ArticleFrontiers in immunology2023
Automated clustering reveals CD4
Article in Frontiers in immunology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
What it found
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
12 citing papers in PubMed.
- The efficacy and safety of short-term and low-dose IL-2 combined with tocilizumab to treat rheumatoid arthritis.Frontiers in immunology · 2024Trial
- Targeting NFATc1-regulated MTHFD2 one-carbon metabolism to suppress sustained T-cell-mediated inflammation in rheumatoid arthritis.Signal transduction and targeted therapy · 2026Article
- Review
- Immune profiling in orthopaedic diseases using mass cytometry : a narrative review of applications and future directions.Bone & joint research · 2026Article
- Immunological heterogeneity in rheumatoid arthritis: challenges in early-stage stratification, non-response to targeted therapy, and the restoration of immune tolerance.Frontiers in immunology · 2026Review
- Th Cell Phenotypes and Their Correlations with Disease Activity in Patients with Rheumatoid Arthritis.Journal of clinical medicine · 2025Article
- Understanding rheumatic disease through continuous cell state analysis.Nature reviews. Rheumatology · 2025Review
- Immunophenotyping of Patients With Rheumatoid Arthritis Reveals Difference in CD27Mediators of inflammation · 2025Article
- Metabolic reprogramming as a therapeutic target for modulating the Th17/Treg balance in autoimmune diseases: a comprehensive review.Frontiers in immunology · 2025Review
- CyCadas: accelerating interactive annotation and analysis of clustered cytometry data.Bioinformatics (Oxford, England) · 2024Article
- Article
- Augmenting regulatory T cells: new therapeutic strategy for rheumatoid arthritis.Frontiers in immunology · 2024Review
Corrections and comments
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Authors and funding
9 authors.
Funding
Abstract
Background: Despite the report of an imbalance between CD4 Objectives: To capture previously reported Th imbalance in RA with deep immunophenotyping techniques; to compare hypothesis-free unsupervised automated clustering with hypothesis-driven conventional biaxial gating and explore if Th cell heterogeneity accounts for conflicting association results. Methods: Unstimulated and stimulated peripheral blood mononuclear cells from 10 patients with RA and 10 controls were immunophenotyped with a 37-marker panel by mass cytometry (chemokine receptors, intra-cellular cytokines, intra-nuclear transcription factors). First, conventional biaxial gating and standard definitions of Th cell subsets were applied to compare subset frequencies between cases and controls. Second, unsupervised clustering was performed with FlowSOM and analysed using mixed-effects modelling of Associations of Single Cells (MASC). Results: Conventional analytical techniques fail to identify classical Th subset imbalance, while unsupervised automated clustering, by allowing for unusual marker combinations, identified an imbalance between pro- and anti-inflammatory subsets. For example, a pro-inflammatory Th1-like (IL-2 Conclusion: Taking an unbiased approach to large dataset analysis using automated clustering algorithms captures non-canonical CD4
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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.