All-trans retinoic acid down-regulates inflammatory responses by shifting the Treg/Th17 profile in human ulcerative and murine colitis
Bibliographic record
Abstract
IBD is characterized by uncontrolled immune responses in inflamed mucosa, with dominance of IL-17-producing cells and deficiency of Treg cells. The aim of this study was to explore the effect and mechanisms of RA, the ligand of RARalpha, on immune responses in human and murine colitis. Colonic biopsies from patients with UC were cultured and treated with RA as the agonist of RARalpha or LE135 as the antagonist of RARalpha. Expressions of IL-17 and FOXP3 were detected by immunohistochemistry. Murine colitis was induced by intrarectal administration with TNBS at Day 1. Mice were then i.p.-treated with RA or LE135 daily for 7 days. Cytokine levels in the cultures of mouse LPMCs were measured. Expressions of FOXP3 and IL-17 in colon tissues or MLN were detected by immunohistological analysis. Body weight and colon inflammation were evaluated. RA treatment up-regulated FOXP3 expression and down-regulated IL-17 expression in colon biopsies of patients and in colon tissues and MLN of mice with colitis compared with controls. LPMCs from RA-treated mice produced lower levels of proinflammatory cytokines (TNF-alpha, IL-1beta, IL-17) but more regulatory cytokines (IL-10, TGF-beta) compared with that of untreated mice. LE135 showed the opposite effect of RA. Furthermore, RA ameliorated TNBS-induced colitis in a dose-dependent manner, as seen by improved body weight and colon inflammation. RA down-regulates colon inflammatory responses in patients with IBD in vitro and in murine colitis in vivo, representing a potential therapeutic approach in IBD treatment.
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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 | 0.000 |
| 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".