ArticleScientific reports2017
Image based Machine Learning for identification of macrophage subsets.
Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 104 papers.
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Who cites it
104 citing papers in PubMed, 190 citations in OpenAlex.
- Article
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- Cellular Morphometric Analysis (CellMorph)-a comprehensive imaging-based tool for quantifying cellular phenotype heterogeneity and dynamics across biological processes.The FEBS journal · 2026Article
- Isolation of Human Osteal Macrophages.Life (Basel, Switzerland) · 2026Article
- The morpho-kinetic landscape of macrophage modes during wound healing in zebrafish.Scientific reports · 2026Article
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- Immunomodulation in the repair of osteonecrosis of the femoral head: reprogramming strategies for macrophages and immune cells.Frontiers in immunology · 2026Review
- PRKCSH deficiency promotes an anti-tumor immune microenvironment via UPR activation and M1 macrophage polarization.Cancer cell international · 2025Article
- Proteomic and morphologic characterization of ovine macrophage differentiation and polarization.Scientific reports · 2025Article
- The role of cisplatin in modulating the tumor immune microenvironment and its combination therapy strategies: a new approach to enhance anti-tumor efficacy.Annals of medicine · 2025Review
- Engineering macrophage responses through 3D scaffold microarchitecture.Materials today. Bio · 2025Article
- Metabolomic profiling of host-pathogen interactions: differential effects of Gram-positive and Gram-negative bacterial secretomes on THP-1 macrophage metabolism.RSC advances · 2025Article
- Transcriptome profiling of L. infantum-infected human macrophages reveals sex-specific type I interferon induction.PLoS pathogens · 2025Article
- Multivariate Screening and Automated Clustering of Macrophage Immunoreactome to Nanoparticles and Photothermal Therapy.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Nanofibrillar Cellulose Hydrogels with Anionic Surface Modifications for Modulating Macrophage Phenotype in 3D Culture.ACS applied materials & interfaces · 2025Article
- Microenvironmental conditions and serum availability alter primary human macrophage NF-κB inflammatory response and function.Journal of leukocyte biology · 2025Article
- The nucleosome remodeling and deacetylase-SWItch/sucrose non-fermentable antagonism regulates the coordinated activation of epithelial-to-mesenchymal transition and inflammation in oral cancer.Journal of the National Cancer Institute · 2025Article
- Intrinsic immunosuppressive features of monocytes suppress CAR-T19 through IL-1 pathway modulation in mantle cell lymphoma.Molecular therapy. Oncology · 2025Article
44 more citing papers are in PubMed but not listed here.
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Authors and funding
5 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Macrophages play a crucial rule in orchestrating immune responses against pathogens and foreign materials. Macrophages have remarkable plasticity in response to environmental cues and are able to acquire a spectrum of activation status, best exemplified by pro-inflammatory (M1) and anti-inflammatory (M2) phenotypes at the two ends of the spectrum. Characterisation of M1 and M2 subsets is usually carried out by quantification of multiple cell surface markers, transcription factors and cytokine profiles. These approaches are time-consuming, require large numbers of cells and are resource intensive. In this study, we used machine learning algorithms to develop a simple and fast imaging-based approach that enables automated identification of different macrophage functional phenotypes using their cell size and morphology. Fluorescent microscopy was used to assess cell morphology of different cell types which were stained for nucleus and actin distribution using DAPI and phalloidin respectively. By only analysing their morphology we were able to identify M1 and M2 phenotypes effectively and could distinguish them from naïve macrophages and monocytes with an average accuracy of 90%. Thus we suggest high-content and automated image analysis can be used for fast phenotyping of functionally diverse cell populations with reasonable accuracy and without the need for using multiple markers.
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Registered trials
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.