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Researchers with support from the U.S. National Science Foundation published a global benchmark of microplastic distribution in the ocean, revealing thousands of plastic specks even at the extreme depths of the Mariana Trench.

The study’s findings show that not only could fisheries take an economic hit, but humans could be at risk for exposure to contaminated seafood.

The team synthesized data from nearly 2,000 ocean sampling stations, mostly in northern ocean waters near larger populations between 2014 and 2024. “The discovery that microplastics are not just floating on the sea surface but also form a plastic smog, throughout the depths of the ocean, was surprising and concerning,” said Aron Stubbins, an author on the paper and professor at Northeastern University.

Abundant microplastic materials smaller than 5 micrometers — or about 100 times less than the width of a human hair — may be eaten by zooplankton, which in turn feed larger marine animals. Microplastics can disrupt marine food chains, causing health declines and potential drops in populations for fish and other marine creatures.

“Even when we are studying what we think of as completely natural processes in the ocean, we have to be aware of humankind’s influence,” said Henrietta Edmonds, an NSF program director.

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For the first time, scientists have used Earth-based telescopes funded by the U.S. National Science Foundation to look back over 13 billion years and measure how the first stars in the universe affected light emitted from the Big Bang. Using the NSF Cosmology Large Angular Scale Surveyor (NSF CLASS) telescopes in northern Chile, astrophysicists have measured this polarized microwave light to create a clearer picture of one of the least understood epochs in the history of the universe, the cosmic dawn.

The NSF CLASS telescopes are uniquely designed to detect the large-scale fingerprints left by the first stars in the relic Big Bang light — a feat that previously had only been accomplished by instruments in space. The findings will help better define signals coming from the residual glow of the Big Bang, or the cosmic microwave background, and form a clearer picture of the early universe. The research is led by Johns Hopkins University and The University of Chicago and published in The Astrophysical Journal.

“No other ground-based experiment can do what NSF CLASS is doing,” says Nigel Sharp, program director in the NSF Division of Astronomical Sciences, which has supported NSF CLASS for over 15 years. “The CLASS team has greatly improved measurement of the cosmic microwave polarization signal, and this impressive leap forward is a testament to the scientific value produced by

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With support from the U.S. National Science Foundation, researchers at the University of Houston have captured the dynamics of microscopic cholesterol crystal formation on video for the first time. Understanding these mechanisms could help scientists develop more effective treatments for managing high cholesterol, a condition that affects 25 million adults in the U.S., according to the U.S. Centers for Disease Control and Prevention. A better understanding of crystal formation could also enhance optoelectronics, which are electronic devices that work by controlling and sensing light.

NSF-supported researchers Jeffrey Rimer and Peter Vekilov are known for their work in crystal engineering and therapeutics that help prevent crystallization in human diseases. Their latest achievement shows the fundamental layered process involved in crystal formation in environments that mimic the human body. This is the first time anyone has taken images of the surface growth of cholesterol crystals in real time at near-molecular resolution. The study was published in the Proceedings of the National Academy of Science.

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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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