Post-transcriptional regulatory pre-complex assembly drives timely cell-state transitions during differentiation
Bibliographic record
Abstract
Abstract Complexes that control mRNA stability and translation promote timely cell-state transitions during differentiation by ensuring appropriate expression patterns of key developmental regulators. The Drosophila RNA-binding protein Brain tumor (Brat) promotes degradation of target transcripts during the maternal-to-zygotic transition in syncytial embryos and in uncommitted intermediate neural progenitors (immature INPs). We identified Ubiquitin-specific protease 5 (Usp5) as a Brat interactor essential for the degradation of Brat target mRNAs in both cell types. Usp5 promotes Brat-dedadenylase pre-complex assembly in mitotic neural stem cells (neuroblasts) by bridging Brat and the scaffolding components of deadenylase complexes lacking their catalytic subunits. The adaptor protein Miranda binds the RNA-binding domain of Brat, limiting its ability to bind target mRNAs in mitotic neuroblasts. Cortical displacement of Miranda activates Brat-mediated mRNA decay in immature INPs. We propose that the assembly of an enzymatically inactive and RNA-binding-deficient pre-complex poises mRNA degradation machineries for rapid activation driving timely developmental transitions.
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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 | 0.001 |
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".