Computational physiology : Simula Summer School 2021 -- student reports

Computational physiology Simula Summer School 2021 -- student reports

This open access volume compiles student reports from the 2021 Simula Summer School in Computational Physiology. Interested readers will find herein a number of modern approaches to modeling excitable tissue. This should provide a framework for tools available to model subcellular and tissue-level p...

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Detalles Bibliográficos
Autor Corporativo: Simula Summer School in Computational Physiology (-)
Otros Autores: McCabe, Kimberly J. (Editor)
Formato: Libro electrónico
Idioma:Inglés
Publicado: Cham : Springer International Publishing AG 2022.
Colección:Simula SpringerBriefs on computing 12
Materias:
Physiology > Computer simulation > Congresses.
Physiology > Data processing > Congresses.
Fisiologia
Processament de dades
Simulació per ordinador
Computational Physiology
Scientific computing
Electrophysiology
Pharmacology
Mechanics
Machine learning
Fluid mechanics
Bioengineering
Numerical analysis
Congressos
Llibres electrònics
Ver en Biblioteca Universitat Ramon Llull:https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009660894306719
Tabla de Contenidos:
  • Intro
  • Preface
  • Acknowledgements
  • Contents
  • Chapter 1 A Pipeline for Automated Coordinate Assignment in Anatomically Accurate Biventricular Models
  • 1.1 Introduction
  • 1.2 Methods
  • 1.2.1 Semi-Automated Surface Extraction
  • Algorithm 1
  • 1.2.2 Biventricular Coordinate System
  • 1.2.2.1 Creation of the Coordinate System Cobiveco
  • 1.2.3 Mapping Vector Fields
  • 1.3 Results
  • 1.4 Conclusion
  • 1.4.1 Limitations
  • References
  • Chapter 2 3D Simulations of Fetal and Maternal Ventricular Excitation for Investigating the Abdominal ECG
  • 2.1 Introduction
  • 2.2 Methods
  • 2.2.1 Geometrical mesh construction
  • 2.2.2 Electrophysiological modelling
  • 2.2.3 Extracellular potential measurements
  • 2.2.4 Fetal ECG extraction using signal processing methods
  • 2.3 Results
  • 2.4 Discussion
  • 2.5 Conclusions
  • References
  • Chapter 3 Ordinary Differential Equation-based Modeling of Cells in Human Cartilage
  • 3.1 Introduction
  • 3.2 Methods
  • 3.2.1 Mathematical modelling of ATP-sensitive K+ currents
  • 3.2.2 Population of Models
  • 3.3 Results
  • 3.3.1 Validation
  • 3.3.2 Results for the ATP-sensitive K+ currents
  • 3.3.3 Populations of Models
  • 3.4 Discussion and Conclusion
  • References
  • Chapter 4 Conduction Velocity in Cardiac Tissue as Function of Ion Channel Conductance and Distribution
  • 4.1 Introduction
  • 4.2 Models and methods
  • 4.2.1 The monodomain model
  • 4.2.2 The EMI model
  • 4.3 Results
  • 4.4 Discussion
  • 4.4.1 Influence of ion channel conductance on CV
  • 4.4.2 Influence of ion channel distribution
  • 4.5 Conclusions
  • References
  • Chapter 5 Computational Prediction of Cardiac Electropharmacology - How Much Does the Model Matter?
  • 5.1 Introduction
  • 5.2 Methods
  • 5.2.1 Models of Cardiac Electrophysiology
  • 5.2.2 Feature Extraction
  • 5.2.3 Sensitivity Analysis and Translation
  • 5.3 Results
  • 5.3.1 Model Translation
  • 5.3.2 Translation Discrepancies
  • 5.4 Discussion
  • 5.5 Conclusion
  • References
  • Chapter 6 A Computational Study of Flow Instabilities in Aneurysms
  • 6.1 Introduction
  • 6.2 Methods
  • 6.2.1 Baseflow equations
  • 6.2.2 Flow perturbations and instability
  • 6.2.3 Discretization
  • 6.2.4 Computational Methodology
  • 6.3 Results
  • 6.4 Discussion
  • References
  • Chapter 7 Investigating the Multiscale Impact of Deoxyadenosine Triphosphate (dATP) on Pulmonary Arterial Hypertension (PAH) Induced Heart Failure
  • 7.1 Introduction
  • 7.2 Methods
  • 7.2.1 Cell Level Changes
  • 7.2.1.1 The SERCA Pump and Calcium transients
  • 7.2.1.2 Cross-bridge cycling kinetics
  • 7.2.2 Organ Level Model
  • 7.3 Results
  • 7.4 Discussion and Conclusion
  • 7.5 Acknowledgements
  • 7.6 Supplementary Information
  • References
  • Chapter 8 Identifying Ionic Channel Block in a Virtual Cardiomyocyte Population Using Machine Learning Classifiers
  • 8.1 Introduction
  • 8.2 Methods
  • 8.2.1 Data

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