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.

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.

When we are engaged in a task, our brain’s auditory system changes how it works. One of the main auditory centers of the brain, auditory cortex, is filled with neural activity that is not sound driven – rather, this activity times the task, each neuron ticking at a different moment during task performance.