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Hyperspectral image processing for the identification and quantification of lentiviral particles in fluid samples

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dc.contributor.author Gomez‑Gonzalez, Emilio
dc.contributor.author Fernandez‑Muñoz, Beatriz
dc.contributor.author Barriga‑Rivera, Alejandro
dc.contributor.author Navas‑Garcia, Jose Manuel
dc.contributor.author Fernandez‑Lizaranzu, Isabel
dc.contributor.author Muñoz‑Gonzalez, Francisco Javier
dc.contributor.author Parrilla‑Giraldez, Ruben
dc.contributor.author Requena‑Lancharro, Desiree
dc.contributor.author Guerrero‑Claro, Manuel
dc.contributor.author Gil‑Gamboa, Pedro
dc.contributor.author Rosell‑Valle, Cristina
dc.contributor.author Gomez‑Gonzalez, Carmen
dc.contributor.author Mayorga‑Buiza, Maria Jose
dc.contributor.author Martin‑Lopez, Maria
dc.contributor.author Muñoz, Olga
dc.contributor.author Gomez Martin, Juan Carlos
dc.contributor.author Relimpio Lopez, Maria Isabel
dc.contributor.author Aceituno‑Castro, Jesus
dc.contributor.author Perales‑Esteve, Manuel A.
dc.contributor.author Puppo‑Moreno, Antonio
dc.contributor.author Gómez Gutiérrez, Emilia, 1975-
dc.contributor.author Sanchez Pernaute, Rosario
dc.contributor.author Padillo‑Ruiz, Javier
dc.contributor.author Marquez‑Rivas, Javier
dc.date.accessioned 2023-02-22T07:25:32Z
dc.date.available 2023-02-22T07:25:32Z
dc.date.issued 2021
dc.identifier.citation Gomez‑Gonzalez E, Fernandez‑Muñoz B, Barriga‑Rivera, A, Navas‑Garcia JM, Fernandez‑Lizaranzu I, Munoz‑Gonzalez FJ, Parrilla‑Giraldez R, Requena‑Lancharro D, Guerrero‑Claro M, Gil‑Gamboa P, Rosell‑Valle C, Gomez‑Gonzalez C, Mayorga‑Buiza MJ, Martin‑Lopez M, Muñoz O, Gomez Martin JC, Relimpio Lopez MI, Aceituno‑Castro J, Perales‑Esteve MA, Puppo‑Moreno A, Garcia Cozar FJ, Olvera‑Collantes L, de los Santos‑Trigo S, Gomez E, Sanchez Pernaute R, Padillo‑Ruiz J, Marquez‑Rivas J. Hyperspectral image processing for the identification and quantification of lentiviral particles in fluid samples. Sci Rep. 2021;11:16201. DOI: 10.1038/s41598-021-95756-3
dc.identifier.issn 2045-2322
dc.identifier.uri http://hdl.handle.net/10230/55845
dc.description.abstract Optical spectroscopic techniques have been commonly used to detect the presence of biofilm-forming pathogens (bacteria and fungi) in the agro-food industry. Recently, near-infrared (NIR) spectroscopy revealed that it is also possible to detect the presence of viruses in animal and vegetal tissues. Here we report a platform based on visible and NIR (VNIR) hyperspectral imaging for non-contact, reagent free detection and quantification of laboratory-engineered viral particles in fluid samples (liquid droplets and dry residue) using both partial least square-discriminant analysis and artificial feed-forward neural networks. The detection was successfully achieved in preparations of phosphate buffered solution and artificial saliva, with an equivalent pixel volume of 4 nL and lowest concentration of 800 TU·μ L−1. This method constitutes an innovative approach that could be potentially used at point of care for rapid mass screening of viral infectious diseases and monitoring of the SARS-CoV-2 pandemic.
dc.description.sponsorship This research was funded by grants number COV20-00080 and COV20-00173 of the 2020 Emergency Call for Research Projects about the SARS-CoV-2 virus and the COVID-19 disease of the Institute of Health ‘Carlos III’, Spanish Ministry of Science and Innovation, and by grant number EQC2019-006240-P of the 2019 Call for Acquisition of Scientifc Equipment, FEDER Program, Spanish Ministry of Science and Innovation. This work has been supported by the European Commission through the JRC HUMAINT project. ABR was supported by grant number RTI2018-094465-J funded by the Spanish National Agency of Research.
dc.format.mimetype application/pdf
dc.language.iso eng
dc.publisher Nature Research
dc.relation.ispartof Scientific Reports. 2021;11:16201.
dc.relation.isreferencedby https://static-content.springer.com/esm/art%3A10.1038%2Fs41598-021-95756-3/MediaObjects/41598_2021_95756_MOESM1_ESM.docx
dc.rights © Springer Nature Publishing AG https://doi.org/10.1038/s41598-021-95756-3 Creative Commons Attribution Non-Commercial Share Alike
dc.rights.uri http://creativecommons.org/licenses/by/4.0/
dc.subject.other Imatges--Processament
dc.subject.other Aliments--Indústria i comerç
dc.title Hyperspectral image processing for the identification and quantification of lentiviral particles in fluid samples
dc.type info:eu-repo/semantics/article
dc.identifier.doi http://dx.doi.org/10.1038/s41598-021-95756-3
dc.relation.projectID info:eu-repo/grantAgreement/ES/2PE/RTI2018-094465-J
dc.relation.projectID info:eu-repo/grantAgreement/ES/2PE/EQC2019-006240-P
dc.rights.accessRights info:eu-repo/semantics/openAccess
dc.type.version info:eu-repo/semantics/publishedVersion

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