Design of a bioelectronic tongue for glucose monitoring using zinc oxide nanofibers and graphene derivatives - Mercante, Luiza A.; Andre, Rafaela S.; Facure, Murilo H.M.; Fugikawa-Santos, Lucas [UNESP]; Correa, Daniel S. (Elsevier, 2021)
Monitoring glucose levels is critical for diabetes management and might be a key step in the development of individualized treatment strategies. In this scenario, tracking salivary glucose has been recognized as a promising strategy due to its merits of ease sampling and non-invasive nature. In this paper, we report on the development of an electrical impedance-based biosensor array to distinguish glucose at different concentrations in saliva. The enzymatic biosensors were made of gold interdigitated electrodes coated with pristine electrospun zinc oxide nanofibers (NFZ) and NFZ combined with graphene-based nanomaterials (i.e., reduced graphene oxide - rGO and graphene quantum dots - GQDs), on which a layer of glucose oxidase (GOx) enzyme was adsorbed. Electrical impedance measurements indicate that the NFZ-GQDs@GOx and NFZ-rGO@GOx platforms presented good linear relationship with glucose concentration in the range of 0.1 to 6 mM. The highest sensitivity was reached for NFZ-rGO@GOx with a detection limit (LOD) of 14 μM, while the LOD was 32 μM for NFZ-GQDs@GOx. Both biosensors were also capable of detecting glucose in artificial saliva using aliquots of 10 μL, with recovery between 87.3 and 106.8%. Furthermore, the three sensing units (NFZ@GOx, NFZ-rGO@GOx and NFZ-GQDs@GOx) were employed to build a bioelectronic tongue. Using Principal Component Analysis (PCA) technique to project the electrical impedance data of all sensing units allowed the discrimination of the different glucose concentrations and interferents. This study reveals the applicability of the developed bioelectronic tongue as non-invasive glucose sensors, which approach could also be pottentially adapted to detect other disease biomarkers present in saliva.
Keywords: Biosensor array; Electrospinning; Electrospun nanofibers; Glucose detection; Graphene quantum dots; Reduced graphene oxide