Culture

Though we may not always realize it, photodetectors contribute greatly to the convenience of modern life. Also known as photosensors, photodetectors convert light energy into electrical signals to complete tasks such as opening automatic sliding doors and automatically adjusting a cell phone's screen brightness in different lighting conditions.

A new paper, published by a team of Penn State researchers in ACS Nano, seeks to further advance photodetectors' use by integrating the technology with durable Gorilla glass, the material used for smart phone screens that is manufactured by Corning Incorporated.

The integration of photodetectors with Gorilla glass could lead to the commercial development of "smart glass," or glass equipped with automatic sensing properties. Smart glass has a number of applications ranging from imaging to advanced robotics, according to the researchers.

"There are two problems to address when attempting to manufacture and scale photodetectors on glass," said principal investigator Saptarshi Das, assistant professor of engineering science and mechanics (ESM).?"It must be done using relatively low temperatures, as the glass degrades at high temperatures, and must ensure the photodetector can operate on glass using minimal energy."

To overcome the first challenge, Das, along with ESM doctoral student Joseph R. Nasr, determined that the chemical compound molybdenum disulfide was the best material to use as a coating on the glass.

Then, Joshua Robinson, professor of materials science and engineering (MatSE) and MatSE doctoral student Nicholas Simonson used a chemical reactor at 600 degrees Celsius -- a low enough temperature so as not to degrade the Gorilla glass - to fuse together the compound and glass. The next step was to turn the glass and coating into a photodetector by patterning it using a conventional electron beam lithography tool.

"We then tested the glass using green LED lighting, which mimics a more natural lighting source unlike laser lighting, which is commonly used in similar optoelectronics research," Nasr said.

The ultra-thin body of the molybdenum disulfide photodetectors allows for better electrostatic control, and ensures it can operate with low power -- a critical need for the smart glass technology of the future.

"The photodetectors need to work in resource-constrained or inaccessible locations that by nature do not have access to sources of unrestricted electricity," Das said. "Therefore, they need to rely on pre-storing their own energy in the form of wind or solar energy."

If developed commercially, smart glass could lead to technology advances in wide-ranging sectors of industry including in manufacturing, civil infrastructure, energy, health care, transportation and aerospace engineering, according to the researchers. The technology could be applied in biomedical imaging, security surveillance, environmental sensing, optical communication, night vision, motion detection and collision avoidance systems for autonomous vehicles and robots.

"Smart glass on car windshields could adapt to oncoming high-beam headlights when driving at night by automatically shifting its opacity using the technology," Robinson said. "And new Boeing 757 planes could utilize the glass on their windows for pilots and passengers to automatically dim sunlight."

UNIVERSITY PARK, Pa. -- Fake news detectors, which have been deployed by social media platforms like Twitter and Facebook to add warnings to misleading posts, have traditionally flagged online articles as false based on the story's headline or content. However, recent approaches have considered other signals, such as network features and user engagements, in addition to the story's content to boost their accuracies.

However, new research from a team at Penn State's College of Information Sciences and Technology shows how these fake news detectors can be manipulated through user comments to flag true news as false and false news as true. This attack approach could give adversaries the ability to influence the detector's assessment of the story even if they are not the story's original author.

"Our model does not require the adversaries to modify the target article's title or content," explained Thai Le, lead author of the paper and doctoral student in the College of IST. "Instead, adversaries can easily use random accounts on social media to post malicious comments to either demote a real story as fake news or promote a fake story as real news."

That is, instead of fooling the detector by attacking the story's content or source, commenters can attack the detector itself.

The researchers developed a framework -- called Malcom -- to generate, optimize, and add malicious comments that were readable and relevant to the article in an effort to fool the detector. Then, they assessed the quality of the artificially generated comments by seeing if humans could differentiate them from those generated by real users. Finally, they tested Malcom's performance on several popular fake news detectors.

Malcom performed better than the baseline for existing models by fooling five of the leading neural network based fake news detectors more than 93% of the time. To the researchers' knowledge, this is the first model to attack fake news detectors using this method.

This approach could be appealing to attackers because they do not need to follow traditional steps of spreading fake news, which primarily involves owning the content. The researchers hope their work will help those charged with creating fake news detectors to develop more robust models and strengthen methods to detect and filter-out malicious comments, ultimately helping readers get accurate information to make informed decisions.

"Fake news has been promoted with deliberate intention to widen political divides, to undermine citizens' confidence in public figures, and even to create confusion and doubts among communities," the team wrote in their paper, which will be presented virtually during the 2020 IEEE International Conference on Data Mining.

Added Le, "Our research illustrates that attackers can exploit this dependency on users' engagement to fool the detection models by posting malicious comments on online articles, and it highlights the importance of having robust fake news detection models that can defend against adversarial attacks."

Scientists worldwide have been working flat out on research into infectious diseases in the wake of the global outbreak of the COVID-19 disease, caused by the new coronavirus SARS-CoV-2. This concerns not only virologists, but also physicists, who are developing mathematical models to describe the spread of epidemics. Such models are important for testing the effects of various measures designed to contain the disease - such as face masks, closing public buildings and businesses, and the familiar one of social distancing. These models often serve as a basis for political decisions and underline the justification for any measures taken.

Physicists Michael te Vrugt, Jens Bickmann and Prof. Raphael Wittkowski from the Institute of Theoretical Physics and the Center for Soft Nanoscience at the University of Münster have developed a new model showing the spread of infectious diseases. The working group led by Raphael Wittkowski is studying Statistical Physics, i.e. the description of systems consisting of a large number of particles. In their work, the physicists also use dynamical density functional theory (DDFT), a method developed in the 1990s which enables interacting particles to be described.

At the beginning of the corona pandemic, they realised that the same method is useful for describing the spread of diseases. "In principle, people who observe social distancing can be modelled as particles which repel one another because they have, for example, the same electrical charge," explains lead author Michael te Vrugt. "So perhaps theories describing particles which repel one another might be applicable to people keeping their distance from one another," he adds. Based on this idea, they developed the so-called SIR-DDFT model, which combines the SIR model (a well-known theory describing the spread of infectious diseases) with DDFT. The resulting theory describes people who can infect one another but who keep their distance. "The theory also makes it possible to describe hotspots with infected people, which improves our understanding of the dynamics of so-called super-spreader events earlier this year such as the carnival celebrations in Heinsberg or the après-ski in Ischgl," adds co-author Jens Bickmann. The results of the study have been published in the journal "Nature Communications".

The extent of the social distancing being practised is then defined by the strength of the repulsive interactions. "As a result," explains Raphael Wittkowski, the leader of the study, "this theory can also be used to test the effects of social distancing by simulating an epidemic and varying the values for the parameters defining the strength of the interactions." The simulations show that the infection rates do indeed show a marked decrease that is a result of social distancing. The model thus reproduces the familiar "flattening the curve" effect, in which the curve depicting the development of the number of infected people over time becomes much flatter as a result of social distancing. In comparison with existing theories, the new model has the advantage that the effects of social interactions can be explicitly modelled.

In March 2020, New York City, an icon of America, was unfortunately named an early epicenter of the novel coronavirus. Now seven months later, America faces a new surge in coronavirus cases and researchers at Texas A&M University hope to provide information and context to help with the battle ahead.

Rich Whittle, a doctoral student at Texas A&M, cites in a recent study that by April 2020, New York City accounted for more than a third of the nation's confirmed cases, with a transmission rate five times higher than the rest of the country.

Whittle wanted to look at these early stages of the pandemic spread in New York neighborhoods to discover if there were any socioeconomic factors that could be associated with the high positivity rate of COVID-19.

"The world is waking up to the first global pandemic in a while, but it's not going to be the last, so understanding the contact patterns and socioeconomic factors that lead to high-detected case numbers is important for public health," said Whittle.

The study, published in BMC Medicine, identified four significant predictors of COVID-19 cases in New York City: neighborhoods with higher population densities led to an increase in the positivity rate; neighborhoods with younger populations (under 18 years old) also led to an increase; households with a higher income led to a decrease; and race showed a significant association with detected COVID-19 cases - both a lower percentage of white population and higher percentage of Black population led to increased positivity rates.

"From what is available in the early stages, this is what we're seeing from the data, and we know those early stages are really important to keep this and future pandemics under control," said Dr. Ana Diaz Artiles, assistant professor in the Department of Aerospace Engineering at Texas A&M and co-author of the study.

The study used spatial modeling techniques to look at data from roughly 60,000 cases during the first month of the pandemic in New York City.

"I'm really interested in spatial statistics. When I was in the military, I worked in geospatial intelligence so I have a background interest in that," said Whittle. "And I was taking Dr. Diaz Artiles' stats class at the time, so I thought I could combine those two interests and have a look at an ecological study related to COVID-19."

Whittle initiated the study as his final class project for Diaz Artiles' spring Design of Experiments and Statistical Methods course (AERO 689).

"This class gives the opportunity to solve problems that the students are interested in," said Diaz Artiles. "These classes are really useful for students not only in terms of learning statistical tools, but to apply them in practical applications that could even lead to impactful results and publications."

In addition to academic interest, Whittle was motivated to pursue the study because of the value the results could provide, both now and in the future.

"There's a need to understand the beginning stage of the pandemic," said Whittle. "And I think in America, certainly now, there's a lot of discontent. There's a definite public interest in understanding the response in the initial stages of the pandemic."

Whittle and Diaz Artiles emphasize that understanding the early factors and influences of past pandemics, such as the H1N1 pandemic of 2009 and the one we face today, is important in helping to inform future management.

"Hopefully our study will provide a better understanding of the main factors that impact the spread of the disease, thus improving future decision making in the early stages of a pandemic," said Diaz Artiles.

The majority of people infected with SARS-CoV-2 appear to actively shed infectious virus for about 8 days, but there is a wide range of variability from person to person. Understanding how long people can remain actively infected is important, because it provides new details about a disease and a virus that are still not well understood and informs public health decisions. Researchers report November 4 in the journal Cell an unusual case of one woman with leukemia and a low antibody count who was infected with the coronavirus for at least 105 days, and infectious for at least 70, while remaining asymptomatic the entire time.

"At the time we started this study, we really didn't know much about the duration of virus shedding," says senior author Vincent Munster, a virologist at the National Institute of Allergy and Infectious Diseases. "As this virus continues to spread, more people with a range of immunosuppressing disorders will become infected, and it's important to understand how SARS-CoV-2 behaves in these populations."

Munster, an expert in emerging infectious diseases, began publishing research on SARS-CoV-2 in January. He was contacted in April by infectious disease specialist Francis Riedo, a study co-author, about a patient in Kirkland, Washington, who had been infected very early in the COVID-19 pandemic. Riedo's patient had had numerous positive PCR tests for the virus over a period of weeks, and he wanted to know if she was still shedding virus.

The patient, a 71-year-old woman, was immunocompromised due to chronic lymphocytic leukemia and acquired hypogammaglobulinemia. She never showed any symptoms of COVID-19. She was found to be infected with the virus when she was screened after being admitted to the hospital for severe anemia and her doctors recognized that she had been a resident of a rehabilitation facility experiencing a large outbreak.

Munster's lab at NIAID's Rocky Mountain Laboratories in Hamilton, Montana, began studying samples that were regularly collected from the patient's upper respiratory tract. They found that infectious virus continued to be present for at least 70 days after the first positive test, and the woman didn't fully clear the virus until after day 105. "This was something that we expected might happen, but it had never been reported before," Munster says.

The investigators believe the patient remained infectious for so long because her compromised immune system never allowed her to mount a response. Blood tests showed that her body was never able to make antibodies. At one point she was treated with convalescent plasma, but Munster doesn't think the treatment had an effect because of its low concentration of antibodies. Despite her inability to mount an antibody response, she never went on to develop COVID-19.

The team performed deep sequencing on all the virus samples obtained from the patient to see how the virus might have changed over the course of the patient's infection. Samples collected at various times displayed different dominant gene variants. However, the investigators don't think that these mutations played a role in how long the virus persisted, because they saw no evidence of natural selection. Selection would have been implicated if one of the variants had appeared to provide the virus with a survival benefit and had become the dominant variant, but none of them did. They also tested whether or not the mutations affected the ability or speed of the virus to replicate and found no differences.

Munster says that as far as he knows, this is the longest case of anyone being actively infect-ed with SARS-CoV-2 while remaining asymptomatic. "We've seen similar cases with influenza and with Middle East respiratory syndrome, which is also caused by a coronavirus," he notes. "We expect to see more reports like ours coming out in the future."

Microbes and other microscopic organisms could serve as sustainable "factories" to create many types of industrial materials because they naturally convert nutrients such as sugars into byproducts. However, creating industrial amounts of organic acids from renewable resources poses a challenge, because not many organisms can grow in highly acidic environments. With the help of gene editing and computational modeling tools, a team of researchers explored one type of yeast that could survive in the harsh environment created by acidic products.

The team, which includes Penn State, the University of Illinois at Urbana-Champaign and Princeton University researchers, studied the yeast strain Issatchenkia orientalis, considered to be a "non-model" yeast because it has not been researched extensively. After reconstructing the yeast's metabolism into a network model, the team examined its growth on different feedstock and subsequent byproducts. This strain was able to produce succinic acid, which is a precursor for industrial polymer production. The team reported its results in Metabolic Engineering Communications.

The researchers used a combination of genetic sequencing, gene editing, and sophisticated computational modeling to pinpoint which metabolic activities could be changed to maximize production of succinic acid without detriment to the yeast.

"The emergence of efficient CRISPR-Cas tools for making multiple genetic interventions in a single pass has emphasized the need for the development of predictive models and algorithms for suggesting which multiple genetic modifications to implement," said Costas Maranas, the Donald B. Broughton Professor of chemical engineering and Institute for Computational and Data Sciences associate, Penn State, who co-led this study.

The computation-heavy approach, which ran on Penn State's Roar supercomputer, was important in helping to refine the research direction, according to the researchers. The I. orientalis model covers 850 genes and contains 1,826 metabolic reactions, so identifying the right combination of genes and reactions to modify in order to produce succinic acid becomes a needle-in-a-haystack type of problem. Running thousands of computer simulations sifts through the hay and provides a much narrower set of experiments to test in a lab.

"With this approach, we can rank redesign hypotheses much faster than relying on a purely experimentalist approach," said Patrick Suthers, postdoctoral scholar in chemical engineering, Penn State. "Our collaborators worked on developing genetic tools specifically for this organism, but even with their tools, it takes much longer to make modifications."

The team's analysis uses OptKnock, an optimization framework previously developed by the Maranas group, as part of the computational modeling.

Combining the computational techniques with traditional experiments not only informed the models with phenotypic measurements, but it also allowed the researchers to ensure their model was accurate in its predictions.

"One critical part of creating models is being able to say, yes, our predictions do make sense," said Suthers. "In this case, our group focused on taking information from the genome in the organism, which our collaborators had sequenced. Then we take the genome and convert it into the functions that can take place in the cell."

The result is a yeast model that can be used in any number of ways.

"Now that we have this comprehensive genome-scale model, we can look at things like the rates of organism growth and fluxes, and we can nail down key reactions in the metabolic system," said Suthers. "We can also add in new genes to make new types of products."

An earthquake of magnitude 8.0 or larger will almost always cause strong shaking, but a new study suggests that smaller earthquakes--those around magnitude 5.5 or so--are the cause of most occurrences of strong shaking at a 60-kilometer (37-mile) distance.

Small earthquakes are expected to produce relatively weak shaking, and for the most part that's true, said Sarah Minson of the U.S. Geological Survey. However, ground motion is highly variable, and there are always outlier earthquakes at every size that generate more shaking than expected.

Combine that with the fact that there are more smaller magnitude earthquakes than large magnitude earthquakes, and most shaking comes from these "little earthquakes with ambition," Minson and her colleagues report in Seismological Research Letters.

The researchers found that for all distances and for all levels of shaking, "the earthquakes that cause that level of shaking are systematically smaller magnitude than the earthquakes that should cause that level of shaking," said Minson, noting that this makes these smaller earthquakes a significant source of earthquake damage.

The findings could change how people think about and prepare for the "Big One," the large magnitude earthquakes that loom large in the imaginations of people from California to Chile, said Minson.

A future magnitude 8.0 San Andreas Fault earthquake will cause more total damage across the Los Angeles Basin than a smaller, local earthquake like the 1933 magnitude 6.4 Long Beach earthquake, simply because the larger earthquake causes shaking over a wider area. But that just means that there will be more overall shaking, not that the shaking will necessarily be stronger in any particular locality, she explained.

While waiting for the Big One, places like Long Beach are likely to have multiple damaging medium earthquakes, "and thus most damage at any location is probably coming from smaller earthquakes with ambition," Minson added.

The 1969 Santa Rosa, California earthquakes, around magnitude 6, caused about $50 million damage in today's dollars, while the magnitude 5.7 Magna, Utah earthquake earlier this year caused similar amounts of damage just to 100 government buildings, the researchers noted.

"For a lot of us, if we do look back over our personal experiences, the earthquake that we had the greatest amount of damage from is not the largest magnitude earthquake that we've felt at all," Minson said.

It's a "sharks versus cows" concept, she added. "Sharks are scary, and cows are not, but cows kill more people every year than sharks do."

The researchers began with calculations of the variation of expected ground acceleration from an earthquake of a certain magnitude and distance away from the shaking, along with the well-known Gutenberg-Richter magnitude-frequency relationship. The relationship demonstrates how the frequency of earthquakes decreases as the magnitude grows, so that for each magnitude 8 earthquake that occurs within a given region and time period, there will be 10 magnitude 7 earthquakes, 100 magnitude 6 earthquakes, and so on.

Together, these two factors suggest that most shaking should come from smaller earthquakes that are "ambitious outliers" in terms of the amount of ground acceleration they cause. "The probability of any of these small earthquakes producing shaking is tiny, but there are many of them," Minson said.

Minson and colleagues confirmed this hypothesis after examining three data sets of earthquakes from across the globe, ranging from magnitude 0.5 to 8.3.

Ambitious little earthquakes may cause difficulty for some earthquake early warning systems, which alert users to potential damaging shaking after an earthquake begins, the researchers write. The closer users are to the earthquake source, the less likely it is that the alert arrives before they feel the shaking.

"If it turns that most of our shaking is coming from smaller magnitude earthquakes, well, smaller magnitude earthquakes are spatially more compact," Minson said, who noted that some systems also may not send out an alert at all for small earthquakes that aren't expected to produce damaging shaking.

The findings do not change the total amount of earthquake hazard calculated for a region, Minson stressed. "All we did is say, ok, when that shaking comes, what is it likely to come as? And it's much more likely to come as little earthquakes with ambition than a big earthquake doing what big earthquakes do."

This means, as Minson's UGGS co-author Sara McBride says, that "it's time to talk about the medium ones." Surveys and studies show that people often are demotivated by efforts to prepare for the Big One, overwhelmed by fatalism in the face of such an event. Focusing on smaller but significant events could encourage people to devote more time and effort to earthquake preparedness, the researchers suggest.

"If we talk about earthquakes like Loma Prieta and Northridge, and ask people to be prepared for that, it's more tractable," Minson said. "Those are the earthquakes that people have experienced and know how to prepare for and survive."

On April 28, a supermagnetized stellar remnant known as a magnetar blasted out a simultaneous mix of X-ray and radio signals never observed before. The flare-up included the first fast radio burst (FRB) ever seen from within our Milky Way galaxy and shows that magnetars can produce these mysterious and powerful radio blasts previously only seen in other galaxies.

"Before this event, a wide variety of scenarios could explain the origin of FRBs," said Chris Bochenek, a doctoral student in astrophysics at Caltech who led one study of the radio event. "While there may still be exciting twists in the story of FRBs in the future, for me, right now, I think it's fair to say that most FRBs come from magnetars until proven otherwise."

A magnetar is a type of isolated neutron star, the crushed, city-size remains of a star many times more massive than our Sun. What makes a magnetar so special is its intense magnetic field. The field can be 10 trillion times stronger than a refrigerator magnet's and up to a thousand times stronger than a typical neutron star's. This represents an enormous storehouse of energy that astronomers suspect powers magnetar outbursts.

The X-ray portion of the synchronous bursts was detected by several satellites, including NASA's Wind mission.

The radio component was discovered by the Canadian Hydrogen Intensity Mapping Experiment (CHIME), a radio telescope located at Dominion Radio Astrophysical Observatory in British Columbia and led by McGill University in Montreal, the University of British Columbia, and the University of Toronto.

A NASA-funded project called Survey for Transient Astronomical Radio Emission 2 (STARE2) also detected the radio burst seen by CHIME. Consisting of a trio of detectors in California and Utah and operated by Caltech and NASA's Jet Propulsion Laboratory in Southern California, STARE 2 is led by Bochenek, Shri Kulkarni at Caltech, and Konstantin Belov at JPL. They determined the burst's energy was comparable to FRBs.

By the time these bursts occurred, astronomers had already been monitoring their source for more than half a day.

Late on April 27, NASA's Neil Gehrels Swift Observatory spotted a new round of activity from a magnetar called SGR 1935+2154 (SGR 1935 for short) located in the constellation Vulpecula. It was the object's most prolific flare-up yet - a storm of rapid-fire X-ray bursts, each lasting less than a second. The storm, which raged for hours, was picked up at various times by Swift, NASA's Fermi Gamma-ray Space Telescope, and NASA's Neutron star Interior Composition Explorer (NICER), an X-ray telescope mounted on the International Space Station.

About 13 hours after the storm subsided, when the magnetar was out of view for Swift, Fermi and NICER, one special X-ray burst erupted. The blast was seen by the European Space Agency's INTEGRAL mission, the China National Space Administration's Huiyan X-ray satellite, and the Russian Konus instrument on Wind. As the half-second-long X-ray burst flared, CHIME and STARE2 detected the radio burst, which lasted only a thousandth of a second.

"The radio burst was far brighter than anything we had seen before, so we immediately knew it was an exciting event," said Paul Scholz, a researcher at the University of Toronto's Dunlap Institute for Astronomy & Astrophysics and a member of the CHIME/FRB Collaboration. "We've studied magnetars in our galaxy for decades, while FRBs are an extragalactic phenomenon whose origins have been a mystery. This event shows that the two phenomena are likely connected."

Papers from both the CHIME/FRB Collaboration and the STARE2 team were published on Nov. 4 in the journal Nature.

SGR 1935's distance remains poorly established, with estimates ranging from 14,000 to 41,000 light-years. Assuming it lies at the nearer end of this range, the X-ray portion of the simultaneous bursts carried as much energy as our Sun produces over a month. Intriguingly, however, it was not as powerful as some of the flares in the magnetar's storm eruption.

"The bursts seen by NICER and Fermi during the storm are clearly different in their spectral characteristics from the one associated with the radio blast," said George Younes, a researcher at George Washington University in Washington and the lead author of two papers analyzing the burst storm that are now undergoing peer review. "We attribute this difference to the location of the X-ray flare on the star's surface, with the FRB-associated burst likely occurring at or close to the magnetic pole. This may be key to understanding the origin of the exceptional radio signal."

SGR 1935's radio burst was thousands of times brighter than any radio emissions from magnetars in our galaxy. If this event had occurred in another galaxy, it would have been indistinguishable from some of the weaker FRBs observed.

In addition, the radio pulse arrived during an X-ray burst, something that has never before been seen in association with FRBs. Taken together, the observations strongly suggest that SGR 1935 produced the Milky Way's equivalent of an FRB, which means magnetars in other galaxies likely produce at least some of these signals.

For ironclad proof of the magnetar connection, researchers ideally would like to find an FRB outside of our galaxy that coincides with an X-ray burst from the same source. This combination may only be possible for nearby galaxies, which is why CHIME, STARE2 and NASA's high-energy satellites will keep watching the skies.

It is an experience we all share, as miraculous as it is mysterious. Birth.

Today, roughly one in three births in the United States occurs via cesarean section or C-section. In some other countries across the globe, like Brazil and Turkey, this percentage is even higher.

Yet little is known about how delivery by C-section affects an individual's long-term development.

As these interventions become more common in health care to foster positive outcomes for both mothers and babies, it is important to understand these long-term effects, both positive and negative, according to William Kenkel, an assistant professor of psychological and brain sciences at the University of Delaware.

Specifically, Kenkel is interested in understanding how different birth experiences, including vaginal delivery, emergency C-section and scheduled C-section, affect the developing nervous system. He also wants to know whether these changes occur through hormones that surge during birth.

"The body is set up in very redundant ways, and it reuses the same set of hormones for multiple things," said Kenkel, who studies the way hormones affect the brain to shape behavior.

This made Kenkel wonder if the disruption of these naturally occurring hormones during C-section could be a contributing factor in known health effects associated with cesarean. Previous peer-reviewed research, by multiple authors, has identified links between C-section and negative health outcomes in children, including obesity, asthma and autism. For example, studies have shown that delivery by C-section increases a child's risk for obesity by age 5 by an astounding 55%.

"We don't know why these links exist," he said. "Hormones provide a new way to look at these problems."

Understanding the body's stress response
During birth, hormones in the body surge in both mother and baby, sent along by the nervous system. These stress hormones are there to spur delivery and to help a baby adapt to living outside the womb. Some of the transitions babies accomplish at birth include starting to breathe, setting the body's internal temperature and responding to microbes passed along by the mother that help us regulate our immune system, digestion and more.

Looking across the research literature, however, Kenkel found that how one is born can have an effect on the amount of stress hormones released at the time of delivery. For example, vaginal delivery had the highest presence of birth signaling hormones, followed by emergency cesarean, then scheduled cesarean with the lowest levels.

He pointed out, too, that when babies are delivered by cesarean section, some of these normal hormonal signals are disrupted, or, in the case of scheduled C-section, never even started. How long these hormonal differences last remains unknown. This led Kenkel to question whether research should be looking at this more closely because these hormones acting in early life are capable of developmental programming, meaning they can cause permanent changes.

"Most likely there is a very broad, but shallow effect occurring," said Kenkel, who is among only a handful of researchers considering the hormonal implications of birth and the brain.

Other research, particularly related to a healthy microbiome, has focused on whether procedures should be used to reintroduce microbes that babies delivered by cesarean may have missed out on.

Kenkel wonders if the same idea could be used to introduce hormones in children that might not be activated by cesarean delivery. This is not necessarily a new idea. For example, premature infants are often given a hormone called cortisol to help the lungs mature.

"We may want to investigate whether doing a similar intervention makes sense in cesarean for any number of other hormones to get the body off on the right foot," he said.

While a lot of research has looked at the hormone oxytocin and whether or not it could play a role in the causes of autism, according to Kenkel, cesarean delivery and obstetric interventions more broadly, are all things that affect oxytocin signaling during this sensitive period around birth.

"There are times in our development where hormones have long-lasting consequences," said Kenkel. "For example, if I were to experience stress right now, I would generally recover quickly. In early life, however, we are sensitive because we are still trying to learn what the environment is going to be like. So, if my mom experienced high stress levels while I was in utero, that tells me that this environment that I'm going to be born into is a rough one, so I may want to change my development to anticipate that."

These hormones are versatile, too. Oxytocin is well known for its role in social bonding and helping mom bond with her baby, but evolution has found a lot of other uses for it. Oxytocin is also really good at regulating appetite, temperature and stress response.

"These seemingly disconnected aspects of life share connections using the same hormone; and when seemingly unrelated medical interventions affect those hormones, it can translate into surprising outcomes," he said.

If he can establish that hormones during birth play a long-lasting role in life, Kenkel said, it would lend evidence for research to explore possible interventions that could be applied at birth to ensure development that more closely resembles outcomes associated with a vaginal delivery.

Kenkel published his findings in a paper in the Journal of Neuroendocrinology.

He hopes the paper will open the door to new research ideas or directions in this area, particularly greater collaborative research between the fields of neuroscience and obstetrics, given the shared interest in hormone mechanisms and early life.

"At this stage of our understanding, we just need a lot more information," Kenkel said.

Support staff and Black and Latinx hospital employees with and without patient care responsibilities are at highest risk for SARS-CoV-2 infection in health care settings, a Rutgers study found.

After screening 3,904 employees and clinicians at a New Jersey hospital between late April and late June for the SARS-CoV-2 virus and for lgG-antibodies to the virus, whose presence suggests past recent infection, the study, published in the journal Open Forum Infectious Diseases, found that these employees are at higher risk than previously thought.

"The risk to workers in health care settings with little or no patient contact has attracted relatively little attention to date, but our results suggest potentially high infection rates in this group," said lead author Emily S. Barrett, an associate professor at Rutgers School of Public Health and a member of the Environmental and Occupational Health Sciences Institute. "By contrast and to our surprise, physicians, nurses and emergency medical technicians showed much lower infection rates."

Health care workers who live in highly impacted communities may have been susceptible to becoming infected outside of the hospital during the early surge of COVID-19, according to co-lead author Daniel B. Horton, an assistant professor at Rutgers Robert Wood Johnson Medical School and a member of the Institute for Health, Health Care Policy and Aging Research.

"In the early phase of the pandemic, support staff in the hospital may also have had less access to personal protective equipment or less enforcement of safety protocols," he said. "Going forward, as cases of COVID-19 in the hospital rise again, protecting these and all hospital workers from infection both in and out of the hospital is critical."

In the hospital-based study, researchers found that 13 participants tested positive for the virus and 374 tested positive for the antibody, which suggests recent past infection -- nearly 10 percent of those studied -- and that Black and Latinx workers had two times the odds of receiving a positive test for the virus or antibody compared to white workers.

Phlebotomists had the highest proportionate rate of positive tests--nearly 1 in 4 tested--followed by those employed in maintenance/housekeeping, dining/food services and interpersonal/support roles. By comparison, positivity rates were lower among doctors (7 percent) and nurses (9 percent).

Regardless of whether the infections originated in the hospital or in the community, Barrett said, the results suggest a need to enact safety protocols for hospital employees to protect the health care workforce from future waves of infection.

"The 40 percent of infected health care workers who reported having had no symptoms of infection could be a potential source of SARS-CoV-2 spread in hospitals even if their infections were initially acquired in the community," she said.

The very heart of inpatient care for psychiatric patients is socialization, group therapy, shared meals, and a standard two people per room. Then COVID-19 hit with the accompanying public health warnings to isolate, socially distance, and wear masks.

That sent clinicians and staff from The University of Texas Health Science Center at Houston (UTHealth) moving quickly to create a strategy for the UTHealth Harris County Psychiatric Center (UTHealth HCPC) that provided the best psychiatric care within a safe environment in the middle of an epic pandemic. That strategy was published in the October issue of Psychiatry Research.

"When COVID-19 began, we were left with the question of how to manage a highly infectious virus in a freestanding psychiatric hospital. There was no existing published guideline on how to do this," said first author Lokesh Shahani, MD, MPH, assistant professor in the Louis A. Faillace, MD, Department of Psychiatry and Behavioral Sciences at McGovern Medical School at UTHealth and chief medical officer of UTHealth HCPC.

The largest provider of inpatient psychiatric care in the Greater Houston area, the center is a 274-bed, safety-net hospital that provides care to around 9,000 patients each year. It is led by Executive Director Jair C. Soares, MD, PhD, senior author of the paper, and Pat R. Rutherford, Jr. Chair in Psychiatry in the Faillace Department of Psychiatry and Behavioral Sciences.

By mid-March, with rising Harris County cases, hospital leaders realized that the chances of a patient arriving who was infected with COVID-19 were rapidly growing.

"Our mission is to treat patients in the community who have psychiatric conditions and we didn't want to turn anyone away," said Stephen Glazier, COO of the hospital. "The only way to do that was to create an isolated COVID-19 unit."

To create the space, new patients were not admitted to that unit and remaining patients were moved into other units as spots became available. Glazier asked for volunteers willing to staff the unit day and night. Shahani, who is board certified in infectious disease as well as psychiatry, decided to lead the infection control initiative.

"I am honored to work alongside our dedicated nursing staff who stepped up and volunteered to take care of our COVID-19 patients," Shahani said. "Staff safety was our priority and we made sure everyone was trained in appropriately using PPE and had access to the same."

The team turned for advice and leadership from co-author Luis Ostrosky, MD, professor of infectious diseases at McGovern Medical School, and vice chair of Healthcare Quality at McGovern Medical School. "We had to keep staff safe as well as patients," Shahani said. "Being a part of UTHealth and able to consult with Dr. Ostrosky was invaluable for us."

Ostrosky is the COVID-19 Incident Commander for UTHealth. "COVID-19 continues to challenge the way we work. Knowledge acquisition and flexibility have been key in making changes and adapting to our new reality," Ostrosky said. "From transporting patients in helicopters, to figuring out waiting rooms, to making psychiatric care safe, UTHealth is here for our community's needs."

Complicating the process for the team were patients who refused to be tested for the coronavirus or understand why they had to wear a mask.

"In a medical hospital, patients are able to have a private room with attached bathroom, which we don't have, and they are tested for the virus. Psychiatric patients don't always consent for testing because of their severe mental illness, and 40% refused testing," Shahani said. "Wearing a face mask and adhering to hand hygiene are other measures needed to keep people safe, but people with chronic severe mental illness don't have the ability to always follow guidelines such as that."

The team decided to focus on screening for symptoms, fever, contact, and travel history. They used extreme caution: anyone who was suspected of having the virus was isolated.

The first test for the new unit came April 17 when an asymptomatic patient required isolation because of recent travel and exposure. Since then, over 100 patients have been treated in the COVID-19 unit, with 52% of them testing positive for the virus.

"We've had community partners who needed a safe place to treat patients and we have been able to step in and accept these patients," Shahani said. "We have been safely delivering psychiatric care during the pandemic."

"We could not be any prouder of the outstanding team of very committed, compassionate clinicians and staff we have at UTHealth HCPC," Soares said. "They stepped up to help us continue to function at very high levels through this unprecedented crisis with the pandemic."

GRAND RAPIDS, Mich. (Nov. 4, 2020) -- For the first time, scientists have visualized a new class of molecular gates that maintain pH balance within brain cells, a critical function that keeps cells alive and helps prevent stroke and other brain injuries.

These gates, called proton-activated chloride channels (PAC), nest within cell membranes and regulate the passage of small molecules called chloride ions into and out of cells. This allows cells to sense and respond to their environment.

"Proton-activated chloride channels have only recently been described but they are critical for cell survival, particularly in the brain," said Wei Lü, Ph.D., a Van Andel Institute assistant professor and co-corresponding author of the study, which was published today in Nature. "Our new images, coupled with our findings into how these channels work, provide much-needed molecular blueprints that will help answer long-standing questions in the field and provide new insights into how these channels may be therapeutically targeted in disease."

The images reveal a wedding bouquet-like structure, with parts that change configuration in response to environmental pH. When pH shifts from alkaline to acidic, a key pH sensor moves from its "resting" location and is inserted in an "acidic pocket," which signals that the gate allowing ions in and out of the cell should be open. This specific mechanism has never before been described.

This study is a collaboration between the Lü Lab at Van Andel Institute and a group led by Zhaozhu Qiu, Ph.D., an assistant professor at Johns Hopkins University School of Medicine and co-corresponding author of the paper. The Johns Hopkins team first reported the discovery of PAC in Science last year.

Solving PAC structures are another important, early step toward an understanding that may one day impact human health.

A new University of Colorado Boulder-led study sheds light on a protein key to controlling how cells grow, proliferate and function and long implicated in tumor development.

The findings, published this week in the journal Genes and Development, could lead not only to new therapies for hard-to-treat cancers, but also inform novel treatments for neurological diseases and rare developmental disorders, the authors say.

"These findings could have broad biomedical application," said lead author Dylan Taatjes, a professor in the Department of Biochemistry.

For decades, scientists have known that the protein Cyclin Dependent Kinase 7 (CDK7) plays an instrumental role in helping all cell types transcribe, or decode, the genetic instructions provided by their DNA.

As Taatjes explains, each cell contains the same vast library, or genome. But a kidney cell may turn to different sections of that library for instructions than, say, a skin cell or a heart cell. Like a librarian, CDK7 helps ensure that each cell accesses the right instructions at the right time, guiding which genes get flipped on and off.

While that's important during human development and for normal cell function, CDK7 can be exploited by cancer cells to drive runaway growth. In recent years, scientists have discovered that the protein can fuel certain cancers to proliferate out of control, including "triple negative" breast cancers, which are more aggressive and don't respond well to common treatments.

That finding has inspired growing interest in the development of so-called "CDK7-inhibitors" but due to a lack of understanding of what the CDK7 does, early clinical trials have been disappointing.

"We wanted to find out exactly how it's really working inside human cells," Taatjes said.

To that end, the Taatjes lab teamed up with scientists from two pharmaceutical companies, Syros and Paraza, as well as colleagues in other CU Boulder labs, the University of Colorado School of Medicine and the BioFrontiers Institute.

Using sophisticated analytical techniques, basic biochemistry and next-generation genetic sequencing, the team identified, for the first time, the hundreds of specific proteins that CDK7 switches on or off, providing unprecedented insight into its role in cells.

The study also revealed that:

CDK7 plays a role in multiple stages of transcription (decoding the genome), shaping what is known as "transcriptional splicing"--in which unneeded parts of the transcribed genome are pruned away to leave only those necessary for the cellular task at hand. Notably, errors in splicing have been linked to myriad diseases, including blood cancers.

CDK7 serves as a "master regulator" of other key enzymes, turning them on to further drive transcriptional programs. Defects in the execution of such programs have been linked to cognitive diseases, including Alzheimer's disease and rare developmental disorders, including head and facial deformities.

The function of CDK7 is controlled by the company it keeps. When attached to a larger 10-protein complex, known as TFIIH, it is largely inactive. But when it breaks off on its own, its activity ramps way up.

Phase 1 trials are currently underway administering the latest version of CDK7 inhibitors to drug-resistant breast, colorectal, lung, ovarian and pancreatic cancer patients.

The findings of the new study suggest such drugs hold promise, Taatjes said.

"In biology, it is widely recognized that cells will compensate by activating other enzymes if one specific enzyme is inhibited," he said, explaining the mechanism behind drug resistance. "Our results suggest that CDK7 inhibitors could have distinct therapeutic advantages, given that they would not only block CDK7, but would impact the function of other enzymes."

The research could also lead to next-generation therapeutics, which--instead of silencing the protein completely--would target it only in its liberated, most active phase. This could result in more selective inhibitors that would be less damaging to healthy cells, with fewer side effects.

And because of its many roles in shaping how human cells develop and function, other applications may be possible.

"Cancer is an obvious application but it is by no means the only one," Taatjes said.

The ability of SARS-CoV-2 to infect cells depends on interactions between the viral spike protein and the human cell surface protein ACE2. To enable the virus to hook onto the cell surface, the spike protein binds ACE2 using three finger-like protrusions, called the receptor binding domains (RBDs). Blocking the RBDs therefore has the potential to stop the virus from entering human cells. This can be done using antibodies.

Nanobodies, small antibodies found in camels and llamas, are promising as tools against viruses due to their high stability and small size. Although obtaining them from animals is time consuming, technological advances now allow for rapid selection of synthetic nanobodies, called sybodies. A technology platform to select sybodies from large synthetic libraries was recently developed in the lab of Markus Seeger at the University of Zurich, and made available for this study.

In search of the best sybody against SARS-CoV-2

EMBL Hamburg's Christian Löw group searched through the existing libraries to find sybodies that could block SARS-CoV-2 from infecting human cells. First, they used the viral spike protein's RBDs as bait to select those sybodies that bind to them. Next, they tested the selected sybodies according to their stability, effectiveness, and the precision of binding. Among the best binders, one called sybody 23 turned out to be particularly effective in blocking the RBDs.

To learn exactly how sybody 23 interacts with the viral RBDs, researchers in the group of Dmitri Svergun at EMBL Hamburg analysed the binding of sybody 23 to the RBDs by small-angle X-ray scattering. In addition, Martin Hällberg at CSSB and Karolinska Institutet used cryo-EM to determine the structure of the full SARS-CoV-2 spike bound to sybody 23. The RBDs switch between two positions: in the 'up' position the RBDs poke out, ready to bind ACE2; in the 'down' position they are furled to hide from the human immune system. The molecular structures revealed that sybody 23 binds RBDs in both 'up' and 'down' positions, and blocks the areas where ACE2 would normally bind. This ability to block RBDs regardless of their position might explain why sybody 23 is so effective.

Finally, to test if sybody 23 can neutralise a virus, the group of Ben Murrell at Karolinska Institutet used a different virus, called a lentivirus, modified such that it carried SARS-CoV-2's spike protein on its surface. They observed that sybody 23 successfully disabled the modified virus in vitro. Additional tests will be necessary to confirm whether this sybody could stop SARS-CoV-2 infection in the human body.

Scientific collaboration during lockdown

"The collaborative spirit has been enormous in these times, and everybody was motivated to contribute," says Christian Löw, one of the lead scientists in the study. The researchers started the project as soon as they received approval from EMBL leadership to reopen their laboratories during the COVID-19 lockdown. They managed to select the candidate sybodies and perform the analyses in just a few weeks.

"Getting the results so quickly was only possible because the methodologies we used had already been established for other research projects unrelated to SARS-CoV-2. Developing these tools would have taken significantly more time and resources," says Löw.

The results of this project hold out the promise of a potential way to treat COVID-19. In future work, the scientists will perform further analyses to confirm whether sybody 23 could be an effective COVID-19 treatment.

Nara, Japan - Mutants that reveal the secrets of how plants attack? No, it's not a scene from a science fiction movie, but you could be forgiven for thinking that. Instead, it's a scene from real life:

Researchers at Nara Institute of Science and Technology in Japan report in a new study in Science Advances that parasitic plants use the plant hormone ethylene as a signal to invade the roots of host plants.

To develop a successful parasitic relationship, parasitic plants form a specialized structure, the haustorium which attaches to and invades the host plant. The formation of haustoria is regulated by signal molecules derived from the host plant and allows the parasitic plant to absorb water, nutrients, and small materials from the host plant.

"To understand the genetic programs for haustorium development, we identified mutants that displayed haustorial defects on host invasion," says lead author of the study Songkui Cui. "Genome sequencing showed that these mutants have defective ethylene signaling, and it turned out that ethylene signaling genes are crucial for the parasitic plant to infect its host plant."

Ethylene is a gaseous plant hormone that is involved in fruit ripening, aging of leaves, and the formation of root nodules. Ethylene is also widely involved in plant interactions with viruses and numerous organisms, such as insects and bacteria, lending either resistance or susceptibility to plants depending on the types of pathogens.

"Our results indicate that ethylene mediates host recognition in parasitic plants for host invasion," explains project leader Satoko Yoshida. "This is the first time that the mediation of host invasion by parasitic plant genes has been identified via forward genetics. Our findings offer a new understanding of how a parasitic plant uses the ethylene molecule to tweak haustorium development and host invasion."

Forward genetics is used to identify genes, or sets of genes, that produce a particular characteristic in an organism. The model species used in this study is from a family of parasitic plants that includes destructive weeds. But the molecular basis for their parasitism has been largely unexplored until now.

"Our results suggest that parasitic plants have taken over ethylene signaling for parasitism at multiple stages of their life cycle, such as germination, haustorium growth termination, and host invasion. This knowledge could provide new ways to use ethylene and ethylene inhibitors to control a broader range of parasitic weeds, including those that don't rely entirely on hosts to complete their life cycle, by manipulating haustorial function," says Cui.