The classical bidomain model of cardiac tissue views the intracellular and extracellular (interstitial) spaces as two coupled but separate continua. In the present study, the classical bidomain model has been extended by introducing a periodic conductivity in the intracellular space to represent the junctional discontinuity between abutting myocytes. In this model the junctional region of a myocyte is represented in a way that permits variation of junction size and conductivity profile. Employing spectral techniques, a new method was developed for solving the coupled differential equations governing the intracellular and extracellular potentials in a tissue preparation of finite dimensions. Different spectral representations are used for the aperiodic intra- and extracellular potentials (finite Fourier integral transform) and for the periodic intracellular conductivity (Fourier series). As a first application of the method, the response of a 50-cell, single interior fiber to a defibrillating current is examined under steady-state conditions. Transmembrane as well as intra- and extracellular potential distributions along the fiber were calculated.
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Int J Biol Macromol
December 2024
Dipartimento di Scienze della Vita, Università di Modena e Reggio Emilia, via Campi 103, 41125 Modena, Italy. Electronic address:
G protein coupled receptors (GPCRs) are critically regulated by arrestins. In this study, high-resolution data was combined with molecular dynamics simulations to infer the determinants of β-arrestin 1 (βarr1)-GPCR coupling, using the V2 vasopressin receptor (V2R) as a model system. The study highlighted the extremely high plasticity of βarr1-GPCR complexes, dependent on receptor type, state, and membrane environment.
View Article and Find Full Text PDFSci Rep
July 2024
Simula Research Laboratory, Oslo, Norway.
Computational techniques have significantly advanced our understanding of cardiac electrophysiology, yet they have predominantly concentrated on averaged models that do not represent the intricate dynamics near individual cardiomyocytes. Recently, accurate models representing individual cells have gained popularity, enabling analysis of the electrophysiology at the micrometer level. Here, we evaluate five mathematical models to determine their computational efficiency and physiological fidelity.
View Article and Find Full Text PDFSci Adv
July 2024
Department of Chemical and Biological Engineering, University at Buffalo, The State University of New York (SUNY), Buffalo, NY, USA.
Cell therapy for the treatment of demyelinating diseases such as multiple sclerosis is hampered by poor survival of donor oligodendrocyte cell preparations, resulting in limited therapeutic outcomes. Excessive cell death leads to the release of intracellular alloantigens, which likely exacerbate local inflammation and may predispose the graft to eventual rejection. Here, we engineered innovative cell-instructive shear-thinning hydrogels (STHs) with tunable viscoelasticity and bioactivity for minimally invasive delivery of primary human oligodendrocyte progenitor cells (hOPCs) to the brain of a mouse, a model of congenital hypomyelinating disease.
View Article and Find Full Text PDFPLoS One
July 2024
Dipartimento di Matematica, Università degli Studi di Pavia, Pavia, Italy.
Long QT Syndrome type 8 (LQT8) is a cardiac arrhythmic disorder associated with Timothy Syndrome, stemming from mutations in the CACNA1C gene, particularly the G406R mutation. While prior studies hint at CACNA1C mutations' role in ventricular arrhythmia genesis, the mechanisms, especially in G406R presence, are not fully understood. This computational study explores how the G406R mutation, causing increased transmural dispersion of repolarization, induces and sustains reentrant ventricular arrhythmias.
View Article and Find Full Text PDFNPJ Parkinsons Dis
June 2024
Department of Neurology, University of California, San Francisco, San Francisco, CA, USA.
Quantification of motor symptom progression in Parkinson's disease (PD) patients is crucial for assessing disease progression and for optimizing therapeutic interventions, such as dopaminergic medications and deep brain stimulation. Cumulative and heuristic clinical experience has identified various clinical signs associated with PD severity, but these are neither objectively quantifiable nor robustly validated. Video-based objective symptom quantification enabled by machine learning (ML) introduces a potential solution.
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