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Updated: Sep 19, 2025

Development of an Electrochemical DNA Biosensor to Detect a Foodborne Pathogen
Published on: June 3, 2018
Enhanced Acetaminophen Detection in Dolo-650 Tablets Using Electrocatalyst SnWO4-DNA Composite and Its Antibacterial
Sneka Kumaresan1, Girija Srinivasan1, Murugan Shibasini2,3
1Polymer Electronics Lab, Department of Bioelectronics and Biosensors, Alagappa University, Karaikudi 630 003, Tamil Nadu, India.
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Important aspects of this research include the development of a very sensitive electrochemical sensor for acetaminophen (AMP) in D-650 tablets using SnWO4-DNA as the sensing material. The surface area and porosity of the material were investigated using the Brunauer-Emmett-Teller (BET) instrument. Furthermore, a TEM study was performed to observe the presence of DNA in SnWO4, and X-ray photoelectron spectroscopy (XPS) was executed to record the chemical composition. The sensor is based on the chemical interaction between Sn2+ and WO42- ions, which enhances the catalytic activity and the active sites for AMP interaction created by the DNA's nitrogen bases, promoting efficient electron transfer with high sensitivity. The developed sensor performs over AMP detection in D-650 with a much wider linear detection range (200 nM-1 mM), a much lower limit of detection (55 nM), and excellent reversibility. Furthermore, the sensor provides fast detection, suitable for real-time monitoring. In addition, the antibacterial properties of the SnWO4-DNA composite are demonstrated by the effective inhibition growth of Klebsiella pneumoniae and Staphylococcus aureus, making this a multifunctional tool in both AMP and antibacterial applications. Being able to provide simultaneous chemical detection and antibacterial responses allows this material to have dual capability in medical diagnostics. The high sensitivity and multifunctionality of the proposed sensor make it an innovative and promising approach that would have wide application in the medical industry for AMP monitoring, pathogen control, and potentially in personalized medicine for determining the appropriate treatment regimen for patients.

