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Record W2108561315 · doi:10.1093/nar/gkm1007

The eIF4G homolog DAP5/p97 supports the translation of select mRNAs during endoplasmic reticulum stress

2007· article· en· W2108561315 on OpenAlexaff
Stephen M. Lewis, Sonia Cerquozzi, Tyson E. Graber, Nicoleta Hosszu Ungureanu, Marcus H. Andrews

Bibliographic record

VenueNucleic Acids Research · 2007
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEndoplasmic Reticulum Stress and Disease
Canadian institutionsChildren's Hospital of Eastern Ontario
Fundersnot available
KeywordsEIF4GInternal ribosome entry siteUnfolded protein responseBiologyEndoplasmic reticulumTranslation (biology)Cell biologyMessenger RNAGeneticsGene

Abstract

fetched live from OpenAlex

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.503

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.017
GPT teacher head0.312
Teacher spread0.294 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations88
Published2007
Admission routes1
Has abstractyes

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