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Record W4252609642 · doi:10.3410/f.738203812.793583090

Faculty Opinions recommendation of Selective 40S Footprinting Reveals Cap-Tethered Ribosome Scanning in Human Cells.

2021· dataset· en· W4252609642 on OpenAlexaff
Luc DesGroseillers, Florence Bonnet‐Magnaval

Bibliographic record

VenueFaculty Opinions – Post-Publication Peer Review of the Biomedical Literature · 2021
Typedataset
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA and protein synthesis mechanisms
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsFootprintingInitiation factorEIF4EEukaryotic translationRibosomeInternal ribosome entry siteTranslation (biology)Start codonBiologyEukaryotic initiation factorFive prime untranslated regionRibosomal binding siteCell biologyMessenger RNAGeneticsRNAGeneBase sequence

Abstract

fetched live from OpenAlex

Translation regulation occurs largely during the initiation phase. Here, we develop selective 40S footprinting to visualize initiating 40S ribosomes on endogenous mRNAs in vivo. This reveals the positions on mRNAs where initiation factors join the ribosome to act and where they leave. We discover that in most human cells, most scanning ribosomes remain attached to the 5' cap. Consequently, only one ribosome scans a 5' UTR at a time, and 5' UTR length affects translation efficiency. We discover that eukaryotic initiation factor 3B (eIF3B,) eIF4G1, and eIF4E remain bound to 80S ribosomes as they begin translating, with a decay half-length of ∼12 codons. Hence, ribosomes retain these initiation factors while translating short upstream open reading frames (uORFs), providing an explanation for how ribosomes can reinitiate translation after uORFs in humans. This method will be of use for studying translation initiation mechanisms in vivo.Copyright © 2020 Elsevier Inc. All rights reserved. PMID: 32589966

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)0.002
metaresearch head score (Gemma)0.007
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: none
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.027
Threshold uncertainty score0.089

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0020.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.006
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0270.035

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 head0.026
GPT teacher head0.337
Teacher spread0.312 · 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
GenreDataset

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

Citations0
Published2021
Admission routes1
Has abstractyes

Explore more

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