Scientists just transformed a living mouse’s kidney into an incubator for developing human sperm made from blood cells.

It sounds like sci-fi Mad Libs. But a team at the University of Pennsylvania, led by Kotaro Sasaki, pulled it off. For up to nine months, a tiny pouch of human cells nestled beneath a mouse’s kidney gradually developed into immature sperm. The study is the latest in a decade-long quest to grow sperm in the lab.

If successful, lab-grown sperm could open a new window into the earliest stages of sperm development, a process that’s notoriously difficult to study because it begins before birth. The research could also shed light on male infertility—which, in many cases, has no clear cause—and inspire treatments.

More controversially, lab-grown sperm could one day be used to make babies, offering hope to people struggling to conceive and same-sex couples who want to have children genetically related to both parents. That goal is still far off. Though gene activity was similar to their natural counterparts, none of the lab-grown cells were able to develop into functional sperm.

Those results starkly contrast similar attempts in mice. Researchers have already produced functional sperm and egg cells from rodent skin cells, and in two pioneering cases, used them to create healthy pups with two dads. But translating this capability to humans has been difficult, largely because reproductive development differs tons between species.

Still, the new system can help scientists probe the earliest stages of human sperm development. And because any future clinical applications would first need extensive testing in non-human primates, the team also generated immature sperm cells from monkeys, whose reproductive biology more closely mirrors our own.

Recapitulating sperm development in the lab has uses beyond fertility treatment too, such as testing whether drugs interfere with reproduction. The platform “establishes a robust framework for modeling primate germ cell [reproductive cell] development,” the team wrote.

Winning Recipe

For decades, scientist have been able to rewind adult cells into induced pluripotent stem cells (iPSCs). These cells can go on to  become nearly any other cell type. But steering them to become sperm has proven far trickier, largely because human sperm takes years to fully develop.

The journey begins before birth. Early stem cells give rise to spermatogonia, the founder cells that replenish sperm throughout life. These cells are largely dormant until puberty, when some begin meiosis, a special type of cell division that halves their chromosomes. That way, when sperm meets egg, the embryo gains a full genetic set.

But the cells don’t live in a vacuum. Proteins and other molecules instruct immature sperm when to grow, divide, or pause. Physical forces, such as the winding architecture of the testes and the flow of fluid, also play a role. Recreating this intricate environment in a dish has been one of the biggest challenges to the study of sperm development and our ability to grow them in the lab.

Roughly a decade ago, Sasaki and colleagues found a way to transform human iPSCs into early stem cells that could eventually give rise to sperm and egg. On paper, their gene expression profile closely matched that of natural counterparts. But in practice, the cells couldn’t mature further without the right environmental cues.

In an usual workaround, the team next mixed the immature cells with supportive, non-reproductive cells isolated from mice testes. While it was an usual environment, the mice cells provided nutrients and molecular signaling that nudged development forward.

Called xrTestis, the mixture spontaneously organized into tube-like structures resembling those inside testes. “Overall, our culture method accurately recapitulates in vivo human male GC [germ cell] development and allows us to understand the genetic pathways governing this process,” they wrote at the time.

Yet none of the immature sperm advanced beyond developmental stages normally seen in fetuses. And the miniature structure collapsed after 80 days, likely because it lacked a blood supply.

Unexpected Host

To prolong the mixture’s viability and push sperm development further, the team transplanted it into the kidneys of immunodeficient mice.

The graft organized itself into the hallmark tubular structures found in testes within a month and remained stable for at least half a year. The mice showed no signs of discomfort or immune rejection.

Six months later, some human cells developed into spermatogonia—the self-renewing stem cells that eventually generate sperm. Along the way, they underwent a major event: an epigenetic reset. During this process, chemical tags on DNA that influence whether genes are turned on or off are almost completely wiped clean. If that reset is incomplete, it could compromise any sperm eventually used for reproduction.

Here, the team found a “dramatic” genome-wide epigenetic reset. The cells’ gene activity mirrored their natural counterparts. Even though the graft survived for at least nine months, however, none of the cells were able to develop into mature sperm.

This is likely due to the environment. Human and mice testes don’t share the exact same signaling molecules or respond the same way to hormones and other developmental cues. Replacing the mouse support cells with human versions could help the spermatogonia develop further.

The Ultimate Test

The team also tested the technique in monkeys, with results similar to those found in human cells. “While our human iPSC system provided valuable insight into male gametogenesis [the formation of reproductive cells], future studies of fertility competency must be carried out in non-human primates,” they wrote.

Although the cells also halted at the immature stage, the results are still valuable. Previous studies have shown monkey spermatogonia can generate mature sperm after transplantation into recipient testes, opening the door to eventually testing if lab-grown cells can sire healthy offspring.

That idea is precisely what makes some bioethicists uneasy.

Mass-producing sperm and eggs in the lab could generate far more embryos for selection, making it easier for prospective parents to choose desirable traits such as eye color or height. Pairing the technology with gene editing makes “designer babies” less hypothetical. And if skin scrapings or a single hair can be turned into reproductive cells, someone could theoretically create sperm or eggs from another person without consent.

These scenarios are purely speculation, but regulators are already preparing for that future. In 2025, the United Kingdom’s Human Fertilization and Embryology Authority urged the government to explicitly tackle lab-grown reproductive cells in legislation. The International Society for Stem Cell Research has similarly called for careful oversight and public engagement before clinical use. Most countries, however, are only beginning to grapple with how these technologies should be dealt with.

Meanwhile, companies are pressing forward. Paterna Biosciences in Utah recently announced they had produced functional sperm from immature sperm collected during testicular biopsies. According to the company, early embryos created with the lab-grown sperm seemed comparable to those produced through standard in vitro fertilization (IVF). And California startup Conception recently reported generating early human egg cells from iPSCs. Neither company has released results in a preprint or journal article, making the claims hard to evaluate.

Like germline gene editing, conversations weighing the pros and cons of lab-grown reproductive cells will help decide not only what’s possible, but also what should be permitted. For now, the team stresses that their work is only a research tool—not a fertility treatment—and clinical use is a long way off.

The post Scientists Inch Closer to Creating Human Sperm in the Lab appeared first on SingularityHub.

Thinking is hard. It’s no wonder we lean on technology to lighten the load. We use calculators instead of doing long division by hand, GPS or Google Maps for navigation, and search engines instead of countless trips to the library. Yet just a few decades ago, getting around meant unfolding paper maps, and looking up a word required leafing through a hefty dictionary. Cognitive offloading of mental tasks to tools makes us more efficient. What’s the harm?

Then along came ChatGPT, Claude, and Gemini. Unlike earlier digital tools, AI chatbots can tackle an astonishing range of tasks and are easy to use. At a prompt, AI generates essays, analyzes medical images, writes software, and floods our feeds with AI slop. It’s cognitive offloading to the max.

Now people are asking: Is AI dulling our minds?

Yes and no, according to a new paper written by an international team of psychologists. AI can accelerate learning by giving people immediate guidance and feedback. But take the tool away, and those who rely on it often perform worse than people who learned the material on their own. Similarly, using AI to summarize information, rather than researching and organizing it yourself, often leads to shallower understanding.

But it’s not all bad news. Core cognitive abilities—including attention, reasoning, and working memory—seem to be “stubbornly resistant” to manipulation, the team wrote.

As technology evolves, so does the way we gain knowledge and think for ourselves. AI may reshape not just what we learn, but how we learn to learn. And like any other tool, its impact comes down to how we use it. Completely relying on AI is likely detrimental. But as a collaborator that challenges ideas or fills knowledge gaps, it can boost performance even after the tool is taken away.

“There is clearly a risk that AI can make us ‘stupid’ by compromising our skills (and knowledge) if we completely offload them to AI,” wrote the team. “[But] AI may be less likely to diminish the foundational cognitive capacities that underpin our ability to be smart, rather than ‘stupid’, in the first place.”

The AI Crutch

It’s easy to rely on large language models (LLMs)—the algorithms behind chatbots—for help. Why read an assigned novel when AI can summarize it in seconds? Gmail has already drafted an email reply; all I need to do is click send. That pesky essay? A few prompts and voila, done.

It seems like an easy hack, but there’s a cost to handing over too much thinking.

Researchers have long studied the consequences of cognitive offloading, or using external tools to reduce mental effort. Writing down a shopping list and keeping appointments in a calendar free up working memory, the brain’s temporary mental workspace, and allow us to focus on more important tasks without having to remember every detail.

AI is different. Beyond memory, it can offload critical thinking itself.

An MIT preprint introduced the idea of “cognitive debt” to describe the tradeoff. Participants wrote essays either with ChatGPT, using only a search engine, or with just their brains. Researchers monitored their brain activity during the task. Those using AI showed the weakest brain connectivity, which suggests they were less engaged. They also struggled to remember their own writing and felt the completed essay didn’t reflect their own ideas. When asked to write again without AI, they produced weaker work according to human judges.

Like financial debt, cognitive debt offers an immediate payoff with long-term consequences. Outsourcing mental effort makes writing faster and easier, but it slashes opportunities to build knowledge, strengthen reasoning, and practice critical thinking.

“While LLMs offer immediate convenience, our findings highlight potential cognitive costs,” wrote the MIT team.

Other studies have found the same pattern. High school students learning a new mathematical concept solved practice questions better with AI help, but they struggled on a later test when left to think on their own. Using AI “impeded the students’ learning by preventing them from engaging in the practice needed to acquire the skill,” wrote the team.

Habitual reliance on AI may even erode already-acquired expertise. In a large study of over 1,400 patients undergoing colonoscopy screening, doctors used an AI system to help detect abnormal growths. Three months later, when the AI was unavailable, their detection rate dropped from 28.4 to 22.4 percent.

“Continuous exposure to AI…[suggests] a negative effect on endoscopist behavior,” wrote the European team.

These effects extend beyond individual skills. AI can also influence how we build knowledge in the first place.

A recent study asked participants to learn about gardening by either Googling and synthesizing the knowledge themselves or by asking ChatGPT for a summary. They were then asked to give advice to someone else without technological help. Answers from those who relied on ChatGPT were rated as generic and less helpful, suggesting a shallower understanding of the topic.

With Great Power

We’re only beginning to understand how AI reshapes the mind. And it’s not all doom and gloom. The crux is how we use it.

In the MIT essay-writing study, for example, people who initially wrote on their own but later gained access to ChatGPT produced work with higher creativity and stronger arguments, while retaining their original perspectives and voice. Likewise, high school students who used AI as a tutor—asking for hints rather than answers—performed well even after the chatbot was taken away.

Used thoughtfully, AI may also enhance collaborative learning and brainstorming or serve as a writing coach, helping people work less and learn more.

Far less is known about if, and how, AI impacts fundamental cognitive capabilities. Attention, reasoning, and working memory have proven remarkably resilient over decades of cognitive research. Becoming better at a task usually reflects learning to use these mental resources more efficiently, not expanding the brain’s processing power. While AI may erode a specific skill, it could spare this core cognitive architecture, wrote the authors.

Whether that remains true over decades of AI use or during early childhood—when the brain is rapidly developing—is an open question.

Plenty other unknowns remain. Will we eventually adapt to AI, just as we’ve embraced calculators, search engines, and smartphones? Can refresher training ward off skill decay, or will some tasks simply become obsolete? How can we encourage people to strategically offload and benefit from AI use? And perhaps more philosophically: As we increasingly share our thinking with machines, will our definition of thinking evolve?

The post Is AI Making Us Dumber? appeared first on SingularityHub.

Stress does more than take a toll on mental health. After a particularly taxing week or month, it’s easier to catch a cold and harder to recover. Health issues build up as stress lingers, raising the risk of heart disease, diabetes, cancer, and a weakened immune system.

Chronic stress is often treated as an unavoidable part of modern life. While therapy can help people cope, researchers are increasingly asking a deeper question: How do stress signals in the brain ripple through the rest of the body, and can that damage be stopped?

A new study offers one of clearest answers yet. In mice modeling chronic stress, activity dropped in two brain regions governing emotional resilience. By way of a large nerve to the digestive track, the change wiped out a beneficial bacterial strain key to a healthy microbiome.

Without those microbes, the gut produced less of a crucial molecule that helps cells clear damaged proteins and other molecular  junk. These effects impacted the bone marrow, where stem cells generate oxygen-carrying blood cells and components of the immune system. Over time, these stem cells dwindled, leaving signs of premature immune aging in stressed mice.

“One surprising finding of our study was that suppression of only two specific brain regions was sufficient to produce many of the hematopoietic [blood stem cell] defects caused by psychological stress,” study author Linjia Jiang at Sun Yat-sen University said in a press release.

By tracing a direct pathway from brain to gut microbiome and bone marrow, the results could inspire new ways to blunt the biological toll of stress, from targeted probiotics to non-invasive brain stimulation.

Three-Piece Puzzle

De-stressing has become synonymous with self-care. Whether it’s work, family obligations, or a stream of notifications stressing you out, escaping into a good book or a walk in the woods feels like a deep mental exhale.

Stress has its perks. A product of the “fight-or-flight” response, it activates the sympathetic nervous system, a kind of highway connecting brain and body. In extreme cold, the system redirects blood from the skin to vital organs and temporarily slows digestion to prioritize muscles during a marathon. Brief bursts of stress aren’t detrimental. They’re an evolutionary survival hack.

But chronic stress is another story. Decades of research have found that prolonged or repeated mental strain disrupts brain activity and increases the vulnerability to a range of diseases. This is largely related to stress hormones released by the brain. But direct electrical signals traveling to the gut—which is often nicknamed the “second brain”—may also play a major role.

The garden of microbes in our gut roughly matches the number of cells in the body. These bacteria regulate digestion, metabolism, and immunity. They also communicate with the brain. When the ecosystem falls out of balance, it contributes to conditions ranging from diabetes to brain disease.

These beneficial effects can be traced to chemicals gut microbes manufacture. Lactobacillus reuteri, for example, boosts production of spermidine, a molecule that helps cells and tissues clear toxic debris. The process, called autophagy, is essential for the maintenance of healthy tissues but declines with age.

Stress also makes blood stem cells less resilient. Studies have linked prolonged stress to shortened telomeres, the protective caps at the ends of chromosomes, and an accumulation of senescent “zombie” cells. Both are hallmarks of accelerated biological aging.

The brain, gut microbiome, and bone marrow all respond to chronic stress. The new study aimed to find out if they’re connected.

Chain Reaction

To trace how chronic stress ages the body, the team tested four mouse models. Some experienced mild nerve injury. Others faced subtle disruptions to their daily routines, such as lights switching on earlier than expected or their home cages gently rocking at unpredictable times.

The changes put the mice on edge based on established behavioral tests. Mapping brain activity, the team zeroed in on two regions that consistently quieted. One, the medial prefrontal cortex, orchestrates executive control, or the ability to keep ideas in mind while reaching towards a goal. The other, the periaqueductal grey, coordinates attention to potential threats.

As activity decreased in both regions, blood stem cells struggled to divide and replenish immune cells. Inflammation and other toxic pathways flared up, and the cells developed molecular signatures similar to those seen in much older animals. Silencing either brain region with genetic tools reproduced many of the same symptoms, suggesting neural changes are a cause, not just a correlation.

But how was the brain communicating with the bone marrow? The answer lay in the gut microbiome.

Comparing the levels of chemicals surrounding the bone marrow in stressed and unstressed mice, the team zeroed in on spermidine. The molecule is made by gut bacteria and boosts autophagy, a process that’s linked to healthy aging.

Spermidine levels plummeted in stressed mice due to the loss of Lactobacillus reuteri, a beneficial strain of bacteria in the gut ecosystem that supports spermidine production. Stress-related nerve signals from the brain depleted these microbes, which caused spermidine levels to collapse and leaves blood stem cells unable to maintain themselves.

In another test, transplanting gut microbes from a stressed mouse into a happy-go-lucky mouse triggered early blood stem cell aging in the recipient—even though it didn’t experience stress itself. The results strengthen the case that the gut microbiome is a major link between the brain and bone marrow.

Rather than stress hormones, the pathway seems largely driven by electrical signals traveling from stress-sensitive brain regions to the gut. This means targeted brain stimulation could interrupt the cascade. Supplementing Lactobacillus reuteri as a probiotic or directly providing spermidine in a pill may also restore the missing molecule and slow blood stem cell aging.

This is just speculation though. Stress is deeply personal, and mice can’t capture the entire human experience. The team is now investigating whether the same brain circuits operate in people and if targeting this brain-gut-bone marrow axis can benefit the immune system.

“Our findings raise the possibility that managing psychological stress may not only improve mental well-being but also help preserve immune function and promote healthy aging,” said Jiang.

The post Scientists Find a Surprising New Way Stress Cascades From Brain to Body appeared first on SingularityHub.

Watchers held their breath as the robot made its first incision. Hovering over its patient, an anesthetized pig, with a robotic assistant standing nearby, it navigated to the gallbladder and gently removed it.

The operation marked the debut of humanoid robots in a standard surgical setting. The robot, named Surgie, wasn’t autonomous—it was controlled by an expert surgeon—but the study is a step toward using humanoid robots as collaborators in minimally invasive surgery.

“Remotely operated and autonomous humanoid robots have real potential for amplifying access to critical surgeries to which patients would otherwise not have access,” said study author Michael Yip at UC San Diego.

The study included two successful surgeries. Human surgeons remained on standby for emergencies, but the teleoperated robot completed the task with only minimal intervention.

Feedback from surgeons operating Surgie was positive. They reported less physical strain and frustration, along with better overall performance. But they also pointed to practical problems like intermittent overheating and the need to frequently reposition the robot.

Despite a long road ahead, humanoid robots “have a viable future,” said Yip. “You can imagine these robots being deployed in remote communities where staffing is challenging, or in austere environments like search and rescue scenarios where a massive deployment of field medicine is needed in a short period of time.”

Smooth Operator

Robots have assisted surgeons for years. With a human surgeon at the helm, they excel at delicate procedures requiring precision and dexterity. They’re especially well-equipped for laparoscopic surgery, a minimally invasive technique that uses tiny incisions to reduce pain, speed recovery, and lower the risk of infection.

Despite the promise, surgeons face tradeoffs when they use surgical robots. The robots are highly specialized and often require operating rooms to be redesigned to accommodate them.

A major reason for this is the way they’re built. Intuitive Surgical’s Da Vinci system, for example, uses a robot with multiple arms, each independently controlled from a remote console. Other systems, such as Versius from CMR Surgical, deploy several lightweight independent arms, each attached to a mobile base. The robots have to be carted near the patient.

Surgeons operate all these systems from a console using a magnified, high-definition, 3D view of the surgical field, which is often better than what they’d see with their own eyes. Da Vinci 5 adds sharper visuals and depth perception with two cameras, one for each eye. And because the cameras are held by a robot rather than a human assistant, the image is far more stable.

These platforms are already used in a range of operations. But they have weaknesses. Most require proprietary surgical instruments and methods to make extra space for robot docking and maneuvering during procedures. Staff training adds further complexity and cost, limiting where the systems can be deployed.

Humanoid robots, in contrast, are far more mobile and compact. Their human-like bodies could move through standard operating rooms, use conventional surgical instruments, and potentially be easier to incorporate into existing operating rooms.

The timing may also be right. Recent advances in electric components controlling their motion have made humanoid robots faster and more stable than their awkward, stumbling predecessors. Newer AI systems that predict full-body movement and provide feedback have improved robots’ balance and ability to adjust to real-world complexities. Humanoid robots are already stocking warehouses and winning marathons.

But surgery sets a higher bar.

We still don’t know how close humanoid robots are to meeting the requirements for surgical procedures, wrote the team. That’s what they set to find out.

Hello, Surgie

The new system consists of a surgeon’s control console and the robot itself. The surgeon wears a stereoscopic headset with a magnified 3D view of the surgical field and controls the robot with an input device. The robot translates the surgeon’s commands into movements in real time.

The team chose the commercially available Unitree G1 for the job. Unlike Da Vinci, which was built for surgery, G1 is a more general-purpose humanoid with dexterous wrists and multiple joints. The researchers customized the robot’s hands so that it can rapidly switch between surgical tools. Standing just over four feet tall and weighing roughly 77 pounds, the robot takes up a fraction of the space needed by conventional surgical robots.

Precision is key for laparoscopic surgery. Surgical instruments must pivot around a fixed site at the incision, allowing them to move freely inside the body without stretching or tearing neighboring tissues. After extensively mapping Surgie’s movements, the team identified a safe set-up with enough range of motion for most minimally invasive surgeries.

Surgie passed standard robotics benchmarks evaluating surgical skill for both humans and robots. But the real challenge came next. The team performed two gallbladder removal surgeries in a standard operating room. Both operations followed a typical workflow, with a lead surgeon and an assistant responsible for placing the camera, cleaning lenses, and swapping instruments.

Surgie collaborated with the human assistant to locate, identify, and remove the gallbladder with minimal damage to surrounding tissues, including the liver. During part of one procedure, a second humanoid briefly took over camera handling while the human assistant stepped aside.

Both operations went relatively smoothly. One involved minor bleeding and bile leakage from the gallbladder, but both were easily managed. In interviews, surgeons said controlling humanoid robots felt intuitive, particularly because they had two arms and could use standard surgical tools.

“We were surprised at how well Surgie meshed with our workspace and workflow,” said study author Nikita Thareja.

The system is still in early development. Surgie’s restricted reach required frequent repositioning and recalibration, adding more than three minutes each time. The robot also occasionally needed cooling breaks after overheating. In a real operating room, interruptions like these could increase risk by forcing surgeons to split their attention between the procedure and supervising the robot.

Still, Surgie has a leg up on conventional surgical robots: It can walk. Beyond assisting with an operation, it could potentially fetch surgical tools or help clean operation rooms between procedures.

The team is now refining the system to reduce control lag, particularly during long-distance teleoperation, and exploring ways to safely sterilize—or “scrub in”—a humanoid robot for the operating room.

“Our goal is an operating theater of the future, where humanoid robots and humans work side by side as an integrated team to deliver procedures to those in need, both in traditional hospital settings as well as in non-traditional, field medicine scenarios,” said Yip.

The post In a First, a Humanoid Robot Performed Live Surgery Under a Surgeon’s Control appeared first on SingularityHub.

Cancer researchers just found a new way to take on tumors.

CAR T cell therapy revolutionized blood cancer treatment by supercharging a patient’s own immune cells to hunt down cancers. But the approach has struggled in solid cancers. These are some of our top killers—breast, lung, prostate. Roughly two million Americans are expected to be diagnosed with cancer in 2026, and over 600,000 will likely succumb to the disease.

Unlike blood cancers, solid tumors rarely share a single, universal target for CAR T cells. Even cells within the same tumor are a mishmash. Some have little or none of a target protein, allowing them to evade the engineered immune cells, survive treatment, and fuel relapse.

“Target discovery remains a considerable challenge in the development and translation of

CAR T cell therapies for solid tumors,” wrote Christopher Mount and Marcela Maus at the Massachusetts General Brigham Cancer Institute.

Now, two independent teams have converged on the same promising target: A cell-surface protein called GPNMB. In one study, CAR T cells engineered to recognize GPNMB rapidly destroyed glioblastoma—a lethal brain cancer—in tissues taken from patients and shrank tumors in mice.

A second team used a similar strategy against an aggressive soft tissue cancer to fight tumors in organoids and mice. In an early clinical trial involving a single participant, one infusion stabilized the disease for three months without serious side effects.

CAR T designers are often wary of broadly shared targets because they can trigger dangerous attacks on healthy tissue. But GPNMB is an odd duck. In addition to cancer cells, it also sits on immune cells that spur cancer growth or suppress the body’s innate ability to get rid of tumors.

“Our approach attacks both the tumor and the environment that allows it to thrive,” said Sheila Singh at McMaster, who led the glioblastoma study, in a press release. “We’re going beyond targeting the cancer alone and eliminating the immune cells that help shield it from treatment.”

Cancer Fortress

Solid cancers have plenty of tricks to outsmart CAR T cells.

Researchers make these supercharged immune cells  by extracting a patient’s own T cells and genetically engineering them to produce protein “claws” that latch onto a specific cancer target. After infusing the cells back into the body, they seek and destroy tumor cells. CAR T has transformed treatment for several blood cancers and is showing promise in autoimmune diseases and excessive heart and kidney scarring. To simplify the procedure, researchers are also exploring ways to directly transform T cells inside the body with gene therapy.

Solid cancers, however, are far tougher opponents. Unlike blood cancers, which are heavily coated with a shared target called an antigen, solid tumors are molecular patchworks. Cells within the same tumor can display different targets—or none at all—allowing some to evade a CAR T attack and trigger relapse. Many of these targets also appear on healthy tissues, raising the risk of dangerous side effects. And then there’s the tumor microenvironment: A toxic, glue-like “fortress” that hijacks immune cells and uses them to battle incoming CAR T cells.

These barriers aren’t impenetrable. Previous work enlisted  bacteria to help CAR T cells burrow into tumors. Other efforts engineered ultra-sensitive CAR T cells capable of detecting tiny amounts of a cancer target shared across multiple solid tumors.

“Recent reports of activity in several clinical trials reinforce optimism that these efforts may result in true clinical benefit,” wrote Mount and Maus, who were not involved in either study.

But these strategies require additional engineering steps, increasing complexity and cost. And most still leave one major roadblock intact: The tumor’s immune defenses.

One-Two Punch

In the glioblastoma study, the team at McMaster University scoured donated tumors for proteins that distinguished the most aggressive cancer cells. They found one standout: GPNMB. Another test of every protein dotting the cell surface confirmed it as a promising target. The protein is evident across a cancer cell’s membrane, making it readily accessible to CAR T cells.

In lab tests, CAR T cells engineered against GPNMB performed well, nearly eliminating tumors grown from patient samples and extending survival in mice.

The target turned out to be far more valuable than expected. The team soon realized that GPNMB also marked the immune cells that suppress anti-cancer drugs. CAR T cells attacked both fronts simultaneously, weakening the tumor’s immune shield and killing the cancer itself.

“Most approaches have focused on killing cancer cells alone,” said study author Shan Grewal. “Our work suggests we may also need to dismantle the immune support system that helps the tumor survive.”

The second team focused on alveolar soft-part sarcoma, a rare soft-tissue cancer that often spreads to the lungs, brain, and bones before it’s diagnosed. Treatment often comes too late.

The disease is driven by a type of “fusion” gene created when pieces of genetic material are accidentally stitched together. These genes are extremely tough to target directly. Instead, the team screened all surface proteins on the cancer cells and again landed on GPNMB as a top candidate for intervention. The protein’s levels closely tracked the activity of the fusion gene.

CAR T cells targeting GPNMB cleared tumors and prevented metastasis in mice. But because an earlier antibody drug against the protein caused severe skin toxicity in patients, the team also tested their CAR T cells in mice carrying small human skin grafts. Although inflammation initially flared, there were no signs of ongoing skin damage.

Encouraged, the team treated a patient with relapsed, metastasized alveolar soft-part sarcoma. After a single infusion, the engineered cells rapidly divided in the bloodstream and remained detectable for roughly a month. The treatment didn’t trigger skin rashes or more dangerous side effects, like cytokine release syndrome where the body mounts a hyperactive immune defense that harms healthy organs.

The treatment’s benefits outlasted the engineered cells themselves. For roughly three months, imaging tests found fewer of the small, round spots on the patient’s lungs that often signal metastatic cancer, suggesting the disease had stabilized.

A final analysis identified another roadblock: Clusters of cells that suppress the immune system and could blunt the benefits. Adding drugs to block these immune molecules boosted tumor killing in mice. Because the same kind of gene fusion drives other cancers, including kidney, the CAR T cells could have reach beyond this specific type of sarcoma.

Together, the studies underscore that the best CAR T targets might extend beyond cancer cells to expose and attack cancer’s immune cell supporters too. Finding a viable target is a delicate balancing act. Chosen well, and CAR T cells could tackle multiple drivers for cancer growth. Choose poorly, and healthy tissues could get hurt in the crossfire.

Even so, “these two studies indicate that GPNMB represents an actionable target for CAR T cell therapies in several solid tumors,” wrote Mount and Maus.

The post CAR T Revolutionized How We Treat Blood Cancers. Now It’s Closing In on Solid Tumors. appeared first on SingularityHub.

My octogenarian father-in-law is trilingual and a lifelong fan of the World Cup. As he cheers on his favorite teams in English, Spanish, or French—sometimes switching between them mid-sentence—I’m always amazed at how easy it seems.

Scientists have long been fascinated by the brain’s ability to learn and retain multiple languages. Even after years of disuse, a brief exposure can quickly revive a language without having to consciously relearn its grammar or vocabulary. Bilingualism may offer other cognitive perks. Small studies suggest it delays brain aging, lowers dementia risk, and provides a slight edge in executive function (the ability to stay focused on a goal).

But most  of the evidence is from brain imaging studies that offer only a bird’s-eye view of neural activity and miss the finer details.

Now, scientists from the Baylor College of Medicine and collaborators have recorded activity from single neurons in four bilingual volunteers with epilepsy as they listened, read, and spoke in English and Spanish. The participants already had electrodes implanted in the hippocampus—a brain region critical for learning and memory—to track the source of their seizures.

“This is the very first study to look at how bilingual brains work at the level of individual neurons, and to do so in real time,” said study author Xinyuan Yan in a press release.

The results suggest the bilingual brain operates on two levels. Individual neurons often showed a strong preference for one language when participants heard or spoke words with the same meaning. But networks of neurons were largely language independent. They spontaneously organized into a concept map, placing words with related meanings—such as “dog” and “wolf”—closer together than unrelated words like “fork.”

Surprisingly, both languages relied on the same underlying map. Using the English concept map alone, the team could accurately predict clusters of related Spanish words.

“It’s like looking into a room from a different window. Everything inside is the same, but the perspective is different,” said study author Sameer Sheth.

Bridging Worlds

Language is central to human connection. Although some words don’t directly translate, people can express the same ideas across multiple languages without losing their core meaning.

Children raised in multilingual households are especially adept at switching between languages, often blending words and phrases together. Even when languages differ dramatically in grammar, syntax, and pronunciation, the brain somehow keeps their structures distinct while fluidly merging their meanings.

Long before we learn to speak, neural networks transform thoughts into electrical patterns that form words and sentences. Because languages are built differently—for example, where a verb falls in a sentence—it seems reasonable that each language would have a unique neural fingerprint.

But that might not be the case. A recent AI-powered analysis of functional MRI (fMRI) scans from monolingual speakers of 21 languages suggested that languages share a similar neural scaffold that represents meaning and concepts. Even fictional languages, including Klingon from Star Trek and Na’vi from Avatar, appear to tap into the same underlying system.

A growing body of evidence from bilingual speakers echoes these findings. One fMRI study found native Chinese speakers learned English more efficiently when they recruited brain networks used for Chinese. Another study identified shared speech-related brain activity sufficient for decoding words across languages.

Despite hinting at a universal language map, these standard imaging technologies struggle to capture detailed patterns as people switch languages in real time. To see how bilingual brains actually pull off the feat, we need to listen in on single cells.

Mapping It Out

The team studied four volunteers fluent in English and Spanish. All had learned the languages before age five and continued to use them regularly. Each also had electrodes implanted in the hippocampus to monitor seizures as part of epilepsy treatment, allowing researchers to track individual neuron activity as they listened and spoke.

Though often overlooked in language research, the hippocampus is increasingly recognized as a hub for word meaning, and it may also link concepts together. Here, the team monitored more than 100 neurons in each participant as they completed three language tasks.

First, the participants listened to roughly an hour of YouTube videos and the audiobook Eat Pray Love (Come Reza Ama). Next, they read aloud nearly 100 phrases displayed on a screen, such as “let’s have fun” and its Spanish equivalent “vamos a divertirnos.” Finally, they spent up to 90 minutes chatting with native speakers of each language, discussing everything from family to their epilepsy journey.

By the end, the team had compiled thousands of spoken words, hundreds of matched phrases, and hours of natural conversation.

A Language Landscape

Only a handful of neurons appeared truly bilingual, responding similarly to equivalent words such as “friends” and “amigos.” To better interpret the neural activity, the team turned to mBERT, Google’s multilingual language model that understands more than 100 languages. Like other LLMs, the model represents words according to their relationships and context rather than simple dictionary definitions.

The comparison revealed a similar pattern in brains and machines. Individual neurons rarely encoded the same word across languages. Instead, meaning emerged at the population level.

Both neural activity and mBERT tracked broader context, organizing words into an abstract conceptual landscape called semantic geometry. In this map, related concepts cluster together—“cat” sits closer to “dog” than to “galaxy,” for example—even if the precise features defining those relationships are unclear.

Yet the map remained largely unchanged across languages, suggesting it captured a fundamental mechanism for language processing in the brain. Using the English map alone, the team could predict which Spanish words would cluster around “perro” (or “dog”).

“This is how the brain encodes the meaning of words across languages,” said Yan. “It doesn’t rely on individual neurons translating individual words, but groups of neurons adjusting their activities to create the similar pattern for equivalent words in both languages.”

The study focused on semantics, or meaning, as opposed to syntax, the rules governing sentence structure. A recent study also using single-cell recordings from people with epilepsy suggests that other groups of neurons, particularly those in the frontal parts of the brain, may specialize in grammar while ignoring semantics. Whether they also share a “map” across languages remains to be seen.

The next step is to watch these maps emerge. The team hopes to track people as they learn a new language, revealing how new words and concepts are woven into semantic landscapes in real time. The results could deepen our understanding of one of the most fundamental communication skills and even inspire more capable and efficient language models in AI.

“Our study shows that the brain is wired to learn multiple languages,” said study author Benjamin Hayden.

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