Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 649

The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.

SARS‐CoV‐2 Seroconversion in Humans: A Detailed Protocol for a Serological Assay, Antigen Production, and Test Setup

Open access
Stadlbauer, Daniel, Amanat, Fatima, Chromikova, Veronika, Jiang, Kaijun, Strohmeier, Shirin, Arunkumar, Guha Asthagiri, Tan, Jessica, Bhavsar, Disha, Capuano, Christina, Kirkpatrick, Ericka, Meade, Philip, Brito, Ruhi Nichalle, Teo, Catherine, McMahon, Meagan, Simon, Viviana, Krammer, Florian·2020·Current Protocols in Microbiology

Abstract

In late 2019, cases of atypical pneumonia were detected in China. The etiological agent was quickly identified as a betacoronavirus (named SARS‐CoV‐2), which has since caused a pandemic. Several methods allowing for the specific detection of viral nucleic acids have been established, but these only allow detection of the virus during a short period of time, generally during acute infection. Serological assays are urgently needed to conduct serosurveys, to understand the antibody responses mounted in response to the virus, and to identify individuals who are potentially immune to re‐infection. Here we describe a detailed protocol for expression of antigens derived from the spike protein of SARS‐CoV‐2 that can serve as a substrate for immunological assays, as well as a two‐stage serological enzyme‐linked immunosorbent assay (ELISA). These assays can be used for research studies and for testing in clinical laboratories. © 2020 The Authors. Current Protocols in Microbiology published by Wiley Periodicals LLC. Basic Protocol 1: Mammalian cell transfection and protein purification Basic Protocol 2: A two‐stage ELISA for high‐throughput screening of human serum samples for antibodies binding to the spike protein of SARS‐CoV‐2

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1002/cpmc.100

Cites

5 of 5 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Cited by

See all 649

Metadata

Authors
Stadlbauer, D., Amanat, F., Chromikova, V., Jiang, K., Strohmeier, S., Arunkumar, G. A., Tan, J., Bhavsar, D., Capuano, C., Kirkpatrick, E., Meade, P., Brito, R. N., Teo, C., McMahon, M., Simon, V., & Krammer, F.
Venue
Current Protocols in Microbiology
Publisher
Wiley
Published
2020-04-17
Volume
57
Issue
1
Pages
e100-e100
ISSN
  • 1934-8525 (ISSN-L)
  • 1934-8533
OpenAlex
W3016269138
Cited by
649
References
5
FWCI
16.93
Type
journal article
Language
en
Open access
hybrid

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.