Divergence in the requirements for HEB factors in the generation and function of fetal-derived versus adult-derived γδ T cells (HEM2P.245)
Bibliographic record
Abstract
Abstract Gamma-delta (γδ) T cells are involved in mucosal immunity, wound healing, and tumor immunosurveillance. γδ T cells are programmed in the thymus to produce either IL-17 or IFNγ, but the molecular basis of this programming is not well understood. Here we show that mice lacking the E protein transcription factor HEB are defective in their ability to generate Vγ4 γδ T cells in fetal thymic organ culture. Since the HEB null allele is embryonic lethal, we generated mice lacking HEB only in hematopoietic cells by crossing HEBfl/fl mice with Vav-Cre mice (HEBfl/fl;vav-cre). These mice show a partial block in αβ T cell development, as seen in the fetal thymus of HEB-/- mice. In stark contrast to fetal gd T cells, however, the frequency of Vγ4 γδ T cells in the thymus of the HEBfl/fl;vav-cre mice is the equivalent to that in the WT thymus. Nonetheless, there is a skewing toward the CD27+ γδ T cells and away from CCR6+ γδ T cells, in both Vγ4+ and Vγ4- populations, suggesting a biased programming towards an IFNγ producing fate and away from the IL-17 producing fate. Moreover, there is a selective expansion of CD27+ Vγ4+ γδ T cells in the spleen, at the expense of other γδ T cell subsets, and a loss of CCR6+ Vγ4 γδ T cells in the lungs of HEBfl/fl;vav-cre mice. These results reveal that fetal Vγ4 cells are HEB-dependent, while adult Vγ4 cells appear to not require HEB, and strongly suggests that HEB is required for the generation and/or maintenance of IL-17 producing γδ T cells.
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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".