A study appearing Monday, March 31 in Nature Physics presents a striking example of cooperative organization among cells as a potential force in the evolution of multicellular life. Based on the fluid dynamics of cooperative feeding by Stentor, a relatively giant unicellular organism, the study originated from the Marine Biological Laboratory (MBL), Woods Hole, Mass.

Philip Kurian, a theoretical physicist and founding director of the Quantum Biology Laboratory (QBL) at Howard University in Washington, D.C., has used the laws of quantum mechanics, the fundamental physics of computation, and the QBL’s discovery of cytoskeletal filaments exhibiting quantum optical features, to set a drastically revised upper bound on the computational capacity of carbon-based life in the entire history of Earth. Published as a single-author research article in Science Advances, Kurian’s latest work conjectures a relationship between this information-processing limit and that of all matter in the observable universe.

A team of researchers from Arizona State University, the U.S. Army Research Laboratory (ARL), Lehigh University and Louisiana State University has developed a groundbreaking high-temperature copper alloy with exceptional thermal stability and mechanical strength.

The research team’s findings on the new copper alloy, published in prestigious journal Science, introduce a novel bulk Cu-3Ta-0.5Li nanocrystalline alloy that exhibits remarkable resistance to coarsening and creep deformation, even at temperatures near its melting point.

A powerful AI model called Deep Novel Mutation Search (DNMS) predicts virus mutations more accurately and efficiently than traditional, time-consuming lab experiments. Focused on the SARS-CoV-2 spike protein, the model uses a specialized protein language model fine-tuned to understand the virus's specific “language.” DNMS can predict mutations that cause small, functional changes – crucial for viruses like SARS-CoV-2, which evolve through subtle adjustments to maintain function. This approach promises to enhance virus tracking and public health by predicting mutations more accurately and quickly.