Evidence map›Paper›PMID 39665317›Full record

ArticleJournal of extracellular vesicles2024

Direct imaging with multidimensional labelling and high-content analysis allows quantitative categorization and characterizations of individual small extracellular vesicles and nanoparticles (sEVPs).

Simou Sun, Sarah J Cox-Vázquez, Nam-Joon Cho, Guillermo C Bazan, Jay T Groves

Abstract read
In one paragraph

Article in Journal of extracellular vesicles, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
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  3. Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Simou SunInstitute for Digital Molecular Analytics and Science, Nanyang Technological University, Singapore, Singapore.ORCID 0000-0002-0596-1156
Sarah J Cox-VázquezDepartment of Chemistry, National University of Singapore, Singapore, Singapore.
Nam-Joon ChoSchool of Materials Science and Engineering, Nanyang Technological University, Singapore, Singapore.
Guillermo C BazanInstitute for Digital Molecular Analytics and Science, Nanyang Technological University, Singapore, Singapore.
Jay T GrovesInstitute for Digital Molecular Analytics and Science, Nanyang Technological University, Singapore, Singapore.

Funding

Ministry of Education, Singapore
6 · The paper itself

Abstract

Small extracellular vesicles and nanoparticles (sEVPs) are cell-secreted entities with potential as diagnostic biomarkers and therapeutic vehicles. However, significant intrinsic sEVP heterogeneity impedes analysis and understanding of their composition and functions. We employ multidimensional fluorescent labelling on sEVPs, leveraging the robustness of a newly developed membrane probe-conjugated oligoelectrolytes (COEs), and conduct total internal reflection fluorescence (TIRF) microscopy on sEVP arrays. These arrays comprise single sEVPs anchored to a soft material functionalized surface with little bias. We then develop an enhanced algorithm for colocalization analysis of the multiple labels on individual sEVPs and perform deep profiling of particle content. We categorize sEVPs derived from the same cell type into seven distinct subpopulations-some vesicular whereas others non-vesicular, and we demonstrate that sEVPs from four cell types exhibit quantitatively distinguishable subpopulation distributions. Furthermore, we gain insights into specific particle features within each subpopulation, including CD63 counts, relative particle size, relative concentration of cargoes, and correlations among different cargoes. This high-content analysis reveals common cargo sorting features in sEVP subpopulations across different cell types and suggests new statistics within the sEVP inherent heterogeneity that could differentiate sEVPs from two types of cancer cells and two types of normal cells. Collectively, our study presents a robust single-sEVP characterization platform, combining high-content imaging with comprehensive analysis. This platform is poised to advance sEVP-based theranostic assays and facilitate exploration into disease-associated sEVP biogenesis and sEVP-mediated intercellular communication.

Indexed as

Extracellular VesiclesNanoparticlesHumansMicroscopy, FluorescenceParticle SizeTetraspanin 30Tetraspanin 30High‐Content AnalysisHigh‐Throughput ArraysQuantitative ImagingSingle‐EV Characterizations

Identifiers

PMID39665317
PMCPMC11635478

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.