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Record W2064570507 · doi:10.1371/journal.pone.0103601

Switch from Cap- to Factorless IRES-Dependent 0 and +1 Frame Translation during Cellular Stress and Dicistrovirus Infection

2014· article· en· W2064570507 on OpenAlexafffund
Qing S. Wang, Eric Jan

Bibliographic record

VenuePLoS ONE · 2014
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Virus Research Studies
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health ResearchMichael Smith Health Research BCGenome Canada
KeywordsInternal ribosome entry siteTranslation (biology)BiologyCell biologyEukaryotic translationProtein biosynthesisVirologyGeneticsMessenger RNAGene

Abstract

fetched live from OpenAlex

Internal ribosome entry sites (IRES) are utilized by a subset of cellular and viral mRNAs to initiate translation during cellular stress and virus infection when canonical cap-dependent translation is compromised. The intergenic region (IGR) IRES of the Dicistroviridae uses a streamlined mechanism in which it can directly recruit the ribosome in the absence of initiation factors and initiates translation using a non-AUG codon. A subset of IGR IRESs including that from the honey bee viruses can also direct translation of an overlapping +1 frame gene. In this study, we systematically examined cellular conditions that lead to IGR IRES-mediated 0 and +1 frame translation in Drosophila S2 cells. Towards this, a novel bicistronic reporter that exploits the 2A "stop-go" peptide was developed to allow the detection of IRES-mediated translation in vivo. Both 0 and +1 frame translation by the IGR IRES are stimulated under a number of cellular stresses and in S2 cells infected by cricket paralysis virus, demonstrating a switch from cap-dependent to IRES-dependent translation. The regulation of the IGR IRES mechanism ensures that both 0 frame viral structural proteins and +1 frame ORFx protein are optimally expressed during virus infection.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.558
Threshold uncertainty score0.502

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.056
GPT teacher head0.222
Teacher spread0.166 · 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 teacher head, 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

Citations20
Published2014
Admission routes2
Has abstractyes

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