2018
DOI: 10.4269/ajtmh.17-0948
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Virus Reduction Neutralization Test: A Single-Cell Imaging High-Throughput Virus Neutralization Assay for Dengue

Abstract: Abstract.Vaccine immunogenicity and clinical efficacy are often assessed by the measure of serum-neutralizing antibodies. The present gold standard for detecting neutralizing antibodies against many viruses, including dengue, is the plaque/focus reduction neutralization test (P/FRNT). The FRNT is a cell-based assay that inherits high variability, resulting in poor precision and has lengthy turnaround times. The virus reduction neutralization test (VRNT) is a high-throughput alternative to the standard low-thro… Show more

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Cited by 35 publications
(22 citation statements)
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“…VN is considered as the gold standard test for measurement of protective immunity against viruses following vaccination or natural infection ( Haralambieva et al, 2008 ; Whiteman et al, 2018 ). Potential caveats in VN performed on DBS specimens could be extraction conditions and smaller extraction volumes in order to run the assay at lower dilutions.…”
Section: Discussionmentioning
confidence: 99%
“…VN is considered as the gold standard test for measurement of protective immunity against viruses following vaccination or natural infection ( Haralambieva et al, 2008 ; Whiteman et al, 2018 ). Potential caveats in VN performed on DBS specimens could be extraction conditions and smaller extraction volumes in order to run the assay at lower dilutions.…”
Section: Discussionmentioning
confidence: 99%
“…The actual data acquisition is conducted within seconds, using standard ELISA plate readers present in most routine diagnostics departments. We believe that this is advantageous compared to other NT assays that rely on more sophisticated and more expensive devises, e.g., for imaging cytometry ( 39 ). The icELISA and icNT provide increased data quality and precision by generating continuous data sets.…”
Section: Discussionmentioning
confidence: 99%
“…Current COVID-19 diagnostic tools and techniques are shown in Table 1 (Tab. 1) (References in Table 1: Cai et al, 2020[ 7 ]; Carter et al, 2020[ 11 ]; Chan et al, 2020[ 16 ]; Chen et al, 2010[ 19 ]; Park et al, 2009[ 52 ]; Wang et al, 2005[ 65 ]; Whiteman et al, 2018[ 70 ]) and a diagnostic model for COVID-19 in Figure 5 (Fig. 5) .…”
Section: Sars-cov-2 Diagnosismentioning
confidence: 99%