Fragile X syndrome affects roughly 100,000 Americans and is the most common inherited cause of intellectual disability. The disorder stems from changes affecting the FMR1 gene, which disrupts production of FMRP, a protein essential for normal brain development and function. Without adequate FMRP, the brain’s neural circuits develop and operate abnormally, producing a constellation of symptoms that includes intellectual disability, difficulties with learning and memory, social and behavioral challenges, and unusual sensitivity to sensory stimuli such as sound and touch. Fragile X is also recognized as a major genetic contributor to autism spectrum disorder, making advances against the condition relevant far beyond its own patient population.

The central obstacle the collaboration hopes to overcome is one that has frustrated neurologists for decades: the blood-brain barrier. This highly selective interface between the bloodstream and brain tissue blocks the passage of most large molecules, including proteins, which means that even a perfectly designed therapeutic protein is useless if it cannot reach its target cells. Binder explained that Bowen’s FX Therapeutics has used protein engineering to develop versions of the Fragile X-related protein that can be administered systemically, meaning through the bloodstream, and still cross the blood-brain barrier. Once inside the brain, the engineered proteins are designed to replace the function of the protein that is missing or impaired in people with the disorder.

For Binder, the project represents a convergence of two research threads that have matured in parallel: his own years of work characterizing abnormal brain activity in Fragile X, and recent breakthroughs in protein delivery technology. He expressed astonishment at how far the field has come. According to Binder, his collaborators can now engineer a protein and get it into the brain and into cells, something that a few years ago would have seemed like science fiction. That capability, he suggested, transforms what was once a purely observational research program into one that can actively test a potential therapy.

The testing platform for the study is the Fragile X knockout mouse, a well-established animal model in which the gene responsible for the disorder has been removed. These mice exhibit several brain abnormalities that closely resemble those observed in people with Fragile X, including changes in how the brain processes sensory information and how it coordinates neural activity across regions. Because the model recapitulates key features of the human condition, it provides a rigorous preclinical setting in which a candidate therapy can be evaluated before any consideration of human trials.

Binder’s laboratory brings to the collaboration a particular strength in measuring brain activity in living animals, an expertise built over years of studying Fragile X and epilepsy. One of the lab’s principal tools is electroencephalography, or EEG, a technique that records electrical signals generated by neural populations. Rather than examining brain tissue in isolation, the team monitors the whole animal as it behaves and processes stimuli, with the goal of obtaining very high-quality brain recordings from the mice. This approach captures brain function in its natural, dynamic context, which is precisely where the symptoms of Fragile X manifest.

Critically, the lab has already identified specific EEG abnormalities in Fragile X mice, and those measurements now serve as a baseline for the therapeutic study. The logic of the experiment is elegant in its simplicity: if the engineered proteins are doing their job, the characteristic signatures of abnormal brain activity should diminish, and the electrical patterns of treated Fragile X mice should shift toward those of normal mice. Binder and Carrie Jonak, a research associate in the laboratory who generated the preliminary data supporting the grant application and will carry out much of the research, have a straightforward measure of success. As Binder put it, if the Fragile X mice after treatment begin to resemble the normal mice, and their physiology is essentially normalized, that would be a very significant result.

The pilot study is deliberately scoped as a first step rather than a definitive test of clinical benefit. It will not directly determine whether treated mice become better at learning or remembering, since cognitive and behavioral assessments fall outside the one-year project’s scope. However, the researchers argue that brain physiology is upstream of behavior: if the treatment corrects the electrical abnormalities in neural circuits, Binder said his team would predict that some of the associated cognitive and behavioral problems could also improve. In this way, EEG normalization serves as an early, quantifiable biomarker of therapeutic effect, potentially accelerating the path toward more comprehensive studies.

Beyond its scientific promise, the project is also a case study in how targeted foundation funding can bridge the gap between academic neuroscience and biotechnology. Binder framed the collaboration as an example of how foundation support can bring together complementary partners that would not otherwise connect. Bowen’s FX Therapeutics provides access to a promising therapeutic technology, while his laboratory contributes expertise in measuring brain activity in living animals. As he noted, academics would not necessarily have access to these kinds of therapeutics on their own. For a disorder that has resisted every conventional pharmacological approach, the combination of engineered proteins capable of crossing the blood-brain barrier and sensitive physiological readouts in a validated animal model offers a genuinely new strategy, and one whose first results could reshape expectations for treating Fragile X syndrome.

Subject of Research: Protein-based therapy research for Fragile X syndrome

Article Title: Testing a new approach to treating Fragile X

Article References: Testing a new approach to treating Fragile X. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: Fragile X syndrome, FMR1 gene, FMRP, protein engineering, blood-brain barrier, electroencephalography, mouse model, FRAXA Research Foundation, UC Riverside, neuroscience, autism spectrum disorder, biotechnology

The research was led by Stephen Kane, a UC Riverside astrophysicist who has spent much of his career probing the boundaries of planetary habitability. His starting point was the two leading explanations that scientists had previously floated. One held that Venus once had a moon that was obliterated by a massive impact. The other suggested that Venus simply never experienced the kind of giant collision that is thought to have spawned Earth’s moon roughly 4.5 billion years ago. Kane’s modeling shows that neither scenario is required to explain what we observe today. The slow, backward-turning spin of Venus is enough on its own to guarantee that any satellite would eventually be doomed.

To understand why, it helps to look at how Earth and its moon behave. Scientists can measure the Earth-moon distance with extraordinary precision because NASA’s Apollo 11 astronauts left mirrors on the lunar surface, allowing laser ranging from Earth. Those measurements reveal that the moon is receding from our planet at a rate of roughly four centimeters per year. The reason lies in Earth’s rotation. Our planet completes a spin in 24 hours, a comparatively brisk pace, and the energy of that rotation is transferred through tides raised in the oceans and the solid Earth to the moon. The result is a slow but relentless outward migration, a dynamic that has kept our satellite safely aloft for billions of years.

Venus presents the exact opposite situation. The planet takes 243 Earth days to complete a single rotation, making it the slowest-spinning world in the solar system. Rather than pushing a moon outward, that languid spin combined with the planet’s powerful gravity would cause a satellite to spiral inward toward a collision. Tidal forces that, on Earth, act as an escalator carrying the moon away from its planet instead act on Venus as a vise, tightening the orbit with every pass. Any moon Venus ever possessed would have been on a one-way descent from the moment it formed.

Kane tested this idea by writing computer models based on the physics of how planetary bodies interact through gravity. The first step was a crucial sanity check: he reproduced the evolution of Earth and its moon to confirm that the model accurately represented a system we know well. Only then did he turn to Venus, varying the planet’s rotation rate and the size of its hypothetical moons. He tested satellites with masses ranging from half to ten times the mass of Earth’s moon, a broad sweep designed to capture nearly any plausible scenario. In most simulations, the outcome was the same. The moon crashed into Venus. And, counterintuitively, the more massive the moon, the faster it fell.

The uniformity of the results surprised even the researcher. Kane described being shocked by the discovery, having assumed that such a wide range of scenarios would produce a variety of outcomes. Instead, every path led in the same direction, toward the surface of the planet. That consistency is what gives the finding its force. It means the absence of a moon at Venus does not demand a rare catastrophe or an unusual formation history. It follows naturally, almost inevitably, from the planet’s own rotation and gravity. Venus didn’t require a disaster to arrive at what we see today; the physics did the work on its own.

It is important to note what the study does and does not claim. The research does not prove that Venus ever had a moon. Kane believes it may have, but whether a satellite ever formed around the planet in the first place remains an open question, one that hinges on the details of Venus’s early history and its collisional past. What the study does establish is that if Venus had a moon, it could not have survived indefinitely. The slow spin of the planet would have sealed the satellite’s fate, converting any lunar companion into a devastating impact over time.

Finding physical evidence of such a collision would be difficult. Roughly 80 percent of Venus’s surface appears to be of similar age, the signature of a major resurfacing event about a billion years ago that wiped away much of the planet’s earlier geological record. Any surface scars from an ancient lunar impact would likely have been erased in that global renewal. The evidence, if it exists, may instead lie deep beneath the surface. On Earth, scientists believe the moon formed after a massive collision early in the planet’s history, and seismic studies have revealed unusual structures deep within our planet that may be remnants of that formative event. Similar measurements on Venus, probing the planet’s interior, could offer clues about whether it once absorbed a moon of its own.

The stakes of that question extend far beyond lunar archaeology. A moon crashing into Venus would have transferred enormous energy and angular momentum to the planet, potentially reshaping its rotation, its geology, and its climate. If Venus once hosted oceans or other conditions favorable to life, such an impact could have fundamentally altered the course of the planet’s evolution, perhaps helping to transform it from a potentially habitable world into the scorching inferno we observe today. In this sense, the fate of a hypothetical Venusian moon is entangled with one of the most enduring mysteries in planetary science: whether Earth’s nearest neighbor was ever capable of supporting life.

The implications reach out to other star systems as well. Scientists searching for potentially habitable worlds around distant stars often focus on planets that resemble Earth, and the presence of a large moon is frequently cited as a factor that could influence habitability. Earth’s moon drives the tides, may have helped keep the planet geologically active, and has profoundly shaped the evolution of life here. Yet scientists still do not know whether a large moon is strictly necessary for life. Kane’s own view is that there are benefits to having a moon, but that it is not required for habitability; the moon has clearly changed the way Earth has evolved through time, but its full importance remains uncertain. What his findings do suggest is that even planets capable of forming moons may not be able to keep them. Slowly rotating worlds could send their moons spiraling toward their surfaces, dramatically transforming the planets in the process. For astronomers weighing whether an Earth twin around another star has a moon, the answer may often be grim: if such planets do not rotate fast enough, their moons will crash down, and that impact would change the course of history for those worlds.

Subject of Research: The tidal evolution and likely demise of a hypothetical moon of Venus

Article Title: Venus ate its moon

Article References: Venus ate its moon. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: Venus, moon, tidal evolution, planetary science, Stephen Kane, The Astrophysical Journal, Earth-moon system, habitability, exoplanets, planetary rotation, giant impact, UC Riverside

The study, published in Physical Review Letters, was led by Bryan Shaddy, formerly an undergraduate at UC Riverside and now at the University of Southern California, together with UCR materials scientist Alex Greaney and Bhargav Rallabandi, associate professor of mechanical engineering at UCR. Their starting point was a recognition that Arctic sea ice is not the continuous sheet it appears to be from satellites or aircraft. It is a collection of individual slabs, known as floes, ranging in size from several meters to a few kilometers across. Winds push these floes across the ocean surface, causing them to drift and gradually spread apart, but as they move they also collide with their neighbors, and those collisions turn out to matter enormously.

“If you get a lot of ice floes together in the same place with some wind, they bump into each other and transfer energy to neighbors,” Rallabandi said. “We showed that that’s the only ingredient you need to explain these observations.” The claim is striking precisely because it is so economical. Rather than adding new forces or exotic atmospheric phenomena to close the gap between theory and measurement, the team found that the interactions among the floes themselves, driven by nothing more than ordinary wind, were enough to reproduce the anomalous behavior that has resisted explanation.

To test the idea, the researchers built a computer simulation that treats the ice somewhat like grains moving through a silo, with one crucial difference: these grains float on water and are pushed by turbulent winds. The model accounts for drag from the ocean as well as collisions among the floes, capturing the interplay between the external forcing that drives the ice and the internal contacts that redistribute its momentum. The silo analogy is more than a convenience. Granular materials flowing through a container are a classic problem in physics, and the mathematics of many small objects colliding while being pushed along has been studied intensively in that context. The team adapted that framework to the peculiar conditions of the polar ocean.

The real test came from data. The researchers compared their model’s predictions with measurements of sea ice in the Fram Strait, the passage between Greenland and the Norwegian archipelago of Svalbard through which Arctic ice travels toward the Atlantic Ocean. The Fram Strait is one of the main export routes for sea ice leaving the Arctic basin, which makes it an ideal natural laboratory for studying how floes move and disperse over long distances. Using measured local wind and ice conditions, and only one additional parameter that had little influence on the overall results, the model reproduced three previously puzzling observations: how quickly the ice spreads, the distribution of floe speeds, and how ice motion varies across timescales ranging from hours to days.

That a single tunable parameter sufficed is itself notable. Many geophysical models require extensive calibration to match observations, and each free parameter represents a degree of freedom that can mask missing physics. Here, the essential structure of the model was fixed by the collisional mechanics, and the observations fell into place. The reason collisions have such a large effect is that Arctic ice can be densely packed. In concentrated ice fields, floes run into their neighbors much more frequently than the wind changes. Each collision dissipates some of the energy supplied by the wind and shortens the distance a floe can travel freely before encountering another piece of ice. The result is a collective slowdown and a characteristic spread of speeds that no wind-only model can produce.

The implications reach well beyond settling an old puzzle. The amount of ocean covered by ice and the size of individual floes affect how frequently collisions occur, which in turn affects how rapidly the ice spreads. The study provides a physical framework for connecting such small-scale interactions to movement over much larger distances, linking the grain-scale mechanics of individual contacts to the basin-scale transport of the ice pack. As the Arctic warms and the ice cover thins and breaks into smaller pieces, those links could become central to predicting where the ice goes and how quickly it disperses.

The paper does not predict exactly how future warming will alter the destinations of Arctic ice, and the authors are careful on that point. But Rallabandi said the framework could ultimately help researchers investigate questions such as whether changing ice conditions allow floes to disperse more readily and reach warmer waters, where they could melt more quickly. That question sits at the heart of Arctic climate science: the fate of sea ice depends not only on how fast it melts in place but on where currents and winds carry it. A model grounded in the mechanics of collisions offers a way to explore how fragmentation of the ice pack feeds back into its own transport and loss.

The work could also prove useful for climate modeling at the global scale. Global models cannot individually track the enormous number of relatively small floes covering the Arctic; the computational cost would be prohibitive, and the smallest floes fall far below any practical grid resolution. A physics-based description of their collective behavior could help represent processes happening out of immediate view, replacing what would otherwise be an intractable accounting problem with a compact statistical description. For Rallabandi, part of the study’s value lies in demonstrating how a simple process can explain a complex real-world motion, a reminder that the right simplification can be more powerful than an accumulation of complications.

The underlying physics may extend well beyond sea ice. Any system involving many objects colliding while being driven by an unpredictable environment could behave similarly, and the paper points to possible applications including avalanches, landslides, materials science, and particle-filled inks used in 3D printing. In each of these settings, a noisy driving force acts on a dense collection of interacting particles, and the collective statistics of the motion emerge from countless individual contacts. “The model is not restricted to ice,” Rallabandi said. “It just needs a noisy source of force and the things that are moving to experience collisions.” From the Fram Strait to a printing nozzle, the same collisional rules may be quietly at work, and the UC Riverside team has shown how much of the Arctic’s stubborn behavior they can explain.

Subject of Research: Collisional dynamics of Arctic sea ice floes and their role in ice transport

Article Title: Engineers crack puzzle of Arctic sea ice movement

Article References: Engineers crack puzzle of Arctic sea ice movement. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: Arctic sea ice, ice floes, Fram Strait, granular physics, collisions, wind-driven drift, climate modeling, Physical Review Letters, UC Riverside, sea ice transport, mechanical engineering, polar ocean

The study stands apart from most fire research in both scope and focus. Rather than examining wildland blazes in remote forests or dissecting a single catastrophic event, the researchers compiled records of 141 fires that intersected urban areas across the United States, reaching back to 1984. By combining four decades of fire records with population data, development patterns, climate measurements, and demographic information, the team assembled one of the most comprehensive portraits to date of how fire behaves when it crosses into developed landscapes. That long temporal window allowed the researchers to test whether patterns of urban fire exposure have shifted over time, and whether the social and environmental conditions that precede urban fires have remained stable across an era of rapid climate change.

The answer to the second question is a decisive no, at least as far as the profile of the neighborhoods that burn is concerned. According to Dion Kucera, a postdoctoral researcher in urban ecology at UC Riverside and an author of the study, urban fires have consistently clustered in suburban, high-income, owner-occupied developments, and that pattern has not budged in more than 40 years. The numbers bear this out with striking clarity: neighborhoods with substantially higher median incomes had roughly 30 percent higher odds of experiencing fire exposure than less affluent areas. The explanation lies partly in geography and partly in the history of American development. Wealthy enclaves are disproportionately built in fire-prone settings, on slopes and ridgelines and along the wildland-urban interface, where flammable vegetation surrounds homes and steep terrain can accelerate flame spread.

One of the most consequential findings for municipal planners concerns what happens in the months before an urban fire ignites or spreads. The study found that the critical precursor is not long-term drought, the factor most often emphasized in seasonal fire outlooks, but rather a short, intense drying of the environment during the six months preceding the fire. This distinction matters because it changes the timescale at which risk should be monitored. As Kucera explained, three- to six-month moisture measures may be far more useful to city managers trying to identify windows of heightened danger than the longer-term drought assessments that currently dominate many planning frameworks. In practical terms, a city could be emerging from a multi-year drought yet still face acute urban fire risk if recent months have brought rapid desiccation of vegetation within the built environment.

The aftermath of urban fire, the study shows, is often measured in years rather than months. The researchers tracked whether burned neighborhoods returned to their pre-fire ranges of vegetation greenness and surface temperature during the five years following each blaze. For most places, they did not. Approximately 78 percent of severely burned areas failed to return to their pre-fire temperature range within five years, and 73 percent failed to recover their previous level of greenness. The general trajectory for burned urban land was toward hotter and less green conditions, with those ecological shifts persisting long after the flames were extinguished. These are not merely aesthetic changes: elevated surface temperatures and reduced vegetation cover in dense residential areas can alter local microclimates, increase cooling demands on surviving homes, and reshape habitat within city boundaries.

Income emerged as a powerful predictor of recovery as well as exposure. Higher-income neighborhoods tended to regain their pre-fire surface temperatures more quickly and suffered smaller losses in vegetation greenness than poorer areas. The study did not formally test the mechanisms behind this disparity, but the pattern is consistent with well-documented differences in the resources available to wealthy and low-income communities after disasters, including faster rebuilding, more extensive landscaping and irrigation, and greater capacity to fund vegetation restoration. Whatever the underlying drivers, the result points to a compounding inequality: the communities least likely to burn are also the ones best positioned to heal when fire does arrive, while lower-income urban areas that do experience fire face slower and less complete ecological recovery.

The social geography of urban fire also varies sharply by region, a nuance the researchers uncovered by analyzing demographic patterns separately across the country. Nationally, neighborhoods with higher proportions of white residents had lower odds of experiencing fire. In California and other dry regions of the American West, however, that relationship reversed: both white and Black populations experienced greater odds of fire exposure in those states. The reversal likely reflects the particular settlement history of the West, where affluent and diverse communities alike have expanded into fire-prone foothills and canyons. For the researchers, the regional divergence underscores a central argument of the paper: understanding urban fire requires attending to the social characteristics of the places that burn, not just the climate and fuel conditions that govern fire in wildlands.

The study also documented that urban fires behave differently from their wildland counterparts in ways that complicate simple extrapolation. While wildland fires in the United States have been growing both larger and more frequent, the number of fires reaching urban areas did not show a clear increase over the study period. There was, however, evidence that the amount of urban land burned is increasing. That trend was heavily influenced by especially destructive fire years, suggesting that a small number of extreme events may be driving growing losses even without any rise in the overall frequency of urban fire. This pattern echoes a broader theme in fire science, in which the tail of the distribution, the rare but catastrophic fire year, increasingly dominates total damage, and it implies that resilience planning should be calibrated to worst-case scenarios rather than average conditions.

The implications extend beyond ecology and emergency management into the financial architecture of disaster risk. The findings could inform how communities prepare for fire and how insurers assess exposure, although the study did not examine insurance markets directly, and Kucera noted that additional research should explore those questions. If high-income neighborhoods carry systematically higher odds of burning, while low-income areas face slower recovery when they do burn, then both premium structures and public mitigation spending may need to reflect a risk landscape that looks very different from the one implied by wildland fire models alone. More broadly, Kucera argues that scientists need to stop treating fires that enter developed areas as simple extensions of wildland fire. Cities, he contends, have their own patterns of exposure and recovery, shaped by where people build, who lives there, and the resources they can marshal after disaster strikes.

Ultimately, the study reframes urban fire as a problem of social structure as much as climate. The urban fire problem is not governed solely by temperature, precipitation, and fuel loads, as it is in wildlands, but by the spatial distribution of wealth, the historical geography of development, and the short-term moisture dynamics of built environments. As Kucera put it, adapting to the growing intensity of urban fires requires looking beyond the forest and into the social fabric of our cities. With 141 fires and four decades of evidence now assembled, the researchers have provided planners, insurers, and residents with a clearer map of where urban fire strikes, when it strikes, and who is left waiting longest for their neighborhoods to turn green and cool again.

Subject of Research: Urban fire exposure and unequal ecological recovery across U.S. neighborhoods

Article Title: Rich neighborhoods more likely to burn

Article References: Rich neighborhoods more likely to burn. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: urban fire, wildland-urban interface, fire risk, income inequality, ecological recovery, surface temperature, vegetation greenness, drought, urban planning, California, npj Urban Sustainability, UC Riverside

The Moore Foundation’s Experimental Physics Investigators Initiative was built around a simple observation. Mid-career scientists are often at their most creative precisely when conventional grant structures become most restrictive, demanding detailed promises about outcomes before exploratory work can begin. “From the start, our aim has been to accelerate progress at the frontier of experimental physics by giving brilliant mid-career scientists the kind of flexible, sustained support that federal grants rarely can,” said Theodore Hodapp, program director for the initiative. “That freedom lets them take on risky, high-reward experiments and follow ideas when research results lead them down new pathways.”

Cui’s winning proposal, titled “Nanoscale microwave spectroscopy of collective modes in two-dimensional many-body electronic and excitonic systems,” sounds forbidding, but the physics at its core is one of the most consequential questions in condensed matter science: what happens when electrons, normally treated as independent particles, stop behaving independently and begin acting as a single, coordinated whole? In ordinary metals and semiconductors, electrons zip past one another with relatively weak mutual influence. In certain carefully engineered materials, however, the forces between electrons become so strong that the entire electron population reorganizes into exotic collective states, including phases that behave like crystals made purely of charge and others governed by bound pairs of particles rather than free carriers.

Among the most tantalizing of these states is the excitonic phase. In a solid such as a semiconductor or insulator, an electron excited to a higher energy state leaves behind a hole, the absence of an electron that behaves like a positive charge. The negatively charged electron and positively charged hole can bind to each other through electrostatic attraction, forming a neutral composite particle called an exciton. In an excitonic phase, vast numbers of these bound pairs condense into a collective quantum state, in loose analogy to the way photons lock step inside a laser. The result is a material through which energy can propagate without any net electrical charge being transported, a property that has fascinated theorists since the 1960s and that remains extraordinarily difficult to observe and control in the laboratory.

What has changed, Cui argues, is the arrival of a new experimental toolkit. “Recent advances in 2D materials device engineering have enabled devices in which electron interactions can dominate — opening an important experimental regime that has historically been difficult to access,” he said. Two-dimensional materials, the family that includes graphene and atomically thin semiconductors such as tungsten disulfide, can be isolated as layers a single atom or molecule thick and then stacked like atomic LEGO bricks. Because the layers are so thin, electrons are confined to a plane, which amplifies the relative strength of their mutual repulsion. By tuning the density of electrons, applying electric fields, and twisting or aligning adjacent layers, researchers can now push devices into regimes where interactions, rather than the underlying crystal structure, dictate the physics.

Cui’s laboratory has spent years building exactly this kind of capability. His group fabricates specialized devices from atomically thin materials and develops experimental techniques capable of probing collective modes at the appropriate time and length scales. The new grant will center on nanoscale microwave spectroscopy, a technique that uses microwave-frequency electromagnetic fields to interrogate how charge excitations move and oscillate within a material at extremely small dimensions. Because collective states such as electron crystals and excitonic condensates respond to electromagnetic probes in characteristic ways, spectroscopy of this kind can reveal their signatures — how rigidly the electrons organize, how quickly disturbances propagate, and where the boundaries between competing phases lie.

The payoff from mapping these collective modes could be substantial. “Such discoveries could ultimately help guide future efforts to develop high-performance quantum technologies and electronic devices,” Cui said. The connection is more than speculative. Excitonic systems carry energy without charge flow, hinting at dissipationless signal transmission; correlated electron phases underpin some of the most celebrated phenomena in modern physics, including superconductivity and the fractional quantum Hall effect, the latter now a foundation for emerging approaches to topological quantum computation. Understanding the fundamental principles that govern how novel electronic phases emerge from strong interactions is therefore both a question of basic science and a potential roadmap for the next generation of technology.

The $1.35 million award will do more than fund experiments. It will support graduate students and postdoctoral researchers in Cui’s group, sustaining the training pipeline for a field where hands-on expertise in device fabrication and precision measurement is scarce and highly sought after. The funding will also allow the laboratory to acquire specialized, state-of-the-art instrumentation that would be difficult to justify through conventional grant mechanisms, which typically favor incremental, guaranteed results over the construction of new experimental infrastructure.

For Cui, the award’s value lies precisely in the latitude it provides. “This grant provides the crucial support needed to pursue ambitious, high-risk, high-reward research avenues,” he said. “With the support from the Gordon and Betty Moore Foundation, we can push into uncharted experimental frontiers and explore bold ideas with high potential for discovery.” That philosophy mirrors the foundation’s broader strategy, which has historically channeled philanthropic capital into areas where the scientific payoff is uncertain but the potential for transformative insight is high, from astronomy to quantum materials.

The selection also marks a notable moment for UC Riverside, a doctoral research university whose campus has built a growing profile in condensed matter and quantum research. As the cohort of 21 new investigators begins its five-year terms, the collective bet is that flexible support for mid-career experimentalists will yield discoveries that no one can yet specify in a grant proposal — the electron crystals, excitonic condensates, and as-yet-unimagined collective states hiding inside atomically thin materials, waiting for the right instrument and the right question to bring them into view.

Subject of Research: Experimental study of collective electron and exciton phases in two-dimensional materials using nanoscale microwave spectroscopy

Article Title: UC Riverside physicist selected as an experimental physics investigator by Moore Foundation

Article References: UC Riverside physicist selected as an experimental physics investigator by Moore Foundation. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: Yongtao Cui, UC Riverside, Gordon and Betty Moore Foundation, Experimental Physics Investigators, two-dimensional materials, excitonic phase, collective electron states, microwave spectroscopy, condensed matter physics, quantum materials, research funding, device engineering

The central player in this story is phosphorus, an element that most people rarely think about but that every living organism absolutely requires. Phosphorus forms the backbone of DNA and RNA, sits at the heart of energy-carrying molecules like ATP, and builds the structural molecules of cells. As Bekker explained, living things cannot grow or function properly without phosphorus. In the oceans, the amount of this nutrient available to microscopic organisms effectively sets the ceiling on how much biological productivity can occur. When marine organisms die and sink, their organic carbon is buried in sediments, and a crucial side effect of burying that carbon is the release of oxygen into the atmosphere. More available phosphorus therefore means more life, more carbon burial, and ultimately more oxygen accumulating in the air.

The research team found that as oxygen entered Earth’s oceans during and after the Great Oxidation Event, the concentration of sulfate, a chemical form of sulfur, also increased in seawater. This shift mattered enormously for the nutrient cycle. Microbes living in the sediments used the abundant sulfate to break down organic matter more efficiently through sulfate-driven respiration. In the process of decomposing that organic material, the microbes released phosphorus back into the seawater, where it became available once again to fuel new biological growth. The cycle thus reinforced itself: oxygen raised sulfate levels, sulfate boosted phosphorus recycling, recycled phosphorus fueled more life, more life buried more organic carbon, and that burial pumped additional oxygen into the atmosphere.

Demonstrating that this feedback loop operated billions of years ago required a methodological breakthrough. Until now, scientists could measure only the total amount of phosphorus preserved in ancient rocks, which made it extremely difficult to determine how much of that phosphorus had actually been available to support life when the rocks formed. Some phosphorus is bound in minerals that living systems can use, while other phosphorus is locked away in forms that are essentially inaccessible to organisms. A total measurement conflates the two, blurring the picture of nutrient conditions in ancient oceans.

To overcome this limitation, Bekker and his collaborators analyzed ancient rocks from South Africa using a new technique that separates phosphorus according to the different types of minerals it is attached to. By dissolving each mineral type one at a time, the method reveals whether the phosphorus in a given sample was available for biological functions or tied up in minerals that made it unavailable to living systems. The result, as Bekker put it, is that researchers can now separate the phosphorus that was available to organisms from phosphorus that was essentially locked away, giving a much clearer picture of nutrient levels in ancient oceans than was previously possible.

The findings carry implications that extend well beyond the chemistry of a single nutrient. They suggest that oxygen levels fluctuated far more dramatically after the Great Oxidation Event than scientists once believed. Rather than rising smoothly and stabilizing, atmospheric oxygen apparently swung through pronounced variations, and those swings likely reshaped ocean chemistry over tens of millions of years. The way nutrients cycled through the marine environment changed in response, which in turn fed back on biological productivity and atmospheric composition. Earth’s early atmosphere and oceans, in this view, were a dynamically coupled system rather than a simple one-way progression toward modern conditions.

These oscillations also bear directly on one of the deepest questions in the history of life: why did complex organisms take so long to appear? For much of the twentieth century, a popular explanation held that oxygen remained scarce for more than a billion years after the Great Oxidation Event, placing a hard physiological limit on the size and complexity that living things could achieve. The new evidence complicates that narrative. If oxygen remained abundant for extended periods, Bekker noted, then other environmental or biological factors, rather than a severely limited oxygen supply alone, may have slowed the emergence of more complex organisms. The search for those additional constraints, whether ecological, nutritional, or evolutionary, now becomes a central task for researchers studying the Proterozoic Eon.

The research also resonates with urgent questions about the modern ocean. Today, climate change is causing parts of the ocean to lose oxygen, a phenomenon visible in expanding dead zones and shrinking habitable volumes for fish and other marine animals. The ancient record suggests a worrying mechanism: if oxygen loss continues, phosphorus could once again become less available in seawater, reducing marine productivity and making marine ecosystems less resilient. In other words, the same feedback loop that helped stabilize Earth’s early oxygenated atmosphere could, when run in reverse, amplify the stresses that modern ocean life faces. Understanding the ancient coupling between oxygen and nutrients provides a long-term baseline against which present-day changes can be judged.

There is even an astrobiological dimension to the work. Scientists searching for life beyond Earth increasingly focus on ocean-bearing worlds, from icy moons in our own solar system to exoplanets orbiting distant stars. Because the new study shows how oxygen, nutrients, and life evolved together on our planet, it offers a template for recognizing similar coupled conditions elsewhere. Detecting an atmosphere rich in oxygen is one thing; understanding whether a planet’s oceans can recycle the nutrients needed to sustain a biosphere over billions of years is another. Earth’s history demonstrates that these connections matter, and Bekker emphasized that grasping them gives scientists a more nuanced perspective on our own planet’s future and on what to look for on other planets.

What makes the study remarkable is how a single element, measured with new precision in rocks that are billions of years old, can tie together so many threads of Earth’s story: the rise of the air we breathe, the productivity of the seas, the timing of life’s increasing complexity, the vulnerability of modern oceans, and the search for habitable worlds beyond our own. The Great Oxidation Event marked the moment oxygen became a permanent feature of the atmosphere, but this research shows that permanence was not guaranteed. It was earned and maintained by an oceanic chemical cycle in which microbes, sulfate, phosphorus, and buried carbon conspired, over immense stretches of time, to keep the planet breathing.

Subject of Research: The role of ancient ocean phosphorus and sulfate chemistry in sustaining atmospheric oxygen after the Great Oxidation Event

Article Title: How ocean chemistry helped life keep breathing

Article References: How ocean chemistry helped life keep breathing. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: Great Oxidation Event, ocean chemistry, phosphorus, sulfate, oxygenation, Andrey Bekker, UC Riverside, Nature Communications, Proterozoic, nutrient cycling, marine productivity, astrobiology

The central obstacle the team faced was the sheer complexity of the honey bee’s sense of smell. Bees rely on more than 200 odor receptors to navigate their world, detecting and responding to a vast array of volatile compounds in their environment. That sensitivity is what makes bees such effective foragers, but it also makes their olfactory behavior extraordinarily difficult to predict. Finding a scent that reliably repels a bee, rather than attracting it or doing nothing at all, has long been considered a major challenge. Anandasankar Ray, a professor of molecular, cell and systems biology at UC Riverside and an expert on insect olfactory behavior, led the interdisciplinary effort to overcome it.

“Bees rely heavily on their sense of smell to forage, but that sensitivity makes it tough to find odors that push them away instead of drawing them in,” Ray said. “Our goal was to flip that script and find a way to use scent as a deterrent — safely and effectively.” To pursue that goal, Ray’s team collaborated with honey bee researchers in the laboratory of Boris Baer, a professor of entomology at UC Riverside, combining expertise in computational modeling with hands-on knowledge of bee behavior.

The approach the researchers developed was a machine-learning model trained on two kinds of information: the chemical structures of odorant molecules and previously recorded behavioral responses of bees to those odorants. By learning the relationship between molecular features and behavioral outcomes, the model could begin to predict how a bee would respond to a compound it had never encountered. Crucially, the team did not stop with the initial training data. They refined the model with new behavioral data generated in their own laboratory, gathered from both honey bees and Drosophila, the fruit fly that serves as a workhorse of insect olfaction research. That iterative improvement step allowed the system to make increasingly accurate predictions of insect olfactory responses.

One of the most striking aspects of the work is that it succeeded without the enormous datasets usually assumed to be necessary for machine learning. “It is generally thought you need abundant data to do any kind of machine learning, but that’s not true for olfaction,” Ray said. “You simply need good-quality data and iterative improvement steps.” That insight has implications well beyond bee research, suggesting that carefully curated behavioral measurements can substitute for sheer data volume when the underlying structure of the problem is learnable. Once the model was optimized, the researchers put it to work on a truly industrial scale, screening a library of more than 50 million compounds. From that vast chemical space, the system identified roughly 130 candidates predicted to have strong potential as bee repellents.

Predictions, of course, mean little until they are tested against living insects. The team reports in eLife how they put the top-performing candidates through exactly that gauntlet. In laboratory assays, honey bees exposed to the candidate compounds exhibited clear avoidance behaviors, and those responses aligned closely with what the model had predicted. That agreement between computation and behavior is the heart of the study’s significance: it demonstrates that a model trained on limited but high-quality data can generalize to new molecules and correctly forecast how bees will react to them in the real world.

The validation did not stop in the laboratory. The researchers then moved to field experiments with freely foraging bees, a far more demanding test because wild conditions introduce wind, competing odors, and the full complexity of natural foraging behavior. All seven of the compounds tested in the field reliably repelled bees from honey combs, and importantly, they did so without harming the insects. A repellent that injured the very pollinators it was meant to protect would defeat its own purpose, so the demonstration that these odorants deter bees safely is a critical part of the result.

“This is a powerful demonstration of how machine learning can help solve real-world ecological problems,” Ray said. “By keeping bees away from harmful pesticides, we can potentially reduce their risk of exposure without compromising the protection of crops.” The logic of the approach is straightforward: instead of banning or restricting every pesticide that poses a risk to bees — a regulatory path that has already removed some of the most harmful products from use — farmers could blend repellent compounds into their pesticide applications. The crop would retain its protection against pests, while bees, sensing the deterrent odor, would simply choose to forage elsewhere. Unintended exposure to pesticides is widely considered a contributing factor to bee population decline and colony collapse, and minimizing bee contact with treated crops addresses that exposure directly.

The researchers also point to applications that extend well beyond agricultural spraying. “In certain public environments — hospitals, office buildings, and residential areas, for example — reducing the formation of beehives can help avoid human-bee conflicts,” Ray said. In those settings, a safe repellent could discourage bees from establishing colonies where they are unwelcome, without resorting to lethal control. There are agricultural uses as well: some farming practices, particularly with seedless fruit varieties, aim to avoid pollination altogether, and a reliable repellent could help keep bees away from crops where pollination is undesirable rather than essential. According to Ray, the research is a step toward developing bee-friendly pesticide formulations — products that safeguard pollinators while still meeting the needs of modern agriculture.

“Protecting pollinators doesn’t have to come at the expense of food security,” Ray said. “With the right tools, we can strike a balance — and this model helps us get there. We believe our work will help guide further exploration of machine learning-guided solutions in environmental protection and sustainable farming practices.” Ray and Baer were joined in the research by Joel Kowalewski, Barbara Baer-Imhoof, Tom Guda, Matthew Luy, and Payton DePalma. The work was funded by a grant from the California Research Alliance by BASF. The research paper, titled “Machine learning of honey bee olfactory behavior identifies repellent odorants in free flying bees in the field,” was published in eLife on 23 September 2026, with the DOI 10.7554/eLife.104831.3. The authors note that Ray is founder and president of Sensorygen and Remote Epigenetics and holds equity in both companies, Kowalewski holds equity in Sensorygen, and several of the authors are inventors in a patent application covering the compounds discussed in the article. If the approach scales from honey combs to whole orchards, the humble trick of making treated flowers smell unappealing could become one of the more elegant tools in the effort to keep the world’s most important pollinators alive.

Subject of Research: Machine learning-guided discovery of odorant compounds that repel honey bees from pesticide-treated crops

Article Title: Machine learning helps identify chemicals that repel honey bees from pesticides

Article References: Machine learning helps identify chemicals that repel honey bees from pesticides. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: honey bees, machine learning, pollinator protection, pesticides, olfaction, repellents, eLife, UC Riverside, colony collapse, sustainable agriculture, chemical ecology, Drosophila