Artículo
Hyperspectral image processing for the identification and quantification of lentiviral particles in fluid samples
Autor/es | Gómez-González, Emilio
Fernández Muñoz, Beatriz Barriga-Rivera, Alejandro |
Departamento | Universidad de Sevilla. Departamento de Física Aplicada III Universidad de Sevilla. Departamento de Ingeniería Electrónica |
Fecha de publicación | 2021-08 |
Fecha de depósito | 2021-08-11 |
Publicado en |
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Resumen | 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 ... 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. |
Identificador del proyecto | EQC2019-006240-P |
Cita | Gómez-González, E., Fernández Muñoz, B. y Barriga-Rivera, A. [et al.] (2021). Hyperspectral image processing for the identification and quantification of lentiviral particles in fluid samples. Scientific Reports, 11, 16201. |
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