HEB Restrains Effector Gene Expression during Early CD8 <sup>+</sup> Memory Precursor T Cell Differentiation
Bibliographic record
Abstract
Memory T cells are essential for maintaining long-term adaptive immunity. Memory cell precursors and short-lived effector cells emerge from undifferentiated naïve T cells directly downstream of TCR signaling but little is known about how this lineage choice is regulated at the molecular level. The transcription factor HEB is known to be an important regulator of thymic T cell development, but how it functions in peripheral T cell differentiation is poorly understood. We assessed the role of HEB in the differentiation of memory-like T cell precursors by inducing TCR signaling in CD8 T cells in the context of memory-polarizing cytokines or inflammatory conditions and found that CD8 T cells from HEB-deficient mice underwent accelerated differentiation as compared to WT cells. Transcriptomic analysis revealed aberrant upregulation of immune response genes and decreased expression of genes promoting stemness from the earliest stages of post-TCR signal activation and persisting throughout the course of differentiation. In addition, acute viral infection of HEB cKO mice resulted in enhanced memory precursor cell formation and increased effector functionality. Therefore, we have identified HEB as a central participant in the gene regulatory networks that regulate early CD8 memory T cell differentiation and effector gene expression. This study showed that naïve CD8 T cells lacking HEB exhibit increased TCR signal strength and loss of signatures of stem-ness, revealing a role for HEB in promoting immune memory.
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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) | 0.001 | 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".