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Fruit flies offer new insights into how Alzheimer’s disease risk genes affect the brain

Scientists have identified hundreds of genes that may increase the risk of developing Alzheimer’s disease but the roles these genes play in the brain are poorly understood. This lack of understanding poses a barrier to developing new therapies, but in a study published in the American Journal of Human Genetics, researchers at Baylor College of Medicine and the Jan and Dan Duncan Neurological Research Institute (Duncan NRI) at Texas Children’s Hospital offer new insights into how Alzheimer’s disease risk genes affect the brain.

“We studied fruit fly versions of 100 human Alzheimer’s disease risk genes,” said first author Dr. Jennifer Deger, a neuroscience graduate in Baylor’s Medical Scientist Training Program (M.D./Ph. D.), mentored by Drs. Joshua Shulman and Hugo Bellen.

“We developed fruit flies with mutations that ‘turned off’ each gene and determined how this affected the fly’s structure, function and stress resilience as the flies aged.”

Diffusion markers of dendritic density and arborization in gray matter predict differences in intelligence

Previous studies suggest that individual differences in intelligence correlate with circuit complexity and dendritic arborization in the brain. Here the authors use NODDI, a diffusion MRI technique, to confirm that neurite density and arborization are inversely related to measures of intelligence.

Machine learning enables real-time analysis of iron oxide thin film growth in reactive magnetron sputtering

Researchers at University of Tsukuba have developed a technology for real-time estimation of the valence state and growth rate of iron oxide thin films during their formation. This novel technology was realized by analyzing the full-wavelength data of plasma emission spectra generated during reactive sputtering using machine learning. It is expected to enable high-precision control of the film deposition process.

Metal oxide and nitride thin films are commonly used in and energy materials. Reactive sputtering is a versatile technique for depositing thin films by reacting a target metal with gases such as oxygen or nitrogen. A challenge with this process is the transitioning of the target surface between metallic and compound states, causing large fluctuations in film growth rate and composition. At present, there are limited effective methods for real-time monitoring of a material’s chemical state and deposition rate during film formation.

A machine learning technique based on was employed to examine massive emission spectra generated within a reactive sputter plasma. This analysis focused on assessing the state of thin film formation. The results, published in Science and Technology of Advanced Materials: Methods, indicated that the valence state of iron oxide was accurately identified using only the first and second principal components of the spectra. In addition, the film growth rate was predicted with high precision.

3D DNA looping discovery in rice paves the way for higher yields with less fertilizer

A team of Chinese scientists has uncovered a hidden 3D structure in rice DNA that allows the crop to grow more grain while using less nitrogen fertilizer. The finding, published in Nature Genetics by researchers from the Chinese Academy of Sciences (CAS), could guide the next “green revolution” toward higher yields and more sustainable farming.

The study reveals that a looping section of DNA—a “chromatin loop”—controls the activity of a gene called RCN2, which governs how rice plants form their grain-bearing branches. Adjusting this loop boosted both yield and nitrogen use efficiency (NUE), two traits that normally conflict with each other.

According to Prof. Fu Xiangdong from the Institute of Genetics and Developmental Biology of CAS, who led the team, boosting depends on strengthening both the “source” and the “sink” within a plant. The source refers to tissues such as leaves that produce and release sugars through photosynthesis, while the sink includes the growing parts—grains, panicles, young leaves, stems, roots, and fruits—that store or consume those sugars. Improving both sides of this system simultaneously is essential for increasing yield and NUE.

Perovskites reveal ultrafast quantum light in new study

Halide perovskites—already a focus of major research into efficient, low-cost solar cells—have been shown to handle light faster than most semiconductors on the market.

A new paper, published in Nature Nanotechnology, reports quantum transients on the scale of ~2 picoseconds at low temperature in bulk formamidinium lead iodide films grown by scalable solution or vapor methods. That ultrafast timescale indicates use in very fast light sources and other photonic components. Crucially, these effects appear in films made by scalable processing rather than specialized growth in lab settings—suggesting a practical and affordable route to explore ultrafast quantum technology.

“Perovskites continue to surprise us,” said Professor Sam Stranks, who led the study. “This discovery shows how their intriguing nanoscale structure gives rise to intrinsic quantum properties that could be harnessed for future photonic technologies.”

Researcher improves century-old equation to predict movement of dangerous air pollutants

A new method developed at the University of Warwick offers the first simple and predictive way to calculate how irregularly shaped nanoparticles—a dangerous class of airborne pollutant—move through the air.

Every day, we breathe in millions of , including soot, dust, pollen, microplastics, viruses, and synthetic nanoparticles. Some are small enough to slip deep into the lungs and even enter the bloodstream, contributing to conditions such as heart disease, stroke, and cancer.

Most of these are irregularly shaped. Yet the mathematical models used to predict how these particles behave typically assume they are perfect spheres, simply because the equations are easier to solve. This makes it difficult to monitor or predict the movement of real-world, non-spherical—and often more hazardous—particles.

Gravitational wave events hint at ‘second-generation’ black holes

In a paper published in The Astrophysical Journal Letters, the international LIGO-Virgo-KAGRA Collaboration reports on the detection of two gravitational wave events in October and November of 2024 with unusual black hole spins. This observation adds an important new piece to our understanding of the most elusive phenomena in the universe.

Gravitational waves are “ripples” in that result from cataclysmic events in deep space, with the strongest waves produced by the collision of black holes.

Using sophisticated algorithmic techniques and mathematical models, researchers are able to reconstruct many physical features of the detected black holes from the analysis of gravitational signals, such as their masses and the distance of the event from Earth, and even the speed and direction of their rotation around their axis, called spin.

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