Hyperspectral image processing for the identification and quantification of lentiviral particles in fluid sample
| Autor: | Ruben Parrilla-Giraldez, Lucia Olvera-Collantes, Beatriz Fernández-Muñoz, Juan Carlos Gómez Martín, Jose Manuel Navas-Garcia, Desiree Requena-Lancharro, Manuel A Perales-Esteve, María José Mayorga-Buiza, Cristina Rosell-Valle, Isabel Fernandez-Lizaranzu, Jesus Aceituno-Castro, Maria Isabel Relimpio Lopez, Emilia Gómez, Javier Márquez-Rivas, Pedro Gil-Gamboa, Carmen Gomez-Gonzalez, Antonio Puppo-Moreno, Alejandro Barriga-Rivera, Francisco Javier Munoz-Gonzalez, María Martín-López, Francisco J. García Cózar, Olga Muñoz, Rosario Sanchez Pernaute, Manuel Guerrero-Claro, Emilio Gómez-González, Javier Padillo-Ruiz, Silvia de Los Santos-Trigo |
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| Přispěvatelé: | Instituto de Salud Carlos III, Ministerio de Ciencia, Innovación y Universidades (España), Agencia Estatal de Investigación (España), European Commission, Biomedicina, Biotecnología y Salud Pública |
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Imatges--Processament
Science Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Point-of-Care Systems Sensitivity and Specificity Article Near-infrared spectroscopy Image Processing Computer-Assisted Humans Saliva Mass screening Residue (complex analysis) Multidisciplinary Chromatography Spectroscopy Near-Infrared Chemistry Lentivirus technology industry and agriculture Hyperspectral imaging COVID-19 Aliments--Indústria i comerç Hyperspectral image processing VNIR Coronavirus HEK293 Cells Molecular Diagnostic Techniques Viral infection Reagent Lentivirus Infections Medicine |
| Zdroj: | Digital.CSIC. Repositorio Institucional del CSIC instname Scientific Reports Scientific Reports, Vol 11, Iss 1, Pp 1-12 (2021) Sci Rep 11, 16201 (2021) RODIN. Repositorio de Objetos de Docencia e Investigación de la Universidad de Cádiz |
| Popis: | 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·μL−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. 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 Scientific 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. The authors would like to gratefully acknowledge the assistance of the members of the EOD-CBRN Group of the Spanish National Police, whose identities cannot be disclosed, and who are represented here by JMNG. Authors thank continuous support from their institutions. |
| Databáze: | OpenAIRE |
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