Mathematical modeling for women's health : collaborative workshop for women in mathematical biology
Ashlee N. Ford Versypt, Rebecca A. Segal, Suzanne S. Sindi, editors
Bok · Engelsk · 2024
| Medvirkende | |
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| Omfang | v, 240 sider : illustrasjoner
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| Opplysninger | Bidrag fra Collaborative Workshop for Women in Mathematical Biology, avholdt i Minnetonka, Minneapolis, 20.-24. juni 2022. - 3.4 Variability in Each Drug's Maximal Effect Drives Heterogeneity in Outcomes -- 3.5 Examining the Long-Term Effect of Variation on the Combination Protocol -- 4 Discussion -- Supplementary Information -- Analysis of the Two Cell Line Model Dynamics -- References -- Towards a Mathematical Understanding of Ventilator-Induced Lung Injury in Preterm Rat Pups -- 1 Introduction -- 2 Methods -- 2.1 Experimental Data -- 2.2 Reduced Compartmental Model of Pressure-Volume Dynamics -- 2.2.1 State Equations -- 2.2.2 Constitutive Equations -- 2.2.3 Model Formulation -- 2.3 Sensitivity Analysis -- 2.3.1 Morris Effects Analysis -- 2.3.2 Local Sensitivity Analysis -- 2.4 Optimization -- 2.5 Image Analysis -- 2.5.1 Metrics of Lumens -- 2.5.2 Metrics of Tissue -- 2.6 Statistical Analysis -- 3 Results -- 3.1 Model Solutions -- 3.2 Morris Screening -- 3.3 Local Sensitivity Analysis -- 3.4 Optimization Results -- 3.4.1 Mean Values -- 3.4.2 Biomechanical Metrics -- 3.4.3 Sensitivity Analyses -- 3.4.4 Comparisons of Saline Versus Endotoxin -- 3.5 Image Analysis -- 3.5.1 Distributions of Image Metrics -- 3.6 Correlations Between Optimization Metrics, Image Metrics, and Biomechanical and Inflammatory Markers -- 3.6.1 Optimized Parameters vs Biomechanical and Inflammatory Markers -- 3.6.2 Image Metrics vs Biomechanical and Inflammatory Markers -- 3.6.3 All Variables -- 4 Discussion -- 4.1 Compartmental Model Analyses -- 4.2 Image Analysis -- 4.3 Relationship Between Approaches -- 4.4 Extensions and Clinical Implications -- 4.5 Limitations -- 4.6 Conclusions -- References -- Estimation of Time-Dependent Transmission Rate for COVID-19 SVIRD Model Using Predictor-Corrector Algorithm -- 1 Introduction -- 2 Mathematical Model: SVIRD -- 3 Methodology and Algorithm -- 4 Numerical Experiments with Synthetic Data -- 5 Simulations with Real Data for COVID-19 Pandemic.. - 4.3 Subtle Differences in Modeling Inhibins -- 4.4 Incorporation of Hormonal Contraception in Models -- 5 Outlook and Future Directions -- Supplementary Information -- References -- Studying the Effects of Oral Contraceptives on Coagulation Using a Mathematical Modeling Approach -- 1 Introduction -- 2 Methods -- 2.1 Brief Review of Mathematical Model of Flow-Mediated Coagulation -- 2.2 Model Extension: Thrombomodulin and APC Generation in the Reaction Zone -- 2.3 Virtual Patient Population Generation -- 2.4 Model Workflow -- 3 Results -- 3.1 Thrombomodulin in the Reaction Zone -- 3.2 Predicted Effects of Levonorgestrel on Thrombin Generation -- 3.3 Factor Levels Inducing an Extreme Response -- 3.4 APC Sensitivity Metric -- 4 Discussion -- Supplementary Information -- References -- Deconstructing the Contributions of Heterogeneity to Combination Treatment of Hormone-Sensitive Breast Cancer -- 1 Introduction -- 2 Methods -- 2.1 Mathematical Model of Breast Cancer Co-cultures and Combination Therapy -- 2.1.1 Palbociclib's Impact on Cell Growth -- 2.1.2 Modeling the Effects of Fulvestrant on a Heterogenous Tumor -- 2.1.3 Palbociclib and Fulvestrant Pharmacokinetic Models -- 2.2 Parameter Estimation -- 2.2.1 Estimating Tumor Growth Parameters -- 2.2.2 Estimating Drug Effect Parameters from Cell Viability Assays -- 2.2.3 Estimating Pharmacokinetic Parameters -- 2.3 Generating Heterogeneous Pharmacokinetics and Pharmacodynamics -- 2.3.1 Pharmacokinetic Parameters -- 2.3.2 Pharmacodynamic Parameters -- 3 Results -- 3.1 Shorter Treatment Cycle Reduces Aggressive Cell Viabilities as Compared to Conventional Schedule -- 3.2 Initial Tumor Composition Has Little Impact on Treatment Outcomes -- 3.3 The Effects of Pharmacokinetic Variability Are Determined Uniquely Through Fulvestrant Interindividual Variability.. - 6 Conclusion and Future Work -- References -- Index.. - Intro -- Contents -- Collaborative Workshop for Women in Mathematical Biology: Mathematical Modeling for Women's Health -- 1 Aim and Scope -- 2 History and Context -- 3 Research -- 4 Concluding Remarks -- References -- Extended-Release Pre-exposure Prophylaxis and Drug-Resistant HIV -- 1 Introduction -- 2 HIV Replication and Antiretroviral Drugs -- 3 Within-Host Viral Dynamics and T-Cell Model -- 4 Model for CAB-LA Drug Inhibitory Function -- 4.1 General HIV Dose-Response -- 4.2 Human CAB-LA Data and Model -- 4.3 Macaque CAB-LA Data and Model -- 5 Analysis -- 6 Parameter Sensitivity -- 6.1 Elasticity of the Effective Reproduction Number . -- 6.2 Global Sensitivity -- 7 Treatment Simulations -- 7.1 Macaques and Humans: Numerical Validation Without ART or PrEP -- 7.2 PrEP Before SHIV Exposure: Numerical Validation for Macaque Experiment -- 7.3 PrEP After SHIV Infection: Numerical Validation for Macaque Experiment -- 7.4 Macaque and Human Simulations: PrEP Before Exposure -- 7.5 Macaque and Human Simulations: PrEP After Infection -- 8 Discussion -- References -- A Survey of Mathematical Modeling of Hormonal Contraception and the Menstrual Cycle -- 1 Introduction -- 2 Biological Background on the Menstrual Cycle -- 2.1 Stages of the Menstrual Cycle -- 2.2 Introduction to the Role of Hormones in the Menstrual Cycle -- 2.3 Hormonal Contraception and Its Effect on the Menstrual Cycle -- 3 Mathematical Models of the Menstrual Cycle -- 3.1 Early Modeling Efforts -- 3.2 Available Data Sets on Normal Menstrual Cycles -- 3.3 Harris Clark et al. Model -- 3.4 Pasteur and Selgrade Model -- 3.5 Margolskee and Selgrade Model -- 3.6 Wright et al. Model -- 3.7 Gavina et al. Model -- 3.8 Models Incorporating GnRH -- 4 Comparisons Between Existing Menstrual Cycle Models -- 4.1 Sensitivity to VFSH -- 4.2 Variation in Incorporating Delays in the Models.
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| Emner | |
| ISBN | 9783031585159
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