Highspeed Internet, autonomous driving, the Internet of Things: data streams are proliferating at enormous speed. But classic radio technology is reaching its limits: the higher the data rate, the faster the signals need to be transmitted. Researchers at the Helmholtz-Zentrum Dresden-Rossendorf (HZDR) have now demonstrated (DOI: 10.1038/s42005-025-02273-0) that weak radio signals can be efficiently converted into significantly higher frequencies using this material that is just several tens of nanometers thick. And at room temperature, at that. The results open up prospects for future generations of mobile communications and high-resolution sensor technology.

Mitochondria integrally influence plant growth, fertility and adaptation. Notably, multiple chromosomal configurations are present in Saccharum complex mitogenomes. There are substantial genomic reorganization and gene transfer events throughout evolution.

The research team led by Dr. Dae-Yoon Kim at the Functional Composite Materials Research Center of the Korea Institute of Science and Technology (KIST, President Sangrok Oh) has developed a soft robot named 'OCTOID' that freely changes its color and shape, inspired by the camouflage and movement of octopuses. OCTOID is an integrated soft robot that goes beyond simply bending or stretching; it changes color in response to electrical stimulation, moves to match its surroundings, and grasps objects.

Functionalized single-walled carbon nanotubes (SWCNTs) effectively delivered the amh/amhy plasmid into all-female mandarin fish via immersion. At 40 mg/L, plasmid DNA and transcripts were detected in gonads within 7-14 days. By 60-120 days, some fish developed masculinized gonads with downregulated foxl2/cyp19a1a and upregulated amh/dmrt1. The study demonstrates SWCNTs as a viable gene delivery tool in fish and confirms the crucial role of amh/amhy in sex determination via the amhrII/smads pathway activating dmrt1.

Researchers at the University of Windsor developed SH17, a large open-source dataset with 8,099 images and 75,994 labeled instances to improve detection of personal protective equipment (PPE) in manufacturing. Using advanced AI models like YOLOv9, the study achieved over 70% accuracy, offering industries a scalable tool to enhance worker safety and compliance.

New review in iOptics demonstrates how AI is overcoming key challenges in metasurface design, enabling advanced applications in compact optics and computational imaging.