Publisher Health

Newly developed flexible, porous and highly sensitive nitrogen dioxide sensors that can be applied to skin and clothing have potential applications in health care, environmental health monitoring and military use, according to researchers.
Led by Huanyu “Larry” Cheng, assistant professor of engineering science and mechanics at Penn State, the researchers published their sensor designs, which build on previous models, and results in ACS Applied Materials and Interfaces.
The sensors monitor nitrogen dioxide, either from breath if attached under the nose, or from perspiration, if attached elsewhere on the body. Unlike taking blood samples, the direct skin attachment allows for continuous, long-term monitoring of the gas.
Cheng explained that while similar sensors exist, a key differentiator of the new design is breathability.
“The commonly used substrate materials for gas sensors are flexible, but not porous,” he said. “The accumulation of water moisture from the skin surface can potentially lead to irritation or damage to the skin surface. We need to make sure the device can be porous so that moisture can go through the sensor without accumulation on the surface.”
The researchers created the new sensors using a fabrication method known as laser direct writing.
“Laser direct writing is similar to additive manufacturing in that it is easy to set up and low cost, and the laser is widely available,” Cheng said. “The process is relatively robust, rapid and could be scaled up to large-scale manufacturing production.”
Cheng and his team integrated a type of material known as block copolymers with resin to laser write sensors with the desired breathability.
“Block copolymer integration goes beyond the materials we have been using, so we explored extending the substrate material from the typical thin film to virtually anything,” Cheng said. “That can give us breathability and tunability of the pore size.”
Cheng said that the sensor could monitor conditions such as chronic obstructive pulmonary disease, which nitrogen dioxide can cause or make worse. He also noted that while the sensors were developed specifically to detect nitrogen dioxide, they could potentially detect a variety of gases and biomarkers — to determine glucose levels to monitor diabetes, for example, or to identify hazards in industrial or combat settings.
“The sensors can also be useful for monitoring gas in the environment,” he said. “We could monitor air quality and inform patients of potential concerns about too much exhaust from cars, for example. Then, they could use that information to avoid certain areas on certain days.”
Other authors on this paper are Li Yang, Huadong Ji, Chuizhou Meng, Guanhao Zheng, Xue Chen, Guangyu Niu, Jiayi Yan, Ye Xue and Shijie Guo, all of Hebei University of Technology in Tianjin, China; and Yuhang Li of Beihang University in Beijing. The National Natural Science Foundation of China, the Key Research and Development Project of Hebei Province, the National Science Foundation, the National Institutes of Health and Penn State funded this work.
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A hospital or medical clinic might be the last place you’d expect to pick up a nasty infection, but approximately 1.7 million Americans do each year, resulting in nearly 100,000 deaths from infection-related complications and roughly $30 billion in direct medical costs.
The biggest culprits, experts say — accounting for two-thirds of these infections — are medical devices like catheters, stents, heart valves and pacemakers, whose surfaces often become covered with harmful bacterial films. But a novel surface treatment developed by a UCLA-led team of scientists could help improve the safety of these devices and ease the economic burden on the health care system.
The new approach, tested in both laboratory and clinical settings, involves depositing a thin layer of what is known as zwitterionic material on the surface of a device and permanently binding that layer to the underlying substrate using ultraviolet light irradiation. The resulting barrier prevents bacteria and other potentially harmful organic materials from adhering to the surface and causing infection.
The team’s findings are published May 19 in the journal Advanced Materials.
In the laboratory, researchers applied the surface treatment to several commonly used medical device materials, then tested the modified materials’ resistance to various types of bacteria, fungi and proteins. They found that the treatment reduced biofilm growth by more than 80% — and in some cases up 93%, depending on the microbial strain.
“The modified surfaces exhibited robust resistance against microorganisms and proteins, which is precisely what we sought to achieve,” said Richard Kaner, UCLA’s Dr. Myung Ki Hong Professor of Materials Innovation and senior author of the research. “The surfaces greatly reduced or even prevented biofilm formation.

People with neurofibromatosis type 1 (NF1) develop tumors on nerves throughout their bodies. These tumors are usually benign — meaning they don’t spread to other parts of the body and are not considered life-threatening — but they can still cause serious medical problems such as blindness, especially when they form in the brain and nerves.
Researchers at Washington University School of Medicine in St. Louis have discovered that neurons carrying a mutation in the Nf1 gene are hyperexcitable and that suppressing this hyperactivity with lamotrigine, a drug approved by the Food and Drug Administration to treat epilepsy, stops tumor growth in mice.
“Tumors are very common in people with NF1,” said senior author David H. Gutmann, MD, PhD, the Donald O. Schnuck Family Professor and director of the Washington University Neurofibromatosis (NF) Center. “We’ve shown that we can block the growth of NF1 tumors by shutting off neuronal hyperexcitability. We’ve done it now a couple of different ways, and there’s no question that repurposing antiepileptics is an effective way to inhibit tumor growth, at least in mice. This underscores the critical role that neurons play in tumor biology.”
The study is published May 19 in Nature Communications.
NF1 is a genetic disorder that affects one in every 3,000 people worldwide. The condition is caused by mutations in the NF1 gene. Any part of the body can be affected, but the most common signs of the disorder are light brown spots on the skin, benign nerve tumors called neurofibromas, tumors of the brain and optic nerves, bone deformities, and cognitive differences such as autism, learning disabilities and attention deficit hyperactivity disorder.
Last year, Gutmann and Michelle Monje, MD, PhD, a professor of neurology at Stanford University School of Medicine and a Howard Hughes investigator, showed that light induces increased neuronal activity in the eyes of Nf1-mutant mice, which then causes tumors to form on the optic nerve that connects the eyes and the brain. In the new study, they — along with first author Corina Anastasaki, PhD, an assistant professor of neurology at Washington University, and co-author Lu Q. Le, MD, PhD, a professor of dermatology at the University of Texas, Southwestern Medical Center — investigated how increased neuronal activity leads to tumors in people with NF1.
The researchers studied neurons from mice with and without Nf1 gene mutations. At baseline, neurons from mice with tumor-causing Nf1 mutations fired electrical impulses more frequently than neurons from normal mice. These hyperexcitable neurons then released molecules that increased the growth of brain and nerve tumors. This hyperexcitability, the researchers discovered, was the result of a dysfunctional ion channel that changed the baseline electrical activity inside the neurons.
They also studied mice with an Nf1 mutation seen in people with NF1 who do not develop brain or nerve tumors. Anastasaki found that neurons from mice with this specific Nf1 mutation are not hyperexcitable and do not develop tumors — providing the first explanation for why this group of patients with NF1 lack optic gliomas or neurofibromas.
Hyperexcitable neurons are also a feature of epilepsy, and the epilepsy medication lamotrigine targets the same ion channel disrupted in hyperexcitable Nf1-mutant neurons. The researchers gave lamotrigine to a group of Nf1-mutant mice that develop optic nerve tumors. Compared to mice receiving placebo, mice that had received the drug had smaller tumors, which no longer were growing.
Apart from suggesting a new way to treat NF1 tumors, these findings also suggest a new way of thinking about the origins of the disorder’s cognitive symptoms.
“The mutation in the Nf1 gene changes the basic biology of the neuron,” Gutmann said. “During development, neurons form first and tell the rest of the brain how to form. If you have a mutation that affects how neurons behave, that may change everything about how the brain gets set up during development. Nothing we’ve tried so far to prevent learning disabilities has worked. Maybe this discovery could lead to new treatments for the learning and cognitive problems in children with NF1.
“I’m very excited about the scientific and medical implications of these findings. Not hyperexcited,” he added, “but excited.”

Trinity scientists, along with international colleagues, have explored the importance of sea travel in prehistory by examining the genomes of ancient Maltese humans and comparing these with the genomes of this period from across Europe. Previous findings from the archaeological team had suggested that towards the end of the third millennium BC the use of the Maltese temples declined. Now, using genetic data from ancient Maltese individuals the current interdisciplinary research team has suggested a potential contributing cause. Researchers found that these ancient humans lacked some of the signatures of genetic changes that swept across Europe in this period, because of their island separation. Scientists concluded that physical topography, in particular seascapes played a central role as barriers to genetic exchange.
The study is published today in the journal Current Biology.
Researchers found these Mediterranean islanders were unusual for their time. They showed evidence of inbreeding in their family history, a sign of small, restricted population size indicating genetic isolation. Interestingly researchers found that one of the ancient individuals analysed was the offspring of second-degree relatives. This was an outstanding find as the number of highly inbred individuals is very low even in ancient times, and this is the second most inbred individual yet detected from the Neolithic world.
Scientists in the ancient DNA laboratory in Trinity sequenced the genomes of ancient (4500-5000 yrs old) Maltese humans from the collective cave burials at the Xaghra Circle and compared these with genomes of contemporary groups from around Europe. Trinity collaborated with colleagues from Queen’s University Belfast, the University of Cambridge, the Superintendence of Cultural Heritage Malta and others on the study.
Scientists recreated the genetic geography across the whole of Europe at the time of the earliest farmers. They found evidence that it was fundamentally shaped by its seascapes which include barriers distinguishing Ireland and Britain from the continental mainland, and especially distinguishing the populations from the Scottish Orkney islands. These examples are powerful illustrations of genomic insularity. For genes at least, the seaways were more retardant than accelerant of connection.
The first settlers in the Maltese islands were Neolithic, dated by Queen’s University from the sixth millennium BC. Communities developed through a series of cultural phases, with some material indications of external connectivity. Maltese culture flourished from 3600 BC with distinctive craft and architecture only found on the islands. One example was the development of elaborate mortuary structures, such as the Xaghra circle, Gozo. This monumentalized underground tomb yielded the remains of hundreds of individuals and underwent remodelling and enlargement until around 2500 BC when it was abandoned, possibly as part of a wider population decline or replacement.

Everyone has been impacted by the COVID-19 pandemic, but a new study by Lude Franke and colleagues of the University of Groningen, Netherlands finds that some individuals weathered the stress of the pandemic better than others, in part, due to their genetics. The new study is publishing May 12th in the open-access journal PLOS Genetics.
How a person perceives their quality of life depends on a combination of factors that include the genes they inherited from their parents and their environment — a mix of nature and nurture. Studying genes related to quality of life can be complicated, but the COVID-19 pandemic allowed Franke and his colleagues to investigate how this stressful, worldwide event interacted with a person’s genetics to affect their overall wellbeing. The team screened the genomes of more than 27,000 participants in the Netherlands who had donated genetic material to a biobank. Then they looked for connections between genetic variants and the participants’ responses to a series of questionnaires about lifestyle and mental and physical health given over 10 months, starting in March 2020.
The researchers found that some individuals had a genetic tendency toward better wellbeing than others during the pandemic. Additionally, as the pandemic wore on, they found that genetic tendency had an increasingly powerful influence on how those people perceived their quality of life, potentially due to the social isolation required by strict COVID-19 containment measures. Moreover, the findings demonstrate that the contribution of genetics to complex traits like wellbeing can change over time.
Fellow author Robert Warmerdam adds, “The COVID-19 pandemic has been a unique opportunity to investigate the impact of genetics on wellbeing in a time wherein we had to socially isolate ourselves. We found that it is during the first, stressful year of the pandemic that it is our nature that has gained relative impact on how we rate our lives.”
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Repurposed drugs may have a speedier path to clinical use because they have already been shown to be safe in people. A study publishing May 19in the open access journal PLOS Pathogens by Sandrine Belouzard and Jean Dubuisson at Pasteur Institute, Lille, France and colleagues suggests clofoctol may be an effective treatment for SARS-CoV-2 infections in mice.
While COVID-19 vaccines reduce hospitalizations and death, they do not control virus transmission, and affordable, effective therapies are needed. Previous attempts to repurpose medicines to treat COVID-19 patients have been unsuccessful. In order to identify potential antiviral therapies effective against COVID-19, authors accessed the Apteeus drug library, a collection of 1,942 approved drugs to identify molecules that exhibit antiviral activity against SARS-CoV-2. The authors selected clofoctol based on its antiviral potency and tested their hypothesis by testing its effects in SARS-CoV-2-infected mice.
The researchers found that transgenic mice treated with clofoctol had a decreased viral load, reduced inflammatory gene expression, and lowered pulmonary pathology. Future studies are needed to further understand the drug’s therapeutic potential in SARS-CoV-2 patients as the study was limited by the physiological differences between humans and mice. Additionally, the mice were sacrificed only two days after treatment, so longer-term effects remain unknown.
According to the authors, “The antiviral and anti-inflammatory properties of clofoctol, associated with its safety profile and unique pharmacokinetics make a strong case for proposing clofoctol as an affordable therapeutic candidate for the treatment of COVID-19 patients. Finally, the relatively low cost of this drug suggests that it is a potential clinical option for treatment of COVID-19 patients in resource-poor settings.”
“Antivirals targeting SARS-CoV-2 are sorely needed,” adds Dubuisson. “In this study, we screened a library of drug compounds and identified clofoctol as an antiviral against SARS-CoV-2. We further demonstrated that, in vivo, this compound reduces inflammatory gene expression and lowers pulmonary pathology and decreases viral load.”
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Combining a genetic risk score with a clinical risk score improved the prediction of type 2 diabetes in British Pakistani and British Bangladeshi individuals, especially in the young, according to a new study publishing May 19 in the open access journal PLOS Medicine by Sarah Finer of Queen Mary University of London, UK, and colleagues.
The common genetic changes associated with type 2 diabetes have been extensively studied in people of European ancestry. However, it is not known whether all previous findings can be applied to people of south Asian ancestry, who are disproportionately affected yet also underrepresented in genetic studies. The new study used genomic and routine health data from Genes & Health, a large, population study of British Pakistanis and British Bangladeshis, including 7,599 with a diagnosis of type 2 diabetes.
The researchers found significant genetic differences in type 2 diabetes risk compared to what had been seen in previous studies on European populations. Out of 338 genetic loci identified in European populations, just 76 (22.5%) were transferable to the study population of British Pakistanis and British Bangladeshis. The team then constructed a type 2 diabetes polygenic risk score for the population in the study. When combined with QDiabetes, a routinely-used clinical risk score, the tool improved the prediction of type 2 diabetes (OR per SD of 1.57, 95% CI 1.50-1.65). The tool was particularly effective in assessing risk in British Pakistani and British Bangladeshi people under the age of 40 (net reclassification index 5.6%, 95% CI 3.6 — 7.6%), and also in predicting the development of type 2 diabetes after gestational diabetes. Finally, the polygenic risk score was able to elucidate disease subgroups which are linked to differences in the risk of future diabetes complications.
“Our work highlights the importance of greater representation of diverse ancestry groups in genetic studies of type 2 diabetes,” the authors say. “Our polygenic risk score has multiple potential uses, but importantly, it helped identify young, otherwise healthy, individuals who were in fact living at high risk of type 2 diabetes, 1 in 20 of whom might have been mistakenly labelled as low risk by current clinical risk tools. Our work also shows the potential use of polygenic risk scores in characterizing distinct disease subgroups at diagnosis which have different rates of progression to diabetes complications.”
Finer adds, “We hope to see polygenic risk scores being adopted in clinical care in the future, after careful evaluation to understand their potential to improve health outcomes cost-effectively, and with diverse populations who are at greatest need.”
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A common culprit of skin and respiratory infections, Staphylococcus aureus is highly unpredictable. Between 20 and 30 percent of people carry quiet colonies on their skin and in their nostrils, which seldom cause problems beyond the occasional rash. But in some cases these bacteria cause infections that lead to deadly complications, such as pneumonia, deep skin infections, and sepsis. Until recently, there was no way to predict which infections may take a lethal turn.
Now, a new study describes mutations that predispose patients to severe staphylococcal infections. The research, published in Science, identifies a mutated gene common to multiple patients who suffer life-threatening staph infections and suggests that people living with a genetic condition known as 5p- or Cri-du-chat syndrome may be at similar risk.
“We have characterized severe Staphylococcus aureus infection at the genetic, cellular, immunological, and clinical levels,” says András Spaan, first author on the study. “By integrating these levels, we have established causality and provided clues for future interventions.”
A first for cell intrinsic immunity
To better understand why S. aureus causes disease in some people but not others, scientists in the laboratory of Rockefeller immunologist Jean-Laurent Casanova examined the protein-coding genomes of more than 100 patients who had suffered from unexplained severe staph infections.
The common genetic thread linking some of these disparate patients were mutations of a gene called OTULIN, which is perched along the short arm of chromosome 5 and codes for an enzyme involved in regulating inflammation. These individuals were not entirely bereft of OTULIN — only one of their two copies of the gene was mutated — but that deficiency appeared to be all it took to render them vulnerable to infections that would scarcely harm other people.

From extreme weather to another wave of COVID-19, forecasts give decision-makers valuable time to prepare. When it comes to COVID, though, long-term forecasting is a challenge, because it involves human behavior.
While it can sometimes seem like there is no logic to human behavior, new research is working to improve COVID forecasts by incorporating that behavior into prediction models.
UConn College of Agriculture, Health and Natural Resources Allied Health researcher Ran Xu, along with collaborators Hazhir Rahmandad from the Massachusetts Institute of Technology, and Navid Ghaffarzadegan from Virginia Tech, have a paper out today in PLOS Computational Biology where they detail how they applied relatively simple but nuanced variables to enhance modelling capabilities, with the result that their approach out-performed a majority of the models currently used to inform decisions made by the federal Centers for Disease Control and Prevention (CDC).
Xu explains that he and his collaborators are methodologists, and they were interested in examining which parameters impacted the forecasting accuracy of the COVID prediction models. To begin, they turned to the CDC prediction hub, which serves as a repository of models from across the United States.
“Currently there are over 70 different models, mostly from universities and some from companies, that are updated weekly,” says Xu. “Each week, these models give predictions for cases and number of deaths in the next couple of weeks. The CDC uses this information to inform their decisions; for example, where to strategically focus their efforts or whether to advise people to do social distancing.”
The Human Factor
The data was a culmination of over 490,000 point forecasts for weekly death incidents across 57 US locations over the course of one year. The researchers analyzed the length of prediction and how relatively accurate the predictions were across a period of 14 weeks. On further analysis, Xu says they noticed something interesting when they categorized the models based on their methodologies: