Evidence map›Paper›PMID 40331605›Full record

ReviewSe pu = Chinese journal of chromatography2025

[Progress and prospect of separation and analysis of single-cell and single-particle exosomes].

Ai-Xiang Bu, Guang-Yao Wu, Liang-Hai Hu

Abstract readReviewEnglish Abstract
In one paragraph

Review in Se pu = Chinese journal of chromatography, 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. Review
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.

Ai-Xiang BuCenter for Supramolecular Chemical Biology, State Key Laboratory of Supramolecular Structure and Materials, Jilin University, Changchun 130023, China.
Guang-Yao WuCenter for Supramolecular Chemical Biology, State Key Laboratory of Supramolecular Structure and Materials, Jilin University, Changchun 130023, China.
Liang-Hai HuCenter for Supramolecular Chemical Biology, State Key Laboratory of Supramolecular Structure and Materials, Jilin University, Changchun 130023, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Exosomes are nanoscale vesicles secreted by cells and are encapsulated in lipid bilayers. They play crucial roles in cell communication and are involved in a variety of physiological and pathological processes, including immune regulation, angiogenesis, and tumor initiation and metastasis. Exosomes carry a variety of biomolecules from maternal cells and are therefore important vehicles for discovering disease markers. Traditional detection methods only provide average cell-population information for a given sample and cannot establish clear relationships between the biological functions of exosomes and subtype owing to the significant heterogeneity associated with exosomes from different cell subsets. Therefore, characterizing exosomes at the single-cell and single-particle levels requires exosome specificities to be further explored and the characteristics of various exosome subtypes to be distinguished. Commonly used single-particle exosome characterization technologies include flow cytometry, super-resolution microscopy, atomic force microscopy, surface-enhanced Raman spectroscopy, proximity barcoding assay and MS. In this paper, we summarize recent advances in the separation and characterization of single-cell exosomes based on microfluidics and provide future applications prospects for emerging technologies (such as Olink proteomics, click chemistry, and molecular imprinting) for studying single-cell and single-particle exosomes.

Indexed as

ExosomesSingle-Cell AnalysisAnimalsHumansmicrofluidicsreviewseparation and analysissingle-cell exosomessingle-particle exosomes

Identifiers

PMID40331605
PMCPMC12059993

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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.