Scientists call for urgent measures to protect underwater forests in a new global “Marine Animal Forests Manifesto”
Reports and Proceedings
Updates every hour. Last Updated: 21-Dec-2025 11:12 ET (21-Dec-2025 16:12 GMT/UTC)
Scientists from around the world are calling for urgent action to protect, restore, and sustainably manage one of the ocean’s least known yet most important ecosystems: the Marine Animal Forests. The appeal is presented in the document Marine Animal Forests: A Manifesto, launched by an international team of experts led by the Institute of Environmental Science and Technology of the Universitat Autònoma de Barcelona (ICTA-UAB), Spain, together with the Università del Salento, Italy.
LMU-Scientists uncover key proteins that control how Toxoplasma gondii assembles the machinery it uses to invade host cells.
An international study led by the University of Basel has discovered that nuclear pore complexes – tiny gateways in the nuclear membrane – are not rigid or gel-like as once thought. Their interiors are dynamically organized, constantly moving and rearranging. The findings reshape our understanding of a vital transport process in cells and have implications for diseases and potential therapies.
This review systematically examines the integration of machine learning (ML) and artificial intelligence (AI) in nanomedicine for cancer drug delivery. It demonstrates how ML algorithms—including support vector machines, neural networks, and deep learning models—are revolutionizing nanoparticle design, drug release prediction, and personalized therapy planning. The article outlines the complete ML workflow from data acquisition to model interpretation, compares key algorithms, and presents real-world case studies spanning multidrug carrier optimization and cancer diagnostics. While highlighting substantial preclinical advances, the authors identify critical barriers to clinical translation such as data heterogeneity, model opacity, and regulatory challenges. The review concludes with a forward-looking roadmap emphasizing data standardization, explainable AI, and clinical validation to bridge the gap between computational innovation and patient-ready nanomedicine.