Advances in Nanoplasmonic Biosensors: Optimizing Performance for Exosome Detection Applications

Devi Taufiq Nurrohman, Nan Fu Chiu*, Yu Sheng Hsiao, Yun Ju Lai, Himansu Sekhar Nanda

*此作品的通信作者

研究成果: 雜誌貢獻回顧評介論文同行評審

摘要

The development of sensitive and specific exosome detection tools is essential because they are believed to provide specific information that is important for early detection, screening, diagnosis, and monitoring of cancer. Among the many detection tools, surface-plasmon resonance (SPR) biosensors are analytical devices that offer advantages in sensitivity and detection speed, thereby making the sample-analysis process faster and more accurate. In addition, the penetration depth of the SPR biosensor, which is <300 nm, is comparable to the size of the exosome, making the SPR biosensor ideal for use in exosome research. On the other hand, another type of nanoplasmonic sensor, namely a localized surface-plasmon resonance (LSPR) biosensor, has a shorter penetration depth of around 6 nm. Structural optimization through the addition of supporting layers and gap control between particles is needed to strengthen the surface-plasmon field. This paper summarizes the progress of the development of SPR and LSPR biosensors for detecting exosomes. Techniques in signal amplification from two sensors will be discussed. There are three main parts to this paper. The first two parts will focus on reviewing the working principles of each sensor and introducing several methods that can be used to isolate exosomes. This article will close by explaining the various sensor systems that have been developed and the optimizations carried out to obtain sensors with better performance. To illustrate the performance improvements in each sensor system discussed, the parameters highlighted include the detection limit, dynamic range, and sensitivity.

原文英語
文章編號307
期刊Biosensors
14
發行號6
DOIs
出版狀態已發佈 - 2024 6月

ASJC Scopus subject areas

  • 分析化學
  • 生物技術
  • 生物醫學工程
  • 儀器
  • 工程(雜項)
  • 臨床生物化學

指紋

深入研究「Advances in Nanoplasmonic Biosensors: Optimizing Performance for Exosome Detection Applications」主題。共同形成了獨特的指紋。

引用此