Timely detection and diagnosis are essentially needed to guide outbreak measures and infection control. It is vital to improve healthcare quality in public places, markets, schools and airports and provide useful insights into the technological environment and help researchers acknowledge the choices and gaps available in this field. In this narrative review, the detection of coronavirus disease 2019 (COVID-19) technologies is summarized and discussed with a comparison between them from several aspects to arrive at an accurate decision on the feasibility of applying the best of these techniques in the biosensors that operate using laser detection technology. The collection of data in this analysis was done by using six reliable academic databases, namely, Science Direct, IEEE Xplore, Scopus, Web of Science, Google Scholar and PubMed. This review includes an analysis review of three highlights: evaluating the hazard of pandemic COVID-19 transmission styles and comparing them with Severe Acute Respiratory Syndrome (SARS) and Middle East Respiratory Syndrome (MERS) to identify the main causes of the virus spreading, a critical analysis to diagnose coronavirus disease 2019 (COVID-19) based on artificial intelligence using CT scans and CXR images and types of biosensors. Finally, we select the best methods that can potentially stop the propagation of the coronavirus pandemic.
Matched MeSH terms: Biosensing Techniques/statistics & numerical data
In this study, an amino-modified aptasensor using multi-walled carbon nanotubes (MWCNTs)-deposited ITO electrode was prepared and evaluated for the detection of pathogenic Salmonella bacteria. An amino-modified aptamer (ssDNA) which binds selectively to whole-cell Salmonella was immobilised on the COOH-rich MWCNTs to produce the ssDNA/MWCNT/ITO electrode. The morphology of the MWCNT before and after interaction with the aptamers were observed using scanning electron microscopy (SEM). Cyclic voltammetry and electrochemical impedance spectroscopy techniques were used to investigate the electrochemical properties and conductivity of the aptasensor. The results showed that the impedance measured at the ssDNA/MWCNT/ITO electrode surface increased after exposure to Salmonella cells, which indicated successful binding of Salmonella on the aptamer-functionalised surface. The developed ssDNA/MWCNT/ITO aptasensor was stable and maintained linearity when the scan rate was increased from 10 mV s-1 to 90 mV s-1. The detection limit of the ssDNA/MWCNT/ITO aptasensor, determined from the sensitivity analysis, was found to be 5.5 × 101 cfu mL-1 and 6.7 × 101 cfu mL-1 for S. Enteritidis and S. Typhimurium, respectively. The specificity test demonstrated that Salmonella bound specifically to the ssDNA/MWCNT/ITO aptasensor surface, when compared with non-Salmonella spp. The prepared aptasensor was successfully applied for the detection of Salmonella in food samples.
Matched MeSH terms: Biosensing Techniques/statistics & numerical data