Researchers from The University of Osaka found that PM_2.5 air pollutants negatively affect mucociliary clearance, a protective mechanism of the respiratory tract. Air pollution led to the formation of lipid peroxide-derived aldehydes, known to damage protective cells in the airway and increase the risk of infections. ALDH1A1 was found to play an important role in protection against aldehydes, making it a potential therapeutic target to diminish the negative effects of air pollution.

Researchers at Science Tokyo have developed a method to dissolve previously insoluble porous aromatic polymers (PAPs) in water by encapsulating them in aromatic micelles. These 100 nm-sized particles, which normally function only in solid form, can now incorporate hydrocarbons and dyes in solution, forming unique multi-component materials. The technique uses a simple grinding and sonication process, and enables particle size control via centrifugation and filtration. Notably, the presence of hydrocarbons enhances the fluorescence of the embedded dyes up to ninefold. This breakthrough introduces a new class of water-soluble, polycavity materials with potential applications in sensing, storage, and catalysis—opening up new possibilities beyond conventional single-cavity molecular systems.

A research team has designed and implemented a group motivational interviewing system using multiple chatbots to support premenstrual syndrome (PMS), a common disorder among women. The system consists of a facilitator bot and two peer bots, and simulates a group counseling environment for PMS management. These findings provide valuable insights into the use of multiple chatbots for addressing mental health issues.

Despite advances in machine vision, processing visual data requires substantial computing resources and energy, limiting deployment in edge devices. Now, researchers from Japan have developed a self-powered artificial synapse that distinguishes colors with high resolution across the visible spectrum, approaching human eye capabilities. The device, which integrates dye-sensitized solar cells, generates its electricity and can perform complex logic operations without additional circuitry, paving the way for capable computer vision systems integrated in everyday devices. 

Human-AI interactions are well understood in terms of trust and companionship. However, the role of attachment and experiences in such relationships is not entirely clear. In a new breakthrough, researchers from Waseda University have devised a novel self-report scale and highlighted the concepts of attachment anxiety and avoidance toward AI. Their work is expected to serve as a guideline to further explore human-AI relationships and incorporate ethical considerations in AI design.