Rutgers Health researchers have made discoveries about brown fat that may open a new path to helping people stay physically fit as they age.
A team from Rutgers New Jersey Medical School found that mice lacking a specific gene developed an unusually potent form of brown fat tissue that expanded lifespan and increased exercise capacity by roughly 30%. The team is working on a drug that could mimic these effects in humans.
“Exercise capacity diminishes as you get older, and to have a technique that could enhance exercise performance would be very beneficial for healthful aging,” said Stephen Vatner, university professor and director of the Cardiovascular Research Institute in the medical school’s Department of Cell Biology and Molecular Medicine and senior author of the study in Aging Cell. “This mouse model performs exercise better than their normal littermates.”
Unlike white fat, which stores energy, brown fat burns calories and helps regulate body temperature. This study revealed brown fat also plays a crucial role in exercise capacity by improving blood flow to muscles during physical activity.
The genetically modified mice produced unusually high amounts of active brown fat and showed about 30% better exercise performance than normal mice, both in speed and time to exhaustion.
The discovery emerged from broader research into healthy aging. The modified mice, which lack a protein called RGS14, live about 20% longer than normal mice, with females living longer than males — similar to the pattern seen in humans. Even at advanced ages, they maintain a healthier appearance, avoiding the typical signs of aging, such as loss of hair and graying that appear in normal elderly mice. Their brown adipose tissue also protects them from obesity, glucose intolerance, cardiovascular disorders, cancer and Alzheimer’s disease, in addition to reduced exercise tolerance.
To test whether the brown fat — rather than some other result from the missing genes -accounted for the benefits, the researchers transplanted the brown fat to normal mice. They noted that the recipients gained similar benefits within days. Transplants using regular brown fat from normal mice, by contrast, took eight weeks to produce much milder improvements.
The discovery could eventually improve human lifespans — the total time when people enjoy good mental and physical health.
“With all the medical advances, aging and longevity have increased in humans, but unfortunately, healthful aging hasn’t,” Vatner said. “There are a lot of diseases associated with aging — obesity, diabetes, myocardial ischemia, heart failure, cancer — and what we have to do is find new drugs based on models of healthful aging.”
Rather than develop a treatment that addresses aging broadly, which poses regulatory challenges, Vatner said his team plans to test for specific benefits such as improved exercise capacity and metabolism. This approach builds on their previous success in developing a drug based on a different mouse healthful longevity model.
“We’re working with some people to develop this agent, and hopefully, in another year or so, we’ll have a drug that we can test,” Vatner said.
In the meantime, techniques such as deliberate cold exposure can increase brown fat naturally. Studies have found such efforts to produce short-term benefits that range from enhanced immune system function to improved metabolic health, but Vatner said none of the studies have run long enough to find any effect on healthful aging.
He added that most people would prefer to increase brown fat levels by taking pills rather than ice baths and is optimistic about translating the newest finding into an effective medication.
The world’s first “biological computer” that fuses human brain cells with silicon hardware to form fluid neural networks has been commercially launched, ushering in a new age of AI technology. The CL1, from Australian company Cortical Labs, offers a whole new kind of computing intelligence – one that’s more dynamic, sustainable and energy efficient than any AI that currently exists – and we will start to see its potential when it’s in users’ hands in the coming months.
Known as a Synthetic Biological Intelligence (SBI), Cortical’s CL1 system was officially launched in Barcelona on March 2, 2025, and is expected to be a game-changer for science and medical research. The human-cell neural networks that form on the silicon “chip” are essentially an ever-evolving organic computer, and the engineers behind it say it learns so quickly and flexibly that it completely outpaces the silicon-based AI chips used to train existing large language models (LLMs) like ChatGPT.
“Today is the culmination of a vision that has powered Cortical Labs for almost six years,” said Cortical founder and CEO Dr Hon Weng Chong. “We’ve enjoyed a series of critical breakthroughs in recent years, most notably our research in the journal Neuron, through which cultures were embedded in a simulated game-world, and were provided with electrophysiological stimulation and recording to mimic the arcade game Pong. However, our long-term mission has been to democratize this technology, making it accessible to researchers without specialized hardware and software. The CL1 is the realization of that mission.”
The CL-1: a large housing contains all the life support systems required for the survival of the human brain cells that power the chip
Cortical Labs
He added that while this is a groundbreaking step forward, the full extent of the SBI system won’t be seen until it’s in users’ hands.
“We’re offering ‘Wetware-as-a-Service’ (WaaS),” he added – customers will be able to buy the CL-1 biocomputer outright, or simply buy time on the chips, accessing them remotely to work with the cultured cell technology via the cloud. “This platform will enable the millions of researchers, innovators and big-thinkers around the world to turn the CL1’s potential into tangible, real-word impact. We’ll provide the platform and support for them to invest in R&D and drive new breakthroughs and research.”
These remarkable brain-cell biocomputers could revolutionize everything from drug discovery and clinical testing to how robotic “intelligence” is built, allowing unlimited personalization depending on need. The CL1, which will be widely available in the second half of 2025, is an enormous achievement for Cortical – and as New Atlas saw recently with a visit to the company’s Melbourne headquarters – the potential here is much more far-reaching than Pong.
The team made international headlines in 2022 after developing a self-adapting computer ‘brain’ by placing 800,000 human and mouse neurons on a chip and training this network to play the video game. New Atlas readers may already be familiar with Cortical Labs and its formative steps towards SBI, with Loz Blain covering the early advances of this self-adjusting neural network capable of adjusting and adapting to forge new, stimuli-responsive pathways in processing information.
“We almost view it actually as a kind of different form of life to let’s say, animal or human,” Chief Scientific Officer Brett Kagan told Blain in 2023. “We think of it as a mechanical and engineering approach to intelligence. We’re using the substrate of intelligence, which is biological neurons, but we’re assembling them in a new way.”
Cortical Labs has come a long way since that important first step but now-obsolete DishBrain, both in technology and name. Now, with the commercialization of the CL1, researchers can get hands-on with the the technology, and start exploring a vast range of real-world applications.
When New Atlas visited Kagan and team at Cortical Labs’ Melbourne headquarters late last year in the lead-up to this launch, we saw first-hand how far the biotechnology has come since the DishBrain. The CL1 features relatively simple, stable hardware, new ways of optimizing “wetware” – human brain cells – and significant strides towards being able to grow a neural network that works like a fully functional brain. Or, as Kagan explained of a work in progress, the “Minimal Viable Brain.”
In the lab, the early CL1 model is put through its paces as the team monitors its response to stimuli (prompts)
New Atlas
In 2022, the team demonstrated how rodent- and human-induced pluripotent stem cells (hiPSCs) integrated into high-density multielectrode arrays (HD-MEAs) based on complementary metal–oxide–semiconductor (CMOS) technology could be electro-physiologically stimulated to forge autonomous, highly efficient information-exchange paths.
To do so, they needed a way to reward the brain cells when they exhibited desired behaviors, and punish them when they failed a task. In the DishBrain experiments, they proved that predictability was the key; neurons seek out connections that produce energy-efficient, predictable outcomes and will adapt their networks in search of that reward, while avoiding behaviours that produce a random, chaotic electrical signal.
But, as Kagan explained, that was just the start.
“The current version is totally different technology,” Kagan told Blain and I. “The previous one used something called a CMOS chip, which basically gave you a really high-density read, but it was opaque, you couldn’t see the cells. And there were other issues as well – like, when you stimulate with a CMOS chip, you can’t draw out the charge; you can’t balance the charge as well. You end up with a build-up of charge at where you’re stimulating over long periods of time, and that’s pretty bad for the cells.
“With these versions, they’re a much simpler technology, but that means they’re much more stable and you’re much more able to actively balance that charge,” he added. “When you put in two microamps of current, you can draw out 2 microamps of current. And you can keep it more stable for longer.”
Chief Scientific Officer Brett Kagan assesses some stem cells cultivated in the lab
New Atlas
Inside the CL1 system, lab-grown neurons are placed on a planar electrode array – or, as Kagan explained, “basically just metal and glass.” Here, 59 electrodes form the basis of a more stable network, offering the user a high degree of control in activating the neural network. This SBI “brain” is then placed in a rectangular life-support unit, which is then connected to a software-based system to be operated in real time.
“A simple way to describe it would be like a body in a box, but it has filtration for waves, it has where the media is stored, it has pumps to keep everything circulating, gas mixing, and of course temperature control,” Kagan explained.
In the lab, Cortical is assembling these units to construct a first-of-its-kind biological neural network server stack, housing 30 individual units that each contain the cells on their electrode array, which is expected to go online in the coming months.
The team aims to have four such stacks running and available for commercial use through a cloud system before the end of the year. The units themselves are expected to have a price tag of around US$35,000, to start with (anything close to this kind of tech is currently priced at €80,000, or nearly US$85,000).
An entire rack of CL1 units uses only around 850-1,000 W of energy, is fully programmable and offers “bi-directional stimulation and read interface, tailored to enable neural communication and network learning,” the team noted in their launch release. Incredibly, the CL1 unit doesn’t require an external computer to operate, either.
Kagan and team testing the CL1 units, which are built to maintain the health of the cells living on the silicon hardware
New Atlas
The complex, ever-evolving SBI neural networks – which, under a microscope, can be seen forming branches from electrode to electrode – have, to start with, the potential to revolutionize how drug discovery and disease modeling is researched.
“We’re aiming to be significantly more affordable, and we do want to bring that pricing down in the long-term, but that’s the much longer term,” Kagan said. “In the meantime, we provide access to people from anywhere, anyone, any house, through the cloud-based system.
“So even if you don’t have one of these [units],” he added, “you can access one of these from your home.”
Taking us through the Physical Containment Level, or PC2, laboratory – a mix of computer hardware and more traditional biological specimens and equipment – Kagan showed us some of the all-important induced pluripotent stem cells (IPSC) under the microscope. IPSCs, cultivated in the lab from blood samples, are essentially blank slates that can grow into different types of cells.
“What we do is take those, and we start to use two different methods to differentiate them,” he explained. “One, we can either apply small molecules, which is called an ontogenetic differentiation protocol, where we essentially try to mimic the molecules that happen in utero or, rather, in the foetus’ developing brain. The other method is where we directly differentiate them, where we choose to up-regulate specific genes that are involved in neurons.”
One of the team’s methods is quick and produces a high level of cellular purity, however, the downside is that it isn’t exactly representative of the human brain.
“The brain is not a high-purity organ; it has a lot of different cell types, a lot of different connections,” Kagan said. “So if you only have one cell type, you might have that cell type, but you don’t have a brain.”
Just one section of the CL1 stack, with each unit housing living cells
Cortical Labs
The second method, “the small molecule approach,” produces diverse populations of cells, but it’s often unclear as to exactly what they’re working with. And understanding this is critical to Cortical’s ambitious ongoing pursuit of building the Minimal Viable Brain. While the CL1 launch is the first step, the team is also hard at work on the next stage of SBI.
“You can categorize the main cells, but there’s always a lot of sub-cell types – and that’s really good, as we’ve found out, but we’d really like to have fully controlled direct differentiation,” he explains. “We just haven’t resolved that problem yet: What is the ‘Minimal Viable Brain?’”
The MVB is an intriguing concept: How to bioengineer a human-like “brain” with the least amount of superfluous cell differentiation, but one that would have the complexity that growing a neural network made up of homogenous cell types doesn’t have. This kind of tool would be a powerful model, allowing for even more control and nuanced analyses than what is currently possible in research conducted on a real brain.
“It would basically be the key biological components that allow something to process information in a dynamic and responsive way, according to underlying principles,” Kagan explained. “A single neuron can do a lot of stuff, and while it can respond to some degree of dynamic behavior, it can’t, for example, navigate an environment. The smallest working brains we know of have 301 or 302 – depending on who you ask – neurons, and that’s in the C. elegens. But each of those neurons are really highly specified.
Actual human brain cells, living on a silicon chip among an array of input/output electrodes
Cortical Labs
“And another question is: Is the C. elegens brain the minimal viable brain? Do you need all of those neurons or could you achieve it with, you know, 30 neurons that are all uniquely circuited up?” he continued. (The organism is, of course, the science world’s favorite nematode, Caenorhabditis elegans.)“And if that’s the case, can you build a more complex network of those with 100,000 of the same 30? We don’t know the answer to any of this yet, but with this technology we can uncover it.
“We’re starting to add more and more cell types to this culture as we go, but one thing that’s holding us back is the tools,” he said. “The [CL1] unit didn’t exist until we built it, and you need a tool like that to answer questions like, ‘What is the minimal viable brain?'” If you have 120 units, you can set up really well-controlled experiments to understand exactly what drives the appearance of intelligence. You can break things down to the transcriptomic and genetic level to understand what genes and what proteins is actually driving one to learn and another not to learn. And when you have all those units, you can immediately start to take the drug discovery and disease modeling approach.”
This is particularly important for research into better treatments or even cures for conditions such as epilepsy and Alzheimer’s disease, and other brain-related illnesses. In the meantime, the CL1 system, is expected to advance research into diseases and therapeutics considerably.
“The large majority of drugs for neurological and psychiatric diseases that enter clinical trial testing fail, because there’s so much more nuance when it comes to the brain – but you can actually see that nuance when you test with these tools,” he explained. “Our hope is that we’re able to replace significant areas of animal testing with this. Animal testing is unfortunately still necessary, but I think there are a lot of cases where it can be replaced and that’s an ethically good thing.”
The ethics of this technology has been front and center for Cortical – that breakthrough 2022 paper sparked plenty of debate around it, particularly in the area of human “consciousness” and “sentience.” However, guardrails are in place, as much as they can be, for the ethical use of the CL1 units and the remote WaaS access.
The cells form an entirely new kind of artificial intelligence
New Atlas
“There are numerous regulatory approvals required, based on location and specific use cases,” the team noted in its launch statement. “Regulatory bodies may include health agencies, bioethics committees, and governmental organisations overseeing biotechnology or medical devices. Compliance with these regulations is essential to ensure responsible and ethical use of biological computing technologies.”
But as a global frontrunner in this ambitious technology, Cortical knows that – much like the rapid advancement of non-biological AI – it’s not easy to predict the broad applications of SBI. And one other challenge the company faces is funding – something that the realization of CL1 as a tangible, usable technology might change.
“The difficulty I keep hearing [from investors] is that we don’t fit into a box,” Kagan told us, as we took off our lab coats, hair nets and masks, and relocated to a couch by the computer room upstairs. “And we don’t – we’re a technology that crosses a number of different boundaries. If you look at the priority sectors, we can cover everything from the enabling capabilities of biotechnology, robotics, medical science, and a range of other things. We’re not quite AI, we’re not quite medicine – we can do both AI and medicine, but we’re not either. So we often get excluded.”
The complex life-support system inside each CL1 unit
New Atlas
As such, the launch of the physical CL1 system and the Cortical Cloud for WaaS remote use is a huge achievement, with Kagan and team excited to see where SBI can go once its in people’s hands.
“The CL1 is the first commercialized biological computer, uniquely designed to optimize communication and information processing with in vitro neural cultures,” the team noted. “The CL1, with built-in life support to maintain the health of the cells, holds significant possibilities in the fields of medical science and technology.
“SBI is inherently more natural than AI, as it utilizes the same biological material – neurons – that underpin intelligence in living organisms,” Cortical added. “By leveraging neurons as a computational substrate, SBI has the potential to create systems that exhibit more organic and natural forms of intelligence compared to traditional silicon-based AI.”
NASA and the Italian Space Agency made history on March 3, when the Lunar GNSS Receiver Experiment (LuGRE) became the first technology demonstration to acquire and track Earth-based navigation signals on the Moon’s surface.
The LuGRE payload’s success in lunar orbit and on the surface indicates that signals from the GNSS (Global Navigation Satellite System) can be received and tracked at the Moon. These results mean NASA’s Artemis missions, or other exploration missions, could benefit from these signals to accurately and autonomously determine their position, velocity, and time. This represents a steppingstone to advanced navigation systems and services for the Moon and Mars.
An artist’s concept of the LuGRE payload on Blue Ghost and its three main records in transit to the Moon, in lunar orbit and on the Moon’s surface.
NASA/Dave Ryan
[…]
The road to the historic milestone began on March 2 when the Firefly Aerospace’s Blue Ghost lunar lander touched down on the Moon and delivered LuGRE, one of 10 NASA payloads intended to advance lunar science. Soon after landing, LuGRE payload operators at NASA’s Goddard Space Flight Center in Greenbelt, Maryland, began conducting their first science operation on the lunar surface.
Members from NASA and Italian Space Agency watching the Blue Ghost lunar lander touch down on the Moon.
NASA
With the receiver data flowing in, anticipation mounted. Could a Moon-based mission acquire and track signals from two GNSS constellations, GPS and Galileo, and use those signals for navigation on the lunar surface?
Then, at 2 a.m. EST on March 3, it was official: LuGRE acquired and tracked signals on the lunar surface for the first time ever and achieved a navigation fix — approximately 225,000 miles away from Earth.
Now that Blue Ghost is on the Moon, the mission will operate for 14 days providing NASA and the Italian Space Agency the opportunity to collect data in a near-continuous mode, leading to additional GNSS milestones. In addition to this record-setting achievement, LuGRE is the first Italian Space Agency developed hardware on the Moon, a milestone for the organization.
The LuGRE payload also broke GNSS records on its journey to the Moon. On Jan. 21, LuGRE surpassed the highest altitude GNSS signal acquisition ever recorded at 209,900 miles from Earth, a record formerly held by NASA’s Magnetospheric Multiscale Mission. Its altitude record continued to climb as LuGRE reached lunar orbit on Feb. 20 — 243,000 miles from Earth. This means that missions in cislunar space, the area of space between Earth and the Moon, could also rely on GNSS signals for navigation fixes.
Fabled RepairTuber and right to repair crusader Louis Rossmann has shared a new video encapsulating his surprise, and disappointment, that Brother has morphed into an “anti-consumer printer company.” More information about Brother’s embrace of the dark side are shared on Rossmann’s wiki, with the major two issues being new firmware disabling third party toner, and preventing (on color devices) color registration functionality.
Rossmann is clearly perturbed by Brother’s quiet volte-face with regard to aftermarket ink. Above he admits that he used to tell long-suffering HP or Canon printing device owners faces with cartridge DRM issues “Buy a brother laser printer for $100 and all of your woes will be solved.”
Sadly, “Brother is among the rest of them now,” mused the famous RepairTuber. With that, he admitted he would be stumped if asked to recommend a printer today. However, what he has recently seen of Brother makes him determined to keep his current occasionally used output peripheral off the internet and un-updated.
[…]
Rossmann has seen two big issues emerge for Brother printer users with recent firmware updates. Firstly, models that used to work with aftermarket ink, might refuse to work with the same cartridges in place post-update. Brother doesn’t always warn about such updates, so Rossmann says that it is important to keep your printer offline, if possible. Moreover, he reckons it is best to keep your printers offline, and “I highly suggest that you turn off your updates,” in light of these anti-consumer updates.
Another anti-consumer problem Rossmann highlights affects color devices. He cites reports from a Brother MFP user who noticed color calibration didn’t work with aftermarket inks post-update. They used to work, and if the update doesn’t allow the printer to calibrate with this aftermarket ink the cheaper carts become basically unusable.
Making matters worse, and an aspect of this tale which seems particularly dastardly, Rossmann says that older printer firmware is usually removed from websites. This means users can’t roll back when they discover the unwanted new ‘features’ post-update.
The UK Online Safety Act passed into law in 2023, and it properly comes into effect in 2025 with the threats of millions of pounds in fines. For Kevan Davis, the solo British dev behind the text-based zombie MMO Urban Dead, the risks presented by this legislation are too great, and his browser game is set to shut down on March 14, 2025.
“The Online Safety Act comes into force later this month, applying to all social and gaming websites where users interact, and especially those without strong age restrictions,” Davis writes in the announcement. “With the possibility of heavy corporate-sized fines even for solo web projects like this one, I’ve reluctantly concluded that it doesn’t look feasible for Urban Dead to be able to continue operating.”
This legislation is billed as a way of protecting individuals – especially children – from harmful content on social media platforms, requiring content providers to “take robust action against illegal content and activity.” The effort has been widely criticized not just by the major tech companies that it would most directly affect, but by security experts who feel that the proposed efforts would undermine privacy.
Nonetheless, the official timetable for the Online Safety Act is continuing to progress. “So a full 19 years, 8 months and 11 days after its quarantine began, Urban Dead will be shut down,” Davis writes. “No grand finale. No final catastrophe. No helicopter evac. Make your peace or your final stand in whichever part of Malton you called home, and the game will be switched off at noon UTC on 14 March.”
If you want to play Urban Dead ahead of its shutdown later this month, the original website is still online.
