Evaluation of the effect of dimethyl fumarate on human bone marrow-derived mesenchymal stem cells using bottom-up proteomics.

Mesenchymal stem cells (MSCs) have potential as a viable treatment option in the field of regenerative medicine, but MSC-based therapy needs to be more efficient. Preconditioning is a method to improve MSC-based therapy, and dimethyl fumarate (DMF) - an agent that can enhance the antioxidative capacity of cells - can be considered for preconditioning of MSCs. In this study, we treated bone marrow-derived MSCs with DMF and evaluated their proteome using bottom-up proteomics. The MSCs were exposed to 10 µM DMF for 24 h, followed by lysis with an SDS solution, digestion with trypsin using an s-trap column, and analysis using nanoLC-MS/MS, which identified 2262 proteins with confidence. Bioinformatic analysis of the identified proteins revealed 47 upregulated proteins and 81 downregulated proteins upon DMF treatment. Pathway enrichment analysis suggested a possible decrease in autophagy and a decrease in the activity of the TCA cycle, while indicating a potential increase in proliferation and antioxidant activity in DMF-treated MSCs compared to untreated MSCs. Our findings suggest that DMF can enhance the proliferation of MSCs and increase their stability, and that preconditioning could improve the therapeutic efficacy of MSCs for the treatment of regenerative diseases.

Identification of geographical origins of soybean pastes using headspace gas chromatography-mass spectrometry by selecting sample-descriptive components with an Incremental Association Markov Blanket.

The identification of geographical origins of soybean pastes using headspace gas chromatography-mass spectrometry was attempted in this study. Since soybean paste was odor-rich, 36 components were identified in the imported and domestic soybean samples. t-Test, variable importance in projection (VIP), and Incremental Association Markov Blanket (IAMB) were employed to select proper components that could effectively discriminate the two sample groups. The discrimination accuracies were below 87.3 % when all 36 components were fed for either LDA, k-NN, or SVM. When the five t-test-selected components or six VIP score-selected components were employed, the accuracies improved to 95.2-96.2 %. The IAMB selected three different components were 3-methylbutanal, 4-methylnonane, and 2,3-pentanedione, and the correlations among their peak areas were not significant. This suggests that these three components were independently relevant for the discrimination. The accuracy obtained using these three components was superior, 97.7 %, as undescriptive and/or redundant components for the discrimination were excluded.