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荧光成像前沿:疾病生物标志物检测工具

Frontiers in fluorescence imaging: tools for the sensing of disease biomarkers.

作者信息

Yang Lei, Hou Hongwei, Li Jinghong

机构信息

Department of Chemistry, Center for Bioanalytical Chemistry, Key Laboratory of Bioorganic Phosphorus Chemistry & Chemical Biology, Tsinghua University, Beijing 100084, China.

Beijing Life Science Academy, Beijing 102209, China.

出版信息

J Mater Chem B. 2025 Jan 22;13(4):1133-1158. doi: 10.1039/d4tb01867b.

Abstract

Fluorescence imaging has been recognized as a powerful tool for the real-time detection and specific imaging of biomarkers within living systems, which is crucial for early diagnosis and treatment evaluation of major diseases. Over the years, significant advancements in this field have been achieved, particularly with the development of novel fluorescent probes and advanced imaging technologies such as NIR-II imaging, super-resolution imaging, and 3D imaging. These technologies have enabled deeper tissue penetration, higher image contrast, and more accurate detection of disease-related biomarkers. Despite these advancements, challenges such as improving probe specificity, enhancing imaging depth and resolution, and optimizing signal-to-noise ratios still remain. The emergence of artificial intelligence (AI) has injected new vitality into the designs and performances of fluorescent probes, offering new tools for more precise disease diagnosis. This review will not only discuss chemical modifications of classic fluorophores and visualization of various biomarkers including metal ions, reactive species, and enzymes, but also share some breakthroughs in AI-driven fluorescence imaging, aiming to provide a comprehensive understanding of these advancements. Future prospects of fluorescence imaging for biomarkers including the potential impact of AI in this rapidly evolving field are also highlighted.

摘要

荧光成像已被公认为是一种用于实时检测和对生物系统内生物标志物进行特异性成像的强大工具,这对于重大疾病的早期诊断和治疗评估至关重要。多年来,该领域取得了重大进展,特别是随着新型荧光探针以及近红外二区成像、超分辨率成像和三维成像等先进成像技术的发展。这些技术实现了更深的组织穿透、更高的图像对比度以及对疾病相关生物标志物更准确的检测。尽管取得了这些进展,但诸如提高探针特异性、增强成像深度和分辨率以及优化信噪比等挑战仍然存在。人工智能(AI)的出现为荧光探针的设计和性能注入了新的活力,为更精确的疾病诊断提供了新工具。本综述不仅将讨论经典荧光团的化学修饰以及包括金属离子、活性物种和酶在内的各种生物标志物的可视化,还将分享人工智能驱动的荧光成像方面的一些突破,旨在全面了解这些进展。还强调了生物标志物荧光成像的未来前景,包括人工智能在这个快速发展的领域中的潜在影响。

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