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Dye-free spectrophotometric measurement of nucleic acid-to-protein ratio for cell-selective extracellular vesicle discrimination.

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机构: [1]Department of Electrical and Computer Engineering, North Dakota State University, 1411 Centennial Blvd., 101M, Fargo, ND, 58102, USA [2]Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York, NY, 10065, USA [3]School of Biological and Health Systems Engineering, The Biodesign Institute, Arizona State University, 1001 S. McAllister Ave. B 140D, Tempe, AZ, 85287-5001, USA [4]Department of Biochemistry and Molecular Biology, Tulane University School of Medicine, LA, 70112, USA [5]Department of Integrated Traditional Chinese and Western Medicine, West China Hospital of Sichuan University, Shichuan, 610041, China
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关键词: Extracellular vesicles Quality assessment Collective attribute PDAC

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Extracellular vesicles (EVs) can represent a novel source of disease biomarkers, and are under intensive study for their clinical potential. Most EV-based cancer diagnostic studies have focused on establishing EV assays that detect increased expression of a single cancer-associated marker or marker signatures based on multiplex detection of these biomarkers. EV biomarker readouts can be obscured by high background signal leading to false positives, and may markedly differ between analyses due to variation in sample purity during EV isolation. This can obstruct the comparisons among studies and lead to conflicting conclusions. This work reports that the nucleic acid to protein UV absorption ratio of an EV is a cell-specific EV characteristic. This EV collective attribute can be measured at low-cost to discriminate EVs derived from malignant and non-malignant cells rather than employing single markers that may be cancer- or subtype-specific. Our work also highlighted the application for accessing purity in EV preparations irrelevant to EV yield. It can be employed to distinguish from patients with and without malignant disease upon analysis of EVs isolated from their serum samples. Copyright © 2021 Elsevier B.V. All rights reserved.

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出版当年[2021]版:
大类 | 1 区 工程技术
小类 | 1 区 生物物理 1 区 生物工程与应用微生物 1 区 分析化学 1 区 电化学 2 区 纳米科技
最新[2023]版:
大类 | 1 区 生物学
小类 | 1 区 生物物理 1 区 生物工程与应用微生物 1 区 分析化学 1 区 电化学 2 区 纳米科技
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第一作者机构: [1]Department of Electrical and Computer Engineering, North Dakota State University, 1411 Centennial Blvd., 101M, Fargo, ND, 58102, USA
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