Study reveals “two-factor authentication” system that controls microRNA destruction

Cells rely on tiny molecules called microRNAs to tune which genes are active and when. Cells must carefully control the lifespan of microRNAs to prevent widespread disruption to gene regulation.

A new study led by researchers at MIT’s Whitehead Institute for Biomedical Research and Germany’s Max Planck Institute of Biochemistry reveals how cells selectively eliminate certain microRNAs through an unexpectedly intricate molecular recognition system. The open-access work, published on March 18 in Nature, shows that the process requires two separate RNA signals, similar to how many digital systems require two forms of identity verification before granting access.

The findings explain how cells use this “two-factor authentication” system to ensure that only intended microRNAs are destroyed, leaving the rest of the gene regulation machinery in operation.

MicroRNAs are short strands of RNA that help control gene expression. Working together with a protein called Argonaute, they bind to specific messenger RNAs — the molecules that carry genetic instructions from DNA to the cell’s protein-making machinery — and trigger their destruction. In this way, microRNAs can reduce the production of specific proteins.

While scientists recognized that microRNAs could be destroyed through a pathway known as target-directed microRNA degradation, or TDMD, the details of how cells recognized which microRNAs to eliminate remained unclear.

“We knew there was a pathway that could target microRNAs for degradation, but the biochemical mechanism behind it wasn’t understood,” says MIT Professor David Bartel, a Whitehead Institute member and co-senior author of the study.

Earlier work from Bartel’s lab and others had identified a key player in this pathway: the ZSWIM8 E3 ubiquitin ligase. E3 ubiquitin ligases are involved in the cell’s recycling system and attach a small molecular tag called ubiquitin to other proteins, marking them for destruction.

The researchers first showed that the ZSWIM8 E3 ligase specifically binds and tags Argonaute, the protein that holds microRNAs and helps regulate genes. The researchers’ next challenge was to understand how this machinery recognized only Argonaute complexes carrying specific microRNAs that should be degraded.

The answer turned out to be surprisingly sophisticated.

Using a combination of biochemistry and cryo-electron microscopy — an imaging technique that reveals molecular structures at near-atomic resolution — the researchers discovered that the degradation system relies on a dual-RNA recognition process. First, Argonaute must carry a specific microRNA. Second, another RNA molecule called a “trigger RNA” must bind to that microRNA in a particular way.

The degradation machinery activates only when both signals are present.

This dual requirement ensures exquisite specificity. Each cell contains over a hundred thousand Argonaute–microRNA complexes regulating many genes, and destroying them indiscriminately would disrupt essential biological processes.

“The vast majority of Argonaute molecules in the cell are doing useful work regulating gene expression,” says Bartel, who is a professor of biology at MIT and also a Howard Hughes Medical Institute investigator. “You only want to degrade the ones carrying a particular microRNA and bound to the right trigger RNA. Without that specificity, the cell would lose its microRNAs and the essential regulation that they provide.”

The structural images revealed complex molecular interactions. The ZSWIM8 ligase detects multiple structural changes that occur when the two RNAs bind together within the Argonaute protein.

“When we saw the structure, everything clicked,” says Elena Slobodyanyuk, a graduate student in Bartel’s lab and co-first author of the study. “You could see how the pairing of the trigger RNA with the microRNA reshapes the Argonaute complex in a way that the ligase can recognize.”

Beyond explaining how TDMD works, the findings may impact how scientists think about the regulation of RNA molecules more broadly.

“A lot of E3 ligases recognize their targets through simpler signals,” says Jakob Farnung, co-first author and researcher in the Department of Molecular Machines and Signaling at the Max Planck Institute of Biochemistry. “It was like opening a treasure chest where every detail revealed something new and mesmerizing.”

MicroRNAs typically persist in cells for much longer time periods than most messenger RNAs, but some degrade far more quickly, and the TDMD pathway appears to account for many of these unusually short-lived microRNAs.

The researchers are now investigating whether other RNAs can trigger similar degradation pathways and whether additional microRNAs are regulated through variations of the mechanism shown in this study.

“This opens up a whole new way of thinking about how RNA molecules can control protein degradation,” says Brenda Schulman, study co-senior author and director of the Department of Molecular Machines and Signaling at the Max Planck Institute of Biochemistry. “Here, the recognition was far more elaborate than expected. There’s likely much more left to discover.”

Uncovering the details of this intricate regulatory system required interdisciplinary collaboration, combining expertise in RNA biochemistry, structural biology, and ubiquitin enzymology to solve this long-standing molecular puzzle.

“This was a project that required the strengths of two labs working at the forefront of their fields,” says Schulman, who is also an alum of Whitehead Institute. “It was an incredible team effort.”

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How bacteria suppress immune defenses in stubborn wound infections

Chronic wound infections are notoriously difficult to manage because some bacteria can actively interfere with the body’s immune defenses. In wounds, Enterococcus faecalis (E. faecalis) is particularly resilient — it can survive inside tissues, alter the wound environment, and weaken immune signals at the injury site. This disruption creates conditions where other microbes can easily establish themselves, resulting in multi-species infections that are complex and slow to resolve. Such persistent wounds, including diabetic foot ulcers and post-surgical infections, place a heavy burden on patients and health care systems, and sometimes lead to serious complications such as amputations.

Now, researchers have discovered how E. faecalis releases lactic acid to acidify its surroundings and suppresses the immune-cell signal needed to start a proper response to infection. By silencing the body’s defenses, the bacterium can cause persistent and hard-to-treat wound infections. This explains why some wounds struggle to heal, even with treatment, and why infections involving multiple bacteria are especially difficult to eradicate.

The work was led by researchers from the Singapore-MIT Alliance for Research and Technology (SMART) Antimicrobial Resistance (AMR) interdisciplinary research group, alongside collaborators from the Singapore Centre for Environmental Life Sciences Engineering at Nanyang Technological University (NTU Singapore), MIT, and the University of Geneva in Switzerland.

In a paper titled “Enterococcus faecalis-derived lactic acid suppresses macrophage activation to facilitate persistent and polymicrobial wound infections,” recently published in Cell Host & Microbe, the researchers documented how E. faecalis releases large amounts of lactic acid during infection. This acidity suppresses the activation of macrophages — immune cells that normally help to clear infections — and interferes with several important internal processes that help the cell recognize and respond to infection. As a result, the mechanisms that cells rely on to send out “danger” signals are suppressed, leaving the macrophages unable to fully activate.

Researchers found that E. faecalis uses a two‑step mechanism to achieve this. Lactic acid enters the macrophages through a lactate transporter called MCT‑1 and also binds to a lactate-sensing receptor, GPR81, on the cell surface. By engaging both pathways, the bacterium effectively shuts down downstream immune signalling and blocks the macrophage’s inflammatory response, allowing E. faecalis to persist in the wound much longer than it should. Specifically, the lactic acid prevents a key immune alarm signal, known as NF-κB, from switching on inside these cells.

This was proven in a mouse wound model, where strains of E. faecalis that could not make lactic acid were cleared much more quickly, and the wounds also showed stronger immune activity. In wounds infected with both E. faecalis and Escherichia coli, the weakened immune response caused by lactic acid also allowed E. coli to grow better. This explains why wound infections often involve multiple species of bacteria and become harder to treat over time, particularly since E. faecalis is among the most common bacteria found in chronic wounds.

“Chronic wound infections often fail not because antibiotics are powerless, but because the immune system has effectively been ‘switched off’ at the infection site. We found that E. faecalis floods the wound with lactic acid, lowering pH and muting the NF‑κB alarm inside macrophages — the very cells that should be calling for help. By pinpointing how acidity rewires immune signalling, we now have clear targets to reactivate the immune response,” says first author Ronni da Silva, research scientist at SMART AMR, former postdoc in the lab of co-author and MIT professor of biology Jianzhu Chen, and SCELSE-NTU visiting researcher.

“This discovery strengthens our understanding of host-pathogen interactions and offers new directions for developing treatments and wound care that target the bacteria’s immunosuppressive strategies. By revealing how the immune response is shut down, this research may help improve infection management and support better recovery outcomes for patients, especially those with chronic wounds or weakened immunity,” says Kimberly Kline, principal investigator at SMART AMR, SCELSE-NTU visiting academic, professor at the University of Geneva, and corresponding author of the paper.

By identifying lactic‑acid‑driven immune suppression as a root cause of persistent wound infections, this work highlights the potential of treatment approaches that support the immune system, rather than rely on antibiotics alone. This could lead to therapies that help wounds heal more reliably and reduce the risk of complications. Potential directions include reducing acidity in the wound or blocking the signals that lactic acid uses to switch off immune cells.

Building on their study, the researchers plan to explore validation in additional pathogens and human wound samples, followed by assessments in advanced preclinical models ahead of any potential clinical trials.

The research was partially supported by the National Research Foundation Singapore under its Campus for Research Excellence and Technological Enterprise program.

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Helping data centers deliver higher performance with less hardware

To improve data center efficiency, multiple storage devices are often pooled together over a network so many applications can share them. But even with pooling, significant device capacity remains underutilized due to performance variability across the devices.

MIT researchers have now developed a system that boosts the performance of storage devices by handling three major sources of variability simultaneously. Their approach delivers significant speed improvements over traditional methods that tackle only one source of variability at a time.

The system uses a two-tier architecture, with a central controller that makes big-picture decisions about which tasks each storage device performs, and local controllers for each machine that rapidly reroute data if that device is struggling.

The method, which can adapt in real-time to shifting workloads, does not require specialized hardware. When the researchers tested this system on realistic tasks like AI model training and image compression, it nearly doubled the performance delivered by traditional approaches. By intelligently balancing the workloads of multiple storage devices, the system can increase overall data center efficiency.

“There is a tendency to want to throw more resources at a problem to solve it, but that is not sustainable in many ways. We want to be able to maximize the longevity of these very expensive and carbon-intensive resources,” says Gohar Chaudhry, an electrical engineering and computer science (EECS) graduate student and lead author of a paper on this technique. “With our adaptive software solution, you can still squeeze a lot of performance out of your existing devices before you need to throw them away and buy new ones.”

Chaudhry is joined on the paper by Ankit Bhardwaj, an assistant professor at Tufts University; Zhenyuan Ruan PhD ’24; and senior author Adam Belay, an associate professor of EECS and a member of the MIT Computer Science and Artificial Intelligence Laboratory. The research will be presented at the USENIX Symposium on Networked Systems Design and Implementation.

Leveraging untapped performance

Solid-state drives (SSDs) are high-performance digital storage devices that allow applications to read and write data. For instance, an SSD can store vast datasets and rapidly send data to a processor for machine-learning model training.   

Pooling multiple SSDs together so many applications can share them improves efficiency, since not every application needs to use the entire capacity of an SSD at a given time. But not all SSDs perform equally, and the slowest device can limit the overall performance of the pool.

These inefficiencies arise from variability in SSD hardware and the tasks they perform.

To utilize this untapped SSD performance, the researchers developed Sandook, a software-based system that tackles three major forms of performance-hampering variability simultaneously. “Sandook” is an Urdu word that means “box,” to signify “storage.”

One type of variability is caused by differences in the age, amount of wear, and capacity of SSDs that may have been purchased at different times from multiple vendors.

The second type of variability is due to the mismatch between read and write operations occurring on the same SSD. To write new data to the device, the SSD must erase some existing data. This process can slow down data reads, or retrievals, happening at the same time.

The third source of variability is garbage collection, a process of gathering and removing outdated data to free up space. This process, which slows SSD operations, is triggered at random intervals that a data center operator cannot control.

“I can’t assume all SSDs will behave identically through my entire deployment cycle. Even if I give them all the same workload, some of them will be stragglers, which hurts the net throughput I can achieve,” Chaudhry explains.

Plan globally, react locally

To handle all three sources of variability, Sandook utilizes a two-tier structure. A global schedular optimizes the distribution of tasks for the overall pool, while faster schedulers on each SSD react to urgent events and shift operations away from congested devices.

The system overcomes delays from read-write interference by rotating which SSDs an application can use for reads and writes. This reduces the chance reads and writes happen simultaneously on the same machine.

Sandook also profiles the typical performance of each SSD. It uses this information to detect when garbage collection is likely slowing operations down. Once detected, Sandook reduces the workload on that SSD by diverting some tasks until garbage collection is finished.

“If that SSD is doing garbage collection and can’t handle the same workload anymore, I want to give it a smaller workload and slowly ramp things back up. We want to find the sweet spot where it is still doing some work, and tap into that performance,” Chaudhry says.

The SSD profiles also allow Sandook’s global controller to assign workloads in a weighted fashion that considers the characteristics and capacity of each device.

Because the global controller sees the overall picture and the local controllers react on the fly, Sandook can simultaneously manage forms of variability that happen over different time scales. For instance, delays from garbage collection occur suddenly, while latency caused by wear and tear builds up over many months.

The researchers tested Sandook on a pool of 10 SSDs and evaluated the system on four tasks: running a database, training a machine-learning model, compressing images, and storing user data. Sandook boosted the throughput of each application between 12 and 94 percent when compared to static methods, and improved the overall utilization of SSD capacity by 23 percent.

The system enabled SSDs to achieve 95 percent of their theoretical maximum performance, without the need for specialized hardware or application-specific updates.

“Our dynamic solution can unlock more performance for all the SSDs and really push them to the limit. Every bit of capacity you can save really counts at this scale,” Chaudhry says.

In the future, the researchers want to incorporate new protocols available on the latest SSDs that give operators more control over data placement. They also want to leverage the predictability in AI workloads to increase the efficiency of SSD operations.

“Flash storage is a powerful technology that underpins modern datacenter applications, but sharing this resource across workloads with widely varying performance demands remains an outstanding challenge. This work moves the needle meaningfully forward with an elegant and practical solution ready for deployment, bringing flash storage closer to its full potential in production clouds,” says Josh Fried, a software engineer at Google and incoming assistant professor at the University of Pennsylvania, who was not involved with this work.

This research was funded, in part, by the National Science Foundation, the U.S. Defense Advanced Research Projects Agency, and the Semiconductor Research Corporation.

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Working to advance the nuclear renaissance

Today, there are 94 nuclear reactors operating in the United States, more than in any other country in the world, and these units collectively provide nearly 20 percent of the nation’s electricity. That is a major accomplishment, according to Dean Price, but he believes that our country needs much more out of nuclear energy, especially at a moment when alternatives to fossil fuel-based power plants are desperately being sought. He became a nuclear engineer for this very reason — to make sure that nuclear technology is up to the task of delivering in this time of considerable need.

“Nuclear energy has been a tremendous part of our nation’s energy infrastructure for the past 60 years, and the number of people who maintain that infrastructure is incredibly small,” says Price, an MIT assistant professor in the Department of Nuclear Science and Engineering (NSE), as well as the Atlantic Richfield Career Development Professor in Energy Studies. “By becoming a nuclear engineer, you become one of a select number of people responsible for carbon-free energy generation in the United States.” 

That was a mission he was eager to take part in, and the goals he set for himself were far from modest: He wanted to help design and usher in a new class of nuclear reactors, building on the safety, economics, and reliability of the existing nuclear fleet.

Price has never wavered from this objective, and he’s only found encouragement along the way. The nuclear engineering community, he says, “is small, close-knit, and very welcoming. Once you get into it, most people are not inclined to do anything else.”

Illuminating the relationships between physical processes

In his first research project as an undergraduate at the University of Illinois Urbana at Champaign, Price studied the safety of the steel and concrete casks used to store spent reactor fuel rods after they’ve cooled off in tanks of water, typically for several years. His analysis indicated that this storage method was quite safe, although the question as to what should ultimately be done with these fuel casks, in terms of long-term disposal, remains open in this country.

After starting graduate studies at the University of Michigan in 2020, Price took up a different line of research that he’s still engaged in today. That area of study, called multiphysics modeling, involves looking at various physical processes going on in the core of a nuclear reactor to see how they interact — an alternative to studying these processes one at a time.

One key process, neutronics, concerns how neutrons buzz around in the reactor core causing nuclear fission, which is what generates the power. A second process, called thermal hydraulics, involves cooling the reactor to extract the heat generated by neutrons. A multiphysics simulation, analyzing how these two processes interact, could show how the heat carried away as the reactor produces power affects the behavior of neutrons, because the hotter the fuel is, the less likely it is to cause fission.

“If you ever want to change your power level, or do anything with the reactor, the temperature of the fuel is a critical input that you need to know,” says Price. “Multiphysics modeling allows us to correlate the fission neutronics processes with a thermal property, temperature. That, in turn, can help us predict how the reactor will behave under different conditions.”

Multiphysics modeling for light water reactors, which are the ones operating today with capacities on the order of 1,000 megawatts, are pretty well established, Prices says. But methods for modeling advanced reactors — small modular reactors (SMRs with capacities ranging from around 20 to 300 MW) and microreactors (rated at 1 to 20 MW) — are far less advanced. Only a very small number of these reactors are operating today, but Price is focusing his efforts on them because of their potential to produce power more cheaply and more safely, along with their greater flexibility in power and size.   

Although multiphysics simulations have supplied the nuclear community with a wealth of information, they can require supercomputers to solve, or find approximate solutions to, coupled and extremely difficult nonlinear equations. In the hopes of greatly reducing the computational burden, Price is actively exploring artificial intelligence approaches that could provide similar answers while bypassing those burdensome equations altogether. That has been a central theme of his research agenda since he joined the MIT faculty in September 2025.

A crucial role for artificial intelligence

What artificial intelligence and machine-learning methods, in particular, are good at is finding patterns concealed within data, such as correlations between variables critical to the functioning of a nuclear plant. For example, Price says, “if you tell me the power level of your reactor, it [AI] could tell you what the fuel temperature is and even tell you the 3-dimensional temperature distribution in your core.” And if this can be done without solving any complicated differential equations, computational costs could be greatly reduced.

Price is investigating several applications where AI may be especially useful, such as helping with the design of novel kinds of reactors. “We could then rely on the safety frameworks developed over the past 50 years to carry out a safety analysis of the proposed design,” he says. “In this way, AI will not be directly interfacing with anything that is safety-critical.” As he sees it, AI’s role would be to augment established procedures, rather than replacing them, helping to fill in existing gaps in knowledge.

When a machine-learning model is given a sufficient amount of data to learn from, it can help us better understand the relationship between key physical processes — again without having to solve nonlinear differential equations. 

“By really pinning down those relationships, we can make better design decisions in the early stages,” Price says. “And when that technology is developed and deployed, AI can help us make more intelligent control decisions that will enable us to operate our reactors in a safer and more economical way.”

Giving back to the community that nurtured him

Simply put, one of his chief goals is to bring the benefits of AI to the nuclear industry, and he views the possibilities as vast and largely untapped. Price also believes that he is well-positioned as a professor at MIT to bring us closer to the nuclear future that he envisions. As he sees it, he’s working not only to develop the next generation of reactors, but also to help prepare the next generation of leaders in the field.

Price became acquainted with some prospective members of that “next generation” in a design course he co-taught last fall with Curtis Smith, the KEPCO Professor of the Practice of Nuclear Science and Engineering. For Price, that introduction lasted just a few months, but it was long enough for him to discover that MIT students are exceptionally motivated, hard-working, and capable. Not surprisingly, those happen to be the same qualities he’s hoping to find in the students that join his research team.

Price vividly recalls the support he received when taking his first, tentative steps in this field. Now that he’s moved up the ranks from undergraduate to professor, and acquired a substantial body of knowledge along the way, he wants his students “to experience that same feeling that I had upon entering the field.” Beyond his specific goals for improving the design and operation of nuclear reactors, Price says, “I hope to perpetuate the same fun and healthy environment that made me love nuclear engineering in the first place.”

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Toward cheaper, cleaner hydrogen production

Hydrogen sits at the center of some of the world’s most important industrial processes, but its production still comes with a heavy environmental cost. Today, most hydrogen is produced through high-emissions processes like steam methane reforming and coal gasification.

But hydrogen can also be made by splitting water molecules using renewable electricity, eliminating fossil fuel emissions and other toxic byproducts. Such “green hydrogen” is made by running an electric current through water in an electrolyzer.

Green hydrogen won’t scale through decarbonization alone. It also has to be cost-competitive with the traditional methods of production.

1s1 Energy thinks it has the technology to finally make green hydrogen go mainstream. The company says its boron-based membrane material unlocks previously unachievable performance and durability in electrolyzers.

In tests with partners, 1s1 says, electrolyzers with its membranes needed just 70 percent of the energy to produce each kilogram of hydrogen, compared to incumbent devices.

“Green hydrogen has been a hard industry to have success in so far,” acknowledges 1s1 co-founder Dan Sobek ’88, SM ’92, PhD ’97. “The difference with us is we’ve done very targeted customer discovery. We have a very strong value proposition that’s not just about decarbonization. We have a pipeline of potential customers that see around a 60 percent reduction in operating costs with our technology. That’s a nice point of entry.”

Although 1s1 is focused on hydrogen production now, its technology could also be used in fuel cells and solid-state batteries, and to extract critical metals from mining waste. The company is beginning trials in some of those applications, and it is working with a large materials company to scale up production of its membranes for hydrogen production.

“We’re at an inflection point for the company,” Sobek says. “The plan is, by 2030, to have a solid business in several segments: electrolyzers, mineral extraction, and in collaborations with several large companies. But right now, we have to be judicious and focused.”

Improving electrolyzers

Sobek was born and raised in Argentina, but he also grew up at MIT over the course of three degrees and more than a decade. He first studied aeronautics and astronautics at MIT, then jumped to mechanical engineering as a graduate student, then moved to the Department of Electrical Engineering and Computer Science, where he worked under PhD advisors and MIT professors Martha Gray and Stephen Senturia. His thesis focused on a technique for quickly measuring optical properties of large numbers of biological cells.

“A lot of my learnings around microfabrication and materials chemistry ended up being really relevant for 1s1,” Sobek says. “A class that was very important to me was taught by Professor Amar Bose. I was a teaching assistant for him for a couple of semesters, and that had an incredible influence on my thinking.”

Following graduation, Sobek worked in microelectronics and microfluidics before founding his own company, Zymera, in 2004. The company developed deep-tissue imaging technology for detecting cancer and other serious diseases.

Around 2013, Sobek started talking to his Zymera co-founder, Sukanta Bhattacharyya, about making electrolysis more efficient, focusing on “proton exchange membrane” electrolyzers. Such electrolyzers employ a large amount of electricity to split water into hydrogen and oxygen ions. At their center is a membrane that can lose efficiency through voltage resistance.

On top of the efficiency challenge, electricity is often more expensive than fossil fuels in many parts of the world. Traditional hydrogen production also has the benefit of existing infrastructure, making it that much more difficult for green hydrogen production to scale.

Sobek and Bhattacharyya knew the most important part of such electrolyzers is their proton-conducting membrane, which shuttles hydrogen ions from the anode to the cathode in the electrolyzer’s electrochemical cell.

“I asked Sukanta how we could improve the efficiency and durability of that element,” Sobek recalls. “He gave me a one-word answer: boron.”

Boron can be given a negative charge, which makes hydrogen ions, or protons, bond to it more quickly. The hydrogen ions can then be filtered through the membrane and released as they move through the cell. Boron-based materials are also more stable and resistant to corrosion, further improving the long-term performance of electrolyzers.

The company was officially founded in late 2019. After years of development, today 1s1 attaches a chemically tailored version of boron onto polymer materials to create its membranes for exchanging protons.

“These are first-of-a-kind membranes with stable and durable, super-acid proton exchange groups that do not poison catalysts,” Sobek says.

Tiny membranes with big impact

In 2021, the U.S. Department of Energy set a goal for proton exchange membrane electrolysis to achieve 77 percent electrical efficiency by 2031. Sobek says 1s1 is already reaching that milestone in tests.

“It’s not just the technology, but the way we’re applying it,” Sobek says, “We’re making hydrogen viable for use in the production of different industrial chemicals.”

1s1 is currently conducting pilots with partners, including an electrical utility owned by a large steel company in Brazil. The company is also actively exploring other applications for its technology. Last year, 1s1 announced a project to produce green ammonia with the company Nitrofix through joint funding from the U.S. Department of Energy and the Israeli Ministry of Energy and Infrastructure. It’s also working with a large mine in Brazil to extract a material called niobium, which is useful for high-strength steel as well as fast-charging batteries. A similar process could even be used to extract gold.

“We can do that without using harsh chemicals, because the standard processes used to extract niobium and gold use extremely strong acids at high temperatures or extremely toxic chemicals,” Sobek says. “It’s gratifying for me because my home country of Argentina has had a lot of problems with the use of toxic chemicals to extract gold. We’re trying to enable low-cost, responsible mining.”

As 1s1 scales its membrane technology, Sobek says the goal is to deploy wherever the technology can improve processes.

“We have a large number of potential customers because this technology is really foundational,” Sobek says. “Creating high-impact technologies is always fun.”

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Lincoln Laboratory laser communications terminal launches on historic Artemis II moon mission

In 1969, Apollo 11 astronaut Neil Armstrong stepped onto the moon's surface — a momentous engineering and science feat marked by his iconic words: "That's one small step for man, one giant leap for mankind." Now, NASA is making history again.

With the successful launch of NASA's Artemis II mission yesterday, four astronauts are set to become the first humans to travel to the moon in more than 50 years. In 2022, the uncrewed Artemis I mission demonstrated that NASA's new Orion spacecraft could travel farther into space than ever before and return safely to Earth. Building on that success, the 10-day Artemis II mission will pave the way for future Artemis missions, which aim to land astronauts on the moon to prepare for a lasting lunar presence, and eventually human missions to Mars.

As it orbits the moon, the Orion spacecraft will carry an optical (laser) communications system developed at MIT Lincoln Laboratory in collaboration with NASA Goddard Space Flight Center. Called the Orion Artemis II Optical Communications System (O2O), the system is capable of higher-bandwidth data transmissions from space compared to traditional radio-frequency (RF) systems. During the Artemis II mission, O2O will use laser beams to send high-resolution video and images of the lunar surface down to Earth.

"Space-based communications has always been a big challenge," says lead systems engineer Farzana Khatri, a senior staff member in the laboratory's Optical and Quantum Communications Group. "RF communications have served their purpose well. However, the RF spectrum is highly congested now, and RF does not scale well to longer distances across space. Laser communication [lasercom] is a solution that could solve this problem, and the laboratory is an expert in the field, which was really pioneered here."

Artemis II is historic not only for renewing human exploration beyond Earth, but also for being the first crewed lunar flight to demonstrate lasercom technologies, which are poised to revolutionize how spacecraft communicate. Lincoln Laboratory has been developing such technologies for more than two decades, and NASA has been infusing them into its missions to meet the growing demands of long-distance and data-intensive space exploration.

"The Orion spacecraft collects a huge amount of data during the first day of a mission, and typically these data sit on the spacecraft until it splashes down and can take months to be offloaded," Khatri says. "With an optical link running at the highest rate, we should be able to get all the data down to Earth within a few hours for immediate analysis. Furthermore, astronauts will be able to communicate in real-time over the optical link to stay in touch with Earth during their journey, inspiring the public and the next generation of deep-space explorers, much like the Apollo 11 astronauts who first landed on the moon 57 years ago."

At the heart of O2O is the laboratory-developed Modular, Agile, Scalable Optical Terminal (MAScOT). About the size of a house cat, MAScOT features a 4-inch telescope mounted on a two-axis pivoted support (gimbal) with fixed backend optics. The gimbal precisely points the telescope and tracks the laser beam through which communications signals are emitted and received in the direction of the desired data recipient or sender. Underneath the gimbal, in a separate assembly, are the backend optics, which contain light-focusing lenses, tracking sensors, fast-steering mirrors, and other components to finely point the laser beam.

MAScOT made its debut in space as part of the laboratory's Integrated Laser Communications Relay Demonstration (LCRD) LEO User Modem and Amplifier Terminal (ILLUMA-T), which launched to the International Space Station in November 2023. Over the following six months, the laboratory team performed experiments to test and characterize the system's basic functionality, performance, and utility for human crews and user applications. Initially, the team checked whether the ILLUMA-T-to-LCRD optical link was operating at the intended data rates in both directions: 622 Mbps down and 51 Mbps up. In fact, even higher data rates were achieved: 1.2 Gbps down and 155 Mbps up. MAScOT's lasercom terminal architecture, which was recognized with a 2025 R&D 100 Award, is now being used for Artemis II and will support future space missions.

"Our success with ILLUMA-T laid the foundation for streaming HD [high-definition] video to and from the moon," says co-principal investigator Jade Wang, an assistant leader of the Optical and Quantum Communications Group. "You can imagine the Artemis astronauts using videoconferencing to connect with physicians, coordinate mission activities, and livestream their lunar trips."

A dedicated operations team from Lincoln Laboratory is following the 10-day Artemis II mission from ground stations in Houston, Texas, and White Sands, New Mexico, and even as far as an experimental ground station in Australia, which allows for a better view of the spacecraft from the Southern Hemisphere. Leading up to the launch, the operations team had been making monthly trips to the Houston and White Sands ground stations to perform maintenance and simulations of various stages of the Artemis mission — from prelaunch to launch to the journey to the moon and back to the splashdown at the end of the mission. 

"Doing these monthly simulations is important so we all stay fresh and engaged, especially when there is a launch delay," says Khatri, who adds that team members have had the opportunity to meet and speak with the four astronauts several times during these trips.

Lessons learned throughout the Artemis II mission will pave the way for humans to return to the lunar surface and beyond, eventually to Mars. Through the Artemis program, NASA will travel farther into space and explore more of the moon while creating an enduring presence in deep space and a legacy for future generations.

O2O is funded by the Space Communication and Navigation (SCaN) program at NASA Headquarters in Washington. O2O was developed by a team of engineers from NASA's Goddard Space Flight Center and Lincoln Laboratory. This partnership has led to multiple lasercom missions, such as the 2013 Lunar Laser Communication Demonstration (LLCD), the 2021 LCRD, the 2022 TeraByte Infrared Delivery (TBIRD), and the 2023 ILLUMA-T.

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MIT researchers measure traffic emissions, to the block, in real-time

In a study focused on New York City, MIT researchers have shown that existing sensors and mobile data can be used to generate a near real-time, high-resolution picture of auto emissions, which could be used to develop local transportation and decarbonization policies.

The new method produces much more detailed data than some other common approaches, which use intermittent samples of vehicle emissions. The researchers say it is also more practical and scales up better than some studies that have aimed for very granular emissions data from a small number of automobiles at once. The work helps bridge the gap between less-detailed citywide emissions inventories and highly detailed analyses based on individual vehicles.

“Our model, by combining real-time traffic cameras with multiple data sources, allows extrapolating very detailed emission maps, down to a single road and hour of the day,” says Paolo Santi, a principal research scientist in the MIT Senseable City Lab and co-author of a new paper detailing the project’s results. “Such detailed information can prove very helpful to support decision-making and understand effects of traffic and mobility interventions.”

Carlo Ratti, director of the MIT Senseable City Lab, notes that the research “is part of our lab’s ongoing quest into hyperlocal measurements of air quality and other environmental factors. By integrating multiple streams of data, we can reach a level of precision that was unthinkable just a few years ago — giving policymakers powerful new tools to understand and protect human health.”

The new method also protects privacy, since it uses computer vision techniques to recognize types of vehicles, but without compiling license plate numbers. The study leverages technologies, including those already installed at intersections, to yield richer data about vehicle movement and pollution.

“The very basic idea is just to estimate traffic emissions using existing data sources in a cost-effective way,” says Songhua Hu, a former postdoc in the Senseable City Lab, and now an assistant professor at City University of Hong Kong.

The paper, “Ubiquitous Data-driven Framework for Traffic Emission Estimation and Policy Evaluation,” is published in Nature Sustainability.

The authors are Hu; Santi; Tom Benson, a researcher in the Senseable City Lab; Xuesong Zhou, a professor of transportation engineering at Arizona State University; An Wang, an assistant professor at Hong Kong Polytechnic University; Ashutosh Kumar, a visiting doctoral student at the Senseable City Lab; and Ratti. The MIT Senseable City Lab is part of MIT’s Department of Urban Studies and Planning.

Manhattan measurements

To conduct the study, the researchers used images from 331 cameras already in use in Manhattan intersections, along with anonymized location records from over 1.75 million mobile phones. Applying vehicle-recognition programs and defining 12 broad categories of automobiles, the scholars found they could correctly place 93 percent of vehicles in the right category. The imaging also yielded important information about the specific ways traffic signals affect traffic flow. That matters because traffic signals are a major reason for stop-and-go driving patterns, which strongly affect urban emissions but are often omitted in conventional inventories.

The mobile phone data then provided rich information about the overall patterns of traffic and movement of individual vehicles throughout the city. The scholars combined the camera and phone data with known information about emissions rates to arrive at their own emissions estimates for New York City.

“We just need to input all emission-related information based on existing urban data sources, and we can estimate the traffic emissions,” Hu says.

Moreover, the researchers evaluated the changes in emissions that might occur in different scenarios when traffic patterns, or vehicle types, also change.

For one, they modeled what would happen to emissions if a certain percentage of travel demand shifted from private vehicles to buses. In another scenario, they looked at what would happen if morning and evening rush hour times were spread out a bit longer, leaving fewer vehicles on the road at once. They also modeled the effects of replacing fine-grained emissions inputs with citywide averages — finding that the rougher emissions estimates could vary widely, from −49 percent to 25 percent of the more fine-tuned results. That underscores how seemingly small simplifications can introduce large errors into emission estimates.

Major emissions drop

On one level, this work involved altering inputs into the model and seeing what emerged. But one scenario the researchers studied is based on a real-world change: In January 2025, New York City implemented congestion pricing south of 60th Street in Manhattan.

To study that, the researchers looked at what happened to vehicle traffic at intervals of two, four, six, and eight weeks after the program began. Overall, congestion pricing lowered traffic volume by about 10 percent — but there was a corresponding drop in emissions of 16-22 percent.

This finding aligns with a previous study by researchers at Cornell University, which reported a 22 percent reduction in particulate matter (PM2.5) levels within the pricing zone. The MIT team also found that these reductions were not evenly distributed across the network, with larger declines on some major streets and more mixed effects outside the pricing zone.

“We see these kinds of huge changes after the congestion pricing began, Hu says. “I think that’s a demonstration that our model can be very helpful if a government really wants to know if a new policy converts into real-world impact.”

There are additional forms of data that could be fed into the researchers’ new method. For instance, in related work in Amsterdam, the team leveraged dashboard cams from vehicles to yield rich information about vehicle movement.

“With our model we can make any camera used in cities, from the hundreds of traffic cameras to the thousands of dash cams, a powerful device to estimate traffic emissions in real-time,” says Fábio Duarte, the associate director of research and design at the MIT Senseable City Lab, who has worked on multiple related studies.

The research was supported by the MIT Senseable City Consortium, which consists of Atlas University, the city of Laval, the city of Rio de Janeiro, Consiglio per la Ricerca in Agricoltura e l’Analisi dell’Economia Agraria, the Dubai Future Foundation, FAE Technology, KAIST Center for Advanced Urban Systems, Sondotecnica, Toyota, and Volkswagen Group America.

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