277731 20260105141447.0 10.1152/jn.00622.2024 doi pmid:40013734 pmid 0022-3077 ISSN 1522-1598 ISSN DZNE-2025-00452 English 000 Schünemann, Kerstin D 0009-0001-0741-4500 0 Comprehensive analysis of human dendritic spine morphology and density. Bethesda, Md. 2025 Soc. article DRIVER Output Types/Journal article DataCite Journal Article journal journal PUB:(DE-HGF)16 1766399805_14400 PUB:(DE-HGF) ARTICLE BibTeX JOURNAL_ARTICLE ORCID Journal Article 0 EndNote Dendritic spines, small protrusions on neuronal dendrites, play a crucial role in brain function by changing shape and size in response to neural activity. So far, in-depth analysis of dendritic spines in human brain tissue is lacking. This study presents a comprehensive analysis of human dendritic spine morphology and density using a unique dataset from human brain tissue from 27 patients (8 females, 19 males, aged 18-71 yr) undergoing tumor or epilepsy surgery at three neurosurgery sites. We used acute slices and organotypic brain slice cultures to examine dendritic spines, classifying them into the three main morphological subtypes: mushroom, thin, and stubby, via three-dimensional (3-D) reconstruction using ZEISS arivis Pro software. A deep learning model, trained on 39 diverse datasets, automated spine segmentation and 3-D reconstruction, achieving a 74% F1-score and reducing processing time by over 50%. We show significant differences in spine density by sex, dendrite type, and tissue condition. Females had higher spine densities than males, and apical dendrites were denser in spines than basal ones. Acute tissue showed higher spine densities compared with cultured human brain tissue. With time in culture, mushroom spines decreased, whereas stubby and thin spine percentages increased, particularly from 7-9 to 14 days in vitro, reflecting potential synaptic plasticity changes. Our study underscores the importance of using human brain tissue to understand unique synaptic properties and shows that integrating deep learning with traditional methods enables efficient large-scale analysis, revealing key insights into sex- and tissue-specific dendritic spine dynamics relevant to neurological diseases.NEW & NOTEWORTHY This study presents a dataset of nearly 4,000 morphologically reconstructed human dendritic spines across different ages, gender, and tissue conditions. The dataset was further used to evaluate a deep learning algorithm for three-dimensional spine reconstruction, offering a scalable method for semiautomated spine analysis across various tissues and microscopy setups. The findings enhance understanding of human neurology, indicating potential connections between spine morphology, brain function, and the mechanisms of neurological and psychiatric diseases. 351 - Brain Function (POF4-351) G:(DE-HGF)POF4-351 POF4-351 POF IV 0 Dataset connected to CrossRef, PubMed, , Journals: pub.dzne.de deep learning Other dendritic spines Other human tissue Other morphology Other Dendritic Spines: ultrastructure MeSH Humans MeSH Male MeSH Female MeSH Middle Aged MeSH Adult MeSH Dendritic Spines: physiology MeSH Aged MeSH Adolescent MeSH Young Adult MeSH Deep Learning MeSH Imaging, Three-Dimensional: methods MeSH Sex Characteristics MeSH Brain: cytology MeSH Imaging, Three-Dimensional MeSH Hattingh, Roxanne M 0000-0002-8244-5542 1 Verhoog, Matthijs B 0000-0002-8500-1795 2 Yang, Danqing 3 Bak, Aniella V 0000-0003-2449-9689 4 Peter, Sabrina 5 van Loo, Karen M J 0000-0003-3074-5612 6 Wolking, Stefan 0000-0002-1460-6623 7 Kronenberg-Versteeg, Deborah P:(DE-2719)9001451 8 dzne Weber, Yvonne 0000-0002-0806-5592 9 Schwarz, Niklas 0000-0002-4064-3073 10 Raimondo, Joseph V 11 Melvill, Roger 12 Tromp, Sean A 13 Butler, James T 0000-0003-1978-6894 14 Höllig, Anke 0000-0001-6798-5703 15 Delev, Daniel 16 Wuttke, Thomas V 0000-0001-5655-8490 17 Kampa, Björn M 0000-0002-4343-2634 18 Koch, Henner 0000-0002-6883-3071 19 10.1152/jn.00622.2024 Vol. 133, no. 4, p. 1086 - 1102 PERI:(DE-600)1467889-5 4 1086 - 1102 Journal of neurophysiology 133 2025 0022-3077 http://pub.dzne.de/record/277731/files/DZNE-2025-00452_Restricted.pdf OpenAccess http://pub.dzne.de/record/277731/files/DZNE-2025-00452.pdf pdfa http://pub.dzne.de/record/277731/files/DZNE-2025-00452_Restricted.pdf?subformat=pdfa OpenAccess pdfa http://pub.dzne.de/record/277731/files/DZNE-2025-00452.pdf?subformat=pdfa oai:pub.dzne.de:277731 openaire open_access VDB driver dnbdelivery Deutsches Zentrum für Neurodegenerative Erkrankungen I:(DE-588)1065079516 DZNE 8 P:(DE-2719)9001451 DE-HGF Gesundheit Neurodegenerative Diseases G:(DE-HGF)POF4-350 G:(DE-HGF)POF4-351 G:(DE-HGF)POF4 G:(DE-HGF)POF4-300 G:(DE-HGF)POF Brain Function 0 2025 DBCoverage StatID:(DE-HGF)0200 StatID SCOPUS 2025-01-03 DBCoverage StatID:(DE-HGF)0160 StatID Essential Science Indicators 2025-01-03 DBCoverage StatID:(DE-HGF)1050 StatID BIOSIS Previews 2025-01-03 DBCoverage StatID:(DE-HGF)1190 StatID Biological Abstracts 2025-01-03 DBCoverage StatID:(DE-HGF)0600 StatID Ebsco Academic Search 2025-01-03 DBCoverage StatID:(DE-HGF)1040 StatID Zoological Record 2025-01-03 DBCoverage StatID:(DE-HGF)1030 StatID Current Contents - Life Sciences 2025-01-03 WoS StatID:(DE-HGF)0113 StatID Science Citation Index Expanded 2025-01-03 DBCoverage StatID:(DE-HGF)0150 StatID Web of Science Core Collection 2025-01-03 OpenAccess StatID:(DE-HGF)0510 StatID Peer Review StatID:(DE-HGF)0030 StatID ASC 2025-01-03 DBCoverage StatID:(DE-HGF)0300 StatID Medline 2025-01-03 Creative Commons Attribution CC BY 4.0 LIC:(DE-HGF)CCBY4 HGFVOC Nationallizenz StatID:(DE-HGF)0420 StatID 2025-01-03 ger DBCoverage StatID:(DE-HGF)0199 StatID Clarivate Analytics Master Journal List 2025-01-03 I:(DE-2719)1210015 AG Kronenberg-Versteeg Glial Cell Biology 0 journal VDB UNRESTRICTED I:(DE-2719)1210015 FullTexts