Culture

A study published this May in the journal Clinical Infectious Diseases suggests that people who have had dengue in the past are twice as likely to develop symptoms of COVID-19 if they are infected by the novel coronavirus.

The findings of the study were based on an analysis of blood samples from 1,285 inhabitants of Mâncio Lima, a small town in the state of Acre, part of Brazil’s Amazon region. The principal investigator was Marcelo Urbano Ferreira, a professor at the University of São Paulo’s Biomedical Sciences Institute (ICB-USP) in Brazil. The study was supported by FAPESP.

“Our results show that the populations most exposed to dengue, possibly owing to socio-demographic factors, are precisely those that most risk falling very sick if they’re infected by SARS-CoV-2. This is an example of what has been called a syndemic [synergic interaction between two epidemic diseases so that one exacerbates the effects of the other]. On one hand, COVID-19 has hindered efforts to control dengue. On the other, the latter appears to increase the risk for those who contract the former,” Ferreira told Agência FAPESP.

For seven years Ferreira has been conducting research in Mâncio Lima with the aim of combating malaria. In 2018 he began work on a project involving a survey of 20% of the town’s population every six months. His team call on homes, apply questionnaires, and collect blood samples. In early 2020 the project received additional funding from FAPESP so that part of the research effort could be redirected to the monitoring and characterization of SARS-CoV-2 in the region (read more at: agencia.fapesp.br/34728).

“In September 2020, a study by another group was published suggesting that areas with many cases of dengue were relatively little affected by COVID-19. Because we already had blood samples collected from inhabitants of Mâncio Lima before and after the first wave of the pandemic, we decided to use the material to test the hypothesis that prior infection by dengue virus conferred some degree of protection against SARS-CoV-2. What we found was exactly the opposite,” Ferreira said.

Methodology

The blood samples analyzed had been collected in November 2019 and November 2020. They were submitted to tests capable of detecting antibodies against all four dengue serotypes and against SARS-CoV-2.

The results showed that 37% of the cohort studied had contracted dengue before November 2019 and 35% had been infected by the novel coronavirus before November 2020. Clinical data (symptoms and outcomes) of the volunteers diagnosed with COVID-19 were also analyzed.

“We deployed statistical analysis to conclude that prior infection by dengue virus doesn’t alter the risk of being infected by SARS-CoV-2. On the other hand, our study also shows that people who have had dengue are more likely to have symptoms if they’re infected by SARS-CoV-2,” said Vanessa Nicolete, first author of the article. Nicolete is a researcher with a postdoctoral fellowship at ICB-USP.

The causes of the phenomenon described in the article are unclear. There may be a biological basis for it, in the sense that antibodies against dengue virus somehow exacerbate COVID-19, or it may simply be due to socio-demographic factors that make certain population groups more vulnerable to both diseases for various reasons.

“The results evidence the importance of reinforcing both the social distancing measures introduced to contain the spread of SARS-CoV-2 and efforts to control the dengue vector, as the two epidemics are occurring at the same time and affecting the same vulnerable population. This should be getting more attention from the federal government,” Ferreira said.

The article “Interacting epidemics in Amazonian Brazil: prior dengue infection associated with increased COVID-19 risk in a population-based cohort study” by Vanessa C. Nicolete, Priscila T. Rodrigues, Igor C. Johansen, Rodrigo M. Corder, Juliana Tonini, Marly A. Cardoso, Jaqueline G. de Jesus, Ingra M. Claro, Nuno R. Faria, Ester C. Sabino, Marcia C. Castro and Marcelo U. Ferreira is at: academic.oup.com/cid/advance-article/doi/10.1093/cid/ciab410/6270997.

Journal

Clinical Infectious Diseases

DOI

10.1093/cid/ciab410

MINNEAPOLIS/ST. PAUL (03/18/2021) -- A research team, led by the University of Minnesota Medical School, found that regardless of socioeconomic status, Twin Cities residents of underrepresented racial and ethnic backgrounds endure worse COVID-19 outcomes compared to people who are white.

The study was just published in the Journal of General Internal Medicine and is one of the first papers to discuss which social and cultural factors, including non-English speaking, may or may not contribute to racial and ethnic health disparities related to COVID-19.

"For people of color, even in the highest socioeconomic status, our data shows they still have worse COVID-19 outcomes compared to people who are white," said Nicholas Ingraham, MD, a third-year fellow in the Department of Medicine at the U of M Medical School who led the study. "We also found that, independent of race, ethnicity and socioeconomic status, non-English speaking is also associated with worse clinical outcomes in COVID-19. It puts patients at higher risk of disease not only across racial and ethnic populations but also within those populations."

Using a data system developed over the last two years by the Minnesota Critical Care Outcomes and Research Effort (a multidisciplinary and national collaboration founded at the University of Minnesota), the team analyzed 5,577 de-identified patient records from the M Health Fairview system between March 4 and Aug. 19, 2020. A subset of these patients required hospitalization within 45 days of diagnosis, which were used in the study. Researchers evaluated socioeconomic status through a proxy by matching those patients' nine-digit ZIP codes to an area deprivation index - a measure that uses 17 different markers of socioeconomic status from the U.S. Census data, including levels of education, poverty and safe housing, to assess the severity of deprivation within neighborhoods.

"When doing this analysis, we did see that there are differences in COVID-19 severity by race and ethnicity, just as many other national studies have already shared," Ingraham said. "But then, we adjusted for socioeconomic status to test the hypothesis that racial and ethnic disparities stem from differences in socioeconomic factors. When we did that, the race signal should have gone away, and we should have seen socioeconomic status as the cause for higher risk of hospitalization for certain patients. We actually saw the opposite. Socioeconomic status was not associated with severe disease, and race continued to be significant."

The study team recognizes that many other factors, including job type, genetics, testing access and systemic racism, may all play a role in COVID-19 health disparities. To provide more insight, Ingraham plans to expand on the study to determine which of the 17 factors within the area deprivation index may make patients more vulnerable to the disease. The team will also partner with the U of M School of Public Health to link their patient data set to other social determinants of health like environmental pollution and food deserts.

"Seeing an increased risk of severe COVID-19 disease in people of color and non-English speaking, independent of other known risk factors, these populations should be considered high priority for the continued vaccination rollout," Ingraham said.

More than three quarters of Iran's land is under extreme groundwater overdraft, where the rate of human uptake is higher than the rate of natural recharge. This is according to a new study led by Concordia researchers published in the Nature journal Scientific Reports.

The article was co-authored by Samaneh Ashraf, a former Horizon postdoctoral researcher now at the Université de Montréal, and Ali Nazemi, an associate professor in the Department of Building, Civil and Environmental Engineering. Amir AghaKouchak of the University of California, Irvine, also contributed to the paper.

The researchers write that mismanagement by the country's authorities is exacerbating existing strains on the semi-arid country's aquifers by an inefficient agriculture industry. Without urgent action, they note, the country faces multiple national crises.

"The continuation of unsustainable groundwater management in Iran can lead to potentially irreversible impacts on land and the environment, threatening the country's water, food and socioeconomic security," Ashraf says.

The authors write that an estimated 74 km3 of groundwater has been depleted from the country's 500 basins and sub-basins between 2002 and 2015. This has contributed to both growing soil salinity and an increase in land subsidence -- basically, land sinking. Among the most at-risk regions of land subsidence is the Salt Lake Basin, which includes Iran's capital Tehran, home to some 15 million people and already at risk of severe seismic activity.

Human role is clear

The researchers used publicly available data published by the Iranian Ministry of Energy as the basis for the study.

"We wanted to quantify how much of Iran's groundwater was depleted," Nazemi explains. "Then we diagnosed why it was depleted. Was it driven by climate forces, by a lack of natural recharge or because of unsustainable withdrawal?"

After looking at all the data they had available, the researchers concluded that heavy agricultural demands were the overwhelming leading cause of groundwater depletion. The country's west, southwest and northeast, where farmers grow strategic crops like wheat and barley, experienced the most severe drops.

The paper notes that the number of registered wells that draw groundwater for agriculture has almost doubled in a decade and a half, from around 460,000 in 2002 to roughly 794,000 in 2015. Anthropogenic groundwater withdrawals decreased in 25 of the country's 30 basins during that same period. This suggests that the aquifers are being overexploited by human activity.

The researchers looked at soil electrical conductivity as a proxy for measuring salinity levels across the country and found that they were rising as well.

Urgent action required

Compounding all these problems are governments at the local and national levels that are not equipped to address the growing crisis for a variety of reasons, including international sanctions, local corruption and general mistrust of authorities among the population. But the authors say the country is in acute need of both short- and long-term solutions.

"In the short term, the unregistered wells need to be shut down," Nazemi says. "But longer term, Iran clearly needs an agricultural revolution. This requires a number of elements, including improving irrigation practices and adopting crop patterns that fit the country's environment."

While Iran is uniquely at risk due to its natural environment, growing population and ineffective governance, Nazemi warns that its experiences offer warnings to other countries, including Canada.

"Iran's example clearly shows that we need to be careful how we manage our water because one bad decision can have a huge domino effect. And if the problem is ignored, it will easily get out of control," he says. "It also illustrates the importance of environmental justice and stewardship. These are even more important when addressing the problem of climate change."

Medication-assisted treatment, or MAT, is an important tool in the ongoing fight against opioid use dependence in the United States. Employing certain medications in combination with counseling and behavioral therapy, MAT offers a comprehensive, "whole-patient" approach to addressing opioid use.

According to a new study from researchers at the UConn School of Social Work and the Connecticut Department of Mental Health and Addiction Services, Connecticut's MAT programs have higher-than-average patient retention rates - more people who enter Connecticut's programs stay in the program to completion.

But the study - recently published in the journal Substance Use and Misuse - also found that younger patients and patients who reported cocaine or crack use in addition to opioid dependence had a harder time sticking with the MAT treatment program than those who were older or those who might also be using other substances, which has implications for both program providers and policymakers as the country continues to grapple with the opioid epidemic.

"One of the things you look at when folks are coming into a program like this is what kinds of drugs they were using right before this started," says Michael Fendrich, a professor and associate dean for research at the School of Social Work who focuses on policies, services, interventions, and risk factors related to substance misuse and mental health and is the lead author of the new study. "A lot of programs are focused on one substance, but a lot of folks come in there not just using one substance."

The study looked at information about clients enrolled in four federally funded MAT programs in Connecticut over a three-year period, from December 2016 to August 2019, and included 423 clients that followed the same treatment model. In addition to medication, the programs included cognitive behavioral therapy and employed a recovery support coach - a person in recovery from opioid use disorder - as part of the treatment model.

Clients were considered to be "retained" if they were still receiving services from the program at the six-month interview or if they had a successful discharge before the six-month interview. The researchers found that, at six months, 58.9% of participants has been retained in the program. Most of these participants - 71% - were still receiving services. Others had completed services or had successful discharges at six-month follow-ups.

Prior use of other substances did not necessarily lead to lower retention - a finding that Fendrich says he found surprising. In particular, those who reported using benzodiazapines actually had a higher probability of success in the program.

"I don't have a solid reason for that," Fendrich says, "but we do know that benzodiazapine is a dangerous medication to be taken at the same time that you're taking opioid treatment medications, so there might have been a little bit more focus on making sure that those folks were using the treatment medication in the way they were supposed to be using it."

But reported cocaine or crack use was correlated with reduced retention, an area that Fendrich says merits greater study.

"Prior substance use is a complex issue," he says. "You can't just say, 'all prior drug use is going to decrease the chances for success.' But you need to look at what specific drugs are being used. And I would suggest that we just need some more follow up on that one."

Overall, rates of retention did not vary despite differences in location and in the demographics of the clients who sought treatment at the four sites.

"They were dealing with diverse clients, and they were pretty similar kinds of outcomes that they experienced," Fendrich says, "which speaks highly to the implementation of the program in the state."

Demographics, though, did influence success: older clients had higher retention rates than younger clients, suggesting that strategies specifically designed to support younger people who are struggling with opioid dependence are needed.

"I really think that the emerging adult, young adult, group is a group that's at risk for so many things, and I think we need to think about them in an even more focused way," Fendrich says. "As we emerge from the pandemic, this is a group that's struggling on many issues. It's a really difficult time, in terms of employment opportunities, in development - folks are not stabilized in their life - in relationships, and in just general direction in life. And so, it becomes harder when there's also substance dependence that's added into the picture."

While the role of peers employed as recovery support coaches in Connecticut's program was not specifically evaluated as part of the study, the researchers suggested their participation in the treatment model could contribute to Connecticut's higher retention rates. This hypothesis was supported by focus groups the researchers conducted with the program clients; many of the client comments were about the importance of peer support. While not unique to Connecticut, use of recovery support coaches in MAT programs is not universal, Fendrich says.

Programs need to think about the potential unique needs of people coming into the program, he notes, and look comprehensively at supports they might need to be successful.

"It's never just one thing," Fendrich says. "You know, people are complicated. And there is an opioid crisis, but folks who are who are dependent on opioids have lots of other problems. Some are addiction-related, and some are more in what I call the 'psychosocial adjustment realm,' but they all need attention. I think we've been good at attending to those in our programs in Connecticut, and it's a real feather in our cap."

He continues, "We have great programs here in the state, and we'll hopefully continue to build on the success that we've seen in our programs so far. But policy-wise, we need to be comprehensive in our approach to treatment for people who are coming into programs with opioid dependence."

Classic computers use binary values (0/1) to perform. By contrast, our brain cells can use more values to operate, making them more energy-efficient than computers. This is why scientists are interested in neuromorphic (brain-like) computing. Physicists from the University of Groningen (the Netherlands) have used a complex oxide to create elements comparable to the neurons and synapses in the brain using spins, a magnetic property of electrons. Their results were published on 18 May in the journal Frontiers in Nanotechnology.

Although computers can do straightforward calculations much faster than humans, our brains outperform silicon machines in tasks like object recognition. Furthermore, our brain uses less energy than computers. Part of this can be explained by the way our brain operates: whereas a computer uses a binary system (with values 0 or 1), brain cells can provide more analogue signals with a range of values.

Thin films

The operation of our brains can be simulated in computers, but the basic architecture still relies on a binary system. That is why scientist look for ways to expand this, creating hardware that is more brain-like, but will also interface with normal computers. 'One idea is to create magnetic bits that can have intermediate states', says Tamalika Banerjee, Professor of Spintronics of Functional Materials at the Zernike Institute for Advanced Materials, University of Groningen. She works on spintronics, which uses a magnetic property of electrons called 'spin' to transport, manipulate and store information.

In this study, her PhD student Anouk Goossens, first author of the paper, created thin films of a ferromagnetic metal (strontium-ruthenate oxide, SRO) grown on a substrate of strontium titanate oxide. The resulting thin film contained magnetic domains that were perpendicular to the plane of the film. 'These can be switched more efficiently than in-plane magnetic domains', explains Goossens. By adapting the growth conditions, it is possible to control the crystal orientation in the SRO. Previously, out-of-plane magnetic domains have been made using other techniques, but these typically require complex layer structures.

Magnetic anisotropy

The magnetic domains can be switched using a current through a platinum electrode on top of the SRO. Goossens: 'When the magnetic domains are oriented perfectly perpendicular to the film, this switching is deterministic: the entire domain will switch.' However, when the magnetic domains are slightly tilted, the response is probabilistic: not all the domains are the same, and intermediate values occur when only part of the crystals in the domain have switched.

By choosing variants of the substrate on which the SRO is grown, the scientists can control its magnetic anisotropy. This allows them to produce two different spintronic devices. 'This magnetic anisotropy is exactly what we wanted', says Goossens. 'Probabilistic switching compares to how neurons function, while the deterministic switching is more like a synapse.'

The scientists expect that in the future, brain-like computer hardware can be created by combining these different domains in a spintronic device that can be connected to standard silicon-based circuits. Furthermore, probabilistic switching would also allow for stochastic computing, a promising technology which represents continuous values by streams of random bits. Banerjee: 'We have found a way to control intermediate states, not just for memory but also for computing.'

Alzheimer's disease shares some key similarities with healthy aging, according to a new mathematical model described today in eLife.

The model provides unique insights into the multiscale biological alterations in the elderly and neurodegenerative brain, with important implications for identifying future treatment targets for Alzheimer's disease.

Researchers developed their mathematical model using a range of biological data - from 'microscopic' information using gene activity to 'macroscopic' information about the brain's burden of toxic proteins (tau and amyloid), its neuronal function, cerebrovascular flow, metabolism and tissue structure from molecular PET and MRI scans.

"In both aging and disease research, most studies incorporate brain measurements at either micro or macroscopic scale, failing to detect the direct causal relationships between several biological factors at multiple spatial resolutions," explains first author Quadri Adewale, a PhD candidate at the Department of Neurology and Neurosurgery, McGill University, Canada. "We wanted to combine whole-brain gene activity measurements with clinical scan data in a comprehensive and personalised model, which we then validated in healthy aging and Alzheimer's disease."

The study involved 460 people who had at least four different types of brain scan at four different time points as part of the Alzheimer's Disease Neuroimaging Initiative cohort. Among the 460 participants, 151 were clinically identified as asymptomatic or healthy control (HC), 161 with early mild cognitive impairment (EMCI), 113 with late mild cognitive impairment (LMCI) and 35 with probable Alzheimer's disease (AD).

Data from these multimodal scans was combined with data on gene activity from the Allen Human Brain Atlas, which provides detail on whole-brain gene expression for 20,267 genes. The brain was then split into 138 different gray matter regions for the purposes of combining the gene data with the structural and functional data from the scans.

The team then explored causal relationships between the spatial genetic patterns and information from their scans, and cross-referenced this to age-related changes in cognitive function. They found that the ability of the model to predict the extent of decline in cognitive function was highest for Alzheimer's disease, followed in order by the less pronounced decline in cognition (LCMI, ECMI) and finally the healthy controls. This shows that the model can reproduce the individual multifactorial changes in the brain's accumulation of toxic proteins, neuronal function and tissue structure seen over time in the clinical scans.

Next, the team used the model to look for genes that cause cognitive decline over time during the normal process of healthy aging, using a subset of healthy control participants who remained clinically stable for nearly eight years. Cognitive changes included memory and executive functions such as flexible thinking. They found eight genes which contributed to the imaging dynamics seen in the scans and corresponded with cognitive changes in healthy individuals. Of note, the genes that changed in healthy aging are also known to affect two important proteins in the development of Alzheimer's disease, called tau and amyloid beta.

Next, they ran a similar analysis looking for genes that drive the progression of Alzheimer's disease. Here, they identified 111 genes that were linked with the scan data and with associated cognitive changes in Alzheimer's disease.

Finally, they studied the functions of the 111 genes identified, and found that they belonged to 65 different biological processes - with most of them commonly linked to neurodegeneration and cognitive decline.

"Our study provides unprecedented insight into the multiscale interactions among aging and Alzheimer's disease-associated biological factors and the possible mechanistic roles of the identified genes," concludes senior author Yasser Iturria-Medina, Assistant Professor at the Department of Neurology and Neurosurgery at McGill University. "We've shown that Alzheimer's disease and healthy aging share complex biological mechanisms, even though Alzheimer's disease is a separate entity with considerably more altered molecular and macroscopic pathways. This personalised model offers novel insights into the multiscale alterations in the elderly brain, with important implications for identifying targets for future treatments for Alzheimer's disease progression."

A global effort to reduce sulfur and greenhouse gas (GHG) emissions from ships has researchers from the National Renewable Energy Laboratory (NREL) and other Department of Energy facilities investigating the potential use of marine biofuels.

"Biofuels turned out to be very good options because they have zero or very, very low sulfur compared to fossil fuels," said Eric Tan, a senior research engineer at NREL and lead author of a new article published in the journal Environmental Science and Technology.

His co-authors of "Biofuel Options for Marine Applications: Techno-Economic and Life-Cycle Analyses" are Ling Tao, also from NREL, along with scientists with Argonne National Laboratory, Pacific Northwest National Laboratory, and the U.S. Department of Transportation's Maritime Administration.

The International Marine Organization (IMO) has been ratcheting down the allowed amount of sulfur oxides emissions from ships since 2005. The newest upper limit, which took effect at the start of 2020, reduced the sulfur content of ships' fuel oil to 0.5% from 3.5%. IMO said the reduction should have major benefits for the environment and the health of people, particularly those living near ports and along coasts. Additionally, IMO has set aggressive targets to decarbonize marine shipping, targeting at least a 50% reduction in GHG emissions from international shipping by 2050, relative to 2008 levels.

The new regulation, which is enforced by individual countries, requires changes to bring ships into compliance. Ship owners can either install sulfur scrubbers to reduce emissions, or they can adopt a different, low-sulfur fuel. Both options carry an additional cost.

The NREL-directed research provides a starting point for establishing the feasibility of ships using biofuels. Fueling costs already account for a significant part of running a shipping line, so the researchers examined both prices and emissions.

The economics are weighed against the cost of burning heavy fuel oil (HFO), which accounts for about three-quarters of the fuel used by ships. A low-sulfur HFO costs slightly more a gallon than traditional HFO. The low-sulfur HFO prices would be the maximum ship owners are willing to pay for biofuels for a one-to-one replacement. The biofuels are considered to be potential drop-in fuels compatible for use in marine engines, but further work is needed to confirm that compatibility.

Upon examining different types of fuels for their ability to reduce emissions of greenhouse gases and air pollutants, the researchers found biofuels produced entirely from biomass offer much higher reductions in life-cycle greenhouse gas emissions--from 67% to 93% less than HFO. Biomass-derived fuels also are mostly free of sulfur and exhibit reductions in criteria air pollutant emissions such as particulate matter.

Tan's research concluded that, if shipping had no competition, the United States has a large supply of bio-feedstocks for producing substantial amounts of marine biofuels to displace fossil fuels. With ships using 400 million metric tons of fuel annually, a blend of 5% biofuels translates to about 5 billion gallons.

The research was funded by the U.S. Department of Energy's Bioenergy Technologies Office and by the U.S. Department of Transportation Maritime Administration.

NREL is the U.S. Department of Energy's primary national laboratory for renewable energy and energy efficiency research and development. NREL is operated for the Energy Department by the Alliance for Sustainable Energy, LLC.

NEW YORK, NY (May 18, 2021) - An expert panel convened by the Alzheimer's Drug Discovery Foundation (ADDF) and The Association for Frontotemporal Degeneration (AFTD) provides guidance on best practices for the design of early drug trials for Alzheimer's disease, frontotemporal degeneration (FTD), and other neurodegenerative dementias. Their guidance was published in the May 18, 2021 issue of Neurology®, the medical journal of the American Academy of Neurology ("Value-Generating Exploratory Trials in Neurodegenerative Dementias").

These efficiencies in clinical trials can help to achieve proof of concept more rapidly and at lower costs. The estimated cost of developing an Alzheimer's drug is eight times more than a cancer drug and takes nearly twice as long to develop. The panel, which comprised clinicians, researchers, and statisticians from academia, biotech, and pharmaceutical companies, as well as ADDF and AFTD scientific staff, focused on early phase 1 and 2 exploratory trials, which assess a drug's safety and pharmacologic effects on patients. Exploratory studies with optimized study designs can terminate programs not likely to succeed and efficiently move promising programs through the clinical trial process. Later phase 2 and phase 3 trials measure clinical outcomes such as memory and ability to perform daily functions.

"The majority of clinical development costs come from later stage phase 2b and phase 3 studies, which require long treatment periods and a large number of patients to detect meaningful changes in cognitive, behavioral, and functional endpoints," said Howard Fillit, M.D., ADDF founding executive director and chief science officer. "Results from exploratory phase 2a trials are the critical inflection point when researchers decide which drugs to move into these larger and more expensive trials, so clearly these phase 2a trials need to be as rigorous and well-designed as possible."

Panel makes four key recommendations for exploratory trial study designs

By adopting best practices in designing exploratory trials, researchers and companies can be more confident in using their results to make the all-important go/no-go decisions about advancing drugs to larger later-stage trials. The four key panel recommendations are to:

1. Employ rigorous statistical analyses and procedures, engaging statisticians in trial design as early as possible.

2. Incorporate the appropriate biomarker and clinical endpoints that reflect the drug's mechanism of action and the specific study population.

3. Leverage historical data to determine appropriate outcome measures that are well-aligned with the disease and mechanism of action for the treatment.

4. Consider novel clinical development plans to increase efficiency in moving a drug candidate into larger clinical trials or determining that it is ineffective as quickly as possible; avoid "cookie cutter" trial designs that are not optimized or tailored.

"These four recommendations can lead to more efficient trials, with substantial financial savings, as well as more strategic and effective engagement of patients," said AFTD CEO Susan L-J Dickinson. "The latter is a key concern for a rare disease like FTD where the low number of patients pushes the need for strategic study design, with patients enrolled only in studies that will provide a clear and accurate readout of therapeutic efficacy."

"We clearly need exploratory trials to be rigorous and efficient," said Dr. Fillit. "But this is about working toward the ultimate success--effective treatment strategies, which will likely be a combination drug approach that hits several of the biological pathways involved in the neurodegenerative process of dementia. That means being able to take multiple shots on goal--testing a wide variety of plausible drug candidates to identify the most promising ones."

More than a year into the pandemic, the disproportionate burden of COVID-19 among racial and ethnic minorities in the US has been well documented. But a new study by Boston University School of Public Health (BUSPH) reveals that previous research has underestimated the true extent of racial disparities in COVID-19 deaths--as well as the extent to which structural racism contributes to these deaths.

Published in the Journal of Racial and Ethnic Health Disparities, the paper is the first to quantify the state-level differences in racial disparities in COVID-19 mortality among Black and White populations, using directly standardized, age-adjusted death rates. When comparing these age-adjusted rates, the study found that the Black-White disparity in COVID-19 mortality rates across states was substantially greater than what has previously been reported.

Until now, few studies on COVID-19 deaths have taken the age distribution of different populations into account, or explicitly compared race-specific mortality rates at the state level. But age is perhaps the single most important predictor of COVID-19 mortality, says study lead author Dr. Michael Siegel, professor of community health sciences at BUSPH. Different racial and ethnic groups have different age distributions, and comparing crude COVID death rates instead of age-adjusted rates can be misleading, he says.

"Because of structural racism, chronic diseases are much more common among the Black population compared to the White population, and for this reason, life expectancy for Black people is substantially less than that for White people," says Siegel. The shorter life expectancy means that the Black population of a state is going to be considerably younger than the White population for that state, he says.

"If you ignore this fact, then it is going to appear that the COVID death rate is much higher among the White population because there are so many more older people," Siegel says. "To get an accurate idea of the true disparity in death rates, you need to compare the COVID death risk of Black people and White people in a state at the same age."

The study is also the first paper to measure structural racism at the state level, and model this racism as a direct, quantifiable predictor of racial disparities in COVID-19 deaths across states.

Siegel and a team of researchers used data from the Centers for Disease Control and Prevention to calculate both crude and age-adjusted COVID-19 mortality rates for non-Hispanic White and non-Hispanic Black populations in 35 states. Then they compared these age-adjusted rates in order to quantify the racial disparity in mortality rates. Using linear regression analyses, they examined the potential relationship between a previously defined structural racism index and the racial disparity in COVID-19 mortality. The team also utilized linear regression analysis to explore potential mediating effects of exposure based on occupation, prevalence of underlying conditions, and disparities in healthcare access. This analysis yielded the following key findings:

For all 35 states, the Black-White disparity in COVID-19 mortality rates was substantially greater when examining age-adjusted rates compared to crude rates. Thus, relying on crude death rates severely underestimates the true magnitude of the Black-White disparity in COVID-19 mortality rates.

A high level of structural racism was a robust predictor of increased racial disparities in COVID deaths. All 35 states showed a pattern of increasing racial disparities as the state structural racism index increased.

The five states with the highest structural racism indices had an average disparity ratio of 2.7, compared to 2.1 for the five states with the lowest racism indices.

Structural racism appears to be a root cause of the Black-White disparity in COVID-19 mortality.

"Even if we could somehow equalize comorbidities between the White and Black populations, our results suggest that the racial disparity in COVID-19 death rates would still persist," says Siegel. "These findings suggest that the only way to fully address the consequences of structural racism is to dismantle structural racism itself."

(Boston)--Researchers from Boston University School of Medicine (BUSM) report the formation of human cells containing a green fluorescent protein or GFP (one of the most important proteins in biology and fluorescence imaging) genetically fused with two interferon stimulated genes (ISGs), namely Viperin and ISG15. This new creation makes these cells highly valuable reagents for reporting innate immune responses to viral infections, including those caused by coronaviruses.

These engineered cells, which turn green when treated with interferon, are highly novel because this is the first time a reporter gene (a gene that enables the detection or measurement of gene expression), such as GFP, has been inserted into endogenous loci of ISGs.

Viral infections cause human cells to sound a biochemical alarm via interferon signaling, leading to a high-level expression of ISGs. However, ISGs are very tightly regulated genes, because too much expression and an inability to later tamp down ISG levels can be just as detrimental to cellular health.

This overactive innate immune signaling leads to a 'cytokine storm' (when an infection triggers the immune system to flood your bloodstream with inflammatory proteins called cytokines) that distinguishes a mild case of virus infection from fully debilitating symptoms, an outcome all too prevalent in the COVID19 pandemic. "Better research tools for studying ISG regulation are still needed, not just now for coronavirus research but for many other viruses that our society will contend with," explained co-corresponding author Nelson Lau, PhD, associate professor of biochemistry at BUSM.

In order to successfully tag human antiviral genes with GFP, the researchers first needed to produce a new methodology for creating a long DNA repair template for more efficient and authentic CRISPR-Cas9 genome editing in animal cells. They named his template methodology the BL3SSO (sounds like "blasso") because it sets up the DNA for more accurate repair and for introduction of a fluorescent transgene like GFP into the site cut by Cas-9 during genome editing.

These findings are the result of a collaboration between the Lau lab and the lab of Mohsan Saeed, PhD, both faculty members in BUSM's department of biochemistry and investigators at the BU National Emerging Infectious Diseases Laboratories (NEIDL).

These findings appear online in the journal G3: Genes | Genomes | Genetics.

A filter made from polymer nanothreads blew three kinds of commercial masks out of the water by capturing 99.9% of coronavirus aerosols in an experiment.

"Our work is the first study to use coronavirus aerosols for evaluating filtration efficiency of face masks and air filters," said corresponding author Yun Shen, a UC Riverside assistant professor of chemical and environmental engineering. "Previous studies have used surrogates of saline solution, polystyrene beads, and bacteriophages -- a group of viruses that infect bacteria."

The study, led by engineers at UC Riverside and The George Washington University, compared the effectiveness of surgical and cotton masks, a neck gaiter, and electrospun nanofiber membranes at removing coronavirus aerosols to prevent airborne transmission. The cotton mask and neck gaiter only removed about 45%-73% of the aerosols. The surgical mask did much better, removing 98% of coronavirus aerosols. But the nanofiber filter removed almost all of the coronavirus aerosols.

The World Health Organization and Centers for Disease Control have both recognized aerosols as a major mechanism of COVID-19 virus transmission. Aerosols are tiny particles of water or other matter that can remain suspended in air for long periods of time and are small enough to penetrate the respiratory system.

People release aerosols whenever they breathe, cough, talk, shout, or sing. If they are infected with COVID-19, these aerosols can also contain the virus. Inhaling a sufficient quantity of coronavirus-laden aerosols can make people sick. Efforts to curb aerosol spread of COVID-19 focus on minimizing individual exposure and reducing the overall quantity of aerosols in an environment by asking people to wear masks and by improving indoor ventilation and air filtration systems.

Studying a contagious new virus is dangerous and done in labs with the highest biosecurity ratings, which are relatively rare. To date, all studies during the pandemic on mask or filter efficiency have used other materials thought to mimic the size and behavior of coronavirus aerosols. The new study improved on this by testing both aerosolized saline solution and an aerosol that contained a coronavirus in the same family as the virus that causes COVID-19, but only infects mice.

Shen and George Washington University colleague Danmeng Shuai produced a nanofiber filter by sending a high electrical voltage through a drop of liquid polyvinylidene fluoride to spin threads about 300 nanometers in diameter -- about 167 times thinner than a human hair. The process created pores only a couple of micrometers in diameter on the nanofiber's surfaces, which helped them capture 99.9% of coronavirus aerosols.

The production technique, known as electrospinning, is cost effective and could be used to mass produce nanofiber filters for personal protective equipment and air filtration systems. Electrospinning also leaves the nanofibers with an electrostatic charge that enhances their ability to capture aerosols, and their high porosity makes it easier to breathe wearing electrospun nanofiber filters.

"Electrospinning can advance the design and fabrication of face masks and air filters," said Shen. "Developing new masks and air filters by electrospinning is promising because of its high performance in filtration, economic feasibility, and scalability, and it can meet on-site needs of the masks and air filters."

Nearly 15 percent of the U.S. population experiences migraine. One subtype of migraine that is not well understood is migraine with aura (MA). Individuals who experience MA often see flashing lights, blind spots, or jagged lines in their visual field prior to onset of their migraine headaches. Individuals who experience MA also face a heightened risk of stroke and cardiovascular disease, although scientists continue to explore why this correlation exists. In a new study from Brigham and Women's Hospital, researchers used a technique in genetic analysis termed Mendelian randomization to examine 12 coagulation measures, uncovering four that are associated with migraine susceptibility. Interestingly, scientists only observed these associations in individuals who experience MA and did not observe such associations among individuals who experience migraine without aura (MO). Their research suggests that these hemostatic factors could potentially have a causal role in MA. Their results are published in Neurology.

"We've always wanted to know why people with MA have this higher risk of stroke and other cardiovascular diseases," said corresponding author Daniel Chasman, PhD, of the Division of Preventive Medicine at the Brigham. "This study offers promising leads specific to MA. Finding a possible cause for migraine with aura has been an outstanding question in the field for a long time."

There has been speculation in the field about relationships between coagulation and migraine susceptibility for some time, but previous research has been largely inconclusive. Most individuals first experience migraine at a young age for example, during childhood or young adulthood. Because previous study designs included only middle-aged and older adults, investigators have questioned whether coagulation causes migraine or if causality exists between these two elements at all. In this study, leveraging Mendelian randomization, which can support or refute potential causal effects on a health outcome, scientists for the first time found evidence that hemostatic factors may contribute to risk of MA.

"Even if we see an association between migraine and these coagulation factors when we measure both factors in a population at the same time, we still wonder: Which one came first?" said co-author Pamela Rist, ScD, of the Division of Preventive Medicine at the Brigham. "One of the interesting parts of Mendelian randomization is that it allows you to examine potential causality."

Researchers used summary statistics from decades of previously collected data from individuals who experience migraine and individuals who do not experience migraine. Because the diagnostic criteria are different for MA versus MO, they could examine these two conditions separately.

Investigators found a strong association between four coagulation factors and migraine susceptibility. They observed that genetically increased levels of three blood clotting factors: coagulation factor VIII, von Willebrand factor, and phosphorylated fibrinopeptide A, and genetically decreased levels of fibrinogen (a protein important in the late stages of the blood clotting process) were all associated, in part, with migraine susceptibility. Interestingly, scientists did not find this association among individuals who experience migraine without aura (MO), indicating a specific relationship between these hemostatic factors and MA.

Scientists note that Mendelian randomization has its limitations. In the future, researchers could examine if the causal associations implied by genetics can be observed in clinical practice.

"It is very exciting that by using Mendelian randomization we were able to show that hemostatic factors are associated with MA," said first author Yanjun Guo, MD, PhD of the Division of Preventative Medicine at the Brigham. "And because in the observational studies we saw that MA patients have a higher risk of stroke, these findings may reveal a potential connection between MA and stroke."

ITHACA, N.Y. - While examining the prevalence of listeria in agricultural soil throughout the U.S., Cornell University food scientists have stumbled upon five previously unknown and novel relatives of the bacteria.

The discovery, researchers said, will help food facilities identify potential growth niches that until now, may have been overlooked - thus improving food safety.

"This research increases the set of listeria species monitored in food production environments," said lead author Catharine R. Carlin, a doctoral student in food science. "Expanding the knowledge base to understand the diversity of listeria will save the commercial food world confusion and errors, as well as prevent contamination, explain false positives and thwart foodborne outbreaks."

One of the novel species, L. immobilis, lacked motility, or the ability to move. Listeria move a lot. Among scientists, motility was thought to be common among listeria closely related to L. monocytogenes, a well-known foodborne pathogen - and used as a key test in listeria detection methods. This discovery effectively calls for a rewrite of the standard identification protocols issued by food safety regulators, Carlin said.

As listeria species are often found co-existing in environments that support the growth of L. monocytogenes, food facilities will monitor for all listeria species to verify their sanitation practices.

Listeria monocytogenes can have profound pathogenic influence on food processing plants and those plants must be kept clean. Listeriosis has a mortality rate of 20% to 30% - even with a patient taking antibiotics, according to the U.S. Food and Drug Administration.

The Centers for Disease Control and Prevention estimate that 1,600 people in the U.S. get listeriosis annually and nearly 260 die.

"This paper describes some unique characteristics of listeria species that are closely related to listeria monocytogenes, which will be important from an evolutionary perspective and from a practical standpoint for the food industry," said co-author Martin Wiedmann, the professor in food safety and food science. "Likely, some tests will need to be re-evaluated."

Understanding the different listeria species is key to comprehending their similarities. "This will help us to get better about identifying listeria monocytogenes," Wiedmann said, "and not misidentifying it as something else."

Since 2010, Wiedmann's research group has discovered 13 of the 26 species classified in the genus listeria.

"When you're inspecting the environments of food processing plants or restaurants, you need to know the pathogenic listeria from the non-pathogenic species," Wiedmann said. "You need to tell the good guys from the bad guys."

In quiet moments, the brain likes to wander—to the events of tomorrow, an unpaid bill, an upcoming vacation.

Despite little external stimulation in these instances, a part of the brain called the default mode network (DMN) is hard at work. "These regions seem to be active when people aren't asked to do anything in particular, as opposed to being asked to do something cognitively," says Penn neuroscientist Joseph Kable.

Though the field has long suspected that this neural network plays a role in imagining the future, precisely how it works hadn't been fully understood. Now, research from Kable and two former graduate students in his lab, Trishala Parthasarathi, associate director of scientific services at OrtleyBio, and Sangil Lee, a postdoc at University of California, Berkeley, sheds light on the matter.

In a paper published in the Journal of Neuroscience, the research team discovered that, when it comes to imagining the future, the default mode network actually splits into two complementary parts. One helps create and predict the imagined event, what the researchers call the "constructive" function. The other assesses whether that newly constructed event is positive or negative, what they call the "evaluative" function.

"It's a neat division," says Kable. "When psychologists talk about why humans have the ability to imagine the future, usually it's so we can decide what to do, plan, make decisions. But a critical function is the evaluative function; it's not just about coming up with a possibility but also evaluating it as good or bad."

Building on previous work

The DMN itself includes the ventromedial prefrontal cortex, posterior cingulate cortex, and regions in the medial temporal and parietal lobes, such as the hippocampus. It's aptly named, Kable says. "When you put people into a brain scanner and ask them to not do anything, to just sit there, these are the brain regions that seem to be active," he says.

Previous research had revealed which areas make up the DMN and that constructing and evaluating imagined events activates different components. Kable wanted to test that idea further, to better pinpoint the implicated regions and what's happening in each.

To do so, he and his team created a study in which 13 females and 11 males received prompts while in a functional magnetic resonance imaging (fMRI) machine. Participants had seven seconds to read one of 32 cues such as, "Imagine you're sitting on a warm beach on a tropical island," or "Imagine you win the lottery next year." They then had 12 seconds to think about the scenario, followed by 14 seconds to rate vividness and valence.

"Vividness is the degree to which the image that comes to mind has a lot of details and how much those details subjectively pop as opposed to being vague," Kable says. "Valence is an emotional evaluation. How positive or negative is the event? Is this something you want to have happen or not?"

Participants went through the process four times. Each time, the Penn researchers watched brain activity from the fMRI. The work confirmed two sub-networks at play.

"One network, which we'll call the dorsal default mode network, was influenced by valence. In other words, it was more active for positive events than for negative events, but it was not influenced at all by vividness. It seems to be involved in the evaluative function," Kable says.

The other sub-network, the ventral default mode network, was more active for highly vivid events than for events with no detail. "But it wasn't influenced by valence," he says. "It was equally active for both positive and negative events, showing that network really is involved in the construction piece of imagination."

Next steps

According to Kable, the findings offer a first step toward understanding the basis of imaginative abilities. This research asked participants to evaluate the positivity or negativity of an imagined event, but more complex assessments—moving beyond the simple good-versus-bad dimension, for instance—might offer further clues about this neural process.

That kind of analysis will likely comprise future work for the Kable lab, which has already begun using these findings to parse why people don't value future outcomes as much as immediate outcomes.

"One theory is that the future isn't as vivid, isn't as tangible and detailed and concrete as something right in front of your face," he says. "We've started to use our identification of the sub-network involved in construction to ask the question, how active is this network when people are thinking about future outcomes compared to the same outcome in the present."

And although the research was completed before COVID-19, Kable sees pandemic-related implications for these findings. "If you described what someone's life was going to be like to them before the pandemic hit—you're going to work from home and wear a mask every time you go outside and not engage in any social contact—it would blow their mind. And yet, once we have the actual experiences, it's no longer so strange. For me, this demonstrates that we still have far to go in understanding our imaginative capabilities."

[Outline]

A research group led by Specially appointed professor, Dr. Tatsuo Suzuki of Shinshu University School of Medicine developed a new purification protocol for Postsynaptic density (PSD) lattice, a core structure of the PSD of excitatory synapses in the central nervous system. The components of the PSD lattice were identified by comprehensive shotgun mass spectrometry and categorized as either minimum essential component (MEC) or non-MEC proteins. Tubulin was found to be a major component of the MEC, with non-microtubule tubulin widely distributed on the purified PSD lattice. The presence of tubulin in and around PSDs was verified by post-embedding immuno-gold labeling EM of cerebral cortex. This study newly identified the PSD lattice backbone structure and provides a new PSD architecture model comprising a non-microtubule tubulin-based backbone structure and its associated proteins, including various PSD scaffold/adaptor proteins and other PSD proteins.

[Background]

Structural changes in postsynaptic density (PSD) (Fig.1A) are important mechanisms for maintaining synaptic plasticity, the basis for memory and learning. The molecular mechanism underlying changes in PSD structure (PSD remodeling) is currently unknown. A complete understanding of the structure of PSD is indispensable to fully elucidate the molecular mechanisms of spine and PSD dynamics during the expression of synaptic plasticity. Currently, it is tacitly believed that PSD is formed as an assembly of various kinds of scaffold/adaptor proteins (Scaffold/adaptor assembly model) (Fig. 1B right). On the contrary, the PSD lattice meshwork structure was found to be buried in the PSD by EM observation as early as the 1970's. However, major constituents of the PSD lattice and the relationship between the PSD lattice and the scaffold protein assembly model, remain unknown (Fig. 1B). In a previous study, the same research group purified a PSD lattice and proposed "PSD lattice-based dynamic nanocolumn" model (Fig. 3A) for the molecular architecture of PSD, in which the scaffold protein model and the PSD lattice model are combined (Suzuki et al., 2018). However, the group was unable to elucidate the molecular components of the PSD lattice due to the insolubility of the protein components.

[The key results of this research]

1) New purification protocol of PSD lattice was established.

2) PSD lattice backbone structure was newly identified (Fig. 3B).

3) Tubulin was by far the most common component of the PSD lattice backbone structure and widely distributed on the purified PSD lattice structure (Fig. 2A).

4) Tubulin associated with the PSD lattice backbone structure is in a non-microtubule form (Fig. 2A).

5) Postembedding immuno-gold EM observation using anti-tubulin antibody confirmed the presence of tubulin-immunoreactivity in and around PSD in the mouse brain (Fig. 2B).

6) Only a minimum amount of typical PSD scaffold/adaptor proteins are associated with PSD lattice backbone structure.

[Conclusion from the results and significance of this study]

This study proposes a PSD lattice model comprising a non-microtubule tubulin-based backbone structure and its associated proteins, including various PSD scaffold/adaptor proteins and other PSD proteins. (Fig. 3B) (This is the 2nd version of our PSD architecture model proposed in 2018.)

PSD lattice backbone structure is different from the three-dimensional assembly constructed by postsynaptic scaffold/adaptor proteins (Fig. 3B).

In the new model, non-microtubule tubulin may play an important role as a platform to which PSD scaffold/adaptor proteins and various PSD-functioning molecules become associated while synapses mature and reorganize (Fig. 3B).

[Future research prospects]

1) Elucidation of the mechanism of how non-microtubule type tubulin is related with PSD lattice backbone is important.

2) Role of PSD lattice other than essential cytoskeleton for the PSD should be searched.

3) Mechanisms of synaptogenesis and synaptic plasticity involving PSD lattice are important research targets.