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Record W2151961400 · doi:10.1096/fj.11-196915

Influenza A virus inhibits cytoplasmic stress granule formation

2011· article· en· W2151961400 on OpenAlexafffund
Denys A. Khaperskyy, Todd F. Hatchette, Craig McCormick

Bibliographic record

VenueThe FASEB Journal · 2011
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicRNA Research and Splicing
Canadian institutionsBeatrice Hunter Cancer Research InstituteQueen Elizabeth II Health Sciences CentreDalhousie University
FundersCanadian Institutes of Health ResearchNova Scotia Health Research Foundation
KeywordsStress granulePolysomeCell biologyCytoplasmBiologyProtein biosynthesisVirusTranslation (biology)RNAViral replicationMessenger RNAInfluenza A virusChemistryMolecular biologyVirologyRibosomeBiochemistryGene

Abstract

fetched live from OpenAlex

An important component of the mammalian stress response is the reprogramming of translation. A variety of stresses trigger abrupt polysome disassembly and the accumulation of stalled translation preinitiation complexes. These complexes nucleate cytoplasmic stress granules (SGs), sites of mRNA triage in which mRNAs from disassembling polysomes are sorted and the fates of individual transcripts are determined. Here, we demonstrate that influenza A virus (IAV) actively suppresses SG formation during infection, thereby allowing translation of viral mRNAs. Complete inhibition of SG formation is dependent on the function of the viral nonstructural protein 1 (NS1); at late times postinfection, cells infected with NS1-mutant viruses formed SGs in a double-stranded RNA-activated protein kinase (PKR)-dependent fashion. In these cells, SG formation correlated with inhibited viral protein synthesis. Together, these experiments demonstrate the antiviral potential of SGs and reveal a viral countermeasure that limits SG formation.

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 score0.001
Threshold uncertainty score0.002

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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.031
GPT teacher head0.267
Teacher spread0.236 · 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

Citations152
Published2011
Admission routes2
Has abstractyes

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