Abstract
With the global escalation of concerns surrounding prostate cancer (PCa) diagnosis, reliance on the serologic prostate-specific antigen (PSA) test remains the primary approach. However, the imperative for early PCa diagnosis necessitates more effective, accurate, and rapid diagnostic point-of-care (POC) devices to enhance the result reliability and minimize disease-related complications. Among POC approaches, electrochemical biosensors, known for their amenability and miniaturization capabilities, have emerged as promising candidates. In this study, we developed an impedimetric sensing platform to detect urinary zinc (UZn) in both artificial and clinical urine samples. Our approach lies in integrating label-free impedimetric sensing and the introduction of porosity through surface modification techniques. Leveraging a cellulose acetate/reduced graphene oxide composite, our sensor's recognition layer is engineered to exhibit enhanced porosity, critical for improving the sensitivity, capture, and interaction with UZn. The sensitivity is further amplified by incorporating zincon as an external dopant, establishing highly effective recognition sites. Our sensor demonstrates a limit of detection of 7.33 ng/mL in the 0.1-1000 ng/mL dynamic range, which aligns with the reference benchmark samples from clinical biochemistry. Our sensor results are comparable with the results of inductively coupled plasma mass spectrometry (ICP-MS) where a notable correlation of 0.991 is achieved. To validate our sensor in a real-life scenario, tests were performed on human urine samples from patients being investigated for prostate cancer. Testing clinical urine samples using our sensing platform and ICP-MS produced highly comparable results. A linear correlation with R2 = 0.964 with no significant difference between two groups (p-value = 0.936) was found, thus confirming the reliability of our sensing platform.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.