Gfi1 negatively regulates Th17 differentiation by inhibiting ROR t activity
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Bibliographic record
Abstract
T(h) cells have long been divided into two subsets, T(h)1 and T(h)2; however, recently, T(h)17 and inducible regulatory T (iTreg) cells were identified as new T(h) cell subsets. Although T(h)1- and T(h)2-polarizing cytokines have been shown to suppress T(h)17 and iTreg development, transcriptional regulation of T(h)17 and iTreg differentiation by cytokines remains to be clarified. In this study, we found that expression of the growth factor independent 1 (Gfi1) gene, which has been implicated in T(h)2 development, was repressed in T(h)17 and iTreg cells compared with T(h)1 and T(h)2 lineages. Gfi1 expression was enhanced by the IFN-gamma/STAT1 and IL-4/STAT6 pathways, whereas it was repressed by the transforming growth factor-beta1 stimulation at the promoter level. Over-expression of Gfi1 strongly reduced IL-17A transcription in the EL4 T cell line, as well as in primary T cells. This was due to the blockade of recruitment of retinoid-related orphan receptor gammat to the IL-17A promoter. In contrast, IL-17A expression was significantly enhanced in Gfi1-deficient T cells under T(h)17-promoting differentiation conditions as compared with wild-type T cells. In contrast, the impacts of Gfi1 in iTregs were not as strong as in T(h)17 cells. Taken together, these data strongly suggest that Gfi1 is a negative regulator of T(h)17 differentiation, which represents a novel mechanism for the regulation of T(h)17 development by cytokines.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it