The eIF4G homolog DAP5/p97 supports the translation of select mRNAs during endoplasmic reticulum stress
Bibliographic record
Abstract
DAP5/p97 is a member of the eIF4G family of translation initiation factors that has been suggested to play an important role in the translation of select messenger RNA molecules. We have shown previously that the caspase-cleaved form of DAP5/p97, termed p86, is required for the induction of the endoplasmic reticulum (ER)-stress-responsive internal ribosome entry site (IRES) of the caspase inhibitor HIAP2. We show here that expression of DAP5/p97 is enhanced during ER stress by selective recruitment of DAP5/p97 mRNA into polysomes via the DAP5/p97 IRES. Importantly, enhanced translation mediated by the DAP5/p97 IRES is dependent on DAP5/p97 itself, thus providing a positive feedback loop. In addition, we show that activation of DAP5/p97 and HIAP2 IRES during ER stress requires DAP5/p97. Significantly, the induction of DAP5/p97 during ER stress is caspase-independent, whereas the induction of HIAP2 requires proteolytic processing of DAP5/p97. Thus, DAP5/p97 is a translational activator that selectively modulates translation of specific mRNAs during conditions of cellular stress in both a caspase-dependent and caspase-independent manner.
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) | 0.000 | 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".