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Record W2330185538 · doi:10.1080/15476286.2015.1137419

Cellular mRNA recruits the ribosome via eIF3-PABP bridge to initiate internal translation

2016· article· en· W2330185538 on OpenAlexafffund
Nehal Thakor, M. Duane Smith, Luc Roberts, Mame Daro Faye, Harshil Patel, Hans‐Joachim Wieden, J.H.D. Cate, Martin Holčı́k

Bibliographic record

VenueRNA Biology · 2016
Typearticle
Languageen
FieldMedicine
TopicViral Infections and Immunology Research
Canadian institutionsUniversity of OttawaChildren's Hospital of Eastern OntarioUniversity of Lethbridge
FundersCanadian Institutes of Health Research
KeywordsInternal ribosome entry siteBiologyCell biologyTranslation (biology)Eukaryotic translationEukaryotic initiation factorInitiation factorEIF4EMessenger RNARibosomeXIAPRNAGeneticsGeneProgrammed cell deathApoptosisCaspase

Abstract

fetched live from OpenAlex

IRES-mediated translation of key cell fate regulating genes has been implicated in tumorigenesis. Concerted action of canonical eukaryotic initiation factors and IRES transacting factors (ITAFs) was shown to regulate cellular IRES mediated translation; however, the precise molecular mechanism of ribosome recruitment to cellular IRESes remains unclear. Here we show that the X-linked inhibitor of apoptosis (XIAP) IRES operates in an evolutionary conserved viral like mode and the structural integrity, particularly in the vicinity of AUG, is critical for ribosome recruitment. The binding of eIF3 together with PABP potentiates ribosome recruitment to the IRES. Our data support the model in which eIF3 binds directly to the XIAP IRES RNA in a structure-dependent manner and acts as a scaffold for IRES RNA, PABP and the 40S ribosome.

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 score0.007

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 integrity0.0000.001
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 head0.087
GPT teacher head0.359
Teacher spread0.271 · 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

Citations41
Published2016
Admission routes2
Has abstractyes

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