Polycyclic aromatic hydrocarbons (PAHs) are carcinogenic compounds introduced in food due to cooking methods such as smoking, grilling, and frying. Recently, researchers from Seoul National University of Science and Technology have leveraged a new method called QuEChERS-GC-MS to extract and detect PAHs in common food items, finding the highest levels in soybean oil, followed by duck meat and canola oil.

Recurrent meningiomas pose a major clinical challenge, often returning with increased aggressiveness and treatment resistance. Researchers from Korea University used single-cell transcriptomics to map tumor evolution from primary to recurrent states, uncovering COL6A3 as a key molecular driver that links tumor proliferation with immune modulation. The study advances our understanding of meningioma biology and also highlights COL6A3 as a promising prognostic biomarker and therapeutic target, paving the way for smarter risk stratification and precision therapies.

Pathogens are becoming more and more resistant to antibiotics. With the goal of developing new therapeutic approaches to treat bacterial infections more effectively in the future, researchers at the Karlsruhe Institute of Technology (KIT) and the Max Planck Institute in Marburg investigated the plague-related bacterium Yersinia enterocolitica. It employs a special infection mechanism with which it actively switches between reproductive and infectious phases. The results of the study provide new insights into the dynamics of bacterial infections and have been published in PLOS Pathogens (DOI: 10.1371/journal.ppat.1013423)

A zigzag stitch enables fabric to stretch until the thread is straight. University of Tartu researchers report in Advanced Materials that thread packing can encode fabric stretchability, leading the way to tailoring wearables at industrial scale.

Scientists have discovered how to create circuits that are so small they’re invisible to the naked eye using a process that is both precise and economical for manufacturing. 

Perimetry (visual field testing) quantifies a patient’s retinal sensitivity to light and clarifies a deviation from normal retinal sensitivity. Visual field tests generally require high patient concentration, which can be exhausted. We constructed a framework for deep reinforcement learning to train ViFT (Visual Field Transformer), which controls all processes of visual field testing. ViFT achieves the same or higher accuracy than the state-of-the-art strategies, with less than half the test time of the state-of-the-art strategies.