Biomarkers spectral subspace for cancer detection

A novel approach to cancer detection in biomarkers spectral subspace (BSS) is proposed. The basis spectra of the subspace spanned by fluorescence spectra of biomarkers are obtained by the Gram-Schmidt method. A support vector machine classifier (SVM) is trained in the subspace. The spectrum of a sample tissue is projected onto and is classified in the subspace. In addition to sensitivity and specificity, the metrics of positive predictivity, Score1, maximum Score1, and accuracy (AC) are employed for performance evaluation. The proposed BSS using SVM is applied to breast cancer detection using four biomarkers: collagen, NADH, flavin, and elastin, with 340-nm excitation. It is found that the BSS SVM outperforms the approach based on multivariate curve resolution (MCR) using SVM and achieves the best performance of principal component analysis (PCA) using SVM among all combinations of PCs. The descent order of efficacy of the four biomarkers in the breast cancer detection of this experiment is collagen, NADH, elastin, and flavin. The advantage of BSS is twofold. First, all diagnostically useful information of biomarkers for cancer detection is retained while dimensionality of data is significantly reduced to obviate the curse of dimensionality. Second, the efficacy of biomarkers in cancer detection can be determined.

Fate of the herbicides 2,4,5-T, atrazine, and DNOC in a shallow, anaerobic aquifer investigated by in situ passive diffusive emitters and laboratory batch experiments

The fate of the three herbicides 2,4,5-T (2,4,5-trichlorophenoxyacetic acid), atrazine (6-chloro-N-ethyl-N'-[1-methyl-ethyl]-1,3,5-triazine-2,4-diamine), and DNOC (4,6-dinitro-2-methylphenol) in an anaerobic sandy aquifer was investigated. In the field, each of the herbicides was released simultaneously with tritiated water (HTO) as tracer in the depth interval 3 to 4 mbs (meters below surface) by use of passive diffusive emitters. Atrazine and 2,4,5-T were persistent during the approximately 18 days residence time in the aquifer. In contrast, DNOC was rapidly removed from the water phase following first-order kinetics. The removal mechanism was likely an abiotic reduction. At day 25, the first-order rate constant was 1.47 d(-1), but it decreased with time and seemed to stabilize at 0.35 d(-1) after 150 to 200 days. In the laboratory, batch experiments were conducted with sediments from 3 to 4 mbs and from 8 to 9 mbs. In these incubations, formation of Fe2+ and depletion of sulfate showed iron and sulfate reduction in sediment from 3 to 3.5 mbs and sulfate reduction in 3.5 to 4 mbs sediment. In sediment from 8 to 9 mbs, the dominant redox process was methane formation. In sediment from 3 to 3.5 mbs, only 27% to 52% of the 2,4,5-T remained after 196 days. 2,4,5-trichlorophenol was identified as the major metabolite. A lag period of at least 50 days was observed, and no degradation occurred in HgCl2 amended controls, verifying that the process was microbially mediated. In the other 2,4,5-T incubations and all the atrazine incubations, concentrations decreased linearly, but less than 25% was removed within 200 to 250 days. No degradation products could be detected, and slow sorption was the likely explanation. In all the laboratory incubations DNOC was degraded, following first-order kinetics, and when normalized to the sediment/water-ratio, the field and laboratory derived rate constants compared well. The DNOC degradation in the methanogenic incubations (8 to 9 mbs) was up to 50 times faster than in the sediments from 3 to 4 mbs, likely due to the low redox potential.