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Tof-sims Pc-dfa Analysis Of Prostate Cancer Cell Lines

机译:前列腺癌细胞系的Tof-sims Pc-dfa分析

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Three closely related cancer cell lines have been analysed with ToF-SIMS using a C_(60)~+ primary ion beam. Principal component-discriminant function analysis (PC-DFA) has been applied for spectral classification. Various spectral pre-processing methods are discussed and assessed for optimum discrimination of this data set. The sum-normalised PC-DFA spectral model produced sensitivities as high as 83.3% and specificities as high as 100% at the 99% confidence limit. At this confidence limit only one errant spectrum was misclassified. The resulting loadings plots suggest that a range of lipid and amino-acid related signals are responsible for the cell line discrimination.
机译:使用ToF-SIMS使用C_(60)〜+初级离子束分析了三种密切相关的癌细胞系。主成分判别函数分析(PC-DFA)已应用于光谱分类。讨论并评估了各种光谱预处理方法,以最佳区分该数据集。总和归一化的PC-DFA光谱模型在99%的置信度下产生的灵敏度高达83.3%,特异性高达100%。在此置信度限制下,只有一个错误频谱被错误分类。所得的负荷图表明,一系列与脂质和氨基酸相关的信号是细胞系识别的原因。

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