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Sensitive Readout for Microfluidic High-Throughput Applications using Scanning SQUID Microscopy.
Wissberg, Shai; Ronen, Maria; Oren, Ziv; Gerber, Doron; Kalisky, Beena.
Afiliação
  • Wissberg S; Department of Physics, Bar-Ilan University, Ramat-Gan, 52900, Israel.
  • Ronen M; Institute for Nanotechnology and Advanced Materials, Bar-Ilan University, Ramat-Gan, 52900, Israel.
  • Oren Z; Institute for Nanotechnology and Advanced Materials, Bar-Ilan University, Ramat-Gan, 52900, Israel.
  • Gerber D; Mina and Everard Goodman Faculty of Life Sciences, Bar-Ilan University, Ramat-Gan, 52900, Israel.
  • Kalisky B; Mina and Everard Goodman Faculty of Life Sciences, Bar-Ilan University, Ramat-Gan, 52900, Israel.
Sci Rep ; 10(1): 1573, 2020 01 31.
Article em En | MEDLINE | ID: mdl-32005843
Microfluidic chips provide a powerful platform for high-throughput screening of diverse biophysical systems. The most prevalent detection methods are fluorescence based. Developing new readout techniques for microfluidics focusing on quantitative information in the low signal regime is desirable. In this work, we combine the well-established immunoassay approach, with magnetic nanoparticles, with a highly sensitive magnetic imaging technique. We offer to integrate a microfluidic array into a scanning superconducting quantum interference device (SQUID) microscope, to image nanoparticles that were moved through the microfluidic device. We demonstrate the technique on protein-protein interactions (PPI). We compare sensitivity to that of a conventional readout, quantify the amount of interactions, and demonstrate 0.1 atto-mole sensitivity. Our work serves as a proof of concept that will promote the development of a new set of eyes, a stable usable microfluidic-scanning SQUID microscopy.

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies Idioma: En Revista: Sci Rep Ano de publicação: 2020 Tipo de documento: Article País de afiliação: Israel

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Diagnostic_studies Idioma: En Revista: Sci Rep Ano de publicação: 2020 Tipo de documento: Article País de afiliação: Israel