New machine learning models developed by University of South Australia (UniSA) researchers could help clinicians identify when patients can successfully stop long-term antidepressant use.

Kimberlites—carrot-shaped volcanic pipes that erupt from mantle depths greater than 150 km—have long fascinated geologists as windows into the deep Earth. Their mantle-derived melt ascends rapidly through the mantle and crust, with some estimates suggesting ascent rates of up to 80 miles per hour before kimberlites erupt violently at the surface. Along the way, the magma captures xenoliths and xenocrysts, fragments of the rocks encountered on its path. Over 70% of the world’s diamonds are mined from these unique volcanic structures. Yet despite decades of study, scientists are still working to understand how exactly kimberlites erupt from deep in Earth’s mantle to the surface. In a study published this month in the journal Geology, Anzulović and colleagues from the University of Oslo have taken a major step toward solving the puzzle.

Backed by the combined expertise of three USC schools, scientists are developing a new drug aimed at a previously unexplored biological target in Alzheimer’s disease, aided by an $8 million grant from the National Institutes of Health. The team, led by Hussein Yassine of the Keck School of Medicine of USC, is investigating why some carriers of the APOE4 gene — the strongest genetic risk factor for Alzheimer’s — develop dementia while others remain cognitively healthy. His lab has identified an enzyme that predisposes the brain to inflammation and the research team is now working to find a drug that can block it without harmful side effects. Their work points to an enzyme which breaks down protective omega-3 fatty acids in the brain and triggers damaging inflammation.