高级检索
当前位置: 首页 > 详情页

Fabrication of optoplasmonic particles through electroless deposition and the application in SERS-based screening of nodule-involved lung cancer.

| 导出 | |

文献详情

资源类型:
WOS体系:
Pubmed体系:

收录情况: ◇ SCIE

机构: [1]School of Materials and Energy, University of Electronic Science and Technology of China, Chengdu 611731, China. [2]School of Medicine, University of Electronic Science and Technology of China, Chengdu 611731, China. [3]Department of Clinical Laboratory, Sichuan Cancer Hospitall, Chengdu 610042, China. [4]Department of Radiation Oncology, Sichuan Cancer Hospital & Institute, Radiation Oncology Key Laboratory of Sichuan Province, Chengdu 610042, China. [5]School of Automation Engineering & School of Foreign Languages, University of Electronic Science and Technology of China, Chengdu 611731, China. [6]Department of Radiation Oncology, Sichuan Cancer Hospital & Institute, Radiation Oncology Key Laboratory of Sichuan Province, Chengdu 610042, China. Electronic address: cxqyguestc@163.com.
出处:
ISSN:

摘要:
In this work, a core-satellite optoplasmonic particle containing a silica microsphere covered with gold nanoparticles (AuNPs) was developed through wet chemistry synthesis in aqueous phase. The electroless deposition and galvanic replacement were employed to anchor AuNPs onto silica sphere surface. The escalated as well as expanded electric field enhancement within the dielectric-metallic interface was analyzed through finite difference time domain (FDTD) simulation. The numerical models and the surface-enhancement Raman spectroscopy (SERS) measurements over blood serum both support that the equatorial plane is the preferred collecting plane for improved signal intensity and stability. The nanocomposite emerged lower relative standard deviation (RSD) in repetitive measurement compared to AuNPs. In practice, this hybrid structure was applied for lung cancer diagnosis based on serum SERS spectra analysis of the patients diagnosed with nodules. The prediction with the aid of principal component analysis (PCA) and support-vector machine (SVM) was attempted for the classification of healthy, benign and relatively malignant sample groups. The accuracy of distinguish benign samples from malignant ones reaches over 90%. These advantages make the structure a promising SERS substrate for the early screening of cancer based on the non-invasive biological samples.Copyright © 2022 Elsevier B.V. All rights reserved.

语种:
被引次数:
WOS:
PubmedID:
中科院(CAS)分区:
出版当年[2022]版:
大类 | 2 区 化学
小类 | 2 区 光谱学
最新[2023]版:
大类 | 2 区 化学
小类 | 2 区 光谱学
JCR分区:
出版当年[2022]版:
Q1 SPECTROSCOPY
最新[2023]版:
Q1 SPECTROSCOPY

影响因子: 最新[2023版] 最新五年平均 出版当年[2022版] 出版当年五年平均 出版前一年[2021版] 出版后一年[2023版]

第一作者:
第一作者机构: [1]School of Materials and Energy, University of Electronic Science and Technology of China, Chengdu 611731, China.
共同第一作者:
通讯作者:
推荐引用方式(GB/T 7714):
APA:
MLA:

资源点击量:46895 今日访问量:0 总访问量:3333 更新日期:2024-11-01 建议使用谷歌、火狐浏览器 常见问题

版权所有©2020 四川省肿瘤医院 技术支持:重庆聚合科技有限公司 地址:成都市人民南路四段55号