Culture

AMES, Iowa - The United States is suffering from several different simultaneous opioid epidemics, rather than just a single crisis, according to an academic study of deaths caused by drug overdoses.

David Peters, an associate professor of sociology at Iowa State University, co-authored the study, which appeared in the academic journal Rural Sociology. Peters and his co-authors conducted a county-level analysis of death certificates from across the country that noted opioid overdoses as the cause of death. The study found regional differences in the kind of opioids that cause the most overdose deaths, and these differences should lead to policymakers considering varying strategies to address the epidemics, Peters said.

"Our results show that it's more helpful to think of the problem as several epidemics occurring at the same time rather than just one," Peters said. "And they occur in different regions of the country, so there's no single policy response that's going to address all of these epidemics. There needs to be multiple sets of policies to address these distinct challenges."

Multiple epidemics

The study describes three different opioid epidemics in the United States, as well as a syndemic, or a single population experiencing more than one epidemic:

-- A prescription drug epidemic persists in rural southern states where access to opioids centers on local pharmacies. Overdose deaths linked to pharmaceuticals peaked nationwide in 2013 and have fallen in the years since. However, some rural counties continue to struggle with prescription drugs, according to the study.

-- A heroin epidemic has taken root in states out west and in the Midwest, especially in urban areas near major interstates that experience heavy drug trafficking. The study found overdose deaths related to heroin clustered along two major corridors, one linking El Paso to Denver and another linking Texas and Chicago. Peters said those findings correspond with known routes used by cartels smuggling heroin into the United States from Mexico.

-- An epidemic of synthetic opioids, such as fentanyl, has grown as a major concern in urban centers in the northeastern United States. Often these synthetic drugs are mixed with heroin or cocaine and made to resemble prescription medications. These counterfeit street mixes are highly potent and deadly.

-- A syndemic involving multiple simultaneous opioid epidemics exists in counties where the opioid crisis first erupted, particularly in mid-size cities in Kentucky, Ohio and West Virginia that have experienced steep job losses in manufacturing and mining.

Peters said roughly a quarter of all counties in the United States fall into one of the epidemic categories noted in the study.

PRINCETON, N.J.--People perceive a person's competence partly based on subtle economic cues emanating from the person's clothing, according to a study published in Nature Human Behaviour by Princeton University. These judgments are made in a matter of milliseconds, and are very hard to avoid.

In nine studies conducted by the researchers, people rated the competence of faces wearing different upper-body clothing. Clothing perceived as "richer" by an observer -- whether it was a T-shirt, sweater, or other top -- led to higher competence ratings of the person pictured than similar clothes judged as "poorer," the researchers found.

Given that competence is often associated with social status, the findings suggest that low-income individuals may face hurdles in relation to how others perceive their abilities --
simply from looking at their clothing.

"Poverty is a place rife with challenges. Instead of respect for the struggle, people living in poverty face a persistent disregard and disrespect by the rest of society," said study co-author Eldar Shafir, Class of 1987 Professor in Behavioral Science and Public Policy at Princeton's Woodrow Wilson School of Public and International Affairs. "We found that such disrespect -- clearly unfounded, since in these studies the identical face was seen as less competent when it appeared with poorer clothing -- can have its beginnings in the first tenth of a second of an encounter."

"Wealth inequality has worsened since the late 1980s in the United States. Now the gap between the top 1% and the middle class is over 1,000,000%, a mind-numbing figure," said lead author DongWon Oh, who worked on the study as a Ph.D. student at Princeton, and is now a postdoctoral fellow in New York University's Department of Psychology. "Other labs' work has shown people are sensitive to how rich or poor other individuals appear. Our work found that people are susceptible to these cues when judging others on meaningful traits, like competence, and that these cues are hard, if not impossible, to ignore."

Oh and Shafir, who is the inaugural director of Princeton's Kahneman-Treisman Center for Behavioral Science & Public Policy, conducted the study with Alexander Todorov, professor of psychology at Princeton.

The researchers began with images of 50 faces, each wearing clothes rated as "richer" or "poorer" by an independent group of judges who were asked, "How rich or poor does this person look?" Based on those ratings, the researchers selected 18 black and 18 white face-clothing pairs displaying the most prominent rich-poor differences. These were then used across the nine studies.

To make sure the clothes did not portray extreme wealth or poverty, the researchers asked a separate group of judges to describe the clothing seen in the images. The descriptions revealed very mild differences, and extremely positive or negative words were rare. The words "rich" or "poor," or their synonyms, occurred only once out of a total 4,725 words.

Participants were then presented with half of the faces wearing "richer" upper-body clothing, and the other half with "poorer" clothing. They were told that the researchers were interested in how people evaluate others' appearances, and were asked to rate the competence of the faces they saw, relying on their "gut feelings," on a scale of 1 (not at all) to 9 (extremely).

Participants saw the images for three different lengths of time, ranging from about one second to approximately 130 milliseconds, which is barely long enough to realize one saw a face, Shafir said. Remarkably, ratings remained consistent across all time durations.

In several of the studies that followed, the researchers made tweaks to the original design.

In some studies, they replaced all suits and ties with non-formal clothing. In others, they told participants there was no relationship between clothes and competence. In one study, they provided information about the persons' profession and income to minimize potential inferences from clothing. In another, they expanded the participant pool to nearly 200, and explicitly instructed participants to ignore the clothing.

Later, a new set of faces was used, and the participants were again advised to ignore the clothing. To further encourage participants to ignore the clothes, another study offered a monetary reward to those whose ratings were closest to ratings made by a group who saw the faces without clothes. In the final study, instead of asking for individual ratings, the researchers presented pairs of faces from the previous studies and asked participants to choose which person was more competent.

Regardless of these changes, the results remained consistent: Faces were judged as significantly more competent when the clothing was perceived as "richer." This judgment was made almost instantaneously and also when more time was provided. When warned that clothing had nothing to do with competence, or explicitly asked to ignore what the person in the photo was wearing, the biased competency judgments persisted.

Across studies, the researchers found that economic status -- captured by clothing cues -- influenced competency judgments. This persisted even when the faces were presented very briefly, when information was provided about a person's profession or income, when clothing was formal or informal, when participants were advised to ignore the clothing, when participants were warned there was no relationship between clothing and competency, and when they were offered a monetary incentive for making judgments independent of the clothing.

"To overcome a bias, one needs to not only be aware of it, but to have the time, attentional resources, and motivation to counteract the bias," the researchers wrote. "In our studies, we warned participants about the potential bias, presented them with varying lengths of exposure, gave them additional information about the targets, and offered financial incentives, all intended to alleviate the effect. But none of these interventions were effective."

An important concern for future psychological work is how to transcend first impressions, the researchers conclude.

"Knowing about a bias is often a good first step," Shafir said. "A potential, even if highly insufficient, interim solution may be to avoid exposure whenever possible. Just like teachers sometimes grade blindly so as to avoid favoring some students, interviewers and employers may want to take what measures they can, when they can, to evaluate people, say, on paper so as to circumvent indefensible yet hard to avoid competency judgments. Academic departments, for example, have long known that hiring without interviews can yield better scholars. It's also an excellent argument for school uniforms."

CORVALLIS, Ore. - Political affiliations, the presence of local environmental organizations and prior local media coverage of climate change play a role in how a community reacts to an extreme weather event, an article published today in Nature Climate Change concludes.

"Extreme weather events such as a catastrophic wildfire, a 500-year flood or a record-breaking heatwave may result in some local discussion and action around climate change, but not as much as might be expected and not in every community," said Hilary Boudet, the paper's lead author and an associate professor of public policy in Oregon State University's School of Public Policy in the College of Liberal Arts.

"In terms of making links to climate change, local reactions to an extreme weather event depend both on aspects of the event itself, but also on political leanings and resources within the community before the event took place."

Boudet's work is part of a growing body of research exploring the links between personal experience with an extreme weather event and social mobilization around climate change. The study was part of a project examining community reactions to extreme weather in the U.S.

The researchers sought to better understand how extreme weather events might influence local attitudes and actions related to climate change.

Researchers conducted 164 interviews with local residents and community leaders in 15 communities across the United States that had experienced extreme weather events that caused at least four fatalities between 2012 and 2015. They also analyzed media coverage to better understand what kinds of public discussions, actions and policies around climate change occurred in those communities.

Of the 15 communities, nine showed evidence of public discussion about the event's connection to climate change in the wake of the disaster.

"Although many of the extreme events we studied spurred significant emergency response from volunteers and donations for rescue and recovery efforts, we found these events sparked little mobilization around climate change," Boudet said. "Yet there was also a distinct difference between cases where community climate change discussion occurred and where it did not, allowing us to trace pathways to that discussion."

When there was some scientific certainty that the weather event was related to climate change, discussion about the connection was more likely to occur, particularly in communities that leaned Democratic or where residents were highly educated, Boudet said.

However, even in communities where climate change was discussed in relation to the weather event, it was often a marginal issue. Other more immediate concerns, such as emergency response management and economic recovery, generated far more discussion and subsequent action.

Some of those interviewed suggested that broaching the topic of climate change amid disaster recovery efforts could be interpreted as using a tragedy to advance a political agenda, Boudet said.

"Recent shifts in U.S. opinions on climate change suggest that it may become a more acceptable topic of conversation following an extreme weather event," Boudet said. "Yet our results indicate that it may take time for such discussions to take place, particularly in Republican-leaning communities."

While the work challenges the notion that a single extreme weather event will yield rapid local social mobilization around climate change, the researchers found that communities may still make important changes post-event to ensure more effective responses to future events.

Boudet and her team are currently examining local policy action post-event to understand how such action relates to local climate change discussion.

The rapid expansion of cities around the world is having an enormous impact on biodiversity. To gain a clearer picture of the situation, an international group of scientists, including Professor Andrew Gonzalez from McGill's Biology Department, surveyed over 600 studies on the impacts of urban growth on biodiversity. They published their findings today in Nature Sustainability.

"Our understanding of the rising impacts of cities is crucial for future biodiversity targets, but we must quickly fill existing gaps in our knowledge because they impede our ability to make new policy to manage the impacts of urban growth," says Gonzalez.

The research underlines what we know about the effects of urban expansion on natural habitats:

We are living in the fastest period of urban growth in human history. By 2030, more than 2 billion additional people are expected to be living in cities, a pace of urban growth that is the equivalent to building a city the size of New York City every six weeks.

290,000 square kilometers, (an area larger in size than the entire United Kingdom) of natural habitat are forecast to be converted to urban land uses by 2030.

The direct impacts of urban expansion on biodiversity will be most severe in the tropical coastal regions such as those in China, Brazil, and Nigeria where there is a high level of biodiversity.

But the research also suggests that scientists are not studying the impacts of urban growth in the right places. The authors find that more research is needed if we are to build a complete picture of how cities are impacting nature. Key aspects for future research include:

More research into the impacts of urban expansion in lower income countries in the southern hemisphere where loss of natural habitat is projected to be most severe, particularly in the tropical rain forests, such as those along the Brazilian coast, in West Africa and in Southeast Asia.

72% of studies of direct urban impacts on biodiversity are in high-income countries, while the natural habitat loss caused by urban expansion is projected to be most severe in lower-income countries.

Comparatively few studies (only 34%) have quantified the indirect impacts of urban growth on biodiversity.

The indirect impacts of urban expansion on biodiversity, such as the food and energy needed to maintain city residents stretch far beyond the city limits and are likely to have a much greater impact than the direct impacts of the city itself. For example, the amount of agricultural land required to feed the world's cities is 36 times greater in size than the urban areas themselves.

New Rochelle, NY, December 9, 2019--A new study developed and validated a tool for assessing children's overall addiction to digital devices. The study, which found that more than 12% of children ages 9-12 years were at risk of addiction to digital devices for uses including video gaming, social media, and texting, is published in Cyberpsychology, Behavior, and Social Networking, a peer-reviewed journal from Mary Ann Liebert, Inc., publishers. Click here to read the full-text article free on the Cyberpsychology, Behavior, and Social Networking website through January 9, 2019.

The article entitled "The Digital Addiction Scale for Children: Development and Validation" was coauthored by Nazir Hawi and Maya Samaha, Notre Dame University -Louaize (Mosbeh, Lebanon), and Mark Griffiths, Nottingham Trent University (UK). The researchers based the Digital Addiction Scale for Children (DASC) on the nine diagnostic criteria for addiction. They also mapped it onto six core addiction criteria: preoccupation, tolerance, withdrawal, mood modification, conflict, and relapse. They included three additional criteria: problems (with life necessities that could become uncontrollable due to digital addiction, such as sleep, discord with parents, or academic achievement); deception (how children lie to their parents about the amount of time and what they do on their digital devices); and displacement (parental feelings of disconnectedness from their children that result in compromising the family unit).

"Using validated scales, many pediatricians proactively screen their patients for problematic and risky internet use and internet gaming disorder to identify and address issues that may negatively affect child and adolescent health and wellbeing. The DASC may prove a useful assessment tool for clinicians to also consider," says Editor-in-Chief Brenda K. Wiederhold, PhD, MBA, BCB, BCN, Interactive Media Institute, San Diego, California and Virtual Reality Medical Institute, Brussels, Belgium.

The prevalence of cannabis, or marijuana, use in the United States increased from 2005 to 2017 among persons with and without depression and was approximately twice as common among those with depression in 2017. The findings, which are published in Addiction, come from a survey-based study of 728,691 persons aged 12 years or older.

"Perception of great risk associated with regular cannabis use was significantly lower among those with depression in 2017, compared with those without depression, and from 2005 to 2017 the perception of risk declined more rapidly among those with depression. At the same time, the rate of increase in cannabis use has increased more rapidly among those with depression," said corresponding author Renee Goodwin, PhD, MPH, of Columbia University and The City University of New York.

The prevalence of past 30-day cannabis use among those with depression who perceived no risk associated with regular cannabis use was much higher than that among those who perceived significant risk associated with use (38.6% versus 1.6%, respectively).

Certain groups appeared more vulnerable to use. For instance, nearly one third of young adults (29.7%) aged 18-25 with depression reported past 30-day use.

In 2017, the prevalence of past month cannabis use was 18.9% among those with depression and 8.7% among those without depression. Daily cannabis use was common among 6.7% of those with depression and among 2.9% of those without.

Viral and bacterial infections are not the only causes of inflammation of body tissue. It has been known for some time that certain fat molecules in our bloodstream can also trigger an inflammatory response. Patients with higher levels of these fats in their blood have a significantly greater chance of dying early from kidney damage or vascular disease. This causal link has now been clearly demonstrated by an international team of researchers led by Dr. Timo Speer of Saarland University.

The research team was able to show how these fat molecules interact with body cells and how they can mobilize the body's own immune system to damaging effect. The study's findings have now been published in the highly respected medical journal 'Nature Immunology'.

Doctors interested in ways to minimize the risk of cardiovascular disease have long had blood cholesterol levels in their sights. But other types of blood fats (also known as 'lipids') can also be damaging to health. 'Our work has involved studying a special group of lipids, the triglycerides. We've been able to show that when these naturally occurring fats are present at elevated concentrations they can alter our defence cells in such a way that the body reacts as if responding to a bacterial infection. This leads to inflammation, which, if it becomes chronic, can damage the kidneys or cause atherosclerosis - the narrowing of arteries due to a build up of deposits on the inner arterial wall. And atherosclerosis is one of the main causes of heart attacks and strokes,' explains Timo Speer of Saarland University. Speer, who has doctorates in medicine as well as biology, is the lead author of the work just published in Nature Immunology.

The large-scale study was able to demonstrate that patients with elevated levels of triglycerides in their blood had a significantly higher mortality rate than comparison groups with a similar health history. 'Put another way, we can now say that adopting a low-fat diet can significantly extend the life expectancy of high-risk patients, such as those with diabetes or those whose blood pressure is too high,' says Timo Speer. Blood triglyceride levels rise substantially in people who eat a high-fat diet. 'As a result of biochemical changes, the triglycerides develop toxic properties that activate the body's innate immune system. This initiates a series of self-destructive processes including those in which the walls of the arteries are attacked and the blood vessels become occluded, reducing blood flow,' explains Speer. The study has established a definitive link between the chronic inflammation triggered by an elevated triglyceride concentration in the blood and secondary diseases such as kidney failure or heart attack. 'We hope that our results will help in developing new strategies for treating and preventing these life-threatening diseases,' says Timo Speer.

The publication in Nature Immunology is one of the results of the diverse range of scientific investigations being carried out as part of a Transregional Collaborative Research Centre between Saarland University and RWTH Aachen University. The focus of the work performed within the Collaborative Research Centre is to discover which cardiac and vascular diseases can be caused by chronic kidney disease. The German Research Foundation (DFG) is funding this major research programme with ten million euros over a three-year period. Timo Speer is the lead researcher for one the research projects. He is also a senior physician at Saarland University Hospital and laboratory director for experimental and translational nephrology.

UPTON, NY--Scientists at the U.S. Department of Energy's Brookhaven National Laboratory have discovered a new function in a plant enzyme that could have implications for the design of new chemical catalysts. The enzyme catalyzes, or initiates, one of the cornerstone chemical reactions needed to synthesize a wide array of organic molecules, including those found in lubricants, cosmetics, and those used as raw materials for making plastics.

"This enzyme could inspire a new form of 'green' chemistry," said Brookhaven Lab biochemist John Shanklin, who led the research. "Maybe we can adapt this biomolecule to make useful chemicals in plants, or use it as the basis for designing new bio-inspired catalysts to replace more expensive, toxic catalysts currently in use."

Shanklin and his team published a paper describing the research in the journal Plant Physiology.

The team made the discovery in the course of their ongoing research into enzymes that desaturate plant oils. These desaturase enzymes strip hydrogen atoms off specific adjacent carbon atoms in a hydrocarbon chain and insert a double bond between those carbon atoms. Shanklin's group had previously created a triple mutant version of a desaturase enzyme with interesting properties, and they were studying the three mutations separately to see what each one did.

Two of the single mutant enzymes turned out to remove the double bond between adjacent carbon atoms and added an "OH" (hydroxyl group) to each carbon to produce a fatty acid with two adjacent hydroxyl groups.

Fatty acids containing such adjacent OH groups, known as diols, are important chemical components for making lubricants, like those that keep hot engines running smoothly. They can also be converted to building blocks for making plastics or other commodity products.

"Diols are really important industrial chemicals but making them artificially in the lab is quite problematic," Shanklin said.

The best industrial catalysts for this reaction are expensive, highly volatile, and toxic, he noted.

Another problem is that there are distinct forms of diols, and it's hard for chemists to make a single pure form.

"The enzyme mutants we discovered naturally make a single form, so it's ready to use without further processing or waste," Shanklin said.

Tracing the origins of the oxygen atoms in the two OH groups revealed that both came from the same oxygen molecule (O?). The ability to transfer both oxygen atoms from a single O? molecule during a reaction, known as "dioxygenase" chemistry, was something of a surprise for a "diiron" enzyme (one with two iron atoms in its active site).

"Dioxygenase chemistry has not previously been reported for diiron enzymes," Shanklin said. "We had to perform some technically challenging experiments to provide incontrovertible proof that this was indeed happening, and without Ed Whittle's creativity and tenacity, we wouldn't have completed this study."

Whittle, the lead author on the paper (now retired from Brookhaven Lab), has diligently worked on this project over a period of years in Shanklin's lab to nail down this important new discovery.

The team's next goal is to obtain a crystal structure of this enzyme using x-rays at the National Synchrotron Light Source II (NSLS-II)--a DOE Office of Science user facility at Brookhaven Lab.

"We'll share that structural information with our computational chemistry colleagues to figure out the details of how this unprecedented chemistry can occur with this class of catalyst."

That work could help the team learn how to control the configuration of lab-made catalysts to mimic the plant-derived version.

"If we can incorporate what we've learned into the design of industrial catalysts, those reactions could produce purer products with less waste and avoid using toxic chemicals," Shanklin said.

MELBOURNE, FLA. -- New research led by scientists from Florida Institute of Technology found that the strong and long-lasting droughts known as megadroughts parched the usually moist Peruvian cloud forests, spurring farmers to colonize new cropland.

The study, "2,100 years of human adaptation to climate change in the High Andes," reveals that Andean climate changes - especially droughts - over the last 2,100 years were an important determinant of how land was used by native Andean societies. It was published online Dec. 9 in Nature Ecology and Evolution from scientists at Florida Tech, University of Miami and Columbus State University.

The setting of the study is the Laguna de los Cóndores, or Lake of the Condors, in Peru. This is an especially important area to archaeologists as the cliffs above the lake were a tomb-site for over 200 Incan and pre-Incan mummies.

One of the key findings of the study was that the peak of deforestation was about 800 A.D. and that the last deforestation to produce maize agriculture was about 1100 A.D. The farming ended by about 1200 A.D. and the forests reclaimed the valley around the lake. This timing coincided with two things: a wetter regional climate and the beginning of the cliff burials.

"As the landscape changed from a patchwork of maize fields and disturbed forests back to cloud forest, we saw an end to burning and an almost immediate improvement in the lake's water quality," said Mark Bush, professor of biology at Florida Tech and the team leader. "This recovery offers us the hope that some of the bad ecosystem impacts from deforestation and grazing in the Andes are reversible."

But the study also shows that the projected increased droughts resulting from modern climate change in the Andes are likely to cause farmers to deforest and exploit cloud forest regions.

A grant to Bush from the National Geographic Society funded the fieldwork, and follow-up laboratory funding was provided by grants from the National Science Foundation and NASA.

The analysis of sediments recovered from the bottom of the lake provided multiple lines of evidence that included fossil pollen, charcoal and algae, and sediment chemistry. Data from these sources allowed the team to reconstruct an almost year-by-year history of the land use around the lake spanning the last 2,100 years. Multiple cycles of farming activity followed by abandonment aligned to changing climates were recorded, as were five megadroughts.

Each drought lasted for as much as a decade, and each time farmers exploited the valley. Between these dry periods, under the more normal, wetter conditions, the valley was largely abandoned, and forests regrew.

"We were surprised to see how responsive these populations were to climate change," said Christine Åkesson, who conducted the study as a Ph.D. student at Florida Tech and is the lead author of the paper. "We expected to see a steady rise in land use peaking with the internment of mummies in the cliffs and the collapse of Incan society when the Spanish conquered this part of Peru in the 1570s, but that isn't what happened."

CORVALLIS, Ore. - A study by Oregon State University researchers has identified forests in the western United States that should be preserved for their potential to mitigate climate change through carbon sequestration, as well as to enhance biodiversity.

Those forests are mainly along the Pacific coast and in the Cascade Range, with pockets of them in the northern Rocky Mountains as well. Not logging those forests would be the carbon dioxide equivalent of halting eight years' worth of fossil fuel burning in the western lower 48, the scientists found, noting that making land stewardship a higher societal priority is crucial for altering climate change trajectory.

The findings, published in Ecological Applications, are important because capping global temperature increases at 1.5 degrees Celsius above pre-industrial levels, as called for in the 2016 Paris Agreement, would maintain substantial proportions of ecosystems while also benefiting economies and human health, scientists say.

"The greater frequency and intensity of extreme events such as wildfires have adversely affected terrestrial ecosystems," said study co-author Beverly Law, professor of forest ecosystems and society in the OSU College of Forestry. "Although climate change is impacting forests in many regions, other regions are expected to have low vulnerability to fires, insects and drought in the future."

Law, Oregon State forestry professor William Ripple, postdoctoral research associate Polly Buotte and Logan Berner of EcoSpatial Services analyzed forests in the western United States to simulate potential carbon sequestration through the 21st century.

The five-year study supported by the U.S. Department of Agriculture's National Institute of Food and Agriculture identified, and targeted for preservation, forests with high carbon sequestration potential, low vulnerability to drought, fire and beetles, and high biodiversity value.

Largely through the burning of fossil fuels, which releases the greenhouse gas carbon dioxide into the atmosphere, the Earth has already warmed by 1 degree Celsius. Arctic sea ice is declining at the fastest rate in 1,500 years, sea levels have risen more than 8 inches since 1880, and extreme weather events are becoming more common and damaging.

Atmospheric CO2 has increased 40 percent since the dawn of the Industrial Age. According to the National Atmospheric and Oceanic Administration's Global Monitoring Division, the global average atmospheric carbon dioxide concentration on Jan 1, 2019, was 410 parts per million, higher than at any time in at least 800,000 years.

"Smart land management can mitigate the effects of climate-induced ecosystem changes to biodiversity and watersheds, which influence ecosystem services that play a key role in human well-being," said Buotte, the study's corresponding author.

Preserving temperate forests in the western United States that have medium to high potential carbon sequestration and low future climate vulnerability could account for about a third of the global mitigation potential previously identified for temperate and boreal forests, the authors say.

"At the same time, it would promote ecosystem resilience and maintenance of biodiversity," Law said. "We are in the midst of a climate crisis and a biodiversity crisis. Preserving these forests is one of the greatest things we can do in our region of North America to help on both fronts."

Led by researchers at Baylor College of Medicine, a study published in the journal Cell Stem Cell reveals a new mechanism that contributes to adult bone maintenance and repair and opens the possibility of developing therapeutic strategies for improving bone healing.

"Adult bone repair relies on the activation of bone stem cells, which still remain poorly characterized," said corresponding author Dr. Dongsu Park, assistant professor of molecular and human genetics and of pathology and immunology at Baylor. "Bone stem cells have been found both in the bone marrow inside the bone and also in the periosteum - the outer layer of tissue - that envelopes the bone. Previous studies have shown that these two populations of stem cells, although they share many characteristics, also have unique functions and specific regulatory mechanisms."

Of the two, periosteal stem cells are the least understood. It is known that they comprise a heterogeneous population of cells that can contribute to bone thickness, shaping and fracture repair, but scientists had not been able to distinguish between different subtypes of bone stem cells to study how their different functions are regulated.

In the current study, Park and his colleagues developed a method to identify different subpopulations of periosteal stem cells, define their contribution to bone fracture repair in live mouse models and identify specific factors that regulate their migration and proliferation under physiological conditions.

Periosteal stem cells are major contributors to bone healing

The researchers discovered specific markers for periosteal stem cells in mouse models. The markers identified a distinct subset of stem cells that contributes to life-long adult bone regeneration.

"We also found that periosteal stem cells respond to mechanical injury by engaging in bone healing," Park said. "They are important for healing bone fractures in the adult mice and, interestingly, their contribution to bone regeneration is higher than that of bone marrow stem cells."

In addition, the researchers found that periosteal stem cells also respond to inflammatory molecules called chemokines, which are usually produced during bone injury. In particular, they responded to chemokine CCL5.

Periosteal stem cells have receptors - molecules on their cell surface - that bind to CCL5, which sends a signal to the cells to migrate toward the injured bone and repair it. Deleting the CCL5 gene in mouse models resulted in marked defects in bone repair or delayed healing. When the researchers supplied CCL5 to CCL5-deficient mice, bone healing was accelerated.

The findings suggested potential therapeutic applications. For instance, in individuals with diabetes or osteoporosis in which bone healing is slow and may lead to other complications resulting from limited mobility, accelerating bone healing may reduce hospital stay and improve prognosis.

"Our findings contribute to a better understanding of how adult bones heal. We think this is one of the first studies to show that bone stem cells are heterogeneous and that different subtypes have unique properties regulated by specific mechanisms," Park said. "We have identified markers that enable us to tell bone stem cell subtypes apart and studied what each subtype contributes to bone health. Understanding how bone stem cell functions are regulated offers the possibility to develop novel therapeutic strategies to treat adult bone injuries."

Grown as Christmas trees, Fraser firs are highly prized for their rich color and pleasant scent as well as their ability to hold their needles. Unfortunately, they are also highly susceptible to devastating root rot diseases caused by water molds in the genus Phytophthora.

Scientists in Connecticut were conducting experiments testing various methods to grow healthier Fraser trees when they accidentally discovered a new species of Phytophthora. They collected the diseased plants, isolated and grew the pathogen on artificial media, then inoculated it into healthy plants before re-isolating it to prove its pathogenicity.

"Once the organism was isolated, the presence of unusually thick spore walls alerted us that this may not be a commonly encountered species," said Rich Cowles, a scientist at the Connecticut Agricultural Experiment Station involved with this study, "and so comparison of several genes' sequences with known Phytophthora species was used to discover how our unknown was related to other, previously described species." In fact, they had discovered a new species altogether.

The fact that these scientists so readily discovered a new species of Phytophthora infecting Christmas trees suggests that there could be many more species waiting to be discovered. Recognizing the greater biodiversity among this genus infecting Christmas trees is important. Transportation of infected nursery stock and chance encounters of different Phytophthora species in the field can lead to new hybrids arising, which can have different pathogenic characteristics than their parent species.

"Knowing how many and which species are present is important, not only for Christmas tree growers, but also for protecting our natural environment," Cowles adds.

Also of note, this research was conducted using apples to do the initial isolation of Phytophthora, a method that dates back to 1931, demonstrating that old methods in plant pathology are still valid and useful. "Combining this robust old technique worked well with modern molecular biology methods to isolate, and then identify our unknown plant disease," according to Cowles.

You see them all over city streets: pedestrians wearing headphones or earbuds - their faces glued to their phones as they stroll along oblivious to their surroundings.

Known as "twalking," the behavior is not without its dangers. Headphone-wearing pedestrians often can't hear the auditory cues - horns, shouts, or the sound of approaching cars - that signal imminent harm. As a result, the number of injuries and deaths caused by twalking in the U.S. has tripled in the last seven years. Last year, moreover, pedestrian deaths in the U.S. were at their highest level since 1990.

To counter this growing public safety concern, researchers at the Data Science Institute, Columbia, are designing an intelligent headphone system that warns pedestrians of imminent dangers. The headphones have miniature microphones and intelligent signal processing that detects sounds of approaching vehicles. If a hazard appears near, the system sends an audio alert to the pedestrian's headphones. The research team is developing prototypes and testing them on streets close to Columbia. Once developed, the intelligent wearable system could help reduce pedestrian injuries and fatalities.

"We are exploring a new area in developing an inexpensive and low-power technology that creates an audio-alert mechanism for pedestrians," says Fred Jiang, a Data Science Institute member and an assistant professor of electrical engineering at Columbia Engineering.

The smart-headphone project was awarded a $1.2 million grant from the National Science Foundation in 2017, and the team has since published two conference papers as well as a journal paper in IEEE Internet of Things Journal on their research. They've also received several honors including a best demo award from an ACM conference and a best presentation award from an IEEE conference. The research team includes Peter Kinget, chair of the Electrical Engineering Department at Columbia and an affiliate of the Data Science Institute; Shahriar Nirjon, a professor of Computer Science at the University of North Carolina at Chapel Hill; and Joshua New, a psychology professor from Barnard College. Graduate students from both Columbia and UNC also work on the project.

The research and development of the smart headphones is complex: It involves embedding multiple miniature microphones in the headset as well as developing a low-power data pipeline to process all the sounds near to the pedestrian. It must also extract the correct cues that signal impending danger. The pipeline will contain an ultra-low power, custom-integrated circuit that extracts the relevant features from the sounds while using little battery power.

The researchers are also using the most advanced data science techniques to design the smart headset. Machine-learning models on the user's smartphone will classify hundreds of acoustical cues from city streets and nearby vehicles and warn users when they are in danger. The mechanism will be designed so that people will recognize the alert and respond quickly. The team is now testing its design both in the lab and on the streets of New York - a city known for its congestion and its cacophony of sounds. New, the psychology professor from Barnard, says he'll conduct perceptual and behavioral experiments with people to see how the alerts can be effectively provided to pedestrians who walk in cities wearing headphones.

Jiang said his aim is to develop a prototype of the smart headphone system at Columbia and then transfer the technology to a commercial company.

"We hope that once refined," he says, "the technology will be commercialized and mass produced in a way that will help cities reduce pedestrian fatalities."

HOUSTON -- (Dec. 9, 2019) -- Online shoppers typically string together a few words to search for the product they want, but in a world with millions of products and shoppers, the task of matching those unspecific words to the right product is one of the biggest challenges in information retrieval.

Using a divide-and-conquer approach that leverages the power of compressed sensing, computer scientists from Rice University and Amazon have shown they can slash the amount of time and computational resources it takes to train computers for product search and similar "extreme classification problems" like speech translation and answering general questions.

The research will be presented this week at the 2019 Conference on Neural Information Processing Systems (NeurIPS 2019) in Vancouver. The results include tests performed in 2018 when lead researcher Anshumali Shrivastava and lead author Tharun Medini, both of Rice, were visiting Amazon Search in Palo Alto, California.

In tests on an Amazon search dataset that included some 70 million queries and more than 49 million products, Shrivastava, Medini and colleagues showed their approach of using "merged-average classifiers via hashing," (MACH) required a fraction of the training resources of some state-of-the-art commercial systems.

"Our training times are about 7-10 times faster, and our memory footprints are 2-4 times smaller than the best baseline performances of previously reported large-scale, distributed deep-learning systems," said Shrivastava, an assistant professor of computer science at Rice.

Medini, a Ph.D. student at Rice, said product search is challenging, in part, because of the sheer number of products. "There are about 1 million English words, for example, but there are easily more than 100 million products online."

There are also millions of people shopping for those products, each in their own way. Some type a question. Others use keywords. And many aren't sure what they're looking for when they start. But because millions of online searches are performed every day, tech companies like Amazon, Google and Microsoft have a lot of data on successful and unsuccessful searches. And using this data for a type of machine learning called deep learning is one of the most effective ways to give better results to users.

Deep learning systems, or neural network models, are vast collections of mathematical equations that take a set of numbers called input vectors, and transform them into a different set of numbers called output vectors. The networks are composed of matrices with several parameters, and state-of-the-art distributed deep learning systems contain billions of parameters that are divided into multiple layers. During training, data is fed to the first layer, vectors are transformed, and the outputs are fed to the next layer and so on.

"Extreme classification problems" are ones with many possible outcomes, and thus, many parameters. Deep learning models for extreme classification are so large that they typically must be trained on what is effectively a supercomputer, a linked set of graphics processing units (GPU) where parameters are distributed and run in parallel, often for several days.

"A neural network that takes search input and predicts from 100 million outputs, or products, will typically end up with about 2,000 parameters per product," Medini said. "So you multiply those, and the final layer of the neural network is now 200 billion parameters. And I have not done anything sophisticated. I'm talking about a very, very dead simple neural network model."

"It would take about 500 gigabytes of memory to store those 200 billion parameters," Medini said. "But if you look at current training algorithms, there's a famous one called Adam that takes two more parameters for every parameter in the model, because it needs statistics from those parameters to monitor the training process. So, now we are at 200 billion times three, and I will need 1.5 terabytes of working memory just to store the model. I haven't even gotten to the training data. The best GPUs out there have only 32 gigabytes of memory, so training such a model is prohibitive due to massive inter-GPU communication."

MACH takes a very different approach. Shrivastava describes it with a thought experiment randomly dividing the 100 million products into three classes, which take the form of buckets. "I'm mixing, let's say, iPhones with chargers and T-shirts all in the same bucket," he said. "It's a drastic reduction from 100 million to three."

In the thought experiment, the 100 million products are randomly sorted into three buckets in two different worlds, which means that products can wind up in different buckets in each world. A classifier is trained to assign searches to the buckets rather than the products inside them, meaning the classifier only needs to map a search to one of three classes of product.

"Now I feed a search to the classifier in world one, and it says bucket three, and I feed it to the classifier in world two, and it says bucket one," he said. "What is this person thinking about? The most probable class is something that is common between these two buckets. If you look at the possible intersection of the buckets there are three in world one times three in world two, or nine possibilities," he said. "So I have reduced my search space to one over nine, and I have only paid the cost of creating six classes."

Adding a third world, and three more buckets, increases the number of possible intersections by a factor of three. "There are now 27 possibilities for what this person is thinking," he said. "So I have reduced my search space by one over 27, but I've only paid the cost for nine classes. I am paying a cost linearly, and I am getting an exponential improvement."

In their experiments with Amazon's training database, Shrivastava, Medini and colleagues randomly divided the 49 million products into 10,000 classes, or buckets, and repeated the process 32 times. That reduced the number of parameters in the model from around 100 billion to 6.4 billion. And training the model took less time and less memory than some of the best reported training times on models with comparable parameters, including Google's Sparsely-Gated Mixture-of-Experts (MoE) model, Medini said.

He said MACH's most significant feature is that it requires no communication between parallel processors. In the thought experiment, that is what's represented by the separate, independent worlds.

"They don't even have to talk to each other," Medini said. "In principle, you could train each of the 32 on one GPU, which is something you could never do with a nonindependent approach."

Shrivastava said, "In general, training has required communication across parameters, which means that all the processors that are running in parallel have to share information. Looking forward, communication is a huge issue in distributed deep learning. Google has expressed aspirations of training a 1 trillion parameter network, for example. MACH, currently, cannot be applied to use cases with small number of classes, but for extreme classification, it achieves the holy grail of zero communication."

EVANSTON, Ill. --- There have been many headlines in recent years about the potentially negative impacts contact sports can have on athletes' brains. But a new Northwestern University study shows that, in the absence of injury, athletes across a variety of sports - including football, soccer and hockey - have healthier brains than non-athletes.

"No one would argue against the fact that sports lead to better physically fitness, but we don't always think of brain fitness and sports," said senior author Nina Kraus, the Hugh Knowles Professor of Communication Sciences and Neurobiology and director of Northwestern's Auditory Neuroscience Laboratory (Brainvolts). "We're saying that playing sports can tune the brain to better understand one's sensory environment."

Athletes have an enhanced ability to tamp down background electrical noise in their brain to better process external sounds, such as a teammate yelling a play or a coach calling to them from the sidelines, according to the study of nearly 1,000 participants, including approximately 500 Northwestern Division I athletes. 

Kraus likens the phenomenon to listening to a DJ on the radio. 

"Think of background electrical noise in the brain like static on the radio," Kraus said. "There are two ways to hear the DJ better: minimize the static or boost the DJ's voice. We found that athlete brains minimize the background 'static' to hear the 'DJ' better."

The study will be published Dec. 9 in the journal Sports Health.

"A serious commitment to physical activity seems to track with a quieter nervous system," Kraus said. "And perhaps, if you have a healthier nervous system, you may be able to better handle injury or other health problems."

The findings could motivate athletic interventions for populations that struggle with auditory processing.  In particular, playing sports may offset the excessively noisy brains often found in children from low-income areas, Kraus said. 

This is the latest study from the neural processing of sound in sports concussions and contact sports partnership, a five-year, National Institutes of Health-funded research collaboration between Brainvolts and Northwestern University Athletics, which launched last year. 
The study examined the brain health of 495 female and male Northwestern student athletes and 493 age- and sex-matched control subjects. 

Kraus and her collaborators delivered speech syllables to study participants through earbuds and recorded the brain's activity with scalp electrodes. The team analyzed the ratio of background noise to the response to the speech sounds by looking at how big the response to sound was relative to the background noise. Athletes had larger responses to sound than non-athletes, the study showed. 

Like athletes, musicians and those who can speak more than one language also have an enhanced ability to hear incoming sound signals, Kraus said. However, musicians' and multilinguals' brains do so by turning up the sound in their brain versus turning down the background noise in their brain. 

"They all hear the 'DJ' better but the musicians hear the 'DJ' better because they turn up the 'DJ,' whereas athletes can hear the 'DJ' better because they can tamp down the 'static,'" Kraus said.