TGF‐β1 production by CD4<sup>+</sup>CD25<sup>+</sup> regulatory T cells is not essential for suppression of intestinal inflammation
Bibliographic record
Abstract
Naturally occurring CD4+ CD25+ regulatory T cells (Treg) are potent suppressors of CD4+ and CD8+ T cell responses in vitro and inhibit several organ-specific autoimmune diseases. While most in vitro studies suggest that CD4+ CD25+ Treg cells adopt a cytokine-independent but cell contact-dependent mode of T cell regulation, their precise mechanism of suppression in vivo remains largely unknown. Here we examine the functional contribution of Treg cell-derived TGF-beta1 and effector T cell responsiveness to TGF-beta in CD4+ CD25+ T cell-mediated suppression of inflammatory bowel disease (IBD). We show that CD4+ CD25+ Treg cells from either TGF-beta1+/+ or neonatal TGF-beta1-/- mice can suppress the incidence and severity of IBD as well as colonic IFN-gamma mRNA expression induced by WT CD4+ CD25- effector T cells. Furthermore, TGF-beta-resistant Smad3-/- CD4+ CD25+ Treg cells are equivalent to WT Treg cells in their capacity to suppress disease induced by either WT or Smad3-/- CD4+ CD25- effector T cells. Finally, anti-TGF-beta treatment exacerbates the colitogenic potential of CD4+ CD25- effector T cells in the absence of CD4+ CD25+ Treg cells. Together, these data demonstrate that in certain situations CD4+ CD25+ T cells are able to suppress intestinal inflammation by a mechanism not requiring Treg cell-derived TGF-beta1 or effector T cell/Treg cell responsiveness to TGF-beta via Smad3.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".