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1.
Journal of quantitative spectroscopy & radiative transfer ; 2023.
Article in English | EuropePMC | ID: covidwho-2260923

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. Approach 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-μL 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 imaging several samples under 380-420 nm illumination at angles similar to those of maximal DLP. Per-pixel image analysis included quantification and combination of polarization feature descriptors in 475 samples. Main 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 at 10-degree and 15-degree configurations. Significance Polarimetric imaging in the visible spectrum may help improve fast, non-contact detection and identification of viral particles, and/or other microbes such as tuberculosis, in multiple dry fluid samples simultaneously, particularly when combined with other imaging modalities. Further analysis including realistic concentrations of real SARS-CoV-2 virus particles in relevant human fluids is required. Polarimetric imaging under visible light may contribute to fast, cost-effective screening of SARS-CoV-2 and other pathogens.

2.
J Quant Spectrosc Radiat Transf ; 302: 108567, 2023 Jul.
Article in English | MEDLINE | ID: covidwho-2260924

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. Approach: 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 prepared in two biofluids (saline solution and artificial saliva), in four concentrations, and deposited as 5-µL 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 from87 samples at 405 nm and 514 nm. A polarimetric camera was used for imaging several samples under 380-420 nm illumination at angles similar to those of maximal DLP. Per-pixel image analysis included quantification and combination of polarization feature descriptors in 475 samples. Main results: The angles (from sample surface) of maximal DLP were 3° for 405 nm and 6° for 514 nm. Similar viral particles that differed only in the characteristic spike protein of the SARS-CoV-2, their corresponding negative controls, fluids, and the sample holder were discerned at 10-degree and 15-degree configurations. Significance: Polarimetric imaging in the visible spectrum may help improve fast, non-contact detection and identification of viral particles, and/or other microbes such as tuberculosis, in multiple dry fluid samples simultaneously, particularly when combined with other imaging modalities. Further analysis including realistic concentrations of real SARS-CoV-2 viral particles in relevant human fluids is required. Polarimetric imaging under visible light may contribute to a fast, cost-effective screening of SARS-CoV-2 and other pathogens when combined with other imaging modalities.

3.
Sci Rep ; 12(1): 3402, 2022 03 01.
Article in English | MEDLINE | ID: covidwho-1908228

ABSTRACT

Medical research is progressing to clarify the full spectrum of sub-acute and long-term effects of the post-COVID-19 syndrome. However, most manuscripts published to date only analyze the effects of post-COVID-19 in patients discharged from hospital, which may induce significant bias. Here, we propose a pioneering study to analyze the single and multiple associations between post-COVID-19 characteristics with up to 6-months of follow-up in hospitalized and non-hospitalized COVID-19 patients. The cohort study was conducted from May to October 2020 at the University Hospital Virgen de la Nieves, the leading hospital assigned for patients with COVID-19 in Granada, Spain. A total of 372 and 217 patients-with 217 and 207 included in the first and second follow-up visits-were referred 2 and 6 months after diagnosing COVID-19, respectively. We find out that post-COVID-19 clinical and mental health impairment symptoms are correlated with patient gender. Logistic adjustments showed strong statistically robust single and multiple associations of demographic, clinical, mental health, X-ray, laboratory indices, and pulmonary function variables. The functional lung tests are good predictors of chest CT imaging abnormalities in elderly patients. Bilateral lung involvement, subpleural reticulum, ground-glass opacity, peripheral lung lesions, and bronchiectasis were the most common findings of the high-resolution computed tomography images. Non-hospitalized patients suffer more severe thromboembolic events and fatigue than those hospitalized.


Subject(s)
COVID-19/complications , Hospitalization , Lung/diagnostic imaging , Tomography, X-Ray Computed , Aged , COVID-19/diagnostic imaging , COVID-19/epidemiology , COVID-19/therapy , Female , Humans , Male , Middle Aged , Prospective Studies , Spain/epidemiology , Post-Acute COVID-19 Syndrome
4.
Sci Rep ; 12(1): 2356, 2022 02 18.
Article in English | MEDLINE | ID: covidwho-1706307

ABSTRACT

Effective testing is essential to control the coronavirus disease 2019 (COVID-19) transmission. Here we report a-proof-of-concept study on hyperspectral image analysis in the visible and near-infrared range for primary screening at the point-of-care of SARS-CoV-2. We apply spectral feature descriptors, partial least square-discriminant analysis, and artificial intelligence to extract information from optical diffuse reflectance measurements from 5 µL fluid samples at pixel, droplet, and patient levels. We discern preparations of engineered lentiviral particles pseudotyped with the spike protein of the SARS-CoV-2 from those with the G protein of the vesicular stomatitis virus in saline solution and artificial saliva. We report a quantitative analysis of 72 samples of nasopharyngeal exudate in a range of SARS-CoV-2 viral loads, and a descriptive study of another 32 fresh human saliva samples. Sensitivity for classification of exudates was 100% with peak specificity of 87.5% for discernment from PCR-negative but symptomatic cases. Proposed technology is reagent-free, fast, and scalable, and could substantially reduce the number of molecular tests currently required for COVID-19 mass screening strategies even in resource-limited settings.


Subject(s)
Exudates and Transudates/virology , Mass Screening/methods , SARS-CoV-2/isolation & purification , Saliva/virology , Spectroscopy, Near-Infrared , Humans , Point-of-Care Testing , Proof of Concept Study
5.
Sci Rep ; 11(1): 16201, 2021 08 10.
Article in English | MEDLINE | ID: covidwho-1351977

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·[Formula: see text]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.


Subject(s)
Image Processing, Computer-Assisted/methods , Lentivirus Infections/diagnosis , Molecular Diagnostic Techniques/methods , Spectroscopy, Near-Infrared/methods , HEK293 Cells , Humans , Image Processing, Computer-Assisted/standards , Lentivirus/isolation & purification , Lentivirus/pathogenicity , Lentivirus Infections/virology , Molecular Diagnostic Techniques/standards , Point-of-Care Systems , Saliva/virology , Sensitivity and Specificity , Spectroscopy, Near-Infrared/standards
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