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Record W2130410721 · doi:10.1089/jir.2012.0142

The Oncogene eIF4E: Using Biochemical Insights to Target Cancer

2013· review· en· W2130410721 on OpenAlex
Martin Carroll, Katherine L. B. Borden

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Interferon & Cytokine Research · 2013
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPI3K/AKT/mTOR signaling in cancer
Canadian institutionsUniversité de MontréalInstitute for Research in Immunology and Cancer
FundersNational Cancer InstituteCanadian Institutes of Health ResearchNational Institutes of Health
KeywordsEIF4ETranslation (biology)BiologyPI3K/AKT/mTOR pathwayMessenger RNAMAPK/ERK pathwayCell biologyEIF4A1Initiation factorOncogeneProtein kinase BCancer researchPhosphorylationSignal transductionGeneGeneticsCell cycle

Abstract

fetched live from OpenAlex

The eukaryotic translation initiation factor eIF4E is overexpressed in many human malignancies where it is typically a harbinger of poor prognosis. eIF4E is positioned as a nexus in post-transcriptional gene expression. To carry out these functions, eIF4E needs to bind the m(7)G cap moiety on mRNAs. It plays critical roles in mRNA translation, mRNA export, and most likely in mRNA stability as well. Through these activities, eIF4E coordinately modulates the expression of many transcripts involved in proliferation and survival. eIF4E function is controlled by interactions with protein cofactors in concert with many signaling pathways, including Ras, Mnk, Erk, MAPK, PI3K, mTOR, and Akt. This review describes the eIF4E activity and provides several examples of cellular control mechanisms. Further, we describe some therapeutic strategies in preclinical and clinical development.

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.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.765
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0010.002
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 head0.186
GPT teacher head0.490
Teacher spread0.305 · 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