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Bacterial identification in real samples by means of micro-Raman spectroscopy

机译:显微拉曼光谱法鉴定真实样品中的细菌

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Pathogen detection is essential without time delay especially for severe diseases like sepsis. Here, the survival rate is dependent on a prompt antibiosis. For sepsis three hours after the onset of shock the survival rate of the patient drops below 60 %. Unfortunately, the results from standard diagnosis methods like PCR or microbiology can normally be received after 12 or 36 h, respectively. Therefore diagnosis methods which require less cultivation or even no cultivation at all have to be established for medical diagnosis. Here, Raman spectroscopy, as a vibrational spectroscopic method, is a very sensitive and selective approach and monitors the biochemical composition of the investigated sample. Applying micro-Raman spectroscopy allows for a spatial resolution below 1 μm and is therefore in the size range of bacteria. Raman spectra of bacteria depend on the physiological status. Therefore, the databases require the inclusion of the necessary environmental parameters such as temperature, pH, nutrition, etc. Such large databases therefore require a specialized chemometric approach, since the variation between different strains is small. In this contribution we will demonstrate the capability of Raman spectroscopy to identify pathogens without cultivation even from real environmental or medical samples.
机译:病原体检测是必不可少的,没有时间延迟,尤其是对于败血症等严重疾病。在此,存活率取决于及时的抗生作用。在休克发作后三小时的败血症中,患者的存活率降至60%以下。不幸的是,标准诊断方法(如PCR或微生物学)的结果通常可以分别在12或36小时后收到。因此,必须建立需要较少培养甚至根本不需要培养的诊断方法以进行医学诊断。在这里,拉曼光谱法是一种振动光谱法,是一种非常灵敏和选择性的方法,可以监测所研究样品的生化成分。应用微拉曼光谱法可实现低于1μm的空间分辨率,因此在细菌的大小范围内。细菌的拉曼光谱取决于生理状态。因此,数据库要求包括必要的环境参数,例如温度,pH,营养等。由于不同菌株之间的差异很小,因此此类大型数据库需要专用的化学计量学方法。在这项贡献中,我们将证明拉曼光谱技术能够识别病原体而无需从真实环境或医学样本中进行培养的能力。

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