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Related Experiment Video

Updated: Sep 24, 2025

Rapid Fluorescence-based Characterization of Single Extracellular Vesicles in Human Blood with Nanoparticle-tracking Analysis
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Single Small Extracellular Vesicle (sEV) Quantification by Upconversion Nanoparticles.

Guan Huang1, Ying Zhu1,2,3, Shihui Wen1

  • 1Institute for Biomedical Materials and Devices (IBMD), Faculty of Science, University of Technology Sydney, Sydney, New South Wales 2007, Australia.

Nano Letters
|May 2, 2022
PubMed
Summary
This summary is machine-generated.

This study introduces a novel platform for detecting cancer-derived small extracellular vesicles (sEVs) using upconversion nanoparticles (UCNPs). This method offers highly sensitive single-sEV enumeration for improved cancer biomarker discovery and diagnosis.

Keywords:
Cancer DiagnosticsExtracellular Vesicles (EVs)ImagingUpconversion Nanoparticles (UCNPs)

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Area of Science:

  • Biotechnology
  • Nanotechnology
  • Biochemistry

Background:

  • Cancer-derived small extracellular vesicles (sEVs) are promising circulating biomarkers for liquid biopsies.
  • Detecting and quantifying sEVs is challenging due to their small size, low abundance, and molecular heterogeneity.

Purpose of the Study:

  • To develop a highly sensitive platform for single-sEV enumeration.
  • To overcome the limitations of current methods for sEV detection and characterization.

Main Methods:

  • Utilized lanthanide-doped upconversion nanoparticles (UCNPs) for single-sEV detection.
  • Employed total internal reflection fluorescence (TIRF) imaging to eliminate background noise.
  • Validated specificity using EpCAM-positive and EpCAM-negative sEVs.

Main Results:

  • Achieved a limit of detection of 1.8 × 10^6 EVs/mL, nearly 3 orders of magnitude lower than ELISA.
  • Demonstrated high accuracy and correlation (R^2 > 0.99) compared to immunomagnetic-beads flow cytometry.
  • Showcased the platform's capability for evaluating heterogeneous antigen expression on sEVs.

Conclusions:

  • The UCNP-based single-sEV platform provides a sensitive and accurate method for sEV enumeration.
  • This technology facilitates biomarker discovery and disease diagnosis through improved sEV analysis.
  • The platform's adaptability supports the evaluation of sEV heterogeneity for clinical applications.