Publisher Health

New research from NUI Galway and Boston University has identified a blood biomarker that could help identify people with the earliest signs of dementia, even before the onset of symptoms.
The study was published today (Tuesday 26 April) in the Journal of Alzheimer’s Disease.
The researchers measured blood levels of P-tau181, a marker of neurodegeneration, in 52 cognitively healthy adults, from the US-based Framingham Heart Study, who later went on to have specialised brain PET scans. The blood samples were taken from people who had no cognitive symptoms and who had normal cognitive testing at the time of blood testing.
The analysis found that elevated levels of P-tau181 in the blood were associated with greater accumulation of ß-amyloid, an abnormal protein in Alzheimer’s disease, on specialised brain scans. These scans were completed on average seven years after the blood test.
Further analysis showed the biomarker P-tau181 outperformed two other biomarkers in predicting signs of ß-amyloid on brain scans.
Emer McGrath, Associate Professor at the College of Medicine Nursing and Health Sciences at NUI Galway and Consultant Neurologist at Saolta University Health Care Group was lead author of the study.
“The results of this study are very promising — P-tau181 has the potential to help us identify individuals at high risk of dementia at a very early stage of the disease, before they develop memory difficulties or changes in behaviour,” Professor McGrath said.
The research team said the identification of a biomarker also points to the potential for a population screening programme.
Professor McGrath said: “This study was carried out among people living in the community, reflecting those attending GP practices. A blood test measuring P-tau181 levels could potentially be used as a population-level screening tool for predicting risk of dementia in individuals at mid to late-life, or even earlier.
“This research also has important potential implications in the context of clinical trials. Blood levels of P-tau181 could be used to identify suitable participants for further research, including in clinical trials of new therapies for dementia. We could use this biomarker to identify those at a high risk of developing dementia but still at a very early stage in the disease, when there is still an opportunity to prevent the disease from progressing.”
The research was funded in Ireland by a Health Research Board Clinician Scientist Award and in the US by an Alzheimer’s Association Clinician Scientist Fellowship, the National Heart Lung and Blood Institute, the National Institute on Aging, and the National Institute of Neurological Disorders and Stroke.
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A new study found risk factors for heart disease and stroke were higher among adults who said they experienced childhood abuse and varied by race and gender. However, those who described their family life as well-managed and had family members involved in their lives during childhood were less likely to have increased cardiovascular risk factors as adults, according to new research published today in the Journal of the American Heart Association, an open access, peer-reviewed journal of the American Heart Association.
Although cardiovascular disease, which includes heart disease and stroke, is more common among older people, the risks often begin much earlier in life. Previous research confirms physical and psychological abuse and other adverse experiences in childhood increase the risk of developing obesity, Type 2 diabetes, high blood pressure and high cholesterol, which, in turn, increase the risk for cardiovascular diseases, as detailed in the 2018 American Heart Association Scientific Statement: Childhood and Adolescent Adversity and Cardiometabolic Outcomes.
Conversely, healthy childhood experiences — nurturing, loving relationships in a well-managed household, including having family members who are involved and engaged in the child’s life — may increase the likelihood of heart-healthy behaviors that may decrease the cardiovascular disease risks. In this study, researchers explored whether nurturing relationships and well-managed households may offset the likelihood of higher cardiovascular risk factors.
“Our findings demonstrate how the negative and positive experiences we have in childhood can have long-term cardiovascular consequences in adulthood and define key heart disease risk disparities by race and sex,” said study lead author Liliana Aguayo, Ph.D., M.P.H., social epidemiologist and research assistant professor at Emory University’s Rollins School of Public Health in Atlanta.
Researchers examined information from the Coronary Artery Risk Development in Young Adults (CARDIA) Study, an ongoing, long-term study among 5,115 Black and white adults enrolled from 1985-1986 to 2015-2016. Study enrollment occurred in four U.S. cities: Birmingham, Alabama; Chicago; Minneapolis; and Oakland, California. More than half of the study participants were women, and nearly half were Black adults. At the start of the study, participants were 25 years old, on average. All participants received initial clinical examinations and eight additional examinations every few years to assess cardiovascular risks over 30 years.
At ages 33 to 45, participants completed a survey of questions to assess areas of their family life during childhood. For this analysis, three areas were examined: Abuse: how often a parent or adult in their home pushed, grabbed, shoved or hit them so hard that they were injured; and how often a parent or adult in their home swore at them, insulted them or made them feel threatened. Nurturing: how often a parent or adult made them feel loved, supported or cared for; and how often a parent or adult in the family expressed gestures of warmth and affection. Household organization: did they feel the household was well-managed, and did their family know where they were and what they were doing most of the time. (No definitions or criteria were provided for the term “well-managed;” study participants were instructed to determine if the term described their childhood family experience.)Participants were categorized based on their responses to the survey questions: Roughly 30% of participants reported experiencing “occasional/frequent abuse,” which included those who responded, “occasionally or moderate amount of time” or “most or all of the time” to questions related to abuse. About 20% of participants reported they experienced abuse “some or little of the time,” which was categorized as “low abuse.” About half of the participants reported no childhood abuse and described their family life during childhood as nurturing and well-managed.

According to folklore, silver bullets kill werewolves, but in the real world, researchers want to harness this metal to fight another deadly foe: bacteria. Recently, scientists have tried to develop a silver coating for implantable medical devices to protect against infection, but they’ve had limited success. In a study in ACS Central Science, one team describes a new, long-acting silver-ion releasing coating that, in rats, prevents bacteria from adhering to implants and then kills them.
Sometimes medical care requires surgeons to implant a device, such as a tube to drain a wound or the bladder, or to deliver medication directly into the blood. However, bacteria can attach to and collect on the surfaces of these devices, creating a risk for dangerous infections. Researchers have been working to develop bacteria-repelling coatings, including those containing silver, which is known to kill microbes. However, their efforts have faced numerous challenges: Silver can also be toxic to human cells, and it’s difficult to make a coating that continually releases small amounts of the metal over long periods, for example. Dirk Lange and Jayachandran Kizhakkedathu wanted to identify a formula that could overcome these and other difficulties.
To develop a simple-to-use coating, the team screened many sets of ingredients that they could apply to a surface in a single step. The formula that worked the best included silver nitrate, dopamine and two hydrophilic polymers. This silver-based film-forming antibacterial engineered (“SAFE”) coating formed stable, silver-containing assemblies, which gradually released silver ions in lab tests.
When exposed over 28 days to eight of the most common species of bacteria that cause serious infections, this new coating recipe effectively kept the microbes at bay. It did so in a unique way: by both repelling the bacteria from the surface and then killing them with silver ions. To test SAFE’s effectiveness in a living animal, they coated a titanium implant with it, then placed the implant beneath the skin of rats. After a week, the researchers found that implants with the coating had dramatically fewer bacteria than those without it. In addition, there were no signs of toxicity to the rats’ tissues. The coating also appeared tough, showing little wear and tear after being rubbed and sterilized using harsh conditions. This combination of attributes is likely to make the coating useful in many types of medical devices and implants to prevent bacterial infection over the long-term, the researchers say.
The authors acknowledge funding from the Canadian Institutes of Health Research, the Natural Sciences and Engineering Council of Canada, the Canada Foundation for Innovation, the British Columbia Knowledge Development Fund and the Michael Smith Foundation for Health Research.
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Colin Carlson, a biologist at Georgetown University, has started to worry about mousepox.The virus, discovered in 1930, spreads among mice, killing them with ruthless efficiency. But scientists have never considered it a potential threat to humans. Now Dr. Carlson, his colleagues and their computers aren’t so sure.Using a technique known as machine learning, the researchers have spent the past few years programming computers to teach themselves about viruses that can infect human cells. The computers have combed through vast amounts of information about the biology and ecology of the animal hosts of those viruses, as well as the genomes and other features of the viruses themselves. Over time, the computers came to recognize certain factors that would predict whether a virus has the potential to spill over into humans.Once the computers proved their mettle on viruses that scientists had already studied intensely, Dr. Carlson and his colleagues deployed them on the unknown, ultimately producing a short list of animal viruses with the potential to jump the species barrier and cause human outbreaks.In the latest runs, the algorithms unexpectedly put the mousepox virus in the top ranks of risky pathogens.“Every time we run this model, it comes up super high,” Dr. Carlson said.Puzzled, Dr. Carlson and his colleagues rooted around in the scientific literature. They came across documentation of a long-forgotten outbreak in 1987 in rural China. Schoolchildren came down with an infection that caused sore throats and inflammation in their hands and feet.Years later, a team of scientists ran tests on throat swabs that had been collected during the outbreak and put into storage. These samples, as the group reported in 2012, contained mousepox DNA. But their study garnered little notice, and a decade later mousepox is still not considered a threat to humans.If the computer programmed by Dr. Carlson and his colleagues is right, the virus deserves a new look.“It’s just crazy that this was lost in the vast pile of stuff that public health has to sift through,” he said. “This actually changes the way that we think about this virus.”Scientists have identified about 250 human diseases that arose when an animal virus jumped the species barrier. H.I.V. jumped from chimpanzees, for example, and the new coronavirus originated in bats.Ideally, scientists would like to recognize the next spillover virus before it has started infecting people. But there are far too many animal viruses for virologists to study. Scientists have identified more than 1,000 viruses in mammals, but that is most likely a tiny fraction of the true number. Some researchers suspect mammals carry tens of thousands of viruses, while others put the number in the hundreds of thousands.To identify potential new spillovers, researchers like Dr. Carlson are using computers to spot hidden patterns in scientific data. The machines can zero in on viruses that may be particularly likely to give rise to a human disease, for example, and can also predict which animals are most likely to harbor dangerous viruses we don’t yet know about.Barbara Han, a disease ecologist at the Cary Institute of Ecosystem Studies in Millbrook, N.Y., who collaborates with Dr. Carlson.Pamela Freeman/Cary Institute of Ecosystem Studies“It feels like you have a new set of eyes,” said Barbara Han, a disease ecologist at the Cary Institute of Ecosystem Studies in Millbrook, N.Y., who collaborates with Dr. Carlson. “You just can’t see in as many dimensions as the model can.”Dr. Han first came across machine learning in 2010. Computer scientists had been developing the technique for decades, and were starting to build powerful tools with it. These days, machine learning enables computers to spot fraudulent credit charges and recognize people’s faces.But few researchers had applied machine learning to diseases. Dr. Han wondered if she could use it to answer open questions, such as why less than 10 percent of rodent species harbor pathogens known to infect humans.She fed a computer information about various rodent species from an online database — everything from their age at weaning to their population density. The computer then looked for features of the rodents known to harbor high numbers of species-jumping pathogens.Once the computer created a model, she tested it against another group of rodent species, seeing how well it could guess which ones were laden with disease-causing agents. Eventually, the computer’s model reached an accuracy of 90 percent.Then Dr. Han turned to rodents that have yet to be examined for spillover pathogens and put together a list of high-priority species. Dr. Han and her colleagues predicted that species such as the montane vole and Northern grasshopper mouse of western North America would be particularly likely to carry worrisome pathogens.Of all the traits Dr. Han and her colleagues provided to their computer, the one that mattered most was the life span of the rodents. Species that die young turn out to carry more pathogens, perhaps because evolution put more of their resources into reproducing than in building a strong immune system.These results involved years of painstaking research in which Dr. Han and her colleagues combed through ecological databases and scientific studies looking for useful data. More recently, researchers have sped this work up by building databases expressly designed to teach computers about viruses and their hosts.The Northern grasshopper mouse, one of the species Dr. Han’s team predicted would carry a worrisome pathogen.Rick & Nora Bowers/Alamy In March, for example, Dr. Carlson and his colleagues unveiled an open-access database called VIRION, which has amassed half a million pieces of information about 9,521 viruses and their 3,692 animal hosts — and is still growing.Databases like VIRION are now making it possible to ask more focused questions about new pandemics. When the Covid pandemic struck, it soon became clear that it was caused by a new virus called SARS-CoV-2. Dr. Carlson, Dr. Han and their colleagues created programs to identify the animals most likely to harbor relatives of the new coronavirus.SARS-CoV-2 belongs to a group of species called betacoronaviruses, which also includes the viruses that caused the SARS and MERS epidemics among humans. For the most part, betacoronaviruses infect bats. When SARS-CoV-2 was discovered in January 2020, 79 species of bats were known to carry them.But scientists have not systematically searched all 1,447 species of bats for betacoronaviruses, and such a project would take many years to complete.By feeding biological data about the various types of bats — their diet, the length of their wings, and so on — into their computer, Dr. Carlson, Dr. Han and their colleagues created a model that could offer predictions about the bats most likely to harbor betacoronaviruses. They found over 300 species that fit the bill.Since that prediction in 2020, researchers have indeed found betacoronaviruses in 47 species of bats — all of which were on the prediction lists produced by some of the computer models they had created for their study.Daniel Becker, a disease ecologist at the University of Oklahoma who also worked on the betacoronavirus study, said it was striking the way simple features such as body size could lead to powerful predictions about viruses. “A lot of it is the low-hanging fruit of comparative biology,” he said.Dr. Becker is now following up from his own backyard on the list of potential betacoronavirus hosts. It turns out that some bats in Oklahoma are predicted to harbor them.If Dr. Becker does find a backyard betacoronavirus, he won’t be in a position to say immediately that it is an imminent threat to humans. Scientists would first have to carry out painstaking experiments to judge the risk.Pranav Pandit, an epidemiologist at the University of California at Davis cautions that these models are very much a work in progress. When tested on well-studied viruses, they do substantially better than random chance, but could do better.“It’s not at a stage where we can just take those results and create an alert to start telling the world, ‘This is a zoonotic virus,’ he said.”Nardus Mollentze, a computational virologist at the University of Glasgow, and his colleagues have pioneered a method that could markedly increase the accuracy of the models. Rather than looking at a virus’s hosts, their models look at its genes. A computer can be taught to recognize subtle features in the genes of viruses that can infect humans.In their first report on this technique, Dr. Mollentze and his colleagues developed a model that could correctly recognize human-infecting viruses more than 70 percent of the time. Dr. Mollentze can’t yet say why his gene-based model worked, but he has some ideas. Our cells can recognize foreign genes and send out an alarm to the immune system. Viruses that can infect our cells may have the ability to mimic our own DNA as a kind of viral camouflage.When they applied the model to animal viruses, they came up with a list of 272 species at high risk of spilling over. That’s too many for virologists to study in any depth.“You can only work on so many viruses,” said Emmie de Wit, a virologist at Rocky Mountain Laboratories in Hamilton, Mont., who oversees research on the new coronavirus, influenza and other viruses. “On our end, we would really need to narrow it down.”Dr. Mollentze acknowledged that he and his colleagues need to find a way to pinpoint the worst of the worst among animal viruses. “This is only a start,” he said.To follow up on his initial study, Dr. Mollentze is working with Dr. Carlson and his colleagues to merge data about the genes of viruses with data related to the biology and ecology of their hosts. The researchers are getting some promising results from this approach, including the tantalizing mousepox lead.Other kinds of data may make the predictions even better. One of the most important features of a virus, for example, is the coating of sugar molecules on its surface. Different viruses end up with different patterns of sugar molecules, and that arrangement can have a huge impact on their success. Some viruses can use this molecular frosting to hide from their host’s immune system. In other cases, the virus can use its sugar molecules to latch on to new cells, triggering a new infection.This month, Dr. Carlson and his colleagues posted a commentary online asserting that machine learning may gain a lot of insights from the sugar coating of viruses and their hosts. Scientists have already gathered a lot of that knowledge, but it has yet to be put into a form that computers can learn from.“My gut sense is that we know a lot more than we think,” Dr. Carlson said.Dr. de Wit said that machine learning models could some day guide virologists like herself to study certain animal viruses. “There’s definitely a great benefit that’s going to come from this,” she said.But she noted that the models so far have focused mainly on a pathogen’s potential for infecting human cells. Before causing a new human disease, a virus also has to spread from one person to another and cause serious symptoms along the way. She’s waiting for a new generation of machine learning models that can make those predictions, too.“What we really want to know is not necessarily which viruses can infect humans, but which viruses can cause an outbreak,” she said. “So that’s really the next step that we need to figure out.”

A BBC News investigation has exposed serious flaws in the Egyptian beauty industry that are endangering lives and leaving people scarred for life. In Egypt you have to be a dermatologist or plastic surgeon to inject Botox or dermal fillers. Even laser hair removal requires a qualified doctor’s supervision.But the BBC found dozens of unqualified people working in the beauty industry, in breach of Egyptian laws and regulations.Stating that they were overwhelmed by the fast pace of growth in the sector, the body responsible for registering doctors in Egypt, the Doctors’ Syndicate, told the BBC they need more power to take action. The Egyptian Health Ministry has not responded to the BBC’s request to comment.

But prior infection does not guarantee protection from the virus, officials said, and Americans should still get vaccinated and boosted.Sixty percent of Americans, including 75 percent of children, had been infected with the coronavirus by February, federal health officials reported on Tuesday — another remarkable milestone in a pandemic that continues to confound expectations.The highly contagious Omicron variant was responsible for much of the toll. In December 2021, as the variant began spreading, only half as many people had antibodies indicating prior infection, according to new research from the Centers for Disease Control and Prevention.While the numbers came as a shock to many Americans, some scientists said they had expected the figures to be even higher, given the contagious variants that have marched through the nation over the past two years.There may be good news in the data, some experts said. A gain in population-wide immunity may offer at least a partial bulwark against future waves. And the trend may explain why the surge that is now roaring through China and many countries in Europe has been muted in the United States.A high percentage of previous infections may also mean that there are now fewer cases of life-threatening illness or death relative to infections. “We will see less and less severe disease, and more and more a shift toward clinically mild disease,” said Florian Krammer, an immunologist at the Icahn School of Medicine at Mount Sinai in New York.“It will be more and more difficult for the virus to do serious damage,” he added.Administration officials, too, believe that the data augur a new phase of the pandemic in which infections may be common at times but cause less harm.At a news briefing on Tuesday, Dr. Ashish Jha, the White House’s new Covid coordinator, said that stopping infections was “not even a policy goal. The goal of our policy should be: obviously, minimize infections whenever possible, but to make sure people don’t get seriously ill.”The average number of confirmed new cases a day in the United States — more than 49,000 as of Monday, according to a New York Times database — is comparable to levels last seen in late July, even as cases have risen by over 50 percent over the past two weeks, a trend infectious disease experts have attributed to new Omicron subvariants.Dr. Jha and other officials warned against complacency, and urged Americans to continue receiving vaccinations and booster shots, saying that antibodies from prior infections did not guarantee protection from the virus.During the Omicron surge, infections rose most sharply among children and adolescents, according to the new research. Prior infections increased least among adults aged 65 and older, who have the highest rates of vaccination and may be most likely to take precautions.“Evidence of previous Covid-19 infections substantially increased among every age group,” Dr. Kristie Clarke, the agency researcher who led the new study, said at a news briefing on Tuesday.Widespread infection raises a troubling prospect: a potential increase in cases of long Covid, a poorly understood constellation of lingering symptoms.Up to 30 percent of people infected with the coronavirus may have persistent symptoms, including worrisome changes to the brain and heart. Vaccination is thought to lower the odds of long Covid, although it is unclear by how much.“The long-term impacts on health care are not clear but certainly worth taking very seriously, as a fraction of people will be struggling for a long time with the consequences,” said Bill Hanage, an epidemiologist at the Harvard T.H. Chan School of Public Health.Even a very small percentage of infected or vaccinated people who develop Covid would translate to millions nationwide.While the focus is often on preventing the health care system from buckling under a surge, “we should also be concerned that our health care system will be overwhelmed by the ongoing health care needs of a population with long Covid,” said Zoë McLaren, a health policy expert at the University of Maryland, Baltimore County.A mass testing site at Dodger Stadium in Los Angeles. Millions of Americans with no immunity to the virus remain vulnerable to both the short- and long-term consequences of infection.David Mcnew/Getty ImagesThere are still tens of millions of Americans with no immunity to the virus, and they remain vulnerable to both the short- and long-term consequences of infection, said Dr. Tom Inglesby, director of the Center for Health Security at the Johns Hopkins Bloomberg School of Public Health.“Betting that you are in the 60 percent is a big gamble,” he said. “For anyone who’s not been vaccinated and boosted, I would take this new data as a direct message to get that done or expect that the virus is likely to catch up to you if it hasn’t already.”Although cases are once again on the upswing, particularly in the Northeast, the rise in hospitalizations has been minimal, and deaths are still dropping. According to the agency’s most recent criteria, more than 98 percent of Americans live in communities with a low or medium level of risk.Even among those who are hospitalized, “we’re seeing less oxygen use, less I.C.U. stays and we haven’t, fortunately, seen any increase in deaths associated with them,” said the C.D.C.’s director, Dr. Rochelle Walensky. “We are hopeful that positive trends will continue.”The country has recorded about a five-fold drop in P.C.R. testing for the virus since the Omicron peak, and so tracking new cases has become difficult. But the reported count is far less, about 70-fold lower, said Dr. Walensky, reflecting “a true and reliable drop in our overall cases.”New subvariants of Omicron, called BA.2 and BA.2.12.1, have supplanted the previous iteration, BA.1, which began circulating in the country in late November and sent cases soaring to record highs in a matter of weeks.“Of course, even more have been infected now, because BA.2 will have infected some who avoided it thus far,” Dr. Hanage said.By February, three of four children and adolescents in the country had already been infected with the virus, compared with one-third of older adults, according to the new study.That so many children are carrying antibodies may offer comfort to parents of those aged 5 and under, who do not qualify for vaccination, since many may have acquired at least some immunity through infection.But Dr. Clarke urged parents to immunize children who qualify as soon as regulators approve a vaccine for them, regardless of their prior infection. Among children who are hospitalized with the virus, up to 30 percent may need intensive care, she noted.Although many of those children also have other medical conditions, about 70 percent of cases of multisystem inflammatory disease, a rare consequence of Covid-19 infection, occur in otherwise healthy children.“As a pediatrician and a parent, I would absolutely endorse the children get vaccinated, even if they have been infected,” Dr. Clarke said.Some experts said they were concerned about long-term consequences, even in children who have mild symptoms.“Given the very high proportion of infection in kids and adults that happened earlier this year, I worry about the rise in long Covid cases as a result,” said Akiko Iwasaki, an immunologist at Yale University who is studying the condition.To measure of the percentage of the population infected with the virus, the study relied on the presence of antibodies produced in response to an infection.C.D.C. researchers began assessing antibody levels in people at 10 sites early in the pandemic, and have since expanded that effort to all 50 states, the District of Columbia and Puerto Rico. The investigators used a test sensitive enough to identify previously infected people for at least one to two years after exposure.The researchers analyzed blood samples collected from September 2021 to February 2022 for antibodies to the virus, and then parsed the data by age, sex and geographical location. The investigators looked specifically for a type of antibody produced after infection but not after vaccination.Between September and December 2021, the prevalence of antibodies in the samples steadily increased by one to two percentage points every four weeks. But it jumped sharply after December, increasing by nearly 25 points by February 2022.The percentage of samples with antibodies rose from about 45 percent among children aged 11 years and younger, and among adolescents aged 12 to 17 years, to about 75 percent in both age groups.By February 2022, roughly 64 percent of adults aged 18 to 49 years, about 50 percent of those aged 50 to 64 years and about 33 percent of older adults had been infected, according to the study.The C.D.C. may have underestimated of the number of Americans who have been infected, Dr. McLaren said.Despite the record high cases during the Omicron surge, the reported statistics may not have captured all infections, because some people have few to no symptoms, may not have opted for testing, or may have tested themselves at home.According to one upcoming C.D.C. study, there may be more than three infections for each reported case, Dr. Clarke said.Noah Weiland

Children with autism spectrum disorder tend to experience gastrointestinal issues, such as constipation and stomach pain, at a higher rate than their neurotypical peers. Some also experience other internalizing symptoms at the same time, including stress, anxiety, depression and social withdrawal. Until now, no studies have examined the causal relationship between gastrointestinal symptoms and internalizing symptoms.
A new study at the University of Missouri found a “bi-directional” relationship between gastrointestinal issues and internalized symptoms in children and adolescents with autism — meaning the symptoms seem to be impacting each other simultaneously. The findings could influence future precision medicine research aimed at developing personalized treatments to ease pain for individuals with autism experiencing gastrointestinal issues.
“Research has shown gastrointestinal issues are associated with an increased stress response as well as aggression and irritability in some children with autism,” said Brad Ferguson, an assistant research professor in the MU School of Health Professions, Thompson Center for Autism and Neurodevelopmental Disorders and Department of Radiology in the MU School of Medicine. “This likely happens because some kids with autism are unable to verbally communicate their gastrointestinal discomfort as well as how they feel in general, which can be extremely frustrating. The goal of our research is to find out what factors are associated with gastrointestinal problems in individuals with autism so we can design treatments to help these individuals feel better.”
In the study, Ferguson and his team analyzed health data from more than 620 patients with autism at the MU Thompson Center for Autism and Neurodevelopmental Disorders under the age of 18 who experience gastrointestinal issues. Then, the team examined the relationship between the gastrointestinal issues and internalized symptoms, such as stress, anxiety, depression, and social withdrawal. Ferguson explained the findings provide more evidence on the importance of the “gut-brain axis,” or connection between the brain and the digestive tract, in gastrointestinal disorders in individuals with autism.
“Stress signals from the brain can alter the release of neurotransmitters like serotonin and norepinephrine in the gut which control gastrointestinal motility, or the movement of stool through the intestines. Stress also impacts the balance of bacteria living in the gut, called the microbiota, which can alter gastrointestinal functioning,” Ferguson said. “The gut then sends signals back to the brain, and that can, in turn, lead to feelings of anxiety, depression and social withdrawal. The cycle then repeats, so novel treatments addressing signals from both the brain and the gut may provide the most benefit for some kids with gastrointestinal disorders and autism.”
Ferguson said an interdisciplinary team of specialists is needed to help solve this complex problem and develop treatments going forward.

An artificial intelligence (AI) tool developed by Cedars-Sinai investigators accurately predicted who would develop pancreatic cancer based on what their CT scan images looked like years prior to being diagnosed with the disease. The findings, which may help prevent death through early detection of one of the most challenging cancers to treat, are published in the journal Cancer Biomarkers.
“This AI tool was able to capture and quantify very subtle, early signs of pancreatic ductal adenocarcinoma in CT scans years before occurrence of the disease. These are signs that the human eye would never be able to discern,” said Debiao Li, PhD, director of the Biomedical Imaging Research Institute, professor of Biomedical Sciences and Imaging at Cedars-Sinai, and senior and corresponding author of the study. Li is also the Karl Storz Chair in Minimally Invasive Surgery in Honor of George Berci, MD.
Pancreatic ductal adenocarcinoma is not only the most common type of pancreatic cancer, but it’s also the most deadly. Less than 10% of people diagnosed with the disease live more than five years after being diagnosed or starting treatment. But recent studies have reported that finding the cancer early can increase survival rates by as much as 50%. There currently is no easy way to find pancreatic cancer early, however.
People with this type of cancer may experience symptoms such as general abdominal pain or unexplained weight loss, but these symptoms are often ignored or overlooked as signs of the cancer since they are common in many health conditions.
“There are no unique symptoms that can provide an early diagnosis forpancreatic ductal adenocarcinoma,” said Stephen J. Pandol, MD, director of Basic and Translational Pancreas Research and program director of the Gastroenterology Fellowship Program at Cedars-Sinai, and another author of the study. “This AI tool may eventually be used to detect early disease in people undergoing CT scans for abdominal pain or other issues.”
The investigators reviewed electronic medical records to identify people who were diagnosed with the cancer within the last 15 years and who underwent CT scans six months to three years prior to their diagnosis. These CT images were considered normal at the time they were taken. The team identified 36 patients who met these criteria, the majority of whom had CT scans done in the ER because of abdominal pain.
The AI tool was trained to analyze these pre-diagnostic CT images from people with pancreatic cancer and compare them with CT images from 36 people who didn’t develop the cancer. The investigators reported that the model was 86% accurate in identifying people who would eventually be found to have pancreatic cancer and those who would not develop the cancer.
The AI model picked up on variations on the surface of the pancreas between people with cancer and healthy controls. These textural differences could be the result of molecular changes that occur during the development of pancreatic cancer.
“Our hope is this tool could catch the cancer early enough to make it possible for more people to have their tumor completely removed through surgery,” said Touseef Ahmad Qureshi, PhD, a scientist at Cedars-Sinai and first author of the study.
The investigators are currently collecting data from thousands of patients at healthcare sites throughout the U.S. to continue to study the AI tool’s prediction capability.
Funding: The study was funded by the Board of Counselors of Cedars-Sinai Medical Center, the Cedars-Sinai Samuel Oschin Comprehensive Cancer Institute and the National Institutes of Health under award number R01 CA260955.
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China’s mountainous southwestern area is home to one of the country’s most ethnically diverse populations. In the most comprehensive genetic analysis of the native people there to date, researchers reveal that the ethnic groups’ peopling and migration history is more complex than previously concluded. The study appears April 26 in the journal Cell Reports.
The Tibetan-Yi corridor (TYC), named after two main ethnic groups in the region, on the eastern edge of Tibet Plateau in southwestern China is thought to have served as an important area for ethnic migration and diversification. The corridor’s corrugated landscape of deep river valleys and tall ridges formed natural passages and barriers for gene flow.
Scientists have previously analyzed how people in the region are genetically related to the Tibetans, who live mostly west of the region, and the Han, China’s main ethnic group. But prior studies had limited gene samples from the region, which inhabit over a dozen of different ethnic groups.
To gain a better understanding of ethnic groups in the TYC, Shengbin Li, the paper’s co-corresponding author at Xi’an Jiaotong University in central China, spent a decade collecting blood samples from more than 200 people from all 16 ethnic groups in the region.
“The steep mountains that contributed to the high levels of ethnic diversity in the area also made data collection extremely difficult,” says Li. “Most of the places were inaccessible by car, so we had to travel on horseback. And some groups were so isolated that we had to walk for hours to get there.”
The team selected individuals from each ethnic group with at least three generations of history living in a relatively fixed area. By comparing the genomes of different ethnic groups, and those of Han and Tibetan populations, the team found that all ethnic groups in the region are genetically similar, suggesting that they shared a common ancestor. But people living in the northern TYC are related more closely to Tibetan Highlanders living on the plateau, while southern TYC inhabitants have a closer genetic relationship with southeast Asians, such as Thai people and Cambodians.
Previous research suggests that the region’s earliest settlers came from the upper reaches of the Yellow River region in northern China during the Neolithic period, and the corridor was gradually populated as the settlers expanded southward. The new study, while not contradicting the previous conclusion, found that the migration pattern is more complex than a simple north-to-south movement. For example, new data suggest that the ancestors of some southern TYC populations might have originated from southeastern Asia.
“More studies are needed to further understand the origin and flow of the region’s population, especially a more comprehensive analysis that incorporates not only genetic but also archaeological, cultural, linguistic and geographical evidence,” says Shuaicheng Li, the study’s co-corresponding author at City University of Hong Kong.
Next, the team hopes to study the gut microbiota of the TYC people. “The region has no air pollution, and locals don’t eat processed food with chemicals. Their microbiota has the potential to reveal more connections between gut and health,” Shuaicheng Li says.
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Materials provided by Cell Press. Note: Content may be edited for style and length.

The COVID-19 pandemic and its public response created large shifts in how people travel. In some areas, these restrictions on travel appear to have had little effect on air pollution, and some cities have worse air quality than ever.
In Chaos, by AIP Publishing, researchers in China created a network model drawn from the traffic index and air quality index of 21 cities across six regions in their country to quantify how traffic emissions from one city affect another. They wanted to leverage data from COVID-19 lockdown procedures to better explain the relationship between traffic and air pollution and saw the COVID-19 lockdowns as a rare opportunity for research.
“Air pollution is a typical ‘commons governance’ issue,” said author Jingfang Fan. “The impact of the pandemic has led cities to implement different traffic restriction policies, one after another, which naturally forms a controlled experiment to reveal their relationship.”
To address these questions, they turned to a weighted climate network framework to model each city as a node using pre-pandemic data from 2019 and data from 2020. They added a two-layer network that incorporated different regions, lockdown stages, and outbreak levels.
Surrounding traffic conditions influenced air quality in Beijing-Tianjin-Hebei, the Chengdu-Chongqing Economic Circle, and central China after the outbreak. Pollution tended to peak in cities as they made initial progress for containing the virus.
During this time, pollution in Beijing-Tianjin-Hebei and central China lessened over time. Beijing-Tianjin-Hebei, however, saw another spike as control measures for outbound traffic from Wuhan and Hubei were lifted.
“Air pollution in big cities, such as Beijing and Shanghai, is more affected by other cities,” said author Saini Yang. “This is contrary to what we generally think, that air pollution in big cities is mainly caused by its own conditions, including the traffic congestion.”
Author Weiping Wang hopes the team’s work inspires other interdisciplinary teams to explore unique ways to explore problems in environmental science. They will look to improve their model with a higher degree of detail for traffic emissions.
“Our discovery is that in order to improve air pollution, it is not only necessary to improve and reduce our own urban traffic and increase green travel, but also need the joint efforts of surrounding cities,” said author Na Ying. “Everyone is important in the governance of commons.”
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Materials provided by American Institute of Physics. Note: Content may be edited for style and length.