The patterns that make up the weaves in textiles are seemingly endless. Certain patterns produce different qualities, such as making a material better at allowing sound to travel through it. But given the vast arrangement possibilities, testing each pattern arrangement can be a never-ending process. Now, a research team has developed an AI-assisted method to sift through the pattern possibilities.

Researchers from the University of Osaka uncovered the first steps of disease development in ANCA-associated autoimmune glomerulonephritis. Injured kidney cells send signals to attract immune cells, including neutrophils, and induce inflammation. The researchers tested the effects of modified antibodies on halting disease progression in a mouse model, showing that the modified antibodies successfully reduced kidney injury. The findings offer hope for a potential treatment aimed at stopping the disease at its earliest stage.

Researchers at the Nano Life Science Institute (WPI-NanoLSI) at Kanazawa University have developed a way to observe how antibodies interact with a cancer-related protein carried on tiny membrane-bound vesicles released by cells. Using high-speed atomic force microscopy, they found that measuring how much of the protein is present does not necessarily show how accessible it is to antibodies. The findings reported in the journal Small Methods provide a new way to investigate differences between individual cancer-derived vesicles although further research is needed before the approach can be used clinically.

Tokyo, Japan- Prediction is a defining feature of intelligent behavior. Researchers at The University of Tokyo developed a spiking-network model that learned what event would occur, when it would occur, and how likely it was. The single network rapidly recalibrated when timing or probabilities changed, using local learning. The findings suggest a computational framework for adaptive, brain-inspired AI and testable ideas about how neural systems update expectations across dynamic environments and changing real-world conditions.

A study from the Research Center for Materials Nanoarchitectonics (MANA), one of the centers under the National Institute for Materials Science (NIMS), presents a new method to decode hidden material disorder contained in complex photoluminescence spectra, paving the way for new optical diagnostics of material disorder in two-dimensional semiconductors and related light-emitting materials.

Researchers at Tohoku University and collaborators have demonstrated key technologies for controlling and measuring electrons in zinc oxide quantum dots, an important step toward developing spin-based quantum devices. Their results provide a new platform for exploring how electron spins behave in this promising material.

Correlation does not imply causation. Using AI to discover new materials is becoming more common, but data-driven approaches sometimes rely heavily on correlations and make testing AI-based predictions difficult. A new perspective paper published by Tohoku University researchers developed a framework for incorporating physics-based principles into AI to generate more interpretable, testable, and meaningful predictions.

Researchers at the University of Osaka developed a simple two-step culture system that turns human blood-derived B cells into germinal center-like B cells using CD40L, IL-4, and IL-21 in a specific sequence. The resulting cells closely resemble genuine human germinal center B cells and undergo somatic hypermutation. The platform provides a practical tool for studying antibody formation directly in human cells and may support future vaccine and autoimmune disease research.