LEADER 06702nam 22007453u 450 001 9910567787803321 005 20250628110049.0 035 $a(CKB)5680000000038261 035 $aEBL6978014 035 $a(OCoLC)1315573272 035 $a(AU-PeEL)EBL6978014 035 $a(MiAaPQ)EBC6978014 035 $a(oapen)https://directory.doabooks.org/handle/20.500.12854/81659 035 $a(PPN)269155376 035 $a(ODN)ODN0010067646 035 $a(Au-PeEL)EBL6978014 035 $a(oapen)doab81659 035 $a(EXLCZ)995680000000038261 100 $a20250630d2022 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aComputational physiology $eSimula Summer School 2021 -- student reports /$feditor, Kimberly J. McCabe 205 $a1st ed. 210 $aCham $cSpringer International Publishing AG$d2022 215 $a1 online resource (xi, 109 pages) $cillustrations (some color) 225 1 $aSimula SpringerBriefs on computing$vv.12 300 $aDescription based upon print version of record. 311 1 $a9783031051630 311 1 $a3031051637 311 1 $a9783031051647 311 1 $a3031051645 327 $aIntro -- 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 327 $a2.2.1 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 327 $a3.4 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 327 $a5.2.2 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 327 $aChapter 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 327 $a8.2.1 Data 330 $aThis open access volume compiles student reports from the 2021 Simula Summer School in Computational Physiology. Interested readers will find herein a number of modern approaches to modeling excitable tissue. This should provide a framework for tools available to model subcellular and tissue-level physiology across scales and scientific questions. In June through August of 2021, Simula held the seventh annual Summer School in Computational Physiology in collaboration with the University of Oslo (UiO) and the University of California, San Diego (UCSD). The course focuses on modeling excitable tissues, with a special interest in cardiac physiology and neuroscience. The majority of the school consists of group research projects conducted by Masters and PhD students from around the world, and advised by scientists at Simula, UiO and UCSD. Each group then produced a report that addreses a specific problem of importance in physiology and presents a succinct summary of the findings. Reports may not necessarily represent new scientific results; rather, they can reproduce or supplement earlier computational studies or experimental findings. Reports from eight of the summer projects are included as separate chapters. The fields represented include cardiac geometry definition (Chapter 1), electrophysiology and pharmacology (Chapters 2?5), fluid mechanics in blood vessels (Chapter 6), cardiac calcium handling and mechanics (Chapter 7), and machine learning in cardiac electrophysiology (Chapter 8). 410 0$aSimula SpringerBriefs on computing$v12 606 $aPhysiology$xComputer simulation$vCongresses 606 $aPhysiology$xData processing$vCongresses 606 $aFisiologia$2thub 606 $aProcessament de dades$2thub 606 $aSimulació per ordinador$2thub 608 $aCongressos$2thub 608 $aLlibres electrònics$2thub 615 0$aPhysiology$xComputer simulation 615 0$aPhysiology$xData processing 615 7$aFisiologia 615 7$aProcessament de dades 615 7$aSimulació per ordinador. 686 $aCOM014000$aMAT003000$aMAT006000$aTEC059000$2bisacsh 700 $aMcCabe$b Kimberly J$4edt$01237063 701 $aMcCabe$b Kimberly J$01237063 712 02$aSimula Summer School in Computational Physiology 801 0$bAU-PeEL 801 1$bAU-PeEL 801 2$bAU-PeEL 906 $aBOOK 912 $a9910567787803321 996 $aComputational Physiology$92871900 997 $aUNINA