We demonstrated the utility of direct near-infrared (NIR) bile analysis for the identification of gallbladder (GB) cancer by employing two-trace two-dimensional (2T2D) correlation analysis to recognize dissimilar spectral features among diverse bile samples for potential improvement of discrimination accuracy. To represent more diverse clinical cases for reliable assessment, bile samples obtained from five normal, 44 gallstone, 25 GB polyp, six hepatocellular cancer (HCC), and eight GB cancer subjects were analyzed. Due to the altered metabolic pathways by carcinogenesis, the NIR spectral features of GB cancer samples, including intensity ratios of main peaks, were different from those of other sample groups.
View Article and Find Full Text PDFSpectrochim Acta A Mol Biomol Spectrosc
February 2023
To demonstrate the infrared (IR)-based bile analysis as a reliable screening tool for gall bladder (GB) cancer, we analyzed a sample set of 37 diverse bile samples (five normal, 18 GB polyp, six hepatocellular carcinoma (HCC), and eight GB cancer subjects). Bile samples of normal subjects (control) and HCC patients were newly included to examine if IR-based bile analysis could be expanded to identify HCC. Concentrations of three bile acids and eight bile salts in the aqueous phase samples were determined in parallel and lipidomic analysis of nine lipid classes in the organic phase samples was performed using liquid chromatography-mass spectrometry.
View Article and Find Full Text PDFA weighted twin support vector machine (wTWSVM) was proposed as a potential discriminant analysis tool and its utility was evaluated for near-infrared (NIR) spectroscopic identification of the geographical origins of 12 different agricultural products including black soybean and garlic. In the wTWSVM, weights were applied on each variable in the sample spectra to highlight detailed NIR spectral features and the optimal weights to minimize the discrimination error were iteratively searched. Then, the weighted spectra were employed to determine the samples' geographical origins using a TWSVM adopting two non-parallel hyperplanes for the discrimination.
View Article and Find Full Text PDFSpectrochim Acta A Mol Biomol Spectrosc
November 2021
A promising infrared (IR) spectroscopic method able to effectively identify defective pre-coated metal (PCM), a pre-painted metal panel, has been demonstrated. A temperature-perturbed IR measurement in conjunction with a two-trace two-dimensional (2T2D) correlation analysis was proposed as a strategy for enhancing defect identification. Our objectives were to induce dissimilar temperature-driven structural variations of base paints and added components, to recognize dissimilarities by 2T2D correlation analysis, and to use subsequent 2T2D correlation features to identify sample defects.
View Article and Find Full Text PDFThis study aims to demonstrate two-trace two-dimensional (2T2D) correlation spectroscopy as an effective tool for improving the accuracy of discriminant analysis. Because 2T2D correlation analysis allows sensitive capturing of asynchronous spectral behaviors between two compared spectra of a sample, the subsequent asynchronous correlation features are expected to reveal more sample-to-sample characteristics and discriminants than the original spectral feature. Initially, near-infrared (NIR) spectroscopic authentication of pure olive oil was performed using the spectra collected at 20 °C and 41 °C.
View Article and Find Full Text PDFVoltage-applied SERS measurement of bile juice in conjunction with two-trace two-dimensional (2T2D) correlation analysis was demonstrated as a potential tool to enhance discrimination of gall bladder (GB) stone and GB polyp. When SERS spectra of the aqueous phases extracted from raw bile juice samples were measured with applying external voltage from -300 to +300 mV (100 mV intervals), subsequent spectral variations of the adsorbed components (bilirubin-containing compounds) on the SERS substrate were minute, and discrimination of the two GB diseases in a principal component score domain was difficult. Therefore, 2T2D correlation analysis, effectively identifying asynchronous (dissimilar) spectral behaviors in the voltage-induced SERS spectra, was used to improve the discrimination.
View Article and Find Full Text PDFThe utility of an autoencoder (AE) as a feature extraction tool for near-infrared (NIR) spectroscopy-based discrimination analysis has been explored and the discrimination of the geographic origins of 8 different agricultural products has been performed as the case study. The sample spectral features were broad and insufficient for component distinction due to considerable overlap of individual bands, so AE enabling of extracting the sample-descriptive features in the spectra would help to improve discrimination accuracy. For comparison, four different inputs of AE-extracted features, raw NIR spectra, principal component (PC) scores, and features extracted using locally linear embedding were employed for sample discrimination using support vector machine.
View Article and Find Full Text PDFA strategy of combining temperature-induced spectral variation and two-dimensional correlation (2D-COS) analysis as a potential tool to improve accuracy of sample discrimination is suggested. The potential application of this method was evaluated using near-infrared (NIR) spectroscopic discrimination of adulterated olive oils. Rather than utilizing static spectral information at a certain temperature, dynamic spectral features induced by an external perturbation such as temperature change would be more informative for sample discrimination, and 2D-COS analysis was a reliable choice to characterize temperature-induced spectral variation.
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