IRF4 is essential for IL-21-mediated induction, amplification, and stabilization of the Th17 phenotype
Bibliographic record
Abstract
Differentiation of murine T-helper (Th) 17 cells is induced by antigenic stimulation and the sequential action of the cytokines IL-6, IL-21, and IL-23, along with TGFbeta. Current dogma proposes that IL-6 induces IL-21, which, in a STAT3-dependent manner, amplifies its own transcription, contributes to IL-17 production, and, moreover, promotes the expression of the IL-23 receptor. This, in turn, prepares cells for IL-23-mediated stabilization of the Th17 phenotype. Here we demonstrate that these effects of IL-21 on Th17 differentiation are completely dependent on IFN regulatory factor 4 (IRF4). After culturing in the presence of IL-21 plus TGFbeta, IRF4-deficient (Irf4(-/-)) Th cells showed a profound intrinsic defect in IL-17 production and in the autocrine IL-21 loop. Likewise, the levels of IL-23 receptor and the lineage-specific orphan nuclear receptors RORalpha and RORgammat were diminished, whereas the T regulatory (Treg) transcription factor forkhead box P3 (Foxp3) was strongly up-regulated, consistent with the reciprocal relationship between Th17 and Treg development. Despite this loss of IL-21 functions, IL-21-induced STAT3 activation was unimpaired and induced normal Socs3 expression. Forced expression of Foxp3 in WT cells inhibited IL-21-mediated IL-17 production, suggesting that the increase in Foxp3 contributes to the Irf4(-/-) phenotype. Additionally, the low levels of RORalpha and RORgammat are also partially responsible, because simultaneous overexpression of both proteins restored IL-17 production in Irf4(-/-) cells to some extent. These data highlight IRF4 as a decisive factor during the IL-21-mediated steps of Th17 development by influencing the balance of Foxp3, RORalpha, and RORgammat.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".