It’s possible that I shall make an ass of myself. But in that case one can always get out of it with a little dialectic. I have, of course, so worded my proposition as to be right either way (K.Marx, Letter to F.Engels on the Indian Mutiny)
Wednesday, July 22, 2026
Researchers develop automated system to accelerate outbreak detection and disease surveillance
PROVIDENCE, R.I. [Brown University] — Biomedical engineers at Brown University have developed a fully automated workflow that simplifies and accelerates the preparation of bacterial samples for genetic sequencing.
The method, dubbed Pathogen2Read, streamlines a critical bottleneck in the genetic sequencing process and could enable small labs without high-throughput automation to more effectively participate in outbreak-monitoring networks operated by the U.S. Food and Drug Administration (FDA) and the Centers for Disease Control. That could make for faster responses to foodborne illnesses and other outbreaks.
“Next-generation sequencing has become a staple in outbreak detection and prevention,” said Kathryn Whitehead, a graduate student in Brown’s School of Engineering who led the work. “But sample preparation involves labor-intensive manual preparation and culture isolation, which can delay real-time outbreak responses. Our laboratory has developed what is, to our knowledge, the first fully automated scientific method that bypasses these limitations.”
Research describing and testing the method, which was developed in collaboration with researchers at the FDA and with funding from the biotech firm Revvity, is published in BMC Genomics.
Next-generation sequencing has revolutionized modern epidemiology by allowing scientists to rapidly sequence the entire genomes of potential pathogens in just a few hours or days. That enables researchers and public health professionals to quickly identify pathogens involved in illness outbreaks or to pinpoint new genetic mutations that may make known pathogens harder to treat.
But the process involved in preparing samples for sequencing is complex and labor-intensive. It’s a multistep process that involves isolating microbes, breaking cell membranes open (a process called lysis), extracting and purifying the DNA, and arranging it into readable segments. Current techniques require eight to 10 hours of hands-on work plus up to 16 hours of waiting time. Any mistakes along the way could require doing the entire process all over again.
The Pathogen2Read workflow includes assay preparation steps, custom software and a specially prepared enzyme cocktail that enables a desktop liquid-handling machine to handle all the steps of DNA sample prep — lysis, extraction and library preparation — entirely on its own. The researchers successfully compressed the hands-on preparation time from nearly a full day to under 45 minutes. Once an operator loads the raw samples and reagents onto a single plate, the system handles the rest automatically over a six-hour run, outputting pristine, sequencer-ready DNA libraries.
The quality of the DNA libraries is critical, particularly when looking for mutations in a bacterial strain.
“Because you're looking for small mutations that may be involved in drug resistance, for example, it’s easy to miss them if you’re not capturing all the sequences,” said co-author Anubhav Tripathi, a professor of engineering and a faculty affiliate of Brown’s Institute for Biology, Engineering and Medicine. “So the quality of the sample preparation is critically important.”
At the crux of the new workflow, Whitehead says, is the enzyme cocktail, which quickly and effectively breaks open different types of bacteria. Bacteria come in two broad structural forms, gram-negative and gram-positive. The membrane structure of gram-positive bacteria makes them more difficult to crack open to extract DNA. That can cause the presence of gram-positive bacteria to be missed in a sample if the preparation process fails to crack them open. The researchers demonstrated an enzyme cocktail that had a nearly 2.5-fold improvement over standard methods in capturing gram-positive DNA, and reduced waiting time from 16 hours to 30 minutes.
The researchers are hopeful the method will improve outbreak monitoring and prevention by bringing smaller, local public health laboratories into the fold.
“The reason we're so excited about this is it was developed with real-world impact in mind,” Whitehead said. “Having that collaboration with the FDA, being able to get their responses and their input on what they need to see, has allowed us to develop a method that actually can be used and doesn't have some of the limitations that you may sometimes see going from academic to translational research.”
Although the effects of air pollution on respiratory diseases are well established, its effects on cardiometabolic health are often overlooked. This population-based European cohort study led by the Barcelona Institute for Global Health (ISGlobal), a centre supported by the ”la Caixa” Foundation, suggests that higher exposure to air pollutionduring childhood at home and at school may increase the risk of metabolic syndrome. The study was published in Environmental Research.
Air pollution is a major environmental risk factor for health and has been linked to a wide range of adverse health outcomes in adults, including cardiovascular disease and metabolic syndrome. Children are particularly vulnerable because their organs and immune systems are still developing, they breathe more air relative to their body weight, and they tend to spend more time outdoors. Metabolic syndrome refers to a cluster of risk factors, including abdominal obesity, high blood pressure, abnormal blood sugar and dyslipidaemia, that can increase the risk of type 2 diabetes and heart disease later in life.
To investigate this, researchers analysed data from 1,147 children aged 6 to 11 years from France, Greece, Lithuania, Norway, Spain, and the United Kingdom who were followed up with between 2013 and 2016 within the HELIX project. “We estimated exposure to PM2.5 and NO2 at home, school and during commuting, and examined its relationship with a metabolic syndrome risk score,” says Anne van Rooijen Korving, researcher at ISGlobal and first author of the study.
Using validated air pollution models based on residential, school and commuting environments, the team estimated annual exposure to both pollutants during the year prior to clinical assessment. Associations with metabolic syndrome risk were examined using multivariable regression models, and metabolic syndrome risk was calculated using a previously validated score based on waist circumference, blood pressure, blood lipids and insulin levels, following International Diabetes Federation criteria.
Stronger associations at school than at home
Air pollution was more strongly associated with metabolic syndrome risk at school than at home, suggesting that children may be particularly vulnerable in the school environment. Although pollution levels at home and at school were highly correlated (with annual PM2.5 and NO2 concentrations consistently exceeding World Health Organization guidelines), susceptibility appears to be greater at school. Previous research indicates that higher levels of physical activity at school increase breathing rates, which could amplify the adverse effects of pollution exposure. Conversely, no associations were found between exposure on commuting routes and metabolic syndrome risk. Similarly, no associations were observed for short-term exposure in the days or week before clinical assessment, supporting the idea that metabolic changes develop gradually over time rather than in response to acute exposure.
Potential biological mechanisms and public health implications
Several biological mechanisms may explain these findings. Air pollution exposure has been linked to systemic inflammation, oxidative stress, and disruptions in lipid metabolism, glucose regulation and blood pressure control — all processes involved in the development of metabolic syndrome.
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Air pollution mixtures may pose hidden risks during pregnancy
Using machine learning, University of Utah researchers found that repeated exposure to combinations of common air pollutants in early pregnancy was associated with nearly three-times greater odds of early preterm birth
Typical cluster characters, determined by comparing the average of each cluster’s pollutant concentrations to the entire distribution (very low, low, moderate, high, very high). Cluster 10 had the strongest relationship to preterm birth.
Credit: Kelly et. al., J Expo Sci Environ Epidemiol (2026)
Pregnancy puts higher oxygen demands on the body, so expectant mothers breathe significantly more air over the course of a day. When air quality is bad, they’re also breathing in more harmful pollutants. Many studies have linked individual air pollutants, such as fine particulate matter (PM2.5) or ozone, to early preterm birth—delivery before 34 weeks’ gestation, when infants face higher risks of health complications. But those studies don’t reflect the reality that people are often exposed to mixtures of pollutants simultaneously.
In a new University of Utah study of 44,874 first-time mothers in Utah, researchers found that exposure to even moderate levels of multiple air pollutants may increase the risk of preterm birth when experienced together—especially during critical stages of pregnancy.
The findings raise questions about whether current air quality index (AQI) ratings—typically based on the single pollutant posing the greatest harm—may be missing serious health risks to the public.
“People are exposed to multiple things at once, over multiple times,”saidBrenna Kelly, lead author on the paper. Kelly is a recent graduate of the University of Utah’s Population Health Sciences PhD program and an incoming Responsible AI Postdoctoral Fellow. “It may matter when pollution is slightly elevated for multiple chemicals.”
Growing evidence suggests that environmental mixtures may have a greater impact on health than individual pollutants alone. But identifying which combinations to study remains a major challenge.
“Finding these patterns is like searching for a needle in a haystack—without the machine learning component, testing all combinations of mixtures would have been intractable,” Kelly said.
This study focused on air pollution and preterm births in Utah, a state that intermittently has some of the worst air quality in the world. The researchers developed an epidemiologic machine learning framework using a self-organizing map, a type of neural network that finds patterns in data. Similar models have assessed environmental mixtures, but this is the first to link them to health outcomes over time.
"Brenna’s work helps demonstrate the potential of machine learning and artificial intelligence in tackling complex environmental problems and in the assessment of their impacts,” said Simon Brewer, professor in the U’s School of Environment, Society & Sustainability and coauthor of the study. “U has been key in supporting this work, both through the DELPHI initiative, and more broadly across campus as thematic areas within the U’s Responsible AI Initiative.”
The scientists provided the model with high-resolution air pollution data from Utah between 2013 and 2016, focusing on temperature and three common pollutants: nitrogen dioxide (NO2), ozone (O3) and fine particulate matter PM2.5. The algorithm identified 12 distinct mixtures, and the researchers then modeled the effect of these exposures on early preterm birth during each week of pregnancy.
Early pregnancy: A critical window
Exposure to a mixture of O3 and PM2.5 in the late first trimester had the strongest relationship to early preterm birth. Because the AQI does not take multiple exposures into account, the EPA would have considered these levels “safe” air quality, although it may still pose risks to health. Women exposed to this mixture in week 11 of pregnancy had 53% greater odds of a preterm birth later in pregnancy. Additionally, those exposed repeatedly over weeks 9-14 had almost three-times greater odds of preterm birth.
“Many different pathways could lead to early preterm birth, including inflammation, infection or problems with placental development,” said Michelle Debbink, associate professor of obstetrics and gynecology at the U and coauthor of the study. “Early pregnancy is a critical period because the placenta and arteries that supply blood and oxygen to the fetus are still developing. Exposure to pollutants at this juncture could impair this process, increasing the risk of complications such as preeclampsia, which can require preterm delivery. Repeated exposures could also cause inflammation and damage that accumulates over time, further increasing the risk of preterm birth.”
Rethinking air quality standards
The authors hope that scientists will use this framework to better understand how other types of environmental hazards may impact human health.
“Public health policy definitely oversimplifies real-world exposures, but research into the health effects of complex mixtures is the first step in improving these policies,” Kelly said.
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Other authors include Robert Silver of the U’s Department of Obstetrics and Gynecology; Heather Holmes of the U’s Department of Chemical Engineering; Heidi Hanson of both the U’s Department of Population Health Sciences (DPH) and Oak Ridge National Laboratory; and Jennifer Doherty of the U’s DPH and Huntsman Cancer Institute; and Joel Schwartz of the Harvard T.H. Chan School of Public Health.
Linking mixtures of air pollution exposures and preterm birth with a self-organizing map
In pilot study, researchers find estrogen-like contaminant in every pregnant participant tested
Rutgers scientists examine hormone-mimicking mycotoxins linked to corn and other grains, calling for awareness of an emerging food contaminant in the U.S.
Consuming common foods such as corn chips and popcorn may put pregnant women at risk of being exposed to mycotoxins – harmful substances produced by mold – according to Rutgers researchers.
Theirstudy, published in the Journal of Exposure Science & Environmental Epidemiology, found hormone-mimicking mycotoxins in 100% of participants and linked exposure levels to the amount of corn and grain products consumed.
One such mycotoxin is zearalenone, a compound produced by Fusarium fungi that contaminate staple crops such as corn, wheat and oats. Zearalenone can indirectly enter human food supplies through meat and dairy from animals that eat contaminated feed. It also is heat-stable, so it can survive cooking and food processing.
As zearalenone can mimic estrogen, a hormone critical to pregnancy and fetal development, it is a mycotoxin that is more specifically classified as a mycoestrogen. Other studies suggest that exposure to mycoestrogens may contribute to greater gestational weight gain and lower infant birthweight.
“Mycoestrogens are among the most common food contaminants worldwide, yet evidence on their dietary sources in the United States has been limited,” said Zorimar Rivera-Núñez, an assistant professor at Rutgers School of Public Health and the lead author of the study. “They have potent estrogenic properties, but we know very little about how these exposures may affect pregnant women and their developing babies.”
The researchers said the pilot study, known as the Jersey Babies pilot study, is among the first in the U.S. to pair pregnant women's dietary intake with mycoestrogen biomarkers collected at the same time. This approach can help researchers pinpoint specific dietary sources of mycoestrogen exposure.
The study followed 33 pregnant women recruited from obstetric clinics at Saint Peter’s University Hospital and Rutgers Robert Wood Johnson University Hospital in New Brunswick, N.J. Participants provided urine samples and completed detailed 24-hour dietary recalls at three points in pregnancy, allowing the researchers to closely match what participants ate with what showed up in their urine.
Researchers analyzed the urine samples for several mycoestrogens, including zearalenone. Findings showed at least one mycoestrogen was detected in every single urine sample collected.
Zearalenone itself was detected in most participant samples at all three visits. Its levels remained relatively stable across pregnancy for several participants, suggesting that exposure was persistent rather than a one-time event.
Researchers found that consumption of corn and other grain products in the 24 hours before a urine sample was collected was strongly associated with higher mycoestrogen levels.
Corn-based foods, including corn, corn chips and corn tortillas, showed the strongest associations, followed by more modest links to cereal grains and oils. By contrast, consumption of chicken and pork showed weaker, inverse associations, suggesting corn and grain products, rather than meat, were the primary dietary contributors to exposure in this study group.
The study’s findings also suggest differences by ethnicity.
Participants who identified as Hispanic had mycoestrogen levels that were higher than non-Hispanic participants across the three study visits. Hispanic participants also reported eating more corn and corn-based products, as well as more dairy, than non-Hispanic participants.
“Identifying groups with higher exposures is a critical first step for our mycoestrogen research program,” Rivera-Núñez said. “It helps us understand the factors driving those exposures and provides the information needed to develop strategies that protect maternal and child health.”
According to the researchers, the U.S. Food and Drug Administration added zearalenone to its Mycotoxin Compliance Program in 2024 but hasn’t yet established maximum allowable limits in food. On a global scale, the European Commission has set limits for zearalenone in cereals, baked goods and infant food.
The researchers said the findings establish mycoestrogens as an emerging and understudied exposure among U.S. pregnant women, setting a foundation for future research into potential reproductive, developmental and child health outcomes.
“Pregnancy represents a unique opportunity for prevention,” Rivera-Núñez said. “By understanding how everyday dietary choices contribute to environmental chemical exposures, we can provide families with information that supports both maternal and child health.”
Journal
Journal of Exposure Science & Environmental Epidemiology
Research suggests that more than half of children with autism spectrum disorder, a neurodevelopmental condition, experience motor impairments. An analysis in Developmental Medicine & Child Neurology indicates that sports-based interventions may improve motor skills in children with autism spectrum disorder, with martial arts and aquatic training demonstrating the most consistent benefits.
The analysis was based on data from 11 clinical trials of various sports. Martial arts demonstrated consistently large improvements in balance, total motor skills, and object control skills, with especially strong effects in Tai Chi Chuan and kata programs. Aquatic training demonstrated large improvements across balance, locomotor skills, and object control skills. Gymnastics and trampoline interventions demonstrated large improvements in balance and bilateral coordination, with additional effects on total motor scores in trampoline studies. Table tennis produced broad gross motor improvements, and Australian football had a large effect on object control skills and had a medium effect on balance and total motor skills. Across all sports categories, balance was the most consistently improved motor domain.
The authors noted that many of the studies had significant limitations, however, and higher-quality studies are needed.
“Organized sports-based interventions may offer benefits beyond recreation for children with autism by supporting motor skill development,” said corresponding author Sonia Khurana, PT, PhD, of Old Dominion University. “While our review identified promising effects, particularly for martial arts and aquatic training, larger and more rigorous studies are needed to confirm these benefits and guide evidence-based recommendations.”
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About the Journal Developmental Medicine & Child Neurology is a multidisciplinary journal that has defined the fields of paediatric neurology and childhood-onset neurodisability for over 60 years. DMCN disseminates the latest clinical research results globally to enhance the care and improve the lives of disabled children and their families.
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