HEB-Deficient T-Cell Precursors Lose T-Cell Potential and Adopt an Alternative Pathway of Differentiation
Bibliographic record
Abstract
Early thymocytes possess multilineage potential, which is progressively restricted as cells transit through the double-negative stages of T-cell development. DN1 cells retain the ability to become natural killer cells, dendritic cells, B cells, and myeloid cells as well as T cells, but these options are lost by the DN3 stage. The Notch1 signaling pathway is indispensable for initiation of the T-cell lineage and inhibitory for the B-cell lineage, but the regulatory mechanisms by which the T-cell fate is locked in are largely undefined. Previously, we discovered that the E-protein transcription factor HEBAlt promoted T-cell specification. Here, we report that HEB(-/-) T-cell precursors have compromised Notch1 function and lose T-cell potential. Moreover, reconstituting HEB(-/-) precursors with Notch1 activity enforced fidelity to the T-cell fate. However, instead of becoming B cells, HEB(-/-) DN3 cells adopted a DN1-like phenotype and could be induced to differentiate into thymic NK cells. HEB(-/-) DN1-like cells retained GATA3 and Id2 expression but had lower levels of the Bcl11b gene, a Notch target gene. Therefore, our studies have revealed a new set of interactions between HEB, Notch1, and GATA3 that regulate the T-cell fate choice in developing thymocytes.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".