Over the past decade, Okayama University of Science has turned wine into a platform for education, research and regional collaboration. Its Wine Project has trained students in grape cultivation and winemaking, developed the new wine grape Muscat Shiragai, and worked with local producers on sake and wine. Now, researchers are looking to the project’s next chapter: making wine from Muscat Shiragai using locally discovered yeast to create a wine distinctly rooted in Okayama.

Marine plastic debris can persist for long periods and gradually break down into microplastics that are difficult to remove. Researchers from Ritsumeikan University used a system dynamics model to examine how reducing marine plastic inputs and varying the timing and intensity of cleanup could affect plastic accumulation by 2050. The findings show that halting plastic inputs is essential but insufficient on its own. Earlier cleanup of legacy macroplastics can reduce accumulation, but at higher costs.

The enigmatic assembly pathway behind the refractile-body proteins may have finally been resolved, as reported by researchers from Science Tokyo. Using genetic engineering and several protein structural analysis techniques, they investigated how four different proteins work together to produce the correct nanoscale to microscale structure of these complex, pH-responsive protein machines. These findings could help establish new frameworks to engineer dynamic protein systems as biotechnological tools.

Limited weather observations over Antarctica often lead to less accurate forecasts in the Southern Hemisphere (SH) compared to the Northern Hemisphere. In a new study, Japanese researchers found that adding continuous radar observations from Antarctica improved forecasts of atmospheric rivers—long, narrow bands of moisture that can bring heavy rain, snow, and flooding. Their findings highlight the value of continuous Antarctic observations for more reliable weather forecasting across SH.

A research team led by Kyushu University have developed a new water-soluble and metal-free molecule that could be detected by both fluorescence imaging and utilized as an MRI contrast agent. The team modified the luminescent organic radical tris(2,4,6-trichlorophenyl) methyl (TTM) to make it water-soluble. The new molecule produced deep-red fluorescence in water and enhanced the contrast of MRI phantom images by approximately 2.5 to 4.5 times stronger than that of previously reported water-soluble TTM radicals.

Development of a compact current comparator capable of evaluating both AC and DC current ratios using the same setup

Using an integrated New Approach Methodologies (NAMs) framework combining bioinformatics, 3D modeling, machine learning, and in vitro assays, this study analyzed 107 ecological factors and estrogen receptor alpha (ERα) diversity across 169 mammalian species. Key discoveries include an expanded ligand-binding pocket in omnivores, a cetacean-specific substitution, and brain-to-body mass ratio as a sensitivity predictor. These findings provide essential molecular mechanisms for predicting wildlife chemical sensitivity.

Chemists routinely optimize reactions to maximize the yield of their desired products, but understanding why those reactions work can require laborious experiments that track reactions through time. Researchers at the University of Tokyo have developed a method to extract hidden information on reaction speeds from yield data obtained during reaction optimization using machine learning together with rate equations developed by chemists. Concentration-dependent yield analysis (CYAN) uses machine learning to expand the yield data from reaction optimization experiments, then uses this information to calculate how quickly the different steps of a reaction occur. This gives chemists a tool to understand, improve and design complex high-yield chemical reactions. 

Kyoto, Japan -- While silicon carbide -- SiC -- has long been promoted as the key to developing electronics suitable for extreme environments, the field has been stuck in the lab for some time. Now, a team of researchers focusing on junction field-effect transistors, or JFETs, have succeeded in developing a new SiC transistor structure that can operate at 600°C, as announced recently by Kyoto University.* One of the team's goals after their previous study was to scale up to wafer-level production, so that is what they have now accomplished.

Compared with the previous study, wafer-scale production refers to building much smaller components and involves developing a minuscule but more efficient SiC transistor. Progressing to the wafer-scale is essential for practical implementation, as the fabrication of integrated circuits requires a large number of very small transistors.

However, wafer-scale production is virtually impossible to accomplish in a university laboratory due to equipment constraints. This motivated the team to collaborate with Phenitec Semiconductor Corp, which operates a mass-production fabrication plant, making this next step in their research feasible.

Cameras have long been regarded as tools for capturing what the human eye can see. But that assumption may soon be challenged.

“If we change the way we capture data, the potential of Artificial Intelligence (AI) expands dramatically,” says Associate Professor Hiroyuki Kubo of the Graduate School of Informatics. Dr. Kubo is developing methods to visualize what is normally invisible—such as blood vessels beneath the skin or vehicles hidden in fog—using not specialized equipment, but systems built with ordinary projectors and cameras. His approach could significantly accelerate advances in AI. Beyond imaging, Dr. Kubo is also exploring new possibilities in AI-assisted coloring. By designing systems in which humans and AI collaborate to efficiently color large volumes of animation cels, his research aims to enhance productivity in anime production.

We spoke with Dr. Kubo about his work and his vision for the future as he continues to push the boundaries of what cameras—and AI—can do.