Speaker
Description
The rapid and accurate detection of COVID-19 is critical in managing and controlling the spread of the virus. This study aims to develop a Carbon Quantum Dot (CQD)- based biosensor for the detection of COVID-19 from total RNA extracted from real samples. The main objectives of this research are to test the performance of the CQD-Interdigitated Electrode (IDE) biosensor in terms of sensitivity, specificity, and reproducibility, to evaluate signal interactions and amplification between the Coronavirus and biomarkers using the Electrical Measurements Test (Keithley 2450), as well as to validate the biosensor's efficiency by comparing it with the established Reverse Transcription Polymerase Chain Reaction (RT-PCR) method. The CQD-IDE biosensor was meticulously tested for its ability to detect the presence of Coronavirus RNA in various samples. Sensitivity and specificity metrics were rigorously assessed, showing promising results that indicate high detection accuracy. Signal interactions were analyzed through Keithley 2450, demonstrating significant amplification correlated with the presence of target viral RNA. Clinical validation was performed on real clinical samples, showing a detection accuracy of 98% compared to standard RT-PCR methods. Comparative validation against RT-PCR highlighted the CQD-IDE biosensor’s potential for rapid, reliable, and cost-effective COVID-19 diagnostics. These findings suggest that the CQD-IDE biosensor could be a valuable tool in the ongoing efforts to enhance COVID-19 detection capabilities, offering a robust alternative to current diagnostic methods.
