Buildings are responsible for an enormous share of global electricity demand, and the way their air conditioners, lights, and heating systems are scheduled can make the difference between a grid under strain and one running smoothly. For years, engineers have tried to optimize these schedules with evolutionary algorithms and reinforcement learning, but the problem becomes brutally hard when dozens of buildings share a single electrical network and must be coordinated simultaneously. A new study published in Discover Artificial Intelligence proposes a strikingly different approach: instead of searching step by step for the best schedule, a generative artificial intelligence model learns to paint one directly out of pure noise, guided by a map of how the buildings are physically wired together.

The framework, called DMCBO, short for Diffusion-driven Multi-objective Collaborative Optimization for Building Clusters, was developed by Yalan Zheng of Zhengzhou Technical College and Taixiang Yin of North China University of Water Resources and Electric Power. Their central insight is that the joint scheduling of equipment settings and load distribution across an entire cluster of buildings can be treated as a high-dimensional data sample, much like an image. Diffusion models, the same family of generative techniques behind modern text-to-image systems, work by progressively corrupting data with Gaussian noise and then learning to reverse that corruption. The researchers reformulated multi-objective building optimization as exactly this kind of conditional denoising process: starting from random noise, the model strips away noise step by step until a complete, Pareto-optimal collaborative schedule for every piece of equipment in every building emerges.

Technically, the forward diffusion process is a fixed Markov chain that adds tiny amounts of Gaussian noise to real scheduling data over one hundred steps, with the noise coefficient increasing linearly from 0.0001 to 0.02 until the original data becomes indistinguishable from standard Gaussian noise. A neural network is then trained to predict the noise that was added at each step, given the noisy schedule and a conditional encoding vector describing the current situation. Once trained, the model can generate fresh solutions at inference time by sampling pure noise and running the reverse process, refining it over one hundred denoising steps into a schedule tailored to the prevailing weather, occupancy, and grid conditions. Because this generation is a gradient-based learning process rather than an iterative search, it avoids the local optima traps that plague traditional multi-objective evolutionary algorithms and the reward oscillations that destabilize deep reinforcement learning.

What makes the system genuinely cluster-aware is its use of graph neural networks. The researchers model the building cluster as a graph mapped onto a radial distribution microgrid topology, where nodes represent buildings and edges encode physical constraints such as maximum line thermal capacities and transformer limits. A two-layer graph convolutional network passes messages between neighboring buildings, fusing spatial-topological dependencies and network constraints into a single graph embedding. This embedding is concatenated with an adjustable preference weight vector to form the condition that steers the denoising trajectory. In effect, when the model generates a control strategy for one building, it simultaneously perceives the state of its neighbors and the limits of the shared electrical infrastructure, suppressing systemic coordination errors from 0.18 down to 0.06 in the team’s experiments.

The multi-objective aspect is handled through an elegant scalarization trick. Each objective, such as energy consumption, operating cost, or thermal comfort, is normalized to a dimensionless value between zero and one using Min-Max normalization based on historical operational bounds. The normalized objectives are then blended into a single scalar condition via a weight vector whose components sum to one. During training, these weights are sampled from a uniform Dirichlet distribution, exposing the model to the entire space of possible preferences so it learns the distribution of the full Pareto front. At deployment, a decision maker can slide the weight vector like an adjustment knob, instantly generating schedules that emphasize energy saving, comfort, or a balanced compromise, all within the same trained model.

The denoising backbone itself is a U-Net adapted to process one- and two-dimensional building scheduling tensors. Diffusion time steps are embedded through sinusoidal positional encodings, while the graph-derived condition is injected into every residual block via Adaptive Layer Normalization. A bottleneck layer with multi-head self-attention captures long-range dependencies across the entire daily scheduling horizon, and symmetric skip connections preserve high-resolution information during reconstruction. The authors trained the model for 300 epochs on dual NVIDIA Tesla V100 GPUs, and the loss curves dropped from 0.75 to below 0.03 with training and validation curves closely coinciding, indicating no overfitting. As the reverse diffusion step count decreased from 90 to 10 during analysis, the noise-prediction error distribution became sharply concentrated at zero, demonstrating extremely high denoising precision at the end of generation.

Validation was carried out on the open-access Building Data Genome Project 2 dataset, which supplied real hourly weather records, operational schedules, and annual electricity, cooling, and heating load profiles across diverse climate zones. Because that dataset provides metered energy data rather than physical building models, the team used United States Department of Energy Commercial Reference Buildings as templates and calibrated them in EnergyPlus, a high-fidelity thermodynamic simulation platform, to create a digital twin consistent with the real data. All results were benchmarked against a rule-based control strategy with static thermostat setpoints of 25 degrees Celsius in summer and 22 degrees in winter, and every experiment was repeated ten independent times to confirm statistical significance.

The headline numbers are impressive. In high-demand summer conditions, DMCBO achieved an average energy-saving rate of 28.6 percent and cut peak load by 38.5 percent, shaving the afternoon peak from roughly 560 kilowatts down to about 440 kilowatts and saving approximately 142.80 US dollars per day. Cumulative daily power savings exceeded 1,000 kilowatt-hours, compared with 400 kilowatt-hours for a traditional collaborative strategy and just 120 kilowatt-hours without coordination. In winter, peak shaving and valley filling reached about 39 and 42 percent respectively, far above the 22 and 25 percent of conventional methods. When the solution sets were projected into objective space, DMCBO dominated the baselines: it reached a hypervolume indicator of 0.95 within 12,000 function evaluations, versus 0.85 for NSGA-II and 0.70 for MOPSO, while keeping operating costs between 140 and 160 dollars against more than 210 dollars for deep reinforcement learning and 260 to 300 dollars for a GAN-based generative approach.

Robustness and scalability proved equally compelling. Under injected stochastic disturbances mimicking sudden weather changes and occupancy swings, the framework confined power fluctuations to a narrow band of plus or minus 5 kilowatts, whereas the deep reinforcement learning baseline swung between minus 15 and plus 20 kilowatts. Scaling from 5 to 50 buildings, the global energy-saving rate actually rose from 28.5 to 31.2 percent, because larger clusters unlock more load-complementary opportunities that the graph encoder can safely exploit within encoded grid boundaries. Computation time grew to 9.8 seconds at the 50-building scale, but that remains comfortably within the 15-minute control horizon used by real building management systems, and the hypervolume index slipped only slightly to 0.88. Ablation experiments confirmed that both the graph neural network module and the choice of 100 diffusion steps, which yields a 50-millisecond inference latency, were essential to this balance of speed, accuracy, and stability.

The authors are candid about limitations. The framework has so far been validated only in simulation, and EnergyPlus simplifies sub-minute mechanical actuation latencies that real HVAC hardware would introduce; they propose cascading PID loops and predictive safety margins to absorb those delays in practice. Data quality, generalization to residential buildings and extreme climates, the computational cost of scaling to city-sized networks, and the black-box nature of the generative process all remain open challenges, with explainable AI and transfer learning flagged as future work. Still, the architecture is designed to slot into standard building management systems as a supervisory layer, transmitting setpoints over protocols such as BACnet or Modbus. If the simulation gains survive contact with physical buildings, the idea of generating optimal energy schedules from noise, guided by a graph of the grid itself, could become a powerful new tool in the push toward decarbonized cities.

Subject of Research: Conditional diffusion models with graph neural networks for multi-objective energy optimization in building clusters

Article Title: Diffusion model-driven multi-objective collaborative optimization for building energy management using graph neural networks

Article References: Zheng, Y., & Yin, T. (2026). Diffusion model-driven multi-objective collaborative optimization for building energy management using graph neural networks. Discover Artificial Intelligence, 6(1), Article 1383. https://doi.org/10.1007/s44163-026-02140-z

Image Credits: AI Generated

DOI: 10.1007/s44163-026-02140-z

Keywords: diffusion models, graph neural networks, building energy management, multi-objective optimization, EnergyPlus, smart buildings, Pareto optimization, deep learning, energy efficiency, HVAC control, microgrids, generative AI

TCP, the data transport protocol upon which pretty much the entire web and most of cloud computing is built, is ill-suited for emerging AI workloads, a retired Stanford University professor argues. To solve the problem, he's promoting a new protocol called Homa. “TCP, for all the amazing things it has done, is not a good match for datacenters,” said John Ousterhout, a professor emeritus of computer science at Stanford University, in a recent talk at the AI Engineer World’s Fair. Shedding TCP sounds like an immense task, given the global reliance on the protocol. But adding Homa into a network is fairly simple, Ousterhout told The Register. Compile Homa from its GitHub source, then install the module into the Linux kernels on the clients and servers. No reboot required. “Homa works side by side with TCP, so you can gradually move applications from TCP to Homa,” he wrote. Running Homa even makes the remaining TCP applications run faster. Old wine, new skin Homa is a clean-slate rethink of how networks should manage traffic congestion, Ousterhout said. Work on the protocol began as a PhD dissertation first published in 2019 by Behnam Montazeri, now a Google staff engineer. Now that Ousterhout has retired from teaching, he has taken on the task of propagating Homa as his “life’s mission,” he said. What makes Homa different from TCP is primarily that it is message-based, rather than stream-based. Much like the remote procedure call (RPC), Homa message lengths are explicitly defined. Unlike TCP, Homa designates the receiver to manage congestion control. The first packet the receiver gets has information on how much data is incoming. It can then explicitly schedule when packets should be sent. In doing so, it prioritizes shorter messages over longer ones using a shortest-remaining-processing-time (SRPT) algorithm. This approach cuts the latency of shorter messages by an order of magnitude, Ousterhout said. The 99th percentile (p99) of latency for shorter messages is 92 microseconds for Homa, which is 13 times faster than the 1.2 milliseconds p99 for TCP (based on packets swimming through a 100 Gbps network at 80% utilization). Even on the longest messages, Homa is better by a factor of two, Ousterhout said. A long list of other tasks where TCP falls short Currently, Ousterhout is drafting an IETF standardization document of the protocol, as well as working through the process of upstreaming Homa into the Linux kernel. In March, the protocol was backported to Red Hat Enterprise Linux versions 8 and 9.5. He is also helping large companies investigate Homa’s applicability – he is currently working with one large financial services company on a prototype. Not that everyone is on board with tossing TCP over a few latency issues. Prominent network architect Ivan Pepelnjak wrote a scathing position paper in 2023 about Homa, questioning Ousterhout’s performance characterizations of TCP and critiquing Homa as a solution looking for a problem. To be fair, the AI community is not the only ecosystem frustrated by the dowdy TCP. In the high-performance database community, DPDK (Data Plane Development Kit) is being used to bypass the TCP stack for faster querying. Storage area networks turned to NVMe-oF (NVMe over Fabrics) to speed access to solid-state drives over network fabrics, using transports including RDMA, Fibre Channel, and TCP. For the Web, Google devised QUIC – which became the basis for HTTP/3 – to bypass TCP’s head-of-line blocking and enable browsers to download more assets simultaneously. Also, the high-frequency trading and multi-player gaming communities have felt the pinch of TCP sluggishness. Specialized RDMA fabrics and Amazon Web Services’ Scalable Reliable Datagram have also tackled the issue of TCP latency. Top-of-rack switches have also gotten smarter at managing congestion, setting queue thresholds and marking packets with early congestion notifications. Control lag is real Vint Cerf and his fellow beardies created TCP to bring order to the unruly hordes of message packets across networks, giving them proper flow control, guaranteed delivery, connection handshakes and congestion control. Congestion control means avoiding overload in the network path, including switches and routers, while separate flow-control mechanisms keep senders from overwhelming receivers. TCP’s data model is built on byte streams, a continuous flow of data packets with no differentiation. Messages are serialized as a single byte stream with no priority. For the receiver, longer sets of byte streams are indistinguishable from shorter ones. A server deluged with traffic can send alerts to senders to slow input, but it has limited visibility over how much traffic is still coming in. The sender itself, which regulates its output depending on the timeliness of acknowledgments sent back from the receiver, has to guess how much to slow its roll. For regular internet traffic or large-scale transfers within a datacenter, modest latency increases may be tolerable. But for latency-sensitive AI workloads, even delays measured in milliseconds can sting. Think of the GPUs The frontier labs driving the development of large language models (LLMs) have always required top-notch network performance for chores such as weight gradients, model weights, KV cache entries, and checkpoints. However, large data transfers must increasingly share bandwidth with short bursts of traffic from agents and control tasks such as metadata coordination and cache lookups. “For these workloads, what really matters is latency,” Ousterhout said. Even a millisecond of latency causes an expensive GPU to go idle. “Legacy protocols are poorly suited for this environment,” Ousterhout said. So has Homa finally found its problem to solve? Or was it just ahead of its time all along? For now anyway, TCP remains the champ.®

BT Email customers say they have been bombarded with hundreds – and in one case more than 1,000 – unsolicited password reset messages, leaving the telco investigating what is causing the deluge. The reports began appearing on BT's community forums over the weekend, with customers describing sudden bursts of PIN messages arriving within minutes despite them making no attempt to reset their passwords. One customer said they received between 50 and 70 PIN texts "in the space [of] a few minutes," while a second reported more than 100. A third said the number had passed 500, and another claimed to have received more than 1,000. One BT customer who contacted The Register separately said they had received around 300 password reset emails over the previous 24 hours, typically arriving in bursts of around 50 within a minute before stopping for several hours. BT has acknowledged the problem but has yet to explain what is behind it. "We are aware that some customers have received a large number of password reset pin messages and we are actively investigating the cause of this," a BT moderator said on the company's community forum. "If you have received multiple messages like this, please ignore them and remain vigilant for any unusual activity with further messages or unexpected calls." BT added that customers' email accounts are secure and that those receiving the messages do not need to take any action. At least one customer, however, claims someone accessed their account during the PIN barrage. The user said they lost access to both their email and BT ID overnight, but managed to request a PIN before whoever was accessing the account could change the telephone number attached to it. That account has not been independently verified, and it isn't clear whether the apparent takeover was connected to the flood of PIN messages. The cause of the wider problem remains a mystery. It isn’t yet clear whether it’s the result of someone deliberately hammering a password recovery mechanism, a fault within BT's systems, or something else entirely. The Register has asked BT how many customers are affected, whether the messages are being generated by external password-reset attempts, and whether it has found any evidence of malicious activity. We've also asked the telco what rate limiting it applies to password reset requests, given reports of hundreds of PINs arriving within minutes, and whether both email and SMS messages are affected. BT says it's investigating. In the meantime, some customers are getting enough PINs to start their own lottery. ®

The UK's Advanced Research and Invention Agency (ARIA) is funding projects aimed at delivering connectivity using high-flying aircraft, including technology to beam power from the ground to keep them in the air. Britain's science and technology body, inspired by America's DARPA but on a more modest budget, says it is backing 18 projects to develop aircraft capable of operating reliably and cost-effectively in the stratosphere, as part of a program known as Enduring Atmospheric Platforms. Success will be measured by whether any aircraft can continuously supply 300 W of power to a communications payload for an entire week, while holding station above the UK. The intent is to create an alternative to orbital satellites for providing connectivity to underserved parts of the UK and elsewhere in the world. These are known as high-altitude pseudo-satellites (HAPS). The agency says that satellites have been the default way to reach users or communities that are not well served by terrestrial networks, but their distance and orbits impose physical limits on what they can deliver. ARIA is allocating £70 million ($94 million) in funding over three and a half years for the projects, which will tackle the power and reliability challenges of sustained operations above the UK. The projects are split into three technical areas, with TA1 set to cover enabling technologies, TA2 comprising system integration and testing, and TA3 focused on deployment and communications. ARIA highlighted a project called Carousel from aerospace startup Menapia. This plans to produce a constellation of high-altitude multi-rotor aircraft, capable of routine operations at altitudes up to 20 km (12 miles), with the intention of forming a persistent "canopy" over the UK. Another is Enduring Drone Networks, being developed by VFP Aerospace, which is aiming for persistent presence via a relay team of units that will cycle between their service altitude and ground stations for recharging. It says it is targeting a production cost of £50,000 ($67,000) per drone. In the enabling technologies category, a firm called Hypanode Ltd is working on a fuel cell power system to deliver 20 times more energy than current battery technology. Scalable Laser Ltd is developing laser-based power beaming technology, pairing high-power laser diodes with advanced photovoltaic receivers, while Space Solar Engineering Ltd is looking at radio frequency power beaming to deliver continuous power to a HAPS aircraft. A more exotic-sounding technology is Stratospheric Navigation and Gravity (STRAT-NAV) from the University of Bath. This seeks to extend the endurance of HAPS craft by allowing them to predict and make use of atmospheric gravity waves – caused when air is forced upward by weather fronts or hills, and gravity pulls it back down, creating a ripple. "This research expands the UK's leadership in high-altitude platforms to become the place where this industry is designed, built, and scaled," says Rico Chandra, ARIA's program director for Enduring Atmospheric Platforms. "Getting there means backing bold ideas, from fixed-wing solar aircraft to designs nobody predicted, including aircraft that fly on spinning wings instead of propellers." ARIA funds teams of scientists and engineers to pursue cutting-edge research. It is a non-departmental public body sponsored by the Department for Business, Innovation, Science and Trade (BIST). It was until recently chaired by entrepreneur Matt Clifford, who stepped down after taking up a role with US AI firm Anthropic. The agency was also controversially spared being asked to make savings leading up to the UK government's Spending Review last year. ®

One of the most popular explanations of human behavior has been that somewhere beneath our rational mind lurks an ancient “lizard brain”—a primitive evolutionary holdover responsible for instinct, emotion, fear, and aggression.

There is just one problem. Neuroscientists have long known that the lizard brain story is wrong. Humans did not evolve a sophisticated new brain by simply stacking it on top of an older reptilian one.

But a new study suggests the enduring lizard brain myth may have inadvertently pointed to something more interesting. Mammalian brains do appear to be organized around two broad computational systems—but not an ancient reptilian brain located beneath a newer, more sophisticated one. Instead, the divide appears to reflect two fundamentally different ways of organizing and processing information.

Published in Science Advances, the research combines anatomical measurements from 182 mammalian species with experiments using artificial neural networks. The researchers found a striking evolutionary trade-off between the neocortex and a collection of structures associated with smell, memory, and the limbic system.

Instead of representing “new” and “old” brains, the researchers say these regions may have evolved different wiring styles optimized for solving different kinds of computational problems.

“Rather than an ‘old’ brain and a ‘new’ brain, our results suggest two systems wired for different kinds of computation,” lead author Dr. Nabil Imam, a researcher at the Georgia Institute of Technology, told The Debrief. “The neocortex is wired to preserve spatial relationships—for example, neighboring points in the visual world are analyzed by neighboring parts of the cortex. The limbic system is more diffusely connected and supports holistic associations across different pieces of information.”

“So, the division between the neocortex and limbic system is about how the two systems are wired,” Dr. Imam added.

This distinction offers a very different picture from the famous lizard brain story.

The lizard brain concept grew from the so-called triune brain theory, which portrays the human brain as having evolved in distinct layers. A primitive “lizard brain” handling basic instincts, a mammalian limbic system producing emotion, and, finally, a newer neocortex responsible for higher thought.

The problem is that neuroscience has long since overturned that evolutionary story. Vertebrate brains did not evolve by progressively stacking newer brain regions on top of older, more primitive ones. Instead, vertebrates share essentially the same broad organizational plan, with existing regions changing in size, connectivity, and function over evolutionary time.

The new study suggests, however, that the mammalian brain may be divided very differently—not by evolutionary age, but by how different neural systems are wired to process information.

Across 182 species from 10 taxonomic groups, animals with an unusually large olfactory system tended to have a smaller-than-expected neocortex. Animals with an expanded neocortex tended to show the opposite pattern.

The nine-banded armadillo provides a particularly dramatic example. Armadillos are largely nocturnal and depend heavily on smell while foraging. As researchers note, the armadillo’s olfactory system was approximately 1.5 times larger than expected for its overall brain size. Its hippocampus—a region central to memory and spatial processing—was about twice its expected size.

Its neocortex, meanwhile, was reduced by a factor of 2.8. Primates such as squirrel monkeys sit closer to the other end of the spectrum. They rely heavily on vision and devote a large portion of their expanded neocortex to processing visual information.

At first glance, that could look like evolution trading smell for sight. But the researchers noticed something more intriguing. The hippocampus grew and shrank alongside the olfactory system, even though memory is obviously not another form of smell. Other structures traditionally grouped into the limbic system, including the amygdala and septum, also tended to change together.

That suggested the important difference might not be what these regions process, but how they are wired to process it.

Two Very Different Ways to Build a Brain

Vision offers a relatively straightforward example. Neighboring points in the visual world are generally processed through neighboring areas of the visual system. Touch operates similarly. Locations beside one another on your body retain spatial relationships as the nervous system processes them. Hearing also uses orderly mappings, including those based on sound frequency.

The result is what neuroscientists call “spatiotopic” organization. In simple terms, the brain preserves relationships between incoming information by arranging it into orderly maps.

However, smell works differently. Odors are represented through combinations of activity distributed across networks rather than being laid out in the same neat spatial fashion.

The researchers suspected that this difference might help explain the anatomical trade-off they had identified across mammals. To test the idea, they turned to artificial neural networks trained to handle vision, touch, hearing, and smell.

They then mapped the networks’ internal models onto artificial two-dimensional surfaces resembling sheets of cortex.

Results showed that networks optimized for vision, touch, and hearing produced smooth, highly ordered maps. On a scale in which 1 represented strong spatial order, the visual network scored 0.90, touch scored 0.86, and hearing scored 0.89.

Yet, the smell network scored just 0.11. Rather than producing a smooth map, information was scattered across a fractured, distributed representation. The researchers even found that imposing localized connectivity on the olfactory model harmed its ability to perform its task.

Researchers then examined memory. Using an artificial network designed to reproduce some relational computations associated with the hippocampus and entorhinal cortex, researchers again saw a fractured, distributed representation resembling the olfactory system rather than vision, hearing or touch.

For Dr. Imam, one of the most surprising results was that artificial networks arrived at an organization resembling real brains despite learning in profoundly different ways.

“Artificial networks are trained by an algorithm that propagates errors through the network, whereas brains are shaped by evolution and through localized changes in synapses,” Imam explained. “The fact that both nevertheless arrive at similar organization suggests that the structure of the information itself—whether visual, auditory, tactile, or olfactory—determines what kind of wiring works best.”

No “Lizard Brain,” But Evolution May Be Trading One Kind of Brainpower for Another

Researchers next wanted to know whether competition between these two wiring styles could reproduce the anatomical patterns seen across real mammals.

They created an evolutionary simulation containing five artificial networks. Vision, hearing, and touch occupied one computational domain based on localized, spatial organization. Smell and hippocampal memory occupied another based on distributed connectivity.

Then an evolutionary algorithm redistributed computational resources between them.

When selection favored vision, resources moved toward the spatially organized networks. When selection favored smell, the distributed networks expanded.

But something interesting occurred to the simulated hippocampal network. Even though researchers weren’t directly selecting for memory, the hippocampal network grew along with the olfactory network because both shared the same broad computational architecture. As resources shifted toward the other system, both contracted.

That closely resembled the pattern found across real mammalian brains.

“It suggests that evolution may not be selecting individual brain regions one at a time, but rather the functions produced by whole patterns of wiring,” Dr. Imam explained. “Because regions that share similar wiring tend to grow or shrink together, selection for one kind of function comes at the expense of another, given that the system must operate with limited energy and space.”

That does not mean an animal with a larger neocortex is simply more intelligent than one with a larger limbic system. Nor does the distributed system represent a primitive emotional brain fighting against a rational one.

Instead, the two architectures appear suited to different computational problems. Evolution may have repeatedly adjusted how much neural real estate mammals devote to each.

Nevertheless, researchers caution that their models are intentionally simplified. Anatomical measurements came from several datasets; some taxonomic groups are better represented than others, and artificial neural networks are not replicas of biological brains.

The evolutionary model is intended to demonstrate that a relatively simple developmental mechanism could produce the observed trade-off, not to reconstruct exactly how mammalian brains evolved.

Still, the research raises another interesting possibility extending beyond the demise of the “lizard brain.” Our brains may arrive in the world with considerably more computational structure already built in than the familiar idea of a blank slate implies.

“The brain may be much less of a blank slate than we often imagine,” Dr. Imam told The Debrief. “Evolution and development build useful assumptions into its wiring before experience-driven learning.”

It is also another example of something scientists are increasingly encountering across very different areas of biology: evolution can produce remarkably sophisticated structures and systems that human engineers are just starting to understand, much less reproduce.

In a recent study covered by The Debrief, researchers discovered that cable bacteria construct microscopic electrical pathways from nickel-rich nanoribbons arranged remarkably like braided electrical wires. The naturally grown structures may achieve extraordinary conductivity while remaining flexible, properties that researchers are now interested in replicating for bio-based electronics.

The mammalian brain represents an enormously more complicated example, but the underlying lesson may be similar. Evolution does not begin with a blank slate each generation. It can build useful solutions into biological architecture itself, leaving subsequent learning along with adaptation to operate within structures refined over immense spans of evolutionary time.

That could also help explain one of the most striking differences between biological intelligence and today’s artificial intelligence. Modern AI systems can require enormous datasets to acquire abilities that biological brains learn from comparatively limited experience.

“That built-in structure may explain why brains can learn efficiently from relatively little experience, whereas most artificial networks require enormous datasets to learn useful functions,” Imam said. “The idea has deep roots in philosophy of mind, but only recently have neuroscience and computer science begun to provide concrete demonstrations of how such built-in structure can aid function.”

The recent study, “Dual computational systems in the development and evolution of mammalian brains,” appeared in Science Advances.

Tim McMillan is a retired law enforcement executive, investigative reporter and co-founder of The Debrief. His writing typically focuses on defense, national security, the Intelligence Community and topics related to psychology. You can follow Tim on Twitter: @LtTimMcMillan.  Tim can be reached by email: tim@thedebrief.org or through encrypted email: LtTimMcMillan@protonmail.com 

Virgin Media is ditching its email services and offering customers a window in which to download their data and move to another email provider. The UK's second-biggest broadband provider is closing its own email service and offering users the option of transferring their addresses and mailboxes to Junara, a service operated by Australian email provider Atmail. Customers who want to retain their Virgin Media email address will be invited to transfer to Junara. The first year will be free for current Virgin Media customers, after which they will have to pay to continue using the service. Virgin Media email users will be contacted directly and given 45 days to sign up with Junara, save their data and move to another provider, or allow their account to close. The change affects all addresses ending in @ntlworld.com, @blueyonder.co.uk, @virgin.net, and @virginmedia.com. Virgin Media stopped issuing new email addresses to broadband customers in 2022, citing the growing popularity of dedicated services such as Gmail and Outlook. A spokesperson for the company told The Register: "As we focus and prioritize our investments and resource on ensuring our customers have the best connectivity experience, we have taken the decision to close the remaining Virgin Media email accounts. We're transferring our email service to Junara, a specialist cloud-based email provider owned by Atmail, giving users a clear route to keep their existing Virgin Media email address if they choose to." "We are writing directly to all impacted customers to clearly explain the changes and will provide a 45-day window to either sign up with Junara, move to an alternative email provider, or close their account. To support users through this transition, all current Virgin Media customers wishing to move to Junara will receive their first year of service free of charge, with additional support available for those who need it." Announcing the change in a blog post, Virgin Media O2 chief operating officer Alan Stott said most people now prefer dedicated email providers to accounts supplied by telecoms operators. "By transferring these email accounts to a specialist provider, we can focus our attention and investment on what we're ultimately here to do – provide fast and reliable broadband, mobile, landline and TV services, and give our customers the best possible experience." Virgin Media has not said how many active email accounts will be affected, but their users will have just 45 days to decide whether keeping their old address is worth signing up for a separate service. ®

A prominent US senator is asking the National Security Agency to provide guidance to the general public on best practices for using virtual private networks to secure their communications from spying by foreign adversaries.

VPNs funnel all of a user’s Internet traffic through an encrypted connection to a remote server. The design provides strong assurances that no one between the user and the server can read the encrypted contents. VPNs also allow users to hide their IP addresses from the destination servers they communicate with. While US agencies have previously recommended use of VPNs, none have given recommendations on which ones provide adequate protection.

It's all in the nuances

There are a host of limitations that can undo many of the protections users may think their VPN provides them. For instance, the encrypted tunnel often terminates once a single server decrypts the traffic and sends it on to its final destination. That means the decrypted traffic or the sending and destination IP addresses may be available for snooping by rogue employees or attackers who hack the server. VPNs also don’t encrypt certain types of metadata, such as time stamps, allowing nation-states to build profiles that can be useful in intelligence gathering.

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As online services get better at blocking malicious traffic, the attackers and scammers behind them have been forced to find new ways to reach their targets. The alternative of choice is now what are known as residential proxy networks. These systems funnel millions of home Internet connections into a unified network, and the proxy operators allow attackers to route their malicious traffic through these connections for a fee. The online services see only IP addresses with good reputations and geolocations that don’t stand out.

More often than not, the home users have no idea that their connections are being used to facilitate crime and occasionally even nation-state attacks. Users who do know often don’t care much. In exchange for leasing out part of their unlimited bandwidth to others, many get free movie and TV show streaming. Several less tech-savvy people I know who own such digital media players have told me, after I explain how the media players piggyback off their connections, that the bonanza of content is worth it. They find the tangible benefits outweigh the abstract harm they pose.

Infecting already compromised devices

Research published Monday brings the threat into much clearer view. Security firm Plume cataloged a vast ecosystem of malware that preys squarely on users of SuperBox, just one of many media players offering pirated content. These malicious apps can be surreptitiously installed by remote attackers even when the devices are positioned behind a router. While Monday’s deep-dive analysis focused exclusively on SuperBox, Plume warned that dozens of similar streaming devices pose precisely the same threat.

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Last month I sat in a networking lab with AWS VP of Global Network Engineering Matt Rehder and cracked a joke about cage nuts cutting your hands to ribbons. I wasn't prepared for the blank stare I got in response, but I really should have been. Mind you, not because the joke wasn't funny (my jokes are hilarious), but rather because the world the joke was referencing no longer exists for them. Racks show up as assembled units, and apparently nobody screws hardware into anything in an AWS datacenter facility these days. It was a peek behind a curtain into a world that powers everything we do in cloud, but that remarkably few of us know exists. My Reg colleague Thomas Claburn toured the lab previously and gave us a deep dive into AWS's paper on this. In summary, "a flat, single-tier network wired in a deliberately near-random pattern leads to a way more resilient network that costs far less to run" and now you're up to speed. The part that I felt didn't get enough attention (and is why I invited myself to tour an AWS facility, much to AWS's surprise) is the economic part and how it impacts AWS customers. In short, their new networking approach can be up to 40 percent more energy efficient, and it's the default for most new datacenter builds (and dear reader, they are building a lot of those these days), and it's been completely invisible both inside and outside of the walls of the world's largest bookstore. The savings and cost efficiencies are real — so where do they go? Cost efficiencies abound Seventeen years ago, Amazon SVP James Hamilton got on stage and pointed out [PDF] that network vendors ran businesses whose margins resembled those of mainframe vendors, who themselves in turn resembled starving pigs at a trough (colorful metaphor mine, but also... not wrong). His big issue with this distilled down to "they're in my way," and he plus his team set out to do something about it. It turns out that "what they did about it" was nothing less than rebuilding the entire networking stack themselves atop commodity hardware. This brings us to a few years ago. Their networking cost efficiencies were already far lower than they would have been running atop traditional networking vendors, and then their Resilient Network Graph shufflebox play took another axe to the cost of networking. So... where have those savings gone over these past few years? I asked point blank whether it was fair to say that they kept the margin improvement rather than passing it back to customers. Their answer was unequivocal: "From a cost perspective? Effectively, yes." AWS cloud economics It's easy to see that answer as damning, but I humbly suggest that if that's your reaction, you haven't been paying attention to broader industry trends these last few years. Unlike its competitors, AWS has not raised prices on existing SKUs. (Yes, the cost of GPU capacity blocks has been raised on a quarterly basis, but that's apparently how those were designed to work, much like a slow version of Spot Instances. And yes, they started charging per public IPv4 address a couple of years ago.) You can go out and spin up the same instance with 64GB of RAM that you could in 2020 and pay the same price today; that's not even increasing a price to keep up with inflation! And while there's a 9 percent increase to go from a Graviton4-based c8g.2xlarge to its equivalent c9g.2xlarge Graviton5 instance, nothing is making you upgrade. Frankly, given the component cost hikes, I'm more than a little astonished that they were able to hold the increase to 9 percent. Further, despite the madness-inducing level of granularity you see in an AWS bill with its millions of SKUs, it's worth noting that each SKU itself obscures dizzying levels of complexity. An EC2 instance charges you per hour (yes, it's metered by the second; do not email me), but that one charge covers the CPU, the RAM, the backplane, the power, the building's physical security, the IAM security bits that keep it from resembling a public computer/something from Microsoft Azure, the employees it takes to build and run these systems, and a stupendous amount of networking magic. A sea change in approach One of those aspects of networking magic is that while it can be usuriously expensive to move traffic between Availability Zones (in major regions each gigabyte has a list price of a penny in and a penny out, so "two cents per gigabyte," which adds up), moving data inside of an AZ remains free. That's impressive when you start to realize how many different datacenter facilities can comprise a single AZ. It's damned impressive when you realize that AZs are expanding, data volumes are increasing, and that expansion comes with costs that thus far AWS has chosen to bear rather than pass on. It's significantly more expensive to move data out of AWS. Their now-defunct Snowball family of devices let you ship data back and forth to AWS. Sending one in cost a set fee, while sending one out cost that fee plus a per-GB charge. Annoying, right? That changed over the last year with the advent of AWS Interconnect - multicloud, which charges you nothing per GB, just an hourly port charge. There's a free tier of one 500 Mbps port per provider, which reduces to zero the AWS-side cost of sending that traffic to GCP, Oracle, and soon Azure. For comparison's sake, it'd be roughly $12,000 to send a month's saturation of that port across the open internet. Stated more plainly, this has never been done before on the AWS side, and it's fascinating. While it's not the primary area of focus for the folks I talked to, I nonetheless asked them about it for an on-the-record answer: "We know customers do not like rate-based network charges because it’s hard to predict their cost, which is why we are moving towards flat-rate pricing for new network products." Well slap me naked and hide my clothes; I'd be less surprised if Matt Garman gave his next re:Invent keynote in iambic pentameter. This bears watching; it's more interesting to me that it comes at a time when prices are rising instead of falling. How hard can it be? Very hard The problem is that a lot of what AWS does is invisible. For example, why am I telling you this instead of AWS? AWS concedes that they're generally bad at telling their own story, but they clearly want to tell it. Historically, they've punted to customers to tell their own stories, on the belief that the benefit will accrue to them. Here's my favorite example: the hard part of a near-random network isn't the cabling so much as the routing. Every protocol you've heard of (BGP, OSPF, a few Cisco-specific protocols that nobody sane uses, etc.) computes shortest paths, and "shortest path" stops meaning much when there are roughly thousands of equivalent routes between any two points. AWS solved that with a protocol called SIDR (Scalable Intent-Driven Routing, pronounced "cider," like the CIDR method for allocating IP addresses because these people are malevolent at naming things) that runs the control plane, while Spraypoint picks up the actual forwarding path. They presented SIDR publicly at re:Invent in 2023, then covered it again at the "Monday Night Live" re:Invent keynote in 2024. Then they published the RNG paper, which doesn't mention SIDR at all. As best I can tell, nobody outside the company has ever connected the protocol to the network it makes possible. I had to ask just in case I was missing something. I'm right. It isn't a secret! They just never got around to mentioning how important it was to making the whole thing go. Unfortunately, their lack of storytelling prowess about these things isn't working for them. The perception runs the other way: the market believes that the neoclouds and the Nvidia reference designs are better. They aren't. You can build a neocloud without knowing much about networking, and some outfits clearly have. A lot of datacenter networks are run by absolute clowns. I know this; I used to be one of said clowns before I got religion / discovered I could pay a cloud provider to make this stuff Matt Rehder's problem. AWS has gotten so good at making network arcana invisible that we don't really stop and think about just how wild it is that you can get damned near full line-rate between any two points in AWS and it just works. In the datacenters you or I build, you get to worry about fun things like "the switch at the top of the rack can only push so much traffic, so not every node can talk at full speed all the time." I have never encountered a real-world scenario of that being a concern in AWS. As a result, when folks set out to build their own datacenters, they don't know what they don't know after a generation of that complexity being hidden away from them, and they approach it with a sense of "how hard could it be?" It is extremely hard, and I have little confidence that the neoclouds spinning up new DC facilities overnight are paying attention to this. I asked Rehder directly whether the "ML datacenter facilities" AWS was launching in places like Mississippi were taking shortcuts since GPU workloads might have different requirements. He looked at me as if I were nuts; every datacenter they build is to the same spec. But customers won't care about that until right after they really should have cared about that; I have faith that a datacenter failure will be sufficiently public, embarrassing, and impactful so as to remind them. The tree of uptime must be periodically refreshed with the blood of massive outages. The humble mumble The folks I spoke to at AWS about this have built something that most of their own customers will never know exists, and they seem generally untroubled by that fact. I found that more admirable than I would have expected to; it's the very definition of thankless work, and AWS shines here. The reason the work is invisible is simply because it succeeds. And they're so humble about it! They politely chuckled at my joke about cage nuts once they got the reference, and I politely chuckled at their joke about how each year's switch is painted the Pantone "Color of the Year," which it turns out was in fact not even slightly a joke. AWS gets a lot wrong. They have ridiculous marketing campaigns, they build five services that do mostly the same thing and then name them like malevolent toddlers, and they've never found a partner they couldn't find a way to compete with. But when it comes to the "chop wood, carry water" type of work that makes the entire cloud possible, the kind that would put most of a keynote audience to sleep, they're the finest in the world. They're just bad at telling the world about it. ®

Police in Mauritius are conducting a criminal investigation into possible forgery related to the annulled June 2025 board election staged by the African Network Information Centre (AFRINIC). AFRINIC is the regional internet registry (RIR) for 54 countries in Africa and the Indian Ocean region. In recent years it has experienced governance and operational problems and been embroiled in a complex set of interlocking legal disputes with one of its members, Cloud Innovation, regarding AFRINIC’s powers to terminate users who do not follow its rules for using IP addresses. The disputes with Cloud Innovation saw AFRINIC unable to convene a board for several years. Courts in Mauritius placed the registry in receivership. The receiver eventually brought the registry into a state that made it possible to stage a board election in June 2025. AFRINIC offered members the chance to vote online, by attending a day of in-person voting in Mauritius, or by appointing a proxy to vote for them at the in-person voting session. During that in-person voting session, the Nomination Committee that oversaw the election became concerned about the voting process and called off the election. AFRINIC’s receiver later annulled the vote, which was re-run under different rules later in the year. AFRINIC has never commented on the reasons for the annulment. The Register sought comment from the four UK-based barristers who comprised the Nomination Committee. None were willing to answer our questions. AFRINIC’s receiver has also not responded to our request for comment. After the annulment, South Africa’s Internet Service Providers' Association (ISPA) made two claims about irregularities at the election: “A duly authorised representative of a resource holder attempting to vote, only to be informed that another person had already submitted a vote on their behalf thanks to a Power of Attorney, which that resource holder had not provided to any third party." "A representative of a resource holder, learning that a Power of Attorney had been submitted on their behalf, only to find that that particular Power of Attorney (the existence of which had already been recorded by AFRINIC staff) had been mysteriously removed from the record by the time a copy was requested.” Mauritius Police this week confirmed to The Register that it is investigating the matter as a possible forgery case. “Two cases related to AFRINIC elections in 2025 are still under investigation at the level of the Central CID of the Mauritius Police Force. Both are alleged Forgery cases,” a spokesperson told The Register. Mauritius Police describes its Central Investigation Division, or Central CID, as “a specialized unit … which deals with sensitive cases and cases involving larger public interest. It deals with all the cases of bribery, fraud and homicides.” And also internet governance election scandals, it seems. AFRINIC revived, revisiting past controversies The court cases that indirectly led to AFRINIC’s annulled election were related to the registry’s powers to terminate users who do not follow its rules. Termination means losing the right to continue using IP addresses allocated by AFRINIC. AFRINIC on Tuesday published an update on the community consultation process it has run to determine members’ interest in, and attitude to, proposed bylaw changes. One proposed change would see AFRINIC add a specific dispute resolution clause to its constitution. Such a clause could perhaps have avoided the lengthy legal battles that the registry continues to fight, but the organization’s Bylaws Review Committee will not recommend adoption of the clause. The Committee also commented on the AFRINIC board’s power to terminate a member, and said it is “considering various options aimed at further strengthening the existing legal safeguards applicable to the exercise of such power.” AFRINIC therefore looks to be trying to strengthen its ability to terminate members, a power that rightly or wrongly has been the source of its many recent travails. The registry also had happier news this week after naming its next CEO: South African lawyer Mike Silber, whose CV includes serving on the board of ICANN and many senior roles at African telcos and tech companies. Silber will take up the position on January 1, 2027, and will clearly have some contentious issues on his desk from day one. ®

ICANN is poring through over 1,600 applications for new global top-level domains (GTLDs) and will reveal which ones it thinks are valid in a few weeks – but hundreds of names applicants hope to secure have already appeared online. GTLDs are the last part of an internet address. The most common and well-known are .com, .net, and .org. In the early 2000s, ICANN allowed a few more GTLDs, and in 2012 ran an open application process that allowed anyone to pay for the privilege of operating their own GTLD. That program saw over 1,900 applications and led to the creation of over 1,200 new GTLDs. Tech companies, including Microsoft, Cisco, and Oracle, scored their own GTLDs. One registry applied for, and won, .sucks – one of many novelty domains that ICANN approved. As The Register reported in May, ICANN this year opened a round of applications for GTLDs and recently announced that it received over 1,600 submissions. The internet governance organization plans a “Reveal Day” in September or October, on which it will publish a list of all applications that have passed administrative checks. Some applicants have jumped the gun and published the list of GTLDs they applied for. The Link Freedom Group has applied for 316 GTLDs, listed here. Among the strings it hopes to turn into GTLDs are .slop, .therapy, and .hype. The outfit also hopes to own .con, .token, and .moon, plus AI-related strings including “agentic” and “AGI”. An unofficial ICANN community Wiki, which The Register understands some applicants have used to share the GTLDs they desire, offers the chance to filter GTLDs in the 2026 application process. It lists the names sought by Link Freedom Group plus hundreds more. Predictably enough, many are strings related to cryptocurrencies, datacenters, AI, or locations in China. ICANN charged an evaluation fee of $227,000 for each submission, and the cost can be higher if a desired string needs extra review due to being considered a highly risky GTLD. It can take months or years for new GTLDs to go live after Reveal Day, because ICANN performs additional reviews and operates a 104-day window in which it considers objections. If you want a domain using any of the GTLDs mentioned above, it’s unlikely registries will be ready to sell you one before late 2027 – and likely rather later than that. ®

Bentham Science Launches Two New Journals to Accelerate Research in Wireless Communications and Engineering

Bentham Science Publishers has announced the launch of two new peer-reviewed journals designed to capture the rapid transformation of modern technology: Wireless and Communication Letters and Current Engineering Letters and Reviews. Both publications are now open for manuscript submissions, offering researchers an international platform to share emerging discoveries in communication systems, engineering technologies, and interdisciplinary innovation. The launches arrive as advances in artificial intelligence, sixth-generation wireless networks, satellite systems, advanced materials, and sustainable engineering continue to reshape scientific research and industrial development.

Wireless and Communication Letters is focused on the technologies that enable today’s increasingly connected world. The journal will publish original letters, full-length research articles, comprehensive reviews, mini-reviews, and guest-edited thematic issues addressing both theoretical developments and practical applications. Its scope covers the complete communication chain, from antennas and radio-frequency hardware to signal processing, network architecture, cybersecurity, and intelligent software. By emphasizing the efficient dissemination of research, the journal aims to provide a rapid channel for findings that could influence the next generation of wireless infrastructure.

The technical challenges addressed by the journal are central to the future of digital connectivity. Fifth-generation networks have already introduced high-speed mobile broadband, ultra-reliable low-latency communication, and massive machine-type connectivity, but researchers are now investigating 6G systems capable of supporting even greater data rates, extremely precise sensing, and seamless integration with artificial intelligence. These systems may combine terahertz frequencies, reconfigurable intelligent surfaces, distributed antennas, edge computing, and advanced machine-learning algorithms. Such technologies require new approaches to spectrum allocation, energy efficiency, network coordination, and data security.

The journal also welcomes research on the Internet of Things and machine-to-machine communication, areas in which billions of sensors and devices are expected to exchange data with minimal human intervention. In these environments, communication protocols must operate reliably despite limited power, unpredictable radio conditions, and enormous numbers of connected nodes. Research into low-power wide-area networks, intelligent scheduling, network virtualization, and secure device authentication could help support applications ranging from industrial automation and smart cities to remote healthcare and environmental monitoring.

A further component of the journal’s scope involves the physical science of communication. Antenna design, electromagnetic propagation, microwave engineering, optical links, and satellite communication determine how information travels through real environments. Engineers must account for obstacles, atmospheric conditions, interference, polarization, bandwidth limitations, and the movement of users or spacecraft. Developments in compact antennas, beamforming, optical wireless communication, and satellite-terrestrial integration could improve connectivity in rural regions, disaster zones, transportation systems, and future space missions.

Wireless and Communication Letters is led by Editor-in-Chief Dr. Nasimuddin of the Antenna and Optical Department at the Institute for Infocomm Research in Singapore. Supported by an international editorial board, the journal states that it will apply a rigorous and objective peer-review process. This is particularly important in a field where theoretical claims must often be tested through simulations, prototypes, channel measurements, or performance comparisons. Research involving modulation, coding, information theory, cognitive radio, software-defined networking, artificial intelligence, privacy, and communication protocols will be considered within the journal’s broad technological remit.

Alongside the communications title, Bentham Science has introduced Current Engineering Letters and Reviews, an interdisciplinary journal intended to connect research across the full spectrum of engineering sciences. Announced on 3 August 2026, the journal will publish research articles, short communications, comprehensive reviews, mini-reviews, and thematic issues. Its mission is to bring together discoveries that are often separated into specialist fields, reflecting the reality that many modern technologies emerge from collaboration among mechanical, electrical, materials, chemical, biomedical, environmental, and computer engineers.

The new engineering journal will cover aerospace, civil, structural, transportation, manufacturing, energy, robotics, automation, nanotechnology, artificial intelligence, and digital engineering. It will also address sustainable engineering, renewable energy systems, smart materials, advanced manufacturing, and biomedical technologies. These subjects are increasingly connected: an electric vehicle, for example, depends simultaneously on materials science, power electronics, software, communications, manufacturing, and transportation engineering. An interdisciplinary publication can provide a forum for examining such systems as integrated technological platforms rather than isolated components.

The scientific importance of this approach is becoming more visible as engineers confront challenges involving climate change, resource efficiency, resilient infrastructure, and automation. Renewable energy systems require improved storage, power conversion, and grid management; smart materials can respond to changes in temperature, pressure, or electromagnetic fields; and artificial intelligence can optimize industrial processes by identifying patterns in large streams of sensor data. At the same time, engineering research must demonstrate reliability, scalability, safety, and economic feasibility if laboratory innovations are to produce measurable benefits in society and industry.

Both journals invite contributions from researchers, engineers, scientists, academics, and industry professionals worldwide. Bentham Science says that information about open-access policies, article processing charges, waiver eligibility, editorial policies, and complaints and appeals procedures is available through the respective journal websites. With their emphasis on rapid communication, technical rigor, and interdisciplinary exchange, the two publications seek to become new hubs for research at the intersection of connectivity, intelligent systems, sustainable technology, and engineering innovation.

Subject of Research: Wireless communications, communication engineering, interdisciplinary engineering research, emerging technologies, artificial intelligence, sustainable engineering, and advanced technological systems.

Article Title: Bentham Science Launches Two New Journals to Accelerate Research in Wireless Communications and Engineering

News Publication Date: 3 August 2026 (for the announcement of Current Engineering Letters and Reviews; no publication date is provided for Wireless and Communication Letters).

Keywords

Wireless communications, 5G, 6G, Internet of Things, satellite communications, antenna design, signal processing, artificial intelligence, engineering research, sustainable engineering, robotics, renewable energy, smart materials, advanced manufacturing.

The federal government is warning users of home and small office routers to secure their devices as Russia state hackers continue to mass-compromise them for use in obscuring nefarious actions against sensitive organizations in the public and private sectors.

Both the Russian and Chinese governments have been compromising routers for years, sometimes in prolonged tugs-of-war to wrest control of devices the other has already commandeered. The US government has occasionally issued covert commands and taken other steps to disinfect routers. Google and other companies have also worked to disrupt the massive botnets that control compromised routers in lockstep. The actions to date are little more than whack-a-mole exercises as the operators simply replace their botnets with new ones.

Proxy networks: The go-to tool

“Russian Federal Security Service (FSB) Center 16 cyber actors continue to exploit poorly configured and vulnerable networking devices worldwide, opportunistically compromising multiple critical infrastructure sector networks,” the Cybersecurity and Infrastructure Security Agency said Monday. The hacking groups are tracked under various names, including Berserk Bear, Energetic Bear, Crouching Yeti, Dragonfly, Ghost Blizzard, and Static Tundra. The advisory was co-issued by governments from around the world, including Australia, Denmark, New Zealand, and the UK.

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In a groundbreaking study poised to reshape our understanding of mitochondrial genetics and neurological disorders, researchers have uncovered profound cortical neuronal disturbances driven by mitochondrial DNA (mtDNA) heteroplasmy in human brain organoids. This revelation centers on the common m.3243A>G mutation, a genetic defect frequently linked to a spectrum of neurodegenerative diseases. The work, published in Nature Communications in 2026 by Hathazi, Lyons, Lagos, and colleagues, offers unprecedented insights into how subtle shifts in mitochondrial DNA populations might disrupt cortical neuron function at a cellular and network level—potentially illuminating new therapeutic avenues for conditions that have long eluded effective treatment.

Mitochondria, often described as the cell’s powerhouses, maintain cellular energy homeostasis by generating adenosine triphosphate (ATP). However, mitochondrial DNA holds a unique genetic code separate from that of the nuclear genome, and it exists in multiple copies within each mitochondrion. Heteroplasmy—an admixture of normal (wild-type) and mutant mtDNA molecules—can fluctuate extensively between cells and tissues. This heterogeneity significantly affects mitochondrial function, but the precise pathological consequences in human neurons have remained elusive. The study by Hathazi and collaborators bridges this gap by meticulously linking mtDNA heteroplasmy directly to measurable disturbances within cortical neurons derived from human organoids.

The researchers employed human pluripotent stem cell-derived cerebral organoids, three-dimensional cellular models that recapitulate many aspects of human cortical development and cellular diversity. By engineering these organoids to harbor varying levels of the m.3243A>G point mutation in the mitochondrial tRNA^Leu(UUR) gene, they generated a physiologically relevant system that models how mtDNA heteroplasmy inherently affects neuronal populations. This mutation impairs mitochondrial protein translation, leading to compromised oxidative phosphorylation—a known driver of metabolic dysfunction in affected cells.

Single-cell analyses revealed marked mitochondrial dysfunction in neurons exhibiting high mutation loads. The mutant mitochondria produced increased reactive oxygen species (ROS), exhibited diminished membrane potential, and showed perturbed calcium handling. These biochemical aberrations culminated in altered electrophysiological properties, including disrupted synaptic transmission and impaired action potential firing patterns. The affected cortical neurons displayed reduced synaptic density and connectivity, phenotypes consistent with impaired network synchronization and cognitive deficits observed in mitochondrial encephalopathies.

Remarkably, the study delineates a threshold effect whereby neuronal function remains relatively preserved below a critical heteroplasmy level but deteriorates precipitously once mutant load surpasses this point. This finding is pivotal in explaining the clinical heterogeneity seen among patients with the m.3243A>G mutation, where symptom severity correlates with mtDNA mutant load. It also underscores the fine balance within mitochondria between normal and mutant genomes that regulates cellular health in the brain.

To establish causality, the investigators utilized gene-editing techniques to reduce the mutant mtDNA proportion within organoids. This intervention partially rescued mitochondrial respiration and restored electrophysiological parameters toward normal, confirming that the mutation-induced mitochondrial defects directly drive neuronal impairment. Pharmacological modulation of mitochondrial stress pathways, such as enhancing mitophagy and antioxidant defenses, further ameliorated neuronal dysfunction, highlighting potential therapeutic strategies.

The implications of these findings extend beyond the m.3243A>G mutation alone. Mitochondrial heteroplasmy is a pervasive phenomenon implicated in aging and numerous neurodegenerative diseases, including Parkinson’s and Alzheimer’s disease. This study suggests that subtle shifts in mitochondrial genetic composition may critically influence disease progression in ways previously unappreciated. Moreover, the use of human cerebral organoids enables modeling of human-specific neuronal vulnerabilities to mitochondrial perturbations, overcoming the limitations inherent in animal models that often lack analogous heteroplasmy dynamics.

The technological advancements leveraged in this research, including high-resolution single-cell mitochondrial assays and precise heteroplasmy editing, represent a tour de force in disease modeling. By recapitulating human cortical development and neuronal network formation in vitro, organoids provide a window into how mitochondrial mutations disrupt developmentally timed neuronal processes leading to widespread cortical dysfunction. These insights could fuel the design of novel mitochondrial-targeted therapies aiming to maintain heteroplasmy below pathological thresholds or to enhance mitochondrial quality control mechanisms.

Furthermore, the findings provoke reconsideration of diagnostic and prognostic approaches in mitochondrial disease. Current clinical assessments largely measure systemic heteroplasmy levels, which may not reflect the mosaicism present within specific brain regions. Non-invasive biomarkers that detect mitochondrial dysfunction in cortical neurons or imaging modalities sensitive to mitochondrial bioenergetics could aid in more accurate disease staging and treatment monitoring.

The study also opens intriguing questions regarding mitochondrial-nuclear genome interactions in the context of heteroplasmy. Given that mitochondrial function is coordinated with nuclear-encoded metabolic pathways, disturbed crosstalk in the presence of mutant mtDNA could exacerbate neuronal pathology. Future research may uncover compensatory nuclear genetic factors that modulate the impact of mtDNA mutations, potentially identifying new therapeutic targets.

In summary, Hathazi and colleagues provide a compelling narrative linking mitochondrial genetic heterogeneity to neuronal network disturbances using a cutting-edge human brain organoid model. This work underscores the critical importance of mtDNA heteroplasmy in shaping neuronal health and disease, particularly within the cerebral cortex, a region central to cognition and behavior. The insights gained promise to accelerate translational efforts aimed at mitigating mitochondrial dysfunction in neurological disorders, paving the way for therapies that restore mitochondrial harmony and preserve brain function.

By marrying sophisticated genetic engineering with organoid technology and comprehensive functional assays, this research sets a new benchmark in mitochondrial neuroscience. The concept that distinct levels of a common mtDNA mutation can finely tune neuronal fate and function introduces a paradigm shift with far-reaching implications. As the field progresses, these findings may herald a future where mitochondrial genomic interventions become integral components of personalized neurotherapeutics, ultimately improving the lives of patients affected by devastating mitochondrial diseases.

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Subject of Research:
Mitochondrial DNA heteroplasmy and its impact on cortical neuronal function in human brain organoids bearing the m.3243A>G mutation.

Article Title:
Mitochondrial DNA heteroplasmy drives cortical neuronal disturbances in human organoids harbouring the common m.3243A>G mutation.

Article References:
Hathazi, D., Lyons, C., Lagos, D. et al. Mitochondrial DNA heteroplasmy drives cortical neuronal disturbances in human organoids harbouring the common m.3243A>G mutation. Nat Commun (2026). https://doi.org/10.1038/s41467-026-74103-y

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This is a monumental biological network.

Hidden underground around the world lie 110 quadrillion kilometers of arbuscular mycorrhizal fungal networks—webs of ultra-thin threads that, if connected in a single line, would stretch almost a billion times the distance between the Earth and the sun, according to new research published in Science on Thursday.

These fungal communities form intimate relationships with the roots of plants, which they provide with nutrients like phosphorus and nitrogen in exchange for carbon, 1 billion tons of which the networks sequester underground annually, previous research has found. If the fungal network wasn’t storing it, that carbon would be warming the atmosphere.

But those networks have never been mapped globally until now. The new study led by Society for the Protection of Underground Networks, or SPUN, an organization founded to map mycorrhizal fungi networks, used a combination of literature review, soil samples from around the globe, machine learning and laboratory testing to estimate the distribution and mass of these systems and map where they are densest.

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British small satellite specialist Open Cosmos is seeking more time to deploy its proposed sovereign broadband constellation for Europe after running into launch issues.

The post Open Cosmos seeks deadline extension for broadband constellation appeared first on SpaceNews.

Authorities in the Netherlands said they dismantled a botnet that comprised more than 17 million devices and were managed by 200 servers in a joint operation by the police and the National Cyber Security Center.

The action, announced Thursday, came about after a security researcher reported the sprawling network to authorities. The host infrastructure was located in the Netherlands.

Used for criminal purposes

“The police then seized several botnet servers from a hosting provider for investigation,” the NCSC said. “The botnet was taken offline by the provider because it was used for criminal purposes.”

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