Culture

Online searches for mobile and isolated activities can help to predict later surges and declines in COVID-19 cases, a team of researchers has found. Its findings, based on a four-month analysis of online searches, offer a potential means to anticipate the pathways of the pandemic--before new infections are reported.

"This is a first step towards building a tool that can help predict COVID case surges by capturing higher-risk activities and intended mobility, which searches for gyms and in-person dining can illuminate," says Anasse Bari, a clinical assistant professor in computer science at New York University's Courant Institute of Mathematical Sciences and one of the authors of the paper, which appears in the journal Social Network Analysis and Mining. "Using such 'alternative data' is nothing new and has been applied for other purposes--for instance, alternative data has been used in finance to generate data-driven investments, such as studying satellite images of cars in parking lots to predict businesses earnings."

"Our research shows the same techniques could be applied to combatting a pandemic by spotting, ahead of time, where outbreaks are likely to occur," adds Megan Coffee, a clinical assistant professor in the Division of Infectious Disease & Immunology at NYU Grossman School of Medicine. "Developing a barometer of behavior would, with further work and validation, allow policymakers and epidemiologists to track the impact of social interventions and brace for rising surges."

The research also showed an association between intended activities outside the home after lockdown restrictions were lifted, pointing to how the effects of policy decisions can be measured using alternative data.

Since the onset of the pandemic, governments have restricted activities, often based on surges of COVID-19 cases, then loosened these restrictions after declines. However, these actions are in response to infection rates and are designed to limit the spread of future cases.

In the Social Network Analysis and Mining study, the researchers sought to determine if there were ways to spot behaviors known to be risky during the pandemic (e.g., visits to barbershops and nail salons) ahead of local and regional outbreaks--and conversely, identify behaviors known to be less risky (e.g., exercising at home) prior to declines in coronavirus cases.

"Our goal was to capture the underlying social dynamics of an unprecedented pandemic using alternative data sources that are new to infectious disease epidemiology," explains Bari. "When someone searches the closing time of a local bar or looks up directions to a local gym, they give some insight into what future risks they may have."

To examine this, they studied online searches from March through June in 2020 in all 50 states. Here, they divided searches into two categories--or "tracks": a mobility index track, which categorized searches linked to interactions with others outside the home (e.g., "theaters near me," "flight tickets"), and an isolation index track, which categorized searches linked to activities done at home ("food delivery," "at-home yoga").

The team's choice of search keywords was informed by a recent Democracy Fund + UCLA Nationscape survey that tracked activities individuals reported they would prioritize attending if "restrictions were lifted on the advice of public health officials regarding activities." The most popular results included "going to a stadium/concert," "going to the movies," and "attending a sports event."

Using Google Trends data, the researchers tracked search trends related to mobility and isolation to develop mobility and isolation indexes. They complemented these with a "net movement index," which was the difference between the mobility index and the isolation index.

The researchers then looked at COVID-19 case growth 10 to 14 days later--the expected lag between exposure and symptoms--at the state level by examining data from state and local health agencies.

Overall, they found that the net movement index correlated with new COVID-19 cases--reported weekly--in 42 of 50 states over the studied period (March-June 2020).

The researchers also looked more closely at five states (Arizona, California, Florida, New York, and Texas) to determine the impact of the ending of stay-at-home orders on searches. In all of these states, the mobility index, which decreased during the initial lockdown phase, increased as re-openings began. Subsequently, COVID-19 cases rose again nationwide in June 2020 and surged in Arizona, California, Florida, and Texas.

By contrast, an earlier sharp decline in mobility indices was followed by a sharp decline in the case growth data in these same five states.

"From this work, we hope to build a knowledge base on human behavior change from alternative data during the life cycle of the pandemic in order to allow machine learning to predict behavior in future epidemics," says Aashish Khubchandani, an NYU undergraduate and one of the paper's authors.

The researchers recognize that search-based methods to predict infection outbreaks raise privacy concerns. However, they emphasize that their tool uses large volumes of search queries, not individual ones, and relies on anonymized data in order to offer health-related projections.

AUGUSTA, Ga (Feb. 8, 2021) - Starting with early childhood, otherwise healthy Black people show signs of slightly diminished heart muscle strength and a slightly higher blood pressure than their white counterparts, factors which may put them on a course for early development of congestive heart failure, researchers report.

The take-home message for parents and physicians is that, particularly for populations at high cardiovascular risk such as Black people, a close check should be kept on blood pressure starting in early adolescence, says the corresponding author of the study in Journal of the American Heart Association.

Children with chronically higher normal blood pressures also may need early assessment of their heart function and/or medication to further lower their blood pressure to protect their future heart health, says Dr. Gaston Kapuku, cardiovascular researcher at the Georgia Prevention Institute at the Medical College of Georgia at Augusta University.

The researchers also found that ejection fraction, a widely used method to assess the strength of the heart muscle by looking at the amount of blood the left ventricle, the main pumping chamber of the heart, pumps out with each contraction is not a good way to identify these at-risk young people as they move through life.

Rather a long-available, but less-utilized analysis called midwall fractional shortening, or MFS, which looks more directly at the contractility of the cardiac muscle, appears to provide earlier insight that the heart wall is beginning to thicken and weaken in response to pushing against higher pressure inside the aorta, the body's largest blood vessel, which delivers oxygen-rich blood to the body.

Kapuku and his colleagues looked at 673 individuals -- about half male and female, half Black and half white -- who have been followed at the Georgia Prevention Institute for more than 30 years as part of the Augusta Heart Study, looking at development of cardiovascular risk factors in children with a family history of risk factors like hypertension and heart attack.

This appears to be the first prospective study to examine changes in cardiac muscle, or myocardium, function in a healthy group of individuals across their life span.

They found that while ejection fraction held steady in Black study participants over the 30-year course of the study, MFS was able to document a fraction of a percentage point of change in heart function: A .54% decrease in MFS in Black participants compared to white participants, as both grew from childhood into young adulthood. They also saw that as the size of the left ventricle grew by 1 gram, or about 0.035 ounces, MFS decreased in Black participants by 0.01%. The entire heart weighs 7-15 ounces, and a heart that gets bigger is an indicator of disease.

Also as pressure inside the aorta, against which the ventricle pumps, slowly crept up over the years, MFS, which indicates muscle strength, crept downward.

Subtle decreases in MFS are associated with increased risk of congestive heart failure, the researchers write. Kapuku notes that while the small decreases in contractility they found are not yet clinically significant in these young people, if the trend continues they likely will become a factor in their heart health.

"When you look at MFS you can actually assess the power of your muscle, you know that it is weakening even though the ejection fraction is normal," Kapuku says.

MFS is a formula that also accounts for the heart wall thickness when it's contracting and relaxed. Kapuku contracts his biceps to show the clear difference contracting and relaxing makes in muscle size. The heart cavity that fills with blood is much bigger when its relaxed, called diastole, and the muscle gets much bigger when it's contracting, called systole.

Kapuku and his colleagues say MFS is an easy, sensitive and inexpensive way to detect slight changes in cardiac muscle strength that are setting the stage for major heart dysfunction down the road, perhaps particularly in young Black individuals.

Heart disease is the leading cause of death for all Americans, but death rates are higher in Black people than white people and other ethnic groups, and disease develops at a younger age, according to The Heart Foundation. Despite cardiovascular disease remaining the number one killer, congestive heart failure is the only adult cardiovascular disease that actually continues to increase in incidence, Kapuku says, primarily because people are living longer. Black people also have the highest rate of congestive heart failure resulting from aging, rather than from direct damage to heart muscle from a heart attack, Kapuku says.

The study helped show the racial disparities, including a slightly higher blood pressure and decreasing heart function, already are evident at a young age, he says. Researchers suspect that stress-induced sodium retention, in which a higher percentage of Black people hold onto more sodium, rather than secreting it in their urine, is a significant factor. Higher sodium levels increase fluid volume inside blood vessels and blood pressure, including pressure inside the aorta, which the left ventricle must continually pump against, called afterload.

That means that despite physical fitness, a young Black person's blood pressure would tend to run higher than his white counterpart's, setting the stage for congestive heart failure earlier in life, Kapuku says.

Like Kapuku's biceps trying to lift increasingly heavier hand weights, the heart will increase muscle mass against this increased pressure but, unlike the biceps, the heart does not function better when it's bigger.

"If I didn't have increased resistance, I would not have increased cardiac load," Kapuku says. "We have to lower the blood pressure as soon as possible. Myocardial dysfunction might occur before the currently defined clinical criteria for hypertension."

That means lowering blood pressure in young Black individuals, likely shortly after they enter adolescence, might help preserve heart function.

A better diet including foods low in salt and high in potassium, like cooked broccoli and spinach, plantains and sweet potatoes, along with regular physical activity likely will help, Kapuku says, "but medical treatment may be the ticket to longevity."

Groups like the American Heart Association say you can appear to have a "normal" ejection fraction and still have heart failure with what is called preserved ejection fraction, where the heart muscle is so thick and stiff it may hold less blood so seems to be pumping out the usual percentage -- 50-70% of the ventricle's contents -- until the total volume is not sufficient to sustain the body.

Early on, like in these study participants, the heart likely tries to compensate, to keep the ejection fraction up, by working harder, which works for a while until it doesn't, Kapuku says.

Congestive heart failure can occur with normal aging as the cardiac muscle cells, or cardiomyocytes, we are born with slowly begin to die off and their former space fills with fibrous tissue, which also starts to encircle remaining cardiomyocytes and eventually weaken the heart's ability to contract. Exercise can slow but not stop the process that makes proper filling and pumping increasingly difficult.

The American Academy of Pediatrics and the National Heart, Lung and Blood Institute both recommend that children have yearly screenings for high blood pressure, starting at age 3, at their annual well-child visits.

Efforts to improve the social success of autistic adolescents and adults have often focused on teaching them ways to think and behave more like their non-autistic peers and to hide the characteristics that define them as autistic. Psychology researchers at The University of Texas at Dallas, however, have been focusing on another approach: promoting understanding and acceptance of autism among non-autistic people.

The researchers published their findings online Jan. 20 in the journal Autism. The study showed that familiarizing non-autistic people with the challenges and strengths of autistic people helped to reduce stigma and misconceptions about autism, but implicit biases about autism were harder to overcome.

Desiree Jones, a psychology doctoral student in the School of Behavioral and Brain Sciences (BBS), is the corresponding author of the paper, and Dr. Noah Sasson, associate professor of psychology, is the senior author.

Autism is characterized by differences in thinking, sensing, and communicating that can make interaction and connection with non-autistic people difficult. Some autistic people are nonspeaking and need a lot of support in their everyday lives, while some are highly verbal and need less support. Jones' work focuses specifically on the experiences of autistic adults without intellectual disability.

"Previous work in our lab has shown that autistic people are often stereotyped as awkward and less likeable," Jones said. "Some might think that autistic people don't want friends or don't want to interact with people. We want to combat those ideas."

Promoting autism knowledge among non-autistic adults represents a shift in philosophy about how to improve the social experiences of autistic people. Jones explained that this tactic borrows from research on race and ethnicity.

"Targeting autistic behavior places the burden of social exclusion on autistic people, when we should really be challenging the attitudes that lead others to stigmatize autistic behaviors," she said. "Research on race suggests that people who have racial biases tend to view that race as a monolith, assigning every member the same features. By exposing them to different people from the group, you can challenge those stereotypes. We believe the same principle applies to autism."

The study participants -- 238 non-autistic adults -- were split into three groups. One group viewed an autism acceptance video originally developed as a PowerPoint presentation by researchers at Simon Fraser University in British Columbia in collaboration with autistic adults. Jones updated it and had narration added. The second group watched a general mental health training presentation that didn't mention autism, and the third received no training at all. Participants then were tested on their explicit and implicit biases about autism.

"The autism video presents autism facts and promotes acceptance. It gives tips on how to befriend an autistic person and talk to them about their interests," Jones said. "It also discusses things to avoid, such as sensory overload and pressuring them into engaging."

Subsequent testing of explicit biases included capturing first impressions of autistic adults in video clips, measuring participants' autism knowledge and stigma, and gauging their beliefs about autistic functional abilities. Implicit biases also were examined, gauging whether participants unconsciously associate autism with negative personal attributes.

As anticipated, the autism acceptance training group demonstrated greater understanding and acceptance of autism on the explicit measures, including expressing more social interest in autistic adults and resulting in more positive first impressions. However, participants continued to implicitly associate autism with unpleasant personal attributes regardless of which training they experienced.

"Explicit biases are consciously held, evolve quickly and are constrained by social desirability," Sasson explained. "Implicit biases reflect more durable underlying beliefs -- associations reinforced over time that are more resistant to change."

Many of the stubborn stereotypes about autism are reinforced by portrayals in the media, whether from TV shows like "The Good Doctor" or movies like "Rain Man."

"A common trope exists of the white male autistic person with savant abilities," Jones said. "They are really smart but very socially awkward. They can be portrayed as flat or without emotion or passion. These beliefs can be harmful and do not reflect how variable these characteristics are among autistic people. They belie the range of unique difficulties and skills that autistic people can have.

"There's a saying that if you've met one autistic person, you've met one autistic person. The community varies so much in individual needs, strengths and difficulties that there's not a very useful prototype. So getting to know actual people and getting away from preconceptions can hopefully help us improve social outcomes for the autistic community."

Jones said that autistic individuals themselves are integral in plotting the path forward.

"Autistic people often feel that they simply aren't listened to, that they are dismissed or not cared about," she said. "A big part of being welcoming is simply acknowledging actual autistic people telling us what they like and what they want research to be. In our lab, we have several autistic master's and undergraduate students who play a big role in our research, and they've taught me a lot."

Sasson described the results as promising and indicative of the promise of well-done training, although the staying power of such effects remains unclear.

"This half-hour presentation was engaging and entertaining and included a lot of compelling first-person narratives," he said. "The fact that non-autistic people experiencing the training were more interested in social interaction with autistic people, had fewer misconceptions about autism, and reported more accurate understanding of autistic abilities after completing it is a success story of sorts.

"Whether the effects persist over time is another question. It could very well be that the benefits are transient, which would significantly limit the promise of training programs like this."

In future work, Jones and Sasson hope to establish a connection between inclusion and acceptance and the mental health and well-being of autistic people, who experience higher levels of depression, anxiety and suicide than the general population.

"It's not easy to be autistic in a predominantly non-autistic world, and making the social world a bit more accommodating and welcoming to autistic differences could go a long way toward improving personal and professional outcomes for autistic people," Sasson said.

Beer-Sheva, Israel...February 8, 2021 - A new discovery by researchers from Ben-Gurion University of the Negev (BGU) and its affiliated Soroka University Medical Center shows that medical cannabis may reduce blood pressure in older adults.

The study, published in the European Journal of Internal Medicine, is the first of its kind to focus on the effect of cannabis on blood pressure, heart rate and metabolic parameters in adults 60 and above with hypertension.

"Older adults are the fastest growing group of medical cannabis users, yet evidence on cardiovascular safety for this population is scarce," says Dr. Ran Abuhasira of the BGU Faculty of Health Sciences, one of Israel's leading medical faculties, and the BGU-Soroka Cannabis Clinical Research Institute. "This study is part of our ongoing effort to provide clinical research on the actual physiological effects of cannabis over time."

Patients were evaluated using 24-hour ambulatory blood pressure monitoring, ECG, blood tests, and body measurements -- both before and three months after initiating cannabis therapy.

In the study, researchers found a significant reduction in 24-hour systolic and diastolic blood pressure values, with the lowest point occurring three hours after ingesting cannabis either orally via oil extracts or by smoking. Patients showed reductions in blood pressure in both daytime and nighttime, with more significant changes at night.

The BGU researchers theorize that the relief from pain, the indication for prescription cannabis in most patients, may also have contributed to a reduction in blood pressure.

"Cannabis research is in its early stages and BGU is at the forefront of evaluating clinical use based on scientific studies," says Doug Seserman, chief executive officer of American Associates, Ben-Gurion University of the Negev. "This new study is one of several that has been published recently by BGU on the medicinal benefits of cannabis."

Scientists studying forest dwelling butterflies in Central and South America have discovered that changes in the way animals perceive and process information from their environment can support the emergence of new species. The study led by the University of Bristol, and published today [9 February] in the Proceedings of the National Academy of Sciences (PNAS), has implications for how new species might evolve and the underappreciated role of changes in the brain.

The international team, led by Dr Stephen Montgomery from the School of Biological Sciences at the University of Bristol, compared the brain morphology of two distinct but closely related lineages of butterfly that occur in distinct tropical forest habitats. The first, including the species Heliconius cydno, lives in deeper forests, where the canopy light levels are low. Its sister lineage, including a species called Heliconius melpomene, lives around the forest edges, where light is much more abundant. Despite their ecological differences, these species are very closely related and can still produce viable offspring, suggesting they sit right at the brink of being new species.

The team found substantial differences in the brains of forest edge and deep forest species, with the latter investing more in parts of the brain that process visual information. By collecting butterflies across south and central America, as well as rearing captive individuals under controlled conditions at the Smithsonian Tropical Research Institute in Panama, the researchers showed that differences in brain morphology have accumulated in a way consistent with natural selection.

Dr Stephen Montgomery, Senior Research Fellow at Bristol, said: "These butterflies aren't separated by huge distances, nor are they distantly related, but their brain structure is finely tuned to the specific habitats they occupy, and we think this process helps keep the two lineages apart, allowing them to become distinct species."

Similar differences were seen when the team examined the how highly different genes were expressed in the brain.

Matteo Rossi, a PhD student at LMU Munich, explained: "Based on the pattern of gene expression in brain tissue we can accurately cluster individuals into the correct species. The expression of genes driving these differences evolve fast, and seem to be located in regions of the genome that are most distinct between the two species."

To further explore these effects the team produced hybrid offspring between forest edge and deep forest species. They found these hybrids showed intermediate brain morphologies and patterns of gene expression in the brain.

Dr Richard Merrill, also from LMU Munich, said: "Our study is exciting because it suggests that hybrids in the wild might be behavioural misfits in both habitats, and suffer the consequences."

The researchers believe that the work may imply adaptations in the brain play an underappreciated role in speciation across environments.

"We're used to thinking about behaviour being important in speciation, but behavioural evolution must have a neural basis, but we're only just beginning to unpick this kind of process" added Dr Stephen Montgomery.

The team also hope their work illustrates how important it is to protect habitat complexity in tropical forests.

"The forest is a tapestry of different conditions, with different structures, resources and cues. This work illustrates how closely species evolve to occupy these different micro-habitats, supporting high numbers of species in seemingly small areas" said Dr Owen McMillan, a co-author from the Smithsonian Tropical Research Institute in Panama, "if we want to protect the diversity of species in these areas, we have to protect the forests in a way that supports their natural variability."

BOSTON -- Hospitals across the United States have gone to great lengths to implement infection control measures to prevent transmission of SARS-CoV-2. And yet, as the pandemic has unfolded, many health care settings have experienced clusters of cases, with the virus spreading among patients, staff or both. Some clusters have been easily traced back to break rooms and shared meals. But other clusters have been challenging to trace and contain. In September 2020, Brigham and Women's Hospital detected a cluster of infections that would ultimately include 14 patients and 38 staff members. The hospital rapidly activated its incident command structure in order to coordinate a controlled response to contain the cluster. Steps taken included widespread and repeated testing of patients and staff, increased attention to staff wearing eye protection, patients wearing masks, re-emphasis on the principles of safe eating, and the pre-emptive use of precautions in uninfected patients. As part of the response to the cluster, Brigham researchers also conducted a case-control study and whole-genome sequencing to identify factors that may have been involved in the virus's spread as well as the most likely chain of transmission. The lessons gleaned from their data have helped inform infection control efforts at the Brigham and beyond. Findings are published in Annals of Internal Medicine.

"We undertook aggressive efforts to not only contain the cluster but to also try to understand what was driving transmission," said corresponding author Michael Klompas, MD, MPH, an infectious disease physician and hospital epidemiologist in the Brigham's Division of Infectious Diseases. "We pulled out all of the stops to contain this cluster and learned a lot in doing so. We want to share those lessons with our colleagues and the larger health care community."

Researchers were able to trace the cluster back to a patient who tested negative for SARS-CoV-2 on a PCR test both upon admission to the hospital and then on a repeat PCR test 12 hours later. The patient, who had pulmonary disease, received nebulizer treatments, in which liquid medication is delivered as a very fine mist that a patient can breathe in. Staff noted that the patient frequently coughed, did not tolerate a mask and had indistinct speech that led many providers to come near to understand them. The patient likely infected multiple staff members as well as patients who shared a room with the patient.

As evidence of the cluster emerged, investigators used testing and tracing to identify potential cluster-related cases among staff and patients. More than 1,200 staff members were tested for SARS-CoV-2. Eleven of 385 direct contacts of case patients and 27 of 1,072 staff associated with cluster units tested positive for SARS-CoV-2. Fifteen patients and 42 employees met epidemiologic criteria for potentially cluster-related SARS-CoV-2 infection. The team used whole-genome sequencing of samples of the virus to further determine which cases were connected to the cluster. After whole-genome sequencing, 14 patients and 38 employees were included in the cluster.

Researchers conducted a case-control study to better understand what risk factors might have contributed to cases. They evaluated responses from 32 employees with cluster-related infections and 128 uninfected but exposed employees. Infected staff members were more likely to report that they:

were present while case patients received nebulizers;

interacted with SARS-CoV-2 positive staff members in clinical areas;

spent more time exposed to case patients;

were less likely to have worn eye protection.

There were no differences between case and control employees' use of breakrooms and workrooms, amount of time spent in breakrooms and workrooms, or eating within six feet of others.

The researchers also found two cases in which staff members -- a radiology technician and speech and language therapy technician -- reported that they were infected despite wearing proper personal protective equipment, including surgical masks and eye protection.

"Infection control is a multi-faceted task," said Klompas. "These cases are a reminder that masks are just one way to protect oneself; no one measure of protection is perfect. So the best defense against infection is to increase safety through many means as appropriate to a given situation. This includes testing all patients (and retesting 3-4 days after admission or every three days if getting certain procedures), assuring good ventilation, symptom screening, masking oneself, assuring others are masked, using eye protection, maintaining distance whenever possible, minimizing the duration of encounters as clinically appropriate, avoiding crowded spaces, and using good hand hygiene."

Since September 2020, the Brigham and entities across the Mass General Brigham system have put in place additional prevention measures. These include:

repeat testing of admitted patients;

serial testing of every patient undergoing aerosol generating procedures (including nebulizer treatment);

increased messaging about eye protection and the rollout of better-quality eye protection;

increased messaging about the importance of masking for patients.

"Case clusters are the exception rather than the rule in health care settings. But this cluster and others show that if there is a cluster, we can contain it, and that there are multiple proactive measures we can take to decrease the risk of SARS-CoV-2 transmission in hospitals," said Klompas.

DALLAS - Feb. 8, 2021 - World health experts have long suspected that the incidence of COVID-19 has been higher than reported. Now, a machine-learning algorithm developed at UT Southwestern estimates that the number of COVID-19 cases in the U.S. since the pandemic began is nearly three times that of confirmed cases.

The algorithm, described in a study published today in PLOS ONE, provides daily updated estimates of total infections to date as well as how many people are currently infected across the U.S. and in 50 countries hardest hit by the pandemic.

As of Feb. 4, according to the model's calculations, more than 71 million people in the U.S. - 21.5 percent of Americans - had contracted COVID-19. That compares with the substantially smaller 26.7 million publicly reported number of confirmed cases, says Jungsik Noh, Ph.D., a UT Southwestern assistant professor in the Lyda Hill Department of Bioinformatics and first author of the study.

Of those 71 million Americans estimated to have had COVID-19, 7 million (2.1 percent of the U.S. population) had current infections and were potentially contagious on Feb. 4, according to the algorithm.

Noh's written study is based on calculations completed in September. At that time, it reports, the number of actual cumulative cases in 25 of the 50 hardest-hit countries was five to 20 times greater than the confirmed case numbers then suggested.

Looking at the current information available on the online algorithm, the estimates are now closer to the reported numbers - but still much higher. On Feb. 4, Brazil had more than 36 million cumulative cases as estimated by the algorithm, almost four times more than the 9.4 million confirmed cases reported. France had 14 million versus the 3.2 million reported. And the United Kingdom had almost 25 million instead of about 4 million - more than six times as many. Mexico, an outlier, had nearly 15 times its reported number of cases - 27.6 million rather than 1.9 million confirmed cases.

"The estimates of actual infections reveal for the first time the true severity of COVID-19 across the U.S. and in countries worldwide," says Noh.

The algorithm uses the number of reported deaths - thought to be more accurate and complete than the number of lab-confirmed cases - as the basis for its calculations. It then assumes an infection fatality rate of 0.66 percent, based on an earlier study of the pandemic in China, and considers other factors such as the average number of days from the onset of symptoms to death or recovery. It also compares its estimate with the number of confirmed cases to calculate a ratio of confirmed-to-estimated infections.

Much is still uncertain about COVID-19 - particularly the death rate - and the estimates are therefore rough, Noh says. But he believes the model's estimates are more accurate and leave out fewer cases than the confirmed ones currently used as guidance for public health policies. Having a more comprehensive estimate about the prevalence of the disease is important, Noh adds.

"These are critical statistics about the severity of COVID-19 in each region. Knowing the true severity in different regions will help us effectively fight against the virus spreading," he explains. "The currently infected population is the cause of future infections and deaths. Its actual size in a region is a crucial variable required when determining the severity of COVID-19 and building strategies against regional outbreaks."

In the U.S., infection rates vary widely by state. California has had almost 7 million infections since the pandemic's start compared with New York's 5.7 million, according to the algorithm's projections for Feb. 4. Also, the model estimated California had 1.3 million active cases on that date, affecting 3.4 percent of the state's population.

Other model estimates for Feb. 4: In Pennsylvania, 11.2 percent of the population had current infections - the highest rate of any state, compared with a low of 0.15 percent of those living in Minnesota; in New York, an early hot spot, 528,000 people had active infections, or about 2.7 percent of its population. Meanwhile, in Texas, 2.3 percent had current infections.

Noh says he developed the algorithm last summer while trying to decide whether to send his sixth-grade daughter back to school in person. There was nowhere to find the data he needed to gauge the safety of doing so, he says.

Once he built the machine algorithm, he discovered the area where he lived had about a 1 percent current infection rate. So his daughter went to school.

Noh checked his findings by comparing his results with existing prevalence rates found in several studies that used blood tests to check for antibodies to the SARS-CoV-2 virus, which causes COVID-19. For most of the areas tested, his algorithm's estimates of infections closely corresponded to the percentage of people who had tested positive for the antibodies, according to the PLOS ONE study.

The online model uses COVID-19 death data from Johns Hopkins University and The COVID Tracking Project, a volunteer organization founded to help track COVID-19, to run its daily updates. However, the estimates published in the PLOS ONE study date from Sept. 3. At that time, about 10 percent of the U.S. population had been infected with COVID-19, based on Noh's algorithm.

One of the dozens of unusual symptoms that have emerged in COVID-19 patients is a condition that's informally called "COVID brain" or "brain fog." It's characterized by confusion, headaches, and loss of short-term memory. In severe cases, it can lead to psychosis and even seizures. It usually emerges weeks after someone first becomes sick with COVID-19.

In the February 8, 2021, issue of the journal Cancer Cell, a multidisciplinary team from Memorial Sloan Kettering reports an underlying cause of COVID brain: the presence of inflammatory molecules in the liquid surrounding the brain and spinal cord (called the cerebrospinal fluid). The findings suggest that anti-inflammatory drugs, such as steroids, may be useful for treating the condition, but more research is needed.

"We were initially approached by our colleagues in critical care medicine who had observed severe delirium in many patients who were hospitalized with COVID-19," says Jessica Wilcox, the Chief Fellow in neuro-oncology at MSK and one of the first authors of the new study. "That meeting turned into a tremendous collaboration between neurology, critical care, microbiology, and neuroradiology to learn what was going on and to see how we could better help our patients."

Recognizing a Familiar Symptom

The medical term for COVID brain is encephalopathy. Members of MSK's Department of Neurology felt well-poised to study it, Dr. Wilcox says, because they are already used to treating the condition in other systemic inflammatory syndromes. It is a side effect in patients who are receiving a type of immunotherapy called chimeric antibody receptor (CAR) T cell therapy, a treatment for blood cancer. When CAR T cell therapy is given, it causes immune cells to release molecules called cytokines, which help the body to kill the cancer. But cytokines can seep into the area around the brain and cause inflammation.

When the MSK team first began studying COVID brain, though, they didn't know that cytokines were the cause. They first suspected that the virus itself was having an effect on the brain. The study in the Cancer Cell paper focused on 18 patients who were hospitalized at MSK with COVID-19 and were experiencing severe neurologic problems. The patients were given a full neurology workup, including brain scans like MRIs and CTs and electroencephalogram (EEG) monitoring, to try to find the cause of their delirium. When nothing was found in the scans that would explain their condition, the researchers thought the answer might lie in the cerebrospinal fluid.

MSK's microbiology team devised a test to detect the COVID-19 virus in the fluid. Thirteen of the 18 patients had spinal taps to look for the virus, but it was not found. At that point, the rest of the fluid was taken to the lab of MSK physician-scientist Adrienne Boire for further study.

Using Science to Ask Clinical Questions

Jan Remsik, a research fellow in Dr. Boire's lab in the Human Oncology and Pathogenesis Program and the paper's other first author, led the analysis of the fluid. "We found that these patients had persistent inflammation and high levels of cytokines in their cerebrospinal fluid, which explained the symptoms they were having," Dr. Remsik says. He adds that some smaller case studies with only a few patients had reported similar findings, but this study is the largest one so far to look at this effect.

"We used to think that the nervous system was an immune-privileged organ, meaning that it didn't have any kind of relationship at all with the immune system," Dr. Boire says. "But the more we look, the more we find connections between the two." One focus of Dr. Boire's lab is studying how immune cells are able to cross the blood-brain barrier and enter this space, an area of research that's also important for learning how cancer cells are able to spread from other parts of the body to the brain.

"One thing that was really unique about Jan's approach is that he was able to do a really broad molecular screen to learn what was going on," Dr. Boire adds. "He took the tools that we use in cancer biology and applied them to COVID-19."

The inflammatory markers found in the COVID-19 patients were similar, but not identical, to those seen in people who have received CAR T cell therapy. And as with CAR T cell therapy, the neurologic effects are sometimes delayed. The initial inflammatory response with CAR T cell treatment is very similar to the reaction called cytokine storm that's often reported in people with COVID-19, Dr. Wilcox explains. With both COVID-19 and CAR T cell therapy, the neurologic effects come days or weeks later. In CAR T cell patients, neurologic symptoms are treated with steroids, but doctors don't yet know the role of anti-inflammatory treatments for people with neurologic symptoms of COVID-19. "Many of them are already getting steroids, and it's possible they may be benefitting," Dr. Wilcox says.

"This kind of research speaks to the cooperation across the departments at MSK and the interdisciplinary work that we're able to do," Dr. Boire concludes. "We saw people getting sick, and we were able to use our observations to ask big clinical questions and then take these questions into the lab to answer them."

As human interaction with robots and artificial intelligence increases exponentially in areas like healthcare, manufacturing, transportation, space exploration, defense technologies, information about how humans and autonomous systems work within teams remains scarce.

Recent findings from human systems engineering research demonstrate that human-autonomy teaming comes with interaction limitations that can leave these teams less efficient than all-human teams.

Existing knowledge about teamwork primarily is based on human-to-human or human-to-automation interaction, which positions humans as supervisors of automated partners.

But as autonomy has increasingly developed decision-making skills based on spontaneous situation assessments, it can become a teammate rather than a servant. These shared decision interactions are identified as human-autonomy teaming, or HAT.

Nancy Cooke is a cognitive psychologist and professor of human systems engineering at the Polytechnic School at Arizona State University (ASU). She explores how an artificial intelligence agent can contribute to team communications failure, and how to improve those interactions, in her discussion at the annual meeting of the American Association for the Advancement of Science (AAAS).

As the director of ASU's Center for Human, Artificial Intelligence and Robot Teaming (CHART), a unit of the Global Security Initiative, Cooke applies her expertise in human teamwork and decision making to human-technology teams.

"One of the key aspects of being on a team is interacting with team members, and a lot of that on human teams happens by communicating in natural language, which is a bit of a sticking point for AI and robots," Cooke said.

Her discussion addresses a study in which teams of two humans and an AI, or "synthetic teammate," fly an unmanned aerial vehicle (UAV). The AI was the pilot, while the people served as a sensor operator and navigator.

The AI, developed by the Air Force Research Laboratory, communicated with the people via text chat.

"The team could function pretty well with the agent as long as nothing went wrong. As soon as things get tough or the team has to be a little adaptive, things start falling apart, because the agent isn't a very good team member."

The AI was unable to anticipate its teammates' needs the way humans do. As a result, it didn't provide critical information until asked -- it doesn't give a "heads up."

"The whole team kind of fell apart," Cooke said. "The humans would say, 'OK, you aren't going to give me any information proactively, I'm not going to give you any either.' It's everybody for themselves."

Cooke's presentation will address the importance of developing effective synthetic teammates and enhanced HAT interactions as these teams become more common and begin to engage in complex and dynamic environments beyond the UAV study parameters.

How did rocks rust on Earth and turn red? A Rutgers-led study has shed new light on the important phenomenon and will help address questions about the Late Triassic climate more than 200 million years ago, when greenhouse gas levels were high enough to be a model for what our planet may be like in the future.

"All of the red color we see in New Jersey rocks and in the American Southwest is due to the natural mineral hematite," said lead author Christopher J. Lepre, an assistant teaching professor in the Department of Earth and Planetary Sciences in the School of Arts and Sciences at Rutgers University-New Brunswick. "As far as we know, there are only a few places where this red hematite phenomenon is very widespread: one being the geologic 'red beds' on Earth and another is the surface of Mars. Our study takes a significant step forward toward understanding how long it takes for redness to form, the chemical reactions involved and the role hematite plays."

The research by Lepre and a Columbia University scientist is in the journal Proceedings of the National Academy of Sciences. It challenges conventional thinking that hematite has limited use for interpreting the ancient past because it is a product of natural chemical changes that occurred long after the beds were initially deposited.

Lepre demonstrated that hematite concentrations faithfully track 14.5 million years of Late Triassic monsoonal rainfall over the Colorado Plateau of Arizona when it was on the ancient supercontinent of Pangea. With this information, he assessed the interrelationships between environmental disturbances, climate and the evolution of vertebrates on land.

Lepre examined part of a 1,700-foot-long rock core from the Chinle Formation in the Petrified Forest National Park in Arizona (the Painted Desert) that is housed at Rutgers. Rutgers-New Brunswick Professor Emeritus Dennis V. Kent examined the same core for a Rutgers-led study that found that gravitational tugs from Jupiter and Venus slightly elongate Earth's orbit every 405,000 years and influenced Earth's climate for at least 215 million years, allowing scientists to better date events like the spread of dinosaurs.

Lepre measured the visible light spectrum to determine the concentration of hematite within red rocks. To the scientists' knowledge, it is the first time this method has been used to study rocks this old, dating to the Late Triassic epoch more than 200 million years ago. Many scientists thought the redness was caused much more recently by the iron in rocks reacting with air, just like rust on a bicycle. So for decades, scientists have viewed hematite and its redness as largely unimportant.

"The hematite is indeed old and probably resulted from the interactions between the ancient soils and climate change," Lepre said. "This climate information allows us to sort out some causes and effects - whether they were due to climate change or an asteroid impact at Manicouagan in Canada, for example - for land animals and plants when the theropod dinosaurs (early ancestors of modern birds and Tyrannosaurus rex) were rising to prominence."

The scientists, in collaboration with Navajo Nation members, have submitted a multi-million dollar grant proposal to retrieve more cores at the Colorado Plateau that will include rocks known to record a very rapid atmospheric change in carbon dioxide similar to its recent doubling as a result of human activity.

Prompted by the need to improve conventional treatments for people infected with the human immunodeficiency virus (HIV-1), a team from the Institut national de la recherche scientifique (INRS) has identified a therapeutic approach to restore the effectiveness of immune cells. The study, led by doctoral student Hamza Loucif and Professor Julien van Grevenynghe, was published in the journal Autophagy.

Most people infected with HIV-1 require daily antiretroviral therapy to control the infection. These drugs cause significant side effects without fully restoring the normal functioning of the immune system. Yet, a specific group of patients, called "elite controllers", are able to live with the infection without any drug intervention.

"They represent an incredible model for detecting, at the molecular level, what needs to be improved for other patients," says Professor Julien van Grevenynghe. "That's why the team of immunologists wanted to find out what differentiates them from conventionally treated patients to develop new weapons against infection."

Scientists demonstrated that the strength of elite controllers comes from their energy metabolism within CD8 lymphocytes. "Cells require energy, produced in the mitochondria to protect the body and carry out their functions. However, this energy is not used effectively by treated patients. Due to a deregulation of the metabolism, the cells are weakened in their immune function," explains Professor van Grevenynghe, who has worked on HIV for 15 years.

Re-educating cells

This energy deficiency is not permanent. Indeed, the research team demonstrated that CD8 lymphocytes can be "re-educated" using a soluble protein that optimizes their energy intake and immune function. "The protein, called interleukin-21 (IL-21), restores mitochondrial energy metabolism through a cell recycling process called autophagy. For elite controllers, the degradation of lipid reserves through autophagy, or lipophagy, is highly effective," explains the Ph.D. student.

"These results have an undeniable therapeutic interest, as the protein already exists! Moreover, the mere fact that elite controllers exist is proof in itself that we will one day be able to survive the infection without aggressive treatment," Professor van Grevenynghe enthusiastically points out. "We might ultimately be thinking about ending the treatment. The cells could also respond better to vaccination and treatment with better energy efficiency."

All the immune protection associated with CD8 lymphocytes comes from the presence of CD4 lymphocytes. These cells act as orchestra conductors' cells of the immune system. Therefore, the research team wants to determine if CD4 lymphocytes also have a metabolic advantage. Ultimately, the group wants to test their therapeutic approach in humanized mouse models and even macaques.

An additional benefit of this breakthrough is that the results of the study would not be limited to HIV-1 alone. "A comparison can be made with other pathologies associated with persistent inflammation, such as cancer, diabetes and even COVID-19 with lung inflammation," notes Julien van Grevenynghe.

A new machine-learning framework uses reported test results and death rates to calculate estimates of the actual number of current COVID-19 infections within all 50 U.S. states and 50 countries. Jungsik Noh and Gaudenz Danuser of the University of Texas Southwestern Medical Center present these findings in the open-access journal PLOS ONE on February 8, 2021.

During the ongoing pandemic, U.S. states and many countries have reported daily counts of COVID-19 infections and deaths confirmed by testing. However, many infections have gone undetected, resulting in under-counting of the total number of people currently infected at any given point in time--an important metric to guide public health efforts.

Now, Noh and Danuser have developed a computational model that uses machine-learning strategies to estimate the actual daily number of current infections for all 50 U.S. states and the 50 most-infected countries. To make the calculations, the model draws on previously published pandemic parameters and publicly available daily data on confirmed cases and deaths. Visualizations of these daily estimates are freely available online.

The model's estimates indicate severe undercounting of cases across the U.S. and worldwide. The cumulative number of actual cases in 9 out of 50 countries is estimated to be at least five times higher than confirmed cases. Within the U.S., estimates of the cumulative number of actual cases within states were in line with the results of an antibody testing study conducted in 46 states.

For some countries, such as the U.S., Belgium, and the U.K., estimates indicate that more than 20 percent of the total population has experienced infection. As of January 31, 2021, some U.S. states--including Pennsylvania, Arizona, and Florida--have currently active cases totaling more than 5 percent of the state's entire population. In Washington, the active cases were estimated to be one percent of the population that day.

Looking ahead, the model has been estimating current COVID-19 case counts within communities, which could help inform contact-tracing and other public health efforts.

The authors add: "Given that the confirmed cases only capture the tip of the iceberg in the middle of the pandemic, the estimated sizes of current infections in this study provide crucial information to determine the regional severity of COVID-19 that can be misguided by the confirmed cases."

Scientists at HSE University have learned that disagreeing with the opinion of other people leaves a 'trace' in brain activity, which allows the brain to later adjust its opinion in favour of the majority-held point of view. The article was published in Scientific Reports.

We often change our beliefs under the influence of others. This social behavior is called conformity and explains varios components of our behaviour, from voting at elections to fashion trends among teenagers.

Brain research has recently well informed about short-term effects of social influence on decision making. If our choice coincides with the point of view of the people who are important to us, this decision is reinforced in the brain's "pleasure" centres involved in the larger dopaminergic system responsible for learning, motor activity and many other functions. Conversely, in instances of disagreement with others, the brain signals that a 'mistake' has been made and triggers conformity.

However, there is little study of how social influence affects brain activity once some time has passed after we have formed an opinion and learned of the opinion held by others. HSE neuroscientists decided to study whether the opinion of others causes long-term changes in brain activity. The scientists used magnetoencephalography (MEG), a unique method that allows you to see in detail activity of the human brain during information processing, and it has a temporal resolution higher than that of traditional fMRI.

At the beginning of the experiment, 20 female participants rated the degree to which they trusted strangers whose faces were depicted in a series of photographs. They then were informed about the collective opinion of a large group of peers on whether to trust these strangers. Sometimes the opinion of the group contradicted the opinion of the participants, and sometimes it coincided with it. After half an hour, the subjects were asked to reassess their trust to the same strangers.

The study showed that the participants changed their opinion about a stranger under the influence of their peers in about half of the cases. In addition, changes occurred in their brain activity: scientists discovered 'traces' of past disagreements with peers. When the subjects again saw the face of a stranger, after a split second, their brain signaled that last time their personal opinion did not coincide with the assessment given by their peers. Most likely, the fixation of this signal allows the brain to predict possible conflicts in the future arising from disagreements in order to avoid them, and this probably occurs subconsciously.

It is interesting that an area such as the superior parietal cortex, an area of the brain responsible for retrieving memories, is involved in coding the signal of past disagreements with the group. It is likely that the faces of strangers, about whom the brain encountered a difference of opinion, are remembered better than others.

Thus, the opinions of others not only influence our behavior, but also cause long-term changes in the way our brains work. Apparently, the brain not only quickly adjusts to the opinions of others, but also begins to perceive information through the eyes of the majority in order to avoid social conflicts in the future.

'Our study shows the dramatic influence of others's opinion on how we perceive information,' says HSE University Professor Vasily Klucharev, one of the authors of the study. 'We live in social groups and automatically adjust our opinions to that of the majority, and the opinion of our peers can change the way our brain processes information for a relatively long time.'

'It was very interesting to use modern methods of neuro-mapping and to see traces of past conflicts with the opinion of the group in the brain's activity,' adds Aleksei Gorin, a PhD student at HSE University. 'The brain absorbs the opinion of others like a sponge and adjusts its functions to the opinion of its social group.'

Geoscientists have released a video that for the first time shows the uninterrupted movement of the Earth's tectonic plates over the past billion years.

The international effort provides a scientific framework for understanding planetary habitability and for finding critical metal resources needed for a low-carbon future.

It reveals a planet in constant movement as land masses move around the Earth's surface, for instance showing that Antarctica was once at the equator.

The video is based on new research published in the March 2021 edition of Earth-Science Reviews.

Co-author and academic leader of the University of Sydney EarthByte geosciences group, Professor Dietmar Müller, said: "Our team has created an entirely new model of Earth evolution over the last billion years.

"Our planet is unique in the way that it hosts life. But this is only possible because geological processes, like plate tectonics, provide a planetary life-support system."

Lead author and creator of the video Dr Andrew Merdith began work on the project while a PhD student with Professor Müller in the School of Geosciences at the University of Sydney. He is now based at the University of Lyon in France.

Co-author, Dr Michael Tetley, who also completed his PhD at the University of Sydney, told Euronews: "For the first time a complete model of tectonics has been built, including all the boundaries"

"On a human timescale, things move in centimetres per year, but as we can see from the animation, the continents have been everywhere in time. A place like Antarctica that we see as a cold, icy inhospitable place today, actually was once quite a nice holiday destination at the equator."

Co-author Dr Sabin Zahirovic from the University of Sydney, said: "Planet Earth is incredibly dynamic, with the surface composed of 'plates' that constantly jostle each other in a way unique among the known rocky planets. These plates move at the speed fingernails grow, but when a billion years is condensed into 40 seconds a mesmerising dance is revealed.

"Oceans open and close, continents disperse and periodically recombine to form immense supercontinents."

Earth scientists from every continent have collected and published data, often from inaccessible and remote regions, that Dr Andrew Merdith and his collaborators have assimilated over the past four years to produce this billion-year model.

It will allow scientists to better understand how the interior of the Earth convects, chemically mixes and loses heat via seafloor spreading and volcanism. The model will help scientists understand how climate has changed, how ocean currents altered and how nutrients fluxed from the deep Earth to stimulate biological evolution.

Professor Müller said: "Simply put, this complete model will help explain how our home, Planet Earth, became habitable for complex creatures. Life on Earth would not exist without plate tectonics. With this new model, we are closer to understanding how this beautiful blue planet became our cradle."

Key points:

Plate tectonics are responsible for the deep-carbon and deep-water cycles.

Arrangement of continents has changed sea level in the past.

The evolution of life is modified by tectonics - continents are rafts with evolving species that mix when continents combine.

A growing focus on renewable and low-carbon technologies will mean we need to find more copper and other resources. To find these deposits our new models of plate tectonics will help reduce the environmental footprint of mineral exploration and extraction.

This discovery was made possible by applying the research method for the comparison of the brain activity between monkeys and humans to artificial neural networks. This finding might be helpful not only to understand the cortical mechanism of attentional selection but also to develop artificial intelligence.

Deep neural networks (DNNs), which are used in the development of artificial intelligence, are mathematical models for obtaining appropriate mechanisms to solve specific problems from the training with a large-scale dataset. However, the detailed mechanisms underlying DNNs through this learning process have not yet been clarified.

A research group led by Nobuhiko Wagatsuma, Lecturer at the Faculty of Science, Toho University, Akinori Hidaka, Associate Professor at the Faculty of Science and Engineering, Tokyo Denki University, and Hiroshi Tamura, Associate Professor at the Graduate School of Frontiers Biosciences, Osaka University, found that the characteristics of responses in DNNs for predicting the attention to the most important location in images were consistent with those of the neural representation in the primary visual cortex (V1) of primates. The discovery was made possible by applying the analysis method designed for comparing the characteristics of the neuronal activity in monkeys with that in humans to DNNs.

The result of this study provides important insight into the neural mechanism of attention. Additionally, the application of the attentional mechanism in the primates including human may accelerate the development of artificial intelligence.

Key Points:

The correspondence between primate visual cortices and deep neural networks has been revealed by applying the research method for comparing the neural activity between different species, such as humans and monkeys, to artificial neural networks.

Recently, deep neural networks are utilized as the main methods for developing artificial intelligence. Wagatsuma et al. have reported the similar properties between deep neural networks for predicting attention and the primary visual cortex (V1) of primates. Additionally, their findings implied that the mechanism of the deep neural networks for attention prediction might be distinct from that for object classification such as VGG 16.

Attention is a function that enables us to attend the most important information at the moment, which is the most critical keyword in the recent development of artificial intelligence. The results of this research might provide contributions not only for understanding the neural mechanisms for attention selection of primates including human but also for developing artificial intelligence.