Promoting the development and application of more accurate, ethically responsible artificial intelligence tools adapted to real clinical needs in order to improve the quality of healthcare is one of the main objectives of the NursIA network, an initiative led by a multidisciplinary team at the Universitat Jaume I in Castelló. The network brings together five research groups in fields such as nursing, biostatistics, machine learning, process mining and applied ethics, with the aim of contributing to the transformation of healthcare through innovative AI-based solutions that improve patient safety and the efficiency of healthcare processes.

Funded by the Universitat Jaume I’s 2025–2026 programme for the promotion of research and knowledge transfer, the network aims to generate impact in three key areas: scientific and technical development, institutional collaboration and knowledge transfer, and communication and outreach. Planned activities include a conference on the practical implementation of AI in clinical environments, the first open NursIA conference on artificial intelligence and healthcare transformation, and several scientific publications on AI applied to healthcare.

More than seventy years after Alan Turing posed the question of whether machines could think, advances in artificial intelligence have shifted the focus from imitation to collaboration. As AI increasingly undertakes complex academic tasks through multi-agent collaboration, a new question emerges: beyond the Turing Test, how should the human role in research be redefined?

Atomic clocks based on entangled atoms can reach extremely high precision but usually suffer from a limited measurement range. Researchers have proposed a new adaptive Bayesian protocol that dynamically adjusts measurement time using prior information. This approach allows GHZ-state atomic clocks to maintain Heisenberg-limited precision while significantly expanding their dynamic range. Simulations show improved accuracy, faster convergence, and stronger resistance to noise. The method offers a powerful framework for next-generation atomic clocks and other quantum sensors requiring both high precision and broad measurement capability.

Researchers at Aarhus University report a proof-of-concept DNA needle inspired by bacteriophages that can deliver molecules directly into cells and help them remain active. In laboratory experiments, the structure avoided endosomal trapping, a major limitation in current delivery methods. The approach may support future development of RNA-based therapies and treatments for rare genetic disorders.

orea Institute of Science and Technology (KIST, President Oh Sang-rok) A joint research team led by Dr. Jeong Sohee from the Center for Extreme Materials Research at KIST and Dr. Lee Kwang-hee from the Advanced Materials Processing Center at the Institute for Advanced Engineering (IAE, President Kim Jin-kyun) has successfully developed a catalyst technology that maximizes the surface activity of the two-dimensional nanomaterial 'tungsten diselenide (WSe₂)'. A joint research team, led by Dr. Sohee Jeong of the Extreme Materials Research Center at the Korea Institute of Science and Technology (KIST; President Oh Sang-Rok) and Dr. Gwang-Hee Lee of the Materials Science and Chemical Engineering Center at the Institute for Advanced Engineering (IAE; President Jin Kyun Kim), has successfully developed a catalyst technology that maximizes the surface activity of the two-dimensional nanomaterial tungsten diselenide (WSe₂).

A study published in the Journal of Bioresources and Bioproducts establishes quantitative structure-activity relationships governing surfactant efficacy against phenolic inhibition in lignocellulose enzymatic hydrolysis. By integrating experimental validation with computational modeling, researchers identified hydrophobicity, hydrogen bonding capacity, and electrophilicity as critical molecular descriptors, demonstrating that optimized surfactants preferentially bind cellulase catalytic tunnels with affinities significantly exceeding those of inhibitory phenolics.