Impact de l'inflammation intestinale sur la dynamique et la fonction des lymphocytes T régulateurs
Bibliographic record
Abstract
Inflammatory bowel disease (IBD) are characterized by an excessive secretion of pro-inflammatory cytokines, hyperactivation of effector T cells (Teff) and insufficient control by regulatory T cells (Treg). We showed that treatment with anti-TNFbeta is accompanied by a significant increase in Foxp3+ Treg in the blood of patients with IBD. Infliximab is also associated with a potentiation of Treg suppressive function. In a second study, we showed that Treg are unable to completely prevent colitis, even as we have shown a significant increase in the number of Treg in the mesenteric lymph nodes and also an increase in number and the ex-vivo suppressive function of Treg cells from the inflammatory colon. The positive impact of intestinal inflammation on the suppressive function of Treg from the mesenteric lymph nodes was selective in the sub-population of Treg NRP1- majority representing iTreg. The significant decrease both in vitro and in vivo neo-conversion of LT to naïve Treg in inflammatory conditions, contributing to the inability of Treg to contain colitis. In a third study, we systematically studied the dynamics of LT Th1, Th17 and Treg as well as subpopulations of CD4+ T cells that co-express IL-17/IFNgamma, IL-17/Foxp3 and IFNgamma/Foxp3 from a cohort of IBD patients in clinical remission followed every 3 months. A rise in the blood of a Treg Foxp3+ mixed population producing IL-17 preceded the onset of a relapse of IBD suggesting a pathogenic potential of this subpopulation of LT. All these elements illustrate the concepts of conversion and plasticity of Treg in IBD but also the key role of Treg as a target to optimize and develop new biological therapies
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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 | 0.001 | 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".