Skip to Main Content (Press Enter)

Logo UNIMORE
  • ×
  • Home
  • Degree programmes
  • Modules
  • Jobs
  • People
  • Research Outputs
  • Academic units
  • Third Mission
  • Projects
  • Skills

UNI-FIND
Logo UNIMORE

|

UNI-FIND

unimore.it
  • ×
  • Home
  • Degree programmes
  • Modules
  • Jobs
  • People
  • Research Outputs
  • Academic units
  • Third Mission
  • Projects
  • Skills
  1. Research Outputs

Digital Detection of Exosomes by Interferometric Imaging

Academic Article
Publication Date:
2016
Short description:
Digital Detection of Exosomes by Interferometric Imaging / G Daaboul, George; Gagni, Paola; Benussi, Luisa; Bettotti, Paolo; Ciani, Miriam; Cretich, Marina; S Freedman, David; Ghidoni, Roberta; Yalcin Ozkumur, Ayca; Piotto, Chiara; Prosperi, Davide; Santini, Benedetta; Selim Ünlü, M; Chiari, Marcella. - In: SCIENTIFIC REPORTS. - ISSN 2045-2322. - 6:(2016), pp. N/A-N/A. [10.1038/srep37246]
abstract:
Exosomes, which are membranous nanovesicles, are actively released by cells and have been attributed to roles in cell-cell communication, cancer metastasis, and early disease diagnostics. The small size (30-100 nm) along with low refractive index contrast of exosomes makes direct characterization and phenotypical classification very difficult. In this work we present a method based on Single Particle Interferometric Reflectance Imaging Sensor (SP-IRIS) that allows multiplexed phenotyping and digital counting of various populations of individual exosomes (>50 nm) captured on a microarray-based solid phase chip. We demonstrate these characterization concepts using purified exosomes from a HEK 293 cell culture. As a demonstration of clinical utility, we characterize exosomes directly from human cerebrospinal fluid (hCSF). Our interferometric imaging method could capture, from a very small hCSF volume (20 uL), nanoparticles that have a size compatible with exosomes, using antibodies directed against tetraspanins. With this unprecedented capability, we foresee revolutionary implications in the clinical field with improvements in diagnosis and stratification of patients affected by different disorders.
Iris type:
Articolo su rivista
List of contributors:
G Daaboul, George; Gagni, Paola; Benussi, Luisa; Bettotti, Paolo; Ciani, Miriam; Cretich, Marina; S Freedman, David; Ghidoni, Roberta; Yalcin Ozkumur, Ayca; Piotto, Chiara; Prosperi, Davide; Santini, Benedetta; Selim Ünlü, M; Chiari, Marcella
Handle:
https://iris.unimore.it/handle/11380/1389481
Full Text:
https://iris.unimore.it//retrieve/handle/11380/1389481/938420/Daaboul%202016.pdf
Published in:
SCIENTIFIC REPORTS
Journal
  • Use of cookies

Powered by VIVO | Designed by Cineca | 26.4.4.0