Dual sensitive and rapid detection of glycated human serum albumin using a versatile lead/graphene nanocomposite probe as a fluorescence-electrochemical aptasensor

Monitoring of glycated human serum albumin (GHSA) as a glycemic marker for screening and monitoring of diabetes mellitus is widely practiced for patients with conditions that affect red blood cells. In this study, a complex comprising Pb ions adsorbed on graphene oxide (GO-Pb) was fabricated and utilized as a versatile probe in a fluorescence-electrochemical aptasensor for GHSA quantification. To simplify the aptasensor, the GO-Pb complex probe was prepared via an ion adsorption process. After modification with a fluorophore-labeled aptamer, the GO-Pb complex served as an excellent energy acceptor in fluorescence-based analysis, as well as generating a high current in the electrochemical transducer. Additionally, the proposed platform can detect GHSA via the dual technique from a single sample, allowing for precise and accurate results. Under optimal conditions, the fluorescence-electrochemical aptasensor exhibited a linear relationship with GHSA concentrations from 0.001 to 80 mu g mL(-1) and from 0.005 to 10 mu g mL(-1) for fluorescence and electrochemical detection, respectively. The corresponding detection limits were 8.80 ng mL(-1) and 0.77 ng mL(-1), respectively. The proposed aptasensor additionally displayed good selectivity and excellent stability. Moreover, its successful application in the analysis of clinical samples further demonstrated its utility. Therefore, the proposed platform has significant potential as a novel, facile, highly responsive, and low-cost monitoring method for the development of diabetes mellitus diagnostic devices intended for a clinical setting.

Automated summary

The study developed a versatile fluorescence-electrochemical aptasensor for the quantification of GHSA using a GO-Pb complex probe, showing a linear relationship and detection limits. The platform demonstrated good selectivity and stability, with potential applications in clinical sample analysis.