Combination of LIBS-based elemental analysis and near-infrared molecular fingerprinting of bile juice to enhance identification of gallbladder cancer.

Laser-induced breakdown spectroscopy (LIBS) and near-infrared (NIR) spectroscopy, enabling the measurement of raw bile directly without sample pretreatment, were cooperatively combined to enhance the discrimination of gallbladder cancer (GBC) from other diseases of gallstone and gallbladder (GB) polyp. Since elemental contents and metabolite compositions of bile vary according to the pathological conditions of pancreaticobiliary patients, the use of complementary information could be synergetic to improve disease identification accuracy. The ratios of Mg and Na peak areas (AMg/ANa) and Na and K peak areas (ANa/AK) in the LIBS spectra of GBC samples were different from those of the remaining samples. Also, the intensity ratios of main NIR peaks differed in GBC. Nonetheless, the use of only element peak area ratio or NIR peak intensity ratio was not sufficient to clearly discriminate GBC. On the other hand, when the ANa/AK values and second NIR principal component scores were combined, the discrimination of GBC from normal/gallstone/GB polyp was substantially enhanced owing to incorporation of both complementary GBC-discriminant spectroscopic signatures.

Exploring two-trace two-dimensional (2T2D) correlation spectroscopy as an effective approach to improve accuracy of discriminant analysis by highlighting asynchronous features in two separate spectra of a sample.

This 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. When the 2T2D slice spectra of the samples were used for the discriminant analysis, the authentication accuracy reached to 100%, while became degraded in the cases of using the spectra collected either at 20 °C or 41 °C. Furthermore, a simple strategy of utilizing the average spectrum of one sample group as the reference spectrum in the 2T2D correlation analysis was proposed for two-group discrimination and evaluated for the NIR identification of the geographical origins of agricultural products (milk vetch root (MVR) and perilla seed samples). Because the average spectrum of one sample group was used for comparison, dissimilar constituent compositions of the samples in another group were better observed, thereby improving the accuracy of discrimination of the geographical origins of the samples in both cases. The overall results demonstrated that 2T2D correlation analysis is effective for highlighting the minute asynchronous spectral features of a sample and can be expanded for diverse vibrational spectroscopy-based discriminant analyses.

Alternative selection of Raman or LIBS spectral information in hierarchical discrimination of raw sapphires according to geographical origin for accuracy improvement.

Both Raman spectroscopy and laser-induced breakdown spectroscopy (LIBS) were cooperatively utilized to improve the geographical origin identification of raw sapphires from five different countries (Mozambique, Laos, Australia, Rwanda, and Congo). A hierarchical support vector machine (H-SVM) was used for multi-group identification. Initially, accuracy improved to 87.5% using merged Raman-LIBS data compared to those of using only Raman (82.8%) or LIBS (71.9%) information. This improvement was attributed to incorporating two complimentary spectroscopic datasets that provided molecular vibrational and elemental information. However, merging both spectroscopic datasets is may not be the best choice since it would make distinct and sample-descriptive information in one spectroscopic dataset less recognized for analysis by the inclusion of less characteristic information in another spectroscopic dataset; using only Raman or LIBS information at each discrimination stage would be more effective. When Raman information was utilized during the first three discrimination stages followed by LIBS data during the fourth (last) discrimination stage in H-SVM, the accuracy improved to 90.6%. The proper selection of molecular vibrational or elemental sample information at different discrimination stages is attributed to this improvement.

Hyperspectral Raman Line Mapping as an Effective Tool To Monitor the Coating Thickness of Pharmaceutical Tablets.

Protective chemical coatings are deposited on drugs during the manufacturing process for the purpose of controlling the pharmacokinetics of active pharmaceutical ingredients (APIs). Although manufacturers attempt to coat all the tablets uniformly, the film thickness of an individual drug is statistically different and depends on the measuring position of the anisotropic structure, and analytical methods for measuring coating thickness must be robust to statistical and geometrical aberrations. Herein, we demonstrate that a spatially offset Raman-spectroscopy-based line mapping method offered excellent calibration and prediction of the coating thickness of 270 acetaminophen ( N-acetyl-para-aminophenol, paracetamol) tablets. Raman-scattered light resurfaced back from the coating and APIs, and offset-resolved spectra were projected according to the vertical positions in an imaging sensor. The Raman intensity ratio between the coating substance and the inner APIs is a key parameter in the analysis, and its variation with respect to the spatial offset is proportional to the coating thickness and duration. The results of this study have implications for the rapid spectroscopic thickness measurement of industrial products coated with transparent or translucent materials.