Evidence map›Paper›PMID 40422033›Full record

ArticleBiosensors2025

An Extracellular Vesicle (EV) Paper Strip for Rapid and Convenient Estimation of EV Concentration.

Gisela Ströhle, Rebecca Goodrum, Huiyan Li

Abstract read
In one paragraph

Article in Biosensors, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

3 authors.

Gisela StröhleSchool of Engineering, University of Guelph, Guelph, ON N1G 2W1, Canada.
Rebecca GoodrumSchool of Engineering, University of Guelph, Guelph, ON N1G 2W1, Canada.ORCID 0000-0001-9291-7163
Huiyan LiSchool of Engineering, University of Guelph, Guelph, ON N1G 2W1, Canada.

Funding

Natural Sciences and Engineering Research Council of Canada 401941the University of Guelph not applicable
6 · The paper itself

Abstract

Extracellular vesicles (EVs) have emerged as promising biomarkers and therapeutic agents, yet their quantification remains technically challenging due to the limitations of conventional methods. Here, a low-cost, fluorescence-based, paper-strip immunoassay is presented for rapid and semi-quantitative estimation of EV concentration, inspired by pH strips. The assay utilizes nitrocellulose membranes functionalized with capture antibodies (anti-CD63, CD9, CD81) and fluorescent dye (ExoBrite™) for EV detection. Systematic optimization of assay parameters-including dye application sequence, incubation time, antibody configuration, and dye concentration-revealed that labeling EVs with dye and incubating on the nitrocellulose paper strips for 20 min yielded the strongest and most reproducible signal. A 200× dilution of ExoBrite™ dye was determined to provide the best balance between sensitivity and specificity. A standard curve generated through twofold serial dilution of EVs from ovarian cancer cell culture medium confirmed a positive, concentration-dependent fluorescence response, establishing a usable dynamic range. Compared to existing technologies, this platform enables fast, simple-to-implement EV quantification using minimal sample volume and equipment. The simplicity and scalability of the method offer strong potential for use in clinical diagnostics and EV research applications.

Indexed as

Biosensing TechniquesExtracellular VesiclesCell Line, TumorFluorescent DyesHumansImmunoassayOvarian NeoplasmsPaperFluorescent Dyesbiosensor stripEV concentrationextracellular vesicles (EVs)fluorescence detectionpaper-based immunoassay

Identifiers

PMID40422033
PMCPMC12109735

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

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.