Evidence map›Paper›PMID 32577655›Full record

ArticlebioRxiv : the preprint server for biology2020

Development and validation of IMMUNO-COV™: a high-throughput clinical assay for detecting antibodies that neutralize SARS-CoV-2.

Rianna Vandergaast, Timothy Carey, Samantha Reiter, Patrycja Lech, Clement Gnanadurai, Mulu Tesfay, Jason Buehler, Lukkana Suksanpaisan, Shruthi Naik, Bethany Brunton and 17 more

Open access · greenAbstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 19 citations in OpenAlex.

  1. Review
  2. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

27 authors at 5 institutions in 1 country.

Rianna Vandergaast
Timothy Carey
Samantha Reiter
Patrycja Lech
Clement Gnanadurai
Mulu Tesfay
Jason Buehler
Lukkana Suksanpaisan
Shruthi Naik
Bethany Brunton
Jordan Recker
Michelle Haselton
Christopher Ziegler
Anne Roesler
John R Mills
Elitza Theel
Scott C Weaver
Grace Rafael
Matthew M Roforth
Calvin Jerde
Sheryl Tran
Rosa Maria Diaz
Alice Bexon
Alina Baum
Christos A Kyratsous
Kah Whye Peng
Stephen J Russell
University of Minnesota Rochester · USMayo Clinic · USMayo Clinic in Arizona · USRegeneron (United States) · USThe University of Texas Medical Branch at Galveston · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We here describe the development and validation of IMMUNO-COV™, a high-throughput clinical test to quantitatively measure SARS-CoV-2-neutralizing antibodies, the specific subset of anti-SARS-CoV-2 antibodies that block viral infection. The test measures the capacity of serum or purified antibodies to neutralize a recombinant Vesicular Stomatitis Virus (VSV) encoding the SARS-CoV-2 spike glycoprotein. This recombinant virus (VSV-SARS-CoV-2-S-Δ19CT) induces fusion in Vero cell monolayers, which is detected as luciferase signal using a dual split protein (DSP) reporter system. VSV-SARS-CoV-2-S-Δ19CT infection was blocked by monoclonal α-SARS-CoV-2-spike antibodies and by plasma or serum from SARS-CoV-2 convalescing individuals. The assay exhibited 100% specificity in validation tests, and across all tests zero false positives were detected. In blinded analyses of 230 serum samples, only two unexpected results were observed based on available clinical data. We observed a perfect correlation between results from our assay and 80 samples that were also assayed using a commercially available ELISA. To quantify the magnitude of the anti-viral response, we generated a calibration curve by adding stepped concentrations of α-SARS-CoV-2-spike monoclonal antibody to pooled SARS-CoV-2 seronegative serum. Using the calibration curve and a single optimal 1:100 serum test dilution, we reliably measured neutralizing antibody levels in each test sample. Virus neutralization units (VNUs) calculated from the assay correlated closely (p < 0.0001) with PRNT

Identifiers

PMID32577655
PMCPMC7302210
OpenAlexW3029467071

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.