Evidence map›Paper›PMID 34013298›Full record

ArticlemedRxiv : the preprint server for health sciences2021

multiSero: open multiplex-ELISA platform for analyzing antibody responses to SARS-CoV-2 infection.

Janie R Byrum, Eric Waltari, Owen Janson, Syuan-Ming Guo, Jenny Folkesson, Bryant B Chhun, Joanna Vinden, Ivan E Ivanov, Marcus L Forst, Hongquan Li and 11 more

Open access · greenAbstract readPreprint
PubMed Full text at PMC Publisher
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed, 14 citations in OpenAlex.

  1. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

21 authors at 3 institutions in 1 country.

Janie R Byrum *Chan Zuckerberg Biohub, San Francisco, CA, USA.
Eric Waltari *Chan Zuckerberg Biohub, San Francisco, CA, USA.
Owen Janson *University of California San Francisco, CA, USA.
Syuan-Ming Guo *Chan Zuckerberg Biohub, San Francisco, CA, USA.
Jenny FolkessonChan Zuckerberg Biohub, San Francisco, CA, USA.
Bryant B ChhunChan Zuckerberg Biohub, San Francisco, CA, USA.
Joanna VindenUniversity of California San Francisco, CA, USA.
Ivan E IvanovChan Zuckerberg Biohub, San Francisco, CA, USA.
Marcus L ForstChan Zuckerberg Biohub, San Francisco, CA, USA.
Hongquan LiStanford University, Palo Alto, CA, USA.
Adam G LarsonStanford University, Palo Alto, CA, USA.
Wesley WuChan Zuckerberg Biohub, San Francisco, CA, USA.
Cristina M TatoChan Zuckerberg Biohub, San Francisco, CA, USA.
Krista M McCutcheonChan Zuckerberg Biohub, San Francisco, CA, USA.
Michael J PelusoUniversity of California San Francisco, CA, USA.
Timothy J HenrichUniversity of California San Francisco, CA, USA.
Steven G DeeksUniversity of California San Francisco, CA, USA.
Manu PrakashChan Zuckerberg Biohub, San Francisco, CA, USA.
Bryan GreenhouseChan Zuckerberg Biohub, San Francisco, CA, USA.
John E PakChan Zuckerberg Biohub, San Francisco, CA, USA.
Shalin B MehtaChan Zuckerberg Biohub, San Francisco, CA, USA.
Chan Zuckerberg Initiative (United States) · USUniversity of California, San Francisco · USPalo Alto University · US

Funding

Training in HIV Translational ResearchT32AI060530 · NIAID · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI Diane V Havlir · 2005 to 2026
$6.4M
Targeting Non Viral Markers of HIV PersistenceR01AI141003 · NIAID · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI HENRICH, TIMOTHY JENSEN · 2018 to 2022
$4.9M
Mentoring translational scientists in international infectious disease researchK24AI144048 · NIAID · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI Bryan R Greenhouse · 2019 to 2026
$1.6M
NIAID NIH HHS K24 AI144048NIAID NIH HHS R01 AI141003NIAID NIH HHS T32 AI060530
6 · The paper itself

Abstract

Serology has provided valuable diagnostic and epidemiological data on antibody responses to SARS-CoV-2 in diverse patient cohorts. Deployment of high content, multiplex serology platforms across the world, including in low and medium income countries, can accelerate longitudinal epidemiological surveys. Here we report multiSero, an open platform to enable multiplex serology with up to 48 antigens in a 96-well format. The platform consists of three components: ELISA-array of printed proteins, a commercial or home-built plate reader, and modular python software for automated analysis (pysero). We validate the platform by comparing antibody titers against the SARS-CoV-2 Spike, receptor binding domain (RBD), and nucleocapsid (N) in 114 sera from COVID-19 positive individuals and 87 pre-pandemic COVID-19 negative sera. We report data with both a commercial plate reader and an inexpensive, open plate reader (nautilus). Receiver operating characteristic (ROC) analysis of classification with single antigens shows that Spike and RBD classify positive and negative sera with the highest sensitivity at a given specificity. The platform distinguished positive sera from negative sera when the reactivity of the sera was equivalent to the binding of 1 ng mL

Identifiers

PMID34013298
PMCPMC8132273
OpenAlexW3163359833

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.