Glycated albumin (GA) is rapidly emerging as a robust biomarker for screening and monitoring of diabetes. To facilitate its rapid, point-of-care measurements, a label-free surface-enhanced Raman spectroscopy (SERS) sensing platform is reported that leverages the specificity of molecular vibrations and signal amplification on silver-coated silicon nanowires (Ag/SiNWs) for highly sensitive and reproducible quantification of GA. The simulations and experimental measurements demonstrate that the disordered orientation of the nanowires coupled with the wicking of the analyte molecules during the process of solvent evaporation facilitates molecular trapping at the generated plasmonic hotspots. Highly sensitive detection of glycated albumin is shown with the ability to visually detect spectral features at as low as 500 × 10-9 m, significantly below the physiological range of GA in body fluids. Combined with chemometric regression models, the spectral data recorded on the Ag/SiNWs also allow accurate prediction of glycated concentration in mixtures of glycated and non-glycated albumin in proportions that reflect those in the bloodstream.
Keywords: biosensing; diabetes screening; glycated albumin; machine learning; nanowires; plasmonics; surface enhanced Raman spectroscopy (SERS).
© 2020 Wiley-VCH GmbH.