Addressing the challenges of fragrance design, researchers at Institute of Science Tokyo  have developed an AI model that can automate the creation of new fragrances based on user-defined scent descriptors. The model uses mass spectrometry profiles of essential oils and corresponding odor descriptors to generate essential oil blends for new scents. This breakthrough is a game-changer for the fragrance industry, moving beyond trial-and-error, enabling rapid and scalable fragrance production.

Researchers led by Keigo Morita and Shinya Kuroda of the University of Tokyo have revealed a temporal disruption in the metabolism of obese mice when adapting to starvation despite no significant structural disruptions in the molecular network. This is a breakthrough discovery as research including the temporal dimension in biology has been notoriously laborious and extracting systematic insight from big data has been difficult. Thus, this study paves the way for further research into more general metabolic processes, such as food intake and disease progression. The findings were published in the journal Science Signaling.

A research team led by Dr. TANAKA Toshiko and Dr. HARUNO Masahiko at the National Institute of Information and Communications Technology (NICT), investigated how avatar-mediated communication affects human decision-making. They discovered that participants were more likely to take risks when facial expressions (such as admiration or contempt) were displayed by avatars than when the same expressions were shown on real human faces. This increase in risk-taking was found to result from a more favorable valuation of the "uncertainty" of facial feedback in the avatar condition. Furthermore, fMRI analysis revealed that this valuation of uncertainty depends on activity in the amygdala.

A research team comprising members from the National Institute for Materials Science (NIMS), Tohoku University, and the Photon Science Innovation Center (PhoSIC) has successfully identified the optimal composition of a Co-Mn-Si Heusler alloy exhibiting the highest spin polarization—a key property of half-metallic materials—in just one day of experiments. This achievement was made possible by fabricating a composition-spread thin film on a single substrate and conducting photoelectron measurements at a 3 GeV high-brilliance synchrotron radiation facility, NanoTerasu. This highly efficient optimization approach is expected to accelerate the development of high-performance spintronic materials.

Scientists have identified a simple, noninvasive method for assessing blood glucose regulation using continuous glucose monitoring (CGM) data. Their approach, which tracks glucose fluctuations, outperforms traditional markers in predicting diabetes risk. To expand accessibility, they have developed a web application for easy calculation of CGM-based indices.

Researchers at Tohoku University explored a colloidal crystal model to produce specific polymorphs, required for use in materials science and pharmaceuticals.

Researchers have developed a light-induced DNA detection method that enables rapid, PCR-free genetic analysis. Their technique offers ultra-sensitive mutation detection in just five minutes, reducing costs and simplifying testing. The method has significant potential in healthcare, environmental conservation, and personal health monitoring.

Ultrasound imaging is one of the most widely used diagnostic tools in modern medicine. Behind its non-invasive magic lies a class of materials known as piezoelectric single crystals, which can convert electrical signals into mechanical vibrations and vice versa. Now, in a world-first, a research team from Kumamoto University has successfully visualized how tiny structures inside one of these crystals respond to electric fields in real time—shedding light on the dynamics of nanostructure in materials used in ultrasound probes.

A NIMS research team has developed an approach capable of accurately and  short-timeframe predicting the degradation behavior of electrocatalysts used in water electrolyzers by employing data assimilation—a method commonly employed in weather forecasting. After analyzing only 300 hours of experimental data, this approach accurately predicted the degradation of an electrocatalytic material occurring after approximately 900 hours of water electrolysis. This approach is able to accelerate and simplify the comparison of degradation properties among various electrocatalytic materials, potentially facilitating investigations into their degradation mechanisms and expediting the development of more efficient, economical and durable electrocatalytic materials.