ArticlemSphere2022
Interlaboratory Reproducibility of Standardized Hemagglutination Inhibition Assays.
Article in mSphere, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
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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
11 citing papers in PubMed, 15 citations in OpenAlex.
- Loss of hemagglutination ability by H3N2 influenza A virus, subclade K.bioRxiv : the preprint server for biology · 2026Article
- Development and validation of a rapid triple-target gold nanoparticle lateral flow immunoassay for detection of three avian mycoplasmas immunochromatographic strip test for avian mycoplasma detection.BMC microbiology · 2026Article
- Immune-Enhancing Effect ofAnimals : an open access journal from MDPI · 2026Article
- Article
- Development and application of a NP-cELISA for the detection of nucleoprotein antibodies of equine influenza virus.Microbiology spectrum · 2025Article
- Systemic and Mucosal Immune Responses Induced by Adenoviral-Vectored Consensus H5 Influenza A Vaccines in Mice and Swine.Vaccines · 2025Article
- Seasonal influenza vaccines: Variability of immune responses to B lineage viruses.Human vaccines & immunotherapeutics · 2024Review
- Immunity and Protective Efficacy of a Plant-Based Tobacco Mosaic Virus-like Nanoparticle Vaccine against Influenza a Virus in Mice.Vaccines · 2024Article
- The role of asymptomatic infections in influenza transmission: what do we really know.The Lancet. Infectious diseases · 2024Review
- Article
- Robustness of the Ferret Model for Influenza Risk Assessment Studies: a Cross-Laboratory Exercise.mBio · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 3 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The hemagglutination inhibition (HI) assay is a prominent and commonly accepted method used to determine quantitative antibody titers for influenza virus. However, the reproducibility and consistency of this assay may be affected by several factors, including its reliance on biological reagents that are difficult to standardize, such as red blood cells. This report assesses HI assay performance across three accredited, global laboratories when using test virus and a human serum panel aliquoted and distributed from a centrally located reagent stock. The panel of human sera comprised samples with expected low, medium, and high HI titers against two influenza viruses: A/H1N1/California/07/2009 and B/Victoria/Brisbane/60/2008. HI analysis followed a consensus test protocol. Overall, the HI assay reproducibility within each laboratory was high for both influenza strains, with a within-assay run and intraday precision of 100%. Interlab reproducibility was assessed by comparing the geometric mean titer (GMT) of each sample at each laboratory to the consensus GMT of the sample. A/H1N1 had 100% interlab reproducibility, and none of the individual laboratory GMT values exceeded a 2-fold difference compared to the consensus GMT in any tested sample. B/Victoria had an overall reproducibility of 83%. The results demonstrate that with standardization of key reagents and the use of a common protocol by trained staff, the biologically based HI assay can provide similar results between geographically dispersed laboratories.
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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.