Culture

Researchers at Karolinska Institutet in Sweden found industrial chemicals in the organs of fetuses conceived decades after many countries had banned the substances. In a study published in the journal Chemosphere, the researchers urge decision makers to consider the combined impact of the mix of chemicals that accumulate in people and nature.

"These are important findings that call for regulators to consider the collective impact of exposure to multiple chemicals rather than evaluating just one chemical at a time," says first author Richelle Duque Björvang, PhD student at the Department of Clinical Science, Intervention and Technology at Karolinska Institutet.

The researchers studied concentrations of 22 persistent organic pollutants (POPs). These are toxic chemicals that remain in the environment for long periods of time and accumulate in humans through food, drinking water and air particles. EU's members and many other countries have signed a treaty that prohibits or restricts manufacturing and use of these chemicals.

In the study, the researchers examined samples of fetal fat tissue, liver, heart, lung and brain from 20 pregnancies that for various reasons had ended in stillbirth in the third trimester in 2015-2016. The researchers identified at least 15 of the 22 POPs in every organ. Four chemicals were found in all tissues in all fetuses. The most pervasive chemicals were:

HCB, a pesticide previously used to protect food crops from fungi;

DDE, a metabolite of DDT, an insect killer used in the mid-1900s;

Variants of PCBs, chemicals formerly used in a range of electrical products.

Most current methods for estimating fetal exposure to chemicals rely on maternal blood and placenta samples as proxies. The new study found that, for some of the chemicals, the concentrations in the fetal tissues exceeded those found in the maternal blood and placenta. This can be explained by the fact that these chemicals tend to accumulate in fat tissue due to their structure. However, levels in fetal liver and lung also exceeded those found in the mother. Some pesticides - PeCB, α-HCH, γ-HCH and oxychlordane - were detected in fetal tissue even when they were not quantified in maternal blood samples or the placenta. According to the researchers, these latest findings suggest that blood and placenta samples may give a misleading picture on the diversity and concentration of chemicals that babies are exposed to during early development.

This study only investigated the presence and concentration of the various chemicals but not their links to potential health risks. However, the researchers point out that several previous studies have linked early life exposure to POPs to adverse health outcomes such as low birth weight, gestational diabetes, ADHD, infertility, obesity and reduced sperm production. For example, the European Food Safety Authority (EFSA) recently revised their risk assessment of dioxins and dioxin-like PCBs, and concluded that the dietary intake in Europe is currently at a level that can disrupt fertility in men.

"Getting an accurate picture of chemical exposure in early human development is critical to assessing both short and long-term health consequences for future generations," says last author Pauliina Damdimopoulou, researcher in the Department of Clinical Science, Intervention and Technology at Karolinska Institutet. "Therefore, we believe today's approaches estimating fetal chemical exposure, for example in birth cohort studies, need to be updated to better reflect the likelihood that for some chemicals, fetal exposure is actually greater than what the blood and placenta samples show."

Thirteen of the pregnancies also had data from an earlier study on PFAS (chemicals used in frying pans, food packaging and firefighting foam). By combining these data, the researchers were able to assess the proportion of chemicals in each type of tissue. While pesticides and PCBs were significantly overrepresented in fat tissue, more than half of the chemicals in the fetal lung, brain, liver and heart was due to PFAS. Overall, the highest concentration of a mix of chemicals were found in fat tissue and the lowest in the brain. The study found that the relative exposure of baby boys was higher compared to baby girls.

"Studies conducted in the 1960s and 1970s, when POPs were widely in use, found higher levels compared to ours," Richelle Duque Björvang says. "This shows that political action leading to restrictions in the use of chemicals has an impact on population exposures, although in the case of persistent chemicals it will take multiple generations to get rid of the exposure."

The researchers recognize that the study has some limitations, including a relatively modest sample size and that it only included fetuses who had died in the womb late in the pregnancy. Thus, it may not be fully representative of babies born alive.

As consumers and corporations alike become more environmentally conscious, the chemical industry is working to find solutions to the plastic waste crisis. One idea is to use biodegradable polymers known as polyhydroxyalkanoates (PHA) as replacements for traditional plastic packaging and other materials. A feature article in Chemical & Engineering News, the weekly newsmagazine of the American Chemical Society, explores the possibilities and pitfalls of PHA.

PHA is not a new human invention; this class of polymers can be found in nature and is used to store cellular energy, writes Senior Editor Alex Tullo. Commercially, it is manufactured through the industrial fermentation of sugars or lipids. As cities around the world ban single-use plastic products, such as straws and bags, companies are working to commercialize PHA as a viable alternative. The main selling point is rapid biodegradability in a variety of environments. Demand has increased for PHA in recent years, with several companies opening or planning commercial plants in the U.S. and beyond. In addition, major food and beverage brands are planning to switch their packaging to PHA-based materials soon.

Despite its much-touted promise, there's reason to believe PHA might be too good to be true. Several companies have tried and failed to bring it to market in recent years, and PHA is much more expensive than its traditional plastic counterparts. Beyond that, some experts have published findings saying the biodegradability of PHA is overstated, and that the rapid degradation time is based on optimized laboratory conditions rather than real-world ones. However, PHA's boosters say that it's still a better alternative to non-biodegradable plastics, and that the industry may be on the cusp of a breakthrough.

Reston, VA--The effects of COVID-19 on the brain can be accurately measured with positron emission tomography (PET), according to research presented at the Society of Nuclear Medicine and Molecular Imaging (SNMMI) 2021 Annual Meeting. In the study, newly diagnosed COVID-19 patients, who required inpatient treatment and underwent PET brain scans, were found to have deficits in neuronal function and accompanying cognitive impairment, and in some, this impairment continued six months after their diagnosis. The detailed depiction of areas of cognitive impairment, neurological symptoms and comparison of impairment over a six-month time frame has been selected as SNMMI's 2021 Image of the Year.

Each year, SNMMI chooses an image that best exemplifies the most promising advances in the field of nuclear medicine and molecular imaging. The state-of-the-art technologies captured in these images demonstrate the capacity to improve patient care by detecting disease, aiding diagnosis, improving clinical confidence, and providing a means of selecting appropriate treatments. This year, the SNMMI Henry N. Wagner, Jr., Image of the Year was chosen from more than 1,280 abstracts submitted to the meeting and voted on by reviewers and the society leadership.

"As the SARS-CoV-2 pandemic proceeds, it has become increasingly clear that neurocognitive long-term consequences occur not only in severe COVID-19 cases, but in mild and moderate cases as well. Neurocognitive deficits like impaired memory, disturbed concentration and cognitive problems may persist well beyond the acute phase of the disease," said Ganna Blazhenets, PhD, a post-doctoral researcher in Medical Imaging at the University Medical Center Freiburg, in Freiburg, Germany.

To study cognitive impairment associated with COVID-19, researchers carried out a prospective study on recently diagnosed COVID-19 patients who required inpatient treatment for non-neurological complaints. A cognitive assessment was performed, followed by imaging with 18F-FDG PET if at least two new neurological symptoms were present. By comparing COVID-19 patients to controls, the Freiburg group established a COVID-19-related covariance pattern of brain metabolism with most prominent decreases in cortical regions. Across patients, the expression of this pattern showed a very high correlation with the patients' cognitive performance.

Follow-up PET imaging was performed six months after the initial COVID-19 diagnosis. Imaging results showed a significant improvement in the neurocognitive deficits in most patients, accompanied by an almost complete normalization of the brain metabolism.

"We can clearly state that a significant recovery of regional neuronal function and cognition occurs for most COVID-19 patients based on the results of this study. However, it is important to recognize the evidence of longer-lasting deficits in neuronal function and accompanying cognitive deficits is still measurable in some patients six months after manifestation of disease," noted Blazhenets. "As a result, post-COVID-19 patients with persistent cognitive complaints should be presented to a neurologist and possibly allocated to cognitive rehabilitation programs."

"18F-FDG PET is an established biomarker of neuronal function and neuronal injury," stated SNMMI's Scientific Program Committee chair, Umar Mahmood, MD, PhD. "As shown the Image of the Year, it can be applied to unravel neuronal correlates of the cognitive decline in patients after COVID-19. Since 18F-FDG PET is widely available, it may therefore aid in the diagnostic work-up and follow-up in patients with persistent cognitive impairment after COVID-19."

CHAMPAIGN, Ill. -- Health care workers often don't adopt new guidelines for best practices in medical care until well after those guidelines are established. A team of researchers led by Eunice E. Santos, the dean of the School of Information Sciences at the University of Illinois Urbana-Champaign, has developed a new computational modeling and simulation framework to analyze decision-making and identify effective dissemination strategies for medical guidelines.

The research team examined guidelines for Type 2 diabetes that were established in 2012 and were still not adopted years later. The researchers found that health care workers' specialties, patient volume and experience were among the factors that affected acceptance of individualized glycemic-control guidelines.

The team developed a novel computational framework that incorporates the interactions and influences among health care workers, along with other intricacies of medical decision-making, to simulate and analyze a wide range of real-world scenarios. Researchers introduced the Culturally Infused Agent Based Model (CI-ABM) and reported their findings in the cover article for the June issue of the IEEE Journal of Biomedical and Health Informatics.

Their research highlights that modeling and simulating human behaviors must take into account factors such as sociocultural context and complex social interactions, without which the models can lead to a profound misunderstanding of human decision-making, they said.

"One of the major challenges is capturing the decision-making of the actors and the factors that influence them. This is especially true when the agents are human beings (e.g., health care workers), where their behavior is uncertain and the information about the factors that influence their decision-making is often incomplete and/or contradictory," they wrote.

The modeling system they developed incorporates social networks and cultural influences that guide decision-making, and it captures how beliefs evolve over time due to personal and external factors. It provides that ability to model real-world events that involve incomplete, imprecise and conflicting information, and it provides a way to handle uncertainty in human behavior. These aspects of their computational model led to better analysis and prediction of guideline-dissemination behaviors, the researchers said.

Santos and her colleagues used the model to analyze the dissemination of a Type 2 diabetes guideline that recommends individualizing glycemic goals for patients. Diabetes care guidelines since 2012 have emphasized individualizing glycemic goals based on patient factors such as age, hypoglycemia risk and overall health. But it isn't known how many doctors have adopted this guideline.

The researchers used two 2015 surveys that focused on challenges faced by doctors in individualizing the glycemic goals of their patients. The surveys included doctors from diverse backgrounds and a range of specialties - including endocrinology, family medicine and geriatrics - experience levels and practice types.

In their simulation, some of the doctors received guideline recommendations from the American Diabetes Association. Best practices also spread through word-of-mouth. The team compared the results of the simulations with the answers given on the surveys. The researchers found that including sociocultural factors and information about social interactions of health care workers in their model increased the accuracy of predicting guideline-adoption behaviors of various demographic groups. In addition, by including sociocultural information, the model helps to identify factors that drive guideline-adoption behavior.

The framework also allows policymakers to study the effect of different barriers to disseminating medical guideline information, identify the factors contributing to guideline adoption and create targeted strategies to improve communication about the guidelines, they said.

The modeling system will help policymakers test different strategies and analyze their effects, the researchers said. It provides a way to capture the effect of unique factors - for example, when modeling guideline dissemination for infectious diseases, it can help analyze the effects of incorporating information about the novelty and mortality of infectious diseases, as well as the impact of changes in social networks due to lockdowns.

The team of researchers included Suresh Subramanian and Vairavan Murugappan, both doctoral students in Illinois' School of Information Sciences; John Korah, a computer science professor at California State Polytechnic University; Elbert S. Huang and Neda Laiteerapong, both professors of medicine at The University of Chicago Medicine; and Ali Cinar, a chemical and biological engineering professor at the Illinois Institute of Technology.

An algorithm can predict when narwhals hunt - a task once nearly impossible to gain insight into. Mathematicians and computer scientists at the University of Copenhagen, together with marine biologists in Greenland, have made progress in gathering knowledge about this enigmatic Arctic whale at a time when climate change is pressuring them.

The small whale, known for its distinctively spiraled tusk, is under mounting pressure due to warming waters and the subsequent increase in Arctic shipping traffic. To better care for narwhals, we need to learn more about their foraging behaviour - and how these may change as a result of human disturbances and global warming. Biologists know almost nothing about this. Because narwhals live in isolated Arctic regions and hunt at depths of up to 1,000 meters, it is very difficult - sometimes impossible - to gain any insight whatsoever.

Ironically, artificial intelligence may be the answer to the mystery of their natural behaviours. An interdisciplinary collaboration between mathematicians, computer scientists and marine biologists from the University of Copenhagen and the Greenland Institute of Natural Resources demonstrates that algorithms can be used to map the foraging behavior of this enigmatic whale.

"We have shown that our algorithm can actually predict that when narwhals emit certain sounds, they are hunting prey. This opens up entirely new insights into the life of narwhals," explains Susanne Ditlevsen, a professor at UCPH's Department of Mathematical Sciences who has helped marine biologists in Greenland with the processing of data for several years.

"It is crucial to gain more insight into where and when narwhals hunt for food as sea ice recedes. If they are disturbed by shipping traffic, it matters whether this is in the middle of an important foraging area. Finding out however, is incredibly difficult. Here, artificial intelligence seems to be able to make a huge difference and to a great extent, provide us with knowledge that could not otherwise have been obtained," says cetacean researcher Mads Peter Heide-Jørgensen, a professor at the Greenland Institute of Natural Resources and adjunct professor at the University of Copenhagen. He adds:

"In a situation where narwhals are in deep water, in the middle of the Bay of Baffin during December, we currently have no way of finding out where or when they are foraging. Here, artificial intelligence seems to be the way forward."

Algorithm maps clicks and buzzes

Until now, the best way to learn about the hunting patterns of narwhals has been to collect acoustic data using measuring instruments attached to their bodies. Like bats, narwhals orient themselves using echolocation. By making clicking sounds, they explore their environment and orient themselves. As they begin to hunt, these clicks shorten in interval to become buzzing.

While the buzzing sounds are therefore interesting to researchers, it is impossible to collect acoustic data in many places. Furthermore, recording these sounds is highly data-intensive and time consuming to analyze manually.

As a result, the researchers set out to investigate whether, by using artificial intelligence, they could find a pattern in the way whales move and the buzzes they emit. In the future, this would make it possible for them to rely only on measurements of animal movements using an accelerometer, a simple to use technology familiar to us from our smartphones.

"The major challenge was that these whales have very complex movement patterns, which can be tough to analyze. This becomes possible only with the use of deep learning, which could learn to recognize both the various swimming patterns of whales as well as their buzzing sounds. The algorithm then discovered connections between the two," explains Assistant Professor Raghavendra Selvan of the Department of Computer Science.

The researchers trained the algorithm using large quantities of data collected from five narwhals in Scoresby Sound fjord in East Greenland.

Now, the researchers hope to add to the algorithm by characterizing different types of buzzing sounds in order to identify the precise buzzing sounds that lead to a catch. This can be achieved by collecting data in which biologists give whales a temperature pill that detects temperature drops in their stomachs as they consume cold fish or squid.

DURHAM, N.C. - Special diets, exercise programs, supplements and vitamins -- everywhere we look there is something supposed to help us live longer. Maybe those work: human average life expectancy has gone from a meager 40-ish years to a whopping 70-something since 1850. Does this mean we are slowing down death?

A new study comparing data from nine human populations and 30 populations of non-human primates says that we are probably not cheating the reaper. The researchers say the increase in human life expectancy is more likely the statistical outcome of improved survival for children and young adults, not slowing the aging clock.

"Populations get older mostly because more individuals get through those early stages of life," said Susan Alberts, professor of Biology and Evolutionary Anthropology at Duke University and senior author of the paper. "Early life used to be so risky for humans, whereas now we prevent most early deaths."

The research team, comprising scientists from 14 different countries, analyzed patterns of births and deaths in the 39 populations, looking at the relationship between life expectancy and lifespan equality.

Lifespan equality tell us how much the age of death varies in a population. If everyone tends to die at around the same age -- for instance, if almost everyone can expect to live a long life and die in their 70s or 80s -- lifespan equality is very high. If death could happen at any age -- because of disease, for example -- lifespan equality is very low.

In humans, lifespan equality is closely related to life expectancy: people from populations that live longer also tend to die at a similarly old age, while populations with shorter life-expectancies tend to die at a wider range of ages.

To understand if this pattern is uniquely human, the researchers turned to our closest cousins: non-human primates. What they found is that the tight relationship between life expectancy and lifespan equality is widespread among primates as well as humans. But why?

In most mammals, risk of death is high at very young ages and relatively low at adulthood, then it increases again after the onset of aging. Could higher life-expectancy be due to individuals ageing slower and living longer?

The primate populations tell us that the answer is probably no. The main sources of variation in the average age of death in different primate populations were infant, juvenile and young adult deaths. In other words, life expectancy and lifespan equality are not driven by the rate at which individuals senesce and become old, but by how many kids and young adults die for reasons unrelated to old age.

Using mathematical modeling, the researchers also found that small changes in the rate of ageing would drastically alter the relationship between life expectancy and lifespan equality. Changes in the parameters representing early deaths, on the other hand, led to variations very similar to what was observed.

"When we change the parameters representing early deaths, we can explain almost all of the variation among populations, for all of these species," said Alberts. "Changes in the onset of aging and rate of ageing do not explain this variation."

These results support the 'invariant rate of ageing' hypothesis.

"The rate of ageing is relatively fixed for a species," said Alberts. "That's why the relationship between life expectancy and lifespan equality is so tight within each species."

The researchers point out that there is some individual variation within species in the rate of ageing and on the onset of senescence, but that this variation is contained to a fairly narrow range, unlike death rates at younger ages.

"We can't slow down the rate at which we're going to age," Alberts said. "What we can do is prevent those babies from dying."

This work was supported by a grant from the National Institute on Aging (P01AG031719), with additional support provided by the Max Planck Institute of Demographic Research and the Duke University Population Research Institute.

Osteoporosis researchers at the UVA School of Medicine have taken a new approach to understanding how our genes determine the strength of our bones, allowing them to identify several genes not previously known to influence bone density and, ultimately, our risk of fracture.

The work offers important insights into osteoporosis, a condition that affects 10 million Americans, and it provides scientists potential new targets in their battle against the brittle-bone disease.

Importantly, the approach uses a newly created population of laboratory mice that allows researchers to identify relevant genes and overcome limitations of human studies. Identifying such genes has been very difficult but is key to using genetic discoveries to improve bone health.

"Genome-wide association studies have revolutionized the identification of regions of the human genome that influence bone mineral density. However, there are challenges to using this information to help patients, such as identifying the specific genes involved. Additionally, such studies have focused only on bone mineral density, although many other aspects of bone contribute to bone strength and risk of fracture but cannot be measured in humans," said Charles Farber, PhD, of UVA's Center for Public Health Genomics and Department of Public Health Sciences. "The ability to use mice in a novel way has allowed us to begin to overcome the challenges associated with human genome-wide association studies."

UNDERSTANDING OSTEOPOROSIS AND BONE STRENGTH

Genome-wide association studies have identified more than 1,000 locations on our chromosomes where genes are found that influence bone mineral density (BMD), a strong predictor of how likely an individual is to experience a bone fracture. But bone mineral density is only one factor in bone strength. Farber and his colleagues wanted to get a more complete picture.

They created a resource by collecting information on 55 different skeletal characteristics in hundreds of mice and then used an approach called systems genetics to analyze the data. The analysis identified a total of 66 genes that contribute to BMD, including 19 not previously linked to BMD.

Of the 19, the researchers were able to determine that two, SERTAD4 and GLT8D2, likely affect bone mineral density through cells that form bone called osteoblasts. This ability to determine the cell types that genes use to perform biological processes is one of the great strengths of systems genetics analysis, the researchers say.

The scientists also found that another gene, QSOX1, plays an important role in determining the mass and strength of the outer, "cortical" layer of bone. This type of bone makes up 80% of our skeleton and is vital for bone strength and weight bearing.

In addition to providing new insights into osteoporosis, the new findings highlight the tremendous potential of using mice to identify important genes in humans, Farber says.

"The information we generated from mice can be used in the future to evaluate these newly identified genes as potential drug targets," said Basel Al-Barghouthi, of UVA's Center for Public Health Genomics, who led the analysis. "Furthermore, these approaches can be applied across a wide range of diseases."

Woods Hole, MA (June 16, 2021) -- Woods Hole Oceanographic Institution (WHOI) climate modeler Dr. Alan Condron and United States Geological Survey (USGS) research geologist Dr. Jenna Hill have found evidence that massive icebergs from roughly 31,000 years ago drifted more than 5000km (> 3,000 miles) along the eastern United States coast from Northeast Canada all the way to southern Florida. These findings were published today in Nature Communications.

Using high resolution seafloor mapping, radiocarbon dating and a new iceberg model, the team analyzed about 700 iceberg scours ("plow marks" on the seafloor left behind by the bottom parts of icebergs dragging through marine sediment ) from Cape Hatteras, North Carolina to the Florida Keys. The discovery of icebergs in this area opens a door to understanding the interactions between icebergs/glaciers and climate.

"The idea that icebergs can make it to Florida is amazing," said Condron. "The appearance of scours at such low latitudes is highly unexpected not only because of the exceptionally high melt rates in this region, but also because the scours lie beneath the northward flowing Gulf Stream."

"We recovered the marine sediment cores from several of these scours, and their ages align with a known period of massive iceberg discharge known as Heinrich Event 3. We also expect that there are younger and older scours features that stem from other discharge events, given that there are hundreds of scours yet to be sampled," added Hill.

To study how icebergs reached the scour sites, Condron developed a numerical iceberg model that simulates how icebergs drift and melt in the ocean. The model shows that icebergs can only reach the scour sites when massive amounts of glacial meltwater (or glacial outburst floods) are released from Hudson Bay. "These floods create a cold, fast flowing, southward coastal current that carries the icebergs all the way to Florida," says Condron. "The model also produces 'scouring' on the seafloor in the same places as the actual scours"

The ocean water temperatures south of Cape Hatteras are about 20-25°C (68-77°F). According to Condron and Hill, for icebergs to reach the subtropical scour locations in this region, they must have drifted against the normal northward direction of flow -- the opposite direction to the Gulf Stream. This indicates that the transport of icebergs to the south occurs during large-scale, but brief periods of meltwater discharge.

"What our model suggests is that these icebergs get caught up in the currents created by glacial meltwater, and basically surf their way along the coast. When a large glacial lake dam breaks, and releases huge amounts of fresh water into the ocean, there's enough water to create these strong coastal currents that basically move the icebergs in the opposite direction to the Gulf Stream, which is no easy task" Condron said.

While this freshwater is eventually transferred northward by the Gulf Stream, mixing with the surrounding ocean would have caused the meltwater to be considerably saltier by the time it reached the most northern parts of the North Atlantic. Those areas are considered critical for controlling how much heat the ocean transports northward to Europe. If these regions become abundant with fresh water, then the amount of heat transported north by the ocean could significantly weaken, increasing the chance that Europe could get much colder.

The routing of meltwater into the subtropics - a location very far south of these regions - implies that the influence of meltwater on global climate is more complex than previously thought, according to Condron and Hill. Understanding the timing and circulation of meltwater and icebergs through the global oceans during glacial periods is crucial for deciphering how past changes in high-latitude freshwater forcing influenced shifts in climate.

"As we are able to make more detailed computer models, we can actually get more accurate features of how the ocean actually circulates, how the currents move, how they peel off, and how they spin around. That actually makes a big difference in terms of how that freshwater is circulated and how it can actually impact climate," Hill added.

Key Takeaways:

The discovery of icebergs in this area opens a door to understanding the interactions between icebergs/glaciers and climate.

Evidence suggests that there may be hundreds of undiscovered scours that range in ages

A newly developed iceberg computer model helped the researchers understand the timing and circulation of meltwater and icebergs through the global oceans during glacial periods, which is crucial for deciphering how past changes in high-latitude freshwater forcing influenced shifts in climate.

Scientists at Weill Cornell Medicine have developed a computational technique that greatly increases the resolution of atomic force microscopy, a specialized type of microscope that "feels" the atoms at a surface. The method reveals atomic-level details on proteins and other biological structures under normal physiological conditions, opening a new window on cell biology, virology and other microscopic processes.

In a study, published June 16 in Nature, the investigators describe the new technique, which is based on a strategy used to improve resolution in light microscopy.

To study proteins and other biomolecules at high resolution, investigators have long relied on two techniques: X-ray crystallography and cryo-electron microscopy. While both methods can determine molecular structures down to the resolution of individual atoms, they do so on molecules that are either scaffolded into crystals or frozen at ultra-cold temperatures, possibly altering them from their normal physiological shapes. Atomic force microscopy (AFM) can analyze biological molecules under normal physiological conditions, but the resulting images have been blurry and low resolution.

"Atomic force microscopy can easily resolve atoms in physics, on solid surfaces of silicates and on semiconductors, so it means that in principle the machine has the precision to do that," said senior author Dr. Simon Scheuring, professor of physiology and biophysics in anesthesiology at Weill Cornell Medicine. "The technique is a bit like if you were to take a pen and scan over the Rocky Mountains, so that you get a topographic map of the object. In reality, our pen is a needle that is sharp down to a few atoms and the objects are single protein molecules."

However, biological molecules have many small parts that wiggle, blurring their AFM images. To address that problem, Dr. Scheuring and his colleagues adapted a concept from light microscopy called super-resolution microscopy. "Theoretically it wasn't possible by optical microscopy to resolve two fluorescent molecules that were closer together than half the wavelength of the light," he said. However, by stimulating the adjacent molecules to fluoresce at different times, microscopists can analyze the spread of each molecule and pinpoint their locations with high precision.

Instead of stimulating fluorescence, Dr. Scheuring's team noted that the natural fluctuations of biological molecules recorded over the course of AFM scans yield similar spreads of positional data. First author Dr. George Heath, who was a postdoctoral associate at Weill Cornell Medicine at the time of the study and is now a faculty member at the University of Leeds, engaged in cycles of experiments and computational simulations to understand the AFM imaging process in greater detail and extract the maximum of information from the atomic interactions between tip and sample.

Using a method like super-resolution analysis, they were able to extract much higher resolution images of the moving molecules. Continuing the topographic analogy, Dr. Scheuring explained that "if the rocks (i.e., atoms) wiggle a little bit up and down, you can detect this one, then that one, and then you average all detections over time and you receive high-resolution information."

Because previous AFM studies have routinely collected the necessary data, the new technique can be applied retroactively to the blurry images the field has generated for decades. As an example, the new paper includes an analysis of an AFM scan of an aquaporin membrane protein, originally acquired during Dr. Scheuring's doctoral thesis. The reanalysis generated a much sharper image that matches X-ray crystallography structures of the molecule closely. "You basically get quasi-atomic resolution on these surfaces now," said Dr. Scheuring. To showcase the power of the method, the authors provide new high-resolution data on annexin, a protein involved in cell membrane repair, and on a proton-chloride antiporter of which they also report structural changes related to its functional.

Besides allowing researchers to study biological molecules under physiologically relevant conditions, the new method has other advantages. For example, X-ray crystallography and cryo-electron microscopy rely on averaging data from large numbers of molecules, but AFM can generate images of single molecules. "Instead of having observations of hundreds of molecules, we observe one molecule a hundred times and calculate a high-resolution map," said Dr. Scheuring.

Imaging individual molecules as they carry out their functions could open entirely new types of analysis. "Let's say you have a [viral] spike protein that's in one conformation and then it gets activated and goes into another conformation," said Dr. Scheuring. "You would in principle be able to calculate a high-resolution map from that same molecule as it transits from one conformation to the next, not from thousands of molecules in one or the other conformation." Such high-resolution single molecule data could provide more detailed information and avoid the potentially misleading results that can occur when averaging data from many molecules. Furthermore, the map might reveal new strategies for precisely redirecting or interrupting such processes.

While crop yield has achieved a substantial boost from nanotechnology in recent years, alarms over the health risks posed by nanoparticles within fresh produce and grains have also increased. In particular, nanoparticles entering the soil through irrigation, fertilizers and other sources have raised concerns about whether plants absorb these minute particles enough to cause toxicity.

In a new study published online in the journal Environmental Science and Technology, researchers at Texas A&M University have used machine learning to evaluate the salient properties of metallic nanoparticles that make them more susceptible for plant uptake. The researchers said their algorithm could indicate how much plants accumulate nanoparticles in their roots and shoots.

Nanoparticles are a burgeoning trend in several fields, including medicine, consumer products and agriculture. Depending on the type of nanoparticle, some have favorable surface properties, charge and magnetism, among other features. These qualities make them ideal for a number of applications. For example, in agriculture, nanoparticles may be used as antimicrobials to protect plants from pathogens. Alternatively, they can be used to bind to fertilizers or insecticides and then programmed for slow release to increase plant absorption.

These agricultural practices and others, like irrigation, can cause nanoparticles to accumulate in the soil. However, with the different types of nanoparticles that could exist in the ground and a staggeringly large number of terrestrial plant species, including food crops, it is not clearly known if certain properties of nanoparticles make them more likely to be absorbed by some plant species than others.

"As you can imagine, if we have to test the presence of each nanoparticle for every plant species, it is a huge number of experiments, which is very time-consuming and expensive," said Xingmao "Samuel" Ma, associate professor in the Zachry Department of Civil and Environmental Engineering. "To give you an idea, silver nanoparticles alone can have hundreds of different sizes, shapes and surface coatings, and so, experimentally testing each one, even for a single plant species, is impractical."

Instead, for their study, the researchers chose two different machine learning algorithms, an artificial neural network and gene-expression programming. They first trained these algorithms on a database created from past research on different metallic nanoparticles and the specific plants in which they accumulated. In particular, their database contained the size, shape and other characteristics of different nanoparticles, along with information on how much of these particles were absorbed from soil or nutrient-enriched water into the plant body.

Once trained, their machine learning algorithms could correctly predict the likelihood of a given metallic nanoparticle to accumulate in a plant species. Also, their algorithms revealed that when plants are in a nutrient-enriched or hydroponic solution, the chemical makeup of the metallic nanoparticle determines the propensity of accumulation in the roots and shoots. But if plants are grown in soil, the contents of organic matter and the clay in soil are key to nanoparticle uptake.

Ma said that while the machine learning algorithms could make predictions for most food crops and terrestrial plants, they might not yet be ready for aquatic plants. He also noted that the next step in his research would be to investigate if the machine learning algorithms could predict nanoparticle uptake from leaves rather than through the roots.

"It is quite understandable that people are concerned about the presence of nanoparticles in their fruits, vegetables and grains," said Ma. "But instead of not using nanotechnology altogether, we would like farmers to reap the many benefits provided by this technology but avoid the potential food safety concerns."

Although each organism has a unique genome, a single gene sequence, each individual has many epigenomes. An epigenome consists of chemical compounds and proteins that can bind to DNA and regulate gene action, either by activating or deactivating them or producing organ- or tissue-specific proteins. As it is a highly dynamic material, it can provide a large amount of information to shed light on the evolution of the various tissues and organs that make up the body.

Now, a team from the Institute of Evolutionary Biology (IBE), a joint centre of the Spanish National Research Council (CSIC) and Pompeu Fabra University, has carried out the largest study to date on the regulatory elements in the genome of primates. The exhaustive analysis conducted by the research team led by Tomas Marquès-Bonet, principal investigator of the Comparative Genomics research group at the IBE, has analysed a wide spectrum of signals regulating genes in the great apes and in humans, including weak activity signals that have been overlooked in previous studies. The study, co-led by the researcher David Juan of the IBE, has revealed that in humans, the weakest regulatory signals, that are not usually studied, play an important role in the regulation of genes linked to brain. The research opens the door to deciphering the impact that these signals may have on the evolution of humans and other primates.

The research lab has carried out the largest study to date on the regulatory elements in the genome of primates.

The research team used high resolution to analyse epigenomic signals in cell lines of great apes and humans. In particular, the research provides new epigenomic data for four species of great apes and other primates: chimpanzees, gorillas, orangutans and macaques.

"In the study we used lymphoblastoid cell lines from humans and other primates because they provide a solid foundation as a model. Then we compared epigenomic signals between the different species, including the weakest activity signals in our analysis", comments Raquel García, a PhD with the Comparative Genomics group of the IBE and first author of the article.

"When we focused on detecting those specific characteristics of humans in the weakest epigenomic signals, we saw that they are related to brain functions", explains Paula Esteller, a PhD student with Marquès-Bonet's group and study co-author. "This opens the door to studying the role of weak epigenomic signals in depth, as they may play an important role in various organs of humans and of other primates".

The study includes weak epigenomic signals, usually ignored, and it has been seen that in humans they are related to brain functions.

The study, carried out using lymphoblastoid cells, which are easily accessible and easy to culture, suggests that this model could provide information on other more inaccessible tissues, such as the brain. The research could help understand how primates' cells are regulated and which of these mechanisms have been conserved over the course of evolution. The study also provides a comprehensive resource of genomic and epigenomic data on primates that are made available to the entire scientific community.

Philadelphia, June 16, 2021 - The SARS-CoV-2 virus that causes COVID-19 may have the ability to reactivate dormant tuberculosis (TB). In a novel study scientists report in The American Journal of Pathology that infection with a specific coronavirus strain reactivated dormant Mycobacterium tuberculosis (MTB) in mice. This knowledge may help to develop new vaccines for COVID-19 and avoid a potential global tuberculosis epidemic.

The COVID-19 pandemic caused by the SARS-CoV-2 virus demonstrates the ability of an emerging virus to affect masses and strain and disrupt the workings of modern healthcare systems around the world. A significant number of infected COVID-19 individuals have recovered. However, a possible host defense or antiviral mechanism against the virus is yet to be identified. There are concerns that in the long-term, the virus might activate dormant bacterial infections such as TB in select infected individuals, as alarmingly, TB is already present in one quarter of the world population. Viral infections such as the influenza virus or SARS-CoV-1 are known to cause transient immune suppression that leads to reactivation of dormant bacterial infection. The highest death rate during the Spanish flu pandemic of 1918 was in patients with TB, and patients with TB or multidrug-resistant TB had a worse prognosis than others during the influenza A (H1N1) pandemic in 2009.

"There is an urgent need to study the association of COVID-19 with dormant TB reactivation to avoid a potential global TB pandemic," explained lead investigator Bikul Das, MD, PhD, Department of Stem Cell and Infectious Diseases, KaviKrishna Laboratory, Guwahati Biotech Park, Indian Institute of Technology, Guwahati, India; and Department of Stem Cell and Infection, Thoreau Lab for Global Health, University of Massachusetts, Lowell, MA, USA. "It is important to understand the host defense mechanism against this disease to develop a better vaccine and/or treatment. We therefore postulated that, similar to bacteria, adult stem cells may also exhibit an altruistic defense mechanism to protect their niche against external threat."

Investigators studied the coronavirus strain murine hepatitis virus-1 (MHV-1) infection in the lung in a mouse model (dMtb) of mesenchymal stem cell (MSC)-mediated MTB dormancy. This showed 20-fold lower viral loads than the dMtb-free control mice by the third week of viral infection and a six-fold increase of altruistic stem cells (ASCs), thereby enhancing the defense. Tuberculosis was reactivated in the dMtb mice, suggesting that dormant TB bacteria hijack these ASCs to replicate in the lung to cause pulmonary TB. Results suggest that these ASCs are transient (they expand for two weeks and then undergo apoptosis or cellular suicide) and exhibit antiviral activities against MHV-1 by secreting soluble factors.

"These findings are important because they reveal a novel ASC defense mechanism against mouse coronavirus infection, which could be used to develop novel therapeutic approaches against COVID-19," noted Bikul Das. "The finding of TB reactivation in a stem cell-mediated Mtb dormancy mouse model during MHV-1 coronavirus infection indicates that in the long-term, post-pandemic, the SARS-CoV-2 virus might activate dormant bacterial infections. This is a significant finding considering the current coronavirus pandemic, where many individuals in India and other developing countries with dormant TB infection may see an increase in active TB cases post COVID-19. The ASC-mediated defense mechanism may be targeted to develop vaccines against viral infections and avoid a potential global TB pandemic."

The presence of pro-inflammatory cytokines in the blood can boost the effects of daily cannabis use and heighten the risk of developing psychosis in adulthood. Similar results have been observed, also in the presence of cytokines, when cannabis is used during adolescence. Psychotic disorders have symptoms such as delirium, loss of a sense of reality, hallucinations, hearing voices, and cognitive and social impairments.

A study by researchers at the University of São Paulo's Ribeirão Preto Medical School (FMRP-USP) in Brazil, reported in an article in the journal Psychological Medicine, finds for the first time that individuals exposed to a combination of these two factors - the presence of pro-inflammatory cytokines in the blood and cannabis use (either daily or during adolescence) - are more likely to suffer from psychosis than those who are exposed to neither or to only one. According to the authors, the study provides "the first clinical evidence that immune dysregulation modifies the cannabis-psychosis association".

The study was part of a project conducted by the European Network of National Schizophrenia Networks Studying Gene-Environment Interactions (EU-GEI), a consortium of research centers in 13 countries, including Brazil. An article published in The Lancet Psychiatry by the consortium in 2019 showed that daily cannabis use increased the likelihood of suffering from a psychotic disorder threefold.

In the more recent study, the researchers analyzed data for 409 people aged 16-64, including patients experiencing their first psychotic episode and community-based controls. The sample was drawn from the populations of Ribeirão Preto and 25 other cities in the region. The variables analyzed included cannabis use frequency (daily, not daily or never), duration (five years or less), and onset age (in adolescence or later).

In addition to the questionnaire on cannabis use, the researchers measured various cytokines in plasma donated by the volunteers and calculated scores representing their systemic inflammatory profiles. They also collected clinical and socio-demographic data, especially variables known as confounders, such as age, gender, schooling, ethnicity, body mass index, smoking, and use of psychoactive substances. The results obtained were independent of confounding factors.

"Not everyone who uses cannabis develops psychosis. This suggests that the association may be modified by other factors, which may be biological, genetic or environmental," said Fabiana Corsi-Zuelli, first author of the article. "In a previous study conducted as part of my master's research, we identified a correlation between plasma cytokines and the first psychotic episode. Following up on this discovery, and the consortium's recent publication showing a higher incidence of psychosis among subjects who used cannabis on a daily basis, our next step was to see if the biological factor [inflammatory profile] affected the link between cannabis use and psychosis."

The main conclusion was that such a link did indeed exist. "We found a statistically significant correlation between inflammatory profile and cannabis use on a daily basis or during adolescence. In sum, the results showed that immune system dysfunction can modify the association between cannabis use and psychosis and that a combination of these two factors increases the odds of suffering from a psychotic disorder," she said.

Corsi-Zuelli is currently a PhD candidate in FMRP-USP's graduate program in neurology and neurosciences, with support from São Paulo Research Foundation - FAPESP.

The principal investigator for the project is Cristina Marta Del-Ben, a professor at FMRP-USP's Department of Neurosciences and Behavioral Sciences. According to Del-Ben, risk factors for psychosis may be biological, including genetic predisposition and problems during pregnancy, as well as environmental, including traumatic experiences during childhood and adolescence, and exposure to psychoactive substances, especially cannabis.

"The mechanisms of the disorder are poorly understood," she said. "Our findings show that frequent current use of cannabis or use of the drug in adolescence is a risk factor for psychosis. We didn't detect the same correlation with occasional or recreational use. In the multicenter study, which included European cities with varying levels and types of cannabis availability, we also found that the risk of psychosis is greater in users of stronger cannabis strains with a THC content or 10% of higher." THC (delta-9-tetrahydrocannabinol) is the primary psychoactive constituent of cannabis or marijuana.

The medical explanation of psychosis is that it is a neuropsychiatric syndrome associated with anatomical and functional alterations in the brain, possibly linked to changes in the action of dopamine, a key neurotransmitter for communication among neurons. Excessive dopamine or direct damage to certain brain regions can lead to hallucinations, delusions, delirium and disorganized behavior.

Other neurotransmitters, such as glutamate, have also been implicated in the neurobiology of psychosis. Specialists are currently discussing what they call the neuroimmune link, and how immune system dysregulation may trigger neurochemical, morphological and behavioral alterations that heighten the risk of developing psychiatric disorders.

Psychotic symptoms may be present in several psychiatric disorders, which may or may not be affective. Recent research has taken note of cases of psychosis in patients infected by SARS-CoV-2. Treatment of psychosis involves a combination of medication, psychotherapy and family support.

Next steps

According to Corsi-Zuelli, the origin of the inflammatory alterations involved in psychosis is still obscure, but it may arise from a combination of genetic and environmental factors. "The inflammation seen in psychiatric disorders is considered low-level and isn't as severe as in patients with autoimmune diseases or sepsis," she said. "Nevertheless, experimental studies suggest it entails sufficient dysregulation to produce neurochemical and behavioral alterations."

The researchers plan next to study genetic variants associated with the immune system and use neuroimaging data to explore the link with environmental risk factors. "Focusing in this way on the interactions between genetics and the environment will help us understand the neurobiology of psychosis, especially the role played by the immune system," she said.

The association between inflammation and psychiatric disorders is highly relevant to clinical practice and has received growing attention. "It's important to the search for alternative treatments for these disorders, and also to answering often neglected questions relating to the physical health of psychiatric patients," Corsi-Zuelli said.

According to Del-Ben, in the pipeline for next steps is a partnership with Geraldo Busatto Filho, a professor at the Medical School (FM) in USP's main campus, to investigate whether inflammatory markers in blood are linked to brain alterations in some of the patients studied.

The research has twice received international recognition. The Society of Biological Psychiatry selected the study for its Predoctoral Scholars Award, which was to have been formalized at SOBP's 2020 annual meeting in New York, but the pandemic forced a postponement until April 2021, when the meeting was held online. And the study was selected by the Schizophrenia International Research Society (SIRS) for presentation at its 2020 Congress, also held online.

Besides the scholarship awarded to Corsi-Zuelli, FAPESP also supported the research via four other grants: 2012/05178-0, 2013/11167-3, 2017/13353-0, and 2018/07581-2.

NEW YORK, NY (June 16, 2021)--Spectacular images of a molecule that shuttles omega-3 fatty acids into the brain may open a doorway for delivering neurological therapeutics to the brain.

"We've managed to obtain a three-dimensional structure of the transporter protein that provides a gateway for omega-3s to enter the brain. In this structure, we can see how omega-3s bind to the transporter. This information may allow for the design of drugs that mimic omega-3s to hijack this system and get into the brain," says first author Rosemary J. Cater, PhD, a Simons Society Fellow in the Mancia Lab at Columbia University Vagelos College of Physicians and Surgeons.

The study was published online on June 16 in the journal Nature.

A major challenge in treating neurological diseases is getting drugs across the blood-brain barrier--a layer of tightly packed cells that lines the brain's blood vessels and zealously blocks toxins, pathogens, and some nutrients from entering the brain. Unfortunately, the layer also blocks many drugs that are otherwise promising candidates to treat neurological disorders.

Essential nutrients like omega-3s require the assistance of dedicated transporter proteins that specifically recognize them and get them across this barrier. "The transporters are like bouncers at a club, only letting molecules with invites or backstage passes in," Cater says.

The transporter--or bouncer--that lets omega-3s in is called MFSD2A and is the focus of Cater's research. "Understanding what MFSD2A looks like and how it pulls omega-3s across the blood-brain barrier may provide us with the information we need to design drugs that can trick this bouncer and gain entry passes."

To visualize MFSD2A, Cater used a technique called single-particle cryo-electron microscopy.

"The beauty of this technique is that we're able to see the shape of the transporter with details down to a fraction of a billionth of a meter," says study co-leader Filippo Mancia, PhD, associate professor of physiology & cellular biophysics at Columbia University Vagelos College of Physicians and Surgeons and an expert in the structure and function of membrane proteins. "This information is critical for understanding how the transporter works at a molecular level."

For cryo-EM analysis, protein molecules are suspended in a thin layer of ice under an electron microscope. Powerful cameras take millions of pictures of the proteins from countless angles which can then be pieced together to construct a 3D map.

Into this map researchers can build a 3D model of the protein, putting each atom in its place. "It reminds me of solving a jigsaw puzzle," Mancia explains. This technique has become remarkably powerful in visualizing biological molecules in recent years, thanks in part to Joachim Frank, PhD, professor of biochemistry & molecular biophysics at Columbia University Vagelos College of Physicians and Surgeons, who won the Nobel Prize in 2017 for his role in developing cryo-electron microscopy data analysis algorithms.

"Our structure shows that MFSD2A has a bowl-like shape and that omega-3s bind to a specific side of this bowl," Cater explains. "The bowl is upside down and faces the inside of the cell, but this is just a single 3D snapshot of the protein, which in real life has to move to transport the omega-3s. To understand exactly how it works, we need either multiple different snapshots or, better yet, a movie of the transporter in motion."

To understand what these movements might look like, a second co-leader of the study, George Khelashvili, PhD, assistant professor of physiology and biophysics at Weill Cornell Medicine, used the 3D model of the protein as a starting point to run computational simulations that revealed how the transporter moves and adapts its shape to release omega-3s into the brain. A third co-leader of the study, David Silver, PhD, professor at the Duke-NUS Medical School in Singapore and pioneer in MFSD2A biology, together with his team tested and confirmed hypotheses derived from the structure and the computational simulations on how MFSD2A works to pinpoint specific parts of the protein that are important.

The team also included researchers from the New York Structural Biology Center, the University of Chicago, and the University of Arizona, all using their specific skills to make this project possible.

The team is now investigating how the transporter first recognizes omega-3s from the bloodstream. "But our study has already given us tremendous insight into how MFSD2A delivers omega-3s to the brain, and we are really excited to see where our results lead to," Cater says.

The long relationships between stars and the planets around them - including the Sun and the Earth - may be even more complex than previously thought. This is one conclusion of a new study involving thousands of stars using NASA's Chandra X-ray Observatory.

By conducting the largest survey ever of star-forming regions in X-rays, a team of researchers has helped outline the link between very powerful flares, or outbursts, from youthful stars, and the impact they could have on planets in orbit.

"Our work tells us how the Sun may have behaved and affected the young Earth billions of years ago," said Kostantin Getman of Pennsylvania State University in University Park, Pennsylvania who led the study. "In some ways, this is our ultimate origin story: how the Earth and Solar System came to be."

The scientists examined Chandra's X-ray data of more than 24,000 stars in 40 different regions where stars are forming. They captured over a thousand stars that gave off flares that are vastly more energetic than the most powerful flare ever observed by modern astronomers on the Sun, the "Solar Carrington Event" in 1859. "Super" flares are at least one hundred thousand times more energetic than the Carrington Event and "mega" flares up to 10 million times more energetic.

These powerful flares observed by Chandra in this work occur in all of the star-forming regions and among young stars of all different masses, including those similar to the Sun. They are also seen at all different stages in the evolution of young stars, ranging from early stages when the star is heavily embedded in dust and gas and surrounded by a large planet-forming disk, to later stages when planets would have formed and the disks are gone. The stars in the study have ages estimated to be less than 5 million years, compared to the Sun's age of 4.5 billion years.

The team found several super-flares occur per week for each young star, averaged over the whole sample, and about two mega-flares every year.

"We want to know what kinds of impact - good and bad - these flares have on the early lives of planets," said co-author Eric Feigelson, also of Penn State. "Flares this powerful can have major implications."

Over the past two decades, scientists have argued that these giant flares can help "give" planets to still-forming stars by driving gas away from disks of material that surround them. This can trigger the formation of pebbles and other small rocky material that is a crucial step for planets to form.

On the other hand, these flares may "take away" from planets that have already formed by blasting any atmospheres with powerful radiation, possibly resulting in their complete evaporation and destruction in less than 5 million years.

The researchers also performed detailed modeling of 55 bright super- and mega-flares and found that most of them resemble long-lasting flares seen on the Sun that produce "coronal mass ejections," powerful ejections of charged particles that can damage planetary atmospheres. The Solar Carrington Event involved such an ejection.

This work is also important for understanding the flares themselves. The team found that the properties of the flares, such as their brightness and frequency, are the same for young stars with and without planet-forming disks. This implies that the flares are likely similar to those seen on the Sun, with loops of magnetic field having both footprints on the surface of the star, rather than one anchored to the disk and one to the star.

"We've found that these giant flares are like ones on the Sun but are just greatly magnified in energy and frequency, and the size of their magnetic loops," said co-author Gordon Garmire from the Huntingdon Institute for X-ray Astronomy in Huntingdon, Pennsylvania". Understanding these stellar outbursts may help us understand the most powerful flares and coronal mass ejections from the Sun."