首页> 美国卫生研究院文献>Journal of the Royal Society Interface >Discrimination between ricin and sulphur mustard toxicity in vitro using Raman spectroscopy.
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Discrimination between ricin and sulphur mustard toxicity in vitro using Raman spectroscopy.

机译:使用拉曼光谱在体外区分蓖麻毒蛋白和芥菜硫的毒性。

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摘要

A Raman spectroscopy cell-based biosensor has been proposed for rapid detection of toxic agents, identification of the type of toxin and prediction of the concentration used. This technology allows the monitoring of the biochemical properties of living cells over long periods of time by measuring the Raman spectra of the cells non-invasively, rapidly and without use of labels (Notingher et al. 2004 doi:10.1016/j.bios.2004.04.008). Here we show that this technology can be used to distinguish between changes induced in A549 lung cells by the toxin ricin and the chemical warfare agent sulphur mustard. A multivariate model based on principal component analysis (PCA) and linear discriminant analysis (LDA) was used for the analysis of the Raman spectra of the cells. The leave-one-out cross-validation of the PCA-LDA model showed that the damaged cells can be detected with high sensitivity (98.9%) and high specificity (87.7%). High accuracy in identifying the toxic agent was also found: 88.6% for sulphur mustard and 71.4% for ricin. The prediction errors were observed mostly for the ricin treated cells and the cells exposed to the lower concentration of sulphur mustard, as they induced similar biochemical changes, as indicated by cytotoxicity assays. The concentrations of sulphur mustard used were also identified with high accuracy: 93% for 200 microM and 500 microM, and 100% for 1,000 microM. Thus, biological Raman microspectroscopy and PCA-LDA analysis not only distinguishes between viable and damaged cells, but can also discriminate between toxic challenges based on the cellular biochemical and structural changes induced by these agents and the eventual mode of cell death.
机译:已经提出了一种基于拉曼光谱细胞的生物传感器,用于快速检测有毒物质,鉴定毒素类型和预测所用浓度。这项技术可通过无创,快速且不使用标记物测量细胞的拉曼光谱来长时间监测活细胞的生化特性(Notingher et al.2004 doi:10.1016 / j.bios.2004.04 .008)。在这里,我们证明了该技术可用于区分毒素蓖麻毒素和化学战剂硫芥末在A549肺细胞中诱导的变化。基于主成分分析(PCA)和线性判别分析(LDA)的多元模型用于分析细胞的拉曼光谱。 PCA-LDA模型的留一法交叉验证表明,可以高灵敏度(98.9%)和高特异性(87.7%)检测受损细胞。还发现了高准确度的有毒物质识别方法:芥子气为88.6%,蓖麻毒蛋白为71.4%。如细胞毒性试验所示,大多数观察到的蓖麻毒素处理过的细胞以及暴露于较低浓度的硫芥子气的细胞存在预测误差,因为它们诱导了相似的生化变化。还可以高精度地确定所使用的芥菜硫的浓度:200 microM和500 microM为93%,1,000 microM为100%。因此,生物拉曼光谱和PCA-LDA分析不仅可以区分存活的细胞和受损的细胞,而且还可以根据由这些试剂引起的细胞生化和结构变化以及最终的细胞死亡模式来区分毒性挑战。

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