Evidence map›Paper›PMID 41302727›Full record

ArticleMicromachines2025

An Integrated Microfluidic System for One-Stop Multiplexed Exosomal PD-L1 and MMP9 Automated Analysis with Deep Learning Model YOLO.

Yunxing Lu, Wenjing Zhang, Qiang Shi, Jianan Hui, Jieyu Wang, Yiman Song, Xiaoyue Yang

Abstract read
In one paragraph

Article in Micromachines, 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. An integrated microfluidic system for automatic and self-validated analysis of cervical extracellular vesicle markers PD-L1 and ERBB3.Analytical sciences : the international journal of the Japan Society for Analytical Chemistry · 2026
    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

7 authors.

Yunxing LuSchool of Science and Technology, Shanghai Open University, Shanghai 200433, China.
Wenjing ZhangDepartment of Obstetrics and Gynecology, The Second Affiliated Hospital of Soochow University, Suzhou 215000, China.ORCID 0009-0008-9314-9555
Qiang ShiSchool of Science and Technology, Shanghai Open University, Shanghai 200433, China.ORCID 0000-0003-4089-5892
Jianan HuiState Key Laboratory of Transducer Technology, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai 200050, China.
Jieyu WangState Key Laboratory of Transducer Technology, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai 200050, China.
Yiman SongState Key Laboratory of Transducer Technology, Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai 200050, China.
Xiaoyue YangThe International Peace Maternity and Child Health Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200030, China.

Funding

Shanghai Jiao Tong University National Facility for Translational Medicine (Shanghai), Open Research Program Key Project TMSK-2024-120Shanghai Municipality 24XTCX00700Shanghai Science and Technology Innovation Action Plan, Medical Innovation Research Special Project 23Y11901900the Chenguang Program of Shanghai Education Development Foundation and Shanghai Municipal Education Commission 23CGB01the National Key R&D Program of China 2023YFB3210300the National Key R&D Program of China 2023YFB3210302
6 · The paper itself

Abstract

While immune escape and physical invasion are two key pathways in tumor development, traditional methods for analyzing their exosomal markers are often complex and face identification bias. Microfluidic technology offers significant advantages for non-invasive liquid biopsy, particularly in the analysis of tumor progression markers carried by exosomes. Here, we developed an integrated microfluidic system for the sensitive, accurate, totally on-chip exosome isolation and automatic quantification of tumor progression markers PD-L1 and MMP9. This platform leverages microfluidic design principles for efficient sample mixing and monodisperses microbeads for precise analysis, allowing for complete processing within 40 min. The system's high efficiency and precision are further enhanced by a lightweight YOLOv5-based positional migration strategy that automates fluorescence quantification. Validation using four different cell lines demonstrated distinct exosomal protein signatures with a low detection limit of 12.58 particles/μL. This innovative microfluidic chip provides a sensitive and easy-to-handle tool for exosomal marker analysis, holding great potential for cancer identification and personalized therapy guidance in the era of point-of-care testing (POCT).

Indexed as

deep learningexosomesimmune escapeintegrated microfluidic systemphysical invasion

Identifiers

PMID41302727
PMCPMC12654492

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.