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Record W2012147632 · doi:10.1152/ajpcell.00511.2008

The eIF4E-binding proteins are modifiers of cytoplasmic eIF4E relocalization during the heat shock response

2009· article· en· W2012147632 on OpenAlexafffund
Rami Sukarieh, Nahum Sonenberg, Jerry Pelletier

Bibliographic record

VenueAmerican Journal of Physiology-Cell Physiology · 2009
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPI3K/AKT/mTOR signaling in cancer
Canadian institutionsMcGill University
FundersNational Cancer InstituteNational Institutes of HealthMcGill University
KeywordsEIF4ETranslation (biology)Cell biologyRepressorHeat shock proteinEukaryotic translationProtein biosynthesisEukaryotic translation initiation factor 4 gammaBiologyMessenger RNAGeneticsTranscription factorGene

Abstract

fetched live from OpenAlex

Stress granules (SGs) arise as a consequence of cellular stress, contain stalled translation preinitiation complexes, and are associated with cell survival during environmental insults. SGs are dynamic entities with proteins relocating into and out of them during stress. Among the repertoire of proteins present in SGs is eukaryotic initiation factor 4E (eIF4E), a translation factor required for cap-dependent translation and that regulates a rate-limiting step for protein synthesis. Herein, we demonstrate that localization of eIF4E to SGs is dependent on the presence of a family of repressor proteins, eIF4E-binding proteins (4E-BPs). Our results demonstrate that 4E-BPs regulate the SG localization of eIF4E.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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.

Opus teacher head0.005
GPT teacher head0.231
Teacher spread0.226 · 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 source (direct Gemma or distilled Codex), 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

Citations30
Published2009
Admission routes2
Has abstractyes

Explore more

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