Game-changing biotech for engineering pathogen-resistant crops
Peer-Reviewed Publication
Updates every hour. Last Updated: 21-Sep-2025 10:11 ET (21-Sep-2025 14:11 GMT/UTC)
The research group led by Drs. Mitsuru Arase, Mari Murakami, and Prof. Kiyoshi Takeda (Graduate School of Medicine/ Immunology Frontier Research Center at The University of Osaka) revealed that transcription factors RUNX2 and BHLHE40 play crucial roles in inducing T cells involved in Crohn's disease.
Tracking human behavioral patterns in cities can be used to determine urban delineations and urban land use, which has the potential to improve urban planning.
Sweat-based enzyme sensors offer a convenient way to measure lactic acid levels in the body, but face challenges due to the loss of lactate oxidase (LOx) activity in sweat. Now, researchers from Japan have improved LOx stability by adding sucrose monolaurate, a sugar-based surfactant, that when added to the electrode forms protective nanostructures around the enzyme. Their approach could enable more durable and accurate sweat lactate sensors for sports training management and continuous health monitoring.
Motor skills, the movements produced by our muscles, are often adjusted based on an individual’s altered visual feedback. This is known as visuomotor adaptation and is influenced by the direct and systematic approaches of explicit strategies. However, cultural biases might influence these strategies. In this study, researchers compared the results of an aiming task between two groups of participants from two different cultures, trying to understand the role of cultural cognitive biases.
English proficiency is crucial for Japanese STEM students, but validated and robust methods for assessing their language learning strategies (LLSs) are lacking. In a recent study, Associate Professor Akihiro Saito from the Tokyo University of Science developed and validated a new instrument specifically tailored for this group. The proposed tool offers key insights into LLSs, paving the way for better English learning.
Researchers at the University of Osaka have developed NeuraLeaf, a revolutionary CG model using deep learning to represent diverse plant species and their leaf deformations. This single model overcomes the limitations of traditional manual modeling by disentangling species-specific shapes from dynamic 3D deformations like wilting or curling. NeuraLeaf allows precise tracking of leaf changes, enhancing growth prediction, disease detection, and agricultural management. Presented at ICCV 2025, this technology promises to advance plant science and contribute to "PlantTwin," a project creating digital twins of plants.