The alarmins IL-1 and IL-33 differentially regulate the functional specialisation of Foxp3+ regulatory T cells during mucosal inflammation
Why this work is in the frame
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Bibliographic record
Abstract
CD4 + Foxp3 + regulatory T (T REG ) cells are critical mediators of peripheral tolerance and modulators of immune responses. Functional adaptation of T REG cells, through acquisition of secondary transcription factors is critical for their effector differentiation towards local inflammatory stimuli including infections. The drivers and consequences of this adaptation of T REG cell function remain largely unknown. Using an unbiased screen, we identified receptors of the IL-1 family controlling the adaptation of T REG cells. Through respiratory infection models, we show that the IL-33 receptor (ST2) and the IL-1 receptor (IL1R1) selectively identify stable and unstable T REG cells at mucosal surfaces, respectively. IL-33, not IL-1, is specifically required for maintaining the suppressive function of T REG cells. In the absence of ST2, T REG cells are prone to lose Foxp3 expression and acquire RORT and IL1R1, while, in the absence of IL-1R1, they maintain Foxp3 expression and resist the acquisition of a Th17 phenotype. Finally, lack of IL-1 signalling enhances the accumulation of ST2 + T REG over pro-inflammatory T REG cells in a Cryptococcus neoformans infection. These observations show that IL-1 and IL-33 exert opposing functions in controlling the functional adaptation of T REG cells, ultimately dictating the dynamics of adaptive immunity to pathogens.
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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 | 0.000 | 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 | 0.001 | 0.001 |
| 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 it