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.
摘要：
阿尔茨海默病（AD）是一种进行性和不可逆的神经退行性脑疾病，具有显著的经济和社会影响，而早期AD诊断仍然是一个相当大的挑战。这里,在微阵列芯片上制作了一个强大而方便的表面增强拉曼散射（SERS）分析平台，以剖析血清成分的变化，用于AD诊断。消除侵入性脑脊液（CSF）为基础和昂贵的仪器依赖的诊断方法。通过在液-液界面自组装制备的AuNOs阵列能够以优异的再现性获得SERS光谱。此外，有限差分时域(FDTD)模拟表明，AuNO聚集产生了显著的等离子体激元杂交，导致高信噪比的SERS光谱。我们建立了Aβ1-40诱导的AD小鼠模型，然后记录了不同阶段的血清SERS光谱。采用基于主成分分析（PCA）加权表示的k近邻（WRKNN）的多变量分析方法进行特征提取，以提高分类性能。准确率超过95%，AUC超过90%，灵敏度超过80%,特异性超过96.7%。这项研究的结果证明了SERS作为诊断筛查方法的应用潜力，在进一步验证和优化后，这可能为未来的生物医学应用开辟新的令人兴奋的机会。
