This month\u2019s \u201cInsights & Outcomes\u201d 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\u00a0minutes.\u00a0<\/p>\n
As always, you can find more science and medicine research news on Yale News\u2019 Science & Technology<\/a> and Health & Medicine<\/a> pages.<\/p>\n New device brings benefits of \u2018rapid\u2019 genetic tests to clinical\u00a0setting<\/p>\n 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\u2019t available for days or weeks, by which time the opportunity for improved patient care may have already been\u00a0missed.<\/p>\n A team of researchers from Yale and Rutgers, however, recently created a\u00a0portable device capable of detecting a rare genetic mutation<\/a> in as little as 10 minutes. The advance, which was described in the journal\u00a0Communications Engineering<\/a>, holds promise for use in emergency rooms and outpatient settings where test results can help inform patient care \u2014 including in cases where doctors may otherwise lose touch with patients after discharge, said\u00a0Curt Scharfe<\/a>, a geneticist at YSM and co-author of the\u00a0study.<\/p>\n Scharfe led the project alongside\u00a0Mehdi Javanmard<\/a>, a professor of electrical engineering at the Rutgers School of\u00a0Engineering.<\/p>\n 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\u00a0not.<\/p>\n 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\u00a0the focus of multiple Yale research programs<\/a>.<\/p>\n Importantly for an emergency department setting, the device enables providers to receive results while the patient is still on the premises, Scharfe\u00a0said.<\/p>\n \u201cIt enables near-patient testing just like a glucometer enables near-patient testing for diabetes management,\u201d he said. \u201cOur combined technologies \u2014 the assay and the device together \u2014 enables us to do the same thing for this mutation with specificity and sensitivity, and\u00a0affordably.\u201d<\/p>\n Tracing the evolution of\u00a0pregnancy<\/p>\n Yale research is shedding new light on the evolution in fetal and maternal cells that helped make mammalian pregnancy\u00a0sustainable.\u00a0<\/p>\n 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\u00a0Nature Ecology & Evolution<\/a>, researchers zeroed in on this critical\u00a0connection.<\/p>\n Specifically, they traced the evolutionary history of gene activity in placental cells from six animals\u00a0that represent all the\u00a0branches 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\u00a0elephants.<\/p>\n By illustrating how evolution shaped cooperation between mother and fetus, the findings may bring new understanding to pregnancy problems \u2014 such as preeclampsia \u2014\u00a0that spring from issues in how maternal and fetal cells\u00a0interact.<\/p>\n \u201cTogether, these species offer a rare window into pregnancy\u2019s evolutionary history,\u201d said study lead author Daniel Stadtmauer, a post-doc at the University of Vienna who started the research as a student in\u00a0Yale\u2019s Graduate School of Arts and Sciences (GSAS), in the Department of Ecology and Evolutionary\u00a0Biology.<\/p>\n The researchers used a technique called \u201csingle-cell transcriptomics,\u201d 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 \u201cinvasive trophoblast,\u201d which has likely helped shape the evolution of the placenta. \u201cWe uncovered a genetic signature linked to these placental cells that has persisted for over 100 million years,\u201d Stadtmauer said. \u201cAnd it\u2019s not unique to humans, as was traditionally thought, but part of an ancient heritage shared even with\u00a0marsupials.\u201d<\/p>\n The findings also revealed that a type of uterine cell \u2014 called decidual cells \u2014 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\u00a0two.<\/p>\n \u201cThis cross-species research opens the door to a powerful new framework for understanding how pregnancy evolved, and how cells cooperate to build complex traits,\u201d said senior author G\u00fcnter Wagner, the\u00a0Alison Richard Professor Emeritus of Ecology and Evolutionary\u00a0Biology.<\/p>\n Other researchers include researcher\u00a0Jamie Maziarz, who is now in the Department of Molecular, Cellular, and Developmental Biology in Yale\u2019s Faculty of Arts and Sciences (FAS), and collaborators from the University of Vienna and the University of Nevada, Las\u00a0Vegas.<\/p>\n 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\u00a0Fund.<\/p>\n Yale chemists go \u2018retro\u2019 with new AI-based\u00a0model<\/p>\n Retrosynthesis, a longstanding challenge in organic chemistry, has a complexity that is similar to a game of chess. You have a target molecule you\u2019re aiming for, a set of basic materials to get there, and must pursue a set of steps to accomplish the\u00a0task.<\/p>\n But in retrosynthesis, the possibilities for each step expand exponentially, making it incredibly difficult and time-consuming to reach a\u00a0target.<\/p>\n But in a recent study published in the Journal of Chemical Information and Modeling<\/a>, Yale\u2019s 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\u00a0Devices.<\/p>\n 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<\/a>, is open-source, and already has filled more than 800 requests from 100\u00a0users.<\/p>\n \u201cInstead of older methods, we re-framed the problem as a sequence prediction task, allowing us to train a transformer model \u2014 the same architecture behind large language models like ChatGPT \u2014 to predict entire synthesis routes natively,\u201d said Anton Morgunov, a Ph.D. candidate in the GSAS (and a member of Batista\u2019s lab) and co-lead of the project with Ph.D. candidate Yu Shee.<\/p>\n 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\u00a0year.<\/p>\n The researchers noted that while they have not completely solved the challenge of retrosynthesis \u2014 their model struggles with particularly complex chemical structures \u2014 their approach shows promise and can be refined\u00a0further.<\/p>\n Machine learning and climate\u00a0change<\/p>\n A Yale Center for Natural Carbon Capture<\/a> (YCNCC) research team has received a $50,000 Phase 1 award from the Bezos Earth Fund\u2019s AI for Climate and Nature Grand Challenge<\/a>.<\/p>\n 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.<\/p>\n 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\u2019s Phase II awards, expected later this year. Each Phase II awardee team will receive up to $2\u00a0million.<\/p>\n 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\u00a0change.<\/p>\n Hungry for\u00a0knowledge<\/p>\n Nearly 4 million<\/a> 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\u00a0students.<\/p>\n A new study from a team of Yale researchers addresses this question, finding that nearly 1 in 4 medical students were food insecure. (\u201cFood insecurity\u201d 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<\/a> Academic Medicine, the study was led by YSM students with support from John Solomon Francis,\u00a0YSM\u2019s associate dean for student affairs and co-author of the\u00a0study.<\/p>\n \u201cFood insecurity among medical students is not just a personal hardship \u2014 it\u2019s a systemic failure,\u201d\u00a0said Mytien Nguyen, an M.D.-Ph.D. candidate at YSM and one of the first authors of the study. \u201cNo student should be expected to learn, train, and care for others while struggling to meet their basic\u00a0needs.\u201d\u00a0<\/p>\n Bassel Shanab, an M.D. candidate at YSM and another first author, added: \u201cFood 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\u00a0physician.\u201d\u00a0<\/p>\n 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\u2019s Household Food Security Survey\u00a0Module.\u00a0<\/p>\n 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\u00a0needs.<\/p>\n Karen Guzman, Jim Shelton, Kevin Dennehy, and Meg Dalton contributed to this\u00a0report.<\/p>\n Research\u00a0Redux:<\/p>\n The cure for cystic fibrosis might start in the\u00a0womb<\/a><\/p>\n Simpler, less costly virus testing in high-risk\u00a0settings<\/a><\/p>\n Yale genome engineers expand the reach and precision of human gene\u00a0editing<\/a><\/p>\n This \u2018jellyfish\u2019 has bunny ears \u2014 and swims in a galaxy\u00a0cluster<\/a><\/p>\n