Breakthroughs, discoveries, and DIY tips sent every weekday. An international team of physicists has developed a new methodology to aid NASA and other government agencies in their ongoing investigations into unidentified aerial phenomena (UAPs). The result is a novel strategy integrating a specially designed artificial intelligence program that was partially inspired by the physicists' own hunt for elusive dark matter. More popularly known as unidentified flying objects or UFOs, UAPs aren't necessarily considered as outlandish as they were decades ago. Setting aside the various theories that point to mysterious visitors from another planet, analysis increasingly centers on determining more worldly explanations.

The question of how the chemical composition of a protein--the amino acid sequence--determines its 3D structure has been one of the biggest challenges in biophysics for more than half a century. This knowledge about the so-called "folding" of proteins is in great demand, as it contributes significantly to the understanding of various diseases and their treatment, among other things. For these reasons, Google's DeepMind research team has developed AlphaFold, an artificial intelligence that predicts 3D structures. A team consisting of researchers from Johannes Gutenberg University Mainz (JGU) and the University of California, Los Angeles, has now taken a closer look at these structures and examined them with respect to knots. We know knots primarily from shoelaces and cables, but they also occur on the nanoscale in our cells. Knotted proteins can not only be used to assess the quality of structure predictions but also raise important questions about folding mechanisms and the evolution of proteins.