This month’s “Insights & Outcomes” digs deep into research about fundamental processes that affect all our lives. We delve into the evolution of pregnancy, new uses for artificial intelligence in chemistry and carbon capture, and a novel device capable of detecting a rare genetic mutation in minutes.
As always, you can find more science and medicine research news on Yale News’ Science & Technology and Health & Medicine pages.
New device brings benefits of ‘rapid’ genetic tests to clinical setting
Despite advances in genetic testing over the past two decades, use of the technology in clinical settings has been hampered by the notoriously long wait for test results. In most cases, laboratory results aren’t available for days or weeks, by which time the opportunity for improved patient care may have already been missed.
A team of researchers from Yale and Rutgers, however, recently created a portable device capable of detecting a rare genetic mutation in as little as 10 minutes. The advance, which was described in the journal Communications Engineering, holds promise for use in emergency rooms and outpatient settings where test results can help inform patient care — including in cases where doctors may otherwise lose touch with patients after discharge, said Curt Scharfe, a geneticist at YSM and co-author of the study.
Scharfe led the project alongside Mehdi Javanmard, a professor of electrical engineering at the Rutgers School of Engineering.
The device combines a technique called allele-specific polymerase chain reaction, also known as ASPCR, with electrical impedance, which measures how DNA samples affect the flow of electricity in microfluidic chips. These tiny chips handle small liquid volumes and measure electrical signals to distinguish DNA sequences that carry a disease-causing mutation from those that do not.
In this case, the device was validated for testing hereditary transthyretin amyloidosis (TTR), a genetic condition that can lead to heart failure, particularly in people of West African ancestry. The condition has been the focus of multiple Yale research programs.
Importantly for an emergency department setting, the device enables providers to receive results while the patient is still on the premises, Scharfe said.
“It enables near-patient testing just like a glucometer enables near-patient testing for diabetes management,” he said. “Our combined technologies — the assay and the device together — enables us to do the same thing for this mutation with specificity and sensitivity, and affordably.”
Tracing the evolution of pregnancy
Yale research is shedding new light on the evolution in fetal and maternal cells that helped make mammalian pregnancy sustainable.
Successful pregnancies depend, in part, on the molecular communication between fetus and mother where the placenta attaches to the uterus. In a new study, published in the journal Nature Ecology & Evolution, researchers zeroed in on this critical connection.
Specifically, they traced the evolutionary history of gene activity in placental cells from six animals that represent all the branches of the mammalian family tree. These included humans, mice, guinea pigs, macaques, and two lesser-studied species: the short-tailed opossum, a marsupial, and the tenrec, a relative of elephants.
By illustrating how evolution shaped cooperation between mother and fetus, the findings may bring new understanding to pregnancy problems — such as preeclampsia — that spring from issues in how maternal and fetal cells interact.
“Together, these species offer a rare window into pregnancy’s evolutionary history,” said study lead author Daniel Stadtmauer, a post-doc at the University of Vienna who started the research as a student in Yale’s Graduate School of Arts and Sciences (GSAS), in the Department of Ecology and Evolutionary Biology.
The researchers used a technique called “single-cell transcriptomics,” which let them examine the genes that individual cells use and map out all the cell types at the placental border. They found that many mammal species share a type of fetal cell called an “invasive trophoblast,” which has likely helped shape the evolution of the placenta. “We uncovered a genetic signature linked to these placental cells that has persisted for over 100 million years,” Stadtmauer said. “And it’s not unique to humans, as was traditionally thought, but part of an ancient heritage shared even with marsupials.”
The findings also revealed that a type of uterine cell — called decidual cells — evolved gradually, shifting their role from immune functions to hormone production, and that the molecular communication system between mother and fetus grew more specialized over time to allow for greater cooperation between the two.
“This cross-species research opens the door to a powerful new framework for understanding how pregnancy evolved, and how cells cooperate to build complex traits,” said senior author Günter Wagner, the Alison Richard Professor Emeritus of Ecology and Evolutionary Biology.
Other researchers include researcher Jamie Maziarz, who is now in the Department of Molecular, Cellular, and Developmental Biology in Yale’s Faculty of Arts and Sciences (FAS), and collaborators from the University of Vienna and the University of Nevada, Las Vegas.
This research was supported by grants from the John Templeton Foundation, the Yale Institute for Biospheric Studies, the National Science Foundation, and the Austrian Science Fund.
Yale chemists go ‘retro’ with new AI-based model
Retrosynthesis, a longstanding challenge in organic chemistry, has a complexity that is similar to a game of chess. You have a target molecule you’re aiming for, a set of basic materials to get there, and must pursue a set of steps to accomplish the task.
But in retrosynthesis, the possibilities for each step expand exponentially, making it incredibly difficult and time-consuming to reach a target.
But in a recent study published in the Journal of Chemical Information and Modeling, Yale’s Victor Batista and members of his lab describe a novel, artificial intelligence-based approach to direct, multistep retrosynthesis. Batista is the John Gamble Kirkwood Professor of Chemistry in the FAS, a member of the Energy Sciences Institute on West Campus and the Yale Quantum Institute, and director of the Center for Quantum Dynamics on Modular Quantum Devices.
Compared to previous methods, the new approach is three times more likely to suggest a correct route to a target molecule on the first attempt, the researchers say. The research has a public web portal, is open-source, and already has filled more than 800 requests from 100 users.
“Instead of older methods, we re-framed the problem as a sequence prediction task, allowing us to train a transformer model — the same architecture behind large language models like ChatGPT — to predict entire synthesis routes natively,” said Anton Morgunov, a Ph.D. candidate in the GSAS (and a member of Batista’s lab) and co-lead of the project with Ph.D. candidate Yu Shee.
Shee, Morgunov, and Batista are authors of the new study, along with Haote Li, who earned a Ph.D. in chemistry at Yale earlier this year.
The researchers noted that while they have not completely solved the challenge of retrosynthesis — their model struggles with particularly complex chemical structures — their approach shows promise and can be refined further.
Machine learning and climate change
A Yale Center for Natural Carbon Capture (YCNCC) research team has received a $50,000 Phase 1 award from the Bezos Earth Fund’s AI for Climate and Nature Grand Challenge.
The team is led by Elizabeth Yankovsky, assistant professor of Earth and planetary sciences in FAS, and YCNCC data scientist Luke Gloege, along with geochemist Noah Planavsky, professor of Earth and planetary sciences in FAS.
The Yale project leverages machine learning to conduct modeling at different scales to unlock monitoring, reporting, and verification (MRV) for geochemical carbon dioxide removal. The team is now in an intensive innovative sprint towards the challenge’s Phase II awards, expected later this year. Each Phase II awardee team will receive up to $2 million.
The challenge is a $100 million competition from the Bezos Earth Fund to advance innovation and opportunities for AI to help solve the critical challenges of nature loss and climate change.
Hungry for knowledge
Nearly 4 million college students in the U.S. are known to experience food insecurity, according to the U.S. Government Accountability Office. But little has been known about the prevalence of food insecurity among medical students.
A new study from a team of Yale researchers addresses this question, finding that nearly 1 in 4 medical students were food insecure. (“Food insecurity” is a measure of whether individuals have enough food to support a healthy, active life, according to the U.S. Department of Agriculture (USDA).) Published in the journal Academic Medicine, the study was led by YSM students with support from John Solomon Francis, YSM’s associate dean for student affairs and co-author of the study.
“Food insecurity among medical students is not just a personal hardship — it’s a systemic failure,” said Mytien Nguyen, an M.D.-Ph.D. candidate at YSM and one of the first authors of the study. “No student should be expected to learn, train, and care for others while struggling to meet their basic needs.”
Bassel Shanab, an M.D. candidate at YSM and another first author, added: “Food insecurity is often described as a rite of passage, anecdotally, from attendings and residents to medical students, along with excessively long workdays and sleep deprivation, on the pathway to becoming a physician.”
The team examined variations in food insecurity among medical students at 15 schools, analyzing differences by disability status, race, ethnicity, and financial background. Between March and October 2024, 1,659 students across those medical schools completed an online survey. The research team then assessed rates of food insecurity using the USDA’s Household Food Security Survey Module.
Low-income students, students with disabilities, and those underrepresented in medicine reported food insecurity at a significantly higher rate than their peers. These findings suggest a promising yet underutilized path for supporting these students: proactively linking them to nutrition resources and advocating for policies that address their essential needs.
Karen Guzman, Jim Shelton, Kevin Dennehy, and Meg Dalton contributed to this report.
Research Redux:
The cure for cystic fibrosis might start in the womb
Simpler, less costly virus testing in high-risk settings
Yale genome engineers expand the reach and precision of human gene editing
This ‘jellyfish’ has bunny ears — and swims in a galaxy cluster
A glimpse into how monkeys — and machines — see a 3D world