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从拉曼光谱在神经科学中的研究到诊断应用:过去与展望

From Research to Diagnostic Application of Raman Spectroscopy in Neurosciences: Past and Perspectives.

作者信息

Klamminger Gilbert Georg, Frauenknecht Katrin B M, Mittelbronn Michel, Kleine Borgmann Felix B

机构信息

Saarland University Medical Center and Faculty of Medicine, Homburg, Germany.

National Center of Pathology (NCP), Laboratoire national de santé (LNS), Dudelange, Luxembourg.

出版信息

Free Neuropathol. 2022 Aug 5;3:19. doi: 10.17879/freeneuropathology-2022-4210. eCollection 2022 Jan.

Abstract

In recent years, Raman spectroscopy has been more and more frequently applied to address research questions in neuroscience. As a non-destructive technique based on inelastic scattering of photons, it can be used for a wide spectrum of applications including neurooncological tumor diagnostics or analysis of misfolded protein aggregates involved in neurodegenerative diseases. Progress in the technical development of this method allows for an increasingly detailed analysis of biological samples and may therefore open new fields of applications. The goal of our review is to provide an introduction into Raman scattering, its practical usage and also commonly associated pitfalls. Furthermore, intraoperative assessment of tumor recurrence using Raman based histology images as well as the search for non-invasive ways of diagnosis in neurodegenerative diseases are discussed. Some of the applications mentioned here may serve as a basis and possibly set the course for a future use of the technique in clinical practice. Covering a broad range of content, this overview can serve not only as a quick and accessible reference tool but also provide more in-depth information on a specific subtopic of interest.

摘要

近年来,拉曼光谱越来越频繁地应用于解决神经科学中的研究问题。作为一种基于光子非弹性散射的无损技术,它可用于广泛的应用,包括神经肿瘤学中的肿瘤诊断或对神经退行性疾病中涉及的错误折叠蛋白质聚集体的分析。该方法技术发展的进步使得能够对生物样品进行越来越详细的分析,因此可能开辟新的应用领域。我们综述的目的是介绍拉曼散射、其实际应用以及常见的相关陷阱。此外,还讨论了使用基于拉曼的组织学图像进行肿瘤复发的术中评估以及寻找神经退行性疾病的非侵入性诊断方法。这里提到的一些应用可能作为该技术未来在临床实践中应用的基础,并可能为其设定方向。本综述涵盖广泛内容,不仅可作为快速便捷的参考工具,还能提供关于特定感兴趣子主题的更深入信息。

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