Evidence map›Paper›PMID 42338032›Full record

ArticleJournal of extracellular vesicles2026

Label-Free Clustering Analysis Platform Drives Cascaded Workflow for Scalable Production of Therapeutic Extracellular Vesicles.

Jing Zhou, Ping Chen, Xin Chen, Xu Xiao, Haonan Di, Yunyun Hu, Yarong Zhen, Xiaomei Yan

Abstract read
In one paragraph

Article in Journal of extracellular vesicles, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

8 authors.

Jing ZhouDiscipline of Intelligent Instrument and Equipment, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen, Fujian, China.
Ping ChenDepartment of Chemical Biology, MOE Key Laboratory of Spectrochemical Analysis & Instrumentation, Key Laboratory for Chemical Biology of Fujian Province, State Key Laboratory of Physical Chemistry of Solid Surfaces, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen, Fujian, China.
Xin ChenDepartment of Chemical Biology, MOE Key Laboratory of Spectrochemical Analysis & Instrumentation, Key Laboratory for Chemical Biology of Fujian Province, State Key Laboratory of Physical Chemistry of Solid Surfaces, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen, Fujian, China.
Xu XiaoDepartment of Chemical Biology, MOE Key Laboratory of Spectrochemical Analysis & Instrumentation, Key Laboratory for Chemical Biology of Fujian Province, State Key Laboratory of Physical Chemistry of Solid Surfaces, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen, Fujian, China.
Haonan DiDepartment of Chemical Biology, MOE Key Laboratory of Spectrochemical Analysis & Instrumentation, Key Laboratory for Chemical Biology of Fujian Province, State Key Laboratory of Physical Chemistry of Solid Surfaces, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen, Fujian, China.
Yunyun HuDepartment of Chemical Biology, MOE Key Laboratory of Spectrochemical Analysis & Instrumentation, Key Laboratory for Chemical Biology of Fujian Province, State Key Laboratory of Physical Chemistry of Solid Surfaces, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen, Fujian, China.
Yarong ZhenDepartment of Plastic Surgery, Zhongshan Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, Fujian, China.
Xiaomei YanDiscipline of Intelligent Instrument and Equipment, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen, Fujian, China.ORCID https://orcid.org/0000-0002-7482-6863

Funding

National Key R&D Program of China 2021YFA0909400National Key R&D Program of China 2024YFA1108700National Natural Science Foundation of China 21934004National Natural Science Foundation of China 32450337
6 · The paper itself

Abstract

Extracellular vesicles (EVs) have emerged as highly promising natural nanomedicines and nanocarriers, holding transformative potential for the treatment of various diseases. However, the lack of rapid and comprehensive characterization techniques for EV preparation analysis, coupled with the absence of efficient quality control methods, significantly hinders process optimization and large-scale production. To address these challenges, we developed a label-free clustering analysis (LFCA) platform that integrates nano-flow cytometry for particle size distribution analysis with a clustering algorithm to deconvolute EV subpopulations and distinguish them from impurities. This platform enables the rapid quantification of EV component distribution and composition within 5 min using minimal sample input. Leveraging the high-throughput capabilities of LFCA, we established a cascaded workflow incorporating a microcarrier-based 3D culture system, a custom tangential flow filtration device, and multimodal size exclusion chromatography for EV preparation from adipose mesenchymal stem cells. This approach achieves a 4-fold increase in EV yield compared to ultracentrifugation while maintaining comparable purity and preserving EV integrity. Critically, the resulting EVs exhibited enhanced functional potency in pro-angiogenic and anti-inflammatory assays, confirming the clinical relevance of our optimized production system. These advancements provide a scalable solution for EV production, paving the way for clinical applications.

Indexed as

Extracellular VesiclesMesenchymal Stem CellsCluster AnalysisClustering AlgorithmsFlow CytometryHumansParticle SizeWorkflowlabel‐free clustering analysis algorithmnano‐flow cytometrytangential flow filtration devicetherapeutic extracellular vesicles

Identifiers

PMID42338032
PMCPMC13291197

What OpenQuestion holds

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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.