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Neurodegenerative diseases like Alzheimer’s are a growing concern in the U.S., with over 7 million Americans living with Alzheimer’s disease today. By 2060, that number is expected to grow, affecting nearly 13 million people. These diseases are not only hard on individuals and families, but are costly, with more than $230 billion spent in the U.S. each year in caregiving alone. As the population ages, the need for new ways to detect and address the silent emergence of these diseases has never been more urgent. 

New artificial intelligence predictive models used in brain research may provide a way to better predict how a person’s brain ages over time, helping doctors recognize warning signs long before clinical symptoms surface. 

Supported by the U.S. National Science Foundation, a team of researchers led by Paul Bogdan, an associate professor in the University of Southern California Department of Electrical and Computer Engineering, has developed a cutting-edge AI system capable of generating a future MRI of a person’s brain from just a single scan. This technology opens the door to identifying subtle changes that may signal the earliest stages of neurodegenerative diseases — potentially years before traditional diagnostic methods could detect them.

To build the tool, the team combined two advanced AI techniques: a 3D diffusion model and a ControlNet, which allow the system to “control” or guide image generation

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The U.S. National Science Foundation today announced a new funding opportunity to support research and technology development that will improve the next generation of wireless communication systems known as NextG.     In collaboration with industry, other government agencies, and international partners, the NSF Verticals-enabling Intelligent NEtwork  Systems (NSF VINES) program will invest up to $100 million to accelerate performance and capabilities of next-generation (NextG) advanced intelligent network systems  spanning the user-edge-core-cloud continuum. 

“NSF VINES will enhance U.S. competitiveness in advanced telecommunications technologies, including NextG wireless telecommunications and emerging potential NextG vertical industries, and prepare the American workforce for jobs available now and in the future,” said Brian Stone, performing the duties of the NSF Director.

“This important investment from NSF, in collaboration with industry and other government agencies, will help strengthen U.S. leadership and ensure the American people reap the benefits in areas such as self-driving cars, advanced manufacturing, energy infrastructure, and beyond,” said Dr. Lynne Parker, Principal Deputy Director of The White House Office of Science and Technology Policy. 

NSF VINES is in partnership with several major industry organizations and U.S. federal agencies, including Ericsson, Intel, Qualcomm, the U.S. Department of Homeland Security, U.S. Department of Defense Office of the Under Secretary for Research and Engineering, and U.S. Department of Commerce National Institute of Standards and Technology, as well as international partners from

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Each year, preeclampsia—a life-threatening pregnancy complication—affects nearly 1 in 25 expectant mothers in the United States. Emerging suddenly after 20 weeks of pregnancy, it can lead to dangerously high blood pressure, premature birth, and long-term health issues for both mother and baby. Despite its severity, the root causes of preeclampsia remain poorly understood, and treatment options are limited.

Currently, the only effective treatment for preeclampsia is early delivery of the placenta, which often leads to premature birth and associated health risks for the baby. While researchers know the placenta plays a central role in the disease, the exact causes of its dysfunction remain unclear. This lack of understanding makes preeclampsia difficult to predict, prevent, or treat effectively.

Researchers at UC San Diego are tackling these challenges with help from NSF-supported computational resources. The team leveraged advanced computing systems like the San Diego Supercomputer Center’s Expanse to conduct large-scale RNA sequencing analysis to compare placental tissue from healthy and preeclamptic pregnancies—processing terabytes of next-generation sequencing data to identify genes that behave differently in the disease.

Expanse also enabled the team to develop a model system of preeclampsia using induced pluripotent stem cells (iPSCs), which allows scientists to recreate the disease in the lab and observe how stress conditions like low oxygen affect placental development. By replicating these abnormal conditions, the team identified biological pathways—like inflammation and

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