HEBAlt enhances the T-cell potential of fetal myeloid-biased precursors
Bibliographic record
Abstract
Hematopoiesis is controlled by the interplay between transcription factors and environmental signals. One of the primary determinants of the T-lineage choice is Delta-like (DL)-Notch signaling, which promotes T-cell development and inhibits B-cell development. We have found that the transcription factor HEBAlt is up-regulated in early hematopoietic precursors in response to DL-Notch signaling and that it can promote early T-cell development. Here, we identified a population of lineage-negative Sca-1⁻c-kit(+) (LK) cells in the mouse fetal liver that rapidly gave rise to myeloid cells and B cells but exhibited very little T-cell potential. However, forced expression of HEBAlt in these precursors restored their ability to develop into T cells. We also showed that Ikaros and Notch1 are up-regulated in response to HEBAlt over-expression and that activated Notch1 enhances the ability of LK cells to enter the T-cell lineage. Furthermore, the myeloid transcription factor C/EBPα is down-regulated in response to HEBAlt. We therefore propose that HEBAlt plays a role in the network that enforces the T-lineage fate and limits myeloid fate during hematopoiesis.
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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) | 0.002 | 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".