Exposure to Streptococcus pyogenes (Strep A) that causes mild or no symptoms can trigger the body’s immune response and naturally build protection, potentially solving a nearly 100-year-old mystery of immunity.

New Griffith University research, with the help of clinical scientists from the Murdoch Children’s Research Institute (MCRI), investigated how immunity developed over time as infection rates declined with age, suggesting progressive immune protection. The paper “Subclinical exposure to Streptococcus pyogenes drives the development of long-lived homologous immunity” has been published in Nature Communications.

Strep A is a common bacterium that can cause painful tonsillitis and impetigo in young children and teenagers...

A popular myth about black holes is that they act like giant cosmic vacuum cleaners, sucking in everything around them. But Wladimir Lyra’s research found a new mechanism around supermassive black holes that is more like a cosmic nursery, giving birth to planets more massive than Jupiter.

“We’re finding objects that are a thousand times the mass of the Earth, but built of pure dust,” Lyra said. “And not only that, but also some of these objects are approaching the mass of the sun.”

Lyra, an associate professor of astronomy at New Mexico State University, began this line of research as a postdoctoral fellow collaborating with Barry McKernan, Saavik Ford and Mordecai-Mark Mac Low at the American Museum of Natural History in 2010.

Bhupendra Mishr...

A new study of sunscreens, baby lotions, shampoos, soaps and other everyday products found that nearly all contained chemicals not disclosed on their labels. Most contained at least one unlabeled chemical with known or suspected health hazards, and one in four contained a chemical that contradicted claims on the package, including “phthalate-free” products that contained phthalates. The research is published in Environment & Health.

“We found undisclosed harmful chemicals in products claiming to be free of them,” said Jenna Hua, senior author of the study and founder of the Million Marker Research Institute...

Artificial intelligence models are jacks of many trades, including writing, generating images, and creating 3D models. But they aren’t as helpful when it comes to testing robots or designs for vehicles in diverse environments, since they don’t understand physics as well as they do pixels or text.

To build an AI system that can reliably simulate a variety of physical scenarios, engineers need physics data at a scale that is not yet feasible. That’s because it is very time-consuming to generate even a few data points that neural networks can understand. They rely on algorithms called “numerical solvers” to calculate physical properties at different points of a 3D shape...