当前位置: X-MOL 学术Expert Rev. Mol. Diagn. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
A look into the use of Raman spectroscopy for brain and breast cancer diagnostics: linear and non-linear optics in cancer research as a gateway to tumor cell identity.
Expert Review of Molecular Diagnostics ( IF 3.9 ) Pub Date : 2020-02-03 , DOI: 10.1080/14737159.2020.1724092
Halina Abramczyk 1 , Beata Brozek-Pluska 1 , Arkadiusz Jarota 1 , Jakub Surmacki 1 , Anna Imiela 1 , Monika Kopec 1
Affiliation  

Introduction: Currently, intensely developing of linear and non-linear optical methods for cancer detection provides a valuable tool to improve sensitivity and specificity. One of the main reasons for insufficient progress in cancer diagnostics is related to the fact that most cancer types are not only heterogeneous in their genetic composition but also reside in varying microenvironments and interact with different cell types. Until now, no technology has been fully proven for effective detecting of invasive cancer, which infiltrating the extracellular matrix.Areas covered: This review investigates the current status of Raman spectroscopy and Raman imaging for brain and breast cancer diagnostics. Moreover, the review provides a comprehensive overview of the applicability of atomic force microscopy (AFM), linear and non-linear optics in cancer research as a gateway to tumor cell identity.Expert commentary: A combination of linear and non-linear optics, particularly Raman-driven methods, has many additional advantages to identify alterations in cancer cells that are crucial for their proliferation and that distinguish them from normal cells.

中文翻译:


探讨拉曼光谱在脑癌和乳腺癌诊断中的应用:癌症研究中的线性和非线性光学作为肿瘤细胞识别的途径。



简介:目前,用于癌症检测的线性和非线性光学方法的大力发展为提高灵敏度和特异性提供了宝贵的工具。癌症诊断进展不足的主要原因之一与大多数癌症类型不仅在遗传组成上具有异质性,而且存在于不同的微环境中并与不同的细胞类型相互作用。到目前为止,还没有任何技术被充分证明可以有效检测浸润细胞外基质的侵袭性癌症。涵盖领域:本综述调查了用于脑癌和乳腺癌诊断的拉曼光谱和拉曼成像的现状。此外,该综述还全面概述了原子力显微镜 (AFM)、线性和非线性光学在癌症研究中作为肿瘤细胞识别途径的适用性。专家评论:线性和非线性光学的组合,特别是拉曼驱动的方法具有许多额外的优势,可以识别癌细胞的变化,这些变化对于癌细胞的增殖至关重要,并将其与正常细胞区分开来。
更新日期:2020-02-03
down
wechat
bug