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Characterizing microglia activation: a spatial statistics approach to maximize information extraction

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dc.contributor.authorSalinas Navarro, Manuel Ángel
dc.contributor.authorCordeiro, M. Francesca
dc.contributor.authorMoons, Lieve
dc.contributor.authorDe Groef, Lies
dc.contributor.authorDavis, Benjamin M.
dc.contributor.departmentAnatomía Humana y Psicobiología
dc.contributor.otherFacultades de la UMU::Facultad de Medicina
dc.date.accessioned2026-02-25T09:58:56Z
dc.date.available2026-02-25T09:58:56Z
dc.date.copyright© 2017 The Authors
dc.date.issued2017
dc.description.abstractMicroglia play an important role in the pathology of CNS disorders, however, there remains significant uncertainty about the neuroprotective/degenerative role of these cells due to a lack of techniques to adequately assess their complex behaviour in response to injury. Advancing microscopy techniques, transgenic lines and well-characterized molecular markers, have made histological assessment of microglia populations more accessible. However, there is a distinct lack of tools to adequately extract information from these images to fully characterise microglia behaviour. This, combined with growing economic pressures and the ethical need to minimise the use of laboratory animals, led us to develop tools to maximise the amount of information obtained. This study describes a novel approach, combining image analysis with spatial statistical techniques. In addition to monitoring morphological parameters and global changes in microglia density, nearest neighbour distance, and regularity index, we used cluster analyses based on changes in soma size and roundness to yield novel insights into the behaviour of different microglia phenotypes in a murine optic nerve injury model. These methods should be considered a generic tool to quantitatively assess microglia activation, to profile phenotypic changes into microglia subpopulations, and to map spatial distributions in virtually every CNS region and disease state.
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dc.identifier.citationDavis, B. M., Salinas-Navarro, M., Cordeiro, M. F., Moons, L., & De Groef, L. (2017). Characterizing microglia activation: a spatial statistics approach to maximize information extraction. Scientific reports, 7(1), 1576.
dc.identifier.doihttps://doi.org/10.1038/s41598-017-01747-8
dc.identifier.eissn2045-2322
dc.identifier.urihttp://hdl.handle.net/10201/213002
dc.languageeng
dc.publisherNature Research
dc.relationThis research was supported by the KU Leuven Research Council (BOF-OT/10/033), the Hercules Foundation (AKUL-09-038), and the Research Foundation Flanders (G.05311.10). BMD and MFC were supported by the Wellcome Trust Healthcare Innovation Challenge fund and Medical Research Council confidence in concept award
dc.relation.publisherversionhttps://www.nature.com/articles/s41598-017-01747-8
dc.rightsAttribution 4.0 International*
dc.rights.accessRightsinfo:eu-repo/semantics/openAccess
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subject.odsNo relacionado con ningún objetivo de desarrollo sostenible
dc.titleCharacterizing microglia activation: a spatial statistics approach to maximize information extraction
dc.typeinfo:eu-repo/semantics/article
dc.type.versioninfo:eu-repo/semantics/publishedVersion
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relation.isAuthorOfPublication81da925b-fa46-4a1a-96fd-ce35568fa423
relation.isAuthorOfPublication.latestForDiscovery81da925b-fa46-4a1a-96fd-ce35568fa423
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