Bibliographic record
Abstract
Shutting down nuclear export of unspliced tRNA keeps cells in G1 during DNA repair, say Ata Ghavidel and colleagues (University of Toronto, Canada). Figure 1 Unspliced tRNAs (green) accumulate in the nucleus in response to DNA damage (right). The authors found that DNA damage caused the nuclear accumulation of tRNAs containing unspliced introns, which are removed in the cytoplasm. This accumulation required the damage-induced signaling molecule Rad53 and correlated with the retention of the main tRNA export receptor, Los1, in the cytoplasm. Without their exporter, tRNAs were stuck in the nucleus, causing cell cycle arrest in G1 and giving the cell time to repair damage before DNA synthesis. Deleting Rad53 prevented the nuclear tRNA build-up, and damaged cells exited G1 prematurely. Deleting Los1 in these cells restored the G1 arrest. The G1 stall was not due to decreased cytoplasmic tRNA, which remained in large excess due to its long turnover time. Instead, the stall stemmed from the surplus of nuclear tRNA, which somehow enhanced translation of a stress response factor called Gcn4—a protein that promotes repair and slows the synthesis of G1 cyclins. “This process couples the nuclear sensing of DNA damage to cytoplasmic protein synthesis,” Ghavidel says. “It was an entirely unanticipated mechanism, since tRNA export has traditionally been viewed as constitutive.” Reference: Ghavidel, A., et al. 2007. Cell. 131:915–926. [PubMed]
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 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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".