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一种通过偏最小二乘判别分析利用整个酵母细胞的红外光谱数据快速区分在碳氮限制条件下生长的酵母细胞的方法。

A rapid method for the differentiation of yeast cells grown under carbon and nitrogen-limited conditions by means of partial least squares discriminant analysis employing infrared micro-spectroscopic data of entire yeast cells.

机构信息

Department of Analytical Chemistry, University of Valencia, Edifici Jeroni Muñoz, 50th Dr. Moliner, E-46100 Burjassot, Spain.

出版信息

Talanta. 2012 Sep 15;99(20-10):566-73. doi: 10.1016/j.talanta.2012.06.036. Epub 2012 Jun 20.

Abstract

This paper shows the ease of application and usefulness of mid-IR measurements for the investigation of orthogonal cell states on the example of the analysis of Pichia pastoris cells. A rapid method for the discrimination of entire yeast cells grown under carbon and nitrogen-limited conditions based on the direct acquisition of mid-IR spectra and partial least squares discriminant analysis (PLS-DA) is described. The obtained PLS-DA model was extensively validated employing two different validation strategies: (i) statistical validation employing a method based on permutation testing and (ii) external validation splitting the available data into two independent sub-sets. The Variable Importance in Projection scores of the PLS-DA model provided deeper insight into the differences between the two investigated states. Hence, we demonstrate the feasibility of a method which uses IR spectra from intact cells that may be employed in a second step as an in-line tool in process development and process control along Quality by Design principles.

摘要

本文展示了中红外测量在正交细胞状态研究中的应用便利性和实用性,以毕赤酵母细胞分析为例。本文描述了一种基于中红外光谱直接采集和偏最小二乘判别分析(PLS-DA)的快速方法,用于区分在碳氮限制条件下生长的整个酵母细胞。通过两种不同的验证策略(i)基于置换检验的统计验证和(ii)将可用数据分为两个独立子集的外部验证,对所获得的 PLS-DA 模型进行了广泛验证。PLS-DA 模型的变量重要性投影得分深入了解了两种研究状态之间的差异。因此,我们证明了一种使用完整细胞的 IR 光谱的方法的可行性,该方法可以在第二步中作为过程开发和基于质量设计原则的过程控制中的在线工具使用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2fcb/3460240/14308d71ce11/fx1.jpg

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