Context-Dependent Regulation of Hematopoietic Lineage Choice by HEBAlt
Bibliographic record
Abstract
Hematopoietic development is controlled by combinatorial interactions between E-protein transcription factors and other lineage regulators that operate in the context of gene-regulatory networks. The E-proteins HEB and E2A are critical for T cell and B cell development, but the mechanisms by which their activities are directed to different genes in each lineage are unclear. We found that a short form of HEB, HEBAlt, acts downstream of Delta-like (DL)-Notch signaling to promote T cell development. In this paper, we show that forced expression of HEBAlt in mouse hematopoietic progenitors inhibited B cell development, but it allowed them to adopt a myeloid fate. HEBAlt interfered with the activity of E2A homodimers and with the expression of the transcription factor Pax5, both of which are critical for B cell development. However, when combined with DL-Notch signaling, HEBAlt enhanced the generation of T cell progenitors at the expense of myeloid cells. The longer form of HEB, HEBCan, also inhibited E47 activity and Pax5 expression, but it did not collaborate with DL-Notch signaling to suppress myeloid potential. Therefore, HEBAlt can suppress B cell or myeloid potential in a context-specific manner, which suggests a role for this factor in maintaining T lineage priming prior to commitment.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".