Effect of All-transretinoic Acid on Th17 and T Regulatory Cell Subsets in Patients with Ankylosing Spondylitis
Bibliographic record
Abstract
OBJECTIVE: We compared Th17 and T regulatory cells in patients with ankylosing spondylitis (AS) and in healthy controls. The effect of all-transretinoic acid (ATRA) was studied on cultured CD4+ T cells of patients with AS compared to controls. METHODS: Eighteen patients with AS and 18 age- and sex-matched healthy controls were included. CD4+ T cells were separated and cultured in conditions of anti-CD3 and anti-CD28 stimulation with and without ATRA. Intracellular and secreted cytokines, transcription factors, and gene expression were evaluated after 72 h. RESULTS: The frequency of CD4+IL-17+ T cells was significantly higher in patients with AS compared to controls, and ATRA could significantly decrease it. The frequency of forkhead box protein 3 (FOXP3)+ retinoic acid-related orphan receptor γt (RORγt) negative T-bet negative CD4+ cells was significantly lower in cases compared to controls. Intracellular and secreted interferon-γ (IFN-γ) was not significantly different between cases and controls. ATRA significantly increased intracellular IFN-γ in cases but not in controls. Tumor necrosis factor-α (TNF-α) secretion was significantly higher and interleukin 10 secretion was significantly lower in culture supernatant of cases compared to controls. ATRA could significantly decrease TNF-α secretion in cases. CONCLUSION: Our findings favor a pathogenic role for Th17 cells in AS. Th1 cells did not seem to contribute in the pathogenesis of this disease. The effect of ATRA as an immunomodulator on deviated immune cells was associated with decreased inflammatory markers. This association could be a reason for a clinical trial of ATRA in patients with AS.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".