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DNA-Engineerable Ultraflat-Faceted Core-Shell Nanocuboids with Strong, Quantitative Plasmon-Enhanced Fluorescence Signals for Sensitive, Reliable MicroRNA Detection.
Hwang, Jae-Ho; Park, Soohyun; Son, Jiwoong; Park, Joon Won; Nam, Jwa-Min.
  • Hwang JH; Department of Chemistry, Seoul National University, Seoul 151-747, South Korea.
  • Park S; Department of Chemistry, Pohang University of Science and Technology, 77 Cheongam-Ro, Nam-Gu, Pohang 37673, South Korea.
  • Son J; Department of Chemistry, Seoul National University, Seoul 151-747, South Korea.
  • Park JW; Department of Chemistry, Pohang University of Science and Technology, 77 Cheongam-Ro, Nam-Gu, Pohang 37673, South Korea.
  • Nam JM; Department of Chemistry, Seoul National University, Seoul 151-747, South Korea.
Nano Lett ; 21(5): 2132-2140, 2021 03 10.
Article en En | MEDLINE | ID: mdl-33596085
ABSTRACT
There has been enormous interest in understanding and utilizing plasmon-enhanced fluorescence (PEF) with metal nanostructures, but maximizing the enhancement in a reproducible, quantitative manner while reliably controlling the distance between dyes and metal particle surface for practical applications is highly challenging. Here, we designed and synthesized fluorescence-amplified nanocuboids (FANCs) with highly enhanced and controlled PEF signals, and fluorescent silica shell-coated FANCs (FS-FANCs) were then formed to fixate the dye position and increase particle stability and fluorescence signal intensity for biosensing applications. By uniformly modifying fluorescently labeled DNA on Au nanorods and forming ultraflat Ag shells on them, we were able to reliably control the distance between fluorophores and Ag surface and obtained an ∼186 fluorescence enhancement factor with these FANCs. Importantly, FS-FANCs were utilized as fluorescent nanoparticle tags for microarray-based miRNA detection, and we achieved >103-fold higher sensitivity than commercially available chemical fluorophores with 100 aM to 1 pM dynamic range.
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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: MicroARNs Tipo de estudio: Diagnostic_studies Idioma: En Año: 2021 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: MicroARNs Tipo de estudio: Diagnostic_studies Idioma: En Año: 2021 Tipo del documento: Article