122831
#Science telegram channel Best science content in telegram
🌞 The Sun Is Waking Up Fast — A Major X-Class Solar Flare Could Happen at Any Moment
Solar activity has accelerated dramatically over the past 48 hours, and space weather scientists are watching closely.
The number of solar flares has surged from 5 per day two days ago, to 8 yesterday, and 17 within the last 24 hours. This morning, the Sun produced its first M-class flares of the current activity spike — leaving only the most powerful category, X-class, yet to appear.
What’s making scientists especially cautious is the location of the Sun’s largest active region of 2026. It is currently facing almost directly toward Earth. Surprisingly, despite its enormous size, it has not yet produced a single X-class flare. Earlier this year, another large sunspot group generated five X-class flares, including the year’s strongest event, X8.1. That makes the current quietness look more like the calm before the storm than a sign of stability.
Space-based observations reveal an even more intriguing picture. Two giant sunspot groups that appear separate on the solar surface are actually connected high above it in the corona, forming a single, highly complex magnetic system. These intertwined magnetic fields continuously exchange energy. On one hand, this can relieve local magnetic stress. On the other, it effectively creates one enormous energy reservoir capable of producing an exceptionally powerful eruption.
Predicting exactly when that energy will be released remains one of the biggest challenges in solar physics. Most of the Sun’s magnetic field lies hidden beneath the visible surface, beyond direct observation, making even the most sophisticated computer models unreliable for systems this complex.
For now, an X-class solar flare could occur at virtually any time. If accompanied by a coronal mass ejection directed toward Earth, it could trigger strong geomagnetic storms, spectacular auroras at unusually low latitudes, and temporary disruptions to satellites, radio communications, and navigation systems.
🔭 The Sun is reminding us that even after centuries of observation, our nearest star can still surprise us.
#Science #Astronomy #Sun #SolarFlare #SpaceWeather #SolarStorm #Heliophysics
🤖 The Transformer Era Is Evolving — NVIDIA’s New Hybrid Model Shows What May Come Next
NVIDIA has released Nemotron 3 Ultra, a 550-billion-parameter open model that matters less for its size than for what sits under the hood.
Instead of being a classic Transformer-only system, Nemotron 3 Ultra uses a hybrid architecture: a Latent Mixture-of-Experts design that interleaves Mamba-2 state-space layers with selected attention layers. In simple terms, NVIDIA is not throwing Transformers away — it is replacing some of the expensive attention machinery with more efficient sequence-processing components, while keeping attention where precision still matters.
The numbers are serious: 550B total parameters, 55B active per token, up to a 1-million-token context window, and Multi-Token Prediction layers for faster generation through native speculative decoding. NVIDIA has released the model weights, data, and recipes under the OpenMDW-1.1 license, making this one of the most ambitious open-weight frontier model releases so far.
The benchmarks are also impressive. NVIDIA reports 71.9% on SWE-Bench Verified, 87.0% on GPQA without tools, 56.4 on Terminal Bench 2.1, and strong long-context performance on RULER at 1M tokens.
But the real story is architectural.
For years, the Transformer has been the default architecture behind modern AI. Its weakness is also well known: standard attention becomes increasingly expensive as context grows. Mamba-style state-space layers offer a different way to process long sequences more efficiently. Nemotron 3 Ultra suggests that the next generation of large models may not be “Transformer vs. Mamba,” but carefully engineered hybrids that combine both.
Nikolas Bush Take
The Mamba moment has arrived — but not as a revolution overnight. NVIDIA did not ship a pure state-space model. It shipped a pragmatic hybrid. That is probably the pattern to watch: keep attention where it creates value, replace it where it becomes too expensive.
Open-weight frontier models are now strategic infrastructure. NVIDIA is not just selling GPUs anymore. By releasing serious open models, datasets, and recipes, it is pulling developers deeper into its full-stack AI ecosystem — hardware, software, inference, agents, and deployment.
The next AI race may be less about raw parameter count and more about architecture, inference efficiency, data quality, and agentic reliability. A 55B-active model with strong benchmark results is a signal that “useful scale” is becoming more nuanced than simply making models bigger.
🌋 Yellowstone May Not Be Powered by a Deep Mantle Plume After All
Yellowstone is one of Earth’s most famous supervolcanoes — and for decades, many geologists explained it with a familiar image: a deep mantle plume, a vertical column of hot rock rising from near Earth’s core, similar to the plume that built Hawaii.
A new study in Science suggests a very different mechanism.
Researchers built a high-resolution 3D geodynamic model of western North America and found that Yellowstone’s magma may be supplied not by a deep plume, but by the shallow asthenosphere — the hot, slowly flowing layer of mantle just beneath the rigid lithosphere.
The driver is what the authors call an eastward “mantle wind”: a broad horizontal flow of hot rock moving beneath North America at geologic speeds.
This flow appears to be linked to the ancient Farallon Plate, which began sliding beneath North America tens of millions of years ago. Remnants of that plate still sit deep under the continent. As they continue to sink, they help generate a large-scale mantle flow that pushes hot asthenospheric material toward Yellowstone.
Then comes the key part: as this buoyant material is forced beneath the thick continental lithosphere, the stretching and pressure changes trigger decompression melting — producing magma without requiring a deep plume rising from the core-mantle boundary.
The model also helps explain Yellowstone’s unusual underground plumbing. Competing tectonic forces appear to tear the lithosphere beneath the region, creating a southwest-dipping channel. This channel acts like a pathway for magma to rise, spread and evolve into a vast “magma mush” system rather than a simple, long-lived liquid magma chamber.
Why it matters: supereruptions can eject more than 1,000 cubic kilometers of material, blanket huge regions in ash and affect climate for years. Understanding what actually sustains systems like Yellowstone is crucial for long-term volcanic hazard models.
The big takeaway: Yellowstone may be less like a blowtorch from Earth’s deep interior — and more like a tectonic wound kept active by the slow, hidden motion of an ancient plate.
Source:
https://www.science.org/doi/10.1126/science.ady2027
Readable summary:
https://www.sciencedaily.com/releases/2026/06/260622014317.htm
#Yellowstone #Supervolcano #Geology #EarthScience #Science
🪐 Earth May Have Been Seeding Venus with Life for Billions of Years
What if any life we eventually discover on Venus didn’t originate there at all?
A fascinating new study suggests that Earth may have been quietly sending microscopic life to our neighboring planet for over a billion years.
Researchers from Johns Hopkins University Applied Physics Laboratory and Sandia National Laboratories modeled how asteroid impacts can eject rocks containing microbes from Earth’s surface into space. Some of those microorganisms could survive the violent launch, the radiation-filled journey through interplanetary space, and even the fiery descent into Venus’ atmosphere — eventually becoming suspended within the planet’s temperate cloud layers.
To estimate the odds, the team used the Venus Life Equation — a framework inspired by the famous Drake Equation — and combined it with the “pancake model,” which describes how incoming meteorites fragment and spread through an atmosphere after an airburst.
Their best estimate is surprisingly specific:
🔹 Asteroid impacts regularly eject Earth material beyond our planet’s gravity
🔹 Some microbes could survive the impact, space travel, and atmospheric entry
🔹 Around 100 viable microbial cells may reach Venus’ cloud layer every year
🔹 Over the last 1 billion years, roughly 20 billion cells could have made the journey
🔹 Venus’ cloud layer at 48–60 km altitude has temperatures of roughly 0–60°C and pressures comparable to those on Earth’s surface
While Venus’ surface remains an inferno—about 475°C under crushing atmospheric pressure—its upper cloud layers are one of the few places in the Solar System outside Earth where temperature and pressure are surprisingly Earth-like.
An important caveat: this study does not report the discovery of life on Venus. It is a theoretical model exploring what is physically possible under known laws of physics. Whether any transferred microbes could actually survive, reproduce, or establish a population remains completely unknown. (ScienceDaily)
The implications, however, are profound. Future missions such as NASA’s DAVINCI and ESA’s EnVision will investigate Venus in unprecedented detail. If they detect convincing biosignatures, scientists may face an extraordinary question:
Would we be looking at alien life—or distant descendants of Earth’s own microbes?
📄 Original paper (Journal of Geophysical Research: Planets) · ScienceDaily
#Venus #Astrobiology #Panspermia #SpaceExploration #Science
🐝 What If Queen Bees Aren’t Made by Royal Jelly Alone?
For decades, the textbook story sounded simple: feed an ordinary honeybee larva royal jelly, and it becomes a queen.
A new study in Nature suggests the real story is far more sophisticated.
Researchers found that future queens are not just fed differently — they are raised inside specially engineered “royal cribs”: peanut-shaped queen cells built from unusual wax, kept warmer and more humid, and maintained by dedicated young worker bees.
These queen cells are not passive containers. Their wax is physically and chemically distinct from ordinary worker-cell wax: softer, less dense, more flexible, and better at holding heat and moisture. In other words, the nursery itself helps shape development.
The key experiment was simple but powerful. Scientists raised queen-destined larvae with the same royal jelly, but changed the wax environment. Larvae exposed to ordinary worker-cell wax were more likely to die and developed into smaller, weaker queens.
So royal jelly matters — but it is not the whole mechanism.
🔹 Queen development depends on diet + architecture + microclimate
🔹 Queen-cell wax is chemically and physically different from ordinary comb wax
🔹 Young “queen cell builders” appear specially adapted to construct and maintain these royal nurseries
🔹 Extra warmth may help queens mature faster: about 16 days vs about 21 days for workers
🔹 Similar patterns were found in western and eastern honeybees, suggesting deep evolutionary roots
Important caveat: this study focused on honeybees, not all social insects. And scientists still need to identify exactly which physical or chemical features of the wax are doing the biological work.
Still, the implication is fascinating: development is not shaped by genes and nutrition alone. Built environments — even tiny wax chambers — can influence what an organism becomes.
If a wax cradle can help decide the fate of a future queen, what other biological outcomes are being shaped by structures we barely notice?
📄 Source: https://www.nature.com/articles/s41586-026-10534-3
#Science #Biology #Bees #Nature #Entomology
🤖 NVIDIA Cosmos 3: AI Is Leaving the Screen and Entering the Physical World
NVIDIA has unveiled Cosmos 3, the world’s first fully open “omnimodel” for Physical AI — a new generation of AI designed not only to understand information, but also to perceive, predict, simulate, and act in the real world.
Unlike traditional AI systems that specialize in a single modality, Cosmos 3 combines visual reasoning, world simulation, and action generation within a unified architecture. The goal is straightforward: build AI that can operate in physical environments rather than merely talk about them.
Potential applications include robotics, autonomous vehicles, manufacturing, industrial automation, and medical simulation. By releasing the model openly, NVIDIA hopes to accelerate development across the entire Physical AI ecosystem.
Nikolas Bush Take
The significance of Cosmos 3 is not the model itself — it’s what it represents.
For the past few years, the AI race has focused on making language models larger and more capable. NVIDIA is betting that the next battleground will be Physical AI: systems that can see, understand, predict, and act in the real world.
If this shift succeeds, the winners of the next decade may not be the companies with the smartest chatbots, but those building the best robots, autonomous machines, industrial agents, and digital-physical ecosystems.
The most important question is no longer:
“Can AI think?”
It’s becoming:
“Can AI reliably interact with reality?”
That is a far more difficult challenge — and a far larger market.
🌌 Einstein’s “Biggest Blunder” May Have a New Explanation — Hidden in the Shape of Space-Time
One of the deepest problems in modern physics is the cosmological constant — the tiny number linked to the accelerating expansion of the universe.
The mystery is brutal: quantum theory suggests empty space should contain an enormous amount of vacuum energy. If that were true, the universe should have expanded so violently that galaxies, stars, and life could never form. But in reality, the cosmological constant is incredibly small.
Now, physicists at Brown University propose a possible explanation: the value may be protected by the topology of space-time itself.
Their idea connects quantum gravity with the quantum Hall effect — a Nobel Prize-winning phenomenon where electrical conductance becomes locked into precise, stable values because of topology: the underlying “shape” of the system.
The researchers argue that space-time may work in a similar way. In their model, the cosmological constant becomes tied to a topological parameter, meaning quantum fluctuations that should make it explode are effectively neutralized.
In simple terms: the universe’s expansion may not be delicately fine-tuned by chance — it may be stabilized by the mathematical structure of space-time.
Important caveat: this is still a theoretical proposal, not an experimental discovery. Whether space-time really has this kind of topological protection remains an open question.
But if the idea is right, it could offer a rare bridge between quantum gravity and experimentally tested condensed-matter physics — and may explain why our universe is stable enough to contain galaxies, stars, and us.
Could the reason we exist be written into the geometry of the universe itself?
Source: Brown University / Physical Review Letters
https://www.brown.edu/news/2026-04-20/cosmological-constant-problem
#Physics #Cosmology #QuantumGravity #DarkEnergy #Einstein
🧠 What If Alzheimer’s Starts Inside Brain Cells — Before the Plaques Take Over?
For decades, Alzheimer’s disease has been strongly associated with amyloid beta plaques — sticky protein deposits that build up between neurons. This idea shaped an entire generation of drug development. But clearing plaques has not been enough to stop or reverse the disease, which suggests the real story may begin earlier and deeper inside the cell.
A new study from the University of California, Riverside, published in PNAS Nexus, proposes a different mechanism: amyloid beta may disrupt neurons by hijacking the same internal “tracks” normally used by tau, another key brain protein.
Inside neurons, microtubules act like tiny railways, helping move vital cargo through long and fragile nerve-cell branches. Tau normally stabilizes these tracks. But the researchers found that amyloid beta can bind to microtubules with roughly similar strength — meaning that, if it accumulates inside neurons, it may compete with tau and push it away from its normal job.
That could trigger a dangerous cascade: microtubules become unstable, cellular transport starts to fail, and displaced tau begins to misbehave — clumping, becoming chemically modified, and moving into parts of the neuron where it does not belong.
In this model, plaques outside cells may not be the original weapon. They may be a visible downstream sign of a much earlier intracellular failure.
Why this matters:
🔹 Amyloid beta and tau appear to compete for overlapping binding sites on microtubules
🔹 The damage may begin inside neurons, before external plaques dominate the picture
🔹 Aging-related decline in autophagy — the cell’s recycling system — could allow amyloid beta to build up internally
🔹 The model may help explain why plaque-clearing drugs have shown limited clinical impact
🔹 It points toward new strategies: protecting microtubules, supporting tau function, or improving intracellular protein cleanup
Important caveat: this is not a clinical trial and not proof that this mechanism causes Alzheimer’s in humans. It is a proposed model based on laboratory experiments — but an interesting one, because it connects two major Alzheimer’s hallmarks, amyloid beta and tau, through the same cellular structure.
More than 57 million people worldwide live with dementia, and Alzheimer’s disease accounts for the majority of cases. If this microtubule-competition model holds up, it could shift part of the field from simply removing plaques to protecting the neuron’s internal transport system before it breaks.
Maybe the real crime scene was never just between brain cells.
Maybe it was inside them all along.
Source: https://doi.org/10.1093/pnasnexus/pgag034
#Alzheimers #Neuroscience #BrainHealth #Dementia #PNASNexus #science
🧬 Scientists May Have Reactivated a Dormant Regeneration Program in Mammals
For a long time, scientists believed that mammals simply lost the ability to regenerate complex body parts during evolution. Salamanders can regrow entire limbs. Mammals usually heal injuries with scar tissue.
But researchers at Texas A&M University have now demonstrated that this regenerative potential may still exist — just in a dormant state.
In a new study published in Nature Communications, the team led by Dr. Ken Muneoka used a two-step treatment that redirected healing away from scar formation and toward actual tissue regeneration. In animal models, amputated digits regrew key structures including bone, tendons, ligaments, and joint tissues — components that mammals normally cannot rebuild once lost.
The approach relies on two growth factors applied in sequence:
• FGF2 (fibroblast growth factor 2) first stimulates the formation of a blastema — a specialized cluster of regenerative cells normally seen in animals such as salamanders.
• Several days later, BMP2 (bone morphogenetic protein 2) provides instructions that guide those cells to rebuild specific tissues.
Key findings:
🔹 Regeneration occurred without transplanting stem cells — the body’s own cells were reprogrammed locally
🔹 Bone, tendon, ligament, and joint structures regenerated after amputation
🔹 Cells could be instructed to form tissues in locations where they would not normally develop
🔹 BMP2 is already FDA-approved for certain medical applications, while FGF2 has undergone extensive clinical investigation
🔹 The regenerated structures were not perfect replicas, but major functional components were restored
Important caveat: these results come from animal studies, not human clinical trials. Whether the same strategy can trigger comparable regeneration in humans remains unknown.
Still, the work suggests that mammalian regeneration may not have disappeared during evolution. Instead, the underlying biological program may still be present — but normally remains switched off.
If that turns out to be true, future regenerative therapies may focus less on adding new cells and more on activating capabilities our bodies already possess.
📄 Original paper (Nature Communications) · ScienceDaily
#RegenerativeMedicine #Biotech #TissueEngineering #NatureCommunications #FutureOfMedicine #science
🐱 Oxford Physicists Just Made Schrödinger’s Cat Even Weirder
Schrödinger’s cat was never really about a cat. It was a way to show how strange quantum mechanics becomes when one object is treated as being in two states at once.
Now physicists at the University of Oxford have created a new family of “cat-like” quantum states — but with an extra twist: the two parts of the superposition are not ordinary, classical-looking wave packets. They are already deeply quantum objects.
In standard lab versions of Schrödinger-cat states, researchers usually combine coherent states — the closest thing quantum physics has to classical motion. The Oxford team went further. Using a single trapped strontium-88 ion, they built superpositions from squeezed, trisqueezed and quadsqueezed motional states: exotic states where quantum uncertainty is reshaped in unusual ways.
The setup is elegant. The ion’s internal electronic state acts like a qubit, while its motion behaves like a quantum harmonic oscillator — a system that can occupy many energy levels. By entangling these two parts and then performing a mid-circuit measurement, the team could “sculpt” the ion’s motion into highly programmable quantum superpositions.
Why is this interesting?
• The states are built from nonclassical components, not just classical-like wave packets
• Their size, orientation and separation can be tuned experimentally
• Wigner-function measurements showed interference and negativity — signatures of genuinely quantum behavior
• Some states displayed striking geometric patterns, including sixfold symmetry in a trisqueezed example
• At the same average energy, these states can be more “quantum-resourceful” than standard cat states or Fock states
This matters because future quantum computers may not rely only on simple qubits. Quantum oscillators can store information across many energy levels, opening a richer route toward bosonic quantum error correction — where information is encoded in oscillator states rather than many separate physical qubits.
It is still early-stage physics, not a ready-made quantum computer. But it gives researchers a new way to build, control and study quantum states that sit far beyond everyday intuition.
And it brings us back to the original question Schrödinger wanted to provoke:
Where does the quantum world end — and the classical world begin?
Source: https://doi.org/10.1103/k1xk-yt42
#QuantumPhysics #SchrodingersCat #QuantumComputing #Physics #Oxfordx #science
🦜 Parrots Don't Just Mimic — They Use Names Like Humans Do, a Massive Study Confirms
For decades, we've known parrots can mimic human speech with uncanny precision. But a new study suggests something far more remarkable: they may actually understand and use names the way humans do — assigning specific vocal labels to specific individuals, and using them flexibly in social situations.
Researchers from the University of Northern Colorado, the University of Pittsburgh, and the University of Vienna analyzed recordings and survey data from nearly 900 captive parrots through the ManyParrots project, a global research network studying parrot cognition.
Out of 413 audio clips submitted by parrot owners, 88 showed clear evidence of birds using names as labels for specific people or animals — not just mimicking sounds, but deploying them in context-appropriate ways.
The team found that parrots don't just categorize broadly ("that's a person"). They can zero in on one specific individual. Some birds even used names to refer to someone who wasn't physically present — a cognitive leap that requires holding an abstract representation of another being in mind.
At the same time, parrots showed their own quirky twists: some would say their own name simply to attract attention, a behavior humans rarely exhibit.
• Nearly half of 889 surveyed parrot owners reported their birds using names
• 88 of 413 audio clips showed parrots labeling specific people or animals
• Parrots can refer to individuals who aren't present — a sign of abstract thinking
• Some birds use their own name as an attention-getting call, unlike humans
• The ability spans multiple parrot species, not just famous talkers like African Greys
While dolphins use signature whistles and some primates have distinct alarm calls, no previous study had shown such a diverse group of animals producing and flexibly using proper names under human linguistic conventions. It challenges our assumptions about what makes human language unique — and suggests the cognitive building blocks of naming may be more widespread than we ever imagined.
If a parrot can hold an abstract name for someone who isn't even in the room, what else is going on in that feathered brain?
📄 Original paper (PLOS ONE) · SciTechDaily summary
#AnimalCognition #Parrots #Language #Biology #PLOSONE #science
🌌 Dark Energy Survives Its Latest Crisis
For a moment, cosmology had a real scare.
A 2025 study suggested that the universe’s accelerating expansion might be partly an illusion — not because dark energy disappeared, but because Type Ia supernovae, the “standard candles” used to measure cosmic distances, may change their brightness depending on the age of the stars that produce them.
If that were true, one of modern cosmology’s biggest discoveries would need a serious rethink.
Now, an international team including Nobel laureates Adam Riess and Brian Schmidt has pushed back hard. In a new paper in Monthly Notices of the Royal Astronomical Society, led by Dr. Phil Wiseman of the University of Southampton, the researchers argue that the evidence for cosmic acceleration remains robust.
The problem, they say, was not dark energy — it was the correction.
The 2025 analysis made two major mistakes. First, it treated the age of a host galaxy as if it were the age of the specific star system that later exploded as a supernova, exaggerating the age difference between nearby and distant supernovae by a factor of three to five. Second, it left out a standard correction for the mass of the host galaxy — something modern supernova cosmology already uses because galaxy environments affect observed brightness.
Once those effects are included, the dramatic claim largely disappears.
• The claimed ~5-billion-year age gap between nearby and distant supernovae was overstated
• After standard corrections, there is no significant brightness difference between young and old supernova environments
• Data from the Dark Energy Survey show no meaningful evolution of the host-mass effect
• Including the proposed bias shifts the dark-energy equation-of-state parameter by less than 0.01
That does not mean we understand dark energy. We still don’t.
It makes up roughly 68% of the universe’s mass-energy budget, yet we have no clear physical explanation for what it actually is. A cosmological constant? Vacuum energy? Something that changes over time? A sign that gravity itself is incomplete on cosmic scales?
The new result does not solve the mystery. It simply says the original signal — the accelerating expansion of the universe — is still standing.
And that matters. Because the next generation of sky surveys, including the Vera C. Rubin Observatory’s 10-year Legacy Survey of Space and Time, is designed to measure exactly this kind of cosmic acceleration with far greater precision.
So the crisis may be averted.
But the real question remains: what kind of invisible “something” can dominate the universe — and still refuse to show itself directly?
https://doi.org/10.1093/mnras/stag797
#DarkEnergy #Cosmology #Astrophysics #Supernova #Physics #science
“Most people do not really want freedom, because freedom involves responsibility, and most people are frightened of responsibility.”
🗂 The @science archive now lives on the web
Every post from this channel — searchable, filtered, and mapped on an interactive timeline. One page, no apps, no logins. Thanks to AI and just 1 prompt.. crazy!
🔹 356 posts and counting — the full archive since 2024, auto-synced with the channel several times a day
🔹 Five frontiers: AI, Space, Biotech, Physics and FutureTech — filter by category or search any keyword across titles and summaries
🔹 An interactive timeline of scientific breakthroughs from 2012 to 2025 — from AlexNet to room-temperature superconductor claims, hover any dot for the story
🔹 Every card links straight back to the original post here on Telegram
🔹 Built lightweight: a single page that loads in under a second, works on any phone
The archive grows automatically as new posts appear on the channel.
🔗 http://144.172.108.222/science/
✨ Pterosaurs Shimmered in Iridescent Greens and Magentas — 120-Million-Year-Old Fossil Rewrites the Look of Earth's First Flying Vertebrates
For decades, paleoartists have imagined pterosaurs in vivid, colorful hues. Now, a stunning new fossil analysis suggests that at least one species really did shimmer with shifting iridescent colors, much like modern starlings and pigeons.
The discovery comes from a specimen of Sinopterus dongi, unearthed in northeastern China. Scanning electron microscopy revealed layered arrays of melanosomes within the creature's pycnofibers — structures that closely resemble those producing iridescence in modern bird feathers. Computer simulations predict deep greens and magentas that shifted with viewing angle.
The diversity and organization of melanosomes matches patterns seen only in warm-blooded birds and mammals, suggesting elevated metabolisms and sophisticated thermoregulation — traits long debated among paleontologists. The finding also hints that iridescent displays may have played a role in courtship rituals.
"This is one of the most intriguing and surprising fossil discoveries of the past few years." — Dr. Steve Brusatte, University of Edinburgh
📄 Original paper (bioRxiv) · Science News summary
🧬 Scientists May Have Found a New Way to Mass-Produce Cancer-Fighting Immune Cells
For more than a decade, cancer immunotherapy has been dominated by T cells. CAR-T therapies can be powerful against some blood cancers, but they remain expensive, highly personalized, and much harder to use against solid tumors.
Now researchers at USC Stem Cell have shifted attention to a different immune lineage: granulocyte-monocyte progenitors, or GMPs — early precursor cells that can produce macrophages, the immune system’s “first responders.”
Macrophages are especially interesting because they naturally enter tumors, engulf abnormal cells, and help coordinate immune responses. But mature macrophages are difficult to grow in large numbers, hard to genetically engineer, and not ideal for freezing and storage.
The USC team worked one step earlier — with GMPs before they mature. Using a defined chemical cocktail, they managed to keep mouse and human GMPs in a progenitor-like state while allowing them to expand long-term in the lab. That is important because long-term self-renewal in the blood system was traditionally associated mainly with true hematopoietic stem cells, not more committed progenitors.
Then the researchers engineered these GMPs with CAR receptors so they could recognize cancer cells. They also added a CAR-Fc design that can recruit other immune cells and help activate broader anti-tumor responses.
In mouse experiments, the engineered GMPs settled into bone marrow and other blood-forming tissues, where they continuously generated tumor-infiltrating macrophages and other myeloid cells. The cells suppressed CD19-positive leukemia and HER2-positive solid tumors, and the dual CAR-Fc design showed stronger effects in allogeneic cancer models.
The same platform also restored antibacterial defense in mice with chronic granulomatous disease, an inherited immune deficiency disorder.
Why this matters: this is not just another CAR-T variant. It is a possible manufacturing breakthrough for an entirely different branch of the immune system — one that may be better suited for solid tumors and potentially easier to produce as an off-the-shelf therapy.
The important caveat: these are still preclinical results in mice. The real test will be whether the platform is safe, durable, and effective in humans.
But the idea is powerful: instead of only engineering mature immune cells, scientists may be learning how to grow a renewable upstream factory that keeps producing cancer-fighting cells from inside the body.
Paper: Cell
https://www.cell.com/cell/fulltext/S0092-8674(26)00643-4
Summary: ScienceDaily
https://www.sciencedaily.com/releases/2026/06/260620100317.htm
#Immunotherapy #Cancer #StemCells #CellTherapy #Biotech
⚛️ Physicists Create a Strange New Quantum State — the “Fractional Fermi Sea”
Quantum simulators are usually built to recreate known physics in a clean, controllable setting. But a team at the University of Innsbruck has pushed the idea further: they engineered a highly unusual quantum state that appears to go beyond one of the standard frameworks for one-dimensional matter.
The researchers used ultracold cesium atoms confined in one-dimensional tubes and drove them far from equilibrium by cycling the interactions between strongly repulsive and strongly attractive regimes. Normally, this kind of forcing might be expected to heat the system and wash out any structure.
Instead, the atoms reorganized into something unexpectedly ordered.
The state is called a “fractional Fermi sea” — a highly excited, yet stable configuration where particles behave as if the usual occupancy rules have been replaced by a reduced, fractional version. It does not literally rewrite the Pauli exclusion principle, but it realizes behavior long associated with Haldane’s generalized exclusion statistics: particles filling available states in a fractional way.
What makes this especially interesting is that the correlations do not fit neatly into the familiar Tomonaga–Luttinger liquid picture, the classic theory used to describe many one-dimensional quantum systems. The particles show distinctive Friedel oscillations — ripples in density correlations — and decay patterns that point to a new kind of critical quantum phase.
In simple terms: the system is not cold, calm, and sitting in its lowest-energy state. It is highly excited — but not chaotic. Hidden order emerges from the drive.
The theoretical work has now been published in Physical Review Letters, while the companion experimental realization is available as a preprint.
Why it matters: quantum simulators are no longer just “physics replay machines.” They can create and probe states of matter that may be extremely hard — or impossible — to find naturally, opening new ways to study strongly correlated systems, exotic statistics, and future quantum technologies.
The big takeaway: sometimes the deepest order in quantum matter appears not when everything is perfectly still, but when a system is pushed far from equilibrium and refuses to fall apart.
📄 Theory paper: Physical Review Letters 136, 230402 (2026)
https://doi.org/10.1103/j3s5-gjpf
📄 Experimental preprint:
https://arxiv.org/abs/2602.17657
📖 Summary:
https://www.uibk.ac.at/en/newsroom/2026/a-novel-critical-quantum-phase/
#QuantumPhysics #CondensedMatter #QuantumSimulation #Physics
🪐 Astronomers Found Two Giant Planets Less Dense Than Cotton Candy
Astronomers have confirmed the existence of two of the puffiest planets ever discovered — gas giants roughly the size of Jupiter, but with densities so low they are less dense than cotton candy.
The pair, named TOI-791 b and TOI-791 c, orbit an F7-type star about 1,110 light-years from Earth in the southern constellation Volans. Their numbers are almost hard to believe: TOI-791 b has an average density of just 0.038 g/cm³, while TOI-791 c comes in at 0.047 g/cm³.
For comparison, Jupiter’s average density is about 1.33 g/cm³. Cotton candy is roughly 0.05 g/cm³. Earth is around 5.5 g/cm³.
That makes these planets not just “fluffy” by astronomical standards — they are among the lowest-density giant planets ever detected.
The discovery, published in Monthly Notices of the Royal Astronomical Society, is especially valuable because the two planets appear to be locked in a rare 5:3 orbital resonance: for every five orbits of the inner planet, the outer one completes almost exactly three. This gravitational interaction slightly shifts the timing of their transits across the star, allowing astronomers to estimate their masses.
🔹 The planets were first spotted by volunteers in the Planet Hunters TESS citizen-science project
🔹 Confirmation required eight years of observations
🔹 Data from the ASTEP telescope at Antarctica’s Concordia Station were crucial
🔹 Each transit lasts more than 11 hours — unusually long for ground-based observations
🔹 Only a handful of systems are known to contain multiple super-puff planets
The leading idea is that these worlds may have relatively small cores surrounded by enormous hydrogen- and helium-rich atmospheres. But exactly how such diffuse planets form — and how they keep their atmospheres for so long — remains an open question.
Important caveat: these measurements come from transits and orbital timing effects, not from direct imaging. The densities are robust within the current model, but the planets’ true atmospheric composition will require follow-up observations — potentially with the James Webb Space Telescope.
Super-puff planets are strange because they sit at the edge of what our planet-formation models can comfortably explain.
If a giant planet can be less dense than cotton candy and still hold itself together, what else is out there that our theories have not yet learned to expect?
📄 Source: https://academic.oup.com/mnras/article-lookup/doi/10.1093/mnras/stag864
#exoplanets #astronomy #space #TESS #superpuffs
🪐 A Wobbling “Peanut” Asteroid May Still Carry Traces of Ancient Water
NASA’s Lucy mission has revealed one of the strangest small worlds ever seen up close: asteroid Donaldjohanson — a young, peanut-shaped rock in the main asteroid belt that tumbles through space and still preserves chemical hints of liquid water from its distant past.
Lucy flew past Donaldjohanson on April 20, 2025, at about 30,000 mph, coming within just 650 miles of the asteroid. The encounter was meant partly as a rehearsal before Lucy reaches Jupiter’s Trojan asteroids in 2027. Instead, it became a science story of its own.
Donaldjohanson does not rotate like a simple spinning rock. Data from Lucy show that it tumbles end-over-end once every 10.5 Earth days, while also wobbling around its long axis every 26.5 days — more like an unstable top than a normal asteroid.
Its shape is just as unusual. Donaldjohanson is a contact binary: two lobes joined by a narrow neck, giving it a cosmic peanut-like form. Scientists think it formed about 155 million years ago, when fragments from a violent collision gently came back together under their own gravity.
Since then, sunlight has been slowly reshaping it. Through the YORP effect — a tiny torque caused when sun-warmed surfaces radiate heat back into space — Donaldjohanson’s spin appears to have slowed by at least a factor of 10 over the last 20–60 million years. As the rotation changed, loose material likely slid down its slopes, softening craters and reshaping the surface.
But the most intriguing clue came from Lucy’s infrared data: iron-rich clay minerals on the surface. These minerals form in the presence of liquid water, meaning Donaldjohanson’s parent body once experienced aqueous alteration. But unlike Bennu and Ryugu, which contain magnesium-rich clays suggesting longer exposure to water, Donaldjohanson’s chemistry points to a much shorter episode.
🔹 Donaldjohanson is a bilobed “contact binary” asteroid
🔹 It tumbles on two axes, with rotation periods of 10.5 and 26.5 days
🔹 Its current body likely formed around 155 million years ago
🔹 Sunlight gradually slowed its spin through the YORP effect
🔹 Iron-rich clays suggest liquid water was present — but only briefly
🔹 The flyby was also a successful rehearsal for Lucy’s Trojan asteroid encounters, beginning with Eurybates in August 2027
Important caveat: this was a fast flyby, not an orbital mission or a sample return. Lucy measured the surface remotely; the asteroid’s interior remains unknown.
Still, Donaldjohanson matters because it gives scientists a rare comparison point. Bennu and Ryugu are near-Earth asteroids with long migration histories. Donaldjohanson is a much younger main-belt object that stayed closer to its birthplace. Its strange shape, unstable spin, and brief water history offer a fresh clue to how small bodies evolved — and how water-rich material may have moved through the early Solar System.
📄 Sources: https://www.science.org/doi/10.1126/science.aec0503
#NASA #LucyMission #Asteroid #PlanetaryScience #SolarSystem
🪐 A Rare Meteorite May Preserve Evidence of a Lost World from the Dawn of the Solar System
Scientists at the University of Colorado Boulder have uncovered what may be the strongest evidence yet for a vanished protoplanet — a planetary embryo that once orbited the young Sun more than 4.5 billion years ago before being destroyed in a catastrophic collision.
The clue comes from an unusual meteorite known as Northwest Africa (NWA) 12774, discovered in the Sahara Desert. It belongs to the angrites, one of the rarest meteorite groups ever found. Out of more than 80,000 known meteorites, only a few dozen are classified as angrites. These rocks formed during the earliest stages of solar system history, just a few million years after the Sun was born.
What makes NWA 12774 remarkable is its mineral chemistry. Researchers found clinopyroxene crystals enriched in aluminum — a signature that indicates formation under enormous pressure. Their calculations suggest pressures exceeding 17.5 kilobars, more than 17 times greater than the pressure at the bottom of the Mariana Trench.
Such conditions could not have existed inside a small asteroid.
The results imply that the meteorite’s parent body had a radius of at least 1,000 km. Because the crystals preserve delicate structures that would likely not survive deep burial, the original world may have been much larger — potentially approaching the size of the Moon and perhaps even Mars.
🔹 Evidence points to a planetary embryo at least 1,000 km in radius
🔹 Formation pressures exceeded 17.5 kilobars
🔹 Its composition differs significantly from Earth and Mars
🔹 It may represent a previously unknown pathway of planetary evolution
🔹 Fragments of similar lost worlds could still be hiding in meteorite collections
The study suggests that the early solar system was far more diverse than previously thought. Many planetary embryos likely formed, collided, merged, or were destroyed before the planets we know today emerged.
How many lost worlds helped build the solar system we live in?
📄 Original paper (Earth and Planetary Science Letters) · ScienceDaily
#astronomy #space #meteorite #planetaryscience #solarsystem
⚠️ Vaping Likely Causes Lung and Oral Cancer — Most Definitive Review Yet
A landmark review led by UNSW Sydney has delivered the strongest verdict yet on e-cigarettes: nicotine vapes are likely to cause cancers of the lungs and oral cavity on their own — not just as a gateway to smoking.
Published in Carcinogenesis, the study examined over 100 studies since 2017. Unlike earlier work that compared vaping to smoking, this review focused exclusively on whether e-cigarettes cause cancer independently.
The evidence came from three converging directions:
🔹 Carcinogens identified in vape aerosols — volatile organic compounds and metals released by heating coils
🔹 Human biomarkers showing DNA damage, oxidative stress, and tissue inflammation in vapers
🔹 Mouse studies producing lung tumors from direct vape aerosol exposure
🔹 Case reports of unusually aggressive oral cancers in young, heavy vapers with no traditional risk factors
The numbers are striking: dual users (vape + smoke) face a four-fold higher lung cancer risk than smokers alone. Young people who start vaping are three times more likely to become regular cigarette smokers.
Important caveat: this is a review of existing evidence, not a long-term population study. Quantifying the exact cancer risk will take decades of epidemiological data. But the biological signals are already strong and consistent.
The historical parallel is sobering. It took nearly a century — from the mid-1800s to the 1964 US Surgeon General's report — to prove that smoking causes lung cancer. "E-cigarettes were introduced about 20 years ago. We should not wait another 80 years to decide what to do," said co-author A/Prof. Freddy Sitas.
For millions of young people who took up vaping believing it was harmless, this review changes the equation.
📄 Original paper (Carcinogenesis) · ScienceDaily
#Vaping #Cancer #PublicHealth #Science #Carcinogenesis
⚛️ A New Particle Has Been Found at the Large Hadron Collider
CERN’s LHCb collaboration has announced the discovery of Ωcc⁺ — a baryon made of two charm quarks and one strange quark.
It was the final missing particle in the family of doubly charmed baryons. LHCb discovered Ξcc⁺⁺ in 2017 and Ξcc⁺ in 2026. With Ωcc⁺, physicists have now completed the basic trio predicted by strong-interaction theory more than 50 years ago.
Ωcc⁺ lives for an incredibly short time: it is produced in proton–proton collisions, travels only a tiny fraction of a millimetre, and then decays. Scientists reconstructed it from the tracks left behind in the LHCb detector.
This is an important test of quantum chromodynamics — the theory that explains how quarks are bound inside protons, neutrons and other particles.
Source: CERN / LHCb
https://home.cern/news/news/physics/lhcb-collaboration-discovers-new-proton-particle
🩻 The Company Behind Midjourney Just Revealed a Machine That Could Scan Your Entire Body in 60 Seconds
Most people know Midjourney as one of the world’s leading AI image generators.
Now the company is attempting something far more ambitious: reinventing medical imaging itself.
Midjourney has unveiled Midjourney Scanner, an experimental full-body imaging system that uses thousands of ultrasound transducers arranged around a person immersed in a water-filled scanning chamber. The goal is to create a detailed 3D map of the human body in about one minute — without radiation and without the massive magnets used in MRI machines.
The concept is surprisingly simple: instead of moving a single ultrasound probe across the body, surround the entire body with ultrasound sensors and capture everything at once.
According to Midjourney founder David Holz, the long-term vision is not just medical diagnosis, but something much bigger:
🔹 Regular full-body scans available to ordinary people
🔹 Tracking changes in muscles, fat, organs, and tissues over time
🔹 Building a continuously updated digital model of your body
🔹 Detecting health changes long before symptoms appear
If the technology succeeds, it could fundamentally change preventive medicine. Today, most people only receive detailed internal imaging after something goes wrong. Midjourney’s vision is a future where full-body imaging becomes as routine as stepping on a scale.
There are important caveats.
The current system is an early prototype. Only a small number of people have been scanned so far, and the device is not yet approved for medical diagnosis. Whether it can eventually match the capabilities of MRI or CT remains unknown.
Still, the announcement raises a fascinating question:
What if the next major breakthrough in medicine doesn’t come from a hospital, pharmaceutical company, or medical device giant — but from an AI company best known for generating artwork?
The company that helped computers imagine images is now trying to help humans see inside themselves.
📄 Source: Midjourney Medical announcement
https://www.midjourney.com/medical/blogpost
#Medicine #HealthTech #AI #MedicalImaging #Ultrasound #FutureOfMedicine #Midjourney
#science
🧠 A Copper-Based Compound May Help the Brain Clear Alzheimer’s Proteins — by Repairing Its “Waste Pumps”
Most Alzheimer’s drug research has focused on attacking amyloid plaques directly. A new study from Monash University suggests a different route: what if the brain’s waste-clearance system could be repaired instead?
The compound is called Cu(ATSM) — a copper-delivering molecule already studied in human safety trials for Parkinson’s disease and ALS. In a mouse model of Alzheimer’s, researchers found that Cu(ATSM) restored levels of P-glycoprotein, or P-gp — a transporter at the blood-brain barrier that helps move amyloid-beta out of the brain.
Think of P-gp as part of the brain’s drainage system. When these pumps weaken, toxic proteins can accumulate. When the researchers boosted them with Cu(ATSM), the results were striking:
• 42% reduction in toxic amyloid-beta over 56 days
• nearly 44% improvement in spatial learning
• 24.1% increase in P-gp clearance pumps at the blood-brain barrier
• evidence that repairing the blood-brain barrier may help lower amyloid burden and improve cognition
The important caveat: this was not a human Alzheimer’s trial. The results come from APP/PS1 mice — a widely used model of the disease — so the next question is whether the same mechanism works in people.
Still, the idea is powerful. Instead of only trying to destroy plaques after they form, future therapies might also help the brain restore its own clearance infrastructure.
If Alzheimer’s is partly a “drainage failure,” could repairing the brain’s plumbing become one of the next big strategies in neurodegeneration?
📄 Source: https://doi.org/10.1021/acschemneuro.6c00252
#Alzheimers #Neuroscience #DrugDiscovery #BloodBrainBarrier #CopperTherapy #science
⚡ Google TurboQuant Cracks the AI Memory Wall — And It's Not About Bigger Models
At ICLR 2026, Google Research introduced TurboQuant, a new two-stage compression method that can reduce transformer KV cache memory usage by 40–60% without retraining and with minimal impact on model quality.
The KV cache — which stores information about every token processed during a conversation or document — has become one of the biggest bottlenecks in modern LLM inference. As context windows expanded from thousands to millions of tokens, KV caches often began consuming more GPU memory than the model weights themselves.
TurboQuant tackles this problem directly. The first stage, called PolarQuant, rotates cached vectors into a representation that is more friendly to quantization. The second stage uses a quantized Johnson–Lindenstrauss projection to compress the remaining error signal into just one bit per dimension. Together, these techniques reduce KV cache storage requirements to roughly 3–4 bits per element.
The implications are significant. Lower memory consumption means more concurrent users per GPU, larger context windows, and lower inference costs without changing the underlying model. In a world where AI infrastructure spending is growing at an unprecedented pace, improvements in efficiency can be just as valuable as improvements in model capability.
Nikolas Bush Take
1. The industry is entering an efficiency era.
For the last several years, the default answer to better AI has been bigger models, larger datasets, and more compute. TurboQuant is part of a growing trend suggesting that algorithmic efficiency may deliver some of the largest gains going forward. A 50% reduction in memory requirements achieved through mathematics rather than billion-dollar infrastructure investments changes the economics of AI deployment.
2. Infrastructure is becoming the real battleground.
Model quality is increasingly converging among frontier AI labs. The next competitive advantage may come from serving those models faster, cheaper, and at larger scale. Techniques such as TurboQuant directly target one of the most expensive components of large-scale inference: memory. In that sense, this is not merely a research paper — it's an infrastructure play.
3. The most important signal is reproducibility.
Breakthroughs matter only if the broader ecosystem can adopt them. If TurboQuant proves effective across different model architectures and hardware environments, it could evolve into a standard optimization layer for inference stacks, much like FlashAttention became a standard component of modern training and inference pipelines.
🚨 The U.S. Government Just Forced Anthropic to Switch Off Fable 5 and Mythos 5
This may be the first real “game over” moment for the old AI deployment model.
On June 11, 2026, Anthropic received a U.S. government export-control directive citing national security authorities. The order required the company to suspend access to Claude Fable 5 and Claude Mythos 5 for any foreign national — not only outside the United States, but also inside the country.
That includes foreign-national employees of Anthropic itself.
To comply, Anthropic says it had to disable Fable 5 and Mythos 5 for all customers globally. Other Claude models remain available. For now.
The reason appears to be a claimed jailbreak method for Fable 5.
Anthropic reviewed the demonstration and argues that the method only identifies a small number of previously known, simple vulnerabilities — the kind of tasks already possible with other public frontier models. According to the company, it did not receive a single example of a jailbreak producing a genuinely harmful result.
And this is where the conflict becomes much bigger than Anthropic.
The real issue is the standard of proof.
If asking a model to read a codebase and identify bugs is enough to trigger a national-security shutdown, then almost every next-generation frontier model becomes politically vulnerable by default. Future models will not get weaker. They will get stronger. So the regulatory question is no longer theoretical.
Who gets access?
Who counts as trusted?
And which jurisdiction gets to decide?
This is a tectonic shift in AI regulation.
Until now, governments mostly relied on voluntary commitments, safety frameworks, evaluations and post-release pressure. Now we have something much more direct: a forced shutdown of a commercial frontier model after deployment.
If this precedent holds, any advanced AI release can be stopped by a government letter.
And the location of frontier AI development may become less about talent, compute or product — and more about citizenship, export law and political risk.
There is also a very awkward human side to this.
If access to leading AI systems starts being restricted by nationality or “U.S. person” status, the blast radius could reach some of the most important people in AI:
• Andrej Karpathy — recently joined Anthropic; publicly described as Slovak-Canadian
• Demis Hassabis — British co-founder and CEO of Google DeepMind
• Geoffrey Hinton — British-Canadian pioneer of deep learning
• Yoshua Bengio — Canadian AI researcher and safety advocate
• Ilya Sutskever — publicly described as Israeli-Canadian; co-founder of Safe Superintelligence
• Mustafa Suleyman — British CEO of Microsoft AI
• Aidan Gomez — British-Canadian co-founder and CEO of Cohere
The point is not that all of them are immediately blocked from anything. The point is that a citizenship-based access regime for frontier AI would create absurd edge cases almost instantly.
The U.S. could end up restricting the very people who built the field.
So no, this probably does not mean AI progress is over.
But it may mean the era of “just ship the model globally” is over.
Order a truckload of popcorn.
China is definitely watching.
#Anthropic #Fable5 #Mythos5 #AIRegulation #ExportControl #FrontierAI #AISafety #science
🧬 Ancient “Language Switches” Hidden in Human DNA — And Neanderthals Had Them Too
A new study from the University of Iowa suggests that a tiny set of ancient genetic regulators may have played an outsized role in shaping human language ability.
These sequences are called HAQERs — Human Ancestor Quickly Evolved Regions. They make up less than 0.1% of the genome, yet appear to have around 200 times more influence on language-related traits than other genomic regions.
The findings, published in Science Advances, push the biological roots of language much deeper into our evolutionary past.
Researchers analyzed genetic and language-development data from 350 Iowa children followed over decades, then used an evolutionary-stratified polygenic score to trace how different layers of our genome contributed to language ability across roughly 65 million years of evolutionary history.
HAQERs are not genes themselves. Think of them more like molecular “volume knobs”: regulatory switches that dial the activity of genes up or down, especially during brain development. Even FOXP2 — the famous gene long associated with speech and language — appears to interact with this regulatory network rather than acting as a single “language gene.”
The most intriguing part: these same regulatory regions were already present before modern humans and Neanderthals split. Some language-associated variants may even have been more common in Neanderthals than in us.
That does not prove Neanderthals spoke like modern humans. But combined with archaeological evidence of tool-making, symbolic behavior, and complex social life, it strengthens the case that sophisticated communication may have emerged long before Homo sapiens stood alone.
There is also an evolutionary tradeoff. HAQERs are linked to fetal brain development — but larger brains and bigger infant skulls would have made childbirth more dangerous before modern medicine. In other words, evolution may have hit a ceiling: better language “hardware” came with a serious survival cost.
Key takeaways:
• HAQERs occupy less than 0.1% of the genome
• They may have ~200× more influence on language-related traits than other genomic regions
• These regulatory switches predate the human-Neanderthal split
• FOXP2 appears to be part of a broader regulatory system, not a standalone “language gene”
• The evolution of language may have been constrained by the risks of childbirth
The next step is to separate inherited genetic effects from the language environment parents create for their children — a question that could eventually help us better understand language disorders.
If Neanderthals had part of the same biological toolkit for language, how close were they to truly speaking?
📄 https://doi.org/10.1126/sciadv.aed5260
#genetics #language #neanderthals #evolution #neurosciencex
🧪 Could Tiny Mineral Particles Have Helped Spark Life on Earth?
One of science's biggest unanswered questions is how life emerged from nonliving matter. A new hypothesis suggests that the answer may lie in something surprisingly small: mineral nanoparticles.
Prof. Yongdong Jin of Shenzhen University has proposed the "Nanozyme Hypothesis" — the idea that naturally occurring mineral nanoparticles may have acted as primitive catalysts on the early Earth, helping transform simple chemicals into increasingly complex organic molecules.
Billions of years ago, our planet was a vast chemical laboratory. Around volcanoes, hydrothermal vents, and hot springs, intense heat and pressure produced nanoparticles made of metals, metal oxides, and sulfides. According to the hypothesis, these particles behaved like enzyme-like catalysts, accelerating reactions that otherwise would have occurred far too slowly.
Jin describes this process as a form of "inorganic photosynthesis" — chemistry powered by minerals long before biological cells existed.
What makes the idea particularly interesting is that it may help bridge several competing origin-of-life models. Rather than choosing between an RNA world, metabolism-first, or lipid-first scenario, nanozymes could have provided the chemical platform that enabled all of them to emerge.
The proposed functions of nanozymes include:
• Catalyzing key chemical reactions
• Concentrating molecules on their surfaces
• Protecting fragile compounds from UV radiation
• Using light to promote specific reactions
• Converting environmental energy into chemically useful forms
Remarkably, mineral nanoparticles are still abundant on Earth today, and many are known to exhibit enzyme-like behavior. The paper also highlights gold nanoparticles as particularly efficient catalysts under certain prebiotic conditions.
If future experiments support this hypothesis, it could reshape the search for life beyond Earth. Worlds with volcanic activity, liquid water, and the right mineral chemistry might possess the same ingredients that once helped kick-start biology here.
Was life an extraordinarily rare accident — or a natural consequence of chemistry under the right conditions?
📄 Original paper (Research, Dec 2025) · ScienceDaily summary
#OriginOfLife #Nanozymes #Abiogenesis #Astrobiology #EarthScience #science
One of the biggest mysteries in astrophysics may be getting closer to an answer.
A new study published in Physical Review Letters suggests that the famous “Amaterasu particle” — one of the most energetic cosmic rays ever detected — may not have been a proton at all. Instead, it could have been an atomic nucleus heavier than iron.
Discovered in 2021 by the Telescope Array in Utah, the Amaterasu particle carried an astonishing 240 exa-electron volts (EeV) of energy. That’s roughly the same kinetic energy as a fast-moving tennis ball — compressed into a single atomic nucleus.
What puzzled scientists most was its apparent origin. The particle seemed to arrive from a vast cosmic void, a region of space with no obvious object capable of accelerating particles to such extreme energies.
Using detailed simulations, researchers found that ultraheavy nuclei may survive intergalactic journeys far better than protons. While lighter particles lose energy through interactions with background radiation, nuclei heavier than iron can retain much more of their original energy over cosmic distances.
If correct, the finding could help explain how particles like Amaterasu reach Earth from seemingly impossible locations.
Possible sources include:
• Collapsing massive stars
• Neutron star mergers
• Gamma-ray bursts
Future instruments such as AugerPrime and the proposed Global Cosmic Ray Observatory may reveal whether these ultraheavy nuclei are truly responsible for some of the most extreme particles ever observed.
Every ultrahigh-energy cosmic ray is a messenger from one of the universe’s most violent events. Understanding what these particles are made of may help us uncover where they come from — and how nature accelerates matter to energies far beyond anything humans can create.
What do you think is the most likely source of particles this extreme?
📄 Original paper · ScienceDaily summary
#CosmicRays #Astrophysics #ParticlePhysics #SpaceScience #NeutronStars
🤖 A 100-billion-parameter AI model was just trained across random GPUs scattered around the globe — not in a billion-dollar datacenter. And it worked.
Macrocosmos, building on the Bittensor network, has demonstrated Orion-100B: a 100B-parameter language model trained across geographically distributed Nvidia A100 GPUs.
Their system, called IOTA, splits the model itself across many machines using 16 pipeline-parallel stages — unlike earlier decentralized approaches that often required each participant to host the full model.
The result: more than 30% model FLOP utilization and roughly 65% of the efficiency of a comparable datacenter setup.
The technical challenge was serious. Macrocosmos had to reduce massive inter-GPU traffic, handle unstable nodes, work with heterogeneous hardware, and keep the training process alive across a decentralized network. Their ResBM activation compression technique reportedly reduced traffic from around 150MB to 2.2MB per stage. The team says it ran more than 700 experiments before scaling from a 1.5B test model to 100B in about a month.
Nikolas Bush’s Take:
This story matters far beyond the technical achievement.
First, if this approach scales, it could change the economics of AI training. A 100B-parameter model trained on geographically distributed A100 GPUs at roughly 65% of comparable datacenter efficiency is not yet a replacement for hyperscaler infrastructure — but it is a serious signal. It suggests that large-scale AI training may not always require a single billion-dollar GPU cluster.
Second, the Bittensor layer is important. This is not just a distributed computing experiment; it is an incentive system. GPU owners can be rewarded for contributing compute, which creates the foundation for a market around idle hardware. In simple terms, this could become something like “Airbnb for AI training”: monetizing unused GPU capacity the way Airbnb monetized unused rooms.
Third, the uncomfortable part: decentralized AI training has often been dismissed by the mainstream AI community as impractical. Orion-100B does not prove that decentralized training will beat datacenters tomorrow. But it does prove that the idea deserves to be taken much more seriously.
The next phase — permissionless participation from consumer hardware — will be the real test. If that works, the AI infrastructure map could become much more distributed than many people expected.