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Brain microenvironment redefines metastatic tumor subtypes, facilitating precision oncology treatment

An interdisciplinary multi-center research team led by the LKS Faculty of Medicine (HKUMed) and Faculty of Dentistry at the University of Hong Kong has constructed the world’s largest multi-omics atlas of brain metastases. This comprehensive analysis included 1,032 brain metastasis samples from diverse primary tumors, together with 82 matched primary tumors and 20 glioblastomas (a highly malignant type of brain tumor) as controls.

The findings provide a novel framework for classifying brain metastases and establish a foundation for the development of personalized treatment strategies, advancing the field of precision oncology. This research was published in the journal Nature Communications.

Lab-grown algae remove microplastics from water

A University of Missouri researcher is pioneering an innovative solution to remove tiny bits of plastic pollution from our water. Mizzou’s Susie Dai recently applied a revolutionary strain of algae toward capturing and removing harmful microplastics from polluted water. Driven by a mission to improve the world for both wildlife and humans, Dai also aims to repurpose the collected microplastics into safe, bioplastic products such as composite plastic films.

“Microplastics are pollutants found almost everywhere in the environment, such as in ponds, lakes, rivers, wastewater and the fish that we consume,” Dai, a professor in the College of Engineering and principal investigator at the Bond Life Sciences Center, said. “Currently, most wastewater treatment plants can only remove large particles of plastic, but microplastics are so small that they slip through and end up in drinking water, polluting the environment and harming ecosystems.”

The findings are published in the journal Nature Communications.

Earth’s largest volcanic event reshaped an oceanic plate, seismic wave analysis reveals

A research group has revealed through seismic wave analysis that the oceanic plate beneath the Ontong Java Plateau—the world’s largest oceanic plateau—was extensively altered by massive volcanic activity during its formation. The study is published in Geophysical Research Letters.

The oceanic plate beneath the Ontong Java Plateau (OJP) has a composite structure consisting of layered structures overlaid by dike swarms. Low seismic velocity anomalies within the plate suggest chemical modification by magma derived from a thermochemical plume. These findings demonstrate that oceanic plates can undergo significant physicochemical modification due to large-scale volcanic activity, contributing to a comprehensive understanding of plate formation processes.

The research was led by Lecturer Azusa Shito of Okayama University of Science, together with Associate Professor Akira Ishikawa of the Institute of Science Tokyo and Professor Masako Yoshikawa of Hiroshima University.

AI streamlines deluge of data from particle collisions

Scientists at the U.S. Department of Energy’s (DOE) Brookhaven National Laboratory have developed a novel artificial intelligence (AI)-based method to dramatically tame the flood of data generated by particle detectors at modern accelerators. The new custom-built algorithm uses a neural network to intelligently compress collision data, adapting automatically to the density or “sparsity” of the signals it receives.

As described in a paper just published in the journal Patterns, the scientists used simulated data from sPHENIX, a particle detector at Brookhaven Lab’s Relativistic Heavy Ion Collider (RHIC), to demonstrate the algorithm’s potential to handle trillions of bits of detector data per second while preserving the fine details physicists need to explore the building blocks of matter.

The algorithm will help physicists gear up for a new era of streaming data acquisition, where every collision is recorded without pre-selecting which ones might be of interest. This will vastly expand the potential for more accurate measurements and unanticipated discoveries.

Using complex networks to tame combustion instability

Engineers have long battled a problem that can cause loud, damaging oscillations inside gas turbines and aircraft engines: combustion instability. These unwanted pressure fluctuations create vibrations so intense that they can cause fatal structural damage to combustor walls, posing a serious threat in many applications. Combustion instability occurs when acoustic waves, heat release, and flow patterns interact in a strong feedback loop, amplifying each other until the entire system becomes unstable.

The complex interaction has made it difficult to predict when and where dangerous oscillations will emerge. This challenge has motivated researchers to seek new analytical frameworks that can capture the key driving regions of combustion instability.

Now, a research team led by Professors Hiroshi Gotoda from Tokyo University of Science and Ryoichi Kurose from Kyoto University, Japan, has developed an innovative approach using network science to understand and suppress combustion instability. Their paper, published in the journal Physical Review Applied on July 1, 2025, applies complex network analysis to spray combustion instability in a backward-facing step combustor.

A clearer look at critical materials, thanks to refrigerator magnets

With an advanced technology known as angle-resolved photoemission spectroscopy (ARPES), scientists are able to map out a material’s electron energy-momentum relationship, which encodes the material’s electrical, optical, magnetic and thermal properties like an electronic DNA. But the technology has its limitations; it doesn’t work well under a magnetic field. This is a major drawback for scientists who want to study materials that are deployed under or even actuated by magnetic fields.

Inspired by refrigerator magnets, a team of Yale researchers may have found a solution. Their study was featured recently on the cover of The Journal of Physical Chemistry Letters.

Quantum materials —such as unconventional superconductors or topological materials—are considered critical to advancing quantum computing, high-efficiency electronics, nuclear fusion, and other fields. But many of them need to be used in the presence of a magnetic field, or even only become activated by magnetic fields. Being able to directly study the electronic structure of these materials in magnetic fields would be a huge help in better understanding how they work.

Natural magnetic materials can control light in unprecedented ways

Imagine shining a flashlight into a material and watching the light bend backward—or in an entirely unexpected direction—as if defying the law of physics. This phenomenon, known as negative refraction, could transform imaging, telecommunications, and countless other technologies. Now, a team of scientists has managed to use a natural magnetic material called CrSBr to achieve negative refraction—without the need for complicated artificial structures. The study, published in Nature Nanotechnology, opens the door to ultra-compact lenses, super-high-resolution microscopes, and reconfigurable optical devices that can be controlled with magnets.

The researchers used a very thin layer of CrSBr, a material that has a unique magnetic structure—its magnetic atoms align in different ways within and between layers. This magnetic order changes how the material interacts with light. When the magnetic order is active, it causes light to bend “the wrong way,” creating negative refraction.

By guiding light into this material on a tiny chip, the team visually confirmed the backward bending of light. They also built a miniature “hyperlens” —a device that can focus light into extremely small spots—an essential step for future high-precision imaging and data processing.

Focusing and defocusing light without a lens: First demonstration of the structured Montgomery effect in free space

Applied physicists in the Harvard John A. Paulson School of Engineering and Applied Sciences (SEAS) have demonstrated a new way to structure light in custom, repeatable, three-dimensional patterns, all without the use of traditional optical elements like lenses and mirrors. Their breakthrough provides experimental evidence of a peculiar natural phenomenon that had been confined mostly to theory.

Researchers from the lab of Federico Capasso, the Robert L. Wallace Professor of Applied Physics and Vinton Hayes Senior Research Fellow in Electrical Engineering, report in Optica the first experimental demonstration of the little-known Montgomery effect, in which a coherent beam of light seemingly vanishes, then sharply refocuses itself over and over, in free space, at perfectly placed distances. This lensless, repeatable patterning of light could lay the groundwork for powerful new tools in many areas including microscopy, sensing, and quantum computing.

This effect had been predicted mathematically in the 1960s but never observed under controlled lab conditions. The new work underscores not only that the effect is real, but that it can be precisely engineered and tuned.

Real-time single-event position detection using high-radiation-tolerance GaN

Silicon semiconductors are widely used as particle detectors; however, their long-term operation is constrained by performance degradation in high-radiation environments. Researchers at University of Tsukuba have demonstrated real-time, two-dimensional position detection of individual charged particles using a gallium nitride (GaN) semiconductor with superior radiation tolerance.

Silicon (Si)-based devices are widely used in electrical and electronic applications; however, prolonged exposure to high radiation doses leads to performance degradation, malfunction, and eventual failure. These limitations create a strong demand for alternative semiconductor materials capable of operating reliably in harsh environments, including high-energy accelerator experiments, nuclear-reactor containment systems, and long-duration lunar or deep-space missions.

Wide-bandgap semiconductors, characterized by strong atomic bonding, offer the radiation tolerance required under such conditions. Among these materials, gallium nitride (GaN)—commonly employed in blue light-emitting diodes and high-frequency, high-power electronic devices—has not previously been demonstrated in detectors capable of two-dimensional particle-position sensing for particle and nuclear physics applications.

Intercity quantum sensor network tightens axion dark matter constraints

Recently, scientists from institutions including the University of Science and Technology of China made a fundamental breakthrough in nuclear-spin quantum precision measurement. They developed the first intercity nuclear-spin-based quantum sensor network, which experimentally constrains the axion topological-defect dark matter and surpasses the astrophysical limits. The study is published in the journal Nature.

Current studies indicate that ordinary visible matter accounts for only about 4.9% of the universe, while dark matter makes up about 26.8%. Axions are among the best-motivated dark matter candidates, and axion fields can form topological defects during phase transitions in the early universe. As Earth crosses topological defects, the defects are expected to interact with nuclear spins and induce signals. However, detection remains a formidable challenge because signals are extremely weak and short-duration.

To overcome the detection challenge, the research team innovatively developed a nuclear-spin quantum precision measurement that “stores” microsecond-scale axion-induced signals in a long-lived nuclear-spin coherent state, enabling a minute-scale readout signal. At the same time, the team used nuclear spin as a quantum spin amplification to further enhance the weak dark-matter signal by at least 100-fold, increasing the sensitivity of spin rotation to about 1 μrad, representing an improvement of more than four orders of magnitude over previous techniques.

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