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基于肝脏组织原位傅里叶变换红外光谱成像的潜在结构判别分析建模的正交投影,用于识别变异性来源。

Orthogonal projections to latent structures discriminant analysis modeling on in situ FT-IR spectral imaging of liver tissue for identifying sources of variability.

作者信息

Stenlund Hans, Gorzsás András, Persson Per, Sundberg Björn, Trygg Johan

机构信息

Computational Life Science Cluster (CLIC), KBC, Umeå University, SE-901 87 Umeå, Sweden.

出版信息

Anal Chem. 2008 Sep 15;80(18):6898-906. doi: 10.1021/ac8005318. Epub 2008 Aug 20.

DOI:10.1021/ac8005318
PMID:18714965
Abstract

In this study, the orthogonal projections to latent structures discriminant analysis (OPLS-DA) method was used to assess the in situ chemical composition of two different cell types in mouse liver samples, hepatocytes and erythrocytes. High spatial resolution FT-IR microspectroscopy equipped with a focal plan array (FPA) detector is capable of simultaneously recording over 4000 spectra from 64 x 64 pixels with a maximum spatial resolution of about 5 microm x 5 microm, which allows for the differentiation of individual cells. The main benefit with OPLS-DA lies in the ability to separate predictive variation (between cell type) from variation that is uncorrelated to cell type in order to facilitate understanding of different sources of variation. OPLS-DA was able to differentiate between chemical properties and physical properties (e.g., edge effects). OPLS-DA model interpretation of the chemical features that separated the two cell types clearly highlighted proteins and lipids/bile acids. The modeled variation that was uncorrelated to cell type made up a larger portion of the total variation and displayed strong variability in the amide I region. This could be traced back to a gradient in the high intensity (high-density) areas vs the low intensity areas (close to empty areas) that as a result of normalization had an adverse effect on FT-IR spectral profiles. This highlights that OPLS-DA provides an effective solution to identify different sources of variability, both predictive and uncorrelated, and also facilitates understanding of any sampling, experimental, or preprocessing issues.

摘要

在本研究中,采用潜在结构判别分析的正交投影法(OPLS-DA)来评估小鼠肝脏样本中两种不同细胞类型,即肝细胞和红细胞的原位化学成分。配备焦平面阵列(FPA)探测器的高空间分辨率傅里叶变换红外(FT-IR)显微光谱仪能够同时记录来自64×64像素的4000多个光谱,最大空间分辨率约为5微米×5微米,这使得能够区分单个细胞。OPLS-DA的主要优势在于能够将预测性变异(细胞类型之间)与与细胞类型不相关的变异分开,以便于理解不同的变异来源。OPLS-DA能够区分化学性质和物理性质(例如边缘效应)。对区分两种细胞类型的化学特征的OPLS-DA模型解释清楚地突出了蛋白质和脂质/胆汁酸。与细胞类型不相关的建模变异在总变异中占较大比例,并且在酰胺I区域表现出强烈的变异性。这可以追溯到高强度(高密度)区域与低强度区域(接近空白区域)之间的梯度,由于归一化,这对FT-IR光谱轮廓产生了不利影响。这突出表明,OPLS-DA为识别预测性和不相关的不同变异来源提供了一种有效的解决方案,并且还便于理解任何采样、实验或预处理问题。

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