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Metaball skinning of synthetic astroglial morphologies into realistic mesh models for in silico simulations and visual analytics
MOTIVATION: Astrocytes, the most abundant glial cells in the mammalian brain, have an instrumental role in developing neuronal circuits. They contribute to the physical structuring of the brain, modulating synaptic activity and maintaining the blood–brain barrier in addition to other significant asp...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8275327/ https://www.ncbi.nlm.nih.gov/pubmed/34252950 http://dx.doi.org/10.1093/bioinformatics/btab280 |
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author | Abdellah, Marwan Foni, Alessandro Zisis, Eleftherios Guerrero, Nadir Román Lapere, Samuel Coggan, Jay S Keller, Daniel Markram, Henry Schürmann, Felix |
author_facet | Abdellah, Marwan Foni, Alessandro Zisis, Eleftherios Guerrero, Nadir Román Lapere, Samuel Coggan, Jay S Keller, Daniel Markram, Henry Schürmann, Felix |
author_sort | Abdellah, Marwan |
collection | PubMed |
description | MOTIVATION: Astrocytes, the most abundant glial cells in the mammalian brain, have an instrumental role in developing neuronal circuits. They contribute to the physical structuring of the brain, modulating synaptic activity and maintaining the blood–brain barrier in addition to other significant aspects that impact brain function. Biophysically, detailed astrocytic models are key to unraveling their functional mechanisms via molecular simulations at microscopic scales. Detailed, and complete, biological reconstructions of astrocytic cells are sparse. Nonetheless, data-driven digital reconstruction of astroglial morphologies that are statistically identical to biological counterparts are becoming available. We use those synthetic morphologies to generate astrocytic meshes with realistic geometries, making it possible to perform these simulations. RESULTS: We present an unconditionally robust method capable of reconstructing high fidelity polygonal meshes of astroglial cells from algorithmically-synthesized morphologies. Our method uses implicit surfaces, or metaballs, to skin the different structural components of astrocytes and then blend them in a seamless fashion. We also provide an end-to-end pipeline to produce optimized two- and three-dimensional meshes for visual analytics and simulations, respectively. The performance of our pipeline has been assessed with a group of 5000 astroglial morphologies and the geometric metrics of the resulting meshes are evaluated. The usability of the meshes is then demonstrated with different use cases. AVAILABILITY AND IMPLEMENTATION: Our metaball skinning algorithm is implemented in Blender 2.82 relying on its Python API (Application Programming Interface). To make it accessible to computational biologists and neuroscientists, the implementation has been integrated into NeuroMorphoVis, an open source and domain specific package that is primarily designed for neuronal morphology visualization and meshing. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. |
format | Online Article Text |
id | pubmed-8275327 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-82753272021-07-13 Metaball skinning of synthetic astroglial morphologies into realistic mesh models for in silico simulations and visual analytics Abdellah, Marwan Foni, Alessandro Zisis, Eleftherios Guerrero, Nadir Román Lapere, Samuel Coggan, Jay S Keller, Daniel Markram, Henry Schürmann, Felix Bioinformatics General Computational Biology MOTIVATION: Astrocytes, the most abundant glial cells in the mammalian brain, have an instrumental role in developing neuronal circuits. They contribute to the physical structuring of the brain, modulating synaptic activity and maintaining the blood–brain barrier in addition to other significant aspects that impact brain function. Biophysically, detailed astrocytic models are key to unraveling their functional mechanisms via molecular simulations at microscopic scales. Detailed, and complete, biological reconstructions of astrocytic cells are sparse. Nonetheless, data-driven digital reconstruction of astroglial morphologies that are statistically identical to biological counterparts are becoming available. We use those synthetic morphologies to generate astrocytic meshes with realistic geometries, making it possible to perform these simulations. RESULTS: We present an unconditionally robust method capable of reconstructing high fidelity polygonal meshes of astroglial cells from algorithmically-synthesized morphologies. Our method uses implicit surfaces, or metaballs, to skin the different structural components of astrocytes and then blend them in a seamless fashion. We also provide an end-to-end pipeline to produce optimized two- and three-dimensional meshes for visual analytics and simulations, respectively. The performance of our pipeline has been assessed with a group of 5000 astroglial morphologies and the geometric metrics of the resulting meshes are evaluated. The usability of the meshes is then demonstrated with different use cases. AVAILABILITY AND IMPLEMENTATION: Our metaball skinning algorithm is implemented in Blender 2.82 relying on its Python API (Application Programming Interface). To make it accessible to computational biologists and neuroscientists, the implementation has been integrated into NeuroMorphoVis, an open source and domain specific package that is primarily designed for neuronal morphology visualization and meshing. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Oxford University Press 2021-07-12 /pmc/articles/PMC8275327/ /pubmed/34252950 http://dx.doi.org/10.1093/bioinformatics/btab280 Text en © The Author(s) 2021. Published by Oxford University Press. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | General Computational Biology Abdellah, Marwan Foni, Alessandro Zisis, Eleftherios Guerrero, Nadir Román Lapere, Samuel Coggan, Jay S Keller, Daniel Markram, Henry Schürmann, Felix Metaball skinning of synthetic astroglial morphologies into realistic mesh models for in silico simulations and visual analytics |
title | Metaball skinning of synthetic astroglial morphologies into realistic mesh models for in silico simulations and visual analytics |
title_full | Metaball skinning of synthetic astroglial morphologies into realistic mesh models for in silico simulations and visual analytics |
title_fullStr | Metaball skinning of synthetic astroglial morphologies into realistic mesh models for in silico simulations and visual analytics |
title_full_unstemmed | Metaball skinning of synthetic astroglial morphologies into realistic mesh models for in silico simulations and visual analytics |
title_short | Metaball skinning of synthetic astroglial morphologies into realistic mesh models for in silico simulations and visual analytics |
title_sort | metaball skinning of synthetic astroglial morphologies into realistic mesh models for in silico simulations and visual analytics |
topic | General Computational Biology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8275327/ https://www.ncbi.nlm.nih.gov/pubmed/34252950 http://dx.doi.org/10.1093/bioinformatics/btab280 |
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