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基于其红外光谱的计算分析来区分细胞类型或群体。

Distinguishing cell types or populations based on the computational analysis of their infrared spectra.

机构信息

Centre for Biophotonics, Lancaster Environment Centre, Lancaster University, Lancaster, UK.

出版信息

Nat Protoc. 2010 Nov;5(11):1748-60. doi: 10.1038/nprot.2010.133. Epub 2010 Oct 7.

Abstract

Infrared (IR) spectroscopy of intact cells results in a fingerprint of their biochemistry in the form of an IR spectrum; this has given rise to the new field of biospectroscopy. This protocol describes sample preparation (a tissue section or cytology specimen), the application of IR spectroscopy tools, and computational analysis. Experimental considerations include optimization of specimen preparation, objective acquisition of a sufficient number of spectra, linking of the derived spectra with tissue architecture or cell type, and computational analysis. The preparation of multiple specimens (up to 50) takes 8 h; the interrogation of a tissue section can take up to 6 h (∼100 spectra); and cytology analysis (n = 50, 10 spectra per specimen) takes 14 h. IR spectroscopy generates complex data sets and analyses are best when initially based on a multivariate approach (principal component analysis with or without linear discriminant analysis). This results in the identification of class clustering as well as class-specific chemical entities.

摘要

红外(IR)光谱学对完整细胞的分析产生了它们生物化学的指纹图谱,这形成了生物光谱学这一新领域。本方案描述了样品制备(组织切片或细胞学标本)、IR 光谱学工具的应用和计算分析。实验考虑因素包括优化标本制备、客观获取足够数量的光谱、将所得光谱与组织结构或细胞类型相关联以及计算分析。多达 50 个标本的制备需要 8 小时;组织切片的检测时间可达 6 小时(约 100 个光谱);细胞学分析(n=50,每个标本 10 个光谱)需要 14 小时。IR 光谱学产生复杂的数据集,当最初基于多变量方法(带或不带线性判别分析的主成分分析)进行分析时,结果最佳。这导致了类聚类以及类特异性化学实体的识别。

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