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一种用于肾癌检测的多孔膜-Ag NPs 高灵敏度 SERS 基底。

A highly sensitive SERS substrate of porous membrane-Ag NPs for kidney cancer detection.

机构信息

School of opto-electronic and Communication Engineering, Xiamen University of Technology, Xiamen, 361024, Fujian, China.

Department of Pathology, Fujian Provincial Tumor Hospital, Fuzhou, 350014, Fujian, China.

出版信息

Anal Chim Acta. 2024 Aug 1;1315:342770. doi: 10.1016/j.aca.2024.342770. Epub 2024 May 21.

Abstract

BACKGROUND

The substrate employed in surface-enhanced Raman spectroscopy (SERS) constitutes an essential element in the cancer detection methodology. In this research, we introduce a three-dimensional (3D) structured SERS substrate that integrates a porous membrane with silver nanoparticles to enhance SERS spectral signals through the utilization of the aggregation effect of silver nanoparticles. This enhancement is crucial because accurate detection results strongly depend on the intensity of specific peaks in Raman spectroscopy. A highly sensitive SERS substrate can significantly improve the accuracy of detection results.

RESULTS

We collected 66 plasma samples from individuals with kidney cancer and control individuals, including both bladder cancer patients and healthy individuals. Then, we utilized substrates with and without porous membranes to acquire the SERS spectra of the samples, enabling us to evaluate the enhancement effect of our SERS substrate. The spectral analysis demonstrated enhanced peak intensities in the experimental group (with porous substrate) compared to the control group (without porous substrate). The uniformity and reproducibility of the SERS substrate are also significantly enhanced, which is very helpful for improving the accuracy of detection results. Additionally, the Principal Component Analysis-Linear Discriminant Analysis algorithm (PCA-LDA) was employed to classify the SERS spectra of both groups. In the experimental group, the classification accuracy was 98.5 % for kidney cancer, and 83.3 % for kidney and bladder cancer. Compared to the control group, it improved by 3 % and 12.6 % respectively.

SIGNIFICANT

This indicates that our 3D structured SERS substrate combined with multivariate statistical algorithms PCA-LDA can not only improve the accuracy of SERS detection technology in single cancer detection, but also has great potential in multiple cancer detection. This 3D structured SERS substrate is expected to become a new auxiliary means for cancer detection.

摘要

背景

表面增强拉曼光谱(SERS)中使用的衬底是癌症检测方法中的一个重要元素。在这项研究中,我们引入了一种具有三维(3D)结构的 SERS 衬底,该衬底将多孔膜与银纳米粒子结合在一起,通过利用银纳米粒子的聚集效应来增强 SERS 光谱信号。这种增强是至关重要的,因为准确的检测结果强烈依赖于拉曼光谱中特定峰的强度。高度灵敏的 SERS 衬底可以显著提高检测结果的准确性。

结果

我们收集了 66 份来自肾癌患者和对照组个体的血浆样本,包括膀胱癌患者和健康个体。然后,我们使用具有和不具有多孔膜的衬底来获取样本的 SERS 光谱,从而评估我们的 SERS 衬底的增强效果。光谱分析表明,实验组(具有多孔衬底)的峰强度增强,而对照组(没有多孔衬底)则没有。SERS 衬底的均匀性和重现性也得到了显著提高,这对提高检测结果的准确性非常有帮助。此外,我们还采用主成分分析-线性判别分析算法(PCA-LDA)对两组 SERS 光谱进行分类。在实验组中,肾癌的分类准确率为 98.5%,肾癌和膀胱癌的分类准确率为 83.3%。与对照组相比,分别提高了 3%和 12.6%。

重要意义

这表明,我们的 3D 结构 SERS 衬底结合多元统计算法 PCA-LDA,不仅可以提高 SERS 检测技术在单一癌症检测中的准确性,而且在多种癌症检测中具有很大的潜力。这种 3D 结构 SERS 衬底有望成为癌症检测的一种新的辅助手段。

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