Quantitative single-particle profiling of extracellular vesicles <i>via</i> fluorescent nanoparticle tracking analysis

An optimised protocol for quantitative profiling of EVs at the single-particle level by fluorescent nanoparticle tracking analysis, which enables precise quantification of EV concentration, size distribution, and surface immunophenotype.

Authors

Institutions

Publication Details

Journal
Sensors & Diagnostics
Published
2025-12-03
DOI
https://doi.org/10.1039/d5sd00119f
Citations
1
Primary Topic
Extracellular vesicles in disease
Type
article
Field-Weighted Citation Impact
0.81

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Quantitative single-particle profiling of extracellular vesicles via fluorescent nanoparticle tracking analysis

Juanfang Ruan, Ying‐Jie Zhu, Yiting Liu, Anthony James El-helou et al.
1 citations
Sensors & Diagnostics
Extracellular vesicles in disease
0.81
article

Quantitative single-particle profiling of extracellular vesicles via fluorescent nanoparticle tracking analysis

Juanfang Ruan, Ying‐Jie Zhu, Yiting Liu, Anthony James El-helou, Bill Söderstörm
article en
1 citations

Abstract

An optimised protocol for quantitative profiling of EVs at the single-particle level by fluorescent nanoparticle tracking analysis, which enables precise quantification of EV concentration, size distribution, and surface immunophenotype.

Sensors & DiagnosticsVol. 5(3)
University of Technology Sydney (AU), Australia Telescope National Facility (AU), UNSW Sydney (AU), St Vincent's Clinic (AU)
Xiamen University
Openalex Percentile: Top 21%
Extracellular vesicles in disease
0.81
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.