Culture

A STUDY into the impact of the COVID-19 lockdown on the mental health of people in Soweto has found a significant link between symptoms of depression and how likely people felt they were to be infected.

Researchers also found that both the perceived risk of infection and the likelihood of depression and anxiety increased among people who had suffered childhood trauma and among those already suffering the effects of poverty and deprivation.

Associations between depression and issues such as hunger, violence, poor healthcare, and high rates of poverty have long been recognised, but this study is the first to look at the mental health effects of the pandemic and national lockdown in South Africa under those conditions.

Researchers spoke to more than 200 adults who were already part of a long-term health study in Soweto. This had surveyed 957 people in the months before the pandemic, measuring their risk of mental ill-health, including depression, by asking them to score their mood, feelings, and behaviour. The participants were also asked about day-to-day adversity, such as family strife, poverty, deprivation, and violence; about their ways of coping, including support from friends, family, and church; and about adverse experiences in childhood like abuse, neglect, and household dysfunction.

The follow-up survey was carried out over the phone after the first six weeks of lockdown. It asked people to score themselves against major symptoms of depression during the previous month, assessed their knowledge of COVID-19 and how to protect against it, and asked whether they thought they were at less risk, the same risk or a greater risk than others.

The results, published in the Cambridge journal, Psychological Medicine, showed people were two times as likely to experience significant depressive symptoms for every step increase in their perceived risk from COVID-19. It was also found that those with a history of childhood trauma were more likely to have a higher perceived risk of contracting the virus.

In all, 14.5 per cent of those surveyed were found to be at risk of depression, with 20 per cent indicating that COVID-19 caused them deep worry, anxiety, or led to them 'thinking too much' about the virus and its impact.

While the majority did not think COVID-19 affected their mental health, both the data and what people said about its impact on their lives suggested otherwise.

Dr. Andrew Wooyoung Kim of Northwestern University, who co-directed the study for the Developmental Pathways for Health Research Unit at the University of the Witwatersrand, said: "This discrepancy may be due to different ideas of mental health, including mental health stigma.

"While participants believed that the pandemic did not affect their mental health or their 'mind', the strong relationship between perceived risk and depressive symptoms raises the concern that they may not be aware of the potential threats to their mental health during COVID-19."

These threats were amplified by other pre-existing adversities, said Dr Kim and his colleagues, including hunger and violence, an overburdened healthcare system, a high prevalence of chronic and infectious disease, and alarming rates of poverty and unemployment.

They argue that the pressures of COVID-19 and lockdown risk adding to the already high levels of mental illness among people in South Africa, where one in three experience some kind of mental disorder in their lifetimes and where only 27 per cent of patients with a severe mental illness receive treatment.

Dr Kim said: "Our study re-emphasizes the importance of prioritizing and provisioning accessible mental health resources for resource-limited communities in Soweto and across South Africa."

From making a small calculator work to generating energy to produce the entire output of an important brewery, solar energy has been undergoing significant growth in recent years, taking the place of nonrenewable energy resources that negatively affect the environment.

In addition to producing clean energy, solar plants can be adapted to different sizes and allow for self-consumption. Over the last few years, their profitability as compared to other kinds of energy has become increasingly greater due to the lowering of prices of the materials used and the continued optimizations that have been applied stemming from research in the science and technology sector.

The University of Cordoba chose to continue improving upon the technical services at solar plants by focusing on some of the still existing disadvantages: the high variability of solar resources and the shadows that are cast among the collectors. Specifically, they focused on photovoltaic plants, those that convert solar light into electricity.

At photovoltaic plants, it is common to use two-axis solar trackers. "These trackers are inspired by sunflowers and they seek to maximize solar light collection by the movement of the photovoltaic modules. However, this movement can create partial shadows among the modules, which negatively affects energy production", explains Luis Manuel Fernández Ahumada, one of the researchers working on the study.

This research integrates two methodologies that were undertaken in previous studies. On the one hand, a mathematical model was created to optimize the collection of solar light, applicable to isolated trackers. On the other hand, using a simplified geometric model, they were able to characterize possible shadows among the trackers.

Having done this analysis, specific design recommendations were proposed that were studied at photovoltaic plants with two-axis tracking systems located in Cordoba. Using the backtracking technique, the panels followed sunlight as they are programmed to do and, when they detected that one could cast a shadow on others, they backtrack, and thus avoid casting shadows upon each other.

"It was proven that with this tracking strategy, these plants could produce at least 2% more energy annually", points out Luis Manuel Fernández Ahumada. Hence, this maximizes the performance of one plant compared to others that do not account for energy loss from shadows being cast among panels.

This study is framed in the Solar Energy Assessment and Planning Tool (SEAP) service within CLARA project that aims to create an ecosystem of services to use weather forecasting data in order to improve processes. Funded by the European Union in the area of the program Horizon 2020, the project is carried out by a European consortium made up of universities, regional governments and businesses. The SEAP service focuses on improving photovoltaic production and is coordinated by the University of Cordoba, participating via the TEP-215 Physics for Renewable Energy research group.

The group continues to work in the field of optimization of solar plants. Currently, they are working on making sensor devices that provide the optimal positioning for solar trackers in real time in order to maximize energy production without creating shadows. In another line of work, they are studying the use of weather forecasting in creating strategies to get optimal solar tracking that will produce the maximum amount of energy possible.

The results of the first theorical-experimental tests are conclusive: compared to diesel, the technology proposed by the CMT-Thermal Engines researchers of the UPV decreases the levels of NOx and soot by 92% and 88% respectively, and CO2 emissions from the exhaust pipe by 15% - down to 52 g/tkm (gram per tonne and kilometre) -, thus getting ahead of the demanding anti-contamination regulation approved for 2025. These results have been published in the journal Energy Conversion and Management.

"The goal of the study was to assess the technical-economical potential of parallel hybrid technology applied alongside dual-fuel technology as an alternative to pure electrification in order to achieve a drastic decrease in CO2 emissions required by 2025 - in five years, these lorries must emit 15% less carbon dioxide. And the figures we have obtained, both for carbon dioxide and some of the other most harmful contaminating agents from combustion engines, have been very positive," highlights Antonio García, full professor at the UPV and researcher at CMT-Thermal Engines.

Along with the CMT-Thermal Engines group of the UPV, companies Volvo Group Trucks Technology (France) and Aramco Overseas Company (France), which CMT-Thermal Engines has worked with for over a decade, have also taken part in the study.

Maximum efficiency, less contamination

Uniting both technologies, dual-fuel combustion and a hybrid structure, makes it possible to maximise the benefits of both of them. "Electrical assistance prevents the use of the thermal engine in low-efficiency conditions. At the same time, the addition of the thermal engine in the full system makes it possible to obtain economically-viable vehicles compared to the purely electrical and relatively clean ones," says Antonio García.

The CMT-Thermal Engines researcher stresses that the dual-fuel parallel hybrid combustion technology makes it possible to decrease NOx emissions by over 90% compared to Diesel, with almost zero soot. Furthermore, optimisation of the electrical components allows the thermal engine to work in its areas of highest performance, with 13% less fuel consumption than a conventional diesel vehicle.

"As well as this proposal for a new engine, we are working on the use of alternative fuels, such a e-fuels, to maximise the benefit of this technology in terms of the analysis of the lifecycle of CO2, thus thinking ahead for possible changes in the upcoming regulation," says García.

Mathematical models are key

Santiago Martínez, researcher at the CMT-Thermal Engines of the UPV highlights the importance of computer simulations in the task of sizing the different electrical components to use them in a parallel hybrid structure together with the dual-fuel combustion system. In this sense, the numerical simulation has been one of the pillars in order to achieve the results of the study in a relatively short period of time.

"For this study, a virtual model of the original vehicle was created with a conventional diesel mechanism, and it was validated by making use of experimental data obtained from the lorry by company Volvo. Afterwards, we conducted the optimisation of the different electrical components such as the engine, generator and battery, taking into account the real driving cycles in which the lorry would conduct its activity. This methodology makes it possible to decrease the amount of experimental trials by a large amount, and therefore also the cost of developing any given technology," highlights Martínez.

Which battery would be the most efficient?

Furthermore, Javier Monsalve, another member of the CMT-Thermal Engines team, explains that in order to determine the potential of this technology compared to current technology, its cost must be evaluated taking into account two main factors. On one hand, the price of the batteries, and on the other, the possible savings in terms of penalisation for an excess of CO2 emissions. In this sense, in their analysis, the researchers took into account the current price of the batteries (approx. €176/kWh) as well as their estimated cost in 2025 (approx. €100/kWh), as well as the economical penalty enforced on lorry manufacturers if they do not respect the CO2 limit in 2025, which will be €4,250 per g/tkm.

"Taking into account the current price of the batteries and the penalties proposed by the European Union for 2025, the dual-fuel technology for lorries between 18 and 25 tonnes has the best benefits when using small-capacity batteries (up to 10kWh). The use of packs of larger batteries would substantially increase the end cost of the vehicle. It is true that it would drop with the foreseeable fall in the price of the lithium-ion technology in coming years. But until then, it will be hard to see purely electrical lorries manufactured in mass," concludes Monsalve.

Osaka, Japan - Power electronics regulate and modify electric power. They are in computers, power steering systems, solar cells, and many other technologies. Researchers are seeking to enhance power electronics by using silicon carbide semiconductors. However, wear-out failures such as cracks remain problematic. To help researchers improve future device designs, early damage detection in power electronics before complete failure is required.

In a study recently published in IEEE Transactions on Power Electronics, researchers from Osaka University monitored in real time the propagation of cracks in a silicon carbide Schottsky diode during power cycling tests. The researchers used an analysis technique, known as acoustic emission, which has not been previously reported for this purpose.

During the power cycling test, the researchers mimicked repeatedly turning the device on and off, to monitor the resulting damage to the diode over time. Increasing acoustic emission corresponds to progressive damage to aluminum ribbons affixed to the silicon carbide Schottsky diode. The researchers correlated the monitored acoustic emission signals to specific stages of device damage that eventually led to failure.

"A transducer converts acoustic emission signals during power cycling tests to an electrical output that can be measured," explains lead author ChanYang Choe. "We observed burst-type waveforms, which are consistent with fatigue cracking in the device."

The traditional method of checking whether a power device is damaged is to monitor anomalous increases in the forward voltage during power cycling tests. Using the traditional method, the researchers found that there was an abrupt increase in the forward voltage, but only when the device was near complete failure. In contrast, acoustic emission counts were much more sensitive. Instead of an all-or-none response, there were clear trends in the acoustic emission counts during power cycling tests.

"Unlike forward voltage plots, acoustic emission plots indicate all three stages of crack development," says senior author Chuantong Chen. "We detected crack initiation, crack propagation, and device failure, and confirmed our interpretations by microscopic imaging."

To date, there has been no sensitive early-warning method for detecting fatigue cracks that lead to complete failure in silicon carbide Schottsky diodes. Acoustic emission monitoring, as reported here, is such a method. In the future, this development will help researchers determine why silicon carbide devices fail, and improve future designs in common and advanced technologies.

In situ sequencing enables gene activity inside body tissues to be depicted in microscope images. To facilitate interpretation of the vast quantities of information generated, Uppsala University researchers have now developed an entirely new method of image analysis. Based on algorithms used in artificial intelligence, the method was originally devised to enhance understanding of social networks. The researchers' study is published in The FEBS Journal.

The tissue composing our organs consists of trillions of cells with various functions. All the cells in an individual contain the same genes (DNA) in their nuclei. Gene expression occurs by means of "messenger RNA" (mRNA) - molecules that carry messages from the nucleus to the rest of the cell, to direct its activities. The mRNA combination thus defines the function and identity of every cell.

RNA transcripts are obtainable through in situ sequencing. The researchers behind the new study had previously been involved in developing this method, which shows millions of detected mRNA sequences as dots in microscope images of the tissue. The problem is that distinguishing all the important details may be difficult. This is where the new AI-based method may come in useful, since it allows unsupervised detection of cell types as well as detection of functions within an individual cell and of interactions among cells.

"We're using the latest AI methods - specifically, graph neural networks, developed to analyse social networks; and adapting them to understand biological patterns and successive variation in tissue samples. The cells are comparable to social groupings that can be defined according to the activities they share in their social networks like Twitter, sharing their Google search results or TV recommendations," says Carolina Wählby, professor of quantitative microscopy at the Department of Information Technology, Uppsala University.

Earlier analytical methods of this type of data depend on knowing which cell types the tissue contains, and identifying the cell nuclei in it, in advance. The method conventionally used, known as "single-cell analysis", may lose some mRNA and miss certain cell types. Even with advanced automated image analysis, it is often difficult to find the various cell nuclei if, for example, the cells are packed densely together.

"With our analysis, which we call 'spage2vec', we can now get corresponding results without any previous knowledge of expected cell types. And what's more, we can find new cell types and intra- or intercellular functions in tissue," Wählby says.

The research group are now working further on its analytical method by investigating differentiation and organisation of various types of cells during the early development of the heart. This is pure basic research, intended to provide more knowledge of the mechanisms that govern development, both when everything is functioning as it should and when a disease is present. In another project, a collaboration with cancer researchers, the Uppsala group are hoping to be able to apply the new methods to gain a better understanding of how tumour tissue interacts, at molecular level, with surrounding healthy tissue. The aim is that, in the long term, this will culminate in better treatments that can be adapted to individual patients.

Bacteria in the small intestine can deaminate levodopa, the main drug that is used to treat Parkinson's disease. Bacterial processing of the unabsorbed fractions of the drug results in a metabolite that reduces gut motility. These findings were described in the journal BMC Biology on 20 October by scientists from the University of Groningen. Since the disease is already associated with constipation, processing of the drug by gut bacteria may worsen gastrointestinal complications.

Patients with Parkinson's disease are treated with levodopa, which is converted into the neurotransmitter dopamine in the brain. Levodopa is absorbed in the small intestine, although not all of it. Eight to ten per cent travels further to a more distal part of the gut and this percentage increases with age and administered drug dosage. In this distal part of the gut, it may encounter bacterial species such as Clostridium sporogenes, which can deaminate (remove an -NH2 group from) aromatic amino acids.

Intestinal motility

'Last year, other scientists demonstrated this bacterium's deamination activity on aromatic amino acids,' says Sahar El Aidy, assistant professor of Microbiology at the University of Groningen. El Aidy knew that the chemical structure of levodopa is similar to that of the aromatic amino acid tyrosine. 'This suggested that the bacterium could metabolize levodopa, which may affect the intestinal motility of individuals with Parkinson's disease.'

Studies by El Aidy and her research team revealed that the bacterium C. sporogenes does indeed break down levodopa into 3-(3,4-dihydroxy phenyl)propionic acid (DHPPA). 'This process involves four steps, three of which were already known. However, we uncovered the initial step, which is mediated by a transaminase enzyme.'

Coffee

Next, the team investigated whether DHPPA has an effect on motility of the distal small bowel, using an ex vivo model system for gut motility. Gut motility was induced by adding acetylcholine, after which DHPPA was added. 'Within five minutes, this decreased the motility by 69 percent, rising to 73 percent after ten to fifteen minutes.' This clearly showed that the levodopa metabolite can reduce gut contractions, which could lead to constipation.

To test whether these findings are relevant to Parkinson's disease patients, Sebastiaan van Kessel, a PhD student in El Aidy's research team, tested patients' stool samples for the presence of DHPPA. 'Because it is also produced as a breakdown product of coffee and fruits, we compared samples from patients with those from healthy controls with a comparable diet,' explains El Aidy. The result showed significantly higher DHPPA levels in stool samples of Parkinson's disease patients who were treated with levodopa. To confirm that this metabolite resulted from the presence and activity of the gut bacterium C. sporogenes, or other gut bacteria capable of anaerobic deamination, bacteria from stool samples were cultured and fed with the precursor of DHPPA. This experiment showed that the bacteria can indeed metabolize levodopa to produce DHPPA.

Inhibitors

All of these results suggest that a residue of the drug levodopa, which is not absorbed early on in the gut, can be metabolized by gut bacteria into DHPPA, which then reduces the motility of the distal gut. As constipation is already one of the symptoms of Parkinson's disease, it is unfortunate that the drug to treat the symptoms can itself further reduce gut motility due to gut bacterial metabolization. 'However, now that we know this, it is possible to look for inhibitors of the enzymes in the deamination pathway identified in our study.'

Simple Science Summary

(Philadelphia, PA) - Like a cold front that moves in, setting the stage for severe weather, coronavirus infection triggers showers of infection-fighting immune molecules - showers that sometimes escalate into a chaotic immune response known as a cytokine storm. About 20 to 30 percent of patients hospitalized with COVID-19 develop severe immune manifestations, in some instances leading to cytokine storm, with life-threatening organ damage and high risk of death.

Predicting which COVID-19 patients will develop cytokine storm is challenging, owing to the many variables that influence immune function. But now, in breakthrough work, researchers at the Lewis Katz School of Medicine at Temple University (LKSOM) have developed and validated predictive criteria for early identification of COVID-19 patients who are developing hyperimmune responses, raising the possibility for early therapeutic intervention.

"If we can anticipate cytokine storm, we can apply treatment sooner and possibly decrease mortality," explained Roberto Caricchio, MD, Chief of the Section of Rheumatology, Director of the Temple Lupus Program, Professor of Medicine and Microbiology and Immunology at LKSOM, and lead author on the new report.

The report, published online in the Annals of the Rheumatic Diseases, is the first to identify criteria that can be readily used in clinical practice to potentially head off the worst of the hyperimmune attack against COVID-19.

The breakthrough is the result of an extensive collaboration between researchers and clinicians across multiple departments in the Lewis Katz School of Medicine and Temple University Hospital, constituting the Temple University COVID-19 Research Group.

According to Dr. Caricchio, large numbers of COVID-19 patients have been treated at Temple since the pandemic emerged in the United States. "We have a significant amount of data in terms of variables to predict cytokine storm," he said.

Since early March, every patient admitted to Temple University Hospital (TUH) has had data on more than 60 different laboratory variables collected daily until the time of recovery or time of death. Among variables measured every day are factors like white blood cell count, metabolic enzyme activity, and markers of inflammation and respiratory function. Importantly these markers are commonly used in hospitals across the globe and therefore are readily available.

The research group carried out statistical analyses on laboratory data for 513 COVID-19 patients hospitalized at TUH in March and April, 64 of whom developed cytokine storm. A genetic algorithm was used to identify cut-off values for each individual laboratory variable to define the predictive requirements for cytokine storm. Genetic algorithms mimic the processes of natural selection and evolution in analyzing the data, and in this case, over multiple iterations, the algorithm turned up variables indicating which patients are most likely to develop cytokine storm.

Overall, the analyses yielded six predictive criteria comprising three clusters of laboratory results relating to inflammation, cell death and tissue damage, and electrolyte imbalance. In particular, patients in cytokine storm exhibited a proinflammatory status and elevated levels of enzymes indicating significant systemic tissue damage. Moreover, patients who met the criteria had extended hospital stays and were at increased risk of death from COVID-19, with almost half of patients who experienced cytokine storm meeting all criteria within the first day of hospitalization.

The researchers validated the criteria in a subsequent cohort of 258 patients admitted to TUH for COVID-19 infection. "The algorithm correctly predicted cytokine storm in almost 70 percent of patients," Dr. Caricchio said.

"The ability to reproduce our results in a second cohort of patients means that our group of variables are effective criteria for cytokine storm diagnosis in COVID-19 patients," he added. The final step now is to have the criteria validated by other centers where COVID-19 patients are admitted for care.

Dr. Caricchio noted that the criteria could be applied to COVID-19 patients at any hospital or level of hospitalization anywhere in the world. "This makes the criteria very valuable for guiding decisions about how to treat COVID-19 patients worldwide," he said. Applied more broadly, the criteria could greatly facilitate early diagnosis and intervention, helping save many lives.

"This was a truly collective effort between frontline clinicians, researchers, and statisticians, and the results are one of the many testaments to the exceptional work Temple University and the Temple University Health System have performed," Dr. Caricchio concluded.

They call it artificial intelligence -- not because the intelligence is somehow fake. It's real intelligence, but it's still made by humans. That means AI -- a power tool that can add speed, efficiency, insight and accuracy to a researcher's work -- has many limitations.

It's only as good as the methods and data it has been given. On its own, it doesn't know if information is missing, how much weight to give differing kinds of information or whether the data it draws on is incorrect or corrupted. It can't deal precisely with uncertainty or random events -- unless it learns how. Relying exclusively on data, as machine-learning models usually do, it does not leverage the knowledge experts have accumulated over years and physical models underpinning physical and chemical phenomena. It has been hard to teach the computer to organize and integrate information from widely different sources.

Now researchers at the University of Delaware and the University of Massachusetts-Amherst have published details of a new approach to artificial intelligence that builds uncertainty, error, physical laws, expert knowledge and missing data into its calculations and leads ultimately to much more trustworthy models. The new method provides guarantees typically lacking from AI models, showing how valuable -- or not -- the model can be for achieving the desired result.

Joshua Lansford, a doctoral student in UD's Department of Chemical and Biomolecular Engineering, and Prof. Dion Vlachos, director of UD's Catalysis Center for Energy Innovation, are co-authors on the paper published Oct. 14 in the journal Science Advances. Also contributing were Jinchao Feng and Markos Katsoulakis of the Department of Mathematics and Statistics at the University of Massachusetts-Amherst.

The new mathematical framework could produce greater efficiency, precision and innovation for computer models used in many fields of research. Such models provide powerful ways to analyze data, study materials and complex interactions and tweak variables in virtual ways instead of in the lab.

"Traditionally in physical modelings, we build a model first using only our physical intuition and expert knowledge about the system," Lansford said. "Then after that, we measure uncertainty in predictions due to error in underlying variables, often relying on brute-force methods, where we sample, then run the model and see what happens."

Effective, accurate models save time and resources and point researchers to more efficient methods, new materials, greater precision and innovative approaches they might not otherwise consider.

The paper describes how the new mathematical framework works in a chemical reaction known as the oxygen reduction reaction, but it is applicable to many kinds of modeling, Lansford said.

"The chemistries and materials we need to make things faster or even make them possible -- like fuel cells -- are highly complex," he said. "We need precision.... And if you want to make a more active catalyst, you need to have bounds on your prediction error. By intelligently deciding where to put your efforts, you can tighten the area to explore.

"Uncertainty is accounted for in the design of our model," Lansford said. "Now it is no longer a deterministic model. It is a probabilistic one."

With these new mathematical developments in place, the model itself identifies what data are needed to reduce model error, he said. Then a higher level of theory can be used to produce more accurate data or more data can be generated, leading to even smaller error boundaries on the predictions and shrinking the area to explore.

"Those calculations are time-consuming to generate, so we're often dealing with small datasets -- 10-15 data points. That's where the need comes in to apportion error."

That's still not a money-back guarantee that using a specific substance or approach will deliver precisely the product desired. But it is much closer to a guarantee than you could get before.

This new method of model design could greatly enhance work in renewable energy, battery technology, climate change mitigation, drug discovery, astronomy, economics, physics, chemistry and biology, to name just a few examples.

Artificial intelligence doesn't mean human expertise is no longer needed. Quite the opposite.

The expert knowledge that emerges from the laboratory and the rigors of scientific inquiry is essential, foundational material for any computational model.

New Orleans, LA - A review of heat-not-burn (HNB) tobacco products from the laboratory of Dr. Jason Gardner, Professor of Physiology at LSU Health New Orleans School of Medicine, reports an association with elevated blood pressure, increased heart rate, cell death, and circulatory dysfunction shown by early studies. Additionally, chemicals found in the vapor produced by HNB devices have previously been shown to impair lung function, put users at risk of heart attack and stroke, cause cancers, increase circulating low-density lipoprotein ("bad cholesterol") and more. The review is published in the American Journal of Physiology-Heart and Circulatory Physiology, available online here.

Cigarette smoking continues to decline globally, but vaping is becoming more popular, especially among youth and young adults. Recent cases of vaping-associated lung injury may lead consumers to try new methods of nicotine consumption. Heat-not-burn products are newcomers to the U.S. market. They produce nicotine-containing vapor by heating tobacco at low temperatures. This is in contrast to cigarettes that use high temperatures to burn tobacco and produce smoke or e-cigarettes that heat e-liquid, which contains nicotine but not tobacco, to produce vapor.

Due to the novelty of these products, little research has been conducted on HNB devices. The Gardner lab compiled findings from dozens of human, animal, and cell culture studies to determine associated inhalants and potential health effects, with an emphasis on the heart, arteries, and veins. Findings suggest that HNB devices produce fewer pollutants than cigarettes, but it is unclear if these reductions are reflected in health outcomes of users.

"While relatively new to the U.S., heat-not-burn products have become popular in other countries including Japan, Italy, and Korea," notes lead author Nicholas Fried, an MD/PhD student in Dr. Gardner's laboratory. "These products are often touted as a replacement for cigarettes, but the evidence does not necessarily support that. Almost all Korean users of heat-not-burn products are also current cigarette smokers; nearly half of Italian users had never even smoked a cigarette. These trends worryingly suggest that heat-not-burn may be a compliment or gateway to cigarette smoking, rather than a 'healthy' replacement. More troubling, nearly 2% of high school students in the U.S. are already using HNB tobacco products, and surveys show that 25% of students are susceptible to trying them. There is potential for these devices to become a significant public health issue."

Dr. Gardner adds, "Heat-not-burn devices are marketed as a safer alternative to cigarettes for existing smokers. However, as we have learned from vaping and e-cigarettes, these products are very likely to be used by minors and never-smokers due to marketing, flavor options, and lack of social stigma that is found with traditional cigarettes."

The authors conclude, "Use of these products can lead to nicotine addiction and additional clinical, basic science, and epidemiological studies are needed to better understand the health effects of HNB products. This knowledge will assist consumers, physicians, lawmakers, and regulatory bodies in making informed decisions about these products."

COLUMBUS, Ohio - Knowing you have developed antibodies against the SARS-CoV-2 virus after recovering from COVID-19 doesn't tell you everything about your immunity. The levels and even types of antibodies can differ among patients, and those differences can influence whether a person is protected against being reinfected.

Scientists at The Ohio State University have developed a new lab testing procedure for the detection of antibodies against SARS-CoV-2 that gives results more quickly than existing assays and specifically identifies so-called "neutralizing" antibodies - those that protect by blocking infection of cells.

"With many assays currently in use, we can detect antibodies, but that doesn't tell us if they're neutralizing antibodies. We only know the level of antibodies someone has," said Shan-Lu Liu, professor in the Ohio State College of Veterinary Medicine's Department of Veterinary Biosciences and the senior author of a new journal article describing the assay.

"Some antibodies might be protective, some might not be protective, and some might even enhance infection - we know with this type of coronavirus and some other viruses, some antibodies can even do harm," he said. "Our assay examines whether antibodies are potentially protective, which means they prevent a patient from reinfection and block viral replication. That's the outcome of infection that we want people to have."

In analyses of blood samples from several different populations that had tested positive for COVID-19, the researchers found with this new assay that, overall, ICU patients had produced the highest concentration of neutralizing antibodies, and convalescent plasma donors and health care workers had the lowest antibody levels.

"So the more severe the disease, the higher the antibody levels produced. And what this tells us is there is a wide spectrum of different antibody levels after infection," said Liu, also an investigator in the Center for Retrovirus Research and co-director of the Viruses and Emerging Pathogens Program in Ohio State's Infectious Diseases Institute. "We're in a pandemic now, but eventually we'll be able to see not just how many people were infected, but also the outcome. Our assay could be used to tell whether antibodies have been developed in individuals who have had contacts with SARS-CoV-2."

The research is published online in the journal JCI Insight.

Liu and colleagues developed what is called a "pseudotype" virus neutralizing antibody assay, in which an HIV vector and core is coated with the SARS-CoV-2 spike protein to detect antibodies against the coronavirus. The team applied a new approach by selecting a different form of light-producing enzyme that can be detected conveniently in culture media containing the virus-infected cells. That choice saved several steps, and time, in the detection process without losing accuracy and sensitivity to the target virus.

Co-first authors Cong Zeng, a postdoctoral researcher, and Jack Evans, a student in the molecular, cellular and developmental biology graduate program, completed the majority of the work to develop the assay.

With the new analytical tool in hand, scientists in the College of Veterinary Medicine collaborated with Gerard Lozanski and others in the College of Medicine to analyze 221 patient blood samples to validate the effectiveness of the assay and verify that the detection test could be scaled up for widespread screening.

The samples were derived from 104 hospitalized COVID-19 patients, 49 of whom were in intensive care; 42 health care professionals who had tested positive for COVID-19; 38 convalescent plasma donors (recovered patients who donated plasma for potential therapeutic use in very sick COVID-19 patients); and 37 control samples from patients who had been hospitalized with respiratory conditions before September 2019.

Results showed that, in general, hospitalized patients - and ICU patients in particular - had the highest concentrations, or titers, of neutralizing antibodies in their systems. However, over 14% of those who had been hospitalized had no or very low levels of antibodies.

Of the health care professionals, 40% were negative for neutralizing antibodies and 36% had low concentrations. And more than half of the convalescent blood donors had concentrations of antibodies that were too low to qualify them as donors for treatment of COVID-19 patients, Liu said.

The assay detected no SARS-CoV-2 antibodies in the samples from people who had been sick with other types of respiratory diseases.

The test accuracy was further validated by verifying in a lab setting that the antibodies detected in the COVID-19 patient blood samples did in fact neutralize the authentic SARS-CoV-2 virus.

It won't be long before the assay is put to a larger test. The effectiveness, sensitivity and specificity of the assay were important factors in Ohio State's successful application for a $10 million National Cancer Institute grant awarded last month for studies of the long-term impact of COVID-19 on first responders, health care workers and the general population. Two of the co-authors on the JCI Insights paper will be co-principal investigators of the first-responders study: Eugene Oltz, chair of microbial infection and immunity in the College of Medicine, and Linda Saif, Distinguished University Professor in the College of Veterinary Medicine's Department of Veterinary Preventive Medicine and the Food Animal Health Research Program in the College of Food, Agricultural and Environmental Sciences.

"We will use this assay to conduct a serological study of first responders in Columbus, among others," Liu said.

Additional applications could include screening for protective qualities in lab-manufactured monoclonal antibodies designed for therapeutic purposes and neutralizing antibody production in vaccine candidates.

Patent applications have been filed covering the assay and its use in a variety of applications. Inventors named on the applications are Liu, Zeng, Evans, and co-authors Panke Qu and Yi Min Zheng.

"We are pleased to have developed a neutralization assay which provides a sensitive, specific and simple method for determining the neutralizing antibody titers in patient serum or plasma with results being achieved in 24 hours - without requiring access to a biosafety level-3 facility," Liu said.

"We'd like to make it widely available as quickly as possible because we think it's a rapid and simple system compared to other systems."

Situated at the threshold of the South Asian monsoon, the Thar Desert is an important region for understanding how past environmental change impacted patterns of human migration and adaptation to new habitats (Figure 1). Recent research highlighting the role of the Thar Desert in human prehistory has indicated that humans spread eastwards into the region starting from 114 thousand years ago during a phase of enhanced monsoonal rainfall, when the desert was transformed into lush grasslands. However, more recent phases of sand dune activity have obscured these ancient landscapes inhabited by earlier human populations.

In a new study published in Quaternary Science Reviews, researchers from The Max Planck Institute for the Science of Human History (MPI-SHH), Anna University, and the Indian Institute of Science, Education and Research (IISER) Kolkata document evidence for river activity in the central Thar Desert. This evidence indicates a river flowed with phases of activity dating to approx. 172, 140, 95 and 78 thousand years ago, nearby to Bikaner, which is over 200 km away from the nearest modern river. These findings predate evidence for activity in modern river courses across the Thar Desert as well as dried up course of the Ghaggar-Hakra River. The presence of a river running through the central Thar Desert would have offered a life-line to Palaeolithic populations, and potentially an important corridor for migrations.

Lost Rivers of the Thar Desert

Located at the threshold of monsoonal Asia, the Thar Desert marks the eastern extent of the desert belt that stretches westwards across Arabia and the Sahara. While this desert belt is typically thought of as inhospitable to early humans, it is becoming increasingly clear that during humid phases in the past human populations have prospered in these landscapes. This is perhaps best known in western South Asia from studying the Indus Civilisation (also known as the Harappan Civilisation) which flourished at the margins of the Thar Desert along the course of the now-seasonal Ghaggar-Hakra River between 3200-1500 BCE, and is thought to have inspired the mythological Saraswati River mentioned in the Rig Veda.

Yet the potential importance of 'lost' rivers for earlier inhabitants of the Thar Desert have been overlooked. "The Thar Desert has a rich prehistory, and we've been uncovering a wide range of evidence showing how Stone Age populations not only survived but thrived in these semi-arid landscapes," says Jimbob Blinkhorn of MPISHH. "We know how important rivers can be to living in this region, but we have little detail on what river systems were like during key periods of prehistory".

Studies of satellite imagery have shown a dense network of river channels crossing the Thar Desert. "These studies can indicate where rivers and streams have flown in the past, but they can't tell us when" explains Prof Hema Achyuthan of Anna University, Chennai. "To demonstrate how old such channels are, we had to find evidence on the ground for river activity in the middle of the desert".

Nal Quarry

A deep deposit of river sands and gravels was studied by the team, which had been exposed by quarrying activity near the village of Nal, just outside of Bikaner. By studying the different deposits, the researchers were able to document different phases of river activity. "We immediately saw evidence for a substantial and very active river system from the bottom of the fluvial deposits, which gradually decreased in power through time" explained Achyuthan. "Standing in the middle of the desert, the question we had to answer was 'How old was this river?'".

The researchers used a method called luminescence dating to understand when quartz grains in the river sands were buried. The results indicated that the strongest river activity at Nal occurred at approx. 172 and 140 thousand years ago, at a time when the monsoon was much weaker than today in the region. River activity continued at the site between 95 to 78 thousand years ago, after which only limited evidence for the presence of a river at the site, with evidence for a brief reactivation of the channel 26 thousand years ago.

A life-line in the desert

The age of this river flowing in the middle of the desert is of particular interest. The river was flowing at its strongest during a phase of weak monsoonal activity in the region, and may have been a life-line to human populations enabling them to inhabit the Thar Desert. The timeframe over which this river was active also overlaps with significant changes in human behaviour in the region, which have been linked with the earliest expansions of Homo sapiens from Africa into India. "This river flowed at a critical timeframe for understanding human evolution in the Thar Desert, across South Asia and beyond" says Blinkhorn, adding "This suggests landscape in which the earliest members of our own species, Homo sapiens, first encountered the monsoons and crossed the Thar Desert may have been very different to the landscape we can see today".

The next phase of research is to demonstrate where the river flowed from. Studies of satellite images have suggested a potential connection with a Himalayan source, such as the Sutlej. "We can't demonstrate where the river flowed from at present" says Blinkhorn, adding "but the Indira Ghandi Canal, sourced from the Sutlej River, gives us some insight into what happens when a river flows through the centre of the Thar Desert - plants and wildlife flourish, providing ideal conditions for early human populations."

October 19, 2020

JUPITER, FL--Human cells are encased by a membrane coated with diverse sugar molecules known as glycans. These glycans play many roles in health and disease, making them important to understand. Due to their unique properties, however, scientists have had limited tools to study them and their interactions in the body.

New research from the lab of biochemist Mia Huang, PhD, an assistant professor at Scripps Research in Jupiter, Florida, presents a strategy for capturing elusive interactions among glycans and their protein activators in live human cells. Huang and her colleagues applied the technique to improve understanding of liver disease and immune activation.

Writing in the journal the Proceedings of the National Academies of Sciences on Friday, Huang and colleagues focus on a glycan-binding protein called galectin-3. Collaborating with the lab of Scripps Research chemist Chris Parker, PhD, the team was able to catalog galectin-3's array of receptors by combining two strategies: proximity labelling and quantitative proteomics.

In the process, they discovered hundreds of galectin-3 interactors in live liver stellate cells and immune cells.

"These interactions escape traditional query because of their weak affinity and dynamic binding events," Huang says. "Our findings will empower our ability to approach, and hopefully treat, diseases based on glycosylation-mediated events, especially liver fibrosis and autoimmune disorders."

Finding the hook

Cells communicate with each other through the release of molecular signals. These signals, such as galectin-3, can activate the inflammatory response following viral infection, or generate a buildup of scar tissue following injury, for example.

At the biochemical level, for this to happen, a glycan-binding protein must attach to its membrane receptor like a fisherman's line hook wading through thick kelp to find its catch. Characterizing which hooks fit which glycoproteins is a necessary step to addressing the root causes of many illnesses, Huang says.

A graduate student in Huang's lab, Eugene Joeh, devised a chemical fishing expedition to search for galectin-3. Joeh, a student in Scripps Research's Skaggs Graduate School of Chemical and Biological Sciences, suggested tethering an enzyme called APEX2, chosen for its relatively small size and ability to stay active both inside and outside the cell, to the galectin-3 molecules. He then allowed the paired molecules to freely diffuse onto cells. Next, he added the chemicals biotin phenol and hydrogen peroxide to create highly reactive tags that label the binding complexes so that they could be more easily identified and characterized. He was helped by a participant in the institute's high school internship program, Kenan Fellow Jonathan Hung, a student at Suncoast High School at the time of his internship, now a freshman at Johns Hopkins University.

Liver fibrosis and beyond

The liver plays many roles. It processes nutrients and medicines absorbed through digestion. It clears toxins, breaks down alcohol, and stores or releases fats and sugars during times of plenty or scarcity. It makes bile to help digest fats. Over time, injury to the liver from conditions such as alcoholism, autoimmune disease, drug abuse, or viral hepatitis, can lead to a condition called liver fibrosis. This can cause chronic high blood pressure, cirrhosis or even liver failure.

The events that lead to this unhealthy cascade involve an interaction between liver-based immune white blood cells called macrophages and fat-storing liver cells called stellate cells. The cascade begins when liver macrophages activate liver stellate cells through the release of galectin-3. The docking of galectin-3 to its sugary glycoprotein receptors triggers the stellate cell to ooze collagen and make other changes.

This signal, galectin-3, isn't only a force to consider in liver fibrosis. It also plays an important role in other cells--especially those in the immune system that help defend against infections, cancer and poisons, Huang says.

"It is noteworthy that several of these proteins are important in both the innate and adaptive immune responses," Huang says.

The discovery of so many galectin-3 receptors raises many new questions, she adds. The work continues.

"This has given us a priority list of proteins that will be the subject of further work on the regulation of immunity and the activation of liver stellate cells," she says.

HERSHEY, Pa. -- Certain oral antiseptics and mouthwashes may have the ability to inactivate human coronaviruses, according to a Penn State College of Medicine research study. The results indicate that some of these products might be useful for reducing the viral load, or amount of virus, in the mouth after infection and may help to reduce the spread of SARS-CoV-2, the coronavirus that causes COVID-19.

Craig Meyers, distinguished professor of microbiology and immunology and obstetrics and gynecology, led a group of physicians and scientists who tested several oral and nasopharyngeal rinses in a laboratory setting for their ability to inactivate human coronaviruses, which are similar in structure to SARS-CoV-2. The products evaluated include a 1% solution of baby shampoo, a neti pot, peroxide sore-mouth cleansers, and mouthwashes.

The researchers found that several of the nasal and oral rinses had a strong ability to neutralize human coronavirus, which suggests that these products may have the potential to reduce the amount of virus spread by people who are COVID-19-positive.

"While we wait for a vaccine to be developed, methods to reduce transmission are needed," Meyers said. "The products we tested are readily available and often already part of people's daily routines."

Meyers and colleagues used a test to replicate the interaction of the virus in the nasal and oral cavities with the rinses and mouthwashes. Nasal and oral cavities are major points of entry and transmission for human coronaviruses. They treated solutions containing a strain of human coronavirus, which served as a readily available and genetically similar alternative for SARS-CoV-2, with the baby shampoo solutions, various peroxide antiseptic rinses and various brands of mouthwash. They allowed the solutions to interact with the virus for 30 seconds, one minute and two minutes, before diluting the solutions to prevent further virus inactivation. According to Meyers, the outer envelopes of the human coronavirus tested and SARS-CoV-2 are genetically similar so the research team hypothesizes that a similar amount of SARS-CoV-2 may be inactivated upon exposure to the solution.

To measure how much virus was inactivated, the researchers placed the diluted solutions in contact with cultured human cells. They counted how many cells remained alive after a few days of exposure to the viral solution and used that number to calculate the amount of human coronavirus that was inactivated as a result of exposure to the mouthwash or oral rinse that was tested. The results were published in the Journal of Medical Virology.

The 1% baby shampoo solution, which is often used by head and neck doctors to rinse the sinuses, inactivated greater than 99.9% of human coronavirus after a two-minute contact time. Several of the mouthwash and gargle products also were effective at inactivating the infectious virus. Many inactivated greater than 99.9% of virus after only 30 seconds of contact time and some inactivated 99.99% of the virus after 30 seconds.

According to Meyers, the results with mouthwashes are promising and add to the findings of a study showing that certain types of oral rinses could inactivate SARS-CoV-2 in similar experimental conditions. In addition to evaluating the solutions at longer contact times, they studied over-the-counter products and nasal rinses that were not evaluated in the other study. Meyers said the next step to expand upon these results is to design and conduct clinical trials that evaluate whether products like mouthwashes can effectively reduce viral load in COVID-19-positive patients.

"People who test positive for COVID-19 and return home to quarantine may possibly transmit the virus to those they live with," said Meyers, a researcher at Penn State Cancer Institute. "Certain professions including dentists and other health care workers are at a constant risk of exposure. Clinical trials are needed to determine if these products can reduce the amount of virus COVID-positive patients or those with high-risk occupations may spread while talking, coughing or sneezing. Even if the use of these solutions could reduce transmission by 50%, it would have a major impact."

Future studies may include a continued investigation of products that inactive human coronaviruses and what specific ingredients in the solutions tested inactivate the virus.

INDIANAPOLIS -- Transfers from the nursing home to the emergency department (ED) or the hospital can have negative longer-term impact on the health of older adults. A new study from Regenstrief Institute and Indiana University School of Medicine looked at which residents were most likely to be admitted to the hospital after a trip to the ED with the hope of identifying areas to improve care and reduce unnecessary transfers.

The study team analyzed hundreds of transfers from the nursing facility to the ED and found the factors most associated with discharge back to the facility were:

Falls, trauma or fracture

Bleeding (non-gastrointestinal)

Pain

Residents who had the following characteristics were more likely to be admitted to the hospital following an ED visit:

Cognitive impairment

Respiratory difficulties

"Transfers of care can be very difficult on the patient. Our goal in analyzing this data is to identify new opportunities to improve care, whether it's preventing transfers to the emergency department or finding ways to avoid hospital admissions," said Kathleen Unroe, M.D., MHA, first author of the paper, Regenstrief research scientist and associate professor of medicine at IU School of Medicine. "This information helps us understand what ailments could potentially be treated in the nursing home, avoiding a potentially risky transfer of care."

About one quarter of nursing facility residents will experience a transfer to the hospital over the course of a year. There is a significant likelihood of reduced functioning and overall negative impact on their health after discharge from the hospital.

Analyzing the data for hospital admission

The research team looked at 867 long-stay nursing home facility residents enrolled in the OPTIMISTIC project. OPTIMISTIC (Optimizing Patient Transfers, Impacting Medical quality, Improving Symptoms -- Transforming Institutional Care) was a demonstration project funded by the Centers for Medicare and Medicaid that successfully reduced potentially avoidable hospitalizations of people in nursing homes.

"Through OPTIMISTIC, we've determined that we can reduce avoidable hospitalizations. The next step is to gain a more nuanced understanding of transfers," said Susan Hickman, PhD, senior author on the paper and director of Indiana University Center for Aging Research at Regenstrief Institute. "This helps us find opportunities for improvement from both the facility perspective and the emergency department perspective."

Researchers say these results suggest one area for exploration may include targeted resources and protocols focused on treatment for falls or symptom management within nursing homes. Another potential area of improvement is the creation of strategies to ensure that providers in the ED have more information when they are assessing the residents, as well as an understanding of the care capabilities of the nursing home to increase the number of discharges back to the facility and avoid hospitalizations.

Life on Earth has a long, but also an extremely turbulent history. On more than one occasion, the majority of all species became extinct and an already highly developed biodiversity shrank to a minimum again, changing the course of evolution each time. The most extensive mass extinction took place about 252 million years ago. It marked the end of the Permian Epoch and the beginning of the Triassic Epoch. About three quarters of all land life and about 95 percent of life in the ocean disappeared within a few thousands of years only.

Gigantic volcanic activities in today's Siberia and the release of large amounts of methane from the sea floor have been long debated as potential triggers of the Permian-Triassic extinction. But the exact cause and the sequence of events that led to the mass extinction remained highly controversial. Now, scientists from Germany, Italy and Canada, in the framework of the EU-funded project BASE-LiNE Earth led by Prof. Dr. Anton Eisenhauer from GEOMAR Helmholtz Centre for Ocean Research Kiel in cooperation with the Helmholtz Centre Potsdam GFZ German Research Centre for Geosciences, have for the first time been able to conclusively reconstruct the entire cascade of events at that time using cutting-edge analytical techniques and innovative geochemical modelling. The study has been published today in the international journal Nature Geoscience.

For their study, the BASE-LiNE Earth team used a previously often neglected environmental archive: the shells of fossil brachiopods. "These are clam-like organisms that have existed on Earth for more than 500 million years. We were able to use well-preserved brachiopod fossils from the Southern Alps for our analyses. These shells were deposited at the bottom of the shallow shelf seas of the Tethys Ocean 252 million years ago and recorded the environmental conditions shortly before and at the beginning of extinction", explains Dr. Hana Jurikova. She is first author of the study, which she conducted as part of the BASE-LiNE Earth project and her doctoral thesis at GEOMAR.

By measuring different isotopes of the element boron in the fossil shells, the team was able to trace the development of the pH values in the ocean 252 million years ago. Since seawater pH is tightly coupled to the CO2 concentration in the atmosphere, the reconstruction of the latter was also possible. For the analyses, the team used high-precision isotope analyses at GEOMAR as well as high-resolution microanalyses on the state-of-the-art large-geometry secondary ion mass spectrometer (SIMS) at GFZ.

"With this technique, we can not only reconstruct the evolution of the atmospheric CO2 concentrations, but also clearly trace it back to volcanic activity. The dissolution of methane hydrates, which had been suggested as a potential further cause, is highly unlikely based on our data", explains Dr. Marcus Gutjahr from GEOMAR, co-author of the study.

As a next step, the team fed their data from the boron and additional carbon isotope-based investigations into a computer-based geochemical model that simulated the Earth's processes at that time. Results showed that warming and ocean acidification associated with the immense volcanic CO2 injection to the atmosphere was already fatal and led to the extinction of marine calcifying organisms right at the onset of the extinction. However, the CO2 release also brought further consequences; with increased global temperatures caused by the greenhouse effect, chemical weathering on land also increased.

Over thousands of years, increasing amounts of nutrients reached the oceans via rivers and coasts, which then became over-fertilized. The result was a large-scale oxygen depletion and the alteration of entire elemental cycles. "This domino-like collapse of the inter-connected life-sustaining cycles and processes ultimately led to the observed catastrophic extent of mass extinction at the Permian-Triassic boundary," summarizes Dr. Jurikova.

The study was conducted within the framework of the EU-funded ITN project BASE-LiNE Earth, in which the use of brachiopods as an environmental archive was systematically studied for the first time, and relevant analytical methods were improved and newly developed. "Without these new techniques it would be difficult to reconstruct environmental processes more than 250 million years ago in the same level of detail as we have done now", emphasizes Prof. Dr. Anton Eisenhauer from GEOMAR, the former BASE-LiNE Earth project coordinator and co-author of the new study, "in addition, the new methods can be applied for other scientific applications".