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用于细菌菌落的多光谱光散射传感器的研制。

Development of a multispectral light-scatter sensor for bacterial colonies.

作者信息

Kim Huisung, Rajwa Bartek, Bhunia Arun K, Robinson J Paul, Bae Euiwon

机构信息

Applied Optics Laboratory, School of Mechanical Engineering, Purdue University, West Lafayette, IN 47907, USA.

Department of Basic Medical Sciences, Purdue University, West Lafayette, IN 47907, USA.

出版信息

J Biophotonics. 2017 May;10(5):634-644. doi: 10.1002/jbio.201500338. Epub 2016 Jul 14.

Abstract

We report a multispectral elastic-light-scatter instrument that can simultaneously detect three-wavelength scatter patterns and associated optical densities from individual bacterial colonies, overcoming the limits of the single-wavelength predecessor. Absorption measurements on liquid bacterial samples revealed that the spectroscopic information can indeed contribute to sample differentiability. New optical components, including a pellicle beam splitter and an optical cage system, were utilized for robust acquisition of multispectral images. Four different genera and seven shiga toxin producing E. coli serovars were analyzed; the acquired images showed differences in scattering characteristics among the tested organisms. In addition, colony-based spectral optical-density information was also collected. The optical model, which was developed using diffraction theory, correctly predicted wavelength-related differences in scatter patterns, and was matched with the experimental results. Scatter-pattern classification was performed using pseudo-Zernike (GPZ) polynomials/moments by combining the features collected at all three wavelengths and selecting the best features via a random-forest method. The data demonstrate that the selected features provide better classification rates than the same number of features from any single wavelength. Three wavelength-merged scatter pattern from E. coli.

摘要

我们报道了一种多光谱弹性光散射仪器,它能够同时检测单个细菌菌落的三波长散射模式及相关光密度,克服了单波长前身仪器的局限性。对液体细菌样本的吸收测量表明,光谱信息确实有助于样本的区分。新的光学组件,包括一个薄膜分束器和一个光学笼系统,被用于稳健地采集多光谱图像。对四种不同属以及七种产志贺毒素大肠杆菌血清型进行了分析;所采集的图像显示了受试生物体之间散射特性的差异。此外,还收集了基于菌落的光谱光密度信息。利用衍射理论开发的光学模型正确地预测了散射模式中与波长相关的差异,并与实验结果相匹配。通过结合在所有三个波长处收集的特征并通过随机森林方法选择最佳特征,使用伪泽尼克(GPZ)多项式/矩进行散射模式分类。数据表明,所选特征比来自任何单个波长的相同数量的特征提供了更好的分类率。大肠杆菌的三波长合并散射模式。

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