HEB plays a critical role in the generation of IL-17 producing Vγ2+ γδ T cells
Bibliographic record
Abstract
Abstract IL-17 producing Vγ2+ γδ T cells (Vγ2 T cells) form an integral part of the immune system of various lymphoid and mucosal tissues in mice. The γδ T cells acquire the ability to produce IL-17 during their thymic development but the molecular basis of this programming is not well understood. Here, we aim to characterized the role of HEB in the development of IL-17 producing Vγ2 T cells by utilizing HEB conditional knockout mice on a vav-Cre background (HEB conKO). First, we observed that there was a block in the development of Vγ2 T cells in the fetal thymic organ culture (FTOC) from HEB conKO embryos at E14. However, in contrast to the near absence of fetal thymic Vγ2 T cells in FTOC, neonatal thymus of HEB conKO mice supported the development of Vγ2 T cells, albeit at a significantly lower frequency than the wildtype thymus. Further, the frequency of Vγ2 T cells in the thymus of adult mice was the equivalent to that in the wildtype thymus, showing a gradual increase in the development of Vγ2 T cells in the HEB conKO thymus with age. As IL-17 producing γδ T cells have been shown to be generated preferentially during fetal development, we characterized the functional subsets of Vγ2 T cells found in adult HEB conKO mice. In fact, there was a significant reduction in the frequency of RORγt+ Vγ2+ T cells in the thymus of adult HEB conKO mice, as well as in the lungs, spleen and lymph nodes. Furthermore, the HEB-deficient Vγ2 T cells in the lungs, spleen and lymph nodes exhibited a profound deficiency in their ability to produce IL-17 in response to stimulation with IL-1β, IL-23 and IL-21 or PMA/Ionomycin. Collectively, our work shows for the first time that HEB is required for the generation of IL-17 producing Vγ2 T cells for various lymphoid and mucosal tissues.
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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) | 0.003 | 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".