The latest United Nations Climate Change Conference (COP30) concluded in November without a roadmap to phase out fossil fuels and without significant progress in strengthening national pledges to reduce climate-altering greenhouse gas emissions. In aggregate, today’s climate policies remain far too unambitious to meet the Paris Agreement’s goal of capping global warming at 1.5 degrees Celsius, setting the world on course to experience more frequent and intense storms, flooding, droughts, wildfires, and other climate impacts. A global policy regime aligned with the 1.5 C target would almost certainly reduce the severity of those impacts.

In the “2025 Global Change Outlook,” researchers at the MIT Center for Sustainability Science and Strategy (CS3) compare the consequences of these two approaches to climate policy through modeled projections of critical natural and societal systems under two scenarios. The Current Trends scenario represents the researchers’ assessment of current measures for reducing greenhouse gas (GHG) emissions; the Accelerated Actions scenario is a credible pathway to stabilizing the climate at a global mean surface temperature of 1.5 C above preindustrial levels, in which countries impose more aggressive GHG emissions-reduction targets.  

By quantifying the risks posed by today’s climate policies — and the extent to which accelerated climate action aligned with the 1.5 C goal could reduce them — the “Global Change Outlook” aims to clarify what’s at stake for environments and economies around the world. Here, we summarize the report’s key findings at the global level; regional details can also be accessed in several sections and through MIT CS3’s interactive global visualization tool.  

Emerging headwinds for global climate action 

Projections under Current Trends show higher GHG emissions than in our previous 2023 outlook, indicating reduced action on GHG emissions mitigation in the upcoming decade. The difference, roughly equivalent to the annual emissions from Brazil or Japan, is driven by current geopolitical events. 

Additional analysis in this report indicates that global GHG emissions in 2050 could be 10 percent higher than they would be under Current Trends if regional rivalries triggered by U.S. tariff policy prompt other regions to weaken their climate regulations. In that case, the world would see virtually no emissions reduction in the next 25 years.

Energy and electricity projections

Between 2025 and 2050, global energy consumption rises by 17 percent under Current Trends, with a nearly nine-fold increase in wind and solar. Under Accelerated Actions, global energy consumption declines by 16 percent, with a nearly 13-fold increase in wind and solar, driven by improvements in energy efficiency, wider use of electricity, and demand response. In both Current Trends and Accelerated Actions, global electricity consumption increases substantially (by 90 percent and 100 percent, respectively), with generation from low-carbon sources becoming a dominant source of power, though Accelerated Actions has a much larger share of renewables.   

“Achieving long-term climate stabilization goals will require more ambitious policy measures that reduce fossil-fuel dependence and accelerate the energy transition toward low-carbon sources in all regions of the world. Our Accelerated Actions scenario provides a pathway for scaling up global climate ambition,” says MIT CS3 Deputy Director Sergey Paltsev, co-lead author of the report.

Greenhouse gas emissions and climate projections

Under Current Trends, global anthropogenic (human-caused) GHG emissions decline by 10 percent between 2025 and 2050, but start to rise again later in the century; under Accelerated Actions, however, they fall by 60 percent by 2050. Of the two scenarios, only the latter could put the world on track to achieve long-term climate stabilization.  

Median projections for global warming by 2050, 2100, and 2150 are projected to reach 1.79, 2.74, and 3.72 degrees C (relative to the global mean surface temperature (GMST) average for the years 1850-1900) under Current Trends and 1.62, 1.56, and 1.50 C under Accelerated Actions. Median projections for global precipitation show increases from 2025 levels of 0.04, 0.11, and 0.18 millimeters per day in 2050, 2100, and 2150 under Current Trends and 0.03, 0.04, and 0.03 mm/day for those years under Accelerated Actions.

“Our projections demonstrate that aggressive cuts in GHG emissions can lead to substantial reductions in the upward trends of GMST, as well as global precipitation,” says CS3 deputy director C. Adam Schlosser, co-lead author of the outlook. “These reductions to both climate warming and acceleration of the global hydrologic cycle lower the risks of damaging impacts, particularly toward the latter half of this century.”

Implications for sustainability

The report’s modeled projections imply significantly different risk levels under the two scenarios for water availability, biodiversity, air quality, human health, economic well-being, and other sustainability indicators. 

Among the key findings: Policies that align with Accelerated Actions could yield substantial co-benefits for water availability, biodiversity, air quality, and health. For example, combining Accelerated Actions-aligned climate policies with biodiversity targets, or with air-quality targets, could achieve biodiversity and air quality/health goals more efficiently and cost-effectively than a more siloed approach. The outlook’s analysis of the global economy under Current Trends suggests that decision-makers need to account for climate impacts outside their home region and the resilience of global supply chains.  

Finally, CS3’s new data-visualization platform provides efficient, screening-level mapping of current and future climate, socioeconomic, and demographic-related conditions and changes — including global mapping for many of the model outputs featured in this report. 

“Our comparison of outcomes under Current Trends and Accelerated Actions scenarios highlights the risks of remaining on the world’s current emissions trajectory and the benefits of pursuing a much more aggressive strategy,” says CS3 Director Noelle Selin, a co-author of the report and a professor in the Institute for Data, Systems and Society and Department of Earth, Atmospheric and Planetary Sciences at MIT. “We hope that our risk-benefit analysis will help inform decision-makers in government, industry, academia, and civil society as they confront sustainability-relevant challenges.” 

This interview is part of a series of short interviews from the Department of Electrical Engineering and Computer Science (EECS). Each spotlight features a student answering their choice of questions about themselves and life at MIT. Today’s interviewee, senior Diego Temkin, is double majoring in courses 6-3 (Computer Science and Engineering) and 11 (Urban Planning). The McAllen, Texas, native is involved with MIT’s Dormitory Council (DormCon), helps to maintain Hydrant (formerly Firehose)/CourseRoad, and is both a member of the Student Information Processing Board (MIT’s oldest computing club) and an Advanced Undergraduate Research Opportunities Program (SuperUROP) scholar.

Q: What’s your favorite key on a standard computer keyboard, and why?

A: The “1” key! During Covid, I ended up starting a typewriter collection and trying to fix them up, and I always thought it was interesting how they didn’t have a 1 key. People were just expected to use the lowercase “l,” which presumably makes anyone who cares about ASCII very upset.

Q: Tell us about a teacher from your past who had an influence on the person you’ve become.

A: Back in middle school, everyone had to take a technology class that taught things like typing skills, Microsoft Word and Excel, and some other things. I was a bit of a nerd and didn’t have too many friends interested in the sort of things I was, but the teacher of that technology class, Mrs. Camarena, would let me stay for a bit after school and encouraged me to explore more of my interests. She helped me become more confident in wanting to go into computer science, and now here I am. 

Q: What’s your favorite trivia factoid?

A: Every floor in Building 13 is painted as a different MBTA line. I don’t know why and can’t really find anything about it online, but once you notice it you can’t unsee it!

Q: Do you have any pets? 

A: I do! His name is Skateboard, and he is the most quintessentially orange cat. I got him off reuse@mit.edu during my first year here at MIT (shout out to Patty K), and he’s been with me ever since. He’s currently five years old, and he’s a big fan of goldfish and stepping on my face at 7 a.m. Best decision I’ve ever made. 

Q: Are you a re-reader or a re-watcher? If so, what are your comfort books, shows, or movies?

A: Definitely a re-watcher, and definitely “Doctor Who.” I’ve watched far too much of that show and there are episodes I can recite from memory (looking at you, “The Eleventh Hour”). Anyone I know will tell you that I can go on about that show for hours, and before anyone asks, my favorite doctor is Matt Smith (sorry to the David Tennant fans; I like him too, though!)

Q: Do you have a bucket list? If so, share one or two of the items on it.

A: I’ve been wanting to take a cross-country Amtrak trip for a while … I think I might try going to the West Coast and some national parks during IAP [Independent Activities Period], if I have the time. Now that it’s on here, I definitely have to do it!

Why did humans evolve the eyes we have today?

While scientists can’t go back in time to study the environmental pressures that shaped the evolution of the diverse vision systems that exist in nature, a new computational framework developed by MIT researchers allows them to explore this evolution in artificial intelligence agents.

The framework they developed, in which embodied AI agents evolve eyes and learn to see over many generations, is like a “scientific sandbox” that allows researchers to recreate different evolutionary trees. The user does this by changing the structure of the world and the tasks AI agents complete, such as finding food or telling objects apart.

This allows them to study why one animal may have evolved simple, light-sensitive patches as eyes, while another has complex, camera-type eyes.

The researchers’ experiments with this framework showcase how tasks drove eye evolution in the agents. For instance, they found that navigation tasks often led to the evolution of compound eyes with many individual units, like the eyes of insects and crustaceans.

On the other hand, if agents focused on object discrimination, they were more likely to evolve camera-type eyes with irises and retinas.

This framework could enable scientists to probe “what-if” questions about vision systems that are difficult to study experimentally. It could also guide the design of novel sensors and cameras for robots, drones, and wearable devices that balance performance with real-world constraints like energy efficiency and manufacturability.

“While we can never go back and figure out every detail of how evolution took place, in this work we’ve created an environment where we can, in a sense, recreate evolution and probe the environment in all these different ways. This method of doing science opens to the door to a lot of possibilities,” says Kushagra Tiwary, a graduate student at the MIT Media Lab and co-lead author of a paper on this research.

He is joined on the paper by co-lead author and fellow graduate student Aaron Young; graduate student Tzofi Klinghoffer; former postdoc Akshat Dave, who is now an assistant professor at Stony Brook University; Tomaso Poggio, the Eugene McDermott Professor in the Department of Brain and Cognitive Sciences, an investigator in the McGovern Institute, and co-director of the Center for Brains, Minds, and Machines; co-senior authors Brian Cheung, a postdoc in the  Center for Brains, Minds, and Machines and an incoming assistant professor at the University of California San Francisco; and Ramesh Raskar, associate professor of media arts and sciences and leader of the Camera Culture Group at MIT; as well as others at Rice University and Lund University. The research appears today in Science Advances.

Building a scientific sandbox

The paper began as a conversation among the researchers about discovering new vision systems that could be useful in different fields, like robotics. To test their “what-if” questions, the researchers decided to use AI to explore the many evolutionary possibilities.

“What-if questions inspired me when I was growing up to study science. With AI, we have a unique opportunity to create these embodied agents that allow us to ask the kinds of questions that would usually be impossible to answer,” Tiwary says.

To build this evolutionary sandbox, the researchers took all the elements of a camera, like the sensors, lenses, apertures, and processors, and converted them into parameters that an embodied AI agent could learn.

They used those building blocks as the starting point for an algorithmic learning mechanism an agent would use as it evolved eyes over time.

“We couldn’t simulate the entire universe atom-by-atom. It was challenging to determine which ingredients we needed, which ingredients we didn’t need, and how to allocate resources over those different elements,” Cheung says.

In their framework, this evolutionary algorithm can choose which elements to evolve based on the constraints of the environment and the task of the agent.

Each environment has a single task, such as navigation, food identification, or prey tracking, designed to mimic real visual tasks animals must overcome to survive. The agents start with a single photoreceptor that looks out at the world and an associated neural network model that processes visual information.

Then, over each agent’s lifetime, it is trained using reinforcement learning, a trial-and-error technique where the agent is rewarded for accomplishing the goal of its task. The environment also incorporates constraints, like a certain number of pixels for an agent’s visual sensors.

“These constraints drive the design process, the same way we have physical constraints in our world, like the physics of light, that have driven the design of our own eyes,” Tiwary says.

Over many generations, agents evolve different elements of vision systems that maximize rewards.

Their framework uses a genetic encoding mechanism to computationally mimic evolution, where individual genes mutate to control an agent’s development.

For instance, morphological genes capture how the agent views the environment and control eye placement; optical genes determine how the eye interacts with light and dictate the number of photoreceptors; and neural genes control the learning capacity of the agents.

Testing hypotheses

When the researchers set up experiments in this framework, they found that tasks had a major influence on the vision systems the agents evolved.

For instance, agents that were focused on navigation tasks developed eyes designed to maximize spatial awareness through low-resolution sensing, while agents tasked with detecting objects developed eyes focused more on frontal acuity, rather than peripheral vision.

Another experiment indicated that a bigger brain isn’t always better when it comes to processing visual information. Only so much visual information can go into the system at a time, based on physical constraints like the number of photoreceptors in the eyes.

“At some point a bigger brain doesn’t help the agents at all, and in nature that would be a waste of resources,” Cheung says.

In the future, the researchers want to use this simulator to explore the best vision systems for specific applications, which could help scientists develop task-specific sensors and cameras. They also want to integrate LLMs into their framework to make it easier for users to ask “what-if” questions and study additional possibilities.

“There’s a real benefit that comes from asking questions in a more imaginative way. I hope this inspires others to create larger frameworks, where instead of focusing on narrow questions that cover a specific area, they are looking to answer questions with a much wider scope,” Cheung says.

This work was supported, in part, by the Center for Brains, Minds, and Machines and the Defense Advanced Research Projects Agency (DARPA) Mathematics for the Discovery of Algorithms and Architectures (DIAL) program.

When Freesia Gaul discovered MIT Open Learning’s OpenCourseWare at just 14 years old, it opened up a world of learning far beyond what her classrooms could offer. Her parents had started a skiing company, and the seasonal work meant that Gaul had to change schools every six months. Growing up in small towns in Australia and Canada, she relied on the internet to fuel her curiosity.

“I went to 13 different schools, which was hard because you're in a different educational system every single time,” says Gaul. “That’s one of the reasons I gravitated toward online learning and teaching myself. Knowledge is something that exists beyond a curriculum.”

The small towns she lived in often didn’t have a lot of resources, she says, so a computer served as a main tool for learning. She enjoyed engaging with Wikipedia, ultimately researching topics and writing and editing content for pages. In 2018, she discovered MIT OpenCourseWare, part of MIT Open Learning, and took her first course. OpenCouseWare offers free, online, open educational resources from more than 2,500 MIT undergraduate and graduate courses. 

“I really got started with the OpenCourseWare introductory electrical engineering classes, because I couldn’t find anything else quite like it online,” says Gaul, who was initially drawn to courses on circuits and electronics, such as 6.002 (Circuits and Electronics) and 6.01SC (Introduction to Electrical Engineering and Computer Science). “It really helped me in terms of understanding how electrical engineering worked in a practical sense, and I just started modding things.”

In true MIT “mens et manus” (“mind and hand”) fashion, Gaul spent much of her childhood building and inventing, especially when she was able to access a 3D printer. She says that a highlight was when she built a life-sized, working version of a Mario Kart, constructed out of materials she had printed.

Gaul calls herself a “serial learner,” and has taken many OpenCourseWare courses. In addition to classes on circuits and electronics, she also took courses in linear algebra, calculus, and quantum physics — in which she took a particular interest. 

When she was 15, she participated in Qubit by Qubit. Hosted by The Coding School, in collaboration with universities (including MIT) and tech companies, this two-semester course introduces high schoolers to quantum computing and quantum physics. 

During that time she started a blog called On Zero, representing the “zero state” of a qubit. “The ‘zero state’ in a quantum computer is the representation of creativity from nothing, infinite possibilities,” says Gaul. For the blog, she found different topics and researched them in depth. She would think of a topic or question, such as “What is color?” and then explore it in great detail. What she learned eventually led her to start asking questions such as “What is a hamiltonian?” and teaching quantum physics alongside PhDs.

Building on these interests, Gaul chose to study quantum engineering at the University of New South Wales. She notes that on her first day of university, she participated in iQuHack, the MIT Quantum Hackathon. Her team worked to find a new way to approximate the value of a hyperbolic function using quantum logic, and received an honorable mention for “exceptional creativity.”

Gaul’s passion for making things continued during her college days, especially in terms of innovating to solve a problem. When she found herself on a train, wanting to code a personal website on a computer with a dying battery, she wondered if there might be a way to make a glove that can act as a type of Bluetooth keyboard — essentially creating a way to type in the air. In her spare time, she started working on such a device, ultimately finding a less expensive way to build a lightweight, haptic, gesture-tracking glove with applications for virtual reality (VR) and robotics.

Gaul says she has always had an interest in VR, using it to create her own worlds, reconstruct an old childhood house, and play Dungeons and Dragons with friends. She discovered a way to put into a glove some small linear resonant actuators, which can be found in a smartphone or gaming controller, and map to any object in VR so that the user can feel it.

An early prototype that Gaul put together in her dorm room received a lot of attention on YouTube. She went on to win the People’s Choice award for it at the SxSW Sydney 2025 Tech and Innovation Festival. This design also sparked her co-founding of the tech startup On Zero, named after her childhood blog dedicated to the love of creation from nothing.

Gaul sees the device, in general, as a way of “paying it forward,” making improved human-computer interaction available to many — from young students to professional technologists. She hopes to enable creative freedom in as many as she can. “The mind is just such a fun thing. I want to empower others to have the freedom to follow their curiosity, even if it's pointless on paper.

“I’ve benefited from people going far beyond what they needed to do to help me,” says Gaul. “I see OpenCourseWare as a part of that. The free courses gave me a solid foundation of knowledge and problem-solving abilities. Without these, it wouldn’t be possible to do what I’m doing now.”

Facing hospital closures, underfunded pediatric trials, and a persistent reliance on adult-oriented tools for children, the Hood Pediatric Innovation Hub welcomed nearly 200 leaders at Boston’s Museum of Science for MIT-Hood Pediatric Innovation 2025, an event focused on transforming the future of pediatric care through engineering and collaboration.

Hosted by the Hood Pediatric Innovation Hub — established at MIT through a gift by the Hood Foundation — the event brought together attendees from academia, health care, and industry to rethink how medical and technological breakthroughs can reach children faster. The gathering marked a new phase in the hub’s mission to connect scientific discovery with real-world impact.

“We have extraordinary science emerging every day, but the translation gap is widening,” said Joseph Frassica, professor of the practice in MIT’s Institute for Medical Engineering and Science and executive director of the Hood Pediatric Innovation Hub. “We can’t rely on the old model of innovation — we need new connective tissue between ideas, institutions, and implementation.”

Building collaboration across sectors

Speakers emphasized that pediatric medicine has long faced structural disadvantages compared with other fields — from smaller patient populations to limited commercial incentives. Yet they also described a powerful opportunity: to make pediatric innovation a proving ground for smarter, more human-centered health systems.

“The Hood Foundation has always believed that if you can improve care for children, you improve care for everyone,” said Neil Smiley, president of the Charles H. Hood Foundation. “Pediatrics pushes medicine to be smarter, more precise, and more humane — and that’s why this collaboration with MIT feels so right.”

Participants discussed how aligning efforts across universities, hospitals, and industry partners could help overcome the fragmentation that slows innovation, and ultimately translation. Speakers at the event highlighted case studies where cross-sector collaboration is already yielding results — from novel medical devices to data-driven clinical insights.

Connecting discovery to delivery

In his remarks, Elazer R. Edelman, the Edward J. Poitras Professor in Medical Engineering and Science at MIT and faculty lead for the Hood Pediatric Innovation Hub, reflected on how MIT’s engineering and medical communities can help close the loop between research and clinical application.

“This isn’t about creating something new for the sake of it — it’s about finally connecting the extraordinary expertise that already exists, from the lab to the clinic to the child’s bedside,” Edelman said. “That’s what MIT does best — we connect the dots.”

Throughout the day, attendees shared experiences from both the engineering and clinical viewpoints — acknowledging the complexities of regulation, funding, and adoption, while highlighting the shared responsibility to move faster on behalf of children.

A moment of convergence

The conversation also turned to the economics of innovation and the broader societal benefits of investing in pediatric health.

“The economic and social stakes couldn’t be higher,” said Jonathan Gruber, Ford Professor of Economics at MIT. “When we invest in children’s health, we invest in longer lives, stronger communities, and greater prosperity. The energy in this room shows what’s possible when we stop working in silos.”

By the end of the event, discussions had shifted from identifying barriers to designing solutions. Participants explored ideas ranging from translational fellowships and shared data platforms to new models for academic–industry partnership — each aimed at accelerating impact where it is needed most.

Looking ahead

“There’s a feeling that this is the moment,” Frassica said. “We have the tools, the data, and the will to transform how we care for children. The key now is keeping that spirit of collaboration alive — because when we do, we move the whole field forward.”

Building on the momentum from MIT-Hood Pediatric Innovation 2025, the Hood Pediatric Innovation Hub will continue to serve as a connector across disciplines and institutions, advancing projects that translate cutting-edge research into improved outcomes for children everywhere. In January, a new cohort of MIT Catalyst Fellows — early-career researchers embedded with frontline clinicians to identify unmet needs — will begin exploring solutions to challenges in pediatric and neonatal health care in partnership with the hub. 

This work is also part of a wider Institute effort. The Hood Pediatric Innovation Hub contributes to the broader mission of the MIT Health and Life Sciences Collaborative (HEALS), which brings together faculty, clinicians, and industry partners to accelerate breakthroughs across all areas of human health. As the hub deepens its own collaborations, its connection to HEALS helps ensure that advances in pediatric medicine are integrated into MIT’s larger push to improve health outcomes at scale.

The hub will also release a request for proposals in the coming months for the development of its first mentored projects — designed to bring together teams from engineering, medicine, and industry to accelerate progress in children’s health. Updates and details will be available at hoodhub.mit.edu.

As Smiley noted, progress in pediatric health often drives progress across all of medicine — and this gathering underscored that shared belief: when we work together for children, we build a healthier future for everyone.

As people age, their immune system function declines. T cell populations become smaller and can’t react to pathogens as quickly, making people more susceptible to a variety of infections.

To try to overcome that decline, researchers at MIT and the Broad Institute have found a way to temporarily program cells in the liver to improve T-cell function. This reprogramming can compensate for the age-related decline of the thymus, where T cell maturation normally occurs.

Using mRNA to deliver three key factors that usually promote T-cell survival, the researchers were able to rejuvenate the immune systems of mice. Aged mice that received the treatment showed much larger and more diverse T cell populations in response to vaccination, and they also responded better to cancer immunotherapy treatments.

If developed for use in patients, this type of treatment could help people lead healthier lives as they age, the researchers say.

“If we can restore something essential like the immune system, hopefully we can help people stay free of disease for a longer span of their life,” says Feng Zhang, the James and Patricia Poitras Professor of Neuroscience at MIT, who has joint appointments in the departments of Brain and Cognitive Sciences and Biological Engineering.

Zhang, who is also an investigator at the McGovern Institute for Brain Research at MIT, a core institute member at the Broad Institute of MIT and Harvard, an investigator in the Howard Hughes Medical Institute, and co-director of the K. Lisa Yang and Hock E. Tan Center for Molecular Therapeutics at MIT, is the senior author of the new study. Former MIT postdoc Mirco Friedrich is the lead author of the paper, which appears today in Nature.

A temporary factory

The thymus, a small organ located in front of the heart, plays a critical role in T-cell development. Within the thymus, immature T cells go through a checkpoint process that ensures a diverse repertoire of T cells. The thymus also secretes cytokines and growth factors that help T cells to survive.

However, starting in early adulthood, the thymus begins to shrink. This process, known as thymic involution, leads to a decline in the production of new T cells. By the age of approximately 75, the thymus is greatly reduced.

“As we get older, the immune system begins to decline. We wanted to think about how can we maintain this kind of immune protection for a longer period of time, and that's what led us to think about what we can do to boost immunity,” Friedrich says.

Previous work on rejuvenating the immune system has focused on delivering T cell growth factors into the bloodstream, but that can have harmful side effects. Researchers are also exploring the possibility of using transplanted stem cells to help regrow functional tissue in the thymus.

The MIT team took a different approach: They wanted to see if they could create a temporary “factory” in the body that would generate the T-cell-stimulating signals that are normally produced by the thymus.

“Our approach is more of a synthetic approach,” Zhang says. “We're engineering the body to mimic thymic factor secretion.”

For their factory location, they settled on the liver, for several reasons. First, the liver has a high capacity for producing proteins, even in old age. Also, it’s easier to deliver mRNA to the liver than to most other organs of the body. The liver was also an appealing target because all of the body’s circulating blood has to flow through it, including T cells.

To create their factory, the researchers identified three immune cues that are important for T-cell maturation. They encoded these three factors into mRNA sequences that could be delivered by lipid nanoparticles. When injected into the bloodstream, these particles accumulate in the liver and the mRNA is taken up by hepatocytes, which begin to manufacture the proteins encoded by the mRNA.

The factors that the researchers delivered are DLL1, FLT-3, and IL-7, which help immature progenitor T cells mature into fully differentiated T cells.

Immune rejuvenation

Tests in mice revealed a variety of beneficial effects. First, the researchers injected the mRNA particles into 18-month-old mice, equivalent to humans in their 50s. Because mRNA is short-lived, the researchers gave the mice multiple injections over four weeks to maintain a steady production by the liver.

After this treatment, T cell populations showed significant increases in size and function.

The researchers then tested whether the treatment could enhance the animals’ response to vaccination. They vaccinated the mice with ovalbumin, a protein found in egg whites that is commonly used to study how the immune system responds to a specific antigen. In 18-month-old mice that received the mRNA treatment before vaccination, the researchers found that the population of cytotoxic T-cells specific to ovalbumin doubled, compared to mice of the same age that did not receive the mRNA treatment.

The mRNA treatment can also boost the immune system’s response to cancer immunotherapy, the researchers found. They delivered the mRNA treatment to 18-month-old mice, who were then implanted with tumors and treated with a checkpoint inhibitor drug. This drug, which targets the protein PD-L1, is designed to help take the brakes off the immune system and stimulate T cells to attack tumor cells.

Mice that received the treatment showed much higher survival rates and longer lifespan that those that received the checkpoint inhibitor drug but not the mRNA treatment.

The researchers found that all three factors were necessary to induce this immune enhancement; none could achieve all aspects of it on their own. They now plan to study the treatment in other animal models and to identify additional signaling factors that may further enhance immune system function. They also hope to study how the treatment affects other immune cells, including B cells.

Other authors of the paper include Julie Pham, Jiakun Tian, Hongyu Chen, Jiahao Huang, Niklas Kehl, Sophia Liu, Blake Lash, Fei Chen, Xiao Wang, and Rhiannon Macrae.

The research was funded, in part, by the Howard Hughes Medical Institute, the K. Lisa Yang Brain-Body Center, part of the Yang Tan Collective at MIT, Broad Institute Programmable Therapeutics Gift Donors, the Pershing Square Foundation, J. and P. Poitras, and an EMBO Postdoctoral Fellowship.