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Synthesis of geometrically realistic and watertight neuronal ultrastructure manifolds for in silico modeling.
Abdellah, Marwan; Foni, Alessandro; Cantero, Juan José García; Guerrero, Nadir Román; Boci, Elvis; Fleury, Adrien; Coggan, Jay S; Keller, Daniel; Planas, Judit; Courcol, Jean-Denis; Khazen, Georges.
Afiliação
  • Abdellah M; Blue Brain Project, École Polytecnique Fédérale de Lausanne (EPFL), Campus Biotech, Chemin des Mines 9, Genève 1202, Switzerland.
  • Foni A; Blue Brain Project, École Polytecnique Fédérale de Lausanne (EPFL), Campus Biotech, Chemin des Mines 9, Genève 1202, Switzerland.
  • Cantero JJG; Blue Brain Project, École Polytecnique Fédérale de Lausanne (EPFL), Campus Biotech, Chemin des Mines 9, Genève 1202, Switzerland.
  • Guerrero NR; Blue Brain Project, École Polytecnique Fédérale de Lausanne (EPFL), Campus Biotech, Chemin des Mines 9, Genève 1202, Switzerland.
  • Boci E; Blue Brain Project, École Polytecnique Fédérale de Lausanne (EPFL), Campus Biotech, Chemin des Mines 9, Genève 1202, Switzerland.
  • Fleury A; Blue Brain Project, École Polytecnique Fédérale de Lausanne (EPFL), Campus Biotech, Chemin des Mines 9, Genève 1202, Switzerland.
  • Coggan JS; Blue Brain Project, École Polytecnique Fédérale de Lausanne (EPFL), Campus Biotech, Chemin des Mines 9, Genève 1202, Switzerland.
  • Keller D; Blue Brain Project, École Polytecnique Fédérale de Lausanne (EPFL), Campus Biotech, Chemin des Mines 9, Genève 1202, Switzerland.
  • Planas J; Blue Brain Project, École Polytecnique Fédérale de Lausanne (EPFL), Campus Biotech, Chemin des Mines 9, Genève 1202, Switzerland.
  • Courcol JD; Blue Brain Project, École Polytecnique Fédérale de Lausanne (EPFL), Campus Biotech, Chemin des Mines 9, Genève 1202, Switzerland.
  • Khazen G; Blue Brain Project, École Polytecnique Fédérale de Lausanne (EPFL), Campus Biotech, Chemin des Mines 9, Genève 1202, Switzerland.
Brief Bioinform ; 25(5)2024 Jul 25.
Article em En | MEDLINE | ID: mdl-39129363
ABSTRACT
Understanding the intracellular dynamics of brain cells entails performing three-dimensional molecular simulations incorporating ultrastructural models that can capture cellular membrane geometries at nanometer scales. While there is an abundance of neuronal morphologies available online, e.g. from NeuroMorpho.Org, converting those fairly abstract point-and-diameter representations into geometrically realistic and simulation-ready, i.e. watertight, manifolds is challenging. Many neuronal mesh reconstruction methods have been proposed; however, their resulting meshes are either biologically unplausible or non-watertight. We present an effective and unconditionally robust method capable of generating geometrically realistic and watertight surface manifolds of spiny cortical neurons from their morphological descriptions. The robustness of our method is assessed based on a mixed dataset of cortical neurons with a wide variety of morphological classes. The implementation is seamlessly extended and applied to synthetic astrocytic morphologies that are also plausibly biological in detail. Resulting meshes are ultimately used to create volumetric meshes with tetrahedral domains to perform scalable in silico reaction-diffusion simulations for revealing cellular structure-function relationships. Availability and implementation Our method is implemented in NeuroMorphoVis, a neuroscience-specific open source Blender add-on, making it freely accessible for neuroscience researchers.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Simulação por Computador / Neurônios Limite: Animals / Humans Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Simulação por Computador / Neurônios Limite: Animals / Humans Idioma: En Ano de publicação: 2024 Tipo de documento: Article