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One of useful geochemical observations for evaluating the volcanic activity is measuring soil gas emission, which may indicate deep-sited changes in the volcanic system. At Mt. Azuma, Japan, a continuous observation station has been deployed since October 2017 to monitor soil gas fluxes. Mt. Azuma exhibited unrest in 2018, and the soil CO2 flux increased drastically in August 2018 (e.g., Fukui et al., 2019). However, the CO2 flux fluctuated largely over the entire observation period because of the perturbation of external environment parameters (such as temperature and humidity), which made it difficult to find smaller flux changes from a deep volcanic origin. In this study, we employed a machine learning approach to detect such small, unclear flux changes.First, we analyzed our CO2 emission data with the multiple regression analysis (e.g., Morita et al., 2019). The model was trained using flux data from October 2017 to July 2018 (just before the significant flux increase) to represent typical background gas emission. Then we calculated flux residuals of the trained model in 2018. The residuals showed that the flux change occurred not only in August 2018 but also in July 2018, indicating that the model might detect the volcanic status change earlier than August 2018. We also applied a deep learning model with a long short-term memory (LSTM) layer to the same dataset and found that the LSTM model also supported the flux change in July. For further investigation, we will test other machine learning techniques and use seismic observation data., The 28th IUGG General Assembly (IUGG2023) (Berlin 2023)

IL-33 is a novel cytokine that is believed to be involved in inflammation and carcinogenesis. However, its source, its production and its secretion process remain unclear. Recently, we have reported that IL-33 is up-regulated in dextran sulfate sodium (DSS) colitis in mice.Production of IL-33 from intestinal tissue was studied in a murine cancer model induced by azoxymethane (AOM) and DSS in vivo and in cultures of IEC-6 epithelial cells. Cytokine levels were measured by real time PCR, immunohistochemistry and elisa.Mice with AOM/DSS-induced colitis expressed all the characteristic symptoms of colon cancer pathology. Immunohistochemical analysis demonstrated epithelial cell-derived IL-33 in colon tissues from mice with AOM/DSS colitis. Real time PCR and quantitative PCR analysis revealed that AOM/DSS colitis tissues expressed up-regulated IL-1β, IL-33, TGF-β, and EGF mRNA. Gefitinib, an EGFR inhibitor, inhibited IL-33 mRNA expression in AOM/DSS colitis mice. The pathophysiological role of IL-33 in the rat intestinal epithelial cell line (IEC-6 cells) was then investigated. We found that EGF, but not TGF-β1 or PDGF, greatly enhanced mRNA expression of IL-33 and its receptor ST2. In accordance with the gene expression and immunohistochemical analysis of IL-33 levels, elisa-based analysis of cytoplasmic and nuclear extracts showed increased IL-33 protein levels in IEC-6 cells after treatment with EGF.Our results suggest that EGF is a key growth factor that increased IL-33 production and ST2 receptor expression during intestinal inflammation and carcinogenesis. The EGF/IL-33/ST2 axis represents a novel therapeutic target in colon cancer.