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Activation of Interferon Regulatory Factor 3 Is Inhibited by the Influenza A Virus NS1 Protein

2000· article· en· W1977457899 on OpenAlexfundno aff
Julie Talon, Curt M. Horvath, Rosalind Polley, Christopher F. Basler, Thomas Muster, Peter Palese, Adolfo García‐Sastre

Bibliographic record

VenueJournal of Virology · 2000
Typearticle
Languageen
FieldMedicine
TopicInfluenza Virus Research Studies
Canadian institutionsnot available
FundersNational Institutes of HealthUniversity of TorontoAustrian Science FundÖsterreichischen Akademie der Wissenschaften
KeywordsBiologyInterferonVirusVirologyInterferon regulatory factorsInfluenza A virusVP40OrthomyxoviridaeHeterologousViral replicationMolecular biologyGeneTranscription factorGenetics

Abstract

fetched live from OpenAlex

We present a novel mechanism by which viruses may inhibit the alpha/beta interferon (IFN-alpha/beta) cascade. The double-stranded RNA (dsRNA) binding protein NS1 of influenza virus is shown to prevent the potent antiviral interferon response by inhibiting the activation of interferon regulatory factor 3 (IRF-3), a key regulator of IFN-alpha/beta gene expression. IRF-3 activation and, as a consequence, IFN-beta mRNA induction are inhibited in wild-type (PR8) influenza virus-infected cells but not in cells infected with an isogenic virus lacking the NS1 gene (delNS1 virus). Furthermore, NS1 is shown to be a general inhibitor of the interferon signaling pathway. Inhibition of IRF-3 activation can be achieved by the expression of wild-type NS1 in trans, not only in delNS1 virus-infected cells but also in cells infected with a heterologous RNA virus (Newcastle disease virus). We propose that inhibition of IRF-3 activation by a dsRNA binding protein significantly contributes to the virulence of influenza A viruses and possibly to that of other viruses.

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 score0.003

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)0.0010.001

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 head0.054
GPT teacher head0.358
Teacher spread0.304 · 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

Citations577
Published2000
Admission routes1
Has abstractyes

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