Evidence map›Paper›PMID 40936944›Full record

ReviewAPL bioengineering2025

Integrated microfluidic platforms for extracellular vesicles: Separation, detection, and clinical translation.

Yang Dai, Yibo Cui, Jinwen Li, Piwu Li, Xiaowen Huang

Abstract readReview
In one paragraph

Review in APL bioengineering, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

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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.

Yang DaiState Key Laboratory of Biobased Material and Green Papermaking, College of Bioengineering, Qilu University of Technology (Shandong Academy of Sciences), Jinan, Shandong 250353, China.
Yibo CuiState Key Laboratory of Biobased Material and Green Papermaking, College of Bioengineering, Qilu University of Technology (Shandong Academy of Sciences), Jinan, Shandong 250353, China.
Jinwen LiState Key Laboratory of Biobased Material and Green Papermaking, College of Bioengineering, Qilu University of Technology (Shandong Academy of Sciences), Jinan, Shandong 250353, China.
Piwu LiState Key Laboratory of Biobased Material and Green Papermaking, College of Bioengineering, Qilu University of Technology (Shandong Academy of Sciences), Jinan, Shandong 250353, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Extracellular vesicles (EVs), secreted by most living cells, encapsulate a diverse array of bioactive molecules from their parent cells, including proteins and nucleic acids. Recent studies underscore the potential of EVs as advanced biomarkers for the early diagnosis of a variety of clinical diseases. Nevertheless, traditional platforms for EVs separation and detection platforms working alone often involve multiple pieces of equipment and complex, multi-step protocols. This extends processing time and the likelihood of bioanalyte loss and cross-contamination, thereby impeding further EVs research. To date, few studies have effectively combined EVs separation, detection, and analysis functions into a single platform. Integrated microfluidic platforms present a compelling solution by enabling seamless progression from sample to result. These platforms can efficiently combine various separation and detection techniques, simplifying complex workflows and facilitating both efficient EVs separation and high-sensitivity detection. This review concentrates on integrated microfluidic platforms for EVs separation and detection, specifically examining whether the separation and detection units are fully integrated. Recent studies underscore the potential of EVs as promising biomarkers for early-stage diagnosis of diseases, including cancer and neurodegenerative disorders. Recent advances in EVs separation and analysis enable overcoming key translational barriers, accelerating their routine adoption in clinical diagnostics.

Identifiers

PMID40936944
PMCPMC12422758

What OpenQuestion holds

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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.