New molecular map reveals how cells control traffic between the nucleus and cytoplasm
Peer-Reviewed Publication
This month, we’re focusing on artificial intelligence (AI), a topic that continues to capture attention everywhere. Here, you’ll find the latest research news, insights, and discoveries shaping how AI is being developed and used across the world.
Updates every hour. Last Updated: 19-Nov-2025 21:15 ET (20-Nov-2025 02:15 GMT/UTC)
An international team of researchers has created the most detailed model yet of how cells regulate traffic through the nuclear pore complex—the gateway between a cell’s nucleus and its cytoplasm. The study solves a decades-old puzzle about how these pores can rapidly and selectively transport molecules, revealing that flexible protein chains create a dynamic “entropic barrier” that admits only properly escorted cargo. This computational model not only clarifies how healthy cells maintain precise control but also provides insight into diseases like cancer, Alzheimer’s, and ALS, where this transport system fails. It opens new avenues for medical and biotech innovation, including the design of artificial nanopores for targeted therapies and biosensing.
Artificial intelligence (AI) technology is revolutionizing antimicrobial drug development. In response to increasingly severe antimicrobial resistance challenges, AI can efficiently predict pathogen evolutionary trends, identify potential drug targets, and accelerate compound design and optimization, thereby significantly shortening the development timeline for antimicrobial agents. This correspondence focuses on the applications of AI in phenotype-driven target identification and validation, rational molecular design, and lead compound optimization for antimicrobial drug development, while highlighting current limitations and providing perspectives on future directions.
Abstract
A team of scientists from School of Physics and Astronomy at Queen Mary University of London has developed a novel artificial intelligence method that could revolutionize our understanding of the universe's most mysterious shapes. Using advanced machine learning, researchers can now explore complex geometric spaces, like the fabric of spacetime itself, without relying on traditional symmetry assumptions.
This new algorithm, called AInstein, tackles one of the most complex puzzles in physics and mathematics: finding the precise shape of space under Einstein field equations. Remarkably, it can do so on spaces as intricate as higher-dimensional spheres, opening new avenues for discovery and shedding light on our understanding of the universe.
Deep-blue light-emitting diodes (LEDs) that satisfy the Rec.2020 color standard are essential for next-generation ultra-high-definition displays. To this end, researchers in China have developed a hydrobromic acid-assisted ligand passivation strategy that markedly improves the performance of CsPbBr3 nanoplatelet-based LEDs. This advance enables efficient deep-blue electroluminescence with color coordinates of (0.136, 0.046), fully meeting the Rec.2020 specification. The work highlights the strong potential of perovskite materials for the commercialization of next-generation ultra-high-definition display technologies.