Unraveling microglial spatial organization in the developing human brain with DeepCellMap, a deep learning approach coupled with spatial statistics

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Publicado en:Nature Communications vol. 16, no. 1 (2025), p. 1577
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Nature Publishing Group
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022 |a 2041-1723 
024 7 |a 10.1038/s41467-025-56560-z  |2 doi 
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245 1 |a Unraveling microglial spatial organization in the developing human brain with DeepCellMap, a deep learning approach coupled with spatial statistics 
260 |b Nature Publishing Group  |c 2025 
513 |a Journal Article 
520 3 |a Mapping cellular organization in the developing brain presents significant challenges due to the multidimensional nature of the data, characterized by complex spatial patterns that are difficult to interpret without high-throughput tools. Here, we present DeepCellMap, a deep-learning-assisted tool that integrates multi-scale image processing with advanced spatial and clustering statistics. This pipeline is designed to map microglial organization during normal and pathological brain development and has the potential to be adapted to any cell type. Using DeepCellMap, we capture the morphological diversity of microglia, identify strong coupling between proliferative and phagocytic phenotypes, and show that distinct spatial clusters rarely overlap as human brain development progresses. Additionally, we uncover an association between microglia and blood vessels in fetal brains exposed to maternal SARS-CoV-2. These findings offer insights into whether various microglial phenotypes form networks in the developing brain to occupy space, and in conditions involving haemorrhages, whether microglia respond to, or influence changes in blood vessel integrity. DeepCellMap is available as an open-source software and is a powerful tool for extracting spatial statistics and analyzing cellular organization in large tissue sections, accommodating various imaging modalities. This platform opens new avenues for studying brain development and related pathologies.DeepCellMap, a deep-learning tool, maps microglial organisation in the developing brain, revealing their spatial diversity, clustering patterns, and associations with blood vessels. DeepCellMap is available as an open-source software. 
653 |a Statistics 
653 |a Hemorrhage 
653 |a Deep learning 
653 |a Microglia 
653 |a Blood vessels 
653 |a Brain 
653 |a Open source software 
653 |a Phenotypes 
653 |a Brain architecture 
653 |a Severe acute respiratory syndrome coronavirus 2 
653 |a Image processing 
653 |a Maps 
653 |a Fetuses 
653 |a Computer program integrity 
653 |a Public domain 
653 |a Clustering 
653 |a Information processing 
653 |a Neuroimaging 
653 |a Spatial discrimination learning 
653 |a Phagocytes 
653 |a Social 
773 0 |t Nature Communications  |g vol. 16, no. 1 (2025), p. 1577 
786 0 |d ProQuest  |t Health & Medical Collection 
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