Mutations in <i>STAT3</i> and <i>IL12RB1</i> impair the development of human IL-17–producing T cells
Bibliographic record
Abstract
The cytokines controlling the development of human interleukin (IL) 17--producing T helper cells in vitro have been difficult to identify. We addressed the question of the development of human IL-17--producing T helper cells in vivo by quantifying the production and secretion of IL-17 by fresh T cells ex vivo, and by T cell blasts expanded in vitro from patients with particular genetic traits affecting transforming growth factor (TGF) beta, IL-1, IL-6, or IL-23 responses. Activating mutations in TGFB1, TGFBR1, and TGFBR2 (Camurati-Engelmann disease and Marfan-like syndromes) and loss-of-function mutations in IRAK4 and MYD88 (Mendelian predisposition to pyogenic bacterial infections) had no detectable impact. In contrast, dominant-negative mutations in STAT3 (autosomal-dominant hyperimmunoglobulin E syndrome) and, to a lesser extent, null mutations in IL12B and IL12RB1 (Mendelian susceptibility to mycobacterial diseases) impaired the development of IL-17--producing T cells. These data suggest that IL-12Rbeta1- and STAT-3--dependent signals play a key role in the differentiation and/or expansion of human IL-17-producing T cell populations in vivo.
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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) | 0.000 | 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) | 0.002 | 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".