Facile Synthesis of Ag/AgVO3/N-rGO Hybrid Nanocomposites for Electrochemical Detection of Levofloxacin for Complex Biological Samples Using Screen-Printed Carbon Paste Electrodes.

Silver vanadate nanorods (ß-AgVO3) with silver nanoparticles (Ag-NPs) decorated on the surface of the rods were synthesized by using simple hydrothermal technique and later anchored onto nitrogen-doped reduced graphene oxide (N-rGO) to make a novel nanocomposite. Experimental analyses were carried out to identify the electronic configuration by X-ray diffraction analysis, Fourier transform infrared spectroscopy, and X-ray photoelectron spectroscopy analysis, which revealed monoclinic patterns of the C12/m1 space group with Wulff construction forming beta silver vanadate (ß-AgVO3) crystals with optical density and phase transformations. Ag nucleation showed consistent results with metallic formation and electronic changes occurring in [AgO5] and [AgO3] clusters. Transmission electron microscopy and field-emission scanning electron microscopy with elemental mapping and EDX analysis of the morphology reveals the nanorod structure for ß-AgVO3 with AgNPs on the surface and sheets for N-rGO. Additionally, a novel electrochemical sensor is constructed by using Ag/AgVO3/N-rGO on screen-printed carbon paste electrodes for the detection of antiviral drug levofloxacin (LEV) which is used as a primary antibiotic in controlling COVID-19. Using differential pulse voltammetry, LEV is determined with a low detection limit of 0.00792 nm for a linear range of 0.09-671 µM with an ultrahigh sensitivity of 152.19 µA µM-1 cm-2. Furthermore, modified electrode performance is tested by real-time monitoring using biological and river samples.

Kinetics of SARS-CoV-2 positivity of infected and recovered patients from a single center.

Recurrence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) positive detection in infected but recovered individuals has been reported. Patients who have recovered from coronavirus disease 2019 (COVID-19) could profoundly impact the health care system. We sought to define the kinetics and relevance of PCR-positive recurrence during recovery from acute COVID-19 to better understand risks for prolonged infectivity and reinfection. A series of 414 patients with confirmed SARS-Cov-2 infection, at The Second Affiliated Hospital of Southern University of Science and Technology in Shenzhen, China from January 11 to April 23, 2020. Statistical analyses were performed of the clinical, laboratory, radiologic image, medical treatment, and clinical course of admission/quarantine/readmission data, and a recurrence predictive algorithm was developed. 16.7% recovered patients with PCR positive recurring one to three times, despite being in strict quarantine. Younger patients with mild pulmonary respiratory syndrome had higher risk of PCR positivity recurrence. The recurrence prediction model had an area under the ROC curve of 0.786. This case series provides characteristics of patients with recurrent SARS-CoV-2 positivity. Use of a prediction algorithm may identify patients at high risk of recurrent SARS-CoV-2 positivity and help to establish protocols for health policy.