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How the brain develops and resolves inflammation

Brain development is a complex process involving, for example, the precise diversification and distribution of cells into distinct areas. The researchers behind the present study have developed a new method called spatial tri-omics, that enables them to simultaneously measure in a specific area of the brain: 1) the activity of genes, 2) how this activity is regulated by epigenetic changes, and 3) if this activity ultimately leads to the production of proteins.

The study is based on analyses of mouse and human brains at different stages of development. The authors generated a spatiotemporal tri-omic atlas of the mouse brain from postnatal day 0 (P0) to P21 and compared corresponding regions with the human developing brain.

“We’ve been able to use this multidimensional method to track brain development over time and map changes from birth to a young age in different parts of the brain, as well as study how the brain reacts to inflammation,” explains the senior author.

Inhibiting a master regulator of aging regenerates joint cartilage in mice

An injection that blocks the activity of a protein involved in aging reverses naturally occurring cartilage loss in the knee joints of old mice, a Stanford Medicine-led study has found. The treatment also prevented the development of arthritis after knee injuries mirroring the ACL tears often experienced by athletes or recreational exercisers. An oral version of the treatment is already in clinical trials with the goal of treating age-related muscle weakness.

Samples of human tissue from knee replacement surgeries—which include both the extracellular scaffolding, or matrix, in the joint as well as cartilage-generating chondrocyte cells—also responded to the treatment by making new, functional cartilage.

The study results suggest it may be possible to regenerate cartilage lost to aging or arthritis with an oral drug or local injection, rendering knee and hip replacement unnecessary.

World’s first fast-neutron nuclear reactor to power AI data centers

French startup Stellaria secures its first power reservation from Equinix for Stellarium, the world’s first fast-neutron reactor that reduces nuclear waste.

The agreement will allow Equinix data centres to leverage the reactor’s energy autonomy, supporting sustainable, decarbonized operations and powering AI capabilities with clean nuclear energy.

The Stellarium reactor, proposed by Stellaria, is a fourth-generation fast-neutron molten-salt design that uses liquid chloride salt fuel and is engineered to operate on a closed fuel cycle.

Brain has five ‘eras’, scientists say — with adult mode not starting until early 30s

Scientists have identified five major “epochs” of human brain development in one of the most comprehensive studies to date of how neural wiring changes from infancy to old age.

The study, based on the brain scans of nearly 4,000 people aged under one to 90, mapped neural connections and how they evolve during our lives. This revealed five broad phases, split up by four pivotal “turning points” in which brain organisation moves on to a different trajectory, at around the ages of nine, 32, 66 and 83 years.

“Looking back, many of us feel our lives have been characterised by different phases. It turns out that brains also go through these eras,” said Prof Duncan Astle, a researcher in neuroinformatics at Cambridge University and senior author of the study.

TACC’s “Horizon” Supercomputer Sets The Pace For Academic Science

As we expected, the “Vista” supercomputer that the Texas Advanced Computing Center installed last year as a bridge between the current “Stampede-3” and “Frontera” production system and its future “Horizon” system coming next year was indeed a precursor of the architecture that TACC would choose for the Horizon machine.

What TACC does – and doesn’t do – matters because as the flagship datacenter for academic supercomputing at the National Science Foundation, the company sets the pace for those HPC organizations that need to embrace AI and that have not only large jobs that require an entire system to run (so-called capability-class machines) but also have a wide diversity of smaller jobs that need to be stacked up and pushed through the system (making it also a capacity-class system). As the prior six major supercomputers installed at TACC aptly demonstrate, you can have the best of both worlds, although you do have to make different architectural choices (based on technology and economics) to accomplish what is arguably a tougher set of goals.

Some details of the Horizon machine were revealed at the SC25 supercomputing conference last week, which we have been mulling over, but there are still a lot of things that we don’t know. The Horizon that will be fired up in the spring of 2026 is a bit different than we expected, with the big change being a downshift from an expected 400 petaflops of peak FP64 floating point performance down to 300 petaflops. TACC has not explained the difference, but it might have something to do with the increasing costs of GPU-accelerated systems. As far as we know, the budget for the Horizon system, which was set in July 2024 and which includes facilities rental from Sabey Data Centers as well as other operational costs, is still $457 million. (We are attempting to confirm this as we write, but in the wake of SC25 and ahead of the Thanksgiving vacation, it is hard to reach people.)

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Key biological marker into why young people self-harm uncovered

As many as one in six teenagers have self-harmed at some point in their lives. As well as being an indicator of emotional pain, self-harm is also the best-known predictor of death by suicide—yet researchers know little about the emotional and biological factors that lead to it.

A new study published in Nature Mental Health, led by Professor Rory O’Connor from the University of Glasgow helps to uncover the biological mechanisms behind why young people self-harm.

Expanding on his research into the psychological factors associated with self-harm, Professor O’Connor’s latest findings reveal that young people with a history of self-harm present a particular biological skin response to electrical activity—a physiological marker associated with difficulties in generating and managing emotions.

New universal law predicts how most objects shatter, from dropped bottles to exploding bubbles

When a plate drops or a glass smashes, you’re annoyed by the mess and the cost of replacing them. But for some physicists, the broken pieces are a source of fascination: Why does everything break into such a huge variety of sizes? Now, Emmanuel Villermaux at Aix-Marseille University in France and the University Institute of France has come up with a simple, elegant law for how objects shatter, whether they are brittle solids, liquid drops, or exploding bubbles.

Scientists have long suspected that there was something universal about fragmentation. If you count how many fragments fall into each size range and make a graph of that distribution, it would have the same shape regardless of the object that shattered.

Google Quantum AI realizes three dynamic surface code implementations

Quantum computers are computing systems that process information leveraging quantum mechanical effects. These computers rely on qubits (i.e., the quantum equivalent of bits), which can store information in a mixture of states, as opposed to binary states (0 or 1).

While quantum computers could tackle some computational and optimization problems faster and more effectively than classical computers, they are also inherently more prone to errors. This is because qubits can be easily disturbed by disturbances from their surrounding environment, also referred to as noise.

Over the past decades, quantum engineers and physicists have been trying to develop approaches to correct noise-related errors, also known as quantum error correction (QEC) techniques. While some of these codes achieved promising results in small-scale tests, reliably implementing them on real circuits is often challenging.

Quantum sensor based on silicon carbide qubits operates at room temperature

Over the past decades, physicists and quantum engineers introduced a wide range of systems that perform desired functions leveraging quantum mechanical effects. These include so-called quantum sensors, devices that rely on qubits (i.e., units of quantum information) to detect weak magnetic or electric fields.

Researchers at the HUN-REN Wigner Research Center for Physics, the Beijing Computational Science Research Center, the University of Science and Technology of China and other institutes recently introduced a new quantum sensing platform that utilizes silicon carbide (SiC)-based spin qubits, which store quantum information in the inherent angular momentum of electrons. This system, introduced in a paper published in Nature Materials, operates at room temperature and measures qubit signals using near-infrared light.

“Our project began with a puzzle,” Adam Gali, senior author of the paper told Phys.org. “Quantum defects that sit just a few nanometers below a surface are supposed to be fantastic sensors—but in practice, they pick up a lot of ‘junk’ signals from the surface itself. This is especially true in SiC. Its standard oxide surface is full of stray charges and spins, and those produce noise that overwhelms the quantum defects we actually want to use for sensing. We wanted to break out of this limitation.”

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