Culture

Researchers from Rutgers Cancer Institute of New Jersey, the state's only National Cancer Institute-designated Comprehensive Cancer Center, evaluated the frequency of SARS-CoV-2, the virus that causes COVID-19, on various environmental surfaces in outpatient and inpatient hematology/oncology settings located within Rutgers Cancer Institute and Robert Wood Johnson University Hospital, an RWJBarnabas Health facility. The study revealed extremely low detection of SARS-CoV-2 on environmental surfaces across multiple outpatient and inpatient oncology areas, including an active COVID-19 floor. Andrew M. Evens, DO, MSc, FACP, associate director for clinical services and director of the Lymphoma Program at Rutgers Cancer Institute and medical director of the oncology service line at RWJBarnabas Health, is senior author of the work, which has been published in the February 18 online edition of Cancer. (doi: 10.1002/cncr.33453)

Patients harboring hematologic malignancies, which are cancers that affect the blood, bone marrow, and lymph nodes, have demonstrated a potential higher mortality rate due to the virus. While COVID-19 is transmitted person to person through respiratory droplets, it has been hypothesized that there is a potential risk of SARS-CoV-2 spreading via contact with contaminated surfaces and equipment, especially in healthcare settings, creating additional concern for patients with blood cancers.

"For patients with blood cancers who may be at higher risk of developing complications from the virus, our findings provide a layer of assurance that these patients are safe when frequenting high impact areas where they receive their cancer care," notes Dr. Evens, who is also a professor of medicine at Rutgers Robert Wood Johnson Medical School. "The results of this study help us further understand how COVID-19 is transmitted in hematology/oncology and other medical settings, and confirm that strategies like enhanced cleaning and disinfecting policies are extremely effective."

Environmental swabbing took place in two outpatient clinics including the malignant hematology and medical oncology units and infusion suites as well as inpatient areas which included the leukemia/lymphoma/CAR T-cell unit, and an inpatient unit caring for patients actively infected with COVID-19. Surfaces were sampled on Mondays, Wednesdays and Fridays from June 17, 2020 through June 29, 2020. Areas included waiting rooms, infusion areas, bathrooms, floors, elevator banks, doors, and exam rooms, computer equipment, pneumatic tubing stations, pharmacy benches, and medication rooms. Medical equipment was also swabbed from these areas including intravenous poles, chemotherapy bags, vitals monitor, telemetry stations, and linen carts.

Analysis of the 130 samples collected were separated into three categories: patient/public areas (85), staff areas (22), and medical equipment (23). In the two outpatient clinics and inpatient leukemia/lymphoma/CAR T-cell unit, no SARS-CoV-2 RNA was detected on any swabbed surfaces. In the inpatient COVID unit, one patient/public sample was positive for detection of SARS-CoV-2 RNA in an area where a patient with recent infection was receiving treatment.

Thus, the overall positive test rate for SARS-CoV-2 RNA across all surfaces in the combined outpatient and inpatient hematology/oncology units was a low 0.5 percent.

The authors note study limitations including the inability to analyze the complete surface area of the varied locations, which may have reduced sensitivity. In addition, researchers did not attempt to culture SARS-CoV-2 from the one positive sample; it is unknown if it contained live virus. Continued studies are needed to monitor rates of virus transmission and the environmental factors involved in the propagation of the SARS-CoV-2 infection.

When there is a choice, wolves in Mongolia prefer to feed on wild animals rather than grazing livestock. This is the discovery by a research team from the University of Göttingen and the Senckenberg Museum Görlitz. Previous studies had shown that the diet of wolves in inland Central Asia consists mainly of grazing livestock, which could lead to increasing conflict between nomadic livestock herders and wild predatory animals like wolves. The study has been published in the journal Mammalian Biology.

Around three million people live in Mongolia, making it the most sparsely populated country in the world. In addition, there are more than 40 million grazing animals. These animals are not just a source of food but also the only source of income for more than half of the population. Livestock cultivation is leading to a massive change in Mongolia's landscape: areas close to nature are increasingly being converted into pastureland: in fact, one third of the country is now used for this purpose. This inevitably leads to conflict with the indigenous wild animals, especially large predators such as the wolf.

Biologist and forest scientist Nina Tiralla from the University of Göttingen studied the feeding behaviour of wolves for her Master's thesis. Together with colleagues from the Senckenberg Museum, she analysed 137 wolf droppings collected during fieldwork in Mongolia between 2008 and 2012. "We were able to show that 89 percent of the wolves' diet consisted of wild ungulates, predominantly Siberian roe deer," says Tiralla. "The remaining 11 per cent consisted of small mammals such as hares or mice." Even remnants of insects and berries could be detected in the faeces - but there was no trace of farmed animals. "This was surprising for us because previous studies had shown grazing animals to be the main food source for wolves," says Tiralla.

The key difference could lie in the situation of the animals: unlike the earlier studies on Mongolian wolves, the samples examined in this study come from near-natural regions with high species diversity. "Although there is also a supply of grazing animals here, the wolves seem to prefer wild animals such as the Siberian roe deer as prey, possibly because they are easier and less dangerous to hunt," the authors explain. They conclude that if wolves live in a near-natural and species-rich landscape with sufficient prey, they pose only a very low threat to grazing livestock. This could apply not only in Mongolia, but in principle also to other countries.

CHAMPAIGN, Ill. -- Researchers report that 4-6-year-old children who walk further than their peers during a timed test - a method used to estimate cardiorespiratory health - also do better on cognitive tests and other measures of brain function. Published in the Journal of Clinical Medicine, the study suggests that the link between cardiorespiratory fitness and cognitive health is evident even earlier in life than previously appreciated.

Most studies of the link between fitness and brain health focus on adults or preadolescent or adolescent children, said doctoral student Shelby Keye, who led the new research with Naiman Khan, a professor of kinesiology and community health at the University of Illinois Urbana-Champaign. Such research has consistently found positive correlations between people's aerobic exercise capacity and their academic achievement and cognitive abilities, she said. Studies have found that higher cardiorespiratory fitness in older children and adults corresponds to the relative size and connectivity of brain structures that are important to cognitive control.

"But it isn't yet known at what point in the developmental trajectory of childhood this relationship emerges," Keye said.

Previous reports suggest that, just like older children and adults, preschoolers are failing to meet daily recommended guidelines for physical activity.

"This is worrisome, since brain development of core cognitive control processes begins in early childhood and continues well into early adulthood," Khan said. And yet, studies of this age group are limited, he said.

To better understand the relationship between cardiorespiratory fitness and brain health in 59 preschool-aged children, the researchers subjected them to several tests. The children walked as far as they could in six minutes, a test that allowed researchers to estimate their cardiorespiratory fitness. An early cognitive and academic development test gave the team a measure of each child's intellectual abilities, and a computerized "flanker" task measured how well they were able to focus on the important part of an image while ignoring distracting information. Participants also took part in a computerized task that required them to alter their responses depending on whether flowers or hearts appeared on the screen - a measure of mental flexibility.

A subset of 33 children also engaged in an auditory task that required them to respond to certain sounds and not others while wearing an EEG cap. The EEG measured electrical activity during the cognitive control task.

"The EEG offers a noninvasive way to measure children's ability to pay attention despite distractions and process information in real time as they complete tasks," Keye said.

Statistical analyses revealed a relationship between the children's physical fitness and their cognitive abilities and brain function, the researchers said.

"Preschool children with higher estimated cardiorespiratory fitness had higher scores on academic ability tasks related to general intellectual abilities as well as their use of expressive language," Keye said. "They had better performance on computerized tasks requiring attention and multitasking skills, and they showed the potential for faster processing speeds and greater resource allocation in the brain when completing these computerized tasks."

The study does not prove that cardiorespiratory fitness enhances cognitive abilities in young children but adds to a growing body of evidence that the two are closely linked - even in children as young as four years old, the researchers said.

A new study concluding out of Lusaka, Zambia last summer has found that as many as 19% (almost 1 in 5) of recently-deceased people tested positive for COVID-19.
A new Boston University School of Public Health (BUSPH) study in Lusaka, Zambia's capital, challenges the common belief that Africa somehow "dodged" the COVID-19 pandemic.

The findings indicate that low numbers of reported infections and deaths across Africa may simply be from lack of testing, with the coronavirus taking a terrible but invisible toll on the continent.

Published in The BMJ, the study found that at least 15% and as many as 19% of recently-deceased people arriving at Lusaka's main morgue over the summer had the coronavirus, peaking at 31% in July. Despite most having had COVID symptoms, few were tested before death.

"Our findings cast doubt on the assumption that COVID-19 somehow skipped Africa or has not impacted the continent as heavily," says study co-author Dr. Lawrence Mwananyanda, a BUSPH adjunct research assistant professor of global health based in Lusaka. "This study shows that with proper diagnostics and testing, we can begin to identify the scale of COVID-19 in African countries such as Zambia. I hope this study will encourage African governments to look closer at the rollout of COVID-19 testing, as well as empower Africans to take proactive steps--such as wearing masks, physically distancing, and skipping handshakes--to protect themselves from COVID-19."

The findings also have important implications for global health decision makers, says study corresponding author Dr. Christopher Gill, associate professor of global health at BUSPH. "We will only end the COVID-19 pandemic if we ensure equitable access to a vaccine. Without the full data picture of the spread of COVID-19 in Africa, it will be impossible to ensure COVID-19 vaccines can get to the people and places that need it most," he says.

An estimated 80% of people who die in Lusaka pass through the University Teaching Hospital morgue. From June to September, polymerase chain reaction tests on 364 recently-deceased people found the coronavirus in 70 of them. While the majority of COVID-19 deaths in the United States and Europe have been in older adults, most of the deceased people who tested positive in this study were under 60 years old, including seven children. The researchers say that such a high proportion of pediatric deaths was particularly surprising given how rare COVID-19 deaths in children have been reported elsewhere.

Of the 70 people who tested positive, the researchers sought information about the symptoms they had been experiencing leading up to their fatal illness. "In nearly all cases where we had those data, we found typical symptoms for COVID-19, yet only 6 had been tested before death," Gill says. And among the 75% of deaths that occurred outside of the hospital, none had been tested before they died.

However, detecting the coronavirus in any country is no easy feat, much less in countries with limited resources. The researchers say Zambia's Ministry of Health has been very proactive and supportive of this and other COVID studies. "They're really grateful that we can provide them this data, and they can make informed decisions moving forward with this epidemic," Mwananyanda says.

The researchers were well-positioned to track COVID in Zambia. With funding from the Bill & Melinda Gates Foundation, they have been conducting the Zambia Pertussis/RSV Infant Mortality Estimation Study (ZPRIME) at the University Teaching Hospital morgue in Lusaka since 2017. In that ongoing study, nurses and physicians' assistants approach families who have lost a child between the ages of four days and six months for consent to conduct a nasal swab of the infant, and to offer grief counseling.

"Building studies such as this from scratch can take time and resources that can be difficult in the time needed to tackle the COVID-19 pandemic. We invested a lot of time and money and human resources to building infrastructure that allowed for that extensive surveillance," says study co-author Rachel Pieciak a research fellow at BUSPH. "So, what we've done was repurpose ZPRIME study capacity to focus on enrolling all deaths across all ages and testing for COVID-19."

Other research teams in similar situations might also be able to pivot in this way, Pieciak says. While many governments don't have the resources to effectively track COVID rates, "there's a lot of research money in places where we're not seeing really great COVID data," she says. "I would encourage other groups like us to think creatively about the resources that they have available, and to contribute to this effort."

For their part, the research team's findings will help inform COVID-19 efforts not just in Zambia, but many other countries. "What this study tells us is that when we looked for COVID-19 in Zambia, we found it--and there are a whole lot of other countries where there's similar lack of testing," says study co-author Dr. William MacLeod, research associate professor of global health at BUSPH.

MALVERN, Pa. -- Doctors and healthcare workers may one day use a machine learning model, called deep learning, to guide their treatment decisions for lung cancer patients, according to a team of Penn State Great Valley researchers.

In a study, the researchers report that they developed a deep learning model that, in certain conditions, was more than 71 percent accurate in predicting survival expectancy of lung cancer patients, significantly better than traditional machine learning models that the team tested. The other machine learning models the team tested had about a 61 percent accuracy rate.

Information on a patient's survival expectancy could help guide doctors and caregivers in making better decisions on using medicines, allocating resources and determining the intensity of care for patients, according to Youakim Badr, associate professor of data analytics.

"This is a high-performance system that is highly accurate and is aimed at helping doctors make these important decisions about providing care to their patients," said Badr. "Of course, this tool can't be used as a substitute for a doctor in making decisions on lung cancer treatments."

According to Robin G. Qiu, professor of information science and engineering and an affiliate of the Institute for Computational and Data Sciences, the model can analyze a large amount of data, typically called features in machine learning, that describe the patients and the disease to understand how a combination of factors affect lung cancer survival periods. Features can include information such as types of cancer, size of tumors, the speed of tumor growth and demographic data.

Deep learning may be uniquely suited to tackle lung cancer prognosis because the model can provide the robust analysis necessary in cancer research, according to the researchers, who report their findings in International Journal of Medical Informatics. Deep learning is a type of machine learning that is based on artificial neural networks, which are generally modelled on how the human brain's own neural network functions.

In deep learning, however, developers apply a sophisticated structure of multiple layers of these artificial neurons, which is why the model is referred to as "deep." The learning aspect of deep learning comes from how the system learns from connections between data and labels, said Badr.

"Deep learning is a machine-learning algorithm that makes associations between the data, itself, and the labels that we use to describe the data examples," said Badr. "By making these associations, it learns from the data."

Qiu added that deep learning's structure offers several advantages for many data science tasks, especially when confronted with data sets that have a large number of records -- in this case, patients -- as well as a large number of features.

"It improves performance tremendously," said Qiu. "In deep learning we can go deeper, which is why they call it that. In traditional machine learning, you have a simple structure of layers of neural networks. In each layer, you have a group of cells. In deep learning, there are many layers of these cells that can be architected into a sophisticated structure to perform better feature transformation and extraction, which gives you the ability to further improve the accuracy of any model."

In the future, the researchers would like to improve the model and test its ability to analyze other types of cancers and medical conditions.

"The accuracy rate is good so far -- but it's not perfect, so part of our future work is to improve the model," said Qiu.

To further improve their deep learning model, the researchers would also need to connect with domain experts, who are people who have specific knowledge. In this case, the researchers would like to connect with experts on specific cancers and medical conditions.

"In a lot of cases, we might not know a lot of features that should go into the model," said Qiu. "But, by collaborating with domain experts, they could help us collect important features about patients that we might not be aware of and that would further improve the model."

The researchers analyzed data from the Surveillance, Epidemiology, and End Results (SEER) program. The SEER dataset is one of the biggest and most comprehensive databases on the early diagnosis information for cancer patients in the United States, according to Shreyesh Doppalapudi, a graduate student research assistant and first author of the paper. The program's cancer registries cover almost 35 percent of the U.S. cancer patients.

"One of the really good things about this data is that it covers a large section of the population and it's really diverse," said Doppalapudi. "Another good thing is that it covers a lot of different features, which you can use for many different purposes. This becomes very valuable, especially when using machine learning approaches."

Doppalapudi added that the team compared several deep learning approaches, including artificial neural networks, convolutional neural networks and recurrent neural networks, to traditional machine learning models. The deep learning approaches performed much better than the traditional machine learning methods, he said.

Deep learning architecture is better suited to processing such large, diverse datasets, such as the SEER program, according to Doppalapudi. Working on these types of datasets requires robust computational capacity. In this study, the researchers relied on ICDS's Roar supercomputer.

With about 800,000 to 900,000 entries in the SEER dataset, the researchers said that manually finding these associations in the data with an entire team of medical researchers would be extremely difficult without assistance from machine learning.

"If it were just three fields, I would say it would be impossible, but, we had about 150 fields," said Doppalapudi. "Understanding all of those different fields and then reading and learning from that information, would just be near impossible."

Mount Sinai researchers have discovered that Polycomb complexes, groups of proteins that maintain gene expression patterns, are essential for proper skin development, according to a paper published in Genes & Development on February 18. This latest discovery could improve development of future stem cell therapies to generate "skin on a dish" to transplant into burn victims and patients with skin-blistering disorders.

Polycomb complexes are groups of proteins that maintain the gene-expression patterns during early development by regulating the structure of DNA and proteins in cells. They play a critical role in the repression of gene expression, or the switching-off of individual genes to help control responses to changing environments and stimuli. The researchers found that Polycomb repressive complex 1 (PRC1) and Polycomb repressive complex 2 (PRC2) each help maintain the skin-specific gene expression pattern necessary for proper development of the skin.

The researchers studied Polycomb complexes in the developing skin of mice. Mice that were bred missing either Polycomb complex still had a functioning skin barrier, albeit with minor defects in skin thickness. In contrast, when researchers bred mice missing both complexes, it resulted in severe skin defects including a significantly thin epidermis that lacked essential layers required for survival. The researchers found that PRC1 and PRC2 help maintain regular function of gene repression, in particular the repression of transcription factors essential for the formation of non-skin tissues.

"We show that Polycomb complexes function redundantly to control proper development of the skin," said the study's corresponding author Elena Ezhkova, PhD, Professor of Cell, Developmental and Regenerative Biology, and Dermatology in the Black Family Stem Cell Institute at the Icahn School of Medicine at Mount Sinai. "Polycomb complexes function together to repress non-skin lineage programs and thus control proper skin development."

The researchers said their discovery has implications for development of stem cell therapies to produce "skin on a dish" to use for transplantation. Since Mount Sinai researchers have established that both Polycomb complexes are vital for skin formation, this discovery could improve current protocols for generating skin cells from stem cells. Polycomb complexes are also often overexpressed in epithelial cancers, including skin cancers, and treatments using Polycomb inhibitors are currently being studied in clinical trials. This study suggests that parallel inhibition, use of both PRC1 and PRC2 inhibitors, may be a more powerful form of treatment for cancer patients.

While Polycomb complexes are important for skin function, their role in other tissues remains unknown. Future studies should explore the role of Polycomb complexes in developing and regenerating tissues, the researcher said.

Richer countries were more likely to see rates of COVID-19 fall faster during the first wave of the pandemic, according to new research published in the journal Frontiers in Public Health.

The study by Anglia Ruskin University (ARU) professors Shahina Pardhan and Nick Drydakis examined economic indicators in 38 European countries, such as Gross Domestic Product (GDP) per capita, life expectancy, and public spending, and the number of new coronavirus cases per million of the population between 1 April and 31 May 2020, using data from Our World in Data based on the seven-day rolling average of new cases for each country.

A significant negative correlation was found between number of cases and GDP per capita across the two months. The study found that the country with the highest GDP per capita in Europe (Luxembourg) experienced the biggest fall in cases (271 per million of the population). The opposite was found for countries with lower GDP per capita, such as Ukraine (fell by one case per million) and Romania (fell by seven cases per million).

Researchers concluded that countries with higher GDP per capita were able to spend more on test and trace solutions, public health messaging and had economies that better facilitated home working than poorer nations. The UK recorded a reduction from 3,706 new cases on 1 April to 1,500 new cases on 31 May, a reduction of 20 cases per million of the population during this time.

Lead author Professor Shahina Pardhan, of ARU's School of Medicine, said: "Our study found a strong negative correlation between number of cases and GDP per capita. This is not only potentially down to the ability of wealthier nations to spend more on healthcare and prevention, but it is possible that suppressing the spread through lockdowns is more difficult to implement in poorer countries where there are a greater number of people working in sectors where manual labour is needed.

"COVID-19 is a global issue and has spread rapidly from country to country. It does not discriminate, and it is in everybody's best interests to ensure that poorer countries are given the assistance they need to fight this virus during this second wave and beyond."

NEW YORK, NY (Feb. 18, 2021)--A research team at the Center of Prevention and Evaluation (COPE) at Columbia University Irving Medical Center and the New York State Psychiatric Institute, led by Drs. Gary Brucato and Ragy R. Girgis, found that, contrary to popular belief, serious mental illness was present in only 11% of all mass murderers and in only 8% of mass shooters.

The study--the first published report on mass shootings from the Columbia Mass Murder Database--appeared online Feb. 17th in Psychological Medicine.

The investigators sought to gain much-needed insight into the relationship between serious mental illness and mass shootings. Creating the database involved extensive review of 14,785 murders publicly described in English in print or online, occurring worldwide between 1900 and 2019.

In the study, the investigators analyzed 1,315 mass murders of all types, from all over the world, to better understand mass shooting events.

People who committed mass murder by other means, such as fire, explosives, poison, stabbing, bludgeoning, or driving vehicles into crowds, had a prevalence of serious mental illness of 18%. Although almost two-thirds of all mass murders were committed with firearms, non-firearm means resulted in significantly more casualties per event.

Examining a wide array of demographic, psychological and other background features of mass murderers available in multiple public reports, the researchers also found that U.S.-based mass shooters were more likely to have legal histories, use recreational drugs or misuse alcohol, or have histories of non-psychotic psychiatric or neurologic symptoms."

They also reported that non-automatic firearms are the weapon of choice of most mass shooters. Furthermore, the investigators found that, among mass shooters in the U.S., the only distinguishing factor between those who used non-automatic vs. semi-automatic weapons is that individuals with any psychiatric or neurologic condition were more likely to use semi-automatic weapons. These findings may have key implications for the way background checks preceding weapon purchases should be conducted.

The authors also found that since 1970 the rate of mass shootings has been far greater than the rate of non-firearm mass murder, with the vast majority of mass shootings occurring in the United States.

Dr. Brucato remarked, "The findings from this potentially definitive study suggest that emphasis on serious mental illness, such as schizophrenia or psychotic mood disorders, as a risk factor for mass shootings is given undue emphasis, leading to public fear and stigmatization."

Coauthor Dr. Paul S. Appelbaum, known for his work on violence in psychiatric samples, noted, "These data suggest that other difficulties, such as legal problems, substance and alcohol use, and difficulty coping with life events seem more useful foci for prevention and policy than an emphasis on serious mental illness."

BOSTON -- COVID-19, the source of the current pandemic, may be caused by a single virus, but it has a variety of presentations that make treatment difficult. Children, for example, almost exclusively experience mild or asymptomatic COVID-19, while adults can develop severe or even fatal COVID-19. But children who contract COVID-19 are at risk for a rare but serious syndrome called multisystem inflammatory syndrome in children (MIS-C). Severe cases of MIS-C can lead to cardiac disease and ventricular failure, and require hospitalization and intense medical support.

Researchers Galit Alter, PhD, core member of the Ragon Institute of MGH, MIT and Harvard, and Lael Yonker, MD, director of the Massachusetts General Hospital Cystic Fibrosis Center, are working to understand why COVID-19 can lead to such distinctly different outcomes in different populations. In a study recently published in Nature Medicine, they and their team identified specific types of antibodies that may be driving these different responses, including one specific to severe disease in adults and another specific to MIS-C in children.

"We noticed children who developed MIS-C after COVID disease or exposure had high levels of a specific type of antibody called IgG," says Yonker. "Normally, IgG acts to control an infection, but with MIS-C, the IgG is triggering activation of immune cells, which may be driving the severe illness seen in MIS-C."

Specifically, explains Yonker, IgG antibodies interact with cells called macrophages, which live throughout the body's tissues. If there are too many IgG bodies activating these macrophages, this could cause inflammation in many different organs and systems, which is seen in MIS-C. These high levels of IgG antibodies were only found in children who developed MIS-C after contracting or being exposed to COVID-19.

Yonker, a pediatric pulmonologist at MGH and assistant professor at Harvard Medical School (HMS), runs a biorepository that collects samples from pediatric cystic fibrosis patients. When the pandemic hit, she began to collect samples from children with mild cases of COVID-19. When Yonker and other pediatricians began seeing children hospitalized with what is now called MIS-C, which typically onsets three to six weeks after developing COVID-19, she quickly began collecting those samples too. She wanted to understand how a mild case of COVID-19 could lead to severe MIS-C weeks after recovery.

Seeking a detailed understanding of the immune response, Yonker teamed up with Alter, who is also a professor at HMS and an immunologist in the Department of Infectious Diseases at MGH. Alter's team used her unique "systems serology" technology to carefully perform a detailed comparison of the immune responses in children--17 with MIS-C and 25 with mild COVID-19--to the responses of 26 adults with severe disease and 34 adults with mild disease.

"We were expecting the children's immune responses to look drastically different from the adults', regardless of the severity of disease," says Alter. "But instead, we found that adults with mild COVID-19 and children with COVID-19 had remarkably similar immune responses. It was only the adults with severe COVID-19 whose immune responses looked different."

For adults with severe COVID-19, Alter explains, they saw increased levels of IgA antibodies, which interact with a type of immune cells called neutrophils and cause the neutrophils to release cytokines. If there are too many IgA antibodies, the neutrophils may be pushed to release too many cytokines, which could contribute to a cytokine storm, one of the symptoms of severe COVID-19.

In both cases, the study shows, it may be a high level of a specific type of antibody causing the disease severity. "In MIS-C, high levels of IgG antibodies may be activating macrophages, which can drive inflammation in organs throughout the body," says Yannic Bartsch, PhD, the study's first author and a research fellow at the Ragon Institute. "In adults with severe COVID-19, high levels of IgA antibodies could be driving neutrophils to release too many cytokines, with the potential of causing a cytokine storm."

Identifying the immune mechanisms of multiple, distinct responses to the same virus is the first step to understanding why it mounts different responses in divergent populations. Discovering how the immune system's response shapes the disease and its outcome in both children and adults can help researchers develop treatments that can prevent or modulate the immune response, keeping its protective functions but lessening the unintentional, yet harmful, ones.

The effects of selective serotonin reuptake inhibitors (SSRIs) and other conventional antidepressants are believed to be based on their increasing the levels of serotonin and noradrenalin in synapses, while ketamine, a new rapid-acting antidepressant, is thought to function by inhibiting receptors for the neurotransmitter glutamate.

Neurotrophic factors regulate the development and plasticity of the nervous system. While all antidepressants increase the quantity and signalling of brain-derived neurotrophic factor (BDNF) in the brain, the drugs have so far been thought to act on BDNF indirectly, through serotonin or glutamate receptors.

A new study published this week in Cell demonstrates, however, that antidepressants bind directly to a BDNF receptor known as TrkB. This finding challenges the primary role of serotonin or glutamate receptors in the effects of antidepressants.

The international study, which was collaboratively led by the Neuroscience Center and the Department of Physics at the University of Helsinki, investigated the binding of antidepressants from different drug classes to the TrkB receptor. All the antidepressants examined, including fluoxetine (an SSRI), imipramine (a tricyclic antidepressant) and the rapid-acting ketamine interacted with TrkB.

"We found that all antidepressants boost BDNF signalling by binding to its TrkB receptor. This signalling is necessary for the cellular and behavioural effects of antidepressants in our experimental models. The effects of antidepressant on plasticity do not therefore require increases in the serotonin levels or the inhibition of glutamate receptors, as previously thought," says Professor Eero Castrén, the principal investigator of the study.

Molecular modelling helped to locate the binding site of antidepressants

The binding site of antidepressants in the transmembrane region of TrkB was identified through molecular modelling, performed in Professor Ilpo Vattulainen's research group at the Department of Physics, University of Helsinki. Biochemical binding studies and mutations introduced in the TrkB receptor verified the site.

Molecular modelling also demonstrated that the structure of TrkB is sensitive to the cholesterol concentration of the cell membrane. TrkB is displaced in cholesterol-rich membrane compartments, such as synaptic membranes.

"The drug binding stabilises dimers, structures composed of two TrkB receptors, inhibiting the displacement of the TrkB receptors and increasing their quantity in synaptic cell membranes, which boosts the effects of BDNF. That is to say that the drugs do not directly activate TrkB. Instead, they sensitise the receptor to the effects of BDNF," Castrén explains.

In addition to findings pertaining to the effects of antidepressants, the study produced a substantial amount of new information on the structure and function of the growth factor receptor.

Why does ketamine have such a rapid effect?

Ketamine, which has been used as an anaesthetic, is becoming increasingly utilized as an antidepressant. The researchers were surprised to find that both slow-acting SSRIs and rapid-acting ketamine act by binding to the same site in TrkB.

SSRI drugs bind to the serotonin transporter protein much more avidly than to TrkB, but the binding of ketamine to the glutamate receptor and TrkB occurs at similar drug concentrations.

"Previous studies have shown that in SSRI therapy, drugs gradually reach the high brain concentration needed for binding to the TrkB receptor, whereas intravenously administered ketamine and esketamine as a nasal spray reach the level needed for binding quickly, in a matter of minutes. The difference in the onset of action for SSRIs and ketamine may be caused by their different capacity to reach in the brain the concentration needed for binding with TrkB receptors," Castrén says.

While the human brain has over 400 miles of total vasculature, little is known about the tiny capillaries that make up much of this intricate labyrinth of blood vessels critical for delivering oxygenated blood and nutrients to billions of brain cells.

According to Dr. Andy Shih, a principal investigator in the Center for Developmental Biology and Regenerative Medicine at Seattle Children's Research Institute, understanding how this vast network regulates blood flow in the brain could hold the key to new treatments for neonatal and childhood neurologic conditions, such as stroke and hypoxia, and issues of aging like dementia and Alzheimer's disease.

"Insufficient blood flow contributes to many of the common neurologic problems seen in children and adults," he said. "Yet, because we can't see the capillaries, which measure about 1/10th the thickness of hair, with in vivo clinical imaging techniques, determining how blood travels through this densely packed bed of vessels has remained elusive."

Wanting to get a closer look, Shih and fellow scientists, Dr. Andree-Anne Berthiaume and Dr. David Hartmann, applied special techniques called two-photon imaging and optogenetics to isolate and study brain capillaries in animal models. Their findings published in Nature Neuroscience describe the dynamics that govern capillary blood flow in the brain and have broad implications for future avenues of brain research.

A cell painted on the blood vessel

In the study, the scientific team led by Shih focused on a cell type called a pericyte. Pericytes cover the capillary surface and are broadly categorized as a vascular mural cell.

"They're called mural cells because they adhere closely to the vessel wall (muralis is Latin for wall), but I to imagine it's like they're painted on the capillaries with long brushstrokes" Shih said. "Pericytes live on all of these brain capillaries, contacting more than 90% of this dense network. Unlike mural cells of arteries and arterioles, they have long appendages that don't surround the whole vessel."

Scientists have long debated if pericytes are structurally equipped to influence blood flow in the brain capillaries.

"Whether brain capillary pericytes constrict and dilate capillaries has remained a controversial hypothesis since they were discovered," Shih said. "Research exploring these dynamics in living organisms have resulted in mixed outcomes, with some studies supporting this theory, and others reporting the contrary."

Shih says there are many reasons brain capillary pericytes are challenging to study in vivo.

"The connectedness of vasculature makes it very difficult to isolate the effects of pericytes from arterioles that strongly, but indirectly, impact capillary blood flow in the brain," he said. "Capillaries also go undetected by most imaging technology that lack the resolution or are more focused on blood flow in the larger arteries."

Pinpointing the pericytes

The researchers proposed a specialized approach to study pericytes in a cell-specific manner.

"We used laser light like a switch to turn individual pericytes on. This was done by combining two-photon microscopy and optogenetics, something that has been done for years to stimulate neurons, but has only recently been applied to other cell types like pericytes," said Hartmann, a MD/PhD student who worked in Shih's lab and is now a medical intern at Stanford University. "The important thing is we could manipulate just one pericyte at a time to understand their specific role in blood flow regulation. Previous studies were unable to flip just one light switch, they turned on the entire circuit breaker."

Their methods involved first engineering animal models with pericytes that could be stimulated with light. Then, they captured the capillaries' response to stimulation using real-time imaging of the living brain.

"When we turned on pericytes, we observed a direct effect of decreased capillary blood flow," Hartmann said. "When we removed pericytes by ablating them with focused light, we observed an increase in capillary blood flow."

The findings confirmed that brain capillary pericytes in adult animal models do in fact regulate blood flow, with one key difference: it happens much more slowly than what is observed with upstream arteries arteries.

"Blood flow changes in arteries can shift within seconds whereas blood flood changes by capillary pericytes might happen over many minutes or even hours," Shih said.

When the research team introduced a clinically used drug, fasudil, known to relax blood vessels into the models, they were unable to manipulate the pericytes in the same way.

"Fasudil acted on the pericytes and stopped them from constricting to optogenetic stimulation," Shih said. "With this evidence, we can begin to think of different brain conditions where it may be possible to identify therapeutics able to relax the pericytes in the living brain and improve blood flow."

Implications for stroke and beyond

Stroke is one example of the broad implications of this research. In stroke, a clot forms causing blood flow to stop. Without oxygenated blood, brain tissue is rapidly damaged.

"Research has shown following a stroke or other conditions like brain or spinal cord injury, even as blood flow in arteries returns over time, capillary pericytes remain in a contracted state for a long time, impairing the entry of blood into the brain tissue," Shih said. "Clinical imaging will confirm normal blood flow in the big vessels, but what are the implications of impeding blood flow in these tiny vessels we can't see and how might we use therapeutics to alleviate that resistance?"

Their findings also extend to Alzheimer's disease, vascular dementia and other conditions of the aging brain marked by accelerated pericyte pathology. Future studies will investigate how loss of pericyte function impacts blood distribution in the brain. Other ongoing research is studying pericytes in vasculature of the developing brain.

"Now that we know more about the dynamics of pericytes in controlling blood flow in the healthy brain, we can start to look for changes to these pericyte functions during disease," said Berthiaume, a postdoctoral researcher in the Shih lab. "In other words, now that we know how pericytes should behave to support brain health, we can work to understand what happens when things go wrong like in stroke or injury."

Shih is also collaborating with Dr. Juliane Gust, a pediatric neurologist studying the neurological side effects of chimeric antigen receptor (CAR) T cell cancer immunotherapies. Studies have suggested pericytes express the same antigen the CAR T cells are programmed to target on cancer cells, causing the engineered cells to attack them. New models are needed to study this more closely in the lab.

"There are a lot of tantalizing questions to follow up on now that we have a better understanding of what capillary pericytes do in the healthy brain and improved tools to study them in the lab," Shih said.

The media has been rife with stories about democracy in decline: the recent coup in Myanmar, the ascent of strongman Narendra Modi in India, and of course ex-President Trump's attempts to overturn the U.S. presidential election--all of which raise alarms about the current status of democracies worldwide. Such threats to the voices of the people are often attributed to the excesses of individual leaders. But while leadership is certainly important, over the past decade, as established democracies like Venezuela and Turkey fell and others slid toward greater authoritarianism, political scientists and pundits have largely overlooked a key factor: how governments are funded. In a new study in the journal Current Anthropology, a team of anthropologists assembled data on 30 pre-modern societies, and conducted a quantitative analysis of the features and durability of "good governance"--that is, receptiveness to citizen voice, provision of goods and services, and limited concentration of wealth and power. The results showed that societies based on a broad, equitable, well-managed tax system and functioning bureaucracies were statistically more likely to have political institutions that were more open to public input and more sensitive to the well-being of the populace.

For more than a century, the accepted textbook account of democracy was that it was peculiarly modern, a purely Western phenomenon born of the "commercial restlessness" of European nations, with older agrarian/rural states viewed as static and authoritarian. However, the current crises of democratic "backsliding" have prompted a deeper dive by anthropologists and political historians into the core features, origins, and sustainability of modern democracy.

"The decline we are seeing today in many democratic governments is difficult to get a handle on," says Richard Blanton, professor emeritus at Purdue University, and the study's lead author. "In a sense, there's a fundamental tension at the heart of every democracy: the greater good versus individual self-interest. We wanted to identify the factors that motivate both leaders and citizens to maintain more egalitarian systems, given the potential of power to corrupt. As archaeologists, we know that the past always has lessons for the present." Blanton and his co-authors assembled data on 30 pre-modern societies, broke them down into numerically coded variables, and generated statistically significant scores for "good government" measures--public goods (like transportation infrastructure, wider access to water, and food security), bureaucratization (citizen voice, equitable taxation, official accountability), and controls over authorities (impeachment ability, limits on leaders' control of resources, institutions that checked each other's clout). The researchers, including Gary Feinman of the Field Museum in Chicago, Lane Fargher of the Instituto Politécnico Nacional-Unidad in Mérida, Mexico, and Stephen Kowalewski of the University of Georgia, were initially surprised by the results. The case studies covered thousands of years of human history and spanned the globe, from the Venetian Republic (1290 to 1600) to the early-mid Ming Dynasty (15th century) to the Asante Kingdom in West Africa (1800 to 1873), but despite the great diversity of geographical, cultural, historical, and social contexts, there was a positive correlation between the three metrics. Capable bureaucracies, public goods, and limits on rulers tended to occur together in relatively good governments, and were largely absent in more autocratic regimes. As Blanton says, "although what we call good governments were not common--only 27% of our examples had relatively high scores--it's clear that it is both a global and trans-historical social process that existed well before Western history and influence." This unexpected finding led the authors to reconsider the broader and causal factors that shape democracy.

Today we tend to equate democracy with elections, but electoral democracies are a fairly recent phenomenon. They are not the only way to assess the voice of citizens, and elections alone are not sufficient to ensure the public's voice in government, or that personal power of leaders is checked. "The key elements of democracies are not elections themselves," says the Field Museum's Gary Feinman, "but rather features like the rule of law, checks and balances on official power, and tools to assess the will of the governed."

Economics are key, the authors argue. Evidence overwhelmingly demonstrates that authoritarian regimes have broad discretion over a nation's wealth, for both personal and political gain. In the study's more authoritarian examples, there were few limits on self-serving leaders, and little incentive to ensure equitable distribution of public goods, or to monitor government administration. "It's no coincidence that the legend of Robin Hood arose in 14th century England," says Feinman, "where our coding identified ill-conceived and oppressive taxing schemes that diverted wealth into private hands." Conversely, the statistical models show that the more democratic systems were marked by broadly based tax revenues, which were responsibly managed by governments. In short, taxpayers generally comply if they see that the government is meeting expectations, and government authorities are incentivized to ensure that revenues will be used for the public good, and not for private gain.

In the United States, these realities were recognized during the founding of our country and that has contributed to the relative longevity of our democracy, Feinman observes. "James Madison put checks and balances in the Constitution because the Founders knew they could not rely on the virtue of leaders alone. One of the key changes in transforming the Articles of Confederation into the Constitution was to give the federal government a stronger foundation to raise funds."

This also underlines the authors' point that leaders, whether virtuous or selfish, are less important than the economic foundations of government, provisioning of public goods/services, and the bureaucratic institutions needed for both. "Look at Iraq after Saddam Hussein," says Feinman. "You could institute voting, and power-sharing agreements, but without an equitable means of financing and provisioning, it didn't matter how much shifting of leaders occurred. The system failed." Likewise, although a majority of people in the U.S. and abroad see Donald Trump as a threat to American democracy and governance, the threats were four decades in the making, with the increasing inequity of the tax base, the devaluing of labor, the lack of infrastructure and public goods funding. "The market fundamentalism that was ushered in with President Reagan, Fed Chair Alan Greenspan, and Prime Minister Margaret Thatcher during the 1980s encouraged people to pursue financial self-interest with no restraint or regulation. Cutting taxes on the wealthy and starving government undermines democracy," says Feinman.

Like modern democracies, good governments have always been fragile and hard to maintain. Across time, neither monarchies nor democracies guaranteed good governance nor excluded its possibility. Rather, the main causal factor was the way that governance was fiscally funded. Above all, the authors of this article emphasize that politics and economics cannot be decoupled in understanding government quality. Nor can we assess by ideologies alone. Rather, we must look at the practice of governance and how it affects people. "Functioning bureaucracy and broad-based, equitable taxation are not stumbling blocks to good governance, as many on both the left and right have argued for years," says Blanton. "Rather, as our historical analysis illustrates, they are key legs of the stool."

For modern-day America and other faltering democracies, the implication is that the global turn toward market fundamentalism 40 years ago, which included reduced taxation rates and lowered values on labor, is likely a key cause of democratic backsliding over the same era. As Feinman notes, "in 1936 Franklin Delano Roosevelt said that 'political equality... [is] meaningless in the face of economic inequality.' But in fact, extreme economic inequality and the monopolization of resources required to fund government may render political equality unsustainable."

Gastrointestinal stromal tumors (GISTs) are a subytpe of cancers known as sarcomas. GIST is the most common type of sarcoma with approximately 5,000 to 6,000 new patient cases annually in the United States. GIST cannot be cured by drugs alone, and targeted therapies are only modestly effective, with a high rate of drug resistance. In a recent study, researchers at University of California San Diego School of Medicine and Moores Cancer Center identified new therapeutic targets that could lead to new treatment options for patients.

The study, published in the February 18, 2021 online edition of Oncogene, found that specific cell-to-cell communication influences GIST biology and is strongly associated with cancer progression and metastasis.

The researchers discovered that certain GIST cancer-associated fibroblasts (CAFs), a cell population within GIST tumors, can communicate with GIST cells. This crosstalk between CAFs and GIST cells results in more aggressive tumor biology.

"By examining the tumor microenvironment of GIST, we were able to look at a previously unrecognized cellular target for GIST therapy that could result in improved disease control and cure rates. It's a paradigm shift for the field," said senior author Jason Sicklick, MD, professor of surgery at UC San Diego School of Medicine and surgical oncologist at Moores Cancer Center at UC San Diego Health.

The study involved animal models of GIST metastasis and bioinformatic analyses from 75 GIST patients.

Currently, single drug therapies are used in the management of GIST. These therapies target the KIT and PDGFRA gene mutations -- signal receivers on GIST cells that drive cancer growth.

"However, when CAFs are present, they produce platelet-derived growth factor (PDGFC), a signal that can activate PDGFRA and overcome drug inhibition," said first author Hyunho Yoon, PhD, a research associate with UC San Diego School of Medicine.

Approximately half of patients with metastatic GIST will develop drug resistance within 20 months of starting first-line therapy. Once the first line of treatment for GIST loses effectiveness, response rates to subsequent therapies also dramatically decline. Thus, said the authors, combination therapies against multiple cellular targets, such as CAFs, could be more effective, especially before the disease has metastasized.

GISTs develop from nerve cells in the wall of the gastrointestinal tract and can occur anywhere from the esophagus to the rectum. These tumors most commonly occur without telltale symptoms, such as feeling full sooner than normal after eating or abdominal pain. Occasionally, symptoms include gastrointestinal bleeding or signs of intestinal obstruction. GIST cases most often develop and are diagnosed in persons age 50 and older.

The researchers said next steps include investigating synergistic drug combinations for CAF-targeted therapies.

"We have to start thinking outside of the box. We've been using bigger and bigger hammers to hit the same target and not seeing different results," said Sicklick. "We need to start hitting a different target. Our study results could be the first insights into a new approach."

FAYETTEVILLE, Ark. -Variation in a specific gene could be related to traits that are beneficial to bonding and relationship satisfaction in the first years of a marriage, according to a new study by a University of Arkansas psychologist.

Recent research indicates that a variation called "CC" in the gene CD38 is associated with increased levels of gratitude. Extending that line of work, U of A psychologist Anastasia Makhanova and her colleagues used data from a study of genotyped newlyweds to explore whether a correlation existed between the CD38 CC variation and levels of trust, forgiveness and marriage satisfaction. They found that individuals with the CC variation did report higher levels of perceptions considered beneficial to successful relationships, particularly trust.

Marriage satisfaction tends to start high then drop, said Makhanova, assistant professor of psychology and first author of the study, published in the journal Nature Scientific Reports. "We were interested in seeing if some of the reasons that people might have a harder time maintaining relationship satisfaction in the newlywed period is due to some potential underlying genetic predispositions."

For the work, researchers studied 142 newlyweds -- 71 couples -- a subset of a larger group used for other studies. The newlyweds' DNA was collected three months after being married, and they also completed a survey at that point as well as one every four months for three years. At the end of the study, researchers compared survey results with the CD38 variations and found that those with the specific CC variation reported higher levels of traits corresponding to marriage satisfaction.

"CC individuals felt more grateful for their partner, reported higher trust in their partner, were more forgiving of their partner, and were more satisfied with their marriages than were AC/AA individuals," the researchers wrote.

While the work points to a possible genetic link to marriage satisfaction,

Makhanova notes that it doesn't mean those without the CD38 CC variation will not have successful relationships.

"So it's not that people who don't have the CC genotype are doomed to have problems," she said. "It's just that they're more likely to have issues in some of these domains, and so those people might have to work a little bit more in those domains."

Irvine, Calif. -- An interdisciplinary team of biologists and mathematicians at the University of California, Irvine has developed a new tool to help decipher the language cells use to communicate with one another.

In a paper published today in Nature Communications, the researchers introduce CellChat, a computational platform that enables the decoding of signaling molecules that transmit information and commands between the cells that come together to form biological tissues and even entire organs.

"To properly understand why cells do certain things, and to predict their future actions, we need to be able to listen to what they are saying to one another; mathematical and machine learning tools enable the translation of such messages," said co-senior author Qing Nie, UCI Chancellor's Professor of mathematics and developmental & cell biology.

"Just like in our world, where we are constantly bombarded with information, all cells experience a lot of molecular words coming at them simultaneously," added co-senior author Maksim Plikus, UCI professor of developmental & cell biology, "What they choose to do is dependent on this steady flow of molecular information and on what words and sentences are being heard the loudest."

To use CellChat to translate molecular messages between cells, researchers feed in a single-cell gene expression, and out comes a detailed report on signaling communication features of a given tissue or organ.

"For each distinct group of cells, CellChat shows what significant signals are being sent to their neighbors and what signals they have the ability to receive," Plikus said. "As an interpreter of cellular language, CellChat provides scientists with a valuable insight into signaling patterns that guide function of the entire organ."

In developing CellChat, the researchers in UCI's NSF-Simons Center for Multiscale Cell Fate Research - including postdoctoral fellows Suoqin Jin, Christian F. Guerrero-Juarez, Raul Ramos and Lihua Zhang - borrowed heavily from machine learning tools and social network theory, which allows the platform to predict a higher level meaning of cellular language and identify contextual similarities that are otherwise not obvious. It breaks down the immense complexity of cellular communication patterns.

Cells produce modifier molecules to add emphasis to a certain command, transforming "do this" to "do this now." CellChat automatically calibrates the strength of signaling communication between cells by considering all significantly present modifier molecules. As a result, its translation becomes more nuanced and helps to minimize inaccuracies that plague other similar yet less sophisticated computational tools.

Beyond the purely fundamental research enterprise of interpreting these biological messages, Nie said CellChat can also be used to compare communication networks in different states of an organ, such as sickness and health. Calling it a "Google Translator for the lexicon of cells," Nie said one of tool's most significant capabilities is that it can be used to uncover molecular drivers in a broad spectrum of maladies including cancer and autoimmune disorders.

"In our paper, we showcase the power of CellChat using atopic dermatitis, a human skin condition, but the tool can be used on any tissue with the same success," Plikus added.