Gold nanoparticles spectral CT imaging and limit of detectability in a new materials contrast-detail phantom.

This study involves the synthesis, characterization, and spectral photon counting CT (SPCCT) imaging of gold nanoparticles tailored for enhancing the contrast of small cancer lesions. We used the modified Turkevich method to produce thiol-capped gold nanoparticles (AuNPs) at different concentrations (20, 15, 10, 5, 2.5, 1.25, 0.6 mg/ml). We thoroughly characterized the AuNPs using Transmission Electron Microscopy (TEM), X-ray diffraction spectroscopy (XRD), Dynamic Light Scattering (DLS), and UV-visible absorption spectroscopy. To assess the AuNPs contrast enhancing performance, we designed and built a new material contrast detail phantom for CT imaging and determined the minimum detectable concentrations of AuNPs in simulated lesions of small diameters (1, 2, 3, and 5 mm). The synthesized AuNPs are spherical with an average size of approximately 20 ± 4 nm, with maximum UV absorption occurring at 527 nm wavelength, and exhibit a face-centered cubic structure of gold according to XRD analysis. The synthesized gold nanoparticles demonstrated high contrast in SPCCT, suggesting their potential as contrast agents for imaging cancer tissues. The AuNPs image contrast was directly proportional to the AuNPs concentration. We are the first to determine that the lowest visually distinguishable contrast was achieved at a gold concentration of 5 mg/ml for a 2 mm simulated lesion. For 1 mm size lesion the smallest visible concentration was 10 mg/ml. This newly developed phantom can be used for determining the minimal concentration required for various high-Z nanoparticles to produce detectable contrast in X-ray imaging for small-size simulated lesions.

Detection and quantification of SARS-CoV-2 RNA in wastewater and treated effluents: Surveillance of COVID-19 epidemic in the United Arab Emirates.

Testing SARS-CoV-2 viral loads in wastewater has recently emerged as a method of tracking the prevalence of the virus and an early-warning tool for predicting outbreaks in the future. This study reports SARS-CoV-2 viral load in wastewater influents and treated effluents of 11 wastewater treatment plants (WWTPs), as well as untreated wastewater from 38 various locations, in the United Arab Emirates (UAE) in May and June 2020. Composite samples collected over twenty-four hours were thermally deactivated for safety, followed by viral concentration using ultrafiltration, RNA extraction using commercially available kits, and viral quantification using RT-qPCR. Furthermore, estimates of the prevalence of SARS-CoV-2 infection in different regions were simulated using Monte Carlo. Results showed that the viral load in wastewater influents from these WWTPs ranged from 7.50E+02 to over 3.40E+04 viral gene copies/L with some plants having no detectable viral RNA by RT-qPCR. The virus was also detected in 85% of untreated wastewater samples taken from different locations across the country, with viral loads in positive samples ranging between 2.86E+02 and over 2.90E+04 gene copies/L. It was also observed that the precautionary measures implemented by the UAE government correlated with a drop in the measured viral load in wastewater samples, which were in line with the reduction of COVID-19 cases reported in the population. Importantly, none of the 11 WWTPs' effluents tested positive during the entire sampling period, indicating that the treatment technologies used in the UAE are efficient in degrading SARS-CoV-2, and confirming the safety of treated re-used water in the country. SARS-CoV-2 wastewater testing has the potential to aid in monitoring or predicting an outbreak location and can shed light on the extent viral spread at the community level.