RT info:eu-repo/semantics/article
T1 Detection of SARS-CoV-2 Infection in Human Nasopharyngeal Samples by Combining MALDI-TOF MS and Artificial Intelligence (doi:  10.3389/fmed.2021.661358)
A1 Peña Méndez, Eladia María
A1 Deulofeu, Meritxell
A1 García Cuesta, Esteban
A1 Conde, José Elías
A1 Jiménez Romero, Orlando
A1 Verdú, Enrique
A1 Serrando, María Teresa
A1 Salvadó, Victoria
A1 Boadas Vaello, Pere
K1 MALDI-TOF MS analysis
K1 Machine learning
K1 SARS-CoV-2
K1 NP samples
K1 Viral transport media
AB The high infectivity of SARS-CoV-2 makes it essential to develop a rapid and accuratediagnostic test so that carriers can be isolated at an early stage. Viral RNA innasopharyngeal samples by RT-PCR is currently considered the reference methodalthough it is not recognized as a strong gold standard due to certain drawbacks. Herewe develop a methodology combining the analysis of from human nasopharyngeal (NP)samples by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry(MALDI-TOF MS) with the use of machine learning (ML). A total of 236 NP samplescollected in two different viral transport media were analyzed with minimal samplepreparation and the subsequent mass spectra data was used to build different MLmodels with two different techniques. The bestmodel showed high performance in termsof accuracy, sensitivity and specificity, in all cases reaching values higher than 90%. Ourresults suggest that the analysis of NP samples by MALDI-TOF MS and ML is a simple,safe, fast and economic diagnostic test for COVID-19.
SN 2296-858X
YR 2021
FD 2021
LK http://riull.ull.es/xmlui/handle/915/35188
UL http://riull.ull.es/xmlui/handle/915/35188
LA en
DS Repositorio institucional de la Universidad de La Laguna
RD 08-may-2024