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Record W2142834124 · doi:10.1128/jvi.00386-15

Timing Is Everything: Coordinated Control of Host Shutoff by Influenza A Virus NS1 and PA-X Proteins

2015· review· en· W2142834124 on OpenAlexafffund
Denys A. Khaperskyy, Craig McCormick

Bibliographic record

VenueJournal of Virology · 2015
Typereview
Languageen
FieldMedicine
TopicInfluenza Virus Research Studies
Canadian institutionsDalhousie University
FundersCanadian Institutes of Health Research
KeywordsBiologyHost (biology)VirologyViral replicationVirusTranslation (biology)Influenza A virusBiogenesisCell biologyMessenger RNAGeneticsGene

Abstract

fetched live from OpenAlex

Like all viruses, influenza viruses (IAVs) use host translation machinery to decode viral mRNAs. IAVs ensure efficient translation of viral mRNAs through host shutoff, a process whereby viral proteins limit the accumulation of host proteins through subversion of their biogenesis. Despite its small genome, the virus deploys multiple host shutoff mechanisms at different stages of infection, thereby ensuring successful replication while limiting the communication of host antiviral responses. In this Gem, we review recent data on IAV host shutoff proteins, frame the outstanding questions in the field, and propose a temporally coordinated model of IAV host shutoff.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
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 head0.153
GPT teacher head0.442
Teacher spread0.289 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations65
Published2015
Admission routes2
Has abstractyes

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