Leaving a tangible mark on your scientific field is a staggering achievement at any stage of your career. Each year, Popular Science honors 10 early-career researchers who’ve gotten a head start: The Brilliant 10. These researchers already stand out as innovators and change makers in their fields. They are asking the unasked questions, adopting novel methods, and pursuing remedies where none exist. Whether they are driven by the desire to fill a need, the pursuit of justice, or sheer fascination, there’s little doubt that each of these awardees will change the world for the better. From more equitable AI to self-assembling lab organs to potential new laws of physics, the groundbreaking work of these up-and-coming researchers offers us a sneak peek at the cutting-edge science of tomorrow. While they’ve already turned heads and earned some of the most prestigious academic awards out there, these experts are just getting started. What on earth will they think of next?
MyDzung Chu: Addressing environmental health disparities within Asian-American communities
Woojin Han: Engineering microenvironments to grow muscle stem cells
Mary Caswell Stoddard: Investigating the wonders of bird eggs to build a better world
Kara McKinley: Understanding how the uterus regenerates
Tina Lasisi: Understanding human skin and hair diversity
Brendan Keith: Breathing new life into old math
Carlos Argüelles-Delgado: Solving space mysteries with Antarctic ice
Quinton Smith: Growing organs to solve health disparities
Robin Brewer: Empowering marginalized communities with AI
Ronald Garcia Ruiz: Aiming lasers at the universe’s origins
Addressing environmental health disparities within Asian-American communities
MyDzung T. Chu: Director of the ADAPT (Addressing Disparities in Asian Populations through Translational Research) Coalition at Tufts University’s Clinical and Translational Science Institute. Credit: Courtesy MyDzung T. Chu
There’s a big problem with how the United States collects health data from its fastest-growing immigrant population. Asians come to the US from dozens of countries, each with its own languages and cultures. Some come as students, others on worker visas, and many others arrive as refugees. Asian immigrants run the socioeconomic gamut, but public health researchers often lump their data together into one cohort.
This aggregation makes it seem as if, on average, Asians in America are pretty healthy. But that buries the experiences of vulnerable minority groups within the community, says MyDzung Chu, an environmental epidemiologist at Tufts Medical Center.
Chu’s mission is to tease apart the nuances of health issues among Asians in the US, especially on the local level. She studies communities in Boston’s Chinatown neighborhood and investigates environmental health disparities that may get hidden in bigger trends. Her research incorporates input and feedback from local groups and individuals. One ongoing project, called Chinatown HEROS and done in collaboration with John Durant, Ponnapa Prakkamakul, and the Asian Community Development Corporation, involves mapping high temperatures and pollution—two climate-change-related variables known to directly harm health—in parks and other open-air spaces throughout Chinatown, with the ultimate aim of educating the community and advocating for changes to make these spaces healthier.
Chu says Chinatown is notorious for being Boston’s hottest neighborhood. Looking at her research group’s initial map of open-air spaces, it’s not hard to see why. Many of the area’s public spaces are fully paved and bake in the sun, while shade-filled green spaces tend to be at the outer edges of Chinatown.
To get a deeper look at the health implications of these disparities, Chu and her team spent the summer of 2023 installing sensors at each open-air site to measure particulate matter, heat, and humidity. They drove around the area in a van that acted as a mobile monitoring station, measuring pollutants like carbon dioxide, soot, and nitrogen dioxide. They also assessed the setup of these spaces, noting how much of each area was paved, shaded, or provided with greenery, among other factors. They’ll begin synthesizing the data later this fall.
The ultimate goal is “to share all this data back, in a very digestible educational way, to the residents of Chinatown,” says Chu—and to use that data to spur change. Chu’s team will work with community partners to create forums and workshops to educate residents of Chinatown on climate and heat hazards, as well as strategies to stay healthy. They’ll also ask locals for feedback, including what kinds of modifications they’d like to see in their parks and green spaces. “We’re going to document that and share it with the city,” says Chu.
This kind of work feels natural for Chu, who grew up in a close-knit Vietnamese community in western Massachusetts. Her father was a public health worker who did tuberculosis outreach. “He was always out in the community seeing patients, seeing new immigrants and refugees in the Vietnamese community who had TB or were at risk for TB,” she recalls. After a Bachelor’s in neuroscience from Smith College, a master’s in public health from Emory University, and a Ph.D. at Harvard T.H. Chan School of Public Health, during which she learned how to layer rigorous research methods on top of community outreach, “It made so much sense” to follow in his footsteps.
Chu has learned that doing this work involves an immense amount of trust and cooperation between researchers and the people they hope to study. That means attending community events, listening to people’s concerns, and understanding local and cultural context. This path has led her, in collaboration with the local organizations Boston Chinatown Neighborhood Center and Asian Women for Health, to research how to improve cultural responsiveness training for community members, often the first responders during a mental health crisis. Chu and her collaborators conducted focus groups to assess the mental health needs of Chinatown’s residents and learn which barriers—like stigma or lack of health insurance—prevented them from seeking care. They evaluated existing training curricula for first responders and found gaps that left trainees ill-equipped to respond to certain problems, such as Asian youth suicidality or the mental health challenges facing transgender Asian individuals. Chu and her colleagues reported their findings to organizations that run mental health first responder training. There’s still more work to do, especially as these trainings get rolled out in different languages, says Chu, “But I’m really proud of this work because I think we were able to do something actually impactful, even with just a small bit of funding.”
It’s validating for people to see their experiences reflected in data, says Chu, and the insights can empower them to make evidence-based arguments to city and county officials to improve their communities. But she stresses that none of that can happen if researchers don’t listen to—and learn from—the people they want to study. “That’s how we’re really able to create something innovative, relevant, and hopefully impactful,” she says. —H.S
Engineering microenvironments to grow muscle stem cells
Woojin Han: Assistant Professor in the Leni and Peter W. May Department of Orthopaedics at the Icahn School of Medicine at Mount Sinai. Credit: Courtesy Woogin Han
If you entered Woojin Han’s New York City lab, you might see rows of tiny Jell-O-like samples, each about the size of a nickel. While these colorless blobs may look unassuming, Han explains that each one is essentially a 3D petri dish. An assistant professor of orthopedics at the Icahn School of Medicine at Mount Sinai, Han is trying to bioengineer hydrogels—those colorless blobs—to resemble the natural microscopic environments of skeletal muscle stem cells.
The goal is to craft a medium where stem cells can “proliferate without losing their self-renewal potency, or ‘stemness,’ as we call it,” says Han. Stem cells are special precisely because they are not yet specialized. They are the raw materials of the body, holding the potential to develop into various different kinds of cells. Besides the totally flexible stem cells that embryos make to start building a body, there are also stem cells in most adult tissues, including muscle. Muscle stem cells can generate new skeletal muscle—the most common kind of muscle in the body—on demand. But this variability makes stem cells difficult to culture in the lab. When they’re placed in a petri dish, they immediately start differentiating—turning into fully fledged cells of one type or another. If Han’s team can mimic the specific microscopic environments where these stem cells grow in our bodies, that could open up new avenues for stem cell therapies and transplantation. In 2022, he received a $2.2 million grant from the National Institutes of Health to pursue this work. The unassuming hydrogel blobs are the key.
To create hydrogel that will allow stem cells to thrive in their ambiguous state, Han and his team have to consider a plethora of variables such as stiffness, shape, chemical composition, and more. He’s found that softer gels better recreate the relative firmness of muscle tissue and help stem cells maintain stemness, and that hydrogels seem to have more success when extruded in the shape of a muscle fiber.
Looking at how skeletal muscle stem cells thrive in the body is key. Normally they are wedged between muscle fibers on one side and the basement membrane, which runs between the body’s tissues, on the other. “Evidence … suggests that this asymmetrically partitioned microenvironment plays a very important role in controlling how the cells establish their polarity and begin to guide their cell division processes,” he says. It creates a delicate balance that keeps the stem cells proliferating, but not differentiating. To recreate this asymmetry, Han and his team have landed on a “sandwich hydrogel system,” whereby the cells are embedded between two different hydrogels. “We’ve made a lot of progress on the material engineering end, and now we are starting to get into the nitty-gritty of the biology.”
Han was already interested in regenerative medicine when he started as a postdoctoral fellow at the Georgia Institute of Technology in 2015. “I always was intrigued by the fact that even though our muscles have this very surprising capacity to regenerate in minor injury contexts, they don’t regenerate in more severe injury or disease,” he says. Han began working with biomaterials, like hydrogels, to study how to improve cell survival after engraftment, which is when donor skeletal muscle stem cells begin making new muscle fibers in their host. He saw a world of potential. A better medium for culturing skeletal muscle stem cells could help make stem cell therapy a viable treatment for people suffering from severe muscle disease.
Research on such treatments is very much still in progress. But for now, “there’s no way to get large quantities of these cells, because they’re quite scarce in the body,” says Han. In the long term, Han hopes to be able to extract skeletal muscle stem cells from patient biopsies. With Han’s hydrogels as a medium, labs would be able to proliferate those stem cells, collect them, and inject them back into patients. This could aid muscle healing and regrowth in people with traumatic volumetric muscle loss and rotator cuff injuries. In theory, Han says, this could even reverse damage seen in diseases like Duchenne muscular dystrophy, a genetic condition that leads muscle fibers to grow progressively weaker. But that’s all in the far future, and “there are still a lot of unknowns.”
Han acknowledges that adequately remaking the microenvironment needed to keep muscle stem cells potent in perpetuity is a huge task. But Han and his colleagues will keep honing their hydrogels, working to stretch that window of “stemness” as long as they can. —H.S
Investigating the wonders of bird eggs to build a better world
Mary Caswell Stoddard: Associate Professor in the Princeton Department of Ecology and Evolutionary Biology, Credit: Courtesy Mary Caswell Stoddard
Birds have always been a part of Mary Caswell “Cassie” Stoddard’s life. Growing up with a mother and grandmother who were both avid bird-watchers meant she absorbed plenty of admiration for the winged creatures.
After an undergraduate degree in biology from Yale University, that appreciation led Stoddard to her Ph.D. in zoology at the University of Cambridge. She began studying the common cuckoo—a bird that stealthily lays its eggs in the nests of other bird species. “In order to get away with this, cuckoos have evolved excellent egg color and pattern mimicry,” she says. “Cuckoos were the entry point that led me to all these questions about eggs.” She took that interest with her in 2016 when she joined Princeton University, where she is now an associate professor of ecology and evolutionary biology.
Egg shape in particular became a major subject of her curiosity. Stoddard can wax poetic about the many possible variations. “You have your typical chicken-egg shape, but many seabirds lay very pointy eggs,” she says. “Hummingbird eggs look like a Tic Tac, and owls lay golf-ball-like round eggs.” But scientists have long lacked a solid understanding of how and why this variation occurs.
One theory suggests egg shape is related to nutrition. Perhaps the spherical eggs of owls, with their smaller ratio of surface area to volume, arose as a solution to the lack of calcium in the birds’ diets. Another school of thought holds that the number of eggs a bird tends to lay in each clutch might affect shape, to ensure they all fit optimally in a nest. Yet another theory suggests that pointier shapes, as seen in eggs laid by seabirds nesting on cliff edges, prevent incubating chicks from rolling off such precipices. But none of these theories have been tested with large enough sample sizes or studied comprehensively enough for significant conclusions.
To get at the why and how of egg shape diversity, Stoddard led a multidisciplinary team of biologists, computer scientists, mathematicians, and more in analyzing more than 49,000 eggs from about 1,400 bird species. This research opened Stoddard’s lab to a variety of interdisciplinary methods. Her lab is also studying other facets of bird biology, including with an ongoing project in the Colorado Rockies on hummingbird vision.
The team translated the shapes of the eggs into mathematical models and incorporated data such as habitat, diet, and how many eggs each species laid at a time. They found that one of the best predictors of egg shape was flight ability. “Birds that are strong fliers—birds that tend to fly a lot or migrate long distances—tend to lay eggs that are more elliptical, or more pointy,” says Stoddard. The team published its findings in the journal Science in 2017.
Its theory is that good fliers have more streamlined body plans, which favor pelvises that can push out only longer, thinner eggs. This is probably not the only evolutionary force behind egg size and shape, Stoddard concedes, and different species could have come to lay outwardly similar eggs due to different evolutionary pressures. But when you look at the amalgam of data from 1,400 bird species, she says, flight is a strong predictor.
Now Stoddard’s lab has turned its attention to the shells themselves. “Right now, one main focus in our group is understanding [the shell’s] biomechanical properties,” says Stoddard. “And that’s taken us down this whole new path with a whole new suite of questions and tools.”
Eggshell is a fascinating and unique material, she says: It’s quite lightweight and comes together very quickly. Crucially, it’s both strong and breakable. The same egg that protects a growing chick must also allow its young resident to break free when the time comes. “My collaborators and I think that what we are learning about eggshell could be applied to the design of novel synthetic materials with special mechanical properties,” Stoddard says. “For example, it is sometimes desirable to have glass windows that are hard to break from the outside but easy to break from the inside.”
The study of eggshells has fascinating scientific implications too. Unpacking the details of how and why eggs form can teach us how birds thrived as their fellow dinosaurs went extinct, as well as how they might be affected by climate change.
Stoddard says that in her lab, questions are always rooted in avian evolution. “Our questions begin with birds … and are rooted in evolutionary biology,” she says. But she and her colleagues use whatever tools and disciplines they can to get at those answers—and they follow the research wherever it leads. —H.S
Understanding how the uterus regenerates
Kara McKinley: Assistant Professor of Stem Cell and Regenerative Biology; Harvard University. Credit: Courtesy Kara McKinley
As a postdoctoral fellow, Kara McKinley came across studies that piqued her interest and altered her scientific trajectory: Researchers had just developed new methods for culturing mini uteruses in petri dishes. At the time, McKinley was studying the regenerative healing properties of the intestine at the University of California at San Francisco. But the more she learned about the biology of the uterus, the more she wanted to know.
The uterus is a bit of an anomaly. As we get older, our bodies experience damage due to aging, disease, and trauma. A body can often repair or replace parts of itself, but not perfectly. Scars form and accumulate, making most tissues less functional over time.
But things are a little different for the uterus. For every month of menstruation, the uterus sheds all or most of its lining (the endometrium) and then perfectly rebuilds what was lost, without any scarring. It’s not impervious to injury; certain medical procedures and infections can leave scar tissue behind. But the fact that the uterus can usually bounce back from the physical trauma of pregnancy and birth is something of a marvel. “It’s a uniquely powerful system to understand regeneration in humans,” says McKinley, now an assistant professor of stem cell and regenerative biology at Harvard University and a Freeman Hrabowski scholar at the Howard Hughes Medical Institute.
Research on menstruation and uterine regeneration is still scant, she says. But studying these processes can open up vast possibilities for future medical treatments. For example, understanding the mechanisms behind this regular, scarless regeneration could help scientists encourage similar healing in other tissues and organs. More comprehensive knowledge of how menstruation works could also lead to treatments for heavy or painful periods.
Many scientists in the field study these possibilities by culturing small uterus analogues in petri dishes. “There’s a lot of beautiful work” that has come from these methods, says McKinley. But her lab is more interested in studying the uterus in context—inside a living body. Scientists studying human organ functions tend to use mice or rats as models. In some ways, their biology is quite similar to ours. But the species generally used in labs do not menstruate. In fact, most mammals don’t have menstrual cycles. Among rodents, just one—the Cairo spiny mouse (Acomys cahirinus)—is known to experience them. That’s the animal McKinley’s lab uses alongside regular lab mice, who can be induced to experience a process analogous to menstruation.
Looking at menstruation in the context of an animal’s whole body is key to understanding our own bodily systems, McKinley says. “Menstruation is a very complicated process, and we don’t yet know all of the components that affect it.” Studying spiny mouse menstruation will help her tease out which variables contribute to the endometrium’s regenerative abilities. McKinley plans to investigate which cells are responsible for rebuilding the uterine lining. Her latest work on the subject is a paper in Annual Reviews that summarizes what scientists currently know about how uterine repairs happen without scarring, and why scarring does occur after certain medical procedures.
Reproductive health is a natural target for McKinley’s academic passions. She has long been interested in issues surrounding gender equity in science. In 2019, she founded a program called Leading Edge that is dedicated to increasing the presence of women and other gender minorities in the biomedical research field.
According to the World Health Organization, there are almost 2 billion women of reproductive age around the world. But “studies of the uterus, particularly the nonpregnant uterus, have received very little attention from the scientific community,” says McKinley. Some of that is due to prevailing taboos and stigma around menstruation. There is also a long-standing tendency to focus on fetal development over all other aspects of female reproductive health. But there are also technical constraints: The uterus is hardly the most accessible body part, and menstruation isn’t always regular or reliable in its timing. And until the 2016 confirmation of the Cairo spiny mouse’s menstruation, researchers also lacked a good animal model for studying the process. Those are factors scientists have had to take into account when designing studies.
McKinley doesn’t think those barriers should get in the way of good science. She believes that the approximately 2 billion people worldwide whose uteruses are capable of shedding and regenerating every 28 days or so deserve solid research on reproductive health. Exploring a field with so many unknowns—and with a potential impact on so many people—is incredibly exciting. But McKinley sees more than just an opportunity for discovery. “We also see it as an obligation,” she says. —H.S
Understanding human skin and hair diversity
Tina Lasisi: Assistant Professor of Anthropology; University of Michigan. Credit: Tina Lasisi
Despite growing up in a multicultural household, Tina Lasisi hadn’t given much thought to the biological science of diversity. Diversity, yes, but the biology of it hadn’t much crossed her mind. That changed in 2011, during an undergraduate class in biological anthropology at the University of Cambridge. A professor showed Lasisi and her classmates how the map of skin pigmentation variation almost perfectly overlapped with differences in ultraviolet radiation exposure across the world. A lightbulb went off.
Lasisi was fascinated to see skin color and melanation explained as a protective force against harmful UV rays. “Cool, that explains skin color and why I’m brown,” she remembers thinking. But she asked an immediate second question: “What about my hair?” She explains, “That’s a very Black-woman thing to do.” Like skin, hair is a highly racialized physical feature that Black people, especially women, often feel pressured to defend or alter.
If skin tone can be measured by melanin and mapped against the intensity of UV ray exposure, Lasisi wondered, was there a similar method for quantifying hair and trying to find links with geography? She started looking for an evolutionary explanation for hair diversity and specifically for hair morphology and curliness. No one could give her a good answer. The scientific literature was sparse. The few studies she found that focused on hair diversity didn’t inquire about the evolutionary function of different hair textures—and none went about trying to quantify the different textures.
So Lasisi began honing her own methodology. She developed a method to measure variation in human hair shape by taking pieces from individual strands of hair, measuring their curves, and using a National Institutes of Health program called ImageJ to analyze and quantify hair from different people. She published her results in 2016 in the American Journal of Physical Anthropology (now known as the American Journal of Biological Anthropology) and a follow-up study in Nature Scientific Reports in 2021.
Many of the existing ways of describing curly hair are laden with bias, Lasisi says: as frizzy, kinky, hard to comb, fragile. “A lot of these metrics have prejudice and bias baked into them,” she says, “because they have a value system baked into them.”
In the 12 years since that formative undergrad class, Lasisi worked to answer unasked questions about hair shape and diversity as a Ph.D. candidate at Pennsylvania State University before completing a science-communication-focused postdoctoral research position at the same institution and a second postdoc focusing on forensic genetic genealogy at the University of Southern California. Now she’s running the Lasisi Lab as an assistant professor of anthropology at the University of Michigan. “I really want to focus on setting up my lab so that we can be a hub for people who want hair samples measured quantitatively and accurately, for all kinds of purposes,” she says.
Now that Lasisi has become a leading expert on hair form and function, the questions she hopes to explore reach far beyond variations in curl pattern. For example, Lasisi is excited to study the complicated interplay between hormones and hair growth. “You can have lots of testosterone coursing through you and still not be able to grow a full beard,” she says, “or still experience hair loss.” These relationships are not well understood but could change treatments for hair loss and options for gender-affirming care. Lasisi is also setting up research into the diversity of facial hair and skin to help reduce bias in artificial intelligence. You can train AI on huge datasets, “but if you don’t understand the structure of a given variation, you might have unwittingly created a biased training dataset,” she says.
Lasisi’s current focus in this area is gathering as much data as possible about hair, including genetic information. “There are a lot of fantastic resources and databases with genetic data, all kinds of scientific data,” Lasisi says, “but the data they include on hair, if they include it at all, is categorical, subjective, and usually self-described,” meaning people provided their own nonstandardized descriptions of their own hair. The Lasisi Lab must continue her work of collecting hair samples to get measurements precise and accurate enough to answer the questions she’s asking. It will also swab saliva to gather genetic data on its hair donors.
Beyond potential applications in medicine and AI, an increased understanding of the evolution behind human diversity can be empowering. Lasisi’s most recent paper presents evidence that human scalp hair evolved to protect the head from the sun, and that tightly curled hair provides the most protection against solar rays while allowing for airy ventilation to cool the head down. Knowing how your traits came to be can change the way you think about yourself, says Lasisi. Learning of that research linking UV rays and skin melanation gave her a newfound appreciation for why she looks the way she does. She hopes to do the same for many others in the years to come. —H.S.
Breathing new life into old math
Brendan Keith: Assistant Professor of Applied Mathematics; Brown University. Credit: Claire Louise Foster
Computer simulations touch everything in our lives. Every branch of manufacturing—shipbuilding, engineering, aerospace, and more—runs on a family of algorithms developed over the last six or so decades, says Brendan Keith, an assistant professor of applied mathematics at Brown University. These types of algorithms, known as finite element methods, help researchers like Keith predict how objects might behave in different environments. You can see why this would be particularly useful for, say, engineers working on massive skyscrapers or manufacturers constructing giant cargo freighters.
As a kid, Brendan Keith never expected to turn into a self-described “computational science nerd.” But he fell in love with high school physics, eager to model how far various careening objects would fly through the air and estimate where they’d land. Eventually, he shifted his focus from physics to geometry and finally to applied math, which he studied for his master’s degree at Canada’s McGill University in 2013. Five years later, he earned his Ph.D. in computational science, engineering and mathematics at the University of Texas at Austin. Now he wields theory in an attempt to explain the world around us.
As an assistant professor at Brown University, Keith is breathing new life into old math. He’s currently trying to update vintage techniques with a method he calls proximal Galerkin (a recent addition to a group of methods named after Soviet mathematician Boris Galerkin).
The problems in question involve keeping simulations in line with how the world works. This includes preventing one object from penetrating another during computer simulations, an error that makes it harder to predict how things will play out off-screen. To take example, when plane manufacturers model how air moves past a jet wing during flight, they need to make sure the air pressure conditions reflect reality. So far, it’s been tricky to simulate such a scenario accurately without violating the laws of real-life physics and thus blowing up a computer model. So Keith and his collaborator Thomas Surowiec found a way to “cut up the problem into little pieces” on a computer, do mathematical transformations on each piece, run their simulations, and then recombine them.
Their new solution ends up reducing the time and costs involved with this type of work, and, most importantly, prevents computer models from going haywire; for example, the proximal Galerkin method can help a car crash simulation run correctly by preventing steel from entering, rather than wrapping around, a telephone pole. This year, Keith received a grant of more than $800,000 from the Department of Energy to fine-tune this research, along with other new numerical methods he’s cooking up.
Keith has also received attention for much loftier calculations. In 2021, he helped develop a new machine learning technique for peering into black holes. Specifically, he found a way to model the motion of a type of black hole based on data from the gravitational waves such black holes produce. Researchers have long accomplished this by solving Einstein’s equations of general relativity. (He suggested that certain chaotic events, like two black holes smashing together, mess with what he called space-time to create the ripples known as gravitational waves.) But that process is time-consuming and costly and can require supercomputers. With Keith’s technique, the math can be done on any laptop—including the nearly decade-old Mac he used for the project. And while someone might need weeks to get an accurate result using traditional models, the new machine learning tool can crank out the answer in less than an hour.
With his new funding, Keith wants to apply his proximal Galerkin method to a whole host of problems. He has been working with researchers from a wide range of fields and is now thinking up ways to better understand bone fractures, design large bridges, and simulate car crashes. In fact, there are so many possibilities that he says it’s hard to decide what his team should tackle first. He does know one thing for sure: He hopes his algorithms continue to prove useful for future generations of researchers.
“My dream would be to actually develop an algorithm that people are still using in 50 years,” Keith says. “Methods come and go, people are always studying the newest-fangled thing on the same old problems, but it’s very rare that somebody comes across something that has that kind of staying power—that’s what I’d really like to be someday.” —M.G.
Solving space mysteries with Antarctic ice
Carlos Argüelles-Delgado: Assistant Professor of Physics; Harvard University. Credit: Kris Snibbe/Harvard Staff Photographer
For decades, physicists have widely accepted a theory that supposedly explains our universe. But some say the Standard Model of physics, which was developed in the early 1970s, is beginning to crumble under pressure. The Standard Model holds that nature is composed of a few types of particles and governed by a handful of forces. But this theory doesn’t explain certain astronomical anomalies. For example, it can’t explain how gravity exists, nor account for the mysterious dark matter and energy that take up most of our universe.
Another hole in the Standard Model: It doesn’t explain a key fact about neutrinos, a teeny type of electrically neutral particle. Each second, about 65 billion of them surge through each square centimeter of your body. While the rules posited by the Standard Model suggest that neutrinos should lack mass, they’re actually the most abundant particles with mass in the universe.
“Particle physicists are like detectives,” says Carlos Argüelles-Delgado, an assistant professor of physics at Harvard University. “You look at the places where things seem to be misbehaving. Neutrinos misbehave.”
This glaring discrepancy intrigued Argüelles-Delgado while they completed a physics master’s program in their native country of Peru just over a decade ago. Neutrino research was starting to really pick up steam. Like many Latin American physicists at the time, Argüelles-Delgado says, their academic adviser lacked the funds for experimental physics equipment. That gave Argüelles-Delgado the opportunity to build up extensive experience on the theory side of things. They credit this focus on theory for spurring them to dig into calculations and attempt to get to know the puzzling particles.
This is a particularly difficult task because neutrinos rarely interact with other types of matter, earning them the nickname “ghost particles.” This means they’re difficult to detect and study. But there’s a major upside here. Since neutrinos hardly touch other forms of matter, they allow researchers to study scenes that light-based telescopes can’t capture—such as the inner workings of the sun or even other galaxies—without stuff like electromagnetic fields and gas getting in the way.
Neutrinos may be hard to spot, but the task is not impossible: You just have to look in unusual places. Argüelles-Delgado’s work at the University of Wisconsin at Madison, where they earned their Ph.D. in physics in 2015, led them to the world’s largest neutrino detector. Fittingly called IceCube, the massive tool incorporates thousands of optical sensors buried up to 8,000 feet within Antarctic ice. When neutrinos interact with the ice, they create electrically charged particles that emit a blue glow called Cherenkov radiation. IceCube’s sensors record the light pattern to gauge the direction and energy of an arriving neutrino. Ice aids in the endeavor because it’s clear enough to provide glimpses of the blue glow, and the light can easily travel within its depths.
Since it launched in 2011, IceCube has detected neutrinos packed with energy from some of the “most violent” locations in the universe, Argüelles-Delgado says. Since they travel in a straight line—a product of their inability to be interrupted or redirected by most other forms of matter—these chaotic neutrinos readily offer clues about their origins.
While many observed neutrinos have zipped over from the sun or within our atmosphere, last year IceCube caught some from a galaxy 47 million light-years away (still relatively close to us in cosmic terms) that’s powered by a supermassive black hole. The hole pulls in particles at high speeds. When these collide, they spawn neutrinos. Argüelles-Delgado also studies neutrinos from our own galactic neighborhood. Back in Cambridge, Argüelles-Delgado sifts through this info for new insights. For instance, they pay close attention to the various types or “flavors” of neutrinos IceCube measures, such as the rarely observed tau neutrino, and what secrets they hold. They have even pioneered a new quantum computing method to model how neutrinos morph into these different varieties.
Such IceCube data, which is being studied by Argüelles-Delgado and their colleagues around the globe, could help in the hunt for elusive dark matter, offer a closer look at black holes, and even identify new laws of physics, because neutrinos point straight toward the phenomena under investigation, like a perp’s footprints at the scene of the crime.
Over the next decade, IceCube will receive fancier sensors and calibration devices and grow around eight times larger. A sharper resolution could lead to new out-of-this-world insights. “We could find a new force, we could find new matter,” Argüelles-Delgado says. “It could just totally change physics.” —M.G.
Growing organs to solve health disparities
Quinton Smith: Assistant Professor of Chemical and Biomolecular Engineering; University of California, Irvine. Credit: Courtesy Quinton Smith
Up to 90 percent of all new drugs fail in human trials, often because substances that proved safe for animal subjects end up being toxic for people. But a high-tech solution could bring us more effective medications with fewer hiccups: growing tissue from stem cells to mimic our organs and how they interact with drugs.
This futuristic field appealed to Quinton Smith, who initially studied to be a chemical engineer at the University of New Mexico starting in 2007 and had considered becoming a doctor. But after realizing that patient interaction didn’t appeal to him as much as research, he decided he wanted to build things to help improve human health and began working in biology labs. He applied his engineering expertise to the human body when he earned his Ph.D. in chemical and biomolecular engineering from Johns Hopkins University in 2017. Smith studied under Sharon Gerecht, an early leader in stem cell engineering. Now he harnesses groups of lab-grown cells called organoids to research, and potentially treat, some of the deadliest and trickiest conditions.
“Having that stem cell perspective and an engineering background is a really powerful tool,” Smith says. “We have this idea: Can we actually replace animal studies and create a body on a chip to really study how tissues interact?”
Researchers have spent decades laying the foundations for today’s organoid experiments. Today, labs can begin with an adult’s own blood or skin cells and transform them into any adult cell type thanks to cocktails of chemicals that direct their growth.
Smith’s lab at the University of California at Irvine, which was founded in 2021, is one of many around the globe tinkering with these organ models. But his team stands apart with a game-changing new technique. Scientists have long struggled to add structures similar to vascular tissue to cells in lab dish experiments. It’s tricky to match the specific types of cells found in blood vessels in the body. But blood vessels are a crucial feature, “the holy grail” of tissue engineering according to Smith: They supply oxygen and nutrients to cells and could enable increasingly large groups of lab-grown structures to communicate and thrive.
Thanks to his engineering know-how, Smith joined a community of scientists who take inspiration from the intricate circuits built into the silicon chips that run our computers. His team first prints tiny channels onto its “organ” chips, which are made of a compound that contains silicon. They fill those divots with a gel containing protein found in blood clots. Inside this gel, they’ve also added lab-grown blood vessel cells and a type of cell called a fibroblast that helps form connective tissue, which work together to form tubes that mimic the vasculature inside our bodies. The final product looks nothing like the slimy tissues inside us, but is rather a see-through gadget with branching wires inside, ranging from the size of a quarter to just a few micrometers across.
Smith’s team can send liquids through the faux blood vessels to learn, for example, how changes in blood flow contribute to disease development, or how a specific drug might affect circulation. Smith says this type of work on liver models, which he first delved into during his postdoctoral research, is particularly important. No FDA-approved drugs exist for end-stage liver diseases like cirrhosis, which disproportionately affects marginalized groups such as Latino and Black people.
By using patients’ own stem cells, he could even create bespoke models to test their unique reactions to drugs and develop personalized stem cell therapies. Smith envisions a future where doctors can restore the function of a diseased organ by implanting stem cells in easy-to-reach places, like under the arm. Such supplementation probably wouldn’t make organ transplants a thing of the past, Smith says, but it could help lower demand and shorten wait times for those in need.
Smith is also harnessing his faux organs to tackle another glaring healthcare gap. He’s interested in investigating the causes of preeclampsia, a potentially deadly complication of pregnancy that causes high blood pressure. It is a risk for any birthing person but is especially prominent among Black women in the United States. In fact, Black women born in the US experience higher rates of preeclampsia than those who immigrate here, perhaps due to stress and discrepancies in hospital experiences tied to systemic racism. But the exact mechanisms behind this phenomenon remain unclear. “There seems to be not only an ancestral contribution, but social, economic, or other factors that can really impact maternal health,” Smith says.
To solve this urgent puzzle, Smith is now using the techniques he’s developed to create placentalike cells. He’s using them to figure out how a pregnant person’s environment might spur inflammation in the placenta and interfere with blood vessels. This is particularly critical work because there are logistical and ethical obstacles to doing studies on pregnant people. Smith’s insights could help scientists around the world illuminate what he calls “the black box” of human development and help ensure safer pregnancies for marginalized communities. —M.G.
Empowering marginalized communities with AI
Robin Brewer: Assistant Professor of Information; School of Information, University of Michigan. Credit: UMSI, Jeffrey Smith
Growing up as an only child, Robin Brewer says she had lots of time to tinker on her computer. She devoured math programs along with roller coaster simulators and typing games. Her parents worked in IT for the government, and her household was one of the first in her Maryland neighborhood to own a PC. When she attended a science and tech high school, her self-described “bossy” only-child nature compelled her to learn how to order computers around with the help of languages like Java and C++. This curiosity led her to study computer science and human-centered computing for her bachelor’s and master’s degrees at the University of Maryland.
But by the time she was working on her Ph.D. at Northwestern University in 2013, Brewer had decided to take a step back and learn how other people interact with technology. She noticed that devices tend to cater to young, nondisabled people, with accessibility features often added as an afterthought.
“I’m really an advocate for more aging-first and disability-first approaches to research and design,” says Brewer, now an assistant professor of information at the University of Michigan.
To help remedy these disparities, Brewer develops accessibility tools based on feedback from older adults and people with disabilities. In recent years, she has focused on the role of AI and voice assistants like Siri in engaging these communities and helping connect people with shared experiences. In June 2023, she co-authored a paper exploring ways to improve cultural sensitivity in voice technologies for older Black users. Some of the participants, for instance, expressed a desire to hear voices that sounded more like their own without relying on stereotypes.
Her work could prove particularly useful as the US contends with a significant shortage of home healthcare workers. While Brewer doesn’t think we should replace human professionals with automatons in this context, she thinks tech can help ease the stress of supporting seniors at home—in 2020, more than 50 million people in the US reportedly cared for someone with particular health needs or disabilities.
Right now, Brewer is working on a program that listens to caregivers and care recipients describe their daily challenges. It then provides a human- or AI-generated summary of what they’ve shared to help them navigate challenging conversations. For example, a care recipient may desire more independence during tasks like grocery shopping, so a voice assistant can work as an intermediary and help communicate this to their caregiver.
While Brewer believes that the artificial intelligence behind much of her work can benefit marginalized populations, she’s also dedicated to confronting the biases baked into the models AI uses. In a study published in June 2023, she collaborated with Google research scientists to highlight the biases that large language models—such as those that power chatbots like ChatGPT—hold toward people with disabilities. The team found that these models tend to view disability in narrow terms, as mostly pertaining to physical limitations, and can make harmful remarks about people who rely on others for assistance.
While researchers have conducted work on the prejudices AI presents toward communities of color and older people, Brewer says that harms against the disabled community have been harder to quantify and act on. She says it’s likely possible to retrain models to be more useful and display more sensitivity.
Last year, Brewer was awarded more than $500,000 from the National Science Foundation’s prestigious early-career prize to study how voice technologies could help older adults avoid lies online. Given the potential shortcomings of tech, along with the risks of invasive surveillance, she wants to help users build digital boundaries and learn to spot misinformation—particularly as chatbots have been found to “hallucinate” and make things up or peddle conspiracy theories.
“It’s not all rainbows and sunshine,” she says. “Every technology has some type of risk to it.” —M.G.
Aiming lasers at the universe’s origins
Ronald Garcia Ruiz: Assistant Professor of Physics; MIT. Credit: Courtesy of Diana Joaqui
Although our universe is billions of years old, there are still a lot of unanswered questions about how the big bang played out. Matter composes everything around us, but how did it evolve? To tackle this existential question, researchers have devised some mind-boggling experiments. Take the Large Hadron Collider at the European Organization for Nuclear Research (CERN) spanning the border between France and Switzerland, where scientists smash together high-energy particles at nearly the speed of light. The team there studies the resulting interactions to test predictions from the Standard Model theory that explains our universe.
But the Large Hadron Collider can’t provide all the answers scientists are looking for, according to MIT assistant professor of physics Ronald Garcia Ruiz. After working at CERN while earning his Ph.D. at KU Leuven in Belgium, Garcia Ruiz decided to approach the same question with the help of lasers.
He compares digging into the beginnings of the universe to peering inside a watermelon. There are two distinct approaches to glimpsing its innards: one rather violent and one more meticulous. You can see inside it by blowing it up with a high-energy particle and then reconstructing the interior, which is essentially the protocol at the Large Hadron Collider (sort of like shooting the fruit and then gluing it back together). Instead, Garcia Ruiz realized he could probe the inside of this “watermelon” with an electron, offering a more clear-cut and precise view.
He and his colleagues create radioactive atoms and molecules to get the job done, since they have an imbalance of neutrons and protons. This asymmetry makes the atoms and molecules highly sensitive to funky physics happenings in the lab and could help explain the uneven ratio of matter and antimatter in the universe, a reality that violates the Standard Model.
It’s hard to concoct these radioactive substances, but Garcia Ruiz and his team work at specialized nuclear physics labs, including CERN and the Facility for Rare Isotope Beams, a U.S. Department of Energy Office of Science user facility operated by Michigan State University. They then wield their unique, highly sensitive laser system to measure the interactions among protons, neutrons, and electrons within these radioactive substances. They can use the laser to measure the minuscule structures of these particles and catch any shifts in energy among different isotopes of the same element. So-called isotope shifts matter because they may reveal phenomena that defy the known fundamental forces of nature.
It all has to happen in a flash, since these radioactive substances can disappear in less than a fraction of a second. This gives Garcia Ruiz an unprecedented look at hard-to-capture properties of the particles and forces that serve as the foundation of the universe’s visible matter. These studies could even identify (or rule out the existence of) never-before-seen particles.
This laser-precise technique nicely complements the Large Hadron Collider method, because it offers scientists a close-up view of the building blocks of nature. “I can do this in a very elegant way,” Garcia Ruiz says.
Garcia Ruiz’s work has made waves outside the world of particle physics too. His team is collaborating with astronomers to help hunt for radioactive molecules in space. By measuring the radiation emitted by these molecules at the lab, Garcia Ruiz offers “fingerprints” scientists can use to seek out similar measurements in the cosmos. This work can also help astronomers pinpoint when astrophysical events went down due to the time-telling properties of radioactive decay. Garcia Ruiz has even tailored his experiments to create radioactive nuclei with tons of neutrons to help teams studying the dynamics of neutron-rich matter such as neutron stars—which form when a giant star runs out of fuel and collapses.
Ultimately, he aims to help plug some of the gaps in the Standard Model and delve deeper into the origins of life, the universe, and everything. Garcia Ruiz even suspects that he could analyze how dark matter, a little-understood substance that constitutes 85 percent of the universe’s matter, engages with the protons, neutrons, and electrons in his lab.
“I think we are really at the age of a revolution in our understanding of fundamental physics,” he says. —M.G.
Source : Popular Science