ArticleFrontiers in cellular neuroscience2021
Classification of Microglial Morphological Phenotypes Using Machine Learning.
Article in Frontiers in cellular neuroscience, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 107 papers.
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107 citing papers in PubMed, 188 citations in OpenAlex.
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- Hippocampal, Microglial, Morphological, and Amyloid Profiles Following Thiamine Pyrophosphate Treatment in 3xTg-AD Mice.International journal of molecular sciences · 2026Article
- Simultaneous spatial transcriptomics and morphology profiling as tools to explore how microglia change with age.Nature aging · 2026Article
- Adolescent anodal tDCS ameliorates behavioral deficits and microglial abnormalities in a maternal immune activation mouse model of schizophrenia.Psychopharmacology · 2026Article
- Macrostructural, microstructural, and cellular effects of neuroinflammation on the mouse brain.Brain, behavior, & immunity - health · 2026Article
- Increased neurotoxic gliosis and blood-brain barrier dysregulation in canine cognitive dysfunction syndrome (CCD).Frontiers in aging · 2026Article
- N-acetylcysteine Restores Impaired Dentate Gyrus Neurogenesis in a Neonatal Maternal Separation Rat Model.Experimental neurobiology · 2025Article
- Microglial clearance, neuroprotection and cognitive recovery via a novel synthetic sulfolipid in Alzheimer's disease.Journal of neuroinflammation · 2025Article
- Article
- Machine learning-assisted design of immunomodulatory lipid nanoparticles for delivery of mRNA to repolarize hyperactivated microglia.Drug delivery · 2025Article
- Protein kinase CK2α' as a dual modulator of immune signaling and synaptic dysfunction in Tauopathy.bioRxiv : the preprint server for biology · 2025Article
- Localised delivery of interleukin-13 from a PLGA microparticle embedded GelMA hydrogel improves functional and histopathological recovery in a mouse contusion spinal cord injury model.Bioactive materials · 2025Article
47 more citing papers are in PubMed but not listed here.
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Authors and funding
7 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Microglia are the brain's immunocompetent macrophages with a unique feature that allows surveillance of the surrounding microenvironment and subsequent reactions to tissue damage, infection, or homeostatic perturbations. Thereby, microglia's striking morphological plasticity is one of their prominent characteristics and the categorization of microglial cell function based on morphology is well established. Frequently, automated classification of microglial morphological phenotypes is performed by using quantitative parameters. As this process is typically limited to a few and especially manually chosen criteria, a relevant selection bias may compromise the resulting classifications. In our study, we describe a novel microglial classification method by morphological evaluation using a convolutional neuronal network on the basis of manually selected cells in addition to classical morphological parameters. We focused on four microglial morphologies, ramified, rod-like, activated and amoeboid microglia within the murine hippocampus and cortex. The developed method for the classification was confirmed in a mouse model of ischemic stroke which is already known to result in microglial activation within affected brain regions. In conclusion, our classification of microglial morphological phenotypes using machine learning can serve as a time-saving and objective method for post-mortem characterization of microglial changes in healthy and disease mouse models, and might also represent a useful tool for human brain autopsy samples.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.