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Spectral image (SI) measurement techniques, such as X-ray absorption fine structure (XAFS) imaging and scanning transmission electron microscopy (STEM) with energy-dispersive X-ray spectroscopy (EDS) or electron energy loss spectroscopy (EELS), are useful for identifying chemical structures in composite materials. Machine-learning techniques have been developed for automatic analysis of SI data and their usefulness has been proven. Recently, an extended measurement technique combining SI with a computed tomography (CT) technique (CT-SI), such as CT-XAFS and STEM-EDS/EELS tomography, was developed to identify the three-dimensional (3D) structures of chemical components. CT-SI analysis can be conducted by combining CT reconstruction algorithms and chemical component analysis based on machine-learning techniques. However, this analysis incurs high-computational costs owing to the size of the CT-SI datasets. To address this problem, this study proposed a fast computational approach for 3D chemical component analysis in an unsupervised learning setting. The primary idea for reducing the computational cost involved compressing the CT-SI data prior to CT computation and performing 3D reconstruction and chemical component analysis on the compressed data. The proposed approach significantly reduced the computational cost without losing information about the 3D structure and chemical components. We experimentally evaluated the proposed approach using synthetic and real CT-XAFS data, which demonstrated that our approach achieved a significantly faster computational speed than the conventional approach while maintaining analysis performance. As the proposed procedure can be implemented with any CT algorithm, it is expected to accelerate 3D analyses with sparse regularized CT algorithms in noisy and sparse CT-SI datasets., (© The Author(s) 2024. Published by Oxford University Press on behalf of The Japanese Society of Microscopy. All rights reserved. For commercial re-use, please contact reprints@oup.com for reprints and translation rights for reprints. All other permissions can be obtained through our RightsLink service via the Permissions link on the article page on our site–for further information please contact journals.permissions@oup.com.)

We tested the hypothesis that α-lactalbumin inhibits the disruption of intestinal barrier function and liver cirrhosis by restoring gut-liver axis function in thioacetamide (TAA) -treated rats. Rat diets were supplemented with α-lactalbumin replacing 50% of dietary protein. After consuming α-lactalbumin for one week, rats were intraperitoneally injected with TAA twice a week for 14 weeks. The α-lactalbumin-enriched diet significantly inhibited the elevation of plasma alanine aminotransferase, aspartate aminotransferase, and hyaluronic acids. The supplement significantly reduced plasma lipopolysaccharide levels and increased occludin mRNA level. Hepatic fibrosis and regenerative nodules was developed and intestinal villi were shortened by TAA; α-Lactalbumin attenuated these histopathological changes. These results indicated that α-lactalbumin improved intestinal barrier function, suppressing endotoxin levels. These data also suggested that α-lactalbumin ameliorated the impairment of the gut-liver axis by TAA, inhibiting the development of liver cirrhosis.

The flavor deterioration of mayonnaise is induced by iron, which is released from egg yolk phosvitin under acidic conditions and promotes lipid oxidation. To prevent oxidative deterioration, natural components, rather than synthetic chemicals such as ethylenediaminetetraacetic acid have been required by consumers. In the present study, we evaluated the inhibitory effects of three egg white components with the same amino acid composition, namely egg white protein, hydrolysate, and the amino acid mixture, on lipid oxidation in mayonnaise and an acidic egg yolk solution as a model system. We found that the hydrolysate had the strongest inhibitory effect on lipid oxidation among the three components. The mechanism underlying the antioxidant effect was associated with Fe 2+ -chelating activity. Thus, egg white hydrolysate may have the potential as natural inhibitors of lipid oxidation in mayonnaise.

The autoxidation of such n-3 polyunsaturated fatty acid (PUFA) ethyl esters as ethyl eicosapentaenoate and ethyl docosahexaenoate was investigated at various temperatures. Extensive studies of the oxidative reaction for ethyl eicosapentaenoate were carried out at different oxygen levels. At the same oxygen level and temperature, the autocatalytic reaction rate, by which oxidation progressed in the first half period, was about 1.5-2.5 times larger than the first-order reaction rate which governed the oxidation in the second half period. The reaction rate constants for ethyl eicosapentaenoate at different oxygen levels correlated well with the Langmuir-type equation of the oxygen concentration, in which the Langmuir parameter was independent of temperature.

On the basis of an autocatalytic and a first order reaction kinetics, a nonisothermal oxidation reaction model was developed for n-3 polyunsaturated fatty acid (PUFA) under temperature-programmed linear heating conditions. With this model, the activation energy of oxidative reaction can easily be obtained with at least three linear heating conditions. The temperature-programmed oxidation experiments of ethyl eicosapentaenoate and ethyl docosahexaenoate were done under linear heating conditions of 4 to 12 K/h. The activation energies and the frequency factors obtained were in good agreement with those by the isothermal oxidation experiments reported previously.