“This is science!” – MIT president talks about the importance of America’s research enterprise on GBH’s Boston Public Radio

In a wide-ranging live conversation, MIT President Sally Kornbluth joined Jim Braude and Margery Eagan live in studio for GBH’s Boston Public Radio on Thursday, February 5. They talked about MIT, the pressures facing America’s research enterprise, the importance of science, that Congressional hearing on antisemitism in 2023, and more – including Sally’s experience as a Type 1 diabetic.

Reflecting on how research and innovation in the treatment of diabetes has advanced over decades of work, leading to markedly better patient care, Kornbluth exclaims: “This is science!”

With new financial pressures facing universities, increased competition for talented students and scholars from outside the U.S., as well as unprecedented pressures on university leaders and campuses, co-host Eagan asks Kornbluth what she thinks will happen in years to come.

“For us, one of the hardest things now is the endowment tax,” remarks Kornbluth. “That is $240 million a year. Think about how much science you can get for $240 million a year. Are we managing it? Yes. Are we still forging ahead on all of our exciting initiatives? Yes. But we’ve had to reconfigure things. We’ve had to merge things. And it’s not the way we should be spending our time and money.”   

Watch and listen to the full episode on YouTube. President Kornbluth appears one hour and seven minutes into the broadcast.

Following Kornbluth’s appearance, MIT Assistant Professor John Urschel – also a former offensive lineman for the Baltimore Ravens –   joined Edgar B. Herwick III, host of GBH’s newest show, The Curiosity Desk, to talk about his love of his family, linear algebra, and football.

On how he eventually chose math over football, Urschel quips: “Well, I hate to break it to you, I like math better… let me tell you, when I started my PhD at MIT, I just fell in love with the place. I fell in love with this idea of being in this environment [where] everyone loves math, everyone wants to learn. I was just constantly excited every day showing up.”

Prof. Urschel appears about 2 hours and 40 minutes into the webcast on YouTube.

Coming up on Curiosity Desk later this month…

Airing weekday afternoons from 1-2 p.m., The Curiosity Desk will welcome additional MIT guests in the coming weeks. On Thursday, Feb. 12 Anette “Peko” Hosoi, Pappalardo Professor of Mechanical Engineering, and Jerry Lu MFin ’24, a former researcher at the MIT Sports Lab, visit The Curiosity Desk to discuss their work using AI to help Olympic figure skaters improve their jumps.

Then, on Thursday, Feb. 19, Professors Sangeeta Bhatia and Angela Belcher talk with Herwick about their research to improve diagnostics for ovarian cancer. We learn that about 80% of the time ovarian cancer starts in the fallopian tubes and how this points the way to a whole new approach to diagnosing and treating the disease. 

MIT News · Curiosity Desk Preview
Source: GBH 

de MIT News https://ift.tt/frEd3P9

I’m walking here! A new model maps foot traffic in New York City

Early in the 1969 film “Midnight Cowboy,” Dustin Hoffman, playing the character of Ratso Rizzo, crosses a Manhattan street and angrily bangs on the hood of an encroaching taxi. Hoffman’s line — “I’m walking here!” — has since been repeated by thousands of New Yorkers. Where cars and people mix, tensions rise.

And yet, governments and planners across the U.S. haven’t thoroughly tracked where it is that cars and people mix. Officials have long measured vehicle traffic closely while largely ignoring pedestrian traffic. Now, an MIT research group has assembled a routable dataset of sidewalks, crosswalks, and footpaths for all of New York City — a massive mapping project and the first complete model of pedestrian activity in any U.S. city.

The model could help planners decide where to make pedestrian infrastructure and public space investments, and illuminate how development decisions could affect non-motorized travel in the city. The study also helps pinpoint locations throughout the city where there are both lots of pedestrians and high pedestrian hazards, such as traffic crashes, and where streets or intersections are most in need of upgrades.

“We now have a first view of foot traffic all over New York City and can check planning decisions against it,” says Andres Sevtsuk, an associate professor in MIT’s Department of Urban Studies and Planning (DUSP), who led the study. “New York has very high densities of foot traffic outside of its most well-known areas.”

Indeed, one upshot of the model is that while Manhattan has the most foot traffic per block, the city’s other boroughs contain plenty of pedestrian-heavy stretches of sidewalk and could probably use more investment on behalf of walkers.

“Midtown Manhattan has by far the most foot traffic, but we found there is a probably unintentional Manhattan bias when it comes to policies that support pedestrian infrastructure,” Sevtsuk says. “There are a whole lot of streets in New York with very high pedestrian volumes outside of Manhattan, whether in Queens or the Bronx or Brooklyn, and we’re able to show, based on data, that a lot of these streets have foot-traffic levels similar to many parts of Manhattan.”

And, in an advance that could help cities anywhere, the model was used to quantify vehicle crashes involving pedestrians not only as raw totals, but on a per-pedestrian basis.

“A lot of cities put real investments behind keeping pedestrians safe from vehicles by prioritizing dangerous locations,” Sevtsuk says. “But that’s not only where the most crashes occur. Here we are able to calculate accidents per pedestrian, the risk people face, and that broadens the picture in terms of where the most dangerous intersections for pedestrians really are.”

The paper, “Spatial Distribution of Foot-traffic in New York City and Applications for Urban Planning,” is published today in Nature Cities.

The authors are Sevtsuk, the Charles and Ann Spaulding Associate Professor of Urban Science and Planning in DUSP and head of the City Design and Development Group; Rounaq Basu, an assistant professor at Georgia Tech; Liu Liu, a PhD student at the City Form Lab in DUSP; Abdulaziz Alhassan, a PhD student at MIT’s Center for Complex Engineering Systems; and Justin Kollar, a PhD student at MIT’s Leventhal Center for Advanced Urbanism in DUSP.

Walking everywhere

The current study continues work Sevtsuk and his colleagues have conducted charting and modeling pedestrian traffic around the world, from Melbourne to MIT’s Kendall Square neighborhood in Cambridge, Massachusetts. Many cities collect some pedestrian count data — but not much. And while officials usually request vehicle traffic impact assessments for new development plans, they rarely study how new developments or infrastructure proposals affect pedestrians.

However, New York City does devote part of its Department of Transportation (DOT) to pedestrian issues, and about 41 percent of trips city-wide are made on foot, compared to just 28 percent by vehicle, likely the highest such ratio in any big U.S. city. To calibrate the model, the MIT team used pedestrian counts that New York City’s DOT recorded in 2018 and 2019, covering up to 1,000 city sidewalk segments on weekdays and up to roughly 450 segments on weekends.

The researchers were able to test the model — which incorporates a wide range of factors — against New York City’s pedestrian-count data. Once calibrated, the model could expand foot-traffic estimates throughout the whole city, not just the points where pedestrian counts were observed.

The results showed that in Midtown Manhattan, there are about 1,697 pedestrians, on average, per sidewalk segment per hour during the evening peak of foot traffic, the highest in the city. The financial district in lower Manhattan comes in second, at 740 pedestrians per hour, with Greenwich Village third at 656.

Other parts of Manhattan register lower levels of foot traffic, however. Morningside Heights and East Harlem register 226 and 227 pedestrians per block per hour. And that’s similar to, or lower than, some parts of other boroughs. Brooklyn Heights has 277 pedestrians per sidewalk segment per hour; University Heights in the Bronx has 263; Borough Park in Brooklyn and the Grand Concourse in the Bronx average 236; and a slice of Queens in the Corona area averages 222. Many other spots are over 200.

The model overlays many different types of pedestrian journeys for each time period and shows that people are generally headed to work and schools in the morning, but conduct more varied types of trips in mid-day and the evening, as they seek out amenities or conduct social or recreational visits.

“Because of jobs, transit stops are the biggest generators of foot traffic in the morning peak,” Liu observes. “In the evening peak, of course people need to get home too, but patterns are much more varied, and people are not just returning from work or school. More social and recreational travel happens after work, whether it’s getting together with friends or running errands for family or family care trips, and that’s what the model detects too.”

On the safety front, pedestrians face danger in many places, not just the intersections with the most total accidents. Many parts of the city are riskier than others on a per-pedestrian basis, compared to the locations with the most pedestrian-related crashes.

“Places like Times Square and Herald Square in Manhattan may have numerous crashes, but they have very high pedestrian volumes, and it’s actually relatively safe to walk there,” Basu says. “There are other parts of the city, around highway off-ramps and heavy car-infrastructure, including the relatively low-density borough of Staten Island, which turn out to have a disproportionate number of crashes per pedestrian.”

Taking the model across the U.S.

The MIT model stands a solid chance of being applied in New York City policy and planning circles, since officials there are aware of the research and have been regularly communicating with the MIT team about it.

For his part, Sevtsuk emphasizes that, as distinct as New York City might be, the MIT model can be applied to cities and town anywhere in the U.S. As it happens, the team is working with municipal officials in two other places at the moment. One is Los Angeles, where city officials are not only trying to upgrade pedestrian and public transit mobility for regular daily trips, but making plans to handle an influx of visitors for the 2028 summer Olympics.

Meanwhile the state of Maine is working with the MIT team to evaluate pedestrian movement in over 140 of its cities and towns, to better understand the kinds of upgrades and safety improvements it could make for pedestrians across the state. Sevtsuk hopes that still other places will take notice of the New York City study and recognize that the tools are in place to analyze foot traffic more broadly in U.S. cities, to address the urgent need to decarbonize cities, and to start balancing what he views as the disproportionate focus on car travel prevalent in 20th century urban planning.

“I hope this can inspire other cities to invest in modeling foot traffic and mapping pedestrian infrastructure as well,” Sevtsuk says. “Very few cities make plans for pedestrian mobility or examine rigorously how future developments will impact foot-traffic. But they can. Our models serve as a test bed for making future changes.” 

de MIT News https://ift.tt/mwSefEo

Some early life forms may have breathed oxygen well before it filled the atmosphere

Oxygen is a vital and constant presence on Earth today. But that hasn’t always been the case. It wasn’t until around 2.3 billion years ago that oxygen became a permanent fixture in the atmosphere, during a pivotal period known as the Great Oxidation Event (GOE), which set the evolutionary course for oxygen-breathing life as we know it today.

A new study by MIT researchers suggests some early forms of life may have evolved the ability to use oxygen hundreds of millions of years before the GOE. The findings may represent some of the earliest evidence of aerobic respiration on Earth.

In a study appearing today in the journal Palaeogeography, Palaeoclimatology, Palaeoecology, MIT geobiologists traced the evolutionary origins of a key enzyme that enables organisms to use oxygen. The enzyme is found in the vast majority of aerobic, oxygen-breathing life forms today. The team discovered that this enzyme evolved during the Mesoarchean — a geological period that predates the Great Oxidation Event by hundreds of millions of years.

The team’s results may help to explain a longstanding puzzle in Earth’s history: Why did it take so long for oxygen to build up in the atmosphere?

The very first producers of oxygen on the planet were cyanobacteria — microbes that evolved the ability to use sunlight and water to photosynthesize, releasing oxygen as a byproduct. Scientists have determined that cyanobacteria emerged around 2.9 billion years ago. The microbes, then, were presumably churning out oxygen for hundreds of millions of years before the Great Oxidation Event. So, where did all of cyanobacteria’s early oxygen go?

Scientists suspect that rocks may have drawn down a large portion of oxygen early on, through various geochemical reactions. The MIT team’s new study now suggests that biology may have also played a role.

The researchers found that some organisms may have evolved the enzyme to use oxygen hundreds of millions of years before the Great Oxidation Event. This enzyme may have enabled the organisms living near cyanobacteria to gobble up any small amounts of oxygen that the microbes produced, in turn delaying oxygen’s accumulation in the atmosphere for hundreds of millions of years.

“This does dramatically change the story of aerobic respiration,” says study co-author Fatima Husain, a postdoc in MIT’s Department of Earth, Atmospheric and Planetary Sciences (EAPS). “Our study adds to this very recently emerging story that life may have used oxygen much earlier than previously thought. It shows us how incredibly innovative life is at all periods in Earth’s history.”

The study’s other co-authors include Gregory Fournier, associate professor of geobiology at MIT, along with Haitao Shang and Stilianos Louca of the University of Oregon.

First respirers

The new study adds to a long line of work at MIT aiming to piece together oxygen’s history on Earth. This body of research has helped to pin down the timing of the Great Oxidation Event as well as the first evidence of oxygen-producing cyanobacteria. The overall understanding that has emerged is that oxygen was first produced by cyanobacteria around 2.9 billion years ago, while the Great Oxidation Event — when oxygen finally accumulated enough to persist in the atmosphere — took place much later, around 2.33 billion years ago.

For Husain and her colleagues, this apparent delay between oxygen’s first production and its eventual persistence inspired a question.

“We know that the microorganisms that produce oxygen were around well before the Great Oxidation Event,” Husain says. “So it was natural to ask, was there any life around at that time that could have been capable of using that oxygen for aerobic respiration?”

If there were in fact some life forms that were using oxygen, even in small amounts, they might have played a role in keeping oxygen from building up in the atmosphere, at least for a while.

To investigate this possibility, the MIT team looked to heme-copper oxygen reductases, which are a set of enzymes that are essential for aerobic respiration. The enzymes act to reduce oxygen to water, and they are found in the majority of aerobic, oxygen-breathing organism today, from bacteria to humans.

“We targeted the core of this enzyme for our analyses because that’s where the reaction with oxygen is actually taking place,” Husain explains.

Tree dates

The team aimed to trace the enzyme’s evolution backward in time to see when the enzyme first emerged to enable organisms to use oxygen. They first identified the enzyme’s genetic sequence and then used an automated search tool to look for this same sequence in databases containing the genomes of millions of different species of organisms.

“The hardest part of this work was that we had too much data,” Fournier says. “This enzyme is just everywhere and is present in most modern living organism. So we had to sample and filter the data down to a dataset that was representative of the diversity of modern life and also small enough to do computation with, which is not trivial.”

The team ultimately isolated the enzyme’s sequence from several thousand modern species and mapped these sequences onto an evolutionary tree of life, based on what scientists know about when each respective species has likely evolved and branched off. They then looked through this tree for specific species that might offer related information about their origins.

If, for instance, there is a fossil record for a particular organism on the tree, that record would include an estimate of when that organism appeared on Earth. The team would use that fossil’s age to “pin” a date to that organism on the tree. In a similar way, they could place pins across the tree to effectively tighten their estimates for when in time the enzyme evolved from one species to the next.

In the end, the researchers were able to trace the enzyme as far back as the Mesoarchean — a geological era that lasted from 3.2 to 2.8 billion years ago. It’s around this time that the team suspects the enzyme — and organisms’ ability to use oxygen — first emerged. This period predates the Great Oxidation Event by several hundred million years.

The new findings suggest that, shortly after cyanobacteria evolved the ability to produce oxygen, other living things evolved the enzyme to use that oxygen. Any such organism that happened to live near cyanobacteria would have been able to quickly take up the oxygen that the bacteria churned out. These early aerobic organisms may have then played some role in preventing oxygen from escaping to the atmosphere, delaying its accumulation for hundreds of millions of years.

“Considered all together, MIT research has filled in the gaps in our knowledge of how Earth’s oxygenation proceeded,” Husain says. “The puzzle pieces are fitting together and really underscore how life was able to diversify and live in this new, oxygenated world.”

This research was supported, in part, by the Research Corporation for Science Advancement Scialog program.

de MIT News https://ift.tt/m96ASXY

Helping AI agents search to get the best results out of large language models

Whether you’re a scientist brainstorming research ideas or a CEO hoping to automate a task in human resources or finance, you’ll find that artificial intelligence tools are becoming the assistants you didn’t know you needed. In particular, many professionals are tapping into the talents of semi-autonomous software systems called AI agents, which can call on AI at specific points to solve problems and complete tasks.

AI agents are particularly effective when they use large language models (LLMs) because those systems are powerful, efficient, and adaptable. One way to program such technology is by describing in code what you want your system to do (the “workflow”), including when it should use an LLM. If you were a software company trying to revamp your old codebase to use a more modern programming language for better optimizations and safety, you might build a system that uses an LLM to translate the codebase one file at a time, testing each file as you go.

But what happens when LLMs make mistakes? You’ll want the agent to backtrack to make another attempt, incorporating lessons it learned from previous mistakes. Coding this up can take as much effort as implementing the original agent; if your system for translating a codebase contained thousands of lines of code, then you’d be making thousands of lines of code changes or additions to support the logic for backtracking when LLMs make mistakes. 

To save programmers time and effort, researchers with MIT’s Computer Science and Artificial Intelligence Laboratory (CSAIL) and Asari AI have developed a framework called “EnCompass.” 

With EnCompass, you no longer have to make these changes yourself. Instead, when EnCompass runs your program, it automatically backtracks if LLMs make mistakes. EnCompass can also make clones of the program runtime to make multiple attempts in parallel in search of the best solution. In full generality, EnCompass searches over the different possible paths your agent could take as a result of the different possible outputs of all the LLM calls, looking for the path where the LLM finds the best solution.

Then, all you have to do is to annotate the locations where you may want to backtrack or clone the program runtime, as well as record any information that may be useful to the strategy used to search over the different possible execution paths of your agent (the search strategy). You can then separately specify the search strategy — you could either use one that EnCompass provides out of the box or, if desired, implement your own custom search strategy.

“With EnCompass, we’ve separated the search strategy from the underlying workflow of an AI agent,” says lead author Zhening Li ’25, MEng ’25, who is an MIT electrical engineering and computer science (EECS) PhD student, CSAIL researcher, and research consultant at Asari AI. “Our framework lets programmers easily experiment with different search strategies to find the one that makes the AI agent perform the best.” 

EnCompass was used for agents implemented as Python programs that call LLMs, where it demonstrated noticeable code savings. EnCompass reduced coding effort for implementing search by up to 80 percent across agents, such as an agent for translating code repositories and for discovering transformation rules of digital grids. In the future, EnCompass could enable agents to tackle large-scale tasks, including managing massive code libraries, designing and carrying out science experiments, and creating blueprints for rockets and other hardware.

Branching out

When programming your agent, you mark particular operations — such as calls to an LLM — where results may vary. These annotations are called “branchpoints.” If you imagine your agent program as generating a single plot line of a story, then adding branchpoints turns the story into a choose-your-own-adventure story game, where branchpoints are locations where the plot branches into multiple future plot lines. 

You can then specify the strategy that EnCompass uses to navigate that story game, in search of the best possible ending to the story. This can include launching parallel threads of execution or backtracking to a previous branchpoint when you get stuck in a dead end.

Users can also plug-and-play a few common search strategies provided by EnCompass out of the box, or define their own custom strategy. For example, you could opt for Monte Carlo tree search, which builds a search tree by balancing exploration and exploitation, or beam search, which keeps the best few outputs from every step. EnCompass makes it easy to experiment with different approaches to find the best strategy to maximize the likelihood of successfully completing your task.

The coding efficiency of EnCompass

So just how code-efficient is EnCompass for adding search to agent programs? According to researchers’ findings, the framework drastically cut down how much programmers needed to add to their agent programs to add search, helping them experiment with different strategies to find the one that performs the best.

For example, the researchers applied EnCompass to an agent that translates a repository of code from the Java programming language, which is commonly used to program apps and enterprise software, to Python. They found that implementing search with EnCompass — mainly involving adding branchpoint annotations and annotations that record how well each step did — required 348 fewer lines of code (about 82 percent) than implementing it by hand. They also demonstrated how EnCompass enabled them to easily try out different search strategies, identifying the best strategy to be a two-level beam search algorithm, achieving an accuracy boost of 15 to 40 percent across five different repositories at a search budget of 16 times the LLM calls made by the agent without search.

“As LLMs become a more integral part of everyday software, it becomes more important to understand how to efficiently build software that leverages their strengths and works around their limitations,” says co-author Armando Solar-Lezama, who is an MIT professor of EECS and CSAIL principal investigator. “EnCompass is an important step in that direction.”

The researchers add that EnCompass targets agents where a program specifies the steps of the high-level workflow; the current iteration of their framework is less applicable to agents that are entirely controlled by an LLM. “In those agents, instead of having a program that specifies the steps and then using an LLM to carry out those steps, the LLM itself decides everything,” says Li. “There is no underlying programmatic workflow, so you can execute inference-time search on whatever the LLM invents on the fly. In this case, there’s less need for a tool like EnCompass that modifies how a program executes with search and backtracking.”

Li and his colleagues plan to extend EnCompass to more general search frameworks for AI agents. They also plan to test their system on more complex tasks to refine it for real-world uses, including at companies. What’s more, they’re evaluating how well EnCompass helps agents work with humans on tasks like brainstorming hardware designs or translating much larger code libraries. For now, EnCompass is a powerful building block that enables humans to tinker with AI agents more easily, improving their performance.

“EnCompass arrives at a timely moment, as AI-driven agents and search-based techniques are beginning to reshape workflows in software engineering,” says Carnegie Mellon University Professor Yiming Yang, who wasn’t involved in the research. “By cleanly separating an agent’s programming logic from its inference-time search strategy, the framework offers a principled way to explore how structured search can enhance code generation, translation, and analysis. This abstraction provides a solid foundation for more systematic and reliable search-driven approaches to software development.”  

Li and Solar-Lezama wrote the paper with two Asari AI researchers: Caltech Professor Yisong Yue, an advisor at the company; and senior author Stephan Zheng, who is the founder and CEO. Their work was supported by Asari AI.

The team’s work was presented at the Conference on Neural Information Processing Systems (NeurIPS) in December.

de MIT News https://ift.tt/WUQb9RN

New vaccine platform promotes rare protective B cells

A longstanding goal of immunotherapies and vaccine research is to induce antibodies in humans that neutralize deadly viruses such as HIV and influenza. Of particular interest are antibodies that are “broadly neutralizing,” meaning they can in principle eliminate multiple strains of a virus such as HIV, which mutates rapidly to evade the human immune system.

Researchers at MIT and the Scripps Research Institute have now developed a vaccine that generates a significant population of rare precursor B cells that are capable of evolving to produce broadly neutralizing antibodies. Expanding these cells is the first step toward a successful HIV vaccine.

The researchers’ vaccine design uses DNA instead of protein as a scaffold to fabricate a virus-like particle (VLP) displaying numerous copies of an engineered HIV immunogen called eOD-GT8, which was developed at Scripps. This vaccine generated substantially more precursor B cells in a humanized mouse model compared to a protein-based virus-like particle that has shown significant success in human clinical trials.

Preclinical studies showed that the DNA-VLP generated eight times more of the desired, or “on-target,” B cells than the clinical product, which was already shown to be highly potent.

“We were all surprised that this already outstanding VLP from Scripps was significantly outperformed by the DNA-based VLP,” says Mark Bathe, an MIT professor of biological engineering and an associate member of the Broad Institute of MIT and Harvard. “These early preclinical results suggest a potential breakthrough as an entirely new, first-in-class VLP that could transform the way we think about active immunotherapies, and vaccine design, across a variety of indications.”

The researchers also showed that the DNA scaffold doesn’t induce an immune response when applied to the engineered HIV antigen. This means the DNA VLP might be used to deliver multiple antigens when boosting strategies are needed, such as for challenging diseases such as HIV.

“The DNA-VLP allowed us for the first time to assess whether B cells targeting the VLP itself limit the development of ‘on target’ B cell responses — a longstanding question in vaccine immunology,” says Darrell Irvine, a professor of immunology and microbiology at the Scripps Research Institute and a Howard Hughes Medical Institute Investigator.

Bathe and Irvine are the senior authors of the study, which appears today in Science. The paper’s lead author is Anna Romanov PhD ’25.

Priming B cells

The new study is part of a major ongoing global effort to develop active immunotherapies and vaccines that expand specific lineages of B cells. All humans have the necessary genes to produce the right B cells that can neutralize HIV, but they are exceptionally rare and require many mutations to become broadly neutralizing. If exposed to the right series of antigens, however, these cells can in principle evolve to eventually produce the requisite broadly neutralizing antibodies.

In the case of HIV, one such target antibody, called VRC01, was discovered by National Institutes of Health researchers in 2010 when they studied humans living with HIV who did not develop AIDS. This set off a major worldwide effort to develop an HIV vaccine that would induce this target antibody, but this remains an outstanding challenge.

Generating HIV-neutralizing antibodies is believed to require three stages of vaccination, each one initiated by a different antigen that helps guide B cell evolution toward the correct target, the native HIV envelope protein gp120.

In 2013, William Schief, a professor of immunology and microbiology at Scripps, reported an engineered antigen called eOD-GT6 that could be used for the first step in this process, known as priming. His team subsequently upgraded the antigen to eOD-GT8. Vaccination with eOD-GT8 arrayed on a protein VLP generated early antibody precursors to VRC01 both in mice and more recently in humans, a key first step toward an HIV vaccine.

However, the protein VLP also generated substantial “off-target” antibodies that bound the irrelevant, and potentially highly distracting, protein VLP itself. This could have unknown consequences on propagating target B cells of interest for HIV, as well as other challenging immunotherapy applications.

The Bathe and Irvine labs set out to test if they could use a particle made from DNA, instead of protein, to deliver the priming antigen. These nanoscale particles are made using DNA origami, a method that offers precise control over the structure of synthetic DNA and allows researchers to attach viral antigens at specific locations.

In 2024, Bathe and Daniel Lingwood, an associate professor at Harvard Medical School and a principal investigator at the Ragon Institute, showed this DNA VLP could be used to deliver a SARS-CoV-2 vaccine in mice to generate neutralizing antibodies. From that study, the researchers learned that the DNA scaffold does not induce antibodies to the VLP itself, unlike proteins. They wondered whether this might also enable a more focused antibody response.

Building on these results, Romanov, co-advised by Bathe and Irvine, set off to apply the DNA VLP to the Scripps HIV priming vaccine, based on eOD-GT8.

“Our earlier work with SARS-CoV-2 antigens on DNA-VLPs showed that DNA-VLPs can be used to focus the immune response on an antigen of interest. This property seemed especially useful for a case like HIV, where the B cells of interest are exceptionally rare. Thus, we hypothesized that reducing the competition among other irrelevant B cells (by delivering the vaccine on a silent DNA nanoparticle) may help these rare cells have a better chance to survive,”  Romanov says.

Initial studies in mice, however, showed the vaccine did not induce sufficient early B cell response to the first, priming dose.

After redesigning the DNA VLPs, Romanov and colleagues found that a smaller diameter version with 60 instead of 30 copies of the engineered antigen dramatically out-performed the clinical protein VLP construct, both in overall number of antigen-specific B cells and the fraction of B cells that were on-target to the specific HIV domain of interest. This was a result of improved retention of the particles in B cell follicles in lymph nodes and better collaboration with helper T cells, which promote B cell survival.

Overall, these improvements enabled the particles to generate eightfold more on-target B cells than the vaccine consisting of eOD-GT8 carried by a protein scaffold. Another key finding, elucidated by the Lingwood lab, was that the DNA particles promoted VRC01 precursor B cells toward the VRC01 antibody more efficiently than the protein VLP.

“In the field of vaccine immunology, the question of whether B cell responses to a targeted protective epitope on a vaccine antigen might be hindered by responses to neighboring off-target epitopes on the same antigen has been under intense investigation,” says Schief, who is also vice president for protein design at Moderna. “There are some data from other studies suggesting that off-target responses might not have much impact, but this study shows quite convincingly that reducing off-target responses by using a DNA VLP can improve desired on-target responses.”

“While nanoparticle formulations have been great at boosting antibody responses to various antigens, there is always this nagging question of whether competition from B cells specific for the particle’s own structural antigens won’t get in the way of antibody responses to targeted epitopes,” says Gabriel Victora, a professor of immunology, virology, and microbiology at Rockefeller University, who was not involved in the study. “DNA-based particles that leverage B cells’ natural tolerance to nucleic acids are a clever idea to circumvent this problem, and the research team’s elegant experiments clearly show that this strategy can be used to make difficult epitopes easier to target.”

A “silent” scaffold

The fact that the DNA-VLP scaffold doesn’t induce scaffold-specific antibodies means that it could be used to carry second and potentially third antigens needed in the vaccine series, as the researchers are currently investigating. It also might offer significantly improved on-target antibodies for numerous antigens that are outcompeted and dominated by off-target, irrelevant protein VLP scaffolds in this or other applications.

“A breakthrough of this paper is the rigorous, mechanistic quantification of how DNA-VLPs can ‘focus’ antibody responses on target antigens of interest, which is a consequence of the silent nature of this DNA-based scaffold we’ve previously shown is stealth to the immune system,” Bathe says.

More broadly, this new type of VLP could be used to generate other kinds of protective antibody responses against pandemic threats such as flu, or potentially against chemical warfare agents, the researchers suggest. Alternatively, it might be used as an active immunotherapy to generate antibodies that target amyloid beta or tau protein to treat degenerative diseases such as Alzheimer’s, or to generate antibodies that target noxious chemicals such as opioids or nicotine to help people suffering from addiction.

The research was funded by the National Institutes of Health; the Ragon Institute of MGH, MIT, and Harvard; the Howard Hughes Medical Institute; the National Science Foundation; the Novo Nordisk Foundation; a Koch Institute Support (core) Grant from the National Cancer Institute; the National Institute of Environmental Health Sciences; the Gates Foundation Collaboration for AIDS Vaccine Discovery; the IAVI Neutralizing Antibody Center; the National Institute of Allergy and Infectious Diseases; and the U.S. Army Research Office through MIT’s Institute for Soldier Nanotechnologies.

de MIT News https://ift.tt/jeIP1AF

“Essential” torch heralds the start of the 2026 Winter Olympics

Before the thrill of victory; before the agony of defeat; before the gold medalist’s national anthem plays, there is the Olympic torch. A symbol of unity, friendship, and the spirit of competition, the torch links today’s Olympic Games to its heritage in ancient Greece.

The torch for the 2026 Milano Cortina Olympic Games and Paralympic Games was designed by Carlo Ratti, a professor of the practice for the MIT Department of Urban Studies and Planning and the director of the Senseable City Lab in the MIT School of Architecture and Planning.

A native of Turin, Italy, and a respected designer and architect worldwide, Ratti’s work and that of his firm, Carlo Ratti Associati, has been featured at various international expositions such as the French Pavilion at the Osaka Expo (World’s Fair) in 2025 and the Italian Pavilion at the Dubai Expo in 2020. Their design for The Cloud, a 400-foot tall spherical structure that would serve as a unique observation deck, was a finalist for the 2012 Olympic Games in London, but ultimately not built.

Ratti relishes the opportunity to participate in these events.

“You can push the boundaries more at these [venues] because you are building something that is temporary,” says Ratti. “They allow for more creativity, so it’s a good moment to experiment.”

Based on his previous work, Ratti was invited to design the torch by the Olympic organizers. He approached the project much as he instructs his students working in his lab.

“It is about what the object or the design is to convey,” Ratti says. “How it can touch people, how it can relate to people, how it can transmit emotions. That’s the most important thing.”

To Ratti, the fundamental aspect of the torch is the flame. A few months before the games begin, the torch is lit in Olympia, Greece, using a parabolic mirror reflecting the sun’s rays. In ancient Greece, the flame was considered “sacred,” and was to remain lit throughout the competition. Ratti, familiar with the history of the Olympic torch, is less impressed with designs that he deems overwrought. Many torches added superfluous ornamentation to its exterior much like cars are designed around their engines, he says. Instead, he decided to strip away everything that wasn’t essential to the flame itself.

What is “essential”

“Essential” — the official name for the 2026 Winter Olympic torch — was designed to perform regardless of the weather, wind, or altitude it would encounter on its journey from Olympia to Milan. The process took three years with many designs created, considered, and discussed with the local and global Olympic committees and Olympic sponsor Versalis. And, as with Ratti’s work at MIT, researchers and engineers collaborated in the effort.

“Each design pushed the boundaries in different directions, but all of them with the key principle to put the flame at the center,” says Ratti who wanted the torch to embody “an ethos of frugality.”

At the core of Ratti’s torch is a high-performance burner powered by bio-GPL produced by energy company ENI from 100 percent renewable feedstocks. Furthermore, the torch can be recharged 10 times. In previous years, torches were used only once. This allowed for a 10-fold reduction in the number of torches created.

Also unique to this torch is its internal mechanism, which is visible via a vertical opening along its side, allowing audiences to see the burner in action. This reinforces the desire to keep the emphasis on the flame instead of the object.

In keeping with the requisite for minimalism and sustainability, the torch is primarily composed of recycled aluminum. It is the lightest torch created for the Olympics, weighing just under 2.5 pounds. The body is finished with a PVD coating that is heat resistant, letting it shift colors by reflecting the environments — such as the mountains and the city lights — through which it is carried. The Olympic torch is a blue-green shade, while the Paralympic torch is gold.

The torch won an honorable mention in Italy’s most prestigious industrial design award, the Compasso d’Oro.

The Olympic Relay

The torch relay is considered an event itself, drawing thousands as it is carried to the host city by hundreds of volunteers. Its journey for the 2026 Olympics started in late November and, after visiting cities across Greece, will have covered all 110 Italian provinces before arriving in Milan for the opening ceremony on Feb. 6.

Ratti carried the torch for a portion of its journey through Turin in mid-January — another joyful invitation to this quadrennial event. He says winter sports are his favorite; he grew up skiing where these games are being held, and has since skied around the world — from Utah to the Himalayas.

In addition to a highly sustainable torch, there was another statement Ratti wanted to make: He wanted to showcase the Italy of today and of the future. It is the same issue he confronted as the curator of the 2025 Biennale Architettura in Venice titled “Intelligens. Natural. Artificial. Collective: an architecture exhibition, but infused with technology for the future.”

“When people think about Italy, they often think about the past, from ancient Romans to the Renaissance or Baroque period,” he says. “Italy does indeed have a significant past. But the reality is that it is also the second-largest industrial powerhouse in Europe and is leading in innovation and tech in many fields. So, the 2026 torch aims to combine both past and future. It draws on Italian design from the past, but also on future-forward technologies.”

“There should be some kind of architectural design always translating into form some kind of ethical principles or ideals. It’s not just about a physical thing. Ultimately, it’s about the human dimension. That applies to the work we do at MIT or the Olympic torch.”

de MIT News https://ift.tt/LVa4tGz

3D-printed metamaterials that stretch and fail by design

Metamaterials — materials whose properties are primarily dictated by their internal microstructure, and not their chemical makeup — have been redefining the engineering materials space for the last decade. To date, however, most metamaterials have been lightweight options designed for stiffness and strength.

New research from the MIT Department of Mechanical Engineering introduces a computational design framework to support the creation of a new class of soft, compliant, and deformable metamaterials. These metamaterials, termed 3D woven metamaterials, consist of building blocks that are composed of intertwined fibers that self-contact and entangle to endow the material with unique properties.

“Soft materials are required for emerging engineering challenges in areas such as soft robotics, biomedical devices, or even for wearable devices and functional textiles,” explains Carlos Portela, the Robert N. Noyce Career Development Professor and associate professor of mechanical engineering.

In an open-access paper published Jan. 26 in the journal Nature Communications, researchers from Portela’s lab provide a universal design framework that generates complex 3D woven metamaterials with a wide range of properties. The work also provides open-source code that allows users to create designs to fit specifications and generate a file for printing or simulating the material using a 3D printer.

“Normal knitting or weaving have been constrained by the hardware for hundreds of years — there’s only a few patterns that you can make clothes out of, for example — but that changes if hardware is no longer a limitation,” Portela says. “With this framework, you can come up with interesting patterns that completely change the way the textile is going to behave.”

Possible applications include wearable sensors that move with human skin, fabrics for aerospace or defense needs, flexible electronic devices, and a variety of other printable textiles.

The team developed general design rules — in the form of an algorithm — that first provide a graph representation of the metamaterial. The attributes of this graph eventually dictate how each fiber is placed and connected within the metamaterial. The fundamental building blocks are woven unit cells that can be functionally graded via control of various design parameters, such as the radius and pitch of the fibers that make up the woven struts.

“Because this framework allows these metamaterials to be tailored to be softer in one place and stiffer in another, or to change shape as they stretch, they can exhibit an exceptional range of behaviors that would be hard to design using conventional soft materials,” says Molly Carton, lead author of the study. Carton, a former postdoc in Portela’s lab, is now an assistant research professor in mechanical engineering at the University of Maryland.

Further, the simulation framework also allows users to predict the deformation response of these materials, capturing complex phenomena such as self-contact within fibers and entanglement, and design to predict and resist deformation or tearing patterns.

“The most exciting part was being able to tailor failure in these materials and design arbitrary combinations,” says Portela. “Based on the simulations, we were able to fabricate these spatially varying geometries and experiment on them at the microscale.”

This work is the first to provide a tool for users to design, print, and simulate an emerging class of metamaterials that are extensible and tough. It also demonstrates that through tuning of geometric parameters, users can control and predict how these materials will deform and fail, and presents several new design building blocks that substantially expand the property space of woven metamaterials.

“Until now, these complex 3D lattices have been designed manually, painstakingly, which limits the number of designs that anyone has tested,” says Carton. “We’ve been able to describe how these woven lattices work and use that to create a design tool for arbitrary woven lattices. With that design freedom, we’re able to design the way that a lattice changes shape as it stretches, how the fibers entangle and knot with each other, as well as how it tears when stretched to the limit.”

Carton says she believes the framework will be useful across many disciplines. “In releasing this framework as a software tool, our hope is that other researchers will explore what’s possible using woven lattices and find new ways to use this design flexibility,” she says. “I’m looking forward to seeing what doors our work can open.”

The paper, “Design framework for programmable three-dimensional woven metamaterials,” is available now in the journal Nature Communications. Its other MIT-affiliated authors are James Utama Surjadi, Bastien F. G. Aymon, and Ling Xu.

de MIT News https://ift.tt/zyZtPxa