The P-body protein 4E-T represses translation to regulate the balance between cell genesis and establishment of the postnatal NSC pool
Bibliographic record
Abstract
Here, we ask how developing precursors maintain the balance between cell genesis for tissue growth and establishment of adult stem cell pools, focusing on postnatal forebrain neural precursor cells (NPCs). We show that these NPCs are transcriptionally primed to differentiate and that the primed mRNAs are associated with the translational repressor 4E-T. 4E-T also broadly associates with other NPC mRNAs encoding transcriptional regulators, and these are preferentially depleted from ribosomes, consistent with repression. By contrast, a second translational regulator, Cpeb4, associates with diverse target mRNAs that are largely ribosome associated. The 4E-T-dependent mRNA association is functionally important because 4E-T knockdown or conditional knockout derepresses proneurogenic mRNA translation and perturbs maintenance versus differentiation of early postnatal NPCs in culture and in vivo. Thus, early postnatal NPCs are primed to differentiate, and 4E-T regulates the balance between cell genesis and stem cell expansion by sequestering and repressing mRNAs encoding transcriptional regulators.
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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) | 0.001 | 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".