IL-1 and IL-33 differentially regulate the functional specialization of mucosal Foxp3+ regulatory T cells.
Bibliographic record
Abstract
Abstract CD4+ regulatory T (TREG) cells are critical mediators of peripheral immune tolerance and homeostasis, and express the forkhead box p3 (Foxp3) transcription factor, the master-regulator driving the programming of the TREG cell suppressive phenotype. TREG cells are abundant at mucosal surfaces, where they acquire tissue-specific adaptations. The biological consequences of these adaptations on the stability of thymic-derived TREG (tTreg) cells remain largely unknown. To determine the signals that drive the fate of TREG cells, we isolated and compared stable from unstable TREG cells using a TREG transfer model where we previously observed the functional reprogramming of Foxp3+ TREG cells into Th1/Th17 effector T cells. We identified the expression of the IL-33 receptor (IL-33R, ST2) on stable tTREG cells and the IL-1 receptor (IL1R1) on unstable exTREG cells undergoing functional reprogramming. We show that both TREG cell populations represent competing subsets in inflammatory conditions. This is further underlined by the fact that the absence of IL1R1 expression (IL1R1−/−) leads to the accumulation of ST2+ TREG cells at mucosal sites in vivo. In two distinct lung infection models, we demonstrate that ST2-expressing TREG cells express GATA3 and resist production of inflammatory cytokines, whereas IL1R1-expressing TREG cells express RORγT and lose Foxp3 expression in vivo. While IL-1 signaling impairs TREG cell suppressive function, ST2 is required for the maintenance of the lineage identity and suppressive function of TREG cells. These observations demonstrate that IL-1 and IL-33 produced during immune challenge exert distinct roles on the functional adaptation of Foxp3+ tTREG cells at mucosal surfaces.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".