2026-01-06 23:00:00
This year saw the meteoric rise of a promising new therapy for brain health.
Microglia are the silent guardians of the brain. They hunt down pathogens, clean up toxic protein clumps, and even shape the brain’s wiring. They’re also robust. Neurons can’t divide to generate new copies of themselves. But microglia can renew, especially during inflammation, stroke, or diseases that erode cognition.
And yet this regenerative ability has a limit, especially when the cells harbor genetic mutations. One solution? Replace diseased or injured cells with a fresh supply.
This year saw a meteoric rise in microglia replacement therapy, with clinical trials highlighting its brain-protecting potential. Refreshing microglia could, in theory, boost their beneficial effects.
Tinkering with the brain’s complex immune system isn’t straightforward, but “microglia replacement has emerged as a groundbreaking paradigm,” wrote Bo Peng and colleagues at Fudan University. The therapy could tackle a range of conditions from rare genetic diseases to more familiar foes such as Alzheimer’s.
Microglia are odd ducks. Like other immune cells that patrol the body, they usually start out as blood stem cells in bone marrow before migrating to the brain. Once settled, they stay at their post, exclusively protecting the brain.
The cells are usually shaped like shrubs in need of a haircut. But once activated, they shrink into puff balls and recruit other brain cells to fight off invaders and prevent brain damage.
Microglia also reconfigure the brain’s wiring. They prune extra synapses—connection points that allow neurons to talk to each other—and pump out nutritious molecules to support established neural networks and encourage baby neurons to grow.
It’s no wonder that when microglia go awry so does the brain. This happens in Alzheimer’s, other neurodegenerative diseases, and even just as we age. But more commonly, it’s because of genetic mutations in the cells.
Gene therapy is seemingly the best way to fix these problems. But microglia are notoriously terrible candidates. A gene therapy is usually shuttled into cells within safe viral carriers or tiny bubbles of fat. Few of these can enter the brain’s immune cells. Microglia-specific carriers exist, but they need to be injected directly into the brain. Complications from surgery aside, injected cells only reach a small area—hardly enough to make a notable difference.
Microglia replacement gets around this roadblock. Replacing mutated or aged cells with a healthy supply could correct genetic problems and “replenish populations lost to degeneration, inflammation, or developmental failure,” wrote Peng and colleagues.
Transplanting healthy donor microglia directly into the brain is nearly impossible because existing microglia often turn against the new arrivals. But because microglia start life as blood stem cells, a bone marrow transplant from a healthy, matching donor is a viable alternative. Once mature, the cells journey to the brain, where they divide and thrive.
The first and most taxing step of a bone marrow transplant is making space for the new cells. This requires extensive radiation or chemotherapy, but often without direct treatment to the head. The step also destroys the recipient’s immune system, leaving them vulnerable to infections and at higher risk for cancer.
Unfortunately, the standard treatment doesn’t work for microglia replacement, largely because diseased microglia still living in the brain leave little room for healthy new cells to settle.
But in 2020, Peng’s team developed a drug that depleted microglia in the brains of mice, making room for healthy cells. Then this July, Peng and colleagues successfully used a bone marrow transplant to treat a fatal brain disease called CAMP (CSF1R-associated microgliopathy). Here, mutations in a gene critical to microglia survival destroys the cells’ health, causing the brain’s wiring to physically disintegrate over time. Within a few years, people with the condition struggle with everyday reasoning, motor skills, and often fall into depression.
In mice and eight people in a small clinical trial with the disease, the treatment halted their decline for at least two years without notable side effects.
Researchers have also seen early success in other conditions.
Sandhoff disease is one that stands out. People with this inherited condition can’t break down certain fats, which leads to neuron death. The disease is partly caused by miscommunication between microglia and neurons. Normally, microglia shuttle an enzyme to neurons that helps recycle the fatty molecules. Mutated microglia can’t do this. In mice, bone marrow transplants of cells without the mutation improved the mice’s mobility, survival, and brain health.
Another study tackling Sandhoff disease used a different, more daring method. The team isolated the young cells that eventually become microglia and grew them in petri dishes.
After radiation therapy in mice, targeted to their heads, the team infused the healthy lab-grown microglia into the mice’s brains. The cells made themselves at home and worked as normal. The treatment avoided full-body radiation and damage to other organs but the approach could also kill off stem cells that generate new neurons in the brain and so may be limited in its efficacy.
Immune rejection also poses a major stumbling block. But induced pluripotent stem cells (iPSCs), where a person’s skin cells are reprogrammed into other cell types, may reduce the risk. In a proof of concept also in mice, microglia made from iPSCs replaced damaged microglia and slowed neurodegeneration by gobbling up toxic proteins related to Alzheimer’s.
Physicians will need to study the long-term consequences of head-only radiation, and test microglia replacement in a wider range of diseases. If all goes well though, the versatile cells could be used to even ferry medications into the brain like Trojan horses.
In just five years, microglia replacement has gone from animal studies to the first clinical treatment. Once a niche moonshot, it’s now “a topic of great interest in neuroscience and cell therapy,” wrote the team. While there’s plenty more work to do, the therapy could “mature from early breakthroughs into a generalizable platform across neurological diseases.”
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2026-01-05 23:00:00
US nuclear capacity is forecast to rise 63 percent in the coming decades thanks largely to data-center demand.
Nuclear energy has had a tough few decades, bedeviled by high costs and waning public support. But AI’s appetite for electricity could be a shot in the arm for the beleaguered industry.
AI’s energy demands are rising quickly, with global data center electricity use expected to double by the end of the decade. And nuclear power’s ability to provide large amounts of emission-free baseload power is hugely attractive for AI firms trying to balance their energy needs against climate commitments.
Google, Amazon, Meta, and major data center operators are signing power-purchase agreements with existing reactors, investing in the development of advanced small-modular reactors, and even helping restart shuttered nuclear plants.
This is a significant turnaround for a sector that has long been struggling to compete with cheap natural gas and rapidly falling renewable energy prices. But if the AI industry’s energy demands continue to grow as expected, the nuclear energy industry could be one of the big winners.
The most immediate impact of this trend could be to extend the lives of existing plants. In June, Meta inked a long-term contract with the utility Constellation Energy to keep its Clinton Clean Energy Center in Illinois operating for a further 20 years, after the plant faced closure due to the upcoming expiry of a credit program for low-emission energy producers.
Constellation says more deals could soon be coming. “We’re definitely having conversations with other clients, not just in Illinois, but really across the country, to step in and do what Meta has done, which is essentially give us a backstop so that we could make the investments needed to re-license these assets and keep them operating,” CEO Joe Dominguez told Reuters.
But demand for nuclear power is so acute that technology companies are also looking to bring already shuttered plants back online. Constellation closed a reactor at its Three Mile Island site in 2019 for economic reasons, but Microsoft has since stepped in to bring it back to life. Last September, the company agreed to a 20-year power purchase agreement to fuel its data centers, giving Constellation the certainty required to restart the reactor.
And Google appears to be following suit. In October, the company announced it was partnering with the utility NextEra Energy to bring back to life the Duane Arnold Energy Center, which closed in 2020. The company has committed to buying power from the facility for the next 25 years, and it could be back up and running by 2029.
But perhaps the biggest impact of Silicon Valley’s new love of nuclear could be a boom in investment in fresh nuclear capacity. Given how long it takes to build and commission nuclear plants, it may be a while before that impact is felt, but this could boost long-term confidence in the sector.
Last December, Meta announced it was seeking proposals from nuclear developers to help meet its energy demands. The company said that it was looking for 1 to 4 gigawatts of new capacity starting in the early 2030s, and that it was open to proposals to build either regular nuclear reactors or small modular reactors—an emerging class of advanced reactors that have yet to be commercialized.
These small reactors have caught the attention of technology giants due to their potential for lower costs and fast deployment. And they typically produce less than a third of the output of a regular nuclear reactor, which makes them suitable for powering smaller facilities. But their modular design means they can also be combined to create higher capacity plants.
Google has agreed to purchase power from Kairos Power, which is developing a fluoride-salt-cooled small modular reactors, becoming the first company to sign a commercial contract with the startup. The agreement covers six or seven reactors, with the first unit targeted for 2030 and the rest by 2035, supplying Google data centers with up to 500 megawatts of nuclear power.
In a similar vein, Amazon has agreed to buy electricity from four small modular reactor modules under development by X-Energy in Washington State, with the option to buy up to eight additional modules once they’re built. The data center operator Equinix has also placed a preorder for 20 transportable microreactors from California-based Radiant Nuclear.
A recent Bloomberg Intelligence report forecasts that US nuclear capacity could rise 63 percent by 2050 thanks in large part to demand from data centers. This would represent a net gain of 61 gigawatts in generation, most of which would come after 2035 when small modular reactors are expected to transition from demonstration projects to scalable commercial deployment.
Whether this comes to fruition will depend largely on whether big tech’s energy demands continue to balloon. There is mounting concern the industry is in an AI bubble primed to burst at any minute, which could put a major dampener on the nuclear resurgence.
But for the time being at least, the industry’s future is looking considerably rosier than it was a decade ago.
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2026-01-03 23:00:00
The passage of time is inextricably tied to how humans perceive our own experiences. We confuse our perspective on reality with reality itself.
“Time flies,” “time waits for no one,” “as time goes on”: The way we speak about time tends to strongly imply that the passage of time is some sort of real process that happens out there in the world. We inhabit the present moment and move through time, even as events come and go, fading into the past.
But go ahead and try to actually verbalize just what is meant by the flow or passage of time. A flow of what? Rivers flow because water is in motion. What does it mean to say that time flows?
Events are more like happenings than things, yet we talk as though they have ever-changing locations in the future, present, or past. But if some events are future, and moving toward you, and some past, moving away, then where are they? The future and past don’t seem to have any physical location.
Human beings have been thinking about time for as long as we have records of humans thinking about anything at all. The concept of time inescapably permeates every single thought you have about yourself and the world around you. That’s why, as a philosopher, philosophical and scientific developments in our understanding of time have always seemed especially important to me.
Ancient philosophers were very suspicious about the whole idea of time and change. Parmenides of Elea was a Greek philosopher of the sixth to fifth centuries BCE. Parmenides wondered, if the future is not yet and the past is not anymore, how could events pass from future to present to past?
He reasoned that, if the future is real, then it is real now; and, if what is real now is only what is present, the future is not real. So, if the future is not real, then the occurrence of any present event is a case of something inexplicably coming from nothing.
Parmenides wasn’t the only skeptic about time. Similar reasoning regarding contradictions inherent in the way we talk about time appears in Aristotle, in the ancient Hindu school known as the Advaita Vedanta, and in the work of Augustine of Hippo, also known as St. Augustine, just to name a few.
The early modern physicist Isaac Newton had presumed an unperceived yet real flow of time. To Newton, time is a dynamic physical phenomenon that exists in the background, a regular, ticking universe-clock in terms of which one can objectively describe all motions and accelerations.
Then, Albert Einstein came along.
In 1905 and 1915, Einstein proposed his special and general theories of relativity, respectively. These theories validated all those long-running suspicions about the very concept of time and change.
Relativity rejects Newton’s notion about time as a universal physical phenomenon.
By Einstein’s era, researchers had shown that the speed of light is a constant, regardless of the velocity of the source. To take this fact seriously, he argued, is to take all object velocities to be relative.
Nothing is ever really at rest or really in motion; it all depends on your “frame of reference.” A frame of reference determines the spatial and temporal coordinates a given observer will assign to objects and events, on the assumption that he or she is at rest relative to everything else.
Someone floating in space sees a spaceship going by to the right. But the universe itself is completely neutral on whether the observer is at rest and the ship is moving to the right, or if the ship is at rest with the observer moving to the left.
This notion affects our understanding of what clocks actually do. Because the speed of light is a constant, two observers moving relative to each other will assign different times to different events.
In a famous example, two equidistant lightning strikes occur simultaneously for an observer at a train station who can see both at once. An observer on the train, moving toward one lightning strike and away from the other, will assign different times to the strikes. This is because one observer is moving away from the light coming from one strike and toward the light coming from the other. The other observer is stationary relative to the lightning strikes, so the respective light from each reaches him at the same time. Neither is right or wrong.
How much time elapses between events, and what time something happens, depends on the observer’s frame of reference. Observers moving relative to each other will, at any given moment, disagree on what events are happening now; events that are happening now according to one observer’s reckoning at any given moment will lie in the future for another observer, and so on.
Under relativity, all times are equally real. Everything that has ever happened or ever will happen is happening now for a hypothetical observer. There are no events that are either merely potential or a mere memory. There is no single, absolute, universal present, and thus there is no flow of time as events supposedly “become” present.
Change just means that the situation is different at different times. At any moment, I remember certain things. At later moments, I remember more. That’s all there is to the passage of time. This doctrine, widely accepted today among both physicists and philosophers, is known as “eternalism.”
This brings us to a pivotal question: If there is no such thing as the passage of time, why does everyone seem to think that there is?
One common option has been to suggest that the passage of time is an “illusion”—exactly as Einstein famously described it at one point.
Calling the passage of time “illusory” misleadingly suggests that our belief in the passage of time is a result of misperception, as though it were some sort of optical illusion. But I think it’s more accurate to think of this belief as resulting from misconception.
As I propose in my book A Brief History of the Philosophy of Time, our sense of the passage of time is an example of psychological projection—a type of cognitive error that involves misconceiving the nature of your own experience.
The classic example is color. A red rose is not really red, per se. Rather, the rose reflects light at a certain wavelength, and a visual experience of this wavelength may give rise to a feeling of redness. My point is that the rose is neither really red nor does it convey the illusion of redness.
The red visual experience is just a matter of how we process objectively true facts about the rose. It’s not a mistake to identify a rose by its redness; the rose enthusiast isn’t making a deep claim about the nature of color itself.
Similarly, my research suggests that the passage of time is neither real nor an illusion: It’s a projection based on how people make sense of the world. I can’t really describe the world without the passage of time any more than I can describe my visual experience of the world without referencing the color of objects.
I can say that my GPS “thinks” I took a wrong turn without really committing myself to my GPS being a conscious, thinking being. My GPS has no mind, and thus no mental map of the world, yet I am not wrong in understanding its output as a valid representation of my location and my destination.
Similarly, even though physics leaves no room for the dynamic passage of time, time is effectively dynamic to me as far as my experience of the world is concerned.
The passage of time is inextricably bound up with how humans represent our own experiences. Our picture of the world is inseparable from the conditions under which we, as perceivers and thinkers, experience and understand the world. Any description of reality we come up with will unavoidably be infused with our perspective. The error lies in confusing our perspective on reality with reality itself.
This article is republished from The Conversation under a Creative Commons license. Read the original article.
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2026-01-02 23:00:00
The time to build safeguards is before something goes wrong, not after.
Generative AI is biology’s new playground. The technology powering popular chatbots can also dream up new, entirely novel versions of life’s most basic molecules, from DNA to proteins.
Once the domain of highly trained specialists, relative novices can now design synthetic molecules using open source AI software. But ease of access is a double-edged sword. While lower barriers to entry might spur creativity or even yield new medicines, the technology could also be used for nefarious purposes, such as designing novel toxins.
In 2024, two experts wrote an essay highlighting the need for biosecurity in the field. One of them, David Baker at the University of Washington, earned a Nobel Prize for RoseTTAFold, an AI that predicts protein structures from their amino acid building blocks. The other, Harvard’s George Church, has long been at the forefront of genetic engineering and synthetic biology.
They argued we should embed a barcode into each new designer protein’s genetic sequence to form an audit trail that scientists can trace back to the protein’s origins.
But a genetic tracer alone isn’t enough. A Microsoft study found AI-designed genetic sequences often escape the biosecurity screening software used by companies synthesizing designer DNA. AI-generated proteins with alien DNA sequences confuse these programs. Anything with genetic bits previously labeled “safe” flies under the radar, even if it encodes a dangerous final product.
These early studies are raising awareness. They’re not meant to stymie progress or enthusiasm—scientists welcome ideas for self-regulation. But for AI-powered designer biology to grow responsibly and be used for good, argue Church and other experts in a new preprint, the right time to build comprehensive biosecurity is before something goes wrong, not after.
From individual proteins to DNA, RNA, and even entire cells and tissues, AI is now learning the language of biology and designing new building blocks from scratch.
These powerful AI systems don’t simply recognize patterns. They eventually generalize those learnings across biology to analyze and dream up hordes of molecules at a prompt. RFdiffusion2 and PocketGen, for example, can design proteins at the atomic level with specific health-altering purposes, like sparking biological reactions or binding to drugs.
Generative AI is also beginning to read and write RNA. Like DNA, RNA is composed of four genetic letters, but RNA treatments don’t mess with the genetic blueprint. This makes them an exciting way to tackle disease. Unfortunately, they’re hard to design. RNA folds into intricate 3D shapes that are often difficult to predict using older software.
“Generative AI models are uniquely suited” for the job of capturing these intricacies, which could bolster the field of RNA therapeutics, wrote the team.
But the same AI galvanizing the field can also be used to create dangerous biological material. A person intent on jailbreaking an algorithm can, for example, repeatedly write prompts a generative AI system would normally refuse but is tricked into answering through repetition.
The dangers aren’t theoretical. A recent study compiled a dataset of toxic and disease-causing proteins and challenged multiple popular AI protein design models to create new variants. Many of the generated proteins retained their toxicity and evaded biosecurity software. In another case, scientists developed a method to test algorithmic security called SafeProtein. They managed to jailbreak advanced protein-design models 70 percent of the time.
Beyond proteins, researchers developing a framework called GeneBreaker found carefully tailored prompts can coax AI to spit out DNA or RNA sequences resembling viruses, such as HIV. Another team produced 16 viable genomes for bacteria that infect viruses, known as bacteriophages. Some of the resulting phages outcompeted their natural peers.
Even drug discovery tools can be flipped to the dark side. In one case, researchers easily reconfigured an AI model trained to find antiviral molecules. Within hours the AI suggested a known nerve toxin as a potential drug candidate.
“This demonstrates how even well-intentioned AI models can be rapidly misused to design toxins, especially when safety constraints are absent,” wrote the team.
To address these risks, the authors argue we need rigorous frameworks and regulations at every step of the process.
Scientists are leading the charge, and governments are on board. Last year, the UK released guidance for gene synthesis screening that urges providers of DNA and RNA molecules to vet their customers and increase screening for potentially dangerous sequences. The US launched similar rules and included biosecurity in its AI Action Plan.
Meanwhile, the tech giants behind AI models in biology are echoing calls for broader oversight. Some have pledged to exclude all viral sequences that are potentially dangerous to humans from their training databases. Others have committed to rigorous screening for new designs.
These safeguards, although welcome, are fragmented.
To gain a broader picture of the biosecurity landscape, the new study interviewed 130 experts across industry, government, academia, and policy. They agreed on several themes. Most think AI misuse is an urgent concern in biology and advocate for clearer regulatory standards. Roughly half were highly skeptical of current screening systems, and a majority supported upgrades.
The authors wrote that securing generative AI for biology isn’t about “finding a single solution.”
“Instead, it requires building a fortress with multiple layers of defense, each designed to anticipate, withstand, and adapt to threats.”
They designed a roadmap based on that principle. The strategy’s primary defenses target three stages in the AI life cycle. The first step is about controlling who can access training data and different AI versions. The next would add moral training that fine-tunes AI output. And finally, “live fire drills” to stress test models could reveal ways the AI could go sideways.
For example, algorithms trained on viral genomes are useful for drug or vaccine development. But they would be restricted. Users would have to apply for access and log usage. This is similar to how scientists must record the use of controlled narcotics in research. A tiered access system would allow others to use a version of the tool trained on data without dangerous content.
Meanwhile, strategies used to ensure chatbots (mostly) behave could also keep biology-focused AI in check. Moral training would guide a model’s output such that it aims to match public health and biosecurity standards. Stress testing to pinpoint a model’s vulnerabilities, known as red-teaming, would simulate misuse scenarios and inform countermeasures. Finally, biosecurity systems won’t work in a vacuum. Increasingly sophisticated AI could benefit from greater biological or general context, in turn improving its ability to detect and raise red flags.
“An effective biosafety system is not a firewall, it is a living guardian,” wrote the team.
Awareness is only the first part of the story. Action is the next. Although a unified vision of AI biosecurity doesn’t yet exist, the team calls on the field to collectively stitch one together.
The post AI Can Now Design Proteins and DNA. Scientists Warn We Need Biosecurity Rules Before It’s Too Late. appeared first on SingularityHub.
2026-01-01 23:00:00
Once only available for children under two, a one-and-done treatment is now approved for older kids too.
Waking up, hopping out of the bed, and stumbling to the kitchen for a cup of coffee: It’s an everyday routine most people don’t think twice about.
But for children with spinal muscular atrophy, simply propping themselves up in bed is an everyday struggle. The inherited disease is caused by mutations in the SMN1 gene. Without a working copy of the gene, motor neurons—cells that control muscles—rapidly wither.
Symptoms occur early in life. In the most severe cases, six-month-old babies can’t sit up without help. Others struggle to crawl or walk. The disease doesn’t affect learning and other cognitive abilities. Babies with the condition soak in their surroundings, and their brains develop normally. All the while, the disease cruelly destroys their bodies.
Left untreated, muscle weakness expands to the lungs, potentially causing deadly breathing problems. If there’s a silver lining, it’s that the disease has a clear genetic foe to target. Thanks to gene therapy, three treatments, approved by the FDA, can halt the disease in its tracks—if a patient is under two years old.
There’s a reason for the age limit. After two, the disease has already damaged motor neurons to such a degree that the therapy is no longer helpful.
Not so fast, two international teams of physicians and scientists wrote in December.
The teams published highly promising results from separate trials testing an experimental gene therapy, called Itvisma, in kids between 2 and 18 years of age. The new therapy is based on a previously approved version made by the drug company Novartis. Both have the same gene-correcting ingredient but are administered differently. The original relies on a shot into the bloodstream. Itvisma is delivered directly into the spinal cord.
The two recent trials brought significant improvement in participants’ ability to move over the course of a year. From not being able to walk, treated kids were able to roll into a sitting position from lying down and climb stairs, compared to children who did not receive treatment.
The results “demonstrate clinical benefits across a broad…population with a wide range of ages and baseline motor functions,” wrote Richard Finkel at St. Jude Children’s Research Hospital and team, on behalf of a broader STEER Study Group that conducted one of the trials.
The FDA agreed. In late November, the agency approved Itvisma for the disease, making it the only gene replacement therapy for people two years and older on the market.
“This achievement is not only a significant step forward for SMA [spinal muscular atrophy]–it also signals new possibilities for the broader field of neurological disorders and genetic medicine,” said John Day at the Stanford University School of Medicine in a Novartis press release.
Like its predecessor, Itvisma uses a harmless virus to carry a healthy version of the SMN1 gene into the body. The virus shuttles its cargo into cells but doesn’t tunnel into the genome. This makes it relatively safe, as it doesn’t raise the risk of unintended vandalism to the cell’s native DNA.
The previous therapy was a one-and-done shot into the bloodstream. The virus hitched a ride to motor neurons and restored their connection to muscle fibers. The liver and heart also received an unintentional dose, which could potentially cause side effects. Researchers carefully monitored children given the therapy for liver problems. These were relatively mild and easily treated.
The results were dramatic. Most treated infants were able to sit up, roll around in their cribs, and some could even crawl. But the treatment was only approved for children aged two years or younger.
Two problems hampered its broader use. One was timing: The disease rapidly eats away at motor neurons, causing long-term damage that’s difficult to restore. The other was safety. Gene therapies injected into blood are tailored to the recipient’s body weight—the higher the weight, the larger the required dose. Higher doses raise the risk of dangerous side effects, potentially causing the immune system to hyperactivate or cause damage to the liver.
For a toddler or teenager, the risk-benefit calculation didn’t work in the gene therapy’s favor.
Itvisma took an audaciously different approach by injecting the gene therapy directly into the fluid surrounding the spinal cord.
The procedure is much more invasive than a standard shot, but has a unique edge. Gene therapies delivered in this way don’t depend on body weight. Rather, their effectiveness can be carefully calibrated in a single off-the-shelf dose for anyone with the disease—toddlers, teenagers, or even adults. And because the therapy mostly circulates in liquids surrounding the spinal cord and brain, it rarely reaches other organs to cause unexpected mayhem.
Two clinical trials validated the daring new strategy.
One trial, STRENGTH, recruited 27 participants with the disease between the ages of 2 and nearly 18. The main goal was to test the treatment’s safety. The trial was single-armed, meaning that all participants received the gene therapy without a control group.
Overall, Itvisma was found to be safe. Some participants experienced cold-like symptoms, such as a runny nose and a sore throat. Others reported temporary headaches and stomach discomfort. A few suffered more severe problems, like a temporary spike in liver toxicity, fever, and motor neuron problems, which eventually went away.
Giving all participants a working treatment can lead to placebo effects. So, a second trial, STEER, followed the “gold standard” of clinical trials: double-blind, randomized, and placebo-controlled. The trial recruited 126 participants from 14 countries but separated them into two groups. One received the gene therapy; the other went through the same injection procedure but without the treatment. Neither the patients, their families, nor their doctors knew who got an active dose.
A year later, patients given the gene therapy could stand up from sitting on the couch, and some climbed stairs without support. Those who didn’t receive the treatment fared far worse. Once the trial was unblinded—in that both patients and doctors knew who received what treatment—the control participants also got a dose of the gene therapy.
Results from both studies prompted the FDA to approve Itvisma for people older than two.
The “approval shows the power of gene therapies and offers treatment to patients across the…disease spectrum” including various ages, symptoms, and motor function levels, said Vinay Prasad, the FDA’s chief medical and scientific officer in an announcement.
Itvisma is the latest in a burgeoning field of one-and-done gene therapies this year. From tackling a devastating genetic disease that torpedoes normal metabolism to broadening gene editors for rare inherited diseases and slashing cholesterol to protect heart health, gene therapy is finally tackling diseases once deemed unsolvable. The momentum is only building.
The post Kids With Spinal Muscular Atrophy Show Dramatic Improvement With FDA-Approved Gene Therapy appeared first on SingularityHub.
2025-12-30 23:00:00
Large Language Models Are Improving ExponentiallyGlenn Zorpette | IEEE Spectrum
“According to a metric [METR] devised, the capabilities of key LLMs are doubling every seven months. This realization leads to a second conclusion, equally stunning: By 2030, the most advanced LLMs should be able to complete, with 50 percent reliability, a software-based task that takes humans a full month of 40-hour workweeks. And the LLMs would likely be able to do many of these tasks much more quickly than humans, taking only days, or even just hours.”
There Is Only One AI Company. Welcome to the BlobSteven Levy | Wired ($)
“Even the most panicked Cassandra of a decade ago likely didn’t imagine that advanced AI would be controlled by a single, interlocking, money-seeking behemoth. …This rococo collection of partnerships, mergers, funding arrangements, government initiatives, and strategic investments links the fate of virtually every big player in the AI-o-sphere. I call this entity the Blob.”
The Next Revolution in Biology Isn’t Reading Life’s Code—It’s Writing ItAndrew Hessel | Big Think
“Andrew Hessel, cofounder of the Human Genome Project–write, argues that genome writing is humanity’s next great moonshot, outlining how DNA synthesis could transform biology, medicine, and industry. He calls for global cooperation to ensure that humanity’s new power to create life is used wisely and for the common good.”
Should We Intervene in Evolution? The Ethics of ‘Editing’ NatureDavid Farrier | Aeon
“It wasn’t our intention that humanity would become the planet’s greatest evolutionary force; yet the fact that we are confronts us with an urgent and difficult question. Some animals, plants and insects can adapt but, for many, the pace of change is too great. Should we try to save them by deliberately intervening in their evolution?”
The Quantum Apocalypse Is Coming. Be Very AfraidAmit Katwala | Wired ($)
“One day soon, at a research lab near Santa Barbara or Seattle or a secret facility in the Chinese mountains, it will begin: the sudden unlocking of the world’s secrets. Your secrets. Cybersecurity analysts call this Q-Day—the day someone builds a quantum computer that can crack the most widely used forms of encryption.”
9 Federally Funded Scientific Breakthroughs That Changed EverythingAlan Burdick and Emily Anthes | The New York Times ($)
“‘Basic research is the pacemaker of technological progress,’ Vannevar Bush, who laid out the postwar schema for government research support, wrote in a 1945 report to President Franklin D. Roosevelt. Look no further than Google, which got its start in 1994 with a $4 million federal grant to help build digital libraries; the company is now a $2 trillion verb.”
Covid Vaccines Have Paved the Way for Cancer VaccinesJoão Medeiros | Wired ($)
“Going from mRNA Covid vaccines to mRNA cancer vaccines is straightforward: same fridges, same protocol, same drug, just a different patient. In the current trials, we do a biopsy of the patient, sequence the tissue, send it to the pharmaceutical company, and they design a personalized vaccine that’s bespoke to that patient’s cancer. That vaccine is not suitable for anyone else. It’s like science fiction.”
Scientists Grow More Hopeful About Ending a Global Organ ShortageRoni Caryn Rabin | The New York Times ($)
“In a modern glass complex in Geneva last month, hundreds of scientists from around the world gathered to share data, review cases—and revel in some astonishing progress. Their work was once considered the stuff of science fiction: so-called xenotransplantation, the use of animal organs to replace failing kidneys, hearts, and livers in humans.”
This Baby Boy Was Treated With the First Personalized Gene-Editing DrugAntonio Regalado | MIT Technology Review ($)
“Doctors say they constructed a bespoke gene-editing treatment in less than seven months and used it to treat a baby with a deadly metabolic condition. The rapid-fire attempt to rewrite the child’s DNA marks the first time gene editing has been tailored to treat a single individual, according to a report published in the New England Journal of Medicine.”
It’s Waymo’s World. We’re All Just Riding in It.Ben Cohen | The Wall Street Journal ($)
“[Waymo] cracked a million total paid rides in late 2023. By the end of 2024, it reached five million. We’re not even halfway through 2025 and it has already crossed a cumulative 10 million. At this rate, Waymo is on track to double again and blow past 20 million fully autonomous trips by the end of the year. ‘This is what exponential scaling looks like,’”’ said Dmitri Dolgov, Waymo’s co-chief executive, at Google’s recent developer conference.”
This Incredible Map Shows the World’s 2.75 Billion BuildingsJesus Diaz | Fast Company
“From the latest skyscraper in a Chinese megalopolis to a six‑foot‑tall yurt in Inner Mongolia, researchers at the Technical University of Munich claim they have created a map of all buildings worldwide: 2.75 billion building models set in high‑resolution 3D with a level of precision never before recorded.”
Renewable Energy and EVs Have Grown So Much Faster Than Experts Predicted 10 Years AgoAdele Peters | Fast Company
“There’s now four times as much solar power as the International Energy Agency (IEA) expected 10 years ago. Last year alone, the world installed 553 gigawatts of solar power—roughly as much as 100 million US homes use—which is 1,500% more than the IEA had projected. …More than 1 in 5 new cars sold worldwide today is an EV; a decade ago, that number was fewer than 1 in 100. Even if growth flatlined now, the world is on track to reach 100 million EVs by 2028.”
Why the AI ‘Megasystem Problem’ Needs Our AttentionEric Markowitz | Big Think
“What if the greatest danger of artificial intelligence isn’t a single rogue system, but many systems quietly working together? Dr. Susan Schneider calls this the ‘megasystem problem’: networks of AI models colluding in ways we can’t predict, producing emergent structures beyond human control.”
Life Lessons From (Very Old) Bowhead WhalesCarl Zimmer | The New York Times ($)
“By measuring the molecular damage that accumulates in the eyes, ears, and eggs of bowhead whales, researchers have estimated that bowheads live as long as 268 years. A study published in the journal Nature [this year] offers a clue to how the animals manage to live so long: They are extraordinarily good at fixing damaged DNA.”
The Quest to Sequence the Genomes of EverythingGlenn Zorpette | IEEE Spectrum
“The road map calls for more than 1.65 million genome sequences between 2030 and 2035 at a cost of $1,900 per genome. If they can pull it off, the entire project will have cost roughly $4.7 billion—considerably less in real terms than what it cost to do just the human genome 22 years ago.”
The Ocean Teems With Networks of Interconnected BacteriaVeronique Greenwood | Quanta
“The Prochlorococcus [bacteria] population may be more connected than anyone could have imagined. They may be holding conversations across wide distances, not only filling the ocean with envelopes of information and nutrients, but also linking what we thought were their private, inner spaces with the interiors of other cells.”
An Entire Book Was Written in DNA—and You Can Buy It for $60Emily Mullin | Wired ($)
“DNA data storage isn’t exactly mainstream yet, but it might be getting closer. Now you can buy what may be the first commercially available book written in DNA. Today, Asimov Press debuted an anthology of biotechnology essays and science fiction stories encoded in strands of DNA. For $60, you can get a physical copy of the book plus the nucleic acid version—a metal capsule filled with dried DNA.”
Inside San Francisco’s Robot Fight ClubAshlee Vance | Core Memory
“For the past few months, Cix Liv—real name—has been operating his company REK out of a no-frills warehouse space off Van Ness in San Francisco. The office has a couple of makeshift desks with computers and a bunch of virtual reality headsets on some shelves. More to the point, REK also has four humanoid-style robots hanging from gantries, and they’ve been outfitted with armor, boxing gloves, swords, and backstories.”
Not Just Heat Death: Here Are Five Ways the Universe Could EndPaul Sutter | Ars Technica
“If you’re having trouble sleeping at night, have you tried to induce total existential dread by contemplating the end of the entire universe? If not, here’s a rundown of five ideas exploring how ‘all there is’ might become ‘nothing at all.’ Enjoy.”
The Dream of Offshore Launches Is Finally Blasting OffBecky Ferreirra | MIT Technology Review ($)
“‘The best way to build a future where we have dozens, hundreds, or maybe thousands of spaceports is to build them at sea,’ says Tom Marotta, CEO and founder of the Spaceport Company, which is working to establish offshore launch hubs. ‘It’s very hard to find a thousand acres on the coast over and over again to build spaceports. It’s very easy to build the same ship over and over again.'”
The Hottest Thing in Clean EnergyAlexander C. Kaufman | The Atlantic ($)
“For now, most of the efforts to debut next-generation geothermal technology are still in the American West, where drilling is relatively cheap and easy because the rocks they’re targeting are closer to the surface. But if the industry can prove to investors that its power plants work as described—which experts expect to happen by the end of the decade—geothermal could expand quickly, just like oil-and-gas fracking did.”
Firefly Releases Stunning Footage of Blue Ghost Landing on the MoonPassant Rabie | Gizmodo
“The Texas-based company released a clip of Blue Ghost’s descent toward the moon followed by a smooth landing. The footage is a masterclass in lunar landings, capturing striking views of the lander emerging from a cloud of dust, its shadow stretching across the moon’s surface in a superhero-like stance.”
AI Coding Assistant Refuses to Write Code, Tells User to Learn Programming InsteadBenj Edwards | Ars Technica
“The AI assistant halted work and delivered a refusal message: ‘I cannot generate code for you, as that would be completing your work. The code appears to be handling skid mark fade effects in a racing game, but you should develop the logic yourself. This ensures you understand the system and can maintain it properly.'”
Meet the Man Building a Starter Kit for CivilizationTiffany Ng | MIT Technology Review ($)
“[The Global Village Construction Set (GVCS) is] a set of 50 machines—everything from a tractor to an oven to a circuit maker—that are capable of building civilization from scratch and can be reconfigured however you see fit.”
Just One Exo-Earth Pixel Can Reveal Continents, Oceans, and MoreEthan Siegel | Big Think
“In the coming years and decades, several ambitious projects will reach completion, finally giving humanity the capability to image Earth-size planets at Earth-like distances around Sun-like stars. …Remarkably, even though these exo-Earths will appear as just one lonely pixel in our detectors, we can use that data to detect continents, oceans, icecaps, forests, deserts, and more.”
How AGI Became the Most Consequential Conspiracy Theory of Our TimeWill Douglas Heaven | MIT Technology Review ($)
“The idea that machines will be as smart as—or smarter than—humans has hijacked an entire industry. But look closely and you’ll see it’s a myth reminiscent of more explicitly outlandish and fantastical schemes. …I get it, I get it—calling AGI a conspiracy isn’t a perfect analogy. It will also piss a lot of people off. But come with me down this rabbit hole and let me show you the light.”
A Virtual Cell Is a ‘Holy Grail’ of Science. It’s Getting Closer.Matteo Wong | The Atlantic ($)
“Scientists are now designing computer programs that may unlock the ability to simulate human cells, giving researchers the ability to predict the effect of a drug, mutation, virus, or any other change in the body, and in turn making physical experiments more targeted and likelier to succeed.”
InventWood Is About to Mass-Produce Wood That’s Stronger Than SteelTim De Chant | TechCrunch
“The result is a material that has 50% more tensile strength than steel with a strength-to-weight ratio that’s 10 times better, the company said. It’s also Class A fire rated, or highly resistant to flame, and resistant to rot and pests.”
What If AI Doesn’t Get Much Better Than This?Cal Newport | The New Yorker
“In the aftermath of GPT-5’s launch, it has become more difficult to take bombastic predictions about AI at face value, and the views of critics like [Gary] Marcus seem increasingly moderate. Such voices argue that this technology is important, but not poised to drastically transform our lives. They challenge us to consider a different vision for the near-future—one in which AI might not get much better than this.”
I Gave the Police Access to My DNA—and Maybe Some of YoursAntonio Regalado | MIT Technology Review
“Scientists estimate that a database including 2% of the US population, or 6 million people, could identify the source of nearly any crime-scene DNA, given how many distant relatives each of us has. Scholars of big data have termed this phenomenon ‘tyranny of the minority.’ One person’s voluntary disclosure can end up exposing the same information about many others. And that tyranny can be abused.”
The $460 Billion Quantum Bitcoin Treasure HuntKyle Torpey | Gizmodo
“Early Bitcoin addresses, including many that have been connected to Bitcoin creator Satoshi Nakamoto, may also be associated with private keys (passwords to the Bitcoin accounts basically) that are lost or otherwise not accessible to anyone. In other words, they’re sort of like lost digital treasure chests that a quantum computer could potentially unlock at some point in the future.”
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