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

Gomez-Gonzalez, Emilio; Fernandez-Munoz, Beatriz; Barriga-Rivera, Alejandro; Navas-Garcia, Jose Manuel; Fernandez-Lizaranzu, Isabel; Munoz-Gonzalez, Francisco Javier; Parrilla-Giraldez, Ruben; Requena-Lancharro, Desiree; Guerrero-Claro, Manuel; Gil-Gamboa,

SCIENTIFIC REPORTS
2021
VL / 11 - BP / - EP /
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.mu 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.

AccesS level

Green published, Gold

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