A research team led by Drs. Byung-Yong Yu and Gwan-Ho Lee at the Advanced Analysis and Data Center of the Korea Institute of Science and Technology (KIST; President Sang-Rok Oh) announced that it has developed a new analytical platform that can precisely measure the accumulation of fine particulate matter in individual organs, overcoming the limitations of existing analytical technologies.

New study suggests using human urine as a fertiliser could significantly boost sustainable agriculture – but key health risks and knowledge gaps must be addressed before it could be widely adopted.

Researchers publishing in Computational Biomedicine have developed a novel artificial intelligence framework that improves epileptic seizure prediction by combining bidirectional long short-term memory networks with a channel attention mechanism. The study highlights how interpretable deep learning models may help identify critical preictal EEG patterns and support the development of more reliable seizure prediction systems.Researchers publishing in Computational Biomedicine have developed a novel artificial intelligence framework that improves epileptic seizure prediction by combining bidirectional long short-term memory networks with a channel attention mechanism. The study highlights how interpretable deep learning models may help identify critical preictal EEG patterns and support the development of more reliable seizure prediction systems.

A study finds that “preparing” biochar through composting can make it far more effective for improving soil fertility and boosting plant growth.

A study has captured, in real time and in three dimensions, how a single piece of biomass changes as it is heated into biochar, offering fresh clues for designing more effective carbon materials for water cleanup, soil improvement, catalysis, and climate-related applications.

A new study outlines a comprehensive framework leveraging AI and big data to combat illegal plant trade, addressing global biodiversity threats with technological innovation.

Single-nucleus RNA-seq atlas of equine skeletal muscle reveals donkey and horse distinct cell types, with species-specific age-related shifts in muscle fiber composition. The conserved upregulation pattern of LDHA reveals the critical role of propanoate metabolism in energy supply for equine locomotion. Cross-species transcriptomic comparison delineates a highly conserved atlas of skeletal muscle cell types.