2026-04-28 22:00:00
AI long ago surpassed humans at games like chess and Go. Now it’s powering robots that can challenge top athletes.
Peter Dürr could barely follow the table-tennis ball as it zoomed across the net, each strike’s trajectory designed to perplex the opponent. This was no ordinary match: Taira Mayuka, one of the top players in the world, was on one side—on the other, was a robot called Ace.
Mayuka launched a twisting smash that should have nailed a point. But in the blink of an eye, Ace answered with a return that kept the game alive. “Yes!” Dürr pumped his fist, knowing his team had engineered a historic moment for robotics.
Sony AI’s Ace is the latest autonomous system to be pitted against humans in a game. Since Deep Blue defeated chess champion Garry Kasparov in 1997, AI has trounced humans in Jeopardy, Go, StarCraft II, and car-racing simulations.
Ace has now taken these virtual victories into the real world.
Up against seven top human players, the AI-controlled robot arm beat three in multiple adrenaline-pumping games. Ace is an “important milestone,” wrote Carlos H. C. Ribeiro and Esther Colombini at the Aeronautics Institute of Technology and University of Campinas, respectively, who were not involved in the study.
Ace joins a humanoid robot that crushed the world record for a half marathon in Beijing last week. Neither project is focused on creating elite robotic athletes. Their main goal is to build next-generation autonomous machines that operate fluidly in the physical world.
“We wanted to prove that AI doesn’t just exist in virtual spaces,” Michael Spranger, president of Sony AI, said in a press release. “It’s not just tech you interact with in the virtual world—you can actually have a physical experience, and the technology is ready for that.”
Robots have come a long way. The clumsy, bumbling humanoids are gone, replaced by agile machines that can navigate all kinds of terrain. Autonomous vehicles once baffled by our roads now cruise the streets. Dexterous robotic arms are increasingly used for surgery, warehouse operations, or even delivering your lunch.
AI is a big part of that leap in capability. Robots are no longer strictly preprogrammed machines. They can now learn, adapt, make decisions, with generative AI models helping them understand what they’re looking at and, increasingly, how to interact with it. They’re a little less like yesterday’s rigid machines, and more like curious kids: Taking in a messy world, figuring it out, and getting better over time.
But compared to humans, robots still struggle to react on the fly, especially in fast-paced games like table tennis. The sport is a brutal mix of speed, perception, and precision. Players must read the ball and strike in a split second. There’s no margin for error. Too much power or the wrong angle, and the ball flies off the table. Too predictable, and you’ve likely handed your opponent the next point.
Professional players can smash shots up to 67 miles per hour and impart “a massive amount of spin on the ball,” exceeding 160 rotations a second, Dürr told Nature, making it tough for rookie humans and robots to react in time.
To Dürr, building a robot that could compete with elite human players was a “dream project” that “would challenge us to push the individual component technologies to their limits.”
Ace seamlessly fuses AI-based software and hardware.
For its eyes, the team placed cameras outside the court that could cover the entire playing area and track the ball’s position about 200 times per second. They also used an event-based image sensor to capture the ball’s spin. Together, these give the “robot the information it needs to anticipate where the ball is going to go, and plan how to hit it back,” said Dürr.
All that data feeds into multiple AI algorithms: Ace’s “brain.” One of these algorithms, borrowed from image processing, focuses on key parts of each frame to increase processing speed. Another, a deep reinforcement algorithm, learned to play table tennis in simulated matches. (Think student and coach: The model decides how to swing, where to aim, and how hard to hit. The “coach” gives feedback—good or bad—without demonstrating any moves.)
“So basically, we shoot a ball in simulation at our robot and let it do random things. At the beginning, it doesn’t know how to react…But eventually, it maybe be lucky enough to hit the ball back on the table,” said Dürr. And over countless iterations, it improves its play.
Expert players coached Ace too. In table tennis, the initial toss sets up the serve. Ace learned from human demonstrations adapted to its mechanics, so every toss follows the game’s rules.
After thousands of simulated hours, and with the help of yet another algorithm to weed out poor plays, the team built a library of realistic serves for Ace to draw upon.
The last component was the arm itself—and off-the-shelf didn’t work. “There’s nothing on the market that would let us play at the level we wanted to play,” said Dürr. So they built their own robot from the ground up. The lightweight, six-jointed arm can whip a racket at over 20 meters (roughly 66 feet) per second and react roughly 11 times faster than a person.
All assembled, Ace is a table-tennis powerhouse—but not unbeatable. Against five elite and two professional players, it dominated the less-experienced elites but fell to the pros. In the months since the team wrote up their results, the robot continued improving against top-tier competition.
Ace didn’t win by simply being faster than humans. Rather, it won by being inventive. It created different kinds of spins, varied its returns, and consistently landed the ball on target. When Olympic table-tennis player, Kinjiro Nakamura, watched Ace play, he was mesmerized by the robot’s unconventional moves. “No one else would have been able to do that. I didn’t think it was possible,” he said. But if a robot can pull it off, maybe humans can too.
For Colombini, who worked on soccer-playing robots, that kind of agility and improvisation is the real goal. Robots need to think on their feet and easily navigate the physical world to work safely with people. “I need the skills and the abilities of these robots, learned in these environments that are easy for us to see how they are evolving,” she said. “So, sports are just a proxy for what we want.”
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2026-04-28 01:14:10
Algorithmic advances are steadily lowering the bar for quantum attacks—even before large-scale hardware exists.
Online data is generally pretty secure. Assuming everyone is careful with passwords and other protections, you can think of it as being locked in a vault so strong that even all the world’s supercomputers, working together for 10,000 years, could not crack it.
But last month, Google and others released results suggesting a new kind of computer—a quantum computer—might be able to open the vault with significantly fewer resources than previously thought.
The changes are coming on two fronts. On one, tech giants such as IBM and Google are racing to build ever-larger quantum computers: IBM hopes to achieve a genuine advantage over classical computers in some special cases this year, and an even more powerful “fault-tolerant” system by 2029.
On the other front, theorists are refining quantum algorithms: Recent work shows the resources needed to break today’s cryptography may be far fewer than earlier estimates.
The net result? The day quantum computers can break widely used cryptography—portentously dubbed “Q-Day”—may be approaching faster than expected.
Quantum computers are built from quantum bits, or qubits, which use the counterintuitive properties of very tiny objects to carry out computations in a different and sometimes far more efficient way from traditional computers.
So far the technology is in its infancy, with the major goal to increase the number of qubits that can be connected to work as a single computer. Bigger quantum computers should be much better at some things than their traditional counterparts—they will have a “quantum advantage.”
Late last year, IBM unveiled a 120-qubit chip which it hopes will demonstrate a quantum advantage for some tasks.
Google also recently announced it planned to speed up its move to adopt encryption techniques that should be safe against quantum computers, known as post-quantum cryptography.
Alongside these tech giants, newer approaches are also flourishing. PsiQuantum is using light-based qubits and traditional chip-manufacturing technology. Experimental platforms such as neutral-atom systems have demonstrated control over thousands of qubits in laboratory settings.
In response, standards bodies and national agencies are setting increasingly concrete timelines for moving away from common encryption systems that are vulnerable to quantum attack.
In the United States, the National Institute of Standards and Technology (NIST) has proposed a transition away from quantum-vulnerable cryptography, with migration largely completed by 2035. In Australia, the Australian Signals Directorate has issued similar guidance, urging organizations to begin planning immediately and transition to post-quantum cryptography by 2030.
Hardware is only half the story. Equally important are advances in quantum algorithms—ways to use quantum computers to attack encryption.
Much interest in quantum computer development was spurred by Peter Shor’s 1994 discovery of an algorithm that showed how quantum computers could efficiently find the prime factors of very large numbers. This mathematical trick is precisely what you need to break the common RSA encryption method.
For decades, it was believed a quantum computer would need millions of physical qubits to pose a threat to real-world encryption. This is far bigger than current systems, so the threat felt comfortably distant.
That picture is now changing.
In March 2026, Google’s Quantum AI team released a detailed study showing that far fewer resources may be needed to attack a different kind of encryption which uses mathematical objects called elliptic curves. This is what systems including Bitcoin and Ethereum use—and the study shows how a quantum computer with fewer than half a million physical qubits may be able to crack it in minutes.
That’s still a long way beyond current quantum computers, but around ten times less than earlier estimates.
At the same time, a March 2026 preprint from a Caltech—Berkeley—Oratomic collaboration explores what might be possible using neutral-atom quantum computers. The researchers estimate that Shor’s algorithm could be implemented with as few as 10,000–20,000 atomic qubits. In one design they propose, a system with around 26,000 qubits could crack Bitcoin’s encryption in a few days, while tougher problems like the RSA method with a 2048-bit key would need more time and resources.
In plain terms: The codebreakers are becoming more efficient. Advances in algorithms and design are steadily lowering the bar for quantum attacks, even before large-scale hardware exists.
So what does this mean in practice?
First, there is no immediate catastrophe—today’s cryptography won’t be broken overnight. But the direction of travel is clear. Each improvement in hardware or algorithms reduces the gap between current capabilities and useful quantum cracking machines.
Second, viable defenses already exist. NIST has standardized several post-quantum cryptographic algorithms which are believed to be resistant to quantum attacks.
Technology companies have begun deploying these in hybrid modes: Google Chrome and Cloudflare, for example, already support post-quantum protections in some protocols and services.
Systems that rely heavily on elliptic-curve cryptography—including cryptocurrencies and many secure communication protocols—will need particular attention. Google’s recent work explicitly highlights the need to migrate blockchain systems to post-quantum schemes.
Finally, this is a two-front race. It is not enough to track progress in quantum hardware alone. Advances in algorithms and error correction can be just as important, and recent results show these improvements can significantly reduce the estimated cost of attacks.
Every new headline about reduced qubit counts or faster quantum algorithms should be understood for what it is: another step toward a future where today’s cryptographic assumptions no longer hold.
The only reliable defense is to move—deliberately but decisively—toward quantum-safe cryptography. 
This article is republished from The Conversation under a Creative Commons license. Read the original article.
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2026-04-26 01:02:39
The People Do Not Yearn for AutomationNilay Patel | The Verge
“Not everything about our lives can be measured and automated and optimized, and it shouldn’t be. And so the tech industry is rushing forward to put AI everywhere at enormous cost—energy, emissions, manufacturing capacity, the ability to buy RAM—and locked into the narrow framework of software brain without realizing they are also asking people to be fundamentally less human.”
AI-Designed Drugs by a DeepMind Spinoff Are Headed to Human Trials
Emily Mullin | Wired ($)
“In a technical paper [released earlier this year], the company touts that the [new IsoDDE] platform more than doubles the accuracy of AlphaFold 3. The startup has formed partnerships with Eli Lilly and Novartis to work together on AI drug discovery and is also advancing its own ‘broad and exciting pipeline of new medicines’ in oncology and immunology, Jaderberg said.”
We Might Finally Know How to Use Quantum Computers to Boost AIKarmela Padavic-Callaghan | New Scientist ($)
“They showed not only that this approach can work but that it would allow the quantum computer to process more data at a smaller memory cost than any conventional computer. The memory advantage is so large, in fact, that a quantum computer made from about 300 error-proof building blocks called logical qubits would outperform a classical computer built using every atom in the observable universe, says Zhao.”
New Gas-Powered Data Centers Could Emit More Greenhouse Gases Than Entire NationsMolly Taft | Wired ($)
“A Wired review of permits for data center projects using natural gas and linked to OpenAI, Meta, Microsoft, and xAI shows they could emit more than 129 million tons of greenhouse gases per year. …As tech companies race to secure massive power deals to build out hundreds of data centers across the country, these projects represent just the tip of the iceberg when it comes to the potential climate cost of the AI boom.”
Anthropic Has Surged to a Trillion-Dollar Valuation on Secondary Markets, Overtaking OpenAIBen Bergman | Business Insider
“Desperate buyers are in a race to secure a dwindling supply of secondary shares in Anthropic, driving the AI company’s valuation on some sites to $1 trillion, a price that would have seemed unthinkable even a few weeks ago. Meanwhile, traders Business Insider spoke with are seeing slumping demand for OpenAI, which is now trading at a discount to Anthropic, despite OpenAI being valued at $852 billion, more than twice Anthropic’s valuation in their most recent funding rounds.”
You’re About to Feel the AI Money SqueezeHayden Field | The Verge
“Ads, rate limits, feature restrictions, price hikes. The AI free ride is over. …To reach that bare minimum of 7 percent [return on invested capital], Gartner forecasts that large AI companies would need to earn cumulatively close to $7 trillion in AI-driven revenue through 2029, which is close to $2 trillion per year by the end of the period.”
BMW Is One Step Closer to Selling You a Color-Changing CarAndrew Liszewski | The Verge
“The new BMW iX3 Flow Edition is potentially the most exciting of all of BMW’s concepts as it embeds the E Ink Prism technology directly into the structure of the vehicle’s hood panel, instead of just slapping it on top. The new approach has ‘undergone BMW’s stringent quality testing’ so that it meets the ‘requirements of automotive engineering and everyday use,’ according to a release from E Ink.”
The FDA Gives the Green Light to the First Gene Therapy for DeafnessRob Stein | NPR
“‘That was like the most surreal moment a mother can feel when your son first hears your voice,’ [said Sierra Smith]. The treatment [Smith’s son] received was the one just approved by the FDA. …The FDA’s decision was based on the results from the treatment of 20 patients born with a defective version of a gene known as OTOF, which is necessary to transmit sound from the ears to the brain.”
Will Fusion Power Get Cheap? Don’t Count On It.Casey Crownhart | MIT Technology Review ($)
“Technologies tend to get less expensive over time. Lithium-ion batteries are now about 90% cheaper than they were in 2013. But historically, different technologies tend to go through this curve at different rates. And the cost of fusion might not sink as quickly as the prices of batteries or solar.”
A Startup Says It Grew Human Sperm in a Lab—and Used It to Make EmbryosEmily Mullin | Wired ($)
“The process involves isolating sperm-making stem cells from testicular tissue and coaxing the cells into becoming fully-fledged sperm in a dish. Scientists have been attempting to produce sperm outside the body, known as in vitro spermatogenesis, for almost a century. A Japanese team was the first to produce viable mouse sperm in the lab in 2011, but making human sperm has turned out to be a more difficult task.”
Are OpenAI and Anthropic Moving Away From Reasoning Tech?Stephanie Palazzolo | The Information ($)
“Early signs point to both Spud and Mythos being more intelligent pretrained models, meaning they got smart during the initial part of the development process. Now, OpenAI’s upcoming Spud model is noticeably better at answering tough questions without relying on reasoning, said two people familiar with it.”
Only Antimatter Provides the Energy We Need for Interstellar TravelEthan Siegel | Big Think
“If our goal is to eventually extend our reach not just to the other worlds of our Solar System, but to exoplanets around other stars, we’ll need a different, more efficient method of propulsion than chemical-based rockets can supply. The most efficient form of energy generation, theoretically, is to reach 100%, and only one fuel is capable of doing that: matter-antimatter annihilation. Here’s why that’s the ultimate dream, and how we might conceivably get there.”
If a Bird Flu Pandemic Starts, We May Have an MRNA Vaccine ReadyMichael Le Page | New Scientist ($)
“It was roughly a year after the earliest cases of covid-19 before the first vaccines against the SARS-CoV-2 virus were ready for roll-out. By then millions had died worldwide and economies were devastated. In the advent of a bird flu pandemic, we will be able to react more rapidly, because we should have an mRNA vaccine already approved and ready to go. A phase III trial of a such a vaccine is now getting under way in the UK and the US.”
The post This Week’s Awesome Tech Stories From Around the Web (Through April 25) appeared first on SingularityHub.
2026-04-25 06:34:04
A year after most robots failed to finish the Beijing race, nearly half the field autonomously ran a course of slopes, narrow passages, and 20 turns.
Humanoid robots are Silicon Valley’s latest obsession, but real-world performance has lagged the hype. That may be starting to change, however, after a robot beat the human record for a half marathon by nearly seven minutes in Beijing.
While tech companies around the world are piling into humanoid robots, China has made it a national priority. The government is pouring subsidies and infrastructure investment into the sector, and Chinese firms already account for around 80 percent of the humanoid machines shipped globally, according to the South China Morning Post.
Eager to show off its prowess, China has been staging sporting events for robots, most notably last year’s inaugural World Humanoid Robot Games. Another such event, the Beijing E-Town Half Marathon, pits humanoid robots against thousands of human runners over a 13-mile course. Last year, most of the non-human competitors failed to finish, and the fastest robots managed an unimpressive two hours and 40 minutes.
But this time around, four robots clocked times under an hour. And the winner, made by Chinese smartphone company Honor, registered a record-breaking 50 minutes, 26 seconds, eclipsing the benchmark set by Ugandan long-distance runner Jacob Kiplimo in Lisbon last month.
“Running faster may not seem meaningful at first, but it enables technology transfer, for example, into structural reliability and cooling, and eventually industrial applications,” Du Xiaodi, an engineer on the winning team, told Reuters.
More than 100 teams fielded 300 robots at this year’s event, up from just 21 entries at the inaugural event last year. But Honor, a spinoff from Chinese telecom giant Huawei, dominated the competition, with separate teams from the company taking all three podium spots.
The winning robot, Lightning, navigated the course entirely autonomously. The bot stands 5 feet 6 inches tall but features legs 37 inches long to mimic the physical attributes of elite runners. It also boasts liquid cooling technology used in the company’s smartphones.
The growing sophistication of the robots’ control software is perhaps one of the starkest shifts since last year, with roughly 40 percent of teams operating autonomously. This is particularly impressive given the challenging course, according to Bernstein Research analysts.
“The course included flat sections, slopes, narrow passages, and ~ 20 turns, demonstrating rapid improvement in robots’ intelligence to handle generalized environments in the real world,” they wrote, according to Bloomberg.
But the technology isn’t bulletproof yet. One robot ran into a barricade and had to be carried off on a stretcher. Another veered into a bush after crossing the finish line. And one continued racing with its torso held together by packing tape after a heavy fall.
Nonetheless, the race showcased the rapid progress China’s tech industry is making, particularly in the raw components used to build these machines, like motors, joints, and batteries. Liu Xiangquan, a robotics professor at Beijing Information Science and Technology University told The South China Morning Post that long-distance running is a great test of how well these components can stand up to the kind of repeated strain that will occur in industrial settings.
And that’s likely to cause some consternation in US policy circles, where many see robotics as a key battlefront in the growing technological rivalry between the two superpowers.
Behind Sunday’s spectacle is a higher-stakes contest between China and the US over who will dominate the next generation of humanoids. US robotics firms have been lobbying Washington to draft a national strategy to counter China, which could include tariffs or bans on Chinese robots to help protect domestic producers.
However, running fast in a straight line is a very different challenge than the fine motor control and perception demanded by commercial applications. Experts told Reuters that despite impressive hardware, robotics companies are still a long way from developing the sophisticated software required to put these humanoids to practical use.
Still, these machines struggled to get over the starting line just a year ago. The gap between humanoid robots and human athletes has closed faster than anyone expected, so betting against further rapid progress seems unwise.
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2026-04-24 06:21:28
That’s a few minutes longer than it takes to fill up the average gas-powered car—but still fast enough it might not matter.
For all their promise, electric cars have always had a big drawback: Charging takes much longer than filling up a gas tank.
But the gap has been closing, and this week, Chinese battery giant CATL announced battery technology nearing parity. On Tuesday, the company said its third-generation Shenxing fast-charging battery goes from 10 percent to 98 percent charged in 6 minutes and 27 seconds.
If you’re driving an electric car around town, charging is a breeze. You probably don’t have to do it more than a couple times a month. And when you do, you can plug your car in overnight at home.
For longer trips, you’ll need a charging station. Smartphone apps can help, and drivers learn to plan ahead, but it’s still a pain. Stations aren’t abundant, and when you find one, there may be a line. A full charge will then take the better part of an hour. Most people aim for 80 percent, but even that consumes up to a half hour. EV fans may find it’s worth the trouble, but range is a sticking point for many drivers.
It’s no wonder that battery makers have been hyper-focused on energy density, which determines how far EVs can go, and charging speed. They’ve improved both in recent years. But increasing range, which involves balancing a complex mix of battery chemistries, weight, and economics, may prove a tougher tradeoff to manage than bringing charging times in line with gas-powered cars at the pump.
In other words, if you can travel the same distance and charge or gas up in roughly the same amount of time, the two become interchangeable on long trips. (This also depends, of course, on infrastructure—more on that below.)
CATL has been pushing the boundaries of charging speeds with its Shenxing line of fast-charging batteries, first announced in 2023. The company is the world’s largest EV battery manufacturer. Its products power EVs in China but also American brands including Tesla and Ford.
The numbers are hard to compare generation to generation and company to company, as the specs reported vary. The second-generation Shenxing battery, announced last year, charged from 5 percent to 80 percent in 15 minutes, according to the Financial Times. Then in March of this year, rival battery maker BYD said its Blade 2.0 model charged 10 percent to 97 percent in 9 minutes.
Notching nearly a full charge in under 10 minutes was already an impressive mark.
But on Tuesday, CATL one-upped BYD with its third-generation Shenxing, which takes a full charge in a little over six minutes. At a maximum legal rate of 10 gallons per minute at gas stations in the US, that’s still a few minutes longer than it takes to fill up most gas-powered cars. But it might also be fast enough not to matter. Big gas-powered trucks are already in the same range. And CATL said charging to 80 percent takes just 3 minutes and 44 seconds—which is nearly a wash.
“This effectively closes the gap with ICE [internal combustion engine] vehicles,” Bernstein analysts wrote in a note quoted by the Wall Street Journal.
Fast-charging batteries have shorter lifespans due to excess heat. But CATL said it’s tamed the heat by decreasing the amount produced in operation, more effectively bleeding it off, and controlling how and when it’s generated. The battery retains over 90 percent capacity after 1,000 charging cycles.
“The boundaries of electrochemistry are still far from being reached, and the possibilities of materials science are still far from being exhausted,” CATL founder and CEO, Robin Zeng, told reporters and investors, per the Financial Times.
With 6-minute charging times, it’s easy to imagine charging station lines evaporating. Instead of drivers grabbing a meal while their car takes up real estate, they’d breeze in and out, like at a gas station.
That vision will take time to materialize, however. There are still far fewer charging stations than there are gas pumps. And those that do exist won’t include chargers that handle the bleeding edge anytime soon.
As for the batteries themselves, splashy press releases don’t usually translate to near-term availability and might not match real-world performance. The third-generation Shenxing isn’t likely to hit roads right away. When it does, it could show up in Chinese models first, be pricey (like BYD’s latest offering), and require fancy new chargers.
Still, it’s no longer theoretical: EVs can compete with the convenience of traditional cars at the gas station.
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2026-04-22 04:08:48
A new tool that tethers healthy mitochondria to ailing cells has shown promise in mice with inherited blindness.
Our cells produce energy in biological power plants called mitochondria. These energy-makers have minds of their own. They operate using a unique set of DNA and can travel outside cells. Like astronauts, they often escape in fatty bubbles, land on other cells, explore them, and sometimes literally fuse with native mitochondria in their new homes.
This makes mitochondrial diseases hard to treat. Few gene editing tools can reach them and fix genetic typos. Even without mutations, mitochondria falter with age, contributing to diabetes, Alzheimer’s disease, heart failure, and other medical scourges.
But an experimental fix is gaining traction. Researchers are shuttling healthy mitochondria into cells—essentially transplanting them—to restore energy production and reboot metabolism.
There’s a major roadblock, however. Getting healthy mitochondria to the right cells is challenging. Scientists at the Institute of Molecular and Clinical Ophthalmology Basel have now developed a system that tethers donated mitochondria to their targets.
Called MitoCatch, the scientists engineered matching proteins and attached them to donor mitochondria and recipient cells. Like hook-and-eye fasteners, the binders pull the two partners into close contact. From there—by mechanisms that are still mysterious—the new mitochondria ride in on fatty bubbles, disembark inside the cell, and get to work.
In the study, the researchers delivered mitochondria to multiple cell types, and an injection of mitochondria saved vulnerable retinal cells in mice with inherited blindness.
“As a therapy, mitochondria transplantation has been hindered by the lack of tools to target healthy mitochondria directly to disease-affected cells,” wrote Samantha Krysa and Jonathan Brestoff at Washington University School of Medicine, who were not involved in the study.
MitoCatch overcomes this barrier.
Roughly two billion years ago, an ancestral cell ate a bacterium. But rather than digesting it, the cell formed an unlikely alliance with its erstwhile prey. The bacterium converted oxygen into energy for the host, and received protection and nutrients in return. Over time, the bacterium gave up its independence and became a critical part of our cells: mitochondria.
Unlike other cell structures called organelles, mitochondria carry 37 unique genes that encode the core components of their energy-making machinery. Their stripped-down genome leaves little margin for error and is especially vulnerable to mutation. It’s also shielded by a double membrane, making it difficult to reach using conventional biotech tools.
But mitochondria have a superpower: They can leave host cells. Research from the last two decades shows that many cells export some mitochondria into the cellular void. The practice could be a way to rid themselves of damaged mitochondria or to deliver healthy ones to struggling neighbors, like an intercellular care package.
This quirk led to the idea of mitochondrial transplantation. Here, healthy mitochondria are injected into tissue or the bloodstream to treat damaged cells. Early results are encouraging. Transplant extends the healthy lifespan of mice with mitochondrial defects, limits injury after stroke or heart attack, accelerates wound healing in people, and hints at benefits for obesity.
Because nearly every human cell depends on mitochondria for energy—and falters when they break—transplantation could unlock treatments for a broad range of diseases hard to treat today. That is, if healthy replacements can reach their destination.
“Being able to deliver mitochondria efficiently to the right cell types has been a key hurdle for this therapeutic strategy,” wrote Krysa and Brestoff.
MitoCatch relies on a cellular “handshake.” All cell surfaces are densely studded with proteins, some universal, others unique to specific cell types. These proteins interact with surrounding molecules to drive biological processes. During infection, for example, antibodies latch onto proteins on bacteria to trigger an immune attack. CAR T cell therapy outfits T cells with protein “binders” so they can better recognize and eliminate cancer cells, senescent cells, or cells involved in autoimmune disorders. In each case, success hinges on matched protein pairs snapping together like hook-and-eye fasteners.
The new system works on the same principle and has three designs. MitoCatch-M helps donor mitochondria recognize markers unique to different types of recipient cells. MitoCatch-C flips the approach, modifying recipient cells with binders that better capture mitochondria. And a third version uses a “bispecific” tether that simultaneously grips mitochondria and target cells. Once in close proximity, mitochondria are packaged in fatty bubbles that drift into the cell.
Then comes a brief moment of terror.
Many of these bubbles are routed to the cell’s waste processing organelle, where their cargo is completely destroyed. The mitochondria must escape before it’s too late.
In cultured brain, retinal, heart, skin, and immune cells, the tailored mitochondria largely avoided death. How they managed this up for debate, and the team is trying to work it out now. But once inside, the donor mitochondria fused with the cell’s native mitochondrial network.
This “suggests that MitoCatch can be used to enhance the efficacy of mitochondria transplantation substantially,” wrote Krysa and Brestoff.
Of course, cells in a dish aren’t the same as those in bodies. In another test, the team injected the engineered mitochondria into the eyes of mice with a hereditary condition where a single mitochondrial genetic defect destroys cells in the retina, resulting in gradual vision loss.
Over 10 days, the healthy mitochondria revamped treated cells’ metabolisms, reduced damage, and boosted survival and response to light. Whether this translates to better vision remains to be seen, but the treatment didn’t trigger an immune response, a promising sign it might be safe. To be clear, the transplanted mitochondria didn’t correct the underlying mutation. Instead, they supplied enough working versions of the gene to bring energy production back to life.
It’s “a proof-of-principle that mitochondria transplantation can be used to correct mutations encoded in the mitochondrial genome that cause a severe form of vision loss,” wrote Krysa and Brestoff.
MitoCatch isn’t ready for prime time. It requires extensive genetic engineering, making the system difficult to translate for routine treatment. It’s also still unclear how long transplanted mitochondria last in their new hosts and whether they have a lasting benefit.
These early results highlight the ways scientists can boost the therapy’s potential. With more work, we may have a new way to tackle previously untreatable mitochondrial disorders.
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