Researchers at the University of Rochester’s Institute of Optics engineered a new desalination method that produces drinking water from seawater without chemical additives. In a study in Light: Science & Applications, Professor Chunlei Guo and his collaborators describe how their solar-powered system uses specially engineered black metal to absorb sunlight. Its self-cleaning surface separates and collects salts, instead of dumping them as harmful brine waste, and from the salts, the system can extract lithium, a key material for rechargeable batteries. The approach could help address global water shortages and growing mineral demand.

Artificial intelligence is rapidly changing how biomedical materials are discovered and designed. In a new review published in Science Bulletin, researchers summarize how machine learning and generative AI are helping scientists predict material behaviors such as drug release, biocompatibility, and catalytic activity, and even propose entirely new inorganic materials for biomedical applications. The review highlights emerging applications in drug delivery, cancer therapy, anti-inflammatory treatment, and tissue engineering, while also discussing the challenges that still limit clinical translation.

A research team led by Professor Gao Zexia from Huazhong Agricultural University in China has successfully cultivated grass carp completely lacking intermuscular bones (IBs)—small, sharp skeletal structures that not only pose consumption risks to consumers but also limit processing efficiency. By runx2b gene editing, the team obtained genetically stable F₂ populations of grass carp without IBs. Comprehensive phenotypic analysis revealed no significant differences between IBs-free and the wild-type grass carp in overall skeletal development, bone mineral density, muscle composition or nutritional content. Multi-omics data further demonstrated adaptive remodeling in Calcium Signaling and Muscle Contraction Pathways, indicating normal physiological compensation. This study provides a feasible strategy for improving the fish efficiency of aquaculture breeding and enhancing the supply of high quality fish protein.

The Universitat Jaume I of Castelló and GEA Biotechnology have developed an antifungal aqueous suspension for the prevention of fungal infections in crops and fruit during the pre- and post-harvest stages. The new formulation is aimed at the biotechnology and agricultural sectors, and the partners are seeking collaboration for further development and adaptation to commercial applications.

The technology is based on biodegradable chitosan microcapsules encapsulating anethole, a natural compound with antifungal activity, which improves its stability and enables controlled release on crop and fruit surfaces. According to the research team, led by Carolina Clausell from the Ecophysiology and Biotechnology research group coordinated by Aurelio Gómez Cadenas, the formulation “enhances the antifungal efficacy of natural compounds and offers a more sustainable alternative to conventional synthetic fungicides”.

Vortices in superconductors have so far been considered a disruption, as they can impair the superconducting properties. Researchers at the Karlsruhe Institute of Technology (KIT) proved now in experiment that magnetic vortices can be used as controllable quantum systems in certain materials. This means that a previously unwanted phenomenon is becoming a potential resource in quantum technologies, opening up new avenues for the development of quantum computers, highly sensitive sensor systems, and innovative approaches in materials research. The results have been published in Nature.  (DOI: 10.1038/s41586-026-10441-7)

EU-funded researchers have completed the most comprehensive assessment ever of Europe's "urban mine" — the critical raw materials embedded in waste streams including electronics, batteries, vehicles, wind turbines, and demolition debris. The  FutuRaM (Future Availability of Secondary Raw Materials) project mapped 42 critical elements across seven waste categories in 31 countries, finding that annual recovery could reach 4.1–5.7 million tonnes by 2050, potentially substituting up to 56% of primary material imports. Recovery of key metals like lithium, cobalt, and nickel could grow dramatically, reducing dependence on China and other suppliers. The project's Urban Mine Platform makes all data publicly accessible to guide investment and policy decisions.

Researchers have proposed a new conceptual framework called “Health Elements” that positions digital technologies and AI as core structural drivers of health alongside biological, behavioral, social, and environmental factors. Published in Health Data Science, the framework argues that health outcomes emerge from dynamic interactions across multiple domains rather than from isolated risk factors alone. The study reflects growing recognition that digital systems—including algorithms, wearable devices, AI-enabled diagnostics, and health data infrastructures—are increasingly shaping health behaviors, access to care, and population-level outcomes.

The authors also discuss how multimodal health data integration, complex systems science, and AI-based analytical methods could support more adaptive public health and clinical decision-making. At the same time, they warn that algorithmic bias, digital inequity, and governance challenges may reinforce existing health disparities if ethical safeguards are not built into future digital health systems. An accompanying editorial describes the framework as a significant extension of traditional Social Determinants of Health models for the digital era.

Dr. Hirokazu Masai of the National Institute of Advanced Industrial Science and Technology (AIST) has developed a highly elastic pristine oxide glass using the conventional melt-quenching method. The transparent glass exhibits both high elastic modulus and thermal stability, making it suitable for vitrification and optical fiber drawing.

Artificial intelligence models using electronic health records and patient-reported outcomes may help identify cancer survivors at increased risk for emergency department visits, hospitalizations and worsening symptoms after treatment. Findings suggest AI-driven risk forecasting could help care teams intervene earlier with more proactive survivorship support.