ArticleThe Journal of allergy and clinical immunology2024
Machine learning-based identification and characterization of mast cells in eosinophilic esophagitis.
Article in The Journal of allergy and clinical immunology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.
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Who cites it
12 citing papers in PubMed, 1 synthesis or guideline pooled it, 17 citations in OpenAlex.
- Systematic Review: Variability in Definitions of Fibrostenosis in Eosinophilic Oesophagitis.Alimentary pharmacology & therapeutics · 2025Pooled it
- Mepolizumab alters gene regulatory networks of nasal airway type-2 and epithelial inflammation in urban children with asthma.Nature communications · 2025Trial
- Developments in Mast Cell Research.The Journal of allergy and clinical immunology · 2026Review
- Roles of systemic CD4Research square · 2026Article
- Emerging Insights into the Inflammatory Phenotypes of Eosinophilic Esophagitis.Journal of inflammation research · 2026Review
- Gastrointestinal endoscopy for physiological assessment in functional gastrointestinal disorders: a perspective.Frontiers in medicine · 2026Article
- Mast cells infiltrates are common in eosinophilic esophagitis and still elevated in histological remission: A digital evaluation in children.Journal of pediatric gastroenterology and nutrition · 2025Article
- Translational approaches to the study of eosinophils in vasculitis.Rheumatology (Oxford, England) · 2025Review
- Comparison of histochemical methods for the analysis of eosinophils and mast cells using a porcine model of eosinophilic esophagitis.Frontiers in veterinary science · 2025Article
- Application of artificial intelligence in eosinophilic esophagitis.Frontiers in immunology · 2025Review
- Advances in omics data for eosinophilic esophagitis: moving towards multi-omics analyses.Journal of gastroenterology · 2024Review
- Advances and ongoing challenges in eosinophilic gastrointestinal disorders presented at the CEGIR/TIGERs Symposium at the 2024 American Academy of Allergy, Asthma & Immunology meeting.The Journal of allergy and clinical immunology · 2024Review
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
Abstract
backgroundEosinophilic esophagitis (EoE) is diagnosed and monitored using esophageal eosinophil levels; however, EoE also exhibits a marked, understudied esophageal mastocytosis.
objectivesUsing machine learning, we localized and characterized esophageal mast cells (MCs) to decipher their potential role in disease pathology.
methodsEsophageal biopsy samples (EoE, control) were stained for MCs by anti-tryptase and imaged using immunofluorescence; high-resolution whole tissue images were digitally assembled. Machine learning software was trained to identify, enumerate, and characterize MCs, designated Mast Cell-Artificial Intelligence (MC-AI).
resultsMC-AI enumerated cell counts with high accuracy. During active EoE, epithelial MCs increased and lamina propria (LP) MCs decreased. In controls and EoE remission patients, papillae had the highest MC density and negatively correlated with epithelial MC density. MC density in the epithelium and papillae correlated with the degree of epithelial eosinophilic inflammation, basal zone hyperplasia, and LP fibrosis. MC-AI detected greater MC degranulation in the epithelium, papillae, and LP in patients with EoE compared with control individuals. MCs were localized further from the basement membrane in active EoE than EoE remission and control individuals but were closer than eosinophils to the basement membrane in active EoE.
conclusionsUsing MC-AI, we identified a distinct population of homeostatic esophageal papillae MCs; during active EoE, this population decreases, undergoes degranulation, negatively correlates with epithelial MC levels, and significantly correlates with distinct histologic features. Overall, MC-AI provides a means to understand the potential involvement of MCs in EoE and other disorders.
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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.