A latest study published in Soil Ecology Letters sheds new light on how mangrove forests adapt to rising salinity levels, a critical threat amplified by climate change. The research, led by Mr. Shamim Ahmed from the Technical University of Munich, demonstrates how soil nutrients and leaf area index (LAI) interact with species and structural diversity to buffer mangrove productivity against salinity stress.

As global populations continue to grow, so does the need for nutritious food and efficient manufacturing processes. Current food production practices generate side streams that could be recycled. Researchers reporting in ACS’ Journal of Agricultural and Food Chemistry fed the side streams of carrot production to fungi, generating a sustainable source of protein. They incorporated the new protein into proof-of-concept vegan patties and sausages that testers ranked as tastier than food made from plant-based proteins.

New ultrasound technology developed at Johns Hopkins can distinguish fluid from solid breast masses with near perfect accuracy, an advance that could save patients, especially those with dense breast tissue, from unnecessary follow-up exams, painful procedures and anxiety.

What if instead of taking a water or soil sample to the lab, you could take the lab to the sample? That’s what a team of researchers reporting in ACS Sensors did with a new nitrate-monitoring “lab-on-a-drone” system. The drone allows for easy, real-time water sampling and analysis in hard-to-reach areas like steep ditches or swampy lowlands. The technology could help farmers optimize their fertilizer use and prevent waterway pollution from excess nitrate runoff.

Free-space optical communications (FSOC), which use lasers for high-speed data links between aircraft, spacecraft, and ground stations, are limited by size and power constraints. To overcome this, researchers from the Karlsruhe Institute of Technology, Germany, proposed and experimentally validated a fiber-bundle-based architecture that could enable compact, multi-directional FSOC.

CatDRX is a generative AI framework developed at Institute of Science Tokyo, which enables the design of new chemical catalysts based on the specific chemical reactions in which they are used. The model learns from large reaction datasets and predicts how well a catalyst will perform, while also proposing new catalyst structures. Validated across various reaction types, CatDRX offers a promising strategy to accelerate catalyst discovery for a wide range of chemical and industrial processes.