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Record W2112318650 · doi:10.1086/344237

Characterization of 2 Influenza A(H3N2) Clinical Isolates with Reduced Susceptibility to Neuraminidase Inhibitors Due to Mutations in the Hemagglutinin Gene

2002· article· en· W2112318650 on OpenAlexaff
Yacine Abed, Anne–Marie Bourgault, Robert J. Fenton, Peter J. Morley, David Gower, Ian J. Owens, Margaret Tisdale, Guy Boivin

Bibliographic record

VenueThe Journal of Infectious Diseases · 2002
Typearticle
Languageen
FieldMedicine
TopicInfluenza Virus Research Studies
Canadian institutionsHôpital Saint-LucUniversité LavalCentre hospitalier de l'Université Laval
Fundersnot available
KeywordsZanamivirNeuraminidaseVirologyBiologyHemagglutinin (influenza)Neuraminidase inhibitorVirusOseltamivirInfluenza A virusIn vitroGeneOrthomyxoviridaeMicrobiologyBiochemistryMedicineInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex

Previous studies have shown that amino acid changes in the hemagglutinin (HA) gene of influenza viruses may result in decreased susceptibility to neuraminidase inhibitors (NAIs) in vitro. However, the emergence and characteristics of such HA variants in the clinical setting remain poorly studied. Herein, we report 2 influenza A(H3N2) isolates, from untreated patients, harboring an Arg229-->Ile substitution in the HA1 gene. The Ile229 variants were as sensitive as the Arg229 viruses to zanamivir and oseltamivir in neuroaminidase inhibition assays but were significantly less susceptible (by 60-140-fold) in cell-based assays. Although the Ile229 variants adsorbed less efficiently to Madin-Darby canine kidney (MDCK) cells in kinetic binding assays, they remained very sensitive to zanamivir in ferrets. Our study shows the importance of the HA1 229 residue in virus binding to MDCK cells and confirms the unreliability of cell-based assays in predicting the in vivo susceptibility of HA variants to NAIs.

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)0.001
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.142
Threshold uncertainty score0.441

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.061
GPT teacher head0.370
Teacher spread0.310 · 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 designObservational
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

Citations58
Published2002
Admission routes1
Has abstractyes

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