Characterizing Extracellular Vesicles from Biological Fluids.

IF 1.2 4区 综合性期刊 Q3 MULTIDISCIPLINARY SCIENCES Jove-Journal of Visualized Experiments Pub Date : 2025-02-28 DOI:10.3791/67699
Brenna S Hefley, Pawan Shrestha, Brenda Vasini, Purnima Sharma, Dimitrios Karamichos
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Abstract

Extracellular vesicles (EVs) are structures that are produced from cells and participate in intercellular communication by transporting biomolecules from one cell to another. EVs have been shown to travel short and far distances in the body and are tissue-specific. EVs are not only found in tissues, but they can also be found in practically all bodily fluids, such as tears, saliva, cerebral spinal fluid, blood, etc. Even though EVs can be collected non-invasively from tears and saliva, only small volumes can be collected at a time, which can cause issues in obtaining enough EVs to analyze proteins. The scanner discussed in this paper is a nanoparticle analyzer that provides a solution to this problem, allowing us to characterize and study the phenotype, size, and total particle count of EVs from as little as 1 µL of biological fluid. This protocol will expand the knowledge of EVs from small volumes of samples that are difficult to extract from patients. This could enhance patient comfort and potentially identify new therapeutic targets for a range of diseases and disorders.

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生物体液中细胞外囊泡的表征
细胞外囊泡(EVs)是由细胞产生的结构,通过将生物分子从一个细胞转运到另一个细胞参与细胞间通讯。研究表明,电动汽车在体内的行驶距离有短有远,而且具有组织特异性。ev不仅存在于组织中,还存在于几乎所有的体液中,如眼泪、唾液、脑脊液、血液等。尽管可以从眼泪和唾液中非侵入性地收集ev,但每次只能收集少量ev,这可能会导致无法获得足够的ev来分析蛋白质。本文讨论的扫描仪是一种纳米颗粒分析仪,它为这个问题提供了解决方案,使我们能够表征和研究ev的表型,大小和总颗粒计数,从1 μ L的生物液中。该方案将从难以从患者身上提取的小批量样本中扩大对ev的认识。这可以提高患者的舒适度,并有可能为一系列疾病和障碍确定新的治疗靶点。
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来源期刊
Jove-Journal of Visualized Experiments
Jove-Journal of Visualized Experiments MULTIDISCIPLINARY SCIENCES-
CiteScore
2.10
自引率
0.00%
发文量
992
期刊介绍: JoVE, the Journal of Visualized Experiments, is the world''s first peer reviewed scientific video journal. Established in 2006, JoVE is devoted to publishing scientific research in a visual format to help researchers overcome two of the biggest challenges facing the scientific research community today; poor reproducibility and the time and labor intensive nature of learning new experimental techniques.
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