About: Serial Profiling of SARS-CoV-2 Antigens and Antibodies in COVID-19 Patient Plasma

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An Entity of Type : schema:ScholarlyArticle, within Data Space : wasabi.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
title	Serial Profiling of SARS-CoV-2 Antigens and Antibodies in COVID-19 Patient Plasma
Creator	Zhu, Quan Marasco, Wayne Ryan, Edward Charles, Richelle Gilboa, Tal Norman, Maia Walt, David Kamkaew, Maliwan Maley, Adam Ogata, Alana Chang, Matthew Gibson, Travis Lazarovits, Roey Mao, Chih-Ping Newton, Gail Nguyen, Katrina Wu, Connie
topic	covid:a3018164f466492d38016e83371458ce42107ddc#this
source	MedRxiv
abstract	The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has infected millions of people worldwide. PCR tests are currently the gold standard for diagnosis of the current coronavirus disease (COVID-19) and serology tests are used to detect seroconversion in infected patients. However, there is a lack of quantitative and ultra-sensitive viral antigen tests for COVID-19. Here we show that Single Molecule Array (Simoa) assays can quantitatively detect SARS-CoV-2 spike, S1 subunit, and nucleocapsid antigens in the plasma of COVID-19 patients. Combined with Simoa anti-SARS-CoV-2 serological assays, we show correlation between production of antibodies and clearance of viral antigens from serial plasma samples from COVID-19 patients. Furthermore, we demonstrate the presence of viral antigens in blood correlates with disease severity in hospitalized COVID-19 patients. These data suggest that SARS-CoV-2 viral antigens in the blood could be a marker for severe COVID-19 cases.
has issue date	2020-07-26(xsd:dateTime)
bibo:doi	10.1101/2020.07.20.20156372
has license	medrxiv
sha1sum (hex)	a3018164f466492d38016e83371458ce42107ddc
schema:url	https://doi.org/10.1101/2020.07.20.20156372
resource representing a document's title	Serial Profiling of SARS-CoV-2 Antigens and Antibodies in COVID-19 Patient Plasma
resource representing a document's body	covid:a3018164f466492d38016e83371458ce42107ddc#body_text
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