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- W4382364355 abstract "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." @default.
- W4382364355 created "2023-06-29" @default.
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- W4382364355 date "2023-12-01" @default.
- W4382364355 modified "2023-09-26" @default.
- W4382364355 title "PCA-WRKNN-assisted label-free SERS serum analysis platform enabling non-invasive diagnosis of Alzheimer’s disease" @default.
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- W4382364355 doi "https://doi.org/10.1016/j.saa.2023.123088" @default.
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