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中文摘要
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项目摘要/摘要 细胞外小泡(EV)是一种由大多数细胞类型分泌的小的脂质双层颗粒,它包裹着 生物分子,包括起源于细胞的脂类、蛋白质和核酸。肠道病毒衍生生物标志物的特征分析 为各种疾病的诊断提供了一种很有前途的方法。然而,主要的挑战之一是 电动汽车的研究和应用缺乏一种可靠的方法来有效地分离电动汽车及其 来自复杂生物体液的亚群。这一领域的研究人员工作流程繁琐,处理时间长 时间长、成本高、电动汽车质量差。为了克服这些挑战,WellSIM在这个第二阶段的项目中提出, 它建立在我们的第一阶段项目产生的有希望的结果的基础上,以完成标签的开发- 游离胞外囊泡自动纯化系统(LEAP系统),用于分离总EVS或EV 以非侵入性和成本效益的方式从各种生物体液中分离出不同的亚群。一旦开发出来, 集成的LEAP系统将为电动汽车隔离提供卓越的电动汽车质量、吞吐量和灵活性, 优于超速离心法和其他分离技术。
英文摘要
PROJECT SUMMARY / ABSTRACT Extracellular vesicles (EVs) are small lipid bilayer particles secreted by most cell types, which encapsulates biomolecules including lipids, proteins, and nucleic acids from cells of origin. Profiling of EV-derived biomarkers provides a promising approach for diagnosis of various diseases. However, one of the primary challenges for the research and application of EVs is a lack of a reliable method for efficient isolation of EVs and their subpopulations from complex biofluids. Researchers in this field suffer from tedious workflow, long processing time, high cost, and poor EV quality. To overcome the challenges, WellSIM proposes in this Phase II project, which built upon the promising results generated from our Phase I project, to complete development of a Label- free Extracellular-vesicle Automated Purification System (LEAP System) for isolation of total EVs or EV subpopulations from a variety of biofluids in a non-invasive and cost-effective manner. Once developed, the integrated LEAP System will offer excellent EV quality, throughput, and flexibility for EV isolation that can outperform ultracentrifugation and other isolation techniques.
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EXODOTS for diagnostic evaluation and monitoring of Alzheimer's disease
Link phenotypic characteristics with gene expression profile of single cells at high throughput for drug discovery and cell therapy development
Multi-omics profiling of individual exosomes for their origin-tracing, biomarker discovery, and biological function characterization
Multi-omics profiling of individual exosomes for their origin-tracing, biomarker discovery, and biological function characterization
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