In Vitro Properties and Virulence of Contemporary Recombinant Influenza B Viruses Harboring Mutations of Cross-Resistance to Neuraminidase Inhibitors
Bibliographic record
Abstract
Three neuraminidase inhibitors (NAIs: Oseltamivir, zanamivir and peramivir) are currently approved in many countries for the treatment of influenza A and B infections. The emergence of influenza B viruses (IBVs) containing mutations of cross-resistance to these NAIs constitutes a serious clinical threat. Herein, we used a reverse genetics system for the current B/Phuket/3073/2013 vaccine strain to investigate the impact on in vitro properties and virulence of H136N, R152K, D198E/N, I222T and N294S NA substitutions (N2 numbering), reported by the World Health Organization (WHO) as clinical markers of reduced or highly-reduced inhibition (RI/HRI) to multiple NAIs. Recombinant viruses were tested by NA inhibition assays. Their replicative capacity and virulence were evaluated in ST6GalI-MDCK cells and BALB/c mice, respectively. All NA mutants (excepted D198E/N) showed RI/HRI phenotypes against ≥ 2 NAIs. These mutants grew to comparable titers of the recombinant wild-type (WT) IBV in vitro, and some of them (H136N, I222T and N294S mutants) induced more weight loss and mortality in BALB/c mice in comparison to the recombinant WT IBV. These results demonstrate that, in contemporary IBVs, some NA mutations may confer RI/HRI phenotypes to existing NAIs without altering the viral fitness. This reinforces the need for development of novel antiviral strategies with different mechanisms of action.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".