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Advances and future trends in the detection of beta-amyloid: A comprehensive review

淀粉样蛋白(真菌学) BETA(编程语言) 计算机科学 医学 计算生物学 数据科学 生物 病理 程序设计语言
作者
Atri Ganguly,Srivalliputtur Sarath Babu,Sumanta Ghosh,Ravichandiran Velyutham,Govinda Kapusetti
出处
期刊:Medical Engineering & Physics [Elsevier BV]
卷期号:135 (1): 104269-104269 被引量:7
标识
DOI:10.1016/j.medengphy.2024.104269
摘要

• A comprehensive exploration of CSF-based techniques and imaging modalities providing a holistic view of detection of Aβ and its pathology. Fluorescent Probes Utility: • An in-depth discussion on diverse fluorescent probes, emphasizing their specific utilities in the nuanced context of Aβ detection. • A thorough examination of colorimetric assays, uncovering their nuances and diverse applications with a range of dyes. • Detailed analysis of optical, mass spectrometric, and electrochemical techniques for detection and quantification of Aβ. • The review not only explores current methodologies but also paves the way for futuristic technologies, presenting alternatives for the detection of Aβ. The neurodegenerative condition known as Alzheimer's disease is typified by the build-up of beta-amyloid plaques within the brain. The timely and precise identification of beta-amyloid is essential for understanding disease progression and developing effective therapeutic interventions. This comprehensive review explores the diverse landscape of beta-amyloid detection methods, ranging from traditional immunoassays to cutting-edge technologies. The review critically examines the strengths and limitations of established techniques such as ELISA, PET, and MRI, providing insights into their roles in research and clinical settings. Emerging technologies, including electrochemical methods, nanotechnology, fluorescence techniques, point-of-care devices, and machine learning integration, are thoroughly discussed, emphasizing recent breakthroughs and their potential for revolutionizing beta-amyloid detection. Furthermore, the review delves into the challenges associated with current detection methods, such as sensitivity, specificity, and accessibility. By synthesizing knowledge from multidisciplinary approaches, this review aims to guide researchers, clinicians, and policymakers in navigating the complex landscape of beta-amyloid detection, ultimately contributing to advancements in Alzheimer's disease diagnostics and therapeutics.
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