%0 Journal Article
%T PCA-WRKNN-assisted label-free SERS serum analysis platform enabling non-invasive diagnosis of Alzheimer's disease.
%A Li W
%A Chen G
%A Chen M
%A Shen K
%A Wu C
%A Shen W
%A Zhang F
%J Spectrochim Acta A Mol Biomol Spectrosc
%V 302
%N 0
%D 2023 Dec 5
%M 37392535
%F 4.831
%R 10.1016/j.saa.2023.123088
%X Alzheimer's disease (AD) is a progressive and irreversible neurodegenerative brain disorder with significant economic and societal impacts, whereas early AD diagnosis remains a considerable challenge. Here, a robust and convenient surface-enhanced Raman scattering (SERS) analysis platform was fabricated on a microarray chip to dissect the variation in serum composition for AD diagnosis, eliminating the invasive cerebrospinal fluid (CSF)-based and costly instrument-dependent diagnostic methods. AuNOs array prepared by self-assembly at liquid-liquid interface enabled the acquirement of SERS spectra with excellent reproducibility. Moreover, a finite-difference time-domain (FDTD) simulation suggested the significant plasmon hybridization generated by AuNOs aggregation, resulting in high signal-to-noise ratio SERS spectra. We established an AD mice model with Aβ1-40 induction followed by recording the serum SERS spectra at different stages. A multivariate analysis method of principal component analysis (PCA)-weighted representation-based k-nearest neighbor (WRKNN) was applied for the characteristics extraction to improve the classification performance, with an accuracy of over 95 %, an AUC of over 90 %, a sensitivity of over 80 %, and a specificity of over 96.7 %. The results of this study demonstrate the potential of SERS application as a diagnostic screening method, following further validation and optimization, which may open up new exciting opportunities for future biomedical applications.