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Piezoelectric Cantilever Biosensors for Label-free, Real-time Detection of DNA and RNA.
Haring, Alexander P; Cesewski, Ellen; Johnson, Blake N.
Afiliação
  • Haring AP; Department of Industrial and Systems Engineering, School of Neuroscience, Macromolecules Innovation Institute, Virginia Tech, 1145 Perry Street, Blacksburg, VA, 24061, USA.
  • Cesewski E; Department of Industrial and Systems Engineering, School of Neuroscience, Macromolecules Innovation Institute, Virginia Tech, 1145 Perry Street, Blacksburg, VA, 24061, USA.
  • Johnson BN; Department of Industrial and Systems Engineering, School of Neuroscience, Macromolecules Innovation Institute, Virginia Tech, 1145 Perry Street, Blacksburg, VA, 24061, USA. bnj@vt.edu.
Methods Mol Biol ; 1572: 247-262, 2017.
Article em En | MEDLINE | ID: mdl-28299693
ABSTRACT
This chapter reviews the design, fabrication, characterization, and application of piezoelectric-excited millimeter-sized cantilever (PEMC) sensors. The sensor transduction mechanism, sensing principle, and mode of operation are discussed. Bio-recognition strategies and surface functionalization methods for detection of DNA and RNA are discussed with a focus on self-assembly-based approaches. Methods for the verification of biosensor response via secondary binding assays, reversible binding assays, and the integration of complementary transduction mechanisms are presented. Sensing applications for medical diagnostics, food safety, and environmental monitoring are provided. PEMC sensor technology provides a robust platform for the real-time, label-free detection of DNA and RNA in complex matrices over nanomolar (nM) to attomolar (aM) concentration ranges.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: DNA / RNA / Técnicas Biossensoriais / Técnicas Eletroquímicas Tipo de estudo: Diagnostic_studies Idioma: En Ano de publicação: 2017 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: DNA / RNA / Técnicas Biossensoriais / Técnicas Eletroquímicas Tipo de estudo: Diagnostic_studies Idioma: En Ano de publicação: 2017 Tipo de documento: Article