The neonatal microenvironment programs innate γδ T cells through the transcription factor STAT5
Bibliographic record
Abstract
IL-17-producing RORγt+ γδ T cells (γδT17 cells) are innate lymphocytes that participate in type 3 immune responses during infection and inflammation. Herein, we show that γδT17 cells rapidly proliferate within neonatal lymph nodes and gut, where, upon entry, they upregulate T-bet and coexpress IL-17, IL-22, and IFN-γ in a STAT3- and retinoic acid-dependent manner. Neonatal expansion was halted in mice conditionally deficient in STAT5, and its loss resulted in γδT17 cell depletion from all adult organs. Hyperactive STAT5 mutant mice showed that the STAT5A homolog had a dominant role over STAT5B in promoting γδT17 cell expansion and downregulating gut-associated T-bet. In contrast, STAT5B preferentially expanded IFN-γ-producing γδ populations, implying a previously unknown differential role of STAT5 gene products in lymphocyte lineage regulation. Importantly, mice lacking γδT17 cells as a result of STAT5 deficiency displayed a profound resistance to experimental autoimmune encephalomyelitis. Our data identify that the neonatal microenvironment in combination with STAT5 is critical for post-thymic γδT17 development and tissue-specific imprinting, which is essential for infection and autoimmunity.
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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 | 0.000 |
| 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 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".