New JWST images of abnormally well-developed galaxy cluster open up the “cosmic noon” frontier
Peer-Reviewed Publication
Updates every hour. Last Updated: 22-Oct-2026 04:16 ET (22-Oct-2026 08:16 GMT/UTC)
A stunningly concentrated and hefty galaxy cluster, from a time in the universe’s history when such massive structures aren’t expected to have fully formed yet, is challenging cosmic evolution theories. Across a series of three recent papers, a team led by researchers from IPAC—a science and data center for astrophysics and planetary science at Caltech—have revealed that the cluster is the most distant example of strong gravitational lensing with a galaxy cluster. The new results, based on observations from NASA’s James Webb Space Telescope (JWST), were presented in a press conference on June 17, 2026 at the 248th meeting of the American Astronomical Society.
The University of Louisville, UofL Health and Kosair for Kids today celebrated the grand opening and ribbon cutting of the newly expanded Kosair for Kids Center for Pediatric NeuroRecovery, a transformative milestone in pediatric rehabilitation, research and care. The 13,631-square-foot, state-of-the-art facility brings clinical care, therapy and research together in one space, creating a first-of-its-kind environment designed to accelerate recovery and expand access for children with spinal cord injuries and other neurological conditions.
Astronomers using the Atacama Large Millimeter/submillimeter Array (ALMA), with help from a ‘natural telescope’ formed by gravity, have identified the source of a neutrino burst. The team expected a supermassive black hole to be the engine driving the remarkably bright galaxy. Instead, the team found that the galaxy was driven by vigorous star formation. This result provides important observational evidence to help explain the mysterious origin of cosmic neutrinos.
A research team led by Qian-Yuan Tang from Hong Kong Baptist University and Weitong Ren from Wenzhou Institute, University of Chinese Academy of Sciences, has reviewed how artificial intelligence is shifting protein science from task-driven prediction toward principle-oriented discovery. They introduced a new concept of AI functioning as an observatory to explore the complex organization of proteins. Moving beyond mere prediction, this perspective leverages AI-derived signals to uncover underlying physical constraints, evolutionary patterns, and functional principles that shape protein structures and dynamics. By viewing AI models as tools for systematic observation, researchers can decode the organizational principles of proteins-paving the way for more informed bioengineering and therapeutic strategies.