ArticleACS nano2026
A Rapid Poly(ethylene glycol)-Assisted Magnetic Isolation Approach for High-Throughput Extracellular Vesicle Isolation and Subsequent Biomarker Analysis.
Article in ACS nano, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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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.
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10 authors.
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Abstract
Extracellular vesicles (EVs) are crucial mediators of intercellular communication and have the potential to serve as biomarkers for disease diagnosis and therapeutic monitoring. However, most EV isolation methods often require large sample volumes and specialized instruments or involve trade-offs between purity, yield, cost, and scalability. We developed MagPEG, a workflow that combines poly(ethylene glycol) (PEG)-mediated EV aggregation with magnetic beads to provide a simple, reproducible alternative to ultracentrifugation, size-exclusion chromatography, and commercial precipitation kits. Our optimization experiments clarified the PEG concentration, ionic strength, and bead surface chemistry that collectively influence EV aggregation, capture efficiency, and contaminant coprecipitation, allowing us to define conditions that improve purity while maintaining high recovery. Compared with commonly used methods, MagPEG produced EVs with comparable size distribution, EV markers, and proteomic profiles while relying only on standard laboratory supplies. A key feature of the platform is that EVs and EV-associated DNA, RNA, and proteins can be sequentially extracted from the same bead-bound material, reducing sample loss and hands-on time and enabling multiomic analysis for limited clinical or small animal samples. MagPEG is compatible with downstream applications including proteomics, bead-based assays, and miRNA quantification. When applied to human serum, the method supported high-throughput EV proteomic profiling and enabled the identification of Alzheimer's disease-associated protein signatures, illustrating its utility for biomarker discovery. Overall, our results establish MagPEG as a powerful, rapid, scalable, and high-throughput solution for translational applications in biomarker discovery.
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