Molecular Pathway of Influenza Pan-neuraminidase Inhibitor Resistance in an Immunocompromised Patient
Bibliographic record
Abstract
BACKGROUND: Neuraminidase (NA) inhibitors (NAIs), including oseltamivir and zanamivir, play an important therapeutic role against influenza infections in immunocompromised patients. In such settings, however, NAI therapy may lead to the emergence of resistance involving mutations within the influenza surface genes. The aim of this study was to investigate the evolution of NA and haemagglutinin (HA) genes of influenza A(H1N1)pdm09 virus in an immunocompromised patient receiving oseltamivir then zanamivir therapies. METHODS: Nasopharyngeal swab (NPS) samples were collected between 27 January 2018 and 11 April 2018 from a haematopoietic stem cell transplant recipient. These include 10 samples collected either pre-therapy, during oseltamivir and zanamivir treatment as well as after therapy. The A(H1N1)pdm09 HA/NA genes were sequenced. The H275Y NA substitution was quantified by droplet digital RT-PCR assay. A(H1N1)pdm09 recombinant viruses containing HA mutations were tested by HA elution experiments to investigate in vitro binding properties. RESULTS: Oseltamivir rapidly induced the H275Y NA mutation which constituted 98.33% of the viral population after 15 days of oseltamivir treatment. The related HA gene contained S135A and P183S substitutions within the receptor-binding site. After a switch to zanamivir, 275H/Y and 119E/G/D mixed populations were detected. In the last samples, the double H275Y-E119G NA variant dominated with S135A and P183S HA substitutions. CONCLUSIONS: This report confirms that oseltamivir can rapidly induce the emergence of the H275Y substitution in A(H1N1)pdm09 viruses and subsequent switch to zanamivir can lead to additional substitutions at codon E119 resulting in multi-drug resistance. Such data additionally suggest a potential compensatory role for HA substitutions near the receptor binding site.
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 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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.003 | 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".