An integrated microfluidic system for automatic and self-validated analysis of cervical extracellular vesicle markers PD-L1 and ERBB3
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Le résumé fourni par la source
Abstract The early and precise diagnosis of gynecological malignancies, such as cervical cancer, is critical for improving patient treatments. Extracellular vesicles (EVs), such as exosomes, which carry molecular signals from their parental cells, offer a promising method for non-invasive liquid biopsy, however, conventional detection methods are often complex, high in reagent consumption, and susceptible to environmental fluctuations. To address this, we present an integrated, self-validated microfluidic system for the rapid, on-chip isolation and multiplexed identification of the gynecological EV markers PD-L1 and ERBB3. The chip achieved simultaneous on-chip processing of test and positive samples for parallel analysis within 1 h, enabling synchronous detection under the same conditions and thereby significantly enhancing the reliability of the assay. Additionally, a deep learning YOLOv8-based self-validated detection strategy facilitates automated and precise fluorescence identification. Validation with four cell lines (SiHa, C33A, HeLa, and H8) revealed remarkable EV protein signatures, achieving a limit of detection (LOD) of 15.56 particles/μL. This platform provides an integrated tool for sensitive and precise EV marker analysis, holding prospective potential for the early screening and personalized therapy guidance of gynecological tumor detection. Graphical abstract Integrated analytical system for one-stop and self-validated exosome complex formation and multiplex tumor fingerprint analysis by deep learning. Exosome samples were immuno-isolated and labeled with probes, followed by monodispersed among the particular arrays for deep learning model YOLOv8-based positional migration and identification automatically. Four kinds of samples were measured and remarkable differences were acquired, the two tumor progressions: immune evasion and proliferative signaling were revealed. The integrated system is pospective for sensitive, easy-handing and automatic exosome markers analysis in POCT field.
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Le contrôle bibliographique ouvert
DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.
- Titre Crossref
- An integrated microfluidic system for automatic and self-validated analysis of cervical extracellular vesicle markers PD-L1 and ERBB3
- Date Crossref
- 16/03/2026
- Éditeur
- Springer Science and Business Media LLC
- Type
- journal-article
Ce recoupement confirme des métadonnées liées au DOI. Il ne confirme ni la méthode ni les conclusions de l’étude, et il ne compte pas comme une seconde source scientifique indépendante.
Où se fait cette recherche
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Shanghai Open University pays non établi dans la noticeUniversité ou école supérieure
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Shanghai Jiao Tong University pays non établi dans la noticeUniversité ou école supérieure
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International Peace Maternity & Child Health Hospital pays non établi dans la noticeÉtablissement de santé
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Soochow University Department of Obstetrics and Gynecology pays non établi dans la noticeUniversité ou école supérieure
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Second Affiliated Hospital of Soochow University pays non établi dans la noticeÉtablissement de santé
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Chinese Academy of Sciences pays non établi dans la noticeOrganisme public
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State Key Laboratory of Transducer Technology pays non établi dans la noticeOrganisme public
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Shanghai Institute of Microsystem and Information Technology pays non établi dans la noticeStructure de recherche
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Dalian Medical University pays non établi dans la noticeUniversité ou école supérieure
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School of Science and Technology pays non établi dans la noticeUniversité ou école supérieure
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School of Medicine The International Peace Maternity and Child Health Hospital pays non établi dans la noticeUniversité ou école supérieure
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Shanghai Frontier Innovation Research Institute pays non établi dans la noticeStructure de recherche
Shanghai Open University, Shanghai Jiao Tong University et International Peace Maternity & Child Health Hospital, avec 9 autres affiliations.
Une affiliation ne permet pas de déduire la nationalité d’un auteur.