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Polarimetric imaging for the detection of synthetic models of SARS-CoV-2: a proof of concept (preprint)
arxiv; 2022.
Preprint
in English
| PREPRINT-ARXIV | ID: ppzbmed-2204.14050v1
ABSTRACT
Objective:
To conduct a proof-of-concept study of the detection of two synthetic models of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) using polarimetric imaging.Methods:
Two SARS-CoV-2 models were prepared as engineered lentiviruses pseudotyped with the G protein of the vesicular stomatitis virus, and with the characteristic Spike protein of SARS-CoV-2. Samples were preparations in two biofluids (saline solution and artificial saliva), in four concentrations, and deposited as 5-{\mu}L droplets on a supporting plate. The angles of maximal degree of linear polarization (DLP) of light diffusely scattered from dry residues were determined using Mueller polarimetry of 87 samples at 405 nm and 514 nm. A polarimetric camera was used for simultaneous imaging of several samples under 380-420 nm illumination at angles similar to those of maximal DLP. A per-pixel image analysis included quantification and combination of polarization feature descriptors in other 475 samples.Results:
The angles (from sample surface) of maximal DLP were 3 degrees for 405 nm and 6 degrees for 514 nm. Similar viral particles that differ only in the characteristic spike protein of the SARS-CoV-2, their corresponding negative controls, fluids, and the sample holder were discerned from polarimetric image analysis at 10-degree and 15-degree configurations.Conclusion:
Polarimetric imaging in the visible spectrum has the potential for non-contact, reagent-free detection of viruses in multiple dry fluid residues simultaneously. Further analysis including real SARS-CoV-2 in human samples -- particularly, fresh saliva -- are required.Significance:
Polarimetric imaging under visible light could contribute to fast, cost-effective screening of SARS-CoV-2 and other pathogens.
Full text:
Available
Collection:
Preprints
Database:
PREPRINT-ARXIV
Language:
English
Year:
2022
Document Type:
Preprint
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