ArticleNPJ vaccines2019
A neuraminidase potency assay for quantitative assessment of neuraminidase in influenza vaccines.
Article in NPJ vaccines, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
8 citing papers in PubMed, 12 citations in OpenAlex.
- Antineuraminidase Antibody Responses in Older Adults After Consecutive Vaccinations With Enhanced Influenza Vaccines: A Randomized Controlled Trial.The Journal of infectious diseases · 2026Trial
- Article
- ELISA-based quantification of neuraminidase in commercial influenza vaccines using virus-derived reference antigens.Microbiology spectrum · 2026Article
- INAAC: An affinity chromatography strategy enabling characterization and quantification of influenza neuraminidase antigens in vaccines.The Journal of biological chemistry · 2026Article
- Article
- Article
- Multiplexed VaxArray immunoassay for rapid antigen quantification in measles and rubella vaccine manufacturing.Vaccine: X · 2021Article
- Multiplexed, microscale, microarray-based serological assay for antibodies against all human-relevant coronaviruses.Journal of virological methods · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Neuraminidase (NA) immunity leads to decreased viral shedding and reduced severity of influenza disease; however, NA content in influenza vaccines is currently not regulated, resulting in inconsistent quality and quantity of NA that can vary from manufacturer to manufacturer, from year to year, and from lot to lot. To address this problem, we have developed an assay for NA quantification that could be used by the industry to move toward developing influenza vaccines that induce a predictable immune response to NA. The VaxArray Influenza Seasonal NA Potency Assay (VXI-sNA) is a multiplexed sandwich immunoassay that relies on six subtype-specific monoclonal antibodies printed in microarray format and a suite of fluor-conjugated "label" antibodies. The performance of the assay as applied to a wide range of influenza vaccines is described herein. The assay demonstrated high NA subtype specificity and high sensitivity, with quantification limits ranging from 1 to 60 ng/mL and linear dynamic ranges of 24-500-fold. When compared to an enzymatic activity assay for samples exposed to thermal degradation conditions, the assay was able to track changes in protein stability over time and exhibited good correlation with enzyme activity. The assay also demonstrated excellent analytical precision with relative error ranging from 6 to 12% over day-to-day, user-to-user, and lot-to-lot variation. The high sensitivity and reproducibility of the assay enabled robust detection and quantification of NA in crude in-process samples and low-dose, adjuvanted vaccines with an accuracy of 100 ± 10%.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.