Alternative to studded winter tires reduces airborne particles by 20 percent
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Updates every hour. Last Updated: 20-Jun-2025 14:10 ET (20-Jun-2025 18:10 GMT/UTC)
Mayo Clinic researchers have pioneered an artificial intelligence (AI) tool, called OmicsFootPrint, that helps convert vast amounts of complex biological data into two-dimensional circular images. The details of the tool are published in a study in Nucleic Acids Research.
In a new study, IIASA scientists show that a mix of policy measures, including both technological solutions and behavioral changes, can significantly reduce greenhouse gas (GHG) emissions from energy use in buildings and transport.
Fish is a high-quality source of protein, containing omega-3 fatty acids and many other beneficial nutrients. However, the accumulation of toxic mercury also makes fish consumption a concern, of which tuna is particularly susceptible. Researchers from Chalmers University of Technology in Sweden have come up with a novel approach to packaging canned tuna infused in the water-based solution of amino acid cysteine. It was shown to remove up to 35 percent of the accumulated mercury in canned tuna, significantly reducing human exposure to mercury via food.
Scientists have created a new low-cost, fast response sensor to detect lung cancer biomarkers, paving the way for the development of screening devices to spot the disease even before symptoms occur. Similar in design to glucose monitoring devices, the sensor provides results from a blood sample in just 40 minutes. The technology has the potential to be used by clinicians to both identify patients at higher risk of lung cancer, and tailor treatments for those already diagnosed in a ‘precision medicine’ approach.
In the three-year research project, Mahdi Arabnejad a former PhD student at Cranfield University, Sam Tothill, Professor of Bio-Nano Sensors, and Dr Iva Chianella, Senior Lecturer in Bio-sensors and Functional Polymers, developed the sensors to screen for two proteins in a blood sample and demonstrated the concept in a lab environment.
The study focused on developing highly sensitive sensors for two key lung cancer biomarkers: neuron-specific enolase (NSE) and carcinoembryonic antigen (CEA). The sensors were tested with buffer and human samples, and achieved clinically relevant detection limits for both NSE and CEA.
The results indicate the technology has significant promise as a valuable tool in the early and accurate detection of lung cancer.