Gfi1 negatively regulates Th17 differentiation by inhibiting ROR t activity
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.001 |
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".