low dose therapies would be virtually ineffective for a cancer with a non-negligible probability of developing a sub-clone with resistance tendencies. Furthermore, calibrating the model to in vivo measurements for breast cancer treatment with Herceptin, the model suggests that standard treatment regimens are ineffective in this mouse model. Using a simple Mor...
Source: Bulletin of Mathematical Biology - March 19, 2024 Category: Bioinformatics Authors: Mason S Lacy Adrianne L Jenner Source Type: research
Impact of Resistance on Therapeutic Design: A Moran Model of Cancer Growth
In this study, a Moran process is used to capture stochastic mutations arising in cancer cells, inferring treatment resistance. The model is used to predict the probability of cancer recurrence given varying treatment modalities. The simulations predict that sustained-low dose therapies would be virtually ineffective for a cancer with a non-negligible probability of developing a sub-clone with resistance tendencies. Furthermore, calibrating the model to in vivo measurements for breast cancer treatment with Herceptin, the model suggests that standard treatment regimens are ineffective in this mouse model. Using a simple Mor...
Source: Bulletin of Mathematical Biology - March 19, 2024 Category: Bioinformatics Authors: Mason S Lacy Adrianne L Jenner Source Type: research
Impact of Resistance on Therapeutic Design: A Moran Model of Cancer Growth
In this study, a Moran process is used to capture stochastic mutations arising in cancer cells, inferring treatment resistance. The model is used to predict the probability of cancer recurrence given varying treatment modalities. The simulations predict that sustained-low dose therapies would be virtually ineffective for a cancer with a non-negligible probability of developing a sub-clone with resistance tendencies. Furthermore, calibrating the model to in vivo measurements for breast cancer treatment with Herceptin, the model suggests that standard treatment regimens are ineffective in this mouse model. Using a simple Mor...
Source: Bulletin of Mathematical Biology - March 19, 2024 Category: Bioinformatics Authors: Mason S Lacy Adrianne L Jenner Source Type: research
Modeling of Mouse Experiments Suggests that Optimal Anti-Hormonal Treatment for Breast Cancer is Diet-Dependent
Bull Math Biol. 2024 Mar 18;86(4):42. doi: 10.1007/s11538-023-01253-1.ABSTRACTEstrogen receptor positive breast cancer is frequently treated with anti-hormonal treatment such as aromatase inhibitors (AI). Interestingly, a high body mass index has been shown to have a negative impact on AI efficacy, most likely due to disturbances in steroid metabolism and adipokine production. Here, we propose a mathematical model based on a system of ordinary differential equations to investigate the effect of high-fat diet on tumor growth. We inform the model with data from mouse experiments, where the animals are fed with high-fat or co...
Source: Bulletin of Mathematical Biology - March 18, 2024 Category: Bioinformatics Authors: Tu ğba Akman Lisa M Arendt J ürgen Geisler Vessela N Kristensen Arnoldo Frigessi Alvaro K öhn-Luque Source Type: research
< mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" > < mml:msub > < mml:mi > R < /mml:mi > < mml:mn > 0 < /mml:mn > < /mml:msub > < /mml:math > May Not Tell Us Everything: Transient Disease Dynamics of Some SIR Models Over Patchy Environments
Bull Math Biol. 2024 Mar 15;86(4):41. doi: 10.1007/s11538-024-01271-7.ABSTRACTThis paper examines the short-term or transient dynamics of SIR infectious disease models in patch environments. We employ reactivity of an equilibrium and amplification rates, concepts from ecology, to analyze how dispersals/travels between patches, spatial heterogeneity, and other disease-related parameters impact short-term dynamics. Our findings reveal that in certain scenarios, due to the impact of spatial heterogeneity and the dispersals, the short-term disease dynamics over a patch environment may disagree with the long-term disease dynami...
Source: Bulletin of Mathematical Biology - March 16, 2024 Category: Bioinformatics Authors: Ao Li Xingfu Zou Source Type: research
