A nuclear translation-like factor eIF4AIII is recruited to the mRNA during splicing and functions in nonsense-mediated decay
Bibliographic record
Abstract
In eukaryotes, a surveillance mechanism known as nonsense-mediated decay (NMD) degrades the mRNA when a premature-termination codon (PTC) is present. NMD requires translation to read the frame of the mRNA and detect the PTC. During pre-mRNA splicing, the exon-exon junction complex (EJC) is recruited to a region 20-24 nt upstream of the exon junction on the mature mRNA. The presence of a PTC upstream from the EJC elicits NMD. Eukaryotic initiation factor 4A (eIF4A) III is a nuclear protein that interacts physically or functionally with translation initiation factors eIF4G and eIF4B, respectively, and shares strikingly high identity with the initiation factors eIF4AI/II. Here we show that siRNA against eIF4AIII, but not against eIF4AI/II, inhibits NMD. Moreover, eIF4AIII, but not eIF4AI, is specifically recruited to the EJC during splicing. The observations that eIF4AIII is loaded onto the mRNA during splicing in the nucleus, has properties related to a translation initiation factor, and functions in NMD raises the possibility that eIF4AIII substitutes for eIF4AI/II during NMD.
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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".