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Record W2989631601 · doi:10.1039/c9np00052f

Selective targeting of the DEAD-box RNA helicase eukaryotic initiation factor (eIF) 4A by natural products

2019· review· en· W2989631601 on OpenAlex
Leo Shen, Jerry Pelletier

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

VenueNatural Product Reports · 2019
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA and protein synthesis mechanisms
Canadian institutionsMcGill University Health CentreMcGill University
FundersCanadian Institutes of Health Research
KeywordsHelicaseRNA Helicase ADEAD boxRNABiologyComputational biologyVirologyGeneticsGene

Abstract

fetched live from OpenAlex

Covering: up to 2019Pharmacological targeting of eukaryotic mRNA translation initiation is a promising approach for cancer therapy, since several signaling pathways that are commonly deregulated during tumor progression converge on this process. The DEAD-box helicase, eukaryotic initiation factor (eIF) 4A, is essential for translation initiation and facilitates the loading of the 43S pre-initiation complex onto mRNAs. Hippuristanol, rocaglates, and pateamine A are natural products that each target eIF4A by interfering with the helicase's RNA-binding activity in distinct manners. They exert a selective change in gene expression that results in potent anti-tumorigenic activity in pre-clinical studies. This review will provide an update on the molecular mechanisms of action of these natural products.

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)0.001
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.368
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.020
GPT teacher head0.284
Teacher spread0.263 · 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