The researchers note that the findings show a relationship, not proof that vitamin D directly reduces tau levels or lowers the risk of dementia.

“These results suggests that higher vitamin D levels in midlife may offer protection against developing these tau deposits in the brain and that low vitamin D levels could potentially be a risk factor that could be modified and treated to reduce the risk of dementia,” said study author Martin David Mulligan, MB BCh BAO, of the University of Galway in Ireland. “Of course, these results need to be further tested with additional studies.”

Long-Term Study Tracks Vitamin D and Brain Biomarkers

The study followed 793 adults who were an average of 39 years old and free of dementia at the beginning. Researchers measured each participant’s blood vitamin D level at the start of the study.

About 16 years later, participants underwent brain scans to evaluate levels of tau and amyloid beta proteins, both of which are considered biomarkers of Alzheimer’s disease. A vitamin D level above 30 nanograms per milliliter (ng/mL) was classified as high, while levels below that threshold were considered low.

Overall, 34% of participants had low vitamin D levels, and only 5% reported taking vitamin D supplements.

Higher Vitamin D Linked to Lower Tau Protein

After accounting for factors such as age, sex and symptoms of depression, the researchers found that higher vitamin D levels were associated with lower levels of tau protein years later.

However, vitamin D levels were not linked to the amount of amyloid beta protein in the brain.

“These results are promising, as they suggest an association between higher Vitamin D levels in early middle-age and lower tau burden on average 16 years later,” Mulligan said. “Mid-life is a time where risk factor modification can have a greater impact.”

Study Limitations and Need for Further Research

One limitation of the study is that vitamin D levels were measured only once rather than tracked over time.

Highlights:

• People with higher vitamin D levels in midlife had lower levels of tau protein later on, a key marker linked to Alzheimer’s disease
• The study shows a link, but it does not prove that vitamin D directly reduces dementia risk
• Researchers found no connection between vitamin D levels and amyloid beta, another Alzheimer’s biomarker
• Further research is needed to confirm these findings and better understand the role of vitamin D in brain health

The study was supported by the National Institute on Aging, National Institute of Neurological Disorders and Stroke, Irish Research Council and Health Research Board of Ireland.

For years, scientists believed that the rapid rise of diverse and complex animals, known as the Cambrian explosion, began around 535 million years ago. This period marked a dramatic shift from simple organisms to a wide variety of more advanced life forms. The new study now indicates that this transformation started at least 4 million years earlier, during the late Ediacaran period.

Lead author Dr. Gaorong Li (Yunnan University at the time of the study, now Museum of Natural History, Oxford University), said: “Our discovery closes a major gap in the earliest phases of animal diversification. For the first time, we demonstrate that many complex animals, normally only found in the Cambrian, were present in the Ediacaran period, meaning that they evolved much earlier than previously demonstrated by fossil evidence.”

Jiangchuan Biota Fossils Show Early Animal Diversity

The fossils were uncovered in the Jiangchuan^[1] Biota in Yunnan Province, where researchers collected more than 700 specimens dating from 554 to 539 million years ago. This site reveals a rich and varied Ediacaran ecosystem, including previously unknown species as well as animals once thought to appear only later in the Cambrian.

Among the most important findings are fossils believed to be the oldest known relatives of deuterostomes, a major group that includes vertebrates such as humans and fish. These discoveries extend the fossil record of this group back into the Ediacaran Period for the first time.

The collection also includes early relatives of starfish and their close counterparts, the acorn worms (the Ambulacraria^[2]). These organisms had U-shaped bodies and were anchored to the seafloor by a stalk. Tentacles near their heads were likely used to capture food.

Co-author Dr. Frankie Dunn (Museum of Natural History, Oxford University) said: “The presence of these ambulacrarians in the Ediacaran period is really exciting. We have already found fossils which are distant relatives of starfish and sea cucumbers and are looking for more. The discovery of ambulacrarian fossils in the Jiangchuan biota also means that the chordates — animals with a backbone — must also have existed at this time.”

Strange Creatures and Transitional Ecosystems

Other fossils include worm-like bilaterian animals (having bilateral symmetry), some showing complex feeding strategies, along with rare specimens thought to represent early comb jellies.

Many of the fossils display unusual combinations of features, such as tentacles, stalks, attachment discs, and feeding structures that could be turned inside out. These combinations do not match any known species from either the Ediacaran or Cambrian periods. “For instance, one specimen looks a lot like the sand worm from Dune!” Dr. Dunn added.

Co-author Associate Professor Luke Parry (Department of Earth Sciences, Oxford University) added: “This discovery is extremely exciting because it reveals a transitional community: the weird world of the Ediacaran giving way to the Cambrian, the following time period where the animals are much easier to place in groups that are alive today. When we first saw these specimens, it was clear that this was something totally unique and unexpected.”

Solving a Long-Standing Evolution Mystery

The findings help answer a long-standing question in evolutionary biology. Previous genetic studies and fossil traces suggested that many animal lineages existed before the Cambrian explosion. However, clear fossil evidence from this earlier period had been largely missing until now.

Exceptional Preservation Reveals Hidden Details

Unlike most Ediacaran fossil sites, which preserve organisms as simple impressions in sandstone, the Jiangchuan Biota fossils are preserved as carbonaceous films. This type of preservation is more commonly associated with famous Cambrian fossil sites such as the Burgess Shale in Canada. It allows scientists to see fine details, including feeding structures, digestive systems, and organs related to movement.

Co-author Associate Professor Ross Anderson (Museum of Natural History, Oxford University) said: “Our results indicate that the apparent absence of these complex animal groups from other Ediacaran sites may reflect differences in preservation rather than true biological absence. Carbonaceous compressions like those at Jiangchuan are rare in rocks of this age, meaning that similar communities may simply not have been preserved elsewhere.”

Years of Fieldwork Lead to Breakthrough Discovery

The fossils were found by a research team at Yunnan University, led by Professor Peiyun Cong and Associate Professor Fan Wei. The group spent nearly a decade searching for diverse Ediacaran animal fossils. Although fossils had previously been discovered in eastern Yunnan, they were limited to algae and did not include animal remains.

Associate Professor Fan said: “After years of fieldwork, we finally found several sites with the right conditions where animal fossils are preserved together with the abundant algae.”

Professor Feng Tang from the Chinese Academy of Geological Science, Beijing, whose earlier work helped guide the research, said: “The new fossils provide the most compelling evidence for the presence of diverse bilaterian animals at the end of the Ediacaran, evidence people have searched for across decades.”

Notes

1. Pronounced ‘jing-choo-an.’
2. Ambulacraria, from the latin ambulacrum, meaning “a walk planted with trees.”

New research led by Craig Walton, a postdoc at the Centre for Origin and Prevalence of Life at ETH Zurich, and ETH Zurich professor Maria Schönbächler shows that these elements must already be available in the right amounts when a planet’s core forms. “During the formation of a planet’s core, there needs to be exactly the right amount of oxygen present so that phosphorus and nitrogen can remain on the surface of the planet,” explains Walton, lead author of the study. On Earth, that appears to have happened about 4.6 billion years ago, giving our planet an unusually fortunate chemical starting point. The result could influence how scientists search for life beyond Earth.

How Planet Core Formation Affects Habitability

Planets begin as bodies of molten rock. As they form, their materials separate by weight. Heavy metals such as iron sink inward and create the core, while lighter material remains above and eventually becomes the mantle and later the crust.

Oxygen levels during this stage are critical. If there is too little oxygen when the core forms, phosphorus bonds with heavy metals such as iron and gets pulled down into the core. Once that happens, it is no longer available in the parts of the planet where life might develop. If there is too much oxygen, phosphorus stays in the mantle, but nitrogen becomes more likely to escape into the atmosphere and be lost.

The Chemical Goldilocks Zone

Using extensive modeling, Walton and his co-authors found that both phosphorus and nitrogen remain in the mantle in large enough amounts only within a very narrow range of moderate oxygen conditions. They describe this as a chemical Goldilocks zone.

“Our models clearly show that the Earth is precisely within this range. If we had had just a little more or a little less oxygen during core formation, there would not have been enough phosphorus or nitrogen for the development of life,” says Walton.

The team also found that other planets, including Mars, formed under oxygen conditions outside this Goldilocks zone. On Mars, that meant more phosphorus in the mantle than on Earth, but less nitrogen, producing difficult conditions for life as we know it.

A New Way to Search for Life Beyond Earth

These findings may change how scientists think about habitability. So far, much of the focus has been on whether a planet has water. Walton and Schönbächler argue that this is not enough.

A planet may have water and still be chemically unfit for life from the very beginning. If oxygen levels were wrong while the core was forming, the planet may never have kept enough phosphorus and nitrogen in the places where life could use them.

Why Sun-Like Stars May Matter Most

Astronomers may be able to estimate these chemical conditions by studying other solar systems with large telescopes. The oxygen available during planet formation depends on the chemical makeup of the host star. Because planets form mostly from the same material as their star, the star’s composition helps shape the chemistry of the entire planetary system.

That means solar systems whose chemistry is very different from ours may be poor candidates in the search for life. “This makes searching for life on other planets a lot more specific. We should look for solar systems with stars that resemble our own Sun,” says Walton.

The findings, published in The Astronomical Journal, come from an international team led by Caleb Cañas of NASA’s Goddard Space Flight Center, with contributions from Carnegie Science’s Shubham Kanodia and others.

A Giant Planet Orbiting a Small Star

TOI-5205 b is about the size of Jupiter but orbits a much smaller star, one that is roughly four times Jupiter’s size and only about 40 percent as massive as the Sun. When the planet passes in front of its star in an event known as a “transit,” it blocks about six percent of the star’s light.

During these transits, astronomers used spectrographs to break the starlight into its component colors. This technique allows them to identify the chemical makeup of the planet’s atmosphere and gain insight into how it formed and evolved alongside its host star.

A Puzzle for Planet Formation Theories

Planets typically form within a rotating disk of gas and dust surrounding a young star. While this process is widely accepted, systems like TOI-5205 b challenge existing models. Massive planets orbiting small, cool stars at close distances are difficult to explain using current theories.

To investigate these unusual systems, Kanodia, Cañas, and Jessica Libby-Roberts of the University of Tampa are leading JWST’s largest Cycle 2 exoplanet program, Red Dwarfs and the Seven Giants. This project focuses on rare worlds like TOI-5205 b, often referred to as GEMS (for giant exoplanets around M dwarf stars).

JWST Detects Unexpected Atmospheric Chemistry

TOI-5205 b was first confirmed in 2023, when Kanodia led follow-up observations based on data from NASA’s Transiting Exoplanet Survey Satellite (TESS). Now, researchers have used JWST to examine its atmosphere in detail for the first time.

After observing three transits, the team encountered an unexpected result. The planet’s atmosphere contains significantly fewer heavy elements compared to hydrogen than Jupiter does. Even more surprising, its metallicity is lower than that of its own host star, making it unlike any giant planet studied so far.

The data also revealed the presence of methane (CH₄) and hydrogen sulfide (H₂S) in the atmosphere.

Heavy Elements May Be Hidden Deep Inside

To better understand these findings, researchers Simon Muller and Ravit Helled at the University of Zurich used advanced models of planetary interiors. Their results suggest that the planet as a whole is about 100 times more metal rich than its atmosphere appears to be.

“We observed much lower metallicity than our models predicted for the planet’s bulk composition, which is calculated from measurements of a planet’s mass and radius. This suggests that its heavy elements migrated inward during formation and now its interior and atmosphere are not mixing,” Kanodia explained. “In summary, these results suggest a very carbon-rich, oxygen-poor planetary atmosphere.”

The GEMS Survey and Future Research

This work is part of the broader GEMS Survey, which aims to study transiting giant planets around M-dwarf stars to better understand their formation, internal structure, and atmospheres. The research team includes Carnegie astronomers Peter Gao, Johanna Teske, and Nicole Wallack, along with former Carnegie postdoctoral fellow Anjali Piette, now at the University of Birmingham.

Additional contributors include researchers from institutions such as Johns Hopkins University’s Applied Physics Laboratory, the Academia Sinica Institute of Astronomy and Astrophysics, Catholic University, the University of Maryland, Caltech, NASA Goddard, the University of St. Andrews, Penn State University, the University of California Irvine, the Tata Institute of Fundamental Research, and the University of Amsterdam.

Correcting for Starspots Improves Accuracy

The team also accounted for interference caused by starspots on the host star. These dark, active regions can distort observations by brightening certain wavelengths and hiding parts of the atmospheric signal.

By correcting for these effects, the researchers improved the accuracy of their measurements. Wallack and Kanodia are now refining this approach in a newer JWST project focused on the same system. Their work could help future studies of planets orbiting active stars produce more reliable results.

This rapid growth has raised concerns about sustainability. In response, researchers at a School of Engineering have created a proof-of-concept AI system designed to be far more efficient. Their approach could reduce energy use by up to 100 times while also improving performance on tasks.

A Hybrid Approach Called Neuro-Symbolic AI

The research comes from the laboratory of Matthias Scheutz, Karol Family Applied Technology Professor. His team is developing neuro-symbolic AI, which combines traditional neural networks with symbolic reasoning. This method mirrors how people approach problems by breaking them into steps and categories.

The work will be presented at the International Conference of Robotics and Automation in Vienna in May and will appear in the conference proceedings.

Teaching Robots to See, Understand, and Act

Unlike familiar large language models (LLMs) such as ChatGPT and Gemini, the team focuses on AI systems used in robotics. These systems are known as visual-language-action (VLA) models. They extend LLM capabilities by incorporating vision and physical movement.

VLA models take in visual data from cameras and instructions from language, then translate that information into real-world actions. For example, they can control a robot’s wheels, arms, or fingers to complete a task.

Why Traditional AI Struggles With Simple Tasks

Conventional VLA systems rely heavily on data and trial-and-error learning. If a robot is asked to stack blocks into a tower, it must first analyze the scene, identify each block, and determine how to place them correctly.

This process often leads to mistakes. Shadows may confuse the system about a block’s shape, or the robot may place pieces incorrectly, causing the structure to collapse.

These errors are similar to the problems seen in LLMs. Just as robots can misplace blocks, chatbots can generate false or misleading outputs. Examples include fabricating legal cases or producing images with unrealistic details such as extra fingers.

How Symbolic Reasoning Improves Accuracy and Efficiency

Symbolic reasoning offers a different strategy. Instead of relying only on patterns from data, it uses rules and abstract concepts such as shape and balance. This allows the system to plan more effectively and avoid unnecessary trial and error.

“Like an LLM, VLA models act on statistical results from large training sets of similar scenarios, but that can lead to errors,” said Scheutz. “A neuro-symbolic VLA can apply rules that limit the amount of trial and error during learning and get to a solution much faster. Not only does it complete the task much faster, but the time spent on training the system is significantly reduced.”

Strong Results in Puzzle Tests

The researchers tested their system using the Tower of Hanoi puzzle, a classic problem that requires careful planning.

The neuro-symbolic VLA achieved a 95% success rate, compared with just 34% for standard systems. When given a more complex version of the puzzle that it had not encountered before, the hybrid system still succeeded 78% of the time. Traditional models failed every attempt.

Training time also dropped sharply. The new system learned the task in only 34 minutes, while conventional models required more than a day and a half.

Massive Energy Savings in Training and Use

Energy consumption was reduced dramatically as well. Training the neuro-symbolic model required only 1% of the energy used by a standard VLA system. During operation, it used just 5% of the energy needed by conventional approaches.

Scheutz compared this inefficiency to everyday AI tools. “These systems are just trying to predict the next word or action in a sequence, but that can be imperfect, and they can come up with inaccurate results or hallucinations. Their energy expense is often disproportionate to the task. For example, when you search on Google, the AI summary at the top of the page consumes up to 100 times more energy than the generation of the website listings.”

The Growing Strain of AI on Power Infrastructure

As AI adoption accelerates across industries, demand for computing power continues to climb. Companies are building increasingly large data centers, some of which require hundreds of megawatts of electricity. That level of consumption can exceed the needs of entire small cities.

This trend has sparked a race to expand infrastructure, raising concerns about long-term energy limits.

A More Sustainable Path for AI

The researchers suggest that current approaches based on LLMs and VLAs may not be sustainable in the long run. While these systems are powerful, they consume large amounts of energy and can still produce unreliable results.

In contrast, neuro-symbolic AI offers a different direction. By combining learning with structured reasoning, it may provide a more efficient and dependable foundation for future AI systems.

Scientists at UC San Francisco have now pinpointed a protein that appears to drive much of this decline.

FTL1 Emerges as a Key Driver of Brain Aging

To understand what changes with age, the researchers tracked shifts in genes and proteins in the hippocampus of mice over time. Among everything they examined, only one stood out as consistently different between young and old animals. That protein is called FTL1.

Older mice showed higher levels of FTL1. At the same time, they had fewer connections between neurons in the hippocampus and performed worse on cognitive tests.

How FTL1 Alters Brain Function

When the team boosted FTL1 levels in young mice, the effects were striking. Their brains began to look and function more like those of older mice, and their behavior reflected this shift.

Lab experiments revealed more detail. Nerve cells engineered to produce high amounts of FTL1 developed simplified structures, forming short, single extensions instead of the complex, branching networks seen in healthy cells.

Reversing Memory Decline by Lowering FTL1

The most surprising result came when researchers reduced FTL1 in older mice. The animals showed clear signs of recovery. Connections between brain cells increased, and their performance on memory tests improved.

“It is truly a reversal of impairments,” said Saul Villeda, PhD, associate director of the UCSF Bakar Aging Research Institute and senior author of the paper, which was published in Nature Aging. “It’s much more than merely delaying or preventing symptoms.”

Metabolism Link Points to New Treatments

Further experiments showed that FTL1 also affects how brain cells use energy. In older mice, higher levels of the protein slowed cellular metabolism in the hippocampus. However, when researchers treated these cells with a compound that boosts metabolism, the negative effects were prevented.

Hope for Future Brain Aging Therapies

Villeda believes these findings could pave the way for treatments that target FTL1 and counter its effects in the brain.

“We’re seeing more opportunities to alleviate the worst consequences of old age,” he said. “It’s a hopeful time to be working on the biology of aging.”

Authors and Funding

Other UCSF authors are Laura Remesal, PhD, Juliana Sucharov-Costa, Karishma J.B. Pratt, PhD, Gregor Bieri, PhD, Amber Philp, PhD, Mason Phan, Turan Aghayev, MD, PhD, Charles W. White III, PhD, Elizabeth G. Wheatley, PhD, Brandon R. Desousa, Isha H. Jian, Jason C. Maynard, PhD, and Alma L. Burlingame, PhD. For all authors see the paper.

This work was funded in part by the Simons Foundation, Bakar Family Foundation, National Science Foundation, Hillblom Foundation, Bakar Aging Research Institute, Marc and Lynne Benioff, and the National Institutes of Health (AG081038, AG067740, AG062357, P30 DK063720). For all funding see the paper.

Manipulating light at extremely small scales is key to advancing modern technology. As traditional electronics begin to reach their limits, photonics offers an alternative by using light instead of electrons to carry information. Because photons move faster and do not have mass like electrons, devices based on light could become both quicker and smaller, opening the door to more powerful and compact technologies.

The Challenge of Light’s Wavelength

Light behaves both as a particle and as a wave, and this wave nature introduces a limitation. Each type of light has a wavelength, which determines how small a structure can be while still controlling it effectively. Visible light has wavelengths of several hundred nanometers, while infrared light extends to a micrometer or more. This raises an important question: can light be confined in structures smaller than its own wavelength?

The research team demonstrated that this is indeed possible. By engineering a subwavelength grating, they were able to trap infrared light within a layer only 40 nanometers thick. This structure consists of closely spaced parallel strips that interact with light similarly to a prism. When these strips are positioned closer together than the wavelength of light, the grating can act like a near-perfect mirror while also holding the light inside a very small volume.

Why Molybdenum Diselenide Works So Well

Earlier versions of such gratings, made from materials like silicon or gallium compounds, required thicknesses of several hundred nanometers to function effectively. Reducing their size caused them to lose their ability to confine light. The key difference in this new approach is the use of molybdenum diselenide, which has a much higher refractive index. In simple terms, light slows down more inside this material than in others. While light slows by about 1.5 times in glass and roughly 3.5 times in silicon or gallium arsenide, it slows by about 4.5 times in MoSe₂. This strong slowing effect allows the structure to shrink dramatically while still trapping light efficiently, resulting in a layer more than a thousand times thinner than a human hair.

Turning Infrared Light Into Blue Light

MoSe₂ also brings additional advantages. Like graphene, it forms layered structures, but unlike graphene, it is a semiconductor. It also exhibits nonlinear optical behavior, including a process known as third harmonic generation. In this process, three infrared photons combine into one photon with a higher frequency, effectively converting infrared light into visible blue light. Because the grating strongly concentrates infrared light, this conversion becomes much more efficient. The researchers found that the effect is more than 1,500 times stronger compared to a flat layer of the same material.

Another major advance lies in how the material was produced. Previously, thin layers of MoSe₂ were created using exfoliation — a method similar to peeling layers off a crystal with adhesive tape. While simple, this technique is inconsistent and limited to very small areas, typically around ten square micrometers, which is not suitable for real-world devices.

To overcome this, the team used molecular beam epitaxy (MBE), a well-established method for growing semiconductor layers. This approach allowed them to produce large, uniform MoSe₂ films spanning several square inches. Despite this large size, the layer maintained a thickness of just 40 nanometers, giving it an extreme aspect ratio. For comparison, the thickness-to-size ratio of this layer is about one to a million, while a typical A4 sheet of paper has a ratio closer to 1:2000.

Toward Practical Photonic Applications

These results suggest that molybdenum diselenide produced in this way could significantly change how light is controlled in future technologies. Structures no longer need to be thick to manipulate light effectively. Instead, extremely thin layers can perform the same function, and in some cases even better. Because the production method is scalable, the path toward real-world applications, such as photonic integrated circuits, is becoming increasingly realistic.

Funding and Support

The research was funded by the National Science Centre under projects OPUS 2020/39/B/ST7/03502 and 2021/41/B/ST3/04183, with European Union funds under ERC-ADVANCED grant No. 101053716, the Foundation for Polish Science under project ENG.02.01-IP.05-T004/23, and by the University of Warsaw under the Excellence Initiative – Research University (IDUB) New Ideas in Priority Research Areas II No. 501-D111-20-2004310 titled “Ultrathin subwavelength gratings based on dichalcogenides.”