{"date_published":"2022-11-11T00:00:00Z","publication_status":"published","acknowledged_ssus":[{"_id":"PreCl"},{"_id":"Bio"},{"_id":"ScienComp"}],"day":"11","author":[{"full_name":"Colombo, Gloria","last_name":"Colombo","id":"3483CF6C-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0001-9434-8902","first_name":"Gloria"}],"doi":"10.15479/at:ista:12378","_id":"12378","alternative_title":["ISTA Thesis"],"project":[{"call_identifier":"H2020","grant_number":"665385","name":"International IST Doctoral Program","_id":"2564DBCA-B435-11E9-9278-68D0E5697425"}],"related_material":{"record":[{"relation":"part_of_dissertation","id":"12244","status":"public"}]},"language":[{"iso":"eng"}],"oa":1,"tmp":{"legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","short":"CC BY (4.0)","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)","image":"/images/cc_by.png"},"user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","file_date_updated":"2023-04-12T22:30:03Z","page":"142","file":[{"file_size":23890382,"date_updated":"2023-04-12T22:30:03Z","content_type":"application/vnd.openxmlformats-officedocument.wordprocessingml.document","creator":"cchlebak","file_id":"12379","checksum":"8cd3ddfe9b53381dcf086023d8d8893a","date_created":"2023-01-25T14:31:32Z","file_name":"Gloria_Colombo_Thesis.docx","access_level":"closed","embargo_to":"open_access","relation":"source_file"},{"date_created":"2023-01-25T14:31:36Z","file_id":"12380","checksum":"8af4319c18b516e8758e9a6cb02b103b","file_name":"Gloria_Colombo_Thesis.pdf","access_level":"open_access","relation":"main_file","file_size":13802421,"date_updated":"2023-04-12T22:30:03Z","creator":"cchlebak","embargo":"2023-04-11","content_type":"application/pdf"}],"date_created":"2023-01-25T14:27:43Z","has_accepted_license":"1","citation":{"ama":"Colombo G. MorphOMICs, a tool for mapping microglial morphology, reveals brain region- and sex-dependent phenotypes. 2022. doi:<a href=\"https://doi.org/10.15479/at:ista:12378\">10.15479/at:ista:12378</a>","ieee":"G. Colombo, “MorphOMICs, a tool for mapping microglial morphology, reveals brain region- and sex-dependent phenotypes,” Institute of Science and Technology Austria, 2022.","ista":"Colombo G. 2022. MorphOMICs, a tool for mapping microglial morphology, reveals brain region- and sex-dependent phenotypes. Institute of Science and Technology Austria.","short":"G. Colombo, MorphOMICs, a Tool for Mapping Microglial Morphology, Reveals Brain Region- and Sex-Dependent Phenotypes, Institute of Science and Technology Austria, 2022.","mla":"Colombo, Gloria. <i>MorphOMICs, a Tool for Mapping Microglial Morphology, Reveals Brain Region- and Sex-Dependent Phenotypes</i>. Institute of Science and Technology Austria, 2022, doi:<a href=\"https://doi.org/10.15479/at:ista:12378\">10.15479/at:ista:12378</a>.","chicago":"Colombo, Gloria. “MorphOMICs, a Tool for Mapping Microglial Morphology, Reveals Brain Region- and Sex-Dependent Phenotypes.” Institute of Science and Technology Austria, 2022. <a href=\"https://doi.org/10.15479/at:ista:12378\">https://doi.org/10.15479/at:ista:12378</a>.","apa":"Colombo, G. (2022). <i>MorphOMICs, a tool for mapping microglial morphology, reveals brain region- and sex-dependent phenotypes</i>. Institute of Science and Technology Austria. <a href=\"https://doi.org/10.15479/at:ista:12378\">https://doi.org/10.15479/at:ista:12378</a>"},"supervisor":[{"orcid":"0000-0001-8635-0877","id":"36ACD32E-F248-11E8-B48F-1D18A9856A87","full_name":"Siegert, Sandra","last_name":"Siegert","first_name":"Sandra"}],"type":"dissertation","date_updated":"2023-08-04T09:40:37Z","month":"11","title":"MorphOMICs, a tool for mapping microglial morphology, reveals brain region- and sex-dependent phenotypes","article_processing_charge":"No","publisher":"Institute of Science and Technology Austria","abstract":[{"text":"Environmental cues influence the highly dynamic morphology of microglia. Strategies to \r\ncharacterize these changes usually involve user-selected morphometric features, which \r\npreclude the identification of a spectrum of context-dependent morphological phenotypes. \r\nHere, we develop MorphOMICs, a topological data analysis approach, which enables semi\u0002automatic mapping of microglial morphology into an atlas of cue-dependent phenotypes,\r\novercomes feature-selection bias and minimizes biological variability. \r\nFirst, with MorphOMICs we derive the morphological spectrum of microglia across seven \r\nbrain regions during postnatal development and in two distinct Alzheimer’s disease \r\ndegeneration mouse models. We uncover region-specific and sexually dimorphic\r\nmorphological trajectories, with females showing an earlier morphological shift than males in \r\nthe degenerating brain. Overall, we demonstrate that both long primary- and short terminal \r\nprocesses provide distinct insights to morphological phenotypes. Moreover, using machine \r\nlearning to map novel condition on the spectrum, we observe that microglia morphologies \r\nreflect a dose-dependent adaptation upon ketamine anesthesia and do not recover to control \r\nmorphologies.\r\nNext, we took advantage of MorphOMICs to build a high-resolution and layer-specific map of \r\nmicroglial morphological spectrum in the retina, covering postnatal development and rd10 \r\ndegeneration. Here, following photoreceptor death, microglia assume an early development\u0002like morphology. Finally, we map microglial morphology following optic nerve crush on the \r\nretinal spectrum and observe a layer- and sex-dependent response. \r\nOverall, MorphOMICs opens a new perspective to analyze microglial morphology across \r\nmultiple conditions, and provides a novel tool to characterize microglial morphology beyond \r\nthe traditionally dichotomized view of microglia.","lang":"eng"}],"ddc":["570"],"year":"2022","publication_identifier":{"issn":["2663-337X"]},"oa_version":"Published Version","department":[{"_id":"GradSch"},{"_id":"SaSi"}],"status":"public","ec_funded":1,"degree_awarded":"PhD"}