Results 71 to 80 of about 20,766 (186)

In silico modelling of multi‐electrode arrays for enhancing cardiac drug testing on hiPSC‐CM heterogeneous tissues

The Journal of Physiology, EarlyView.
Abstract figure legend Schematic overview of the experimental and computational framework for investigating hiPSC‐CM electrophysiology with MEA systems. The MEA‐based model integrates experimental data with phenotype‐specific ionic models and tissue‐level heterogeneity.
Sofia Botti, Rolf Krause, Luca F. Pavarino   +2 more
wiley   +1 more source

Elucidating the cellular determinants of the end‐systolic pressure‐volume relationship of the heart via computational modelling

The Journal of Physiology, EarlyView.
Abstract figure legend Using a multiscale computational model of left ventricular electromechanics, we investigated how sarcomere dynamics influence the end‐systolic pressure‐volume (ESPV) relationship in ejecting beats compared to isovolumetric beats.
Francesco Regazzoni, Corrado Poggesi, Cecilia Ferrantini   +2 more
wiley   +1 more source

Sympathetic stimulation can compensate for hypocalcaemia‐induced bradycardia in human and rabbit sinoatrial node cells

The Journal of Physiology, EarlyView.
Abstract figure legend AC: adenylyl cyclase, APT: adenosine triphosphate, AMP: adenosine monophosphate, cAMP: cyclic adenosine monophosphate, PDE: phosphodiesterase, PKA: protein kinase A, PPT: protein phosphatase, P: phosphorylation, RyR: ryanodine receptor, SERCA: sarcoplasmic/endoplasmic reticulum Ca2+‐adenosine triphosphatase, SR: sarcoplasmic ...
Moritz Linder, Tomas Stary, Gergő Bitay, Norbert Nagy, Axel Loewe   +4 more
wiley   +1 more source

Utility of local capillary supply indices: Insights from computational image‐based modelling

The Journal of Physiology, EarlyView.
Abstract figure legend Local capillary distribution and fibre geometry influence oxygen availability in skeletal muscle. Image‐based modelling of tissue PO2${{P}_{{{{\mathrm{O}}}_2}}}$ shows that area‐based measures of capillary supply – the local capillary density (LCDi) and local maximum diffusion distance (Dmax,i) – most accurately represent the ...
Abdullah A. Al‐Shammari, Roger W. P. Kissane, Ali Ashkanani, Ashraf Al Madhoun, Fahd Al‐Mulla, Eamonn A. Gaffney, Stuart Egginton   +6 more
wiley   +1 more source

PVRI‐GoDeep—A Global Meta‐Registry at the Crossroads of Heart and Lung

Comprehensive Physiology, Volume 16, Issue 2, April 2026.
PVRI GoDeep is a global meta‐registry that harmonizes high‐quality patient‐level data from pulmonary hypertension registries worldwide. With over 45,000 enrolees already included, it enables robust phenotyping, international comparisons, and clinically relevant research across all PH subgroups beyond the scope of single‐center or national datasets ...
Meike T. Fuenderich, Athiththan Yogeswaran, Patrick Janetzko, Khodr Tello, Werner Seeger, Raphael W. Majeed, Jochen Wilhelm, GoDeep Consortium, Mauro Acquaro, Imad Al Ghouleh, James Anderson, Jeffrey S. Annis, Anastasia Anthi, Alexandra Arvanitaki, Aparna Balasubramanian, Felix Ballmann, Harm Jan Bogaard, Evan Brittain, Hugh Buzacott, Hector R. Cajigas, John Cannon, Stephen Y. Chan, Victoria Damonte, Effrosyni Dima, Philipp Douschan, Nathan Dwyer, Diego Echazarreta, Christina A. Eichstaedt, Jean Elwing, Kai Förster, Robert Frantz, Marlize Frauendorf, Stefano Ghio, Hossein‐Ardeschir Ghofrani, George Giannakoulas, Friedrich Grimminger, Ekkehard Grünig, Lars Harbaum, Paul M. Hassoun, Melanie Heberling, Anne Hilgendorff, Luke Howard, Arun Jose, Ernesto Junaeda, David G. Kiely, Ingrid King, Hans Klose, Ziad Konswa, Gabor Kovacs, Philipp Krieb, Keiichiro Kuronuma, Edmund M. Lau, Melanie Lavender, Allan Lawrie, Mona Lichtblau, Kurt Marquardt, Hiromi Matsubara, Farhan Mubashir, Horst Olschewski, Mauricio Orozco‐Levi, Karen Osborn, Joanna Pepke‐Zaba, Alba Ramirez‐Sarmiento, Stephan Rosenkranz, Hani Sabbour, Sandeep Sahay, Khaled Saleh, Laura Scelsi, Yuriy Sirenko, Siva Sivakumaran, Andrew J. Sweatt, Thenappan Thenappan, Ioan Tilea, Olena Torbas, Silvia Ulrich, Andrea Varga, Helen M. Whitford, Christoph B. Wiedenroth, Martin R. Wilkins, Paul G. Williams, Shaun Yo, Roham T. Zamanian, Zhenguo Zhai, Zhu Zhang   +83 more
wiley   +1 more source

Advection‐Pressure Splitting Schemes Applied to a Non‐Conservative 1D Blood Flow Model With Transport for Arteries and Veins

International Journal for Numerical Methods in Fluids, Volume 98, Issue 4, Page 398-432, April 2026.
We introduce new efficient and accurate first order finite volume‐type numerical schemes, for the non‐conservative one‐dimensional blood flow equations with transport, taking into account different velocity profiles. The framework is the flux‐vector splitting approach of Toro and Vázquez‐Cendón (2012), that splits the system in two subsystems of PDEs ...
Alessandra Spilimbergo, Eleuterio F. Toro, Annunziato Siviglia, Lucas O. Müller   +3 more
wiley   +1 more source

31P‐MRS of the Human Heart at 7 T With an Integrated Whole‐Body 31P Radiofrequency Transmit Coil

NMR in Biomedicine, Volume 39, Issue 4, April 2026.
We demonstrate the use of an integrated whole‐body phosphorus‐31 (31P) radiofrequency transmit coil for 31P‐MR spectroscopic imaging of the human heart at 7 T. Intersession measurement repeatability of the mid‐septal myocardial phosphocreatine (PCr) over adenosine triphosphate (ATP) concentration ratio in normal volunteers was 17.7%.
Mark W. J. M. Gosselink, Martijn Froeling, Kathy Verkerk, Dennis W. J. Klomp, Adrianus J. Bakermans, Jeanine J. Prompers   +5 more
wiley   +1 more source

Monitoring of water volume in a porous reservoir using seismic data: Validation of a numerical model with a field experiment

Near Surface Geophysics, Volume 24, Issue 2, Page 110-127, April 2026.
Abstract As global groundwater levels continue to decline rapidly, there is a growing need for advanced techniques to monitor and manage aquifers effectively. This study focuses on validating a numerical model using seismic data from a small‐scale experimental setup designed to estimate water volume in a porous reservoir.
Mahnaz Khalili, Bojan Brodic, Peter Göransson, Suvi Heinonen, Jan S. Hesthaven, Antti Pasanen, Marko Vauhkonen, Rahul Yadav, Timo Lähivaara   +8 more
wiley   +1 more source

Space Correlation Constrained Physics Informed Neural Network for Seismic Tomography

Journal of Geophysical Research: Machine Learning and Computation, Volume 3, Issue 2, April 2026.
Abstract Physics‐informed neural networks (PINNs) integrate physical constraints with neural architectures and leverage their nonlinear fitting capabilities to solve complex inverse problems. Tomography serves as a classic example, aiming to reconstruct subsurface velocity models to improve seismic exploration.
Yonghao Wang, Zhuo Jia, Bowu Jiang, Wenkai Lu   +3 more
wiley   +1 more source

An Effective Physics‐Informed Neural Operator Framework for Predicting Wavefields

Journal of Geophysical Research: Machine Learning and Computation, Volume 3, Issue 2, April 2026.
Abstract Solving the wave equation is fundamental for many geophysical applications. However, numerical solutions of the Helmholtz equation face significant computational and memory challenges. Therefore, we introduce a physics‐informed convolutional neural operator (CNO) (PICNO) to solve the Helmholtz equation efficiently.
X. Ma, T. Alkhalifah
wiley   +1 more source