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Record W200761781 · doi:10.1177/135965350400900404

A Reverse Genetics Study of Resistance to Neuraminidase Inhibitors in An Influenza A/H1N1 Virus

2004· article· en· W200761781 on OpenAlexaff
Yacine Abed, Nathalie Goyette, Guy Boivin

Bibliographic record

VenueAntiviral Therapy · 2004
Typearticle
Languageen
FieldMedicine
TopicInfluenza Virus Research Studies
Canadian institutionsUniversité LavalCentre hospitalier de l'Université Laval
Fundersnot available
KeywordsZanamivirNeuraminidaseOseltamivirMutantVirologyVirusNeuraminidase inhibitorBiologyInfluenza A virusReverse geneticsWild typeViral replicationResistance mutationOrthomyxoviridaeMolecular biologyGeneReverse transcriptaseGeneticsPolymerase chain reactionMedicine

Abstract

fetched live from OpenAlex

A system of reverse genetics was used to generate influenza A/H1N1 viruses harbouring neuraminidase (NA) mutations previously associated with resistance to NA inhibitors in various viral subtypes. The His274Tyr and Glu119Gln mutants were rescued whereas the Arg292Lys and Glu1l9 --> Gly, Val, Ala or Asp mutants could not be generated. In NA inhibition assays, the His274Tyr mutant was resistant to oseltamivir (430-fold over wild-type) and BCX-1812 (50-fold) but was sensitive to zanamivir. A similar trend was seen when the mutant was evaluated by plaque reduction assay (PRA). The Glu119Gln mutant expressed a low level of resistance to oseltamivir (nine-fold) and zanamivir (fourfold) in NA inhibition assay but was only marginally resistant to oseltamivir (fourfold) in PRA. The replication capacity of both mutants, in particular that of the His274Tyr virus, was impaired when compared with the wild-type virus in vitro.

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 score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
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)0.0010.000

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 head0.113
GPT teacher head0.417
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

Citations84
Published2004
Admission routes1
Has abstractyes

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