Culture

They look like microscopic bottle brushes: Polymers with a backbone and tufts of side arms. This molecular design gives them unusual abilities: For example, they can bind active agents and release them again when the temperature changes. With the help of neutrons, a research team from the Technical University of Munich (TUM) has now succeeded to unveil the changes in the internal structure in course of the process.

"The structure of the bottle-brush polymers, which are only nanometers in size, cannot be investigated using classical optical methods: It can be seen that an aqueous solution containing these polymers becomes turbid at a certain temperature. But why this is the case, and how the backbone and the side arms stretch out into in the water or contract, has not yet been clarified," reports Prof. Christine Papadakis.

There is a simple reason why scientists would like to know more about the inner life of bottle-brush polymers: The fluffy molecules, which consist of different polymer chains and abruptly change their solubility in water at a certain temperature, are promising candidates for a variety of applications.

For example, they could be used as catalysts to accelerate chemical reactions, as molecular switches to open or close tiny valves, or as transport media for medical drugs - the molecular brushes could thus bring pharmaceuticals to a center of inflammation and, because the temperature is elevated there, release them directly at the site of action.

However, the basic prerequisite for using the brush molecules is that their behavior can be programmed: Theoretically, chemists can use a combination of water-soluble and water-insoluble building blocks to determine precisely at what temperature the polymers clump together and the liquid in which they were just dissolved becomes cloudy. "In practice, however, you have to know exactly how and under what conditions the structure of the polymers changes if you want to design smart brush molecules," explains Papadakis.

Neutrons reveal their molecular inner life

Together with her team in the Soft Matter Physics Group at the Technical University of Munich, she has now been able to visualize for the first time the changes that bottle-brush polymers with arms made of two different types of building blocks undergo when the temperature reaches the cloud point.

The scientists used neutron radiation from the Research Neutron Source Heinz Maier-Leibnitz (FRM II) on the campus Garching in a special instrument for small angle neutron scattering, which is operated by the Forschungszentrum Jülich

This method is particularly well suited for the investigation because neutrons are electrically neutral and therefore penetrate matter easily. There they are scattered by the atomic nuclei, which results in detailed information about the brush molecules. In combination with modern cryo electron microscopy, a detailed understanding of these molecules could be obtained.

When brushes clump together

The thermoresponsive brush molecules studied by Papadakis' team were synthesized by chemists from the National Hellenic Research Foundation in Greece and the Technische Universität Dresden, respectively.

In the first step, the samples were dissolved in water, then gradually heated up to the cloud point and irradiated with neutrons. A detector monitored the scattered radiation. From the scattering signal, the researchers were able to deduce the structural changes.

Depending on the structure of the polymers, water molecules split-off already before the cloud point was reached. At the cloud point itself, the molecular structure of the polymers collapsed. What remained were water-insoluble polymer coils, which formed loose or compact clusters depending on the residual water content.

"The results will help to develop bottle-brush polymers suitable for practical use," the physicist is convinced. "If you know exactly how polymers change at the cloud point, you can optimize their chemical structure for different applications."

In 2017 the term 'populism' made 'Word of the Year' according to The Cambridge Dictionary for its ubiquitous use across media headlines, in political speeches, campaigns, as well as across numerous academic publications and conferences.

According to new analysis from political scientists at the University of Bath however, the pervasive use of the term - also termed 'populist hype' - has had serious consequences in helping to legitimise certain kinds of politics, most notably the far right.

Writing in the journal Politics, the researchers from the Department of Politics, Languages & International Studies at Bath, analysed coverage from The Guardian's 'new populism' six-month series which ran from November 2018 and was designed to explore the term from different vantages.

In their critique they argue that 'populism' has fast-become a catch-all term attributed to an array of different phenomena and political standpoints - from a jazz musician and the film Sweet Home Alabama, to nationalism, protectionism of an economy and racism. The replacement of more accurate descriptions with 'populism', as well as the lack of care in it use, has muddied the waters as to what exactly we are talking about.

Most commonly though, 'populism' is attributed to far-right politics and this brings its own set of problems. The researchers warn that 'populism' has too often been reported on as a response to pent-up demands from 'the people', while ignoring the role of the media and politicians in its growth in popularity, both as a term and type of politics. Beyond the lack of clarity, it has also created or at least exaggerated links between 'the people' and the far right in particular, lending elitist and minoritarian politics a veneer of democratic legitimacy.

Focusing on The Guardian's new populism series, they suggest this was a missed opportunity to provide clarity on a term and type of politics which have shaped our current political age, but not always as we think it has. Highlighting one article from that series in particular - headline: 'Why is populism suddenly all the rage?'; sub-header: 'In 1998, about 300 Guardian articles mentioned populism. In 2016, 2,000 did. What happened? -they suggest the piece failed to acknowledge that to a large extent the massive upsurge in use was also a result of editorial choices.

Dr Aurelien Mondon of the University of Bath's Department of Politics, Languages & International Studies explains: "While Trump, Orban or Le Pen can indeed make use of populist discourse by pitting a constructed version of a 'people' against an 'elite', this is only a small part of their politics, which draw more from other larger ideologies and ideas such as ultra-conservatism, racism, or even fascism. While populism can help us understand the discursive nature of such politics, it does little on its own to explain their broader meaning and potential consequences."

Co-author Katy Brown also of the Department of Politics, Languages & International Studies, says: "This is by no means a problem unique to The Guardian, and there were many excellent contributions to its 'the new populism' series, but the problems we identify illustrate the importance of critical and careful use of terminology.

"The simplification and trivialisation of the term 'populist' has blurred meanings between phenomena such as nativism, nationalism, protectionism and racism which has helped to legitimate them by avoiding deeper scrutiny of so-called 'populist' policies."

Their critique is not reserved to the media. In their analysis they also highlight a huge upswing in the use of the term 'populism' throughout academic literature, some of it, they argue, without sufficient critical reflection or care taken over how it has been applied.

Dr Mondon adds: "Academics have a real role to play in helping people make sense of society and politics, and the work done on populism is key to this. However, it is essential that we reflect upon the impact our work has and how it is interpreted in wider circles. Hopefully, our article makes one such contribution."

Washington, DC--New work led by Carnegie's Matt Clement reveals the likely original locations of Saturn and Jupiter. These findings refine our understanding of the forces that determined our Solar System's unusual architecture, including the ejection of an additional planet between Saturn and Uranus, ensuring that only small, rocky planets, like Earth, formed inward of Jupiter.

In its youth, our Sun was surrounded by a rotating disk of gas and dust from which the planets were born. The orbits of early formed planets were thought to be initially close-packed and circular, but gravitational interactions between the larger objects perturbed the arrangement and caused the baby giant planets to rapidly reshuffle, creating the configuration we see today.

"We now know that there are thousands of planetary systems in our Milky Way galaxy alone," Clement said. "But it turns out that the arrangement of planets in our own Solar System is highly unusual, so we are using models to reverse engineer and replicate its formative processes. This is a bit like trying to figure out what happened in a car crash after the fact--how fast were the cars going, in what directions, and so on."

Clement and his co-authors--Carnegie's John Chambers, Sean Raymond of the University of Bordeaux, Nathan Kaib of University of Oklahoma, Rogerio Deienno of the Southwest Research Institute, and André Izidoro of Rice University--conducted 6,000 simulations of our Solar System's evolution, revealing an unexpected detail about Jupiter and Saturn's original relationship.

Jupiter in its infancy was thought to orbit the Sun three times for every two orbits that Saturn completed. But this arrangement is not able to satisfactorily explain the configuration of the giant planets that we see today. The team's models showed that a ratio of two Jupiter orbits to one Saturnian orbit more consistently produced results that look like our familiar planetary architecture.

"This indicates that while our Solar System is a bit of an oddball, it wasn't always the case," explained Clement, who is presenting the team's work at the American Astronomical Society's Division for Planetary Sciences virtual meeting today. "What's more, now that we've established the effectiveness of this model, we can use it to help us look at the formation of the terrestrial planets, including our own, and to perhaps inform our ability to look for similar systems elsewhere that could have the potential to host life."

The model also showed that the positions of Uranus and Neptune were shaped by the mass of the Kuiper belt--an icy region on the Solar System's edges composed of dwarf planets and planetoids of which Pluto is the largest member--and by an ice giant planet that was kicked out in the Solar System's infancy.

COLUMBUS, Ohio - As COVID-19 cases begin climbing again in the United States, the possibility arises of a grim moral dilemma: Which patients should be prioritized if medical resources are scarce?

Researchers from the United States and China asked more than 5,000 people from 11 countries how they would make one version of that ethical decision. Study participants considered 15 possible scenarios, choosing which of two COVID-19 patients should get access to a ventilator that could save their life.

The two patients they had to choose between differed on 10 characteristics, including age, gender, probability of survival and criminal history.

Results showed that people worldwide gave two characteristics the most weight when they made their decision: age and probability of survival.

Those two characteristics explained about 50 percent of their decisions, results showed. The other eight characteristics combined explained the other 50 percent.

"People seemed to want to maximize total benefits to society by choosing those who would live longest as a result of the treatment, either because of their younger age or because of overall probability of survival," said Yunhui Huang, co-author of the study and assistant professor of marketing at The Ohio State University's Fisher College of Business.

"It's a very utilitarian way of deciding."

But there were some differences in how people decided that depended on the culture of their country, the number of cases where they lived, and whether they felt personally threatened by the disease, the study showed.

Huang conducted the study with Liyin Jin and Yongheng Liang of Fudan University in Shanghai and Qiang Zhang of the Chinese University of Hong Kong in Shenzhen. The study was published online recently in the Journal of the Association for Consumer Research.

The 5,175 participants came from 11 countries that at the time of the data collection (April 8-18, 2020) covered about 49 percent of the world's population and 69 percent of confirmed COVID-19 cases. China, the United States, Brazil, the United Kingdom, Australia and South Korea were among them.

All people participated online. In the 15 scenarios, the participants were presented with two COVID-19 patients who both needed a ventilator to survive when only one was available. They were asked which patient should be given the ventilator. They then completed a survey that collected demographic information and asked how much they felt COVID-19 affected their own life.

Both patients in the scenarios were described based on 10 characteristics: age, gender, probability of survival, socioeconomic status, criminal record, the number of people who the patient has infected, family members who have also been infected, the expected number of days that this patient needs to be on the ventilators, the costs paid by public finance and nationality.

"Other than age and probability of survival, the other eight were given considerably lower weight in our sample, and their weights did not differ significantly from one another," said Huang.

Still, the findings showed that people generally preferred prioritizing people who shared their own nationality, those who had never committed a crime, and those who were likely to incur lower costs, would need fewer days on the ventilator and had infected fewer people.

The researchers found differences in the responses of people from collectivist cultures, which emphasize the needs and goals of the group, versus individualistic cultures.

In collectivist cultures like China, which emphasize respect for the elderly, there was a weaker preference for saving young versus old patients. They also prioritized people with the same nationality and those without a criminal record.

Individualistic cultures, like the United States, attached greater importance on the patient's probability of survival when deciding who got the ventilator.

There were also differences in responses depending on the attitude of the culture toward power inequalities in society. Study participants from countries like Korea, where inequality among people is more accepted, put more emphasis on criminal records in their decisions.

"Research has shown that cultures that accept a higher degree of inequality also prefer a more structured world, so it makes sense that they would not prioritize patients who disrupt that stability," Huang said.

Cultures that find inequality among people less acceptable attached even greater importance to survival probability, possibly because that attribute is not related to social class and status, she said.

Elements of the COVID-19 pandemic itself affected people's moral choices, the study found. People in areas with more COVID-19 cases were even more likely to favor the young. That is consistent with previous findings that have found that perceived loss of control, which is likely common among people during a pandemic, is linked to more utility-based moral preferences.

But people who said they felt more personally impacted by COVID-19 made a different calculation in their decisions: They put less emphasis on survival probability when deciding who should get the ventilator.

"One possible explanation is that people who feel personally threatened by COVID-19 may put more importance on their own personal characteristics when thinking about who should get a ventilator at the expense of survival probability," Huang said.

These findings about how the pandemic itself affected people's choices have important implications.

"During the course of the pandemic, people's moral choices might change as they feel more or less threatened by what is going on around them," Huang said.

The research is not intended to guide decision-making by doctors or policymakers, Huang said. But it is important to know how the public feels about these ethical issues.

For example, the findings showed that factors like criminal records and nationality, which presumably should not influence treatment decisions, sometimes affected people's choices.

"Doctors and policymakers need to know how the public thinks about these issues as they communicate about their policies involving these difficult decisions," Huang said.

LAWRENCE -- How likely you are to trust a self-driving car or advice from Siri?

A University of Kansas interdisciplinary team led by relationship psychologist Omri Gillath has published a new paper in the journal Computers in Human Behavior showing people's trust in artificial intelligence (AI) is tied to their relationship or attachment style.

The research indicates for the first time that people who are anxious about their relationships with humans tend to have less trust in AI as well. Importantly, the research also suggests trust in artificial intelligence can be increased by reminding people of their secure relationships with other humans.

Grand View Research estimated the global artificial-intelligence market at $39.9 billion in 2019, projected to expand at a compound annual growth rate of 42.2% from 2020 to 2027. However, lack of trust remains a key obstacle to adopting new artificial intelligence technologies.

The new research by Gillath and colleagues suggests new ways to boost trust in artificial intelligence.

In three studies, attachment style, thought to play a central role in romantic and parent-child relationships, was shown also to affect people's trust in artificial intelligence. Some of the research's key findings:

People's attachment anxiety predicts less trust in artificial intelligence.

Enhancing attachment anxiety reduced trust in artificial intelligence.

Conversely, enhancing attachment security increases trust in artificial intelligence.

These effects are unique to attachment security and were not found with exposure to positive affect cues.

"Most research on trust in artificial intelligence focuses on cognitive ways to boost trust. Here we took a different approach by focusing on a 'relational affective' route to boost trust, seeing AI as a partner or a team member rather than a device," said Gillath, professor of psychology at KU.

"Finding associations between one's attachment style -- an individual difference representing the way people feel, think and behave in close relationships -- and her trust in AI paves the way to new understandings and potentially new interventions to induce trust."

The research team includes investigators from a wide array of disciplines, including psychology, engineering, business and medicine. This interdisciplinary approach provides a new perspective on artificial intelligence, trust and associations with relational and affective factors.

"The findings show you can predict and increase people's trust levels in non-humans based on their early relationships with humans," Gillath said. "This has the potential to improve adoption of new technologies and the integration of AI in the workplace."

We may wish some memories could last a lifetime, but many physical and emotional factors can negatively impact our ability to retain information throughout life.

A new study published in the journal Psychological Science found that people who feel enthusiastic and cheerful--what psychologists call "positive affect"--are less likely to experience memory decline as they age. This result adds to a growing body of research on positive affect's role in healthy aging.

A team of researchers analyzed data from 991 middle-aged and older U.S. adults who participated in a national study conducted at three time periods: between 1995 and 1996, 2004 and 2006, and 2013 and 2014.

In each assessment, participants reported on a range of positive emotions they had experienced during the past 30 days. In the final two assessments, participants also completed tests of memory performance. These tests consisted of recalling words immediately after their presentation and again 15 minutes later.

The researchers examined the association between positive affect and memory decline, accounting for age, gender, education, depression, negative affect, and extraversion.

"Our findings showed that memory declined with age," said Claudia Haase, an associate professor at Northwestern University and senior author on the paper. "However, individuals with higher levels of positive affect had a less steep memory decline over the course of almost a decade," added Emily Hittner, a PhD graduate of Northwestern University and the paper's lead author.

Areas of future research might address the pathways that could connect positive affect and memory, such as physical health or social relationships.

Zooplankton can grow faster and produce more offspring when exposed to a substance that affects human happiness.

"These substances are antidepressants, so-called 'happy pills,' that are often used in the treatment of smoking cessation and depression. Our wastewater is one pathway for the substances to end up in nature," says Professor Sigurd Einum at the Norwegian University of Science and Technology's (NTNU) Centre for Biodiversity Dynamics (CBD) in the Department of Biology.

A research group at NTNU is studying how different substances affect animals. Einum and Professor Veerle Jaspers from the same department are leading the group. PhD candidate Semona Issa is the first author of their recently published article. She is also affiliated with the Centre for Biodiversity Dynamics.

The researchers have investigated how changes in the level of the drug dopamine affect daphnia, a small genus of water fleas. Water fleas are small zooplankton that are found in large numbers in many kinds of water. They are important for controlling the growth of algae and bacteria, and also as prey for a number of species.

There are over 400 species of water fleas. The group studied the Daphnia magna species, which is common in freshwater in large parts of the world.

"Dopamine is a neurotransmitter that is produced naturally in the body, and which raises or lowers the activity in various nerve cells. Among other things, dopamine can trigger a feeling of happiness," says Einum.

The release of drug residues or substances that affect dopamine levels in the body occur all the time, especially in wastewater. In Norway alone, doctors prescribe more than 100 million doses of antidepressants a year.

The researchers measured the effect of higher concentrations of both dopamine and the drug bupropion in water fleas. Bupropion is used to reduce depression and to help people quit smoking. The drug affects the concentration of dopamine in human cells.

"We're finding that this substance also affects various characteristics of water fleas, like growth rate and age at sexual maturation," says Einum.

The effect was most evident when little food was to be had in the surroundings.

Apparently, bupropion causes water fleas to grow and produce offspring faster.

"A faster life cycle is usually a sign of stress," says Issa. "But we don't know if this is a short-term effect."

"Water fleas that are exposed to higher dopamine levels could undergo behavioural changes that make them more vulnerable to being eaten, for example, but we haven't tested that yet," Einum says.

"Faster growth due to increased dopamine levels also reduces the amount of energy that can be used for immune function. It could make the water fleas more vulnerable to parasites and diseases," says Issa.

We don't yet know for sure that higher dopamine levels are any advantage over time, nor do we know why water fleas do not naturally produce higher levels of dopamine.

It could be that increased production of dopamine can also increase so-called oxidative stress. This can cause harmful substances to accumulate when the cell releases energy. Oxidation of dopamine occurs in the nerve cells where dopamine is produced. Then reactive oxygen compounds are formed that damage the cells.

As the country enters the final days of a marathon and polarizing election season, politicians' faces are everywhere. And that trend is not likely going anywhere, especially in the realm of social media.

A University of Georgia researcher used computer vision to analyze thousands of images from over 100 Instagram accounts of United States politicians and discovered posts that showed politicians' faces in nonpolitical settings increased audience engagement over traditional posts such as politicians in professional or political settings.

"Faces are a very important vehicle to extracting emotions," said Yilang Peng, an assistant professor in the UGA College of Family and Consumer Sciences. "In general, people are paying attention to posts that feature faces, and especially faces of people they recognize."

Using computer vision methods, Peng analyzed over 59,000 images published on Instagram of 159 U.S. politicians sampled in fall 2018, including presidential candidates, governors, senators and Cabinet members.

"Computer vision is an emerging field that looks at how we can train computers to imitate human vision, like detecting objects," Peng said.

The technique has been applied to facial recognition software, self-driving cars and even in medical imaging, whereby a computer can extract and identify common features from thousands or millions of images.

Using this method, visual messages can be described both in terms of content as well as aesthetic appeal, including brightness, blur, color, composition and even facial expressions, Peng said.

Peng identified four broad categories to classify the setting of the politicians' images:

professional/political setting, such as press conferences, offices, rallies and protests;

text/illustration, such as graphics and test-based messages;

personal setting, showing individuals in private or nonpolitical settings such as restaurants, homes or gyms;

and architecture/landscape, featuring views of buildings or landscapes, often without people.

Roughly 60 percent of the posts analyzed fell into the professional/political setting category.

"These kinds of posts are generally not that successful in terms of attracting comments or likes," Peng said.

On average, images in the personal setting category received about 20 percent more likes on Instagram compared to the professional setting and text/illustration categories.

Images with only the politician's face, as opposed to the politician with other people or images without faces, also attracted more likes and comments.

Personalization strategies, such as posts showing the politician at the local soccer field or at home with a pet, seemed to help drive interaction, Peng said.

"In summary, faces drove audience engagement," Peng said.

Peng said computer vision can have a variety of applications for future political campaigns, including analysis of political videos on social media and other media effects beyond audience engagement.

Peng also published a study in 2018 that used computer vision to detect media bias in portrayals of President Donald Trump and Hillary Clinton.

"In the future you can look at how do these visual materials actually change people's perception of the candidate," Peng said.

Peng's study, "What makes politicians' Instagram posts popular? Analyzing social media strategies of candidates and office holders with computer vision," was published by The International Journal of Press/Politics.

A University of Massachusetts Amherst environmental health scientist has used an unprecedented objective approach to identify which molecular mechanisms in mammals are the most sensitive to chemical exposures.

The study, published in the journal Chemosphere, advances the understanding of the interaction of chemicals, both pollutants and pharmaceuticals, on gene expression and the impact on human health.

"When we identified all the sensitive genes, we were very much surprised that almost every well-known molecular pathway is sensitive to chemicals to a certain degree," says lead author Alexander Suvorov, associate professor in the School of Public Health and Health Sciences.

The study identified genes and molecular pathways most sensitive to chemical exposures, including mechanisms involving aging, lipid metabolism and autoimmune disease. "These findings for the first time prove that current epidemics in metabolic and autoimmune disorders may be partly due to a very broad range of chemical exposures," Suvorov says.

To carry out their analysis, Suvorov and five students - undergraduates Victoria Salemme, Joseph McGaunn and Menna Teffera, and graduate students Anthony Poluyanoff and Saira Amir - extracted data on chemical-gene interactions from the Comparative Toxicogenomics Database, which includes human, rat and mouse genes.

The UMass Amherst team created a database of 591,084 chemical-gene interactions reported in 2,169 studies that used high-throughput gene expression analysis, which means they looked at multiple genes. Low-throughout analysis focuses only on a single gene.

"In the recent past, everything that we knew about molecular mechanisms affected by chemicals was coming from low-throughput experiments," Suvorov says, which led toxicology researchers to focus on those already identified genes, rather than looking for chemical sensitivity among a fuller range of genes.

"I wanted to find some approach that would tell us in a completely unbiased way which mechanisms are sensitive and which are not. I wondered if we were missing a significant toxic response just because no one ever looked for it," Suvorov says. "By overlaying many high-throughput studies, we can see changes in the expression of all genes all at once. And that is unbiased because we are not cherry-picking any particular molecular mechanisms."

The interactions analyzed encompassed 17,338 unique genes and 1,239 unique chemicals. The researchers split their database of chemicals into two parts - pharmaceutical chemicals, which are designed to target known molecular cascades; and other chemicals such as industrial, agricultural, cosmetics and pollutants. When the sensitivity of genes to pharmaceutical chemicals was compared to the sensitivity of genes to the other chemicals, the results were the same. "That proves that when analysis is done on really big numbers of chemicals, their composition does not matter," Suvorov says.

The study confirmed the molecular mechanisms that were previously recognized as being sensitive to chemical exposure, such as oxidative stress. The study's new findings that the pathways involving aging, lipid metabolism and autoimmune disease are also highly sensitive suggest that chemical exposures may have a role in such conditions as diabetes, fatty liver disease, lupus and rheumatoid arthritis, among others.

"This study represents a significant step forward in the use of genomic data for the improvement of public health policies and decisions," Suvorov says, "and the public health field will benefit from a future focus of toxicological research on these identified sensitive mechanisms."

The coronavirus doesn't spread uniformly through a community.

But in the world of disease modeling, many projections take a high-level approach to a geographic area, like a county or state, and forecast based on a general idea that a virus will take root and spread at an equal rate until it reaches its peak of infection.

A research team led by UC Irvine and the University of Washington has created a new model of coronavirus diffusion through a community. This approach, published Sept. 10 in the Proceedings of the National Academy of Sciences, factors in network exposure -- whom one interacts with -- and demographics to simulate at a more detailed level both where and how quickly the coronavirus could spread through Seattle and 18 other major cities.

The team used U.S. Census Bureau tract demographics, simulation techniques and COVID-19 case data from spring 2020 to estimate a range of days for the virus to spread within a given city.

The result: Some neighborhoods peak sooner than others. And in every city, the virus sticks around far longer than some might expect.

"The most basic takeaway from this research is risk. People are at risk longer than they think, the virus will last longer than expected, and the point at which you think you don't need to be vigilant means that it just hasn't happened to you yet," said co-author Zack Almquist, an assistant professor of sociology at the UW.

Almquist and the team took on their study with two basic premises: Account for the social and geographic connections within a tract that could affect the course of the virus; and assume no vaccine or other major intervention alters its path. Then, based on actual COVID-19 and demographic data, project a likely scenario for spread over time.

Take Seattle. The study's map of the city outlines each census tract and provides a color-coded range of days each tract could take to reach peak infection before the virus goes into a low remission. The overall range is vast, from neighborhoods with the fastest peak -- 83 days -- to those that take more than 1,000. That's more than three years, assuming there is no significant intervention to stem the spread.

Denser neighborhoods in Seattle, such as Capitol Hill or the University District, reach peak infection rate earlier. But simulations predict that even nearby neighborhoods won't reach peak infection until weeks or even years later. These models predict more "burst-like" behavior of the virus' spread than standard models -- with short, sudden episodes of infection across the city, Almquist said.

In the study's model of Washington, D.C., census tracts also appear to reach peak infection rates at different times. Again, denser areas tend to peak sooner. But the network connections can cause "bursty" peak infection days, with some areas seeing early peak infections and others seeing it much later based on the neighborhoods' relative connections with each other, Almquist said.

Projecting the path of the virus can help estimate the impact on local hospitals. Researchers predicted this in several ways, such as modeling the number of cases per hospital over time and the number of days a hospital is at peak capacity.

The model of projected hospital cases shows how the geographic variations in the timing in peak COVID-19 infections could affect hospitals in different areas. Without outside intervention, some hospitals would remain at capacity for years, especially those farthest from major population centers.

These types of models are important because they provide a more detailed and nuanced prediction of an unknown like the novel coronavirus, said Almquist. Gauging how the virus might spread throughout a city and strain its hospitals can help local officials and health care providers plan for many scenarios. And while this study assumes no major interventions will rein in the virus, it's reasonable to believe the virus will linger to some degree, even with solutions such as a vaccine, according to Almquist.

"If you project these models for what it means over the country, we might expect to see some areas, such as rural populations, not see infection for months or even years before their peak infection occurs," Almquist said. "These projections, as well as others, are beginning to suggest that it could take years for the spread of COVID-19 to reach saturation in the population, and even if it does so it is likely to become endemic without a vaccine."

Researchers based in Brazil and the United States have completed the first-ever mapping exercise to profile the toxins produced by tube-dwelling anemones, or cerianthids, a family of marine animals belonging to the same phylum (Cnidaria) as sea anemones, jellyfish and corals. The analysis revealed that the toxins that can act on the nervous system, cardiovascular system, and cell walls, among other functions, paving the way to the discovery of novel medications.

“Tube anemones and sea anemones were assigned to the same family for a long time, but since 2014 our group has shown that aside from external anatomy they’re very different. They display distinct forms of behavior, lifecycle, and other traits. We assumed the toxins they produce must also be different,” said Sérgio Stampar, a professor in São Paulo State University’s School of Sciences and Letters (FCL-UNESP) at Assis, Brazil, and principal investigator for the study, which is published in the journal Marine Drugs.

The research was supported by FAPESP via funding for three projects (15/24408-4, 19/03552-0 and 17/50028-0), and was conducted in collaboration with scientists affiliated with the University of Kansas, the University of North Carolina at Charlotte and Florida Southern College.

The researchers took samples of the animals’ tentacles and extracted the RNA, which they then sequenced. They used bioinformatics software to classify most of what was transcribed, which they grouped into families of toxins. The analysis showed that 525 genes were associated with these substances.

The toxins belong to families also found in jellyfish, whose venoms burn humans and can even kill them. In addition, because anemones’ tentacles are part of their digestive system, the researchers expected to find similar compounds in both groups.

More than substances used in digestion, however, tube anemones produce neurotoxins and other substances that affect the bloodstream and destroy cell walls, as is typical of toxins used to kill prey and defend against predators.

“Curiously enough, there are no reports of accidents involving these animals,” Stampar said. “I’ve handled them without gloves a few times and never been stung. We don’t yet know why humans aren’t affected by their toxic arsenal.”

Toxin diversity

Isarachnanthus nocturnus, a species found in Brazil, was found to secrete toxins similar to those of the Australian box jellyfish (Chironex fleckeri), whose venom can be lethal to humans and forms pores in cell walls. Stampar’s group recently sequenced the mitochondrial genome of I. nocturnus, the largest of any animal sequenced to date (read more at: agencia.fapesp.br/30727).

One of the possible explanations for the diversity of toxins in the species is that its larval stage, which lasts about four months, is much longer than those of other tube anemones, which drift for two or three days in the water column before settling on the seabed. Like corals, tube anemones and sea anemones spend most of their lives attached to the ocean floor. I. nocturnus may have developed more effective defenses than other species because it interacts a great deal with predators.

I. nocturnus and Ceriantheomorphe brasiliensis were the only Brazilian species included in the study, which also analyzed Pachycerianthus borealis, the Atlantic tube anemone, found in North America, and Pachycerianthus maua, the Banded tube anemone, found in the Red Sea, Gulf of Aden, and Tanzania.

Hemostatic and hemorrhagic toxins were the most diverse in all four species. One of the toxins found belongs to the same family as the toxins produced by venomous reptiles and resembles the venom of the Komodo dragon (Varanus komodoensis), which uses it to kill mammals larger than itself.

Toxins that alter circulation offer potential for use in drugs to treat cardiovascular problems. Captopril, widely used to treat high blood pressure, is derived from the venom of the jararaca pit viper (Bothrops jararaca), for example.

The researchers also found innate immunity toxins and protease inhibitors, which belong to the family used in antiretroviral drugs against HIV, for example.

“It’s important to bear in mind that marine organisms have been around far longer than humans and have a much more elaborate chemical arsenal,” Stampar said. “As they evolved, they refined their defenses against viruses, bacteria, and even tumors. Isolating these substances could be well worth our while.”

One of the toxins the researchers identified is being tested on breast cancer cells by Karina Alves de Toledo, another professor at FCL-UNESP. Preliminary results have been promising and suggest the compound can kill cancer cells without damaging healthy cells.

Prospecting marine biodiversity for molecules is now one of the most promising branches of biotechnology. The global market for such products is projected to be worth USD 6.4 billion in 2025. Redemsivir, an antiviral drug used against Ebola and recently approved to treat COVID-19 patients in the United States, for example, is made from a substance found in sea sponges; a complete course of treatment can cost between USD 2,000 and USD 3,000 in the US.

Four new species described

In another study, reported in an article published in Records of the Australian Museum, Stampar and collaborators based in Australia and New Zealand described three new species of tube anemones found in the region and a fourth found in Antarctica. The latter, Pachycerianthus antarcticus, is the southernmost species known to science. This distinction previously pertained to a tube anemone that is native to Argentina and has also been described by Stampar’s group.

The Australian species Ceriantheopsis microbotanica is one of the smallest described to date. It is about 5 cm long, compared with 30-40 cm for the rest. It is native to the shallow waters of Botany Bay in Sydney.

“The material resulted from a dredging operation to extend the airport and had been stored in the museum for several years,” Stampar said. “I thought the first specimens I analyzed must be juveniles but realized they were adults when I examined their sexual structures. This may be an adaptation to the uninvitingly dark water.”

Stampar conducted the study while working as a visiting researcher at the Australian Museum on a project funded by FAPESP. Later a New Zealander contacted him to request help with descriptions of two local species. One, Pachycerianthus fiordlandensis, is common enough to be photographed frequently by divers yet had not been described by scientists. The other, Ceriantheopsis zealandiaensis, was described on the basis of two specimens collected in New Zealander region of Fiordland. There are currently 57 species of tube anemone.

An international team of researchers that includes a Texas A&M University professor has studied the lineage of dogs and found that there were at least five different types of dogs as far back as 11,000 years ago.

Anna Linderholm, director of the BiG (bioarchaeology and genomics) Laboratory and an archaeologist at Texas A&M, and a team of worldwide researchers have had their work published in the current issue of Science magazine.

The team studied dog DNA dating as far back as 11,000 years ago, immediately following the last Ice Age. By sequencing the DNA of 27 dogs found in Europe, the Near East and Siberia, team members discovered five different types of dogs with distinct genetic ancestries dating from before any other animal had been domesticated.

Linderholm was part of the genomics team that extracted DNA from skeletal material to see how dogs evolved from thousands of years ago when all humans were still hunters and gatherers.

"We examined dogs from across the old world, and they represent a period that stretches almost 11,000 years back in time," she said.

"The dog samples have been gathered from museums, and other collections from across the world and by several members of this team. Since we don't know when and where dogs were domesticated, we have collected most of the known dogs from the old world, going back as far in time as possible and using dog DNA that has been best preserved."

Linderhom said that samples were taken from collected dog remains, such as a tooth or a piece of bone. From the samples, the DNA was sequenced, enabling the team to read the genetic code that explains the origins of each dog and how it might have been related to modern-day dogs.

"By looking at a dog's genome, we can look at that dog's history, look at his parents and their parents and so on," she said. "It is much like today when people do an ancestry test for humans, trying to find out where they come from."

Linderholm added that dogs look similar genetically, meaning they share a more recent common ancestor.

"The five linages from over 11,000 years ago is more diversity than we have been able to identify before," she said. "Having said this, all dogs seem to have originated from one ancient wolf population, a wolf population that has since disappeared. We have no connection with our modern-day wolf populations with our first domesticated dogs."

She added that the human-dog bond can now be seen a bit more clearly. When humans moved, they almost always took their dogs with them.

"We see this happening when farming was introduced into Europe and other areas such as the Steppes in Asia," she said. "We note a clear link between the movement of people and the introduction of a new type of dogs. This is new, and we also don't see this pattern repeating itself when we have another large population movement. So humans were not always consistent in their actions at this time, but we do see a much greater connection between humans and their dogs, more so than any other animal."

Oct. 29, 2020-- A new study published online in the Annals of the American Thoracic Society examines whether the amount of RNA, or genomic load, of SARS-CoV-2 detected in swab tests of patients being admitted to the hospital with viral pneumonia is associated with more severe COVID-19. SARS-CoV-2 is the virus that causes COVID-19. Previous studies on this question have had conflicting results.

In "Association of SARS-CoV-2 Genomic Load With COVID-19 Patient Outcomes," Ioannis M. Zacharioudakis, MD, infectious disease specialist in the Department of Medicine at the New York University Grossman School of Medicine, and co-authors looked at the medical records of 314 patients who came to the NYU Langone Health emergency room between March 31 and April 10, 2020, diagnosed with COVID-19 on a molecular diagnostic (RT-PCR) test who also had viral pneumonia serious enough to require hospitalization. This research was conducted as a retrospective cohort study--one that follows former patients who had common characteristics.

"We demonstrated that for patients admitted to the hospital with COVID-19 pneumonia, SARS-CoV-2 load, as reflected by the cycle threshold (Ct) value of the PCR, should be looked at as a predictor of adverse outcomes," said Dr. Zacharioudakis. "High viral load was shown to be a predictor of poor outcomes above and beyond age, other medical problems and severity of illness on presentation, indicating that it can be used to risk-stratify, or triage, patients."

Real-time reverse transcriptase-polymerase chain reaction (RT-PCR) tests for SARS-CoV-2 are the most accurate class of COVID tests available today, and they can sample and analyze the greatest amount of genetic material, even at presymptomatic stages of the disease. In this study, respiratory samples that were analyzed by RT-PCR technology were gathered from patients using nasopharyngeal swabs, the long swabs that are widely used in health care settings as well as at public testing sites.

A cycle threshold value is one of the results that the PCR technique gives and can be used as a surrogate of the amount of virus that is detected on nasopharyngeal swabs. Since Ct value is obtained on most commercial RT-PCR testing platforms, it can prove a readily available tool to the provider to help risk-stratify and triage patients admitted to the hospital with COVID-19 pneumonia.

The researchers determined that study endpoints would include whether a patient required mechanical ventilation or extracorporeal membrane oxygenation (ECMO), and whether the patient died while in the hospital or was discharged to hospice. Statistical calculations were done to determine how frequently the endpoints were reached by patients who had high versus low viral load after adjusting for the patients' co-occurring conditions (comorbidities) using the Charlson Comorbidity Index and how severe the pneumonia was at the time of presentation, as shown in the Pneumonia Severity Index.

"We know that the virus multiplies rapidly in the asymptomatic and early symptomatic phases of COVID-19," Dr. Zacharioudakis stated. "Our study is in keeping with this conclusion, as indicated by our finding of higher viral load in patients who presented earlier in the disease."

He added: "The study also found that patients who had multiple comorbid conditions, such as heart disease, diabetes and cancer--or who were immunocompromised due to solid organ transplant--were more likely to have a higher SARS-CoV-2 load at hospital admission and as a result an increased risk for poor outcomes."

An important characteristic of this study was that it focused on patients who required admission to the hospital for COVID-19 pneumonia, a group who are at high risk for serious illness or death. The fact that the association of the high viral load with poor patient outcomes remained after taking into account the patients' underlying conditions, how long they were sick before coming to the hospital and how sick they were at the time they presented adds valuable evidence that demonstrates the ability of SARS-CoV-2 viral load to predict COVID outcomes.

The authors note that, among patients with a severe clinical presentation, those with a high SARS-CoV-2 viral load were almost twice as likely to get intubated or die.

Dr. Zacharioudakis added, "Our study provides a justification for using patients' SARS-CoV-2 load at the time of hospital admission to assess their risk of adverse outcomes. In an era when the availability of antiviral medications proven effective against COVID might be limited and the capacity for intensive monitoring is finite, it is of utmost importance to be able to prioritize the patients who will benefit the most from early treatment or a higher level of care. Further studies are needed to evaluate whether a decrease in viral load of patients hospitalized with COVID-19, who may or may not be treated with antiviral medications such as Remdesivir, correlate with an improvement in clinical status."

The plant pathogenic nematode Heterodera schachtii infects more than 200 different plants, including sugar beets, and causes significant economic losses. Over the past 50 years, the primary management tool in California has been crop rotation. When the number of H. schachtii in a soil exceeds a threshold, growers are contractually required by the local sugar factory to plant crops that do not support the nematode's reproduction. This practice reduces the nematode population so that the next sugar beet crop can flourish.

In a recent study from plant pathologists at the University of California, Riverside, the authors examined a soil fungus that parasitizes the nematode's females and eggs. This fungus, Hyalorbilia aff. multiguttulata (formerly Dactylella oviparasitica), was originally shown to cause a long-term suppression of cyst nematode populations in a field at the University of California Riverside's Agricultural Operations. Other scientists have detected closely related fungal species in Arkansas and California that were able to parasitize and destroy different important nematodes, including the soybean cyst and root-knot nematodes.

In the current study, the authors showed that similar fungi inhabited sugar beet fields in California, suggesting that a group of naturally occurring fungi, given the right conditions, might be able to dramatically reduce nematode populations in one season. Borneman, Becker, and colleagues detected identical or closely related Hyalorbilia species in 21 of 25 field soils. More importantly, baiting with young female H. schachtii and its host Swiss chard led to an approximately 10,000-fold increase in the population densities of these fungi over one nematode generation. "This research could lead to more frequent planting of sugar beets," explained James Borneman. "When the population densities of both the nematode and the fungus are above their threshold values, our research suggests that planting sugar beets would lead to the development of an H. schachtii-suppressive soil by the time the sugar beets are harvested."

"Relatively little is known about the Hyalorbilia spp., yet they appear to occur worldwide as effective parasites of cyst nematodes," said Borneman. "Nematode-suppressive soils are fascinating examples of natural pathogen control. In this example, the key to defeating the enemy is fungus' ability to destroy the mothership (the female nematode) before it can release hundreds of eggs into the soil."

BOSTON - Nearly one-third of cancer patients who decide to undergo surgery for their condition may have second thoughts, and this decision conflict may lead to less favorable treatment outcomes in both the near- and long-term, according to a team of investigators at Massachusetts General Hospital (MGH) and Ariadne Labs, a joint center for health systems innovation at the Harvard T.H. Chan School of Public Health and Brigham and Women's Hospital (BWH).

In a pilot study to see whether a survey and sensor data collected from a smartphone app could help identify clinically significant decision conflict in patients scheduled to undergo cancer surgery, Nikhil Panda, MD, MPH, from MGH and colleagues found that 27 percent reported having a conflict about their decision.

"When we followed that group out to 90 days after surgery, and even after accounting for potential differences between the group that reported conflict before surgery and the group that didn't, the people who said they had conflict were less active overall," Panda said. "In surgery, we know that if people are more active, it's an independent predictor of having better functional outcomes over the long term."

The findings are reported in the journal Annals of Surgery.

Patients with cancers that can be treated by surgery often wrestle with issues such as their treatment goals (for example, the potential for cure or symptom relief) and their health-related quality of life following treatment.

Cancer specialists try their best to engage patients in decision making regarding their care, but as Panda and colleagues write, "the lack of scalable, generalizable, and patient-centered outcome measurement tools means that many patients face cancer treatment, including surgery, without an understanding of how the intervention will affect outcomes that matter the most to them."

That lack of understanding can lead to clinically significant decision conflict, which has been shown in previous studies to be associated with problems such as patients not following treatment plans, strained patient-provider relationships and poorer emotional and psychological health.

To get a better understanding of the effects of decision conflict on postoperative health, the investigators recruited patients who were scheduled for surgery within a week or so to treat cancers of the breast, skin, soft tissues, abdomen or thyroid/parathyroid, and who owned a smartphone running on the Apple iOS or Android operating systems.

The patients were asked to download a data-gathering application that delivered to their phones the Decision Conflict Scale, a certified tool for measuring clinically significant decision conflict. The app also used the phone's motion-sensing accelerometer to gather continual data about activity following surgery.

Of 85 patients who downloaded the app and completed the Decision Conflict Scale, 27 percent reported clinically significant decision conflict, and although this group did not differ in pre-operative physical activity from the patients who did not report decision conflict, Panda and colleagues found that at 30, 60, and 90 days after surgery the patients with decision conflict had significantly lower levels of physical activity.

"If we can find something that's easily modifiable to improve that outcome, that would be a good thing. Factors such as obesity and smoking are very difficult to modify in the short term, but we may be able to reduce conflict by better informed consent, using decision aids, or improving communication between patients and their surgeons. These are all low-hanging fruit," Panda said.