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用于即时护理心血管疾病诊断的关键生物标志物——细胞外囊泡的片上实验室无标记分离和检测的先进多功能光谱纳米生物装置

Advanced Multipurpose Spectroscopic Nanobio-Device for Concurrent Lab-on-a-Chip Label-Free Separation and Detection of Extracellular Vesicles as Key-Biomarkers for Point-of-Care Cardiovascular Disease Diagnostics.

作者信息

Buchan Emma, Rickard Jonathan James Stanley, Thomas Mark Robert, Oppenheimer Pola Goldberg

机构信息

School of Chemical Engineering, College of Engineering and Physical Science, University of Birmingham, Birmingham, B15 2TT, UK.

Department of Physics, Cavendish Laboratory, University of Cambridge, JJ Thomson Avenue, Cambridge, CB3 0HE, UK.

出版信息

Adv Healthc Mater. 2025 Aug;14(21):e2500122. doi: 10.1002/adhm.202500122. Epub 2025 Jun 2.

DOI:10.1002/adhm.202500122
PMID:40457637
Abstract

The global aging population presents a major public health challenge, with cardiovascular diseases (CVDs) remaining the leading cause of death worldwide. Often asymptomatic in early-stages, CVDs are frequently undiagnosed until critical events like myocardial infarction or stroke occur. To address this gap, an advanced integrated multipurpose spectroscopic lab-on-a-chip bionano-device has been developed for early CVD detection through extracellular vesicle (EV). EVs, which reflect the molecular state of their originating cells, are separated and analyzed using the combined Raman spectroscopy's molecular specificity with AI-driven classification from clinical CVD biofluids. AIMSpec-LoC unprecedently achieves rapid, label-free, size-based separation of EV subtypes, including small, mid and large EVs from biofluids, whilst preserving EV integrity and eliminating extensive preprocessing. The device enables real-time, multiplexed molecular profiling of EV cargo, identifying CVD-specific biomarkers with sensitivity and specificity >96% and linking these to CVD progression, achieving >97% accuracy in identifying disease-specific molecular fingerprints. This bionanotechnological device generates quantitative barcodes to support prognostic modeling and therapeutic evaluation, providing clinicians with actionable insights for timely-diagnosis and personalized treatment. AIMSpec-LoC platform offers a transformative solution for point-of-care CVD diagnostics, addressing critical unmet needs in cardiovascular medicine, enhancing clinical decision-making, improving patient health and reducing the global burden of CVDs.

摘要

全球人口老龄化对公共卫生构成了重大挑战,心血管疾病(CVD)仍是全球主要死因。CVD在早期通常没有症状,往往在心肌梗死或中风等危急事件发生之前都未被诊断出来。为了填补这一空白,已开发出一种先进的集成多功能光谱芯片实验室生物纳米设备,用于通过细胞外囊泡(EV)进行CVD早期检测。EV反映其来源细胞的分子状态,利用拉曼光谱的分子特异性与临床CVD生物流体的人工智能驱动分类相结合,对EV进行分离和分析。AIMSpec-LoC以前所未有的速度实现了基于大小的EV亚型的快速、无标记分离,包括从生物流体中分离出小、中、大三种EV,同时保持EV的完整性并消除大量预处理。该设备能够对EV货物进行实时、多重分子分析,识别CVD特异性生物标志物,其灵敏度和特异性>96%,并将这些标志物与CVD进展联系起来,在识别疾病特异性分子指纹方面的准确率>97%。这种生物纳米技术设备生成定量条形码,以支持预后建模和治疗评估,为临床医生提供可采取行动的见解,以便及时诊断和个性化治疗。AIMSpec-LoC平台为即时护理CVD诊断提供了变革性解决方案,满足了心血管医学中关键的未满足需求,增强了临床决策,改善了患者健康,并减轻了全球CVD负担。

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Machine learning models for pancreatic cancer diagnosis based on microbiome markers from serum extracellular vesicles.基于血清细胞外囊泡微生物组标志物的胰腺癌诊断机器学习模型
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通过自监督学习从拉曼光谱中鉴定细胞外囊泡。
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Quantitative Proteomics Identifies Proteins Enriched in Large and Small Extracellular Vesicles.定量蛋白质组学鉴定富含大、小细胞外囊泡的蛋白质。
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