Evidence map›Paper›PMID 42773147›Full record

ArticleNature communications2026

iEVIP: a dual-inspired intelligent platform for smart response extracellular vesicle isolation and single-vesicle profiling.

Han Xie, Tucan Chen, Peiyu Yan, Yuqi Fu, Mengcheng Lei, Yuanyuan Liu, Xudong Zhao, Wei Du, Xiaojun Feng, Xin Liu and 3 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Nature communications, 2026. 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

13 authors.

Han Xie *The Key Laboratory for Biomedical Photonics of MOE at Wuhan National Laboratory for Optoelectronics-Hubei Bioinformatics & Molecular Imaging Key Laboratory, Systems Biology Theme, Department of Biomedical Engineering, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, China.
Tucan Chen *The Key Laboratory for Biomedical Photonics of MOE at Wuhan National Laboratory for Optoelectronics-Hubei Bioinformatics & Molecular Imaging Key Laboratory, Systems Biology Theme, Department of Biomedical Engineering, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, China.
Peiyu YanThe Key Laboratory for Biomedical Photonics of MOE at Wuhan National Laboratory for Optoelectronics-Hubei Bioinformatics & Molecular Imaging Key Laboratory, Systems Biology Theme, Department of Biomedical Engineering, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, China.
Yuqi FuThe Key Laboratory for Biomedical Photonics of MOE at Wuhan National Laboratory for Optoelectronics-Hubei Bioinformatics & Molecular Imaging Key Laboratory, Systems Biology Theme, Department of Biomedical Engineering, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, China.ORCID http://orcid.org/0009-0006-4906-1236
Mengcheng LeiThe Key Laboratory for Biomedical Photonics of MOE at Wuhan National Laboratory for Optoelectronics-Hubei Bioinformatics & Molecular Imaging Key Laboratory, Systems Biology Theme, Department of Biomedical Engineering, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, China.
Yuanyuan LiuThe Key Laboratory for Biomedical Photonics of MOE at Wuhan National Laboratory for Optoelectronics-Hubei Bioinformatics & Molecular Imaging Key Laboratory, Systems Biology Theme, Department of Biomedical Engineering, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, China.
Xudong ZhaoThe Key Laboratory for Biomedical Photonics of MOE at Wuhan National Laboratory for Optoelectronics-Hubei Bioinformatics & Molecular Imaging Key Laboratory, Systems Biology Theme, Department of Biomedical Engineering, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, China.
Wei DuThe Key Laboratory for Biomedical Photonics of MOE at Wuhan National Laboratory for Optoelectronics-Hubei Bioinformatics & Molecular Imaging Key Laboratory, Systems Biology Theme, Department of Biomedical Engineering, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, China.
Xiaojun FengThe Key Laboratory for Biomedical Photonics of MOE at Wuhan National Laboratory for Optoelectronics-Hubei Bioinformatics & Molecular Imaging Key Laboratory, Systems Biology Theme, Department of Biomedical Engineering, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, China.
Xin LiuThe Key Laboratory for Biomedical Photonics of MOE at Wuhan National Laboratory for Optoelectronics-Hubei Bioinformatics & Molecular Imaging Key Laboratory, Systems Biology Theme, Department of Biomedical Engineering, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, China.ORCID http://orcid.org/0000-0003-2464-6458
Yiwei LiThe Key Laboratory for Biomedical Photonics of MOE at Wuhan National Laboratory for Optoelectronics-Hubei Bioinformatics & Molecular Imaging Key Laboratory, Systems Biology Theme, Department of Biomedical Engineering, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, China. yiweili@hust.edu.cn.
Peng ChenThe Key Laboratory for Biomedical Photonics of MOE at Wuhan National Laboratory for Optoelectronics-Hubei Bioinformatics & Molecular Imaging Key Laboratory, Systems Biology Theme, Department of Biomedical Engineering, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, China. gwchenpeng@mail.hust.edu.cn.
Bi-Feng LiuThe Key Laboratory for Biomedical Photonics of MOE at Wuhan National Laboratory for Optoelectronics-Hubei Bioinformatics & Molecular Imaging Key Laboratory, Systems Biology Theme, Department of Biomedical Engineering, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, China. bfliu@mail.hust.edu.cn.ORCID http://orcid.org/0000-0002-2135-0873

Funding

National Natural Science Foundation of China (National Science Foundation of China) 12102142National Natural Science Foundation of China (National Science Foundation of China) 22574058National Natural Science Foundation of China (National Science Foundation of China) 32171248National Natural Science Foundation of China (National Science Foundation of China) 32571640
6 · The paper itself

Abstract

Extracellular vesicles (EVs) are promising non-invasive biomarkers for early cancer detection, yet clinical translation is limited by membrane fouling during isolation and vesicle aggregation during single-vesicle imaging. Here, iEVIP (intelligent extracellular vesicle isolation and profiling), an integrated dual-inspired platform, combines intelligent pulsatile filtration, blood-smear-inspired nanoscale organization and machine-learning-based classification. Real-time transmembrane-pressure monitoring triggers back-aspiration pulses upon membrane fouling, promoting membrane regeneration and stable EV recovery from plasma. A wettability-assisted nano-smear array reduces aggregation and fluorescence overlap, enabling high-throughput multiplexed single-EV imaging. iEVIP achieves 95.32% classification accuracy for cell-line-derived EVs and up to 80.37% in exploratory clinical cohorts using random forest algorithm. By bridging macroscopic engineering principles with nanoscale bioanalysis, iEVIP provides a scalable framework for high-throughput single-EV analysis and exploratory clinical sample classification. However, the limited cohort size and absence of cross-center external validation constrain generalizability, and larger independent cohorts are needed to establish diagnostic robustness and clinical applicability.

Indexed as

Extracellular VesiclesCell Line, TumorFiltrationHumansMachine Learning

Identifiers

PMID42773147
PMCPMC13598092

What OpenQuestion holds

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Read underepoch 390

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.