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二维相关光谱法用于 FT-IR、Raman 和 MALDI-TOF MS 高光谱图像的多模式分析,以研究仓鼠脑组织。

Two-Dimensional Correlation Spectroscopy for Multimodal Analysis of FT-IR, Raman, and MALDI-TOF MS Hyperspectral Images with Hamster Brain Tissue.

机构信息

ZBS6 "Proteomics and Spectroscopy", Robert Koch-Institute , Nordufer 20, D-13353 Berlin, Germany.

Department of Materials Science and Engineering, University of Delaware , Newark, Delaware 19716, United States.

出版信息

Anal Chem. 2017 May 2;89(9):5008-5016. doi: 10.1021/acs.analchem.7b00332. Epub 2017 Apr 11.

Abstract

Hyperspectral imaging (HSI) techniques are useful for obtaining very detailed structural and compositional information from biomedical, pharmaceutical, or clinical samples, among others. The informative value of these methods can be further increased through the application of different HSI techniques and joint analysis of the data. However, interpretation and understanding of multimodal HSI have been impeded by difficulties in registration of the different HSI data sets and by the lack of integrative analysis concepts. Here, we introduce two-dimensional correlation spectroscopy (2DCOS) as a novel technique for jointly analyzing HSI data which allows one to obtain deeper insights into the chemistry of complex samples by decrypting auto- and heterospectral correlations that may exist between features of the different HSI data. The general workflow of 2DCOS analysis is demonstrated by HSI examples acquired from cryo-sections of hamster brain tissue using Fourier-transform infrared (FT-IR) microspectroscopy, confocal Raman microspectroscopy (CRM), and matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry. Multimodal hyperspectral image analysis by 2DCOS opens up new opportunities for spectral band assignments and thus the interpretation of structure-spectra and composition-spectra relationships. We foresee wide application potential for describing complex samples in various fields ranging from biomedicine to industrial applications.

摘要

高光谱成像 (HSI) 技术在获取生物医学、制药或临床样本等的非常详细的结构和组成信息方面非常有用。通过应用不同的 HSI 技术和联合分析数据,可以进一步提高这些方法的信息价值。然而,由于不同 HSI 数据集的配准困难以及缺乏综合分析概念,多模态 HSI 的解释和理解受到了阻碍。在这里,我们介绍二维相关光谱 (2DCOS) 作为一种联合分析 HSI 数据的新技术,通过解密不同 HSI 数据之间可能存在的特征之间的自相关和异谱相关,可以深入了解复杂样品的化学性质。通过使用傅里叶变换红外 (FT-IR) 微光谱、共聚焦拉曼微光谱 (CRM) 和基质辅助激光解吸/电离飞行时间 (MALDI-TOF) 质谱仪从仓鼠脑组织的冷冻切片中获取 HSI 示例,展示了 2DCOS 分析的一般工作流程。通过 2DCOS 进行的多模态高光谱图像分析为光谱波段分配以及结构-光谱和组成-光谱关系的解释开辟了新的机会。我们预计,该技术在从生物医学到工业应用等各个领域描述复杂样本方面具有广泛的应用潜力。

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