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However, the efficient isolation of EVs from complex biofluids and ultrasensitive detection of their low-abundance miRNAs encapsulated in EVs remain formidable challenges. To address this, we designed a multifunctional nanoplatform of UiO-66-NH2@Au@MSDC (UAM), which integrates EV capture and in situ miRNA analysis. The initial construction of UiO-66-NH2@Au (UA) provided a high density of thiol-binding sites for the attachment of mercapto (SH)-spacer-DNA-cholesterol (MSDC) probes to form UiO-66-NH2@Au@MSDC (UAM). The abundant cholesterol motifs on these probes subsequently enabled highly efficient EV capture, achieving a recovery rate of 84.8 \u00b1 2.4% under a low centrifugal force of 8000g while preserving EV structural integrity and bioactivity. For the downstream analysis of EVs, we developed an innovative EXPAR-based strategy, termed Y-EXPAR, to address the specificity challenge in detecting miR-1246. The entire detection system employs a temperature-synergistic strategy at 55 \u00b0C, which simultaneously triggers the membrane fusion of EVs with synthetic cationic liposomes (preloaded with Y-EXPAR reagents) and activates the Y-EXPAR. The resulting fusion creates confined nanoreactors that concentrate trace amounts of miR-1246, thereby enabling ultrasensitive detection with detection limits of 1.4 fM for miR-1246 and 22 particles\/\u03bcL for EVs. This integrated platform overcomes key bottlenecks in EV-based liquid biopsy, providing a practical, low-equipment-demand approach for the early diagnosis of GBM and laying a foundation for advancing precision oncology diagnostics.<\/jats:p>","DOI":"10.1021\/acs.analchem.6c01587","type":"journal-article","created":{"date-parts":[[2026,7,22]],"date-time":"2026-07-22T07:50:34Z","timestamp":1784706634000},"page":"22153-22164","source":"Crossref","is-referenced-by-count":0,"title":["Integrated\nLow-Speed Isolation and Ultrasensitive\nIn-Situ Detection of Glioblastoma EVs via UiO-66-NH2@Au\nNanocomposite with Temperature Synergistic Membrane Fusion and Y-EXPAR\nAssay"],"prefix":"10.1021","volume":"98","author":[{"given":"Yan-Yan","family":"Chen","sequence":"first","affiliation":[{"name":"Southern Medical University , , ,","place":["Guangzhou, P. R. 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China, 510515"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zi-Ye","family":"Chen","sequence":"additional","affiliation":[{"name":"Southern Medical University , , ,","place":["Guangzhou, P. R. China, 510515"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shu-Ya","family":"Sheng","sequence":"additional","affiliation":[{"name":"Southern Medical University , , ,","place":["Guangzhou, P. R. China, 510515"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6946-3623","authenticated-orcid":true,"given":"Jun","family":"Chen","sequence":"additional","affiliation":[{"name":"Southern Medical University , , ,","place":["Guangzhou, P. R. 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Clin."},{"issue":"1","key":"2026080408081591300_cit3","doi-asserted-by":"publisher","DOI":"10.1186\/s12943-021-01309-7","article-title":"Coupled\nliquid biopsy and bioinformatics for pancreatic\ncancer early detection and precision prognostication","volume":"20","author":"Hou","year":"2021","journal-title":"Mol. Cancer"},{"issue":"4","key":"2026080408081591300_cit4","doi-asserted-by":"publisher","first-page":"1917","DOI":"10.1021\/acs.chemrev.7b00534","article-title":"New Technologies for Analysis of Extracellular Vesicles","volume":"118","author":"Shao","year":"2018","journal-title":"Chem. Rev."},{"issue":"1","key":"2026080408081591300_cit5","doi-asserted-by":"publisher","DOI":"10.1186\/s12943-022-01505-z","article-title":"Liquid biopsy in lung cancer: significance\nin diagnostics, prediction,\nand treatment monitoring","volume":"21","author":"Li","year":"2022","journal-title":"Mol. 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