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表面增强拉曼光谱用于生物膜形成菌上清液样品的特征分析。

Surface-enhanced Raman spectroscopy for characterization of supernatant samples of biofilm forming bacterial strains.

机构信息

Department of Chemistry, University of Agriculture Faisalabad, Faisalabad 38000, Pakistan.

Department of Chemistry, University of Agriculture Faisalabad, Faisalabad 38000, Pakistan.

出版信息

Spectrochim Acta A Mol Biomol Spectrosc. 2024 Jan 15;305:123414. doi: 10.1016/j.saa.2023.123414. Epub 2023 Sep 15.

Abstract

Staphylococcus epidermidis is considered major cause of nosocomial infections. Its pathogenicity is mainly due to the ability to form biofilms on different surfaces, particularly indwelling medical devices. This bacterium consists of different strains consisting of non, medium and strong biofilm forming ones. Surface-enhanced Raman spectroscopy (SERS) is a powerful analytical technique that can be used to detect and analyze biochemical composition of the supernatant samples of different strains of bacteria including non, medium and strong biofilm forming bacterial strains. SERS is a powerful technique for the robust, reliable, rapid detection and discrimination of bacteria in the form of characteristic SERS spectral features which can be used for detection and classification. SERS is used to differentiate three classes of bacteria with respect to their biofilm forming ability. Silver nanoparticles (Ag NPs) are used as SERS substrate and synthesized with chemical reduction method. Principal component analysis (PCA) and partial least square discriminant analysis (PLS-DA) are used to discriminate SERS spectral data sets of non, medium and strong biofilm forming bacteria. PLS-DA analysis is a multivariate statistical technique that can be used to analyze data from bacterial sets.

摘要

表皮葡萄球菌被认为是医院感染的主要原因。它的致病性主要是由于能够在不同的表面形成生物膜,特别是在留置的医疗设备上。这种细菌由不同的菌株组成,包括非、中、强生物膜形成菌株。表面增强拉曼光谱(SERS)是一种强大的分析技术,可用于检测和分析不同菌株细菌的上清液样本的生化组成,包括非、中、强生物膜形成细菌菌株。SERS 是一种强大的技术,可以通过特征 SERS 光谱特征来对细菌进行稳健、可靠、快速的检测和区分,这些特征可用于检测和分类。SERS 用于区分具有不同生物膜形成能力的三类细菌。银纳米粒子(Ag NPs)被用作 SERS 基底,并通过化学还原法合成。主成分分析(PCA)和偏最小二乘判别分析(PLS-DA)用于区分非、中、强生物膜形成细菌的 SERS 光谱数据集。PLS-DA 分析是一种多元统计技术,可用于分析来自细菌集的数据。

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