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Enhanced detection sensitivity through enzyme-induced precipitate accumulation in LSPR-active nano-valleys.
Kwak, Su-Heon; Wi, Jung-Sub; Lee, Jieon; Kim, Chunjoong; Na, Hee-Kyung.
Afiliación
  • Kwak SH; Department of Materials Science and Engineering, Chungnam National University Daejeon 34134 Korea ckim0218@cnu.ac.kr.
  • Wi JS; Bio-Imaging Team, Korea Research Institute of Standards and Science (KRISS) Daejeon 34113 Korea nahk@kriss.re.kr.
  • Lee J; Department of Materials Science and Engineering, Hanbat National University Daejeon 34158 Korea.
  • Kim C; Predictive Toxicology Department, Korea Institute of Toxicology (KIT) Daejeon, 34114 Korea.
  • Na HK; Department of Materials Science and Engineering, Chungnam National University Daejeon 34134 Korea ckim0218@cnu.ac.kr.
RSC Adv ; 12(25): 15652-15657, 2022 May 23.
Article en En | MEDLINE | ID: mdl-35685716
ABSTRACT
Biomolecule detection based on the localized surface plasmon resonance (LSPR) phenomenon has advantages in label-free detection, good sensitivity, and measurement simplicity and reproducibility. However, in order to ultimately be used for actual diagnosis, the ability to detect trace amounts of biomarkers is necessary, which requires the development of signal enhancement strategies that enable ultrasensitive detection. In this paper, we provide a straightforward and efficient route to boost LSPR sensitivity based on multiple sample washings. We found that repeated washing and drying cycles lead to a shift in the LSPR peak in a concentration-dependent manner, where this process drives the accumulation of a precipitate, formed by an enzyme reaction with target specificity, in the sample's LSPR active plasmonic nano-valley structure. Results show that the washing and drying process leads to a signal enhancement of more 200 times compared to a sensor with only enzyme-based amplification. To maximize this effect, optimization of the plasmonic nanostructure was also carried out to finally achieve atto-molar detection of miRNA with a distinguishable LSPR peak shift.

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Diagnostic_studies Idioma: En Revista: RSC Adv Año: 2022 Tipo del documento: Article

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Diagnostic_studies Idioma: En Revista: RSC Adv Año: 2022 Tipo del documento: Article