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Inflammation fuels one of the most aggressive forms of lung cancer

Small cell lung cancer (SCLC) is one of the most aggressive forms of lung cancer, with a five-year survival rate of only 5%. Despite this poor prognosis, SCLC is initially highly responsive to chemotherapy. However, patients typically relapse and experience very rapid disease progression. Current research into the biological mechanisms behind SCLC remains essential in order to prolong treatment responses, overcome relapse and, ultimately, improve long-term patient outcomes.

A research team led by Professor Dr. Silvia von Karstedt (Translational Genomics, CECAD Cluster of Excellence on Aging Research, and Center for Molecular Medicine Cologne—CMMC) has discovered a novel mechanism used by this type of cancer that helps explain its aggressive nature. The study titled “Lack of Caspase 8 Directs Neuronal Progenitor-like reprogramming and Small Cell Lung Cancer Progression” is published in Nature Communications.

Production of hydrogen and carbon nanotubes from methane using a multi-pass floating catalyst chemical vapour deposition reactor with process gas recycling

Methane pyrolysis produces hydrogen and carbon materials, but some approaches based on chemical vapour deposition actually consume hydrogen to mitigate unwanted side reactions. Here Peden et al. use gas recycling in a multi-pass floating catalyst chemical vapour deposition reactor to produce hydrogen alongside carbon nanotube aerogels.

Why a chiral magnet is a direction-dependent street for electrons

RIKEN physicists have discovered for the first time why the magnitude of the electron flow depends on direction in a special kind of magnet. This finding could help to realize future low-energy devices.

The work is published in the journal Science Advances.

In a normal magnet, all the spins of electrons point in the same direction. In a special class of magnets known as chiral magnets, the electron spins resemble a spiral staircase, having a helical organization.

Raindrops form ‘sandballs’ as they roll downhill, contributing more to erosion than previously thought

What happens as a raindrop impacts bare soil has been fairly well-studied, but what happens to raindrops afterward is poorly understood. We know that the initial splash of raindrops on soil contributes to erosion, but a new study, published in the Proceedings of the National Academy of Sciences, finds that the journey of the raindrop downhill might have an even bigger impact on erosion than the initial splash.

Somewhere on the “Route de la Sorge” in Ecublens, Switzerland, members of the research team observed natural raindrops hitting the surface of a hillside and noticed that they collected particles of sand as they rolled downhill. This spurred the researchers to document the event with a camera and then take the idea to the lab.

In the lab, they constructed a 1.2 meter long bed covered with dry silicate sand and tilted at an angle of 30°. The lab conditions enabled the team to properly document the phenomenon by recording the evolution of the raindrops’ shapes as they rolled and take precise measurements of the relevant parameters. They found that each raindrop formed what they refer to as “sandballs” and that they took on differing shapes, depending on the conditions, and that the sandballs can move up to 10 times more soil than the initial splash alone.

Ultrafast fluorescence pulse technique enables imaging of individual trapped atoms

Researchers at the ArQuS Laboratory of the University of Trieste (Italy) and the National Institute of Optics of the Italian National Research Council (CNR-INO) have achieved the first imaging of individual trapped cold atoms in Italy, introducing techniques that push single-atom detection into new performance regimes.

By combining intense, microsecond-scale fluorescence pulses with fast re-cooling, the team demonstrated record-speed, low-loss imaging of individual ytterbium atoms—capturing clear single-atom signals in just a few microseconds while keeping more than 99.5% of the atoms trapped and immediately reusable.

This approach allows researchers to distinguish multiple atoms within a single optical tweezer without significant blurring, enabling precise onsite atom counting rather than the binary “zero-or-one” detection typical of existing methods. This capability is key for scaling neutral-atom quantum computers, advancing next-generation atomic clocks, and enhancing quantum simulators that probe complex many-body physics.

Journey to the center of a quantized vortex: How microscopic mutual friction governs superfluid dissipation

Step inside the strange world of a superfluid, a liquid that can flow endlessly without friction, defying the common-sense rules we experience every day, where water pours, syrup sticks and coffee swirls and slows under the effect of viscosity. In these extraordinary fluids, motion often organizes itself into quantized vortices: tiny, long-lived whirlpools that act as the fundamental building blocks of superfluid flow.

An international study conducted at the European Laboratory for Non-Linear Spectroscopy (LENS), involving researchers from CNR-INO, the Universities of Florence, Bologna, Trieste, Augsburg, and the Warsaw University of Technology, has embarked on this journey by investigating the dynamics of vortices within strongly interacting superfluids, uncovering the fundamental mechanisms that govern their behavior.

Using ultracold atomic gases, the scientists open a unique window into this exotic realm, recreating conditions similar to those found in superfluid helium-3, the interiors of neutron stars, and superconductors.

Promising new superconducting material discovered with the help of AI

Tohoku University and Fujitsu Limited have successfully used AI to derive new insights into the superconductivity mechanism of a new superconducting material.

Their findings demonstrate an important use case for AI technology in new materials development and suggest that the technology has the potential to accelerate research and development. This could drive innovation in various industries such as the environment and energy, drug discovery and health care, and electronic devices.

The AI technology was used to automatically clarify causal relationships from measurement data obtained at NanoTerasu Synchrotron Light Source. This achievement was published in Scientific Reports.

Rare Hall effect reveals design pathways for advanced spintronic materials

Scientists at Ames National Laboratory, in collaboration with Indranil Das’s group at the Saha Institute of Nuclear Physics (India), have found a surprising electronic feature in transitional metal-based compounds that could pave the way for a new class of spintronic materials for computing and memory technologies.

Spintronics, a field that harnesses the spin of electrons in addition to their charge, promises breakthroughs in technologies such as brain-like computers and memory devices that retain data without power.

The unexpected feature was found in Mn₂PdIn, a Heusler compound—a type of alloy valued for its tunable magnetic and electronic properties. These alloys can exhibit behaviors not seen in their individual elements, making them prime candidates for spintronic applications.

Scientists crack ancient salt crystals to unlock secrets of 1.4 billion-year-old air

More than a billion years ago, in a shallow basin across what is now northern Ontario, a subtropical lake much like modern-day Death Valley evaporated under the sun’s gentle heat, leaving behind crystals of halite—rock salt.

It was a very different world than the one we know today. Bacteria were the dominant form of life. Red algae had only just appeared on the evolutionary scene. Complex multicellular life like animals and plants wouldn’t show up for another 800 million years.

As the water evaporated into brine, some of it became trapped in tiny pockets within the crystals, effectively frozen in time. Those trapped fluid inclusions contained air bubbles revealing, in fine detail, the composition of early Earth’s atmosphere. The crystals were buried in sediment, effectively sealed off from the rest of the world for 1.4 billion years, their secrets unknown.

Signature neural patterns may help predict recovery from traumatic brain injury

After traumatic brain injury (TBI), some patients may recover completely, while others retain severe disabilities. Accurately evaluating prognosis is challenging in patients on life-sustaining therapy.

Though resting-state functional MRI (rs-fMRI) can assess neurological activity shortly after brain injury, it is unknown whether communication across brain regions at this early juncture predicts long-term recovery.

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