Culture

The enzyme serine palmitoyl-transferase can be used as a metabolically responsive "switch" that decreases tumor growth, according to a new study by a team of San Diego scientists, who published their findings Aug. 12 in the journal Nature.

By restricting the dietary amino acids serine and glycine, or pharmacologically targeting the serine synthesis enzyme phosphoglycerate dehydrogenase, the team induced tumor cells to produce a toxic lipid that slows cancer progression in mice. Further research is needed to determine how this approach might be translated to patients.

Over the last decade researchers have learned that removing the amino acids serine and glycine from animal diets slows the growth of some tumors. However, most research teams have focused on how these diets impact epigenetics, DNA metabolism, and antioxidant activity. In contrast, the researchers from the University of California San Diego and the Salk Institute for Biological Studies identified a dramatic impact of these interventions on tumor lipids, particularly those found on the surface of cells.

"Our work highlights the beautiful complexity of metabolism as well as the importance of understanding physiology across diverse biochemical pathways when considering such metabolic therapies," said Christian Metallo, a professor of bioengineering at the Jacobs School of Engineering at UC San Diego and the paper's corresponding author.

In this case, serine metabolism was the researchers' focus. The enzyme serine palmitoyl-transferase, or SPT, typically uses serine to make fatty molecules called sphingolipids, which are essential for cell function. But if serine levels are low, the enzyme can act "promiscuously" and use a different amino acid such as alanine, which results in the production of toxic deoxysphingolipids.

The team decided on this research direction after examining the affinity that certain enzymes have to serine and comparing them to the concentration of serine in tumors. These levels are known as Km or the Michaelis constant, and the numbers pointed to SPT and sphingolipids.

"By linking serine restriction to sphingolipid metabolism, this finding may enable clinical scientists to better identify which patients' tumors are most sensitive to serine-targeting therapies," Metallo said.

These toxic deoxysphingolipids are most potent at decreasing the growth of cells in "anchorage-independent" conditions--a situation where cells cannot easily adhere to surfaces that better mimics tumor growth in the body. Further studies are necessary to better understand the mechanisms through which deoxysphingolipids are toxic to cancer cells and what effects they have on the nervous system.

In the Nature study, the research team fed a diet low on serine and glycine to xenograft model mice. They observed that SPT turned to alanine to produce toxic deoxysphingolipids instead of normal sphingolipids. In addition, researchers used the amino-acid based antibiotic myriocin to inhibit SPT and deoxysphingolipid synthesis in mice fed low serine and glycine diets and found that tumor growth was improved.

Depriving an organism of serine for long periods of time leads to neuropathy and eye disease, Metallo pointed out. Last year, he co-lead an international team that identified reduced levels of serine and accumulation of deoxysphingolipids as a key driver of a rare macular disease called macular telangiectasia type 2, or MacTel. The work was published in the New England Journal of Medicine. However, serine restriction or drug treatments for tumor therapy would not require the prolonged treatments that induce neuropathy in animals or age-related diseases.

RIVERSIDE, Calif. -- Scientists at the University of California, Riverside, have used machine learning to identify hundreds of new potential drugs that could help treat COVID-19, the disease caused by the novel coronavirus, or SARS-CoV-2.

"There is an urgent need to identify effective drugs that treat or prevent COVID-19," said Anandasankar Ray, a professor of molecular, cell, and systems biology who led the research. "We have developed a drug discovery pipeline that identified several candidates."

The drug discovery pipeline is a type of computational strategy linked to artificial intelligence -- a computer algorithm that learns to predict activity through trial and error, improving over time.

With no clear end in sight, the COVID-19 pandemic has disrupted lives, strained health care systems, and weakened economies. Efforts to repurpose drugs, such as Remdesivir, have achieved some success. A vaccine for the SARS-CoV-2 virus could be months away, though it is not guaranteed.

"As a result, drug candidate pipelines, such as the one we developed, are extremely important to pursue as a first step toward systematic discovery of new drugs for treating COVID-19," Ray said. "Existing FDA-approved drugs that target one or more human proteins important for viral entry and replication are currently high priority for repurposing as new COVID-19 drugs. The demand is high for additional drugs or small molecules that can interfere with both entry and replication of SARS-CoV-2 in the body. Our drug discovery pipeline can help."

Joel Kowalewski, a graduate student in Ray's lab, used small numbers of previously known ligands for 65 human proteins that are known to interact with SARS-CoV-2 proteins. He generated machine learning models for each of the human proteins.

"These models are trained to identify new small molecule inhibitors and activators -- the ligands -- simply from their 3-D structures," Kowalewski said.

Kowalewski and Ray were thus able to create a database of chemicals whose structures were predicted as interactors of the 65 protein targets. They also evaluated the chemicals for safety.

"The 65 protein targets are quite diverse and are implicated in many additional diseases as well, including cancers," Kowalewski said. "Apart from drug-repurposing efforts ongoing against these targets, we were also interested in identifying novel chemicals that are currently not well studied."

Ray and Kowalewski used their machine learning models to screen more than 10 million commercially available small molecules from a database comprised of 200 million chemicals, and identified the best-in-class hits for the 65 human proteins that interact with SARS-CoV-2 proteins.

Taking it a step further, they identified compounds among the hits that are already FDA approved, such as drugs and compounds used in food. They also used the machine learning models to compute toxicity, which helped them reject potentially toxic candidates. This helped them prioritize the chemicals that were predicted to interact with SARS-CoV-2 targets. Their method allowed them to not only identify the highest scoring candidates with significant activity against a single human protein target, but also find a few chemicals that were predicted to inhibit two or more human protein targets.

"Compounds I am most excited to pursue are those predicted to be volatile, setting up the unusual possibility of inhaled therapeutics," Ray said.

"Historically, disease treatments become increasingly more complex as we develop a better understanding of the disease and how individual genetic variability contributes to the progression and severity of symptoms," Kowalewski said. "Machine learning approaches like ours can play a role in anticipating the evolving treatment landscape by providing researchers with additional possibilities for further study. While the approach crucially depends on experimental data, virtual screening may help researchers ask new questions or find new insight."

Ray and Kowalewski argue that their computational strategy for the initial screening of vast numbers of chemicals has an advantage over traditional cell-culture-dependent assays that are expensive and can take years to test.

"Our database can serve as a resource for rapidly identifying and testing novel, safe treatment strategies for COVID-19 and other diseases where the same 65 target proteins are relevant," he said. "While the COVID-19 pandemic was what motivated us, we expect our predictions from more than 10 million chemicals will accelerate drug discovery in the fight against not only COVID-19 but also a number of other diseases."

Ray is looking for funding and collaborators to move toward testing cell lines, animal models, and eventually clinical trials.

Optical-resolution photoacoustic microscopy (OR-PAM) is a powerful imaging tool with a superb ability to image rich optical absorption contrast in biological tissue. Most OR-PAM systems today rely on mechanical scanning to form an image, which restrains their imaging speed. To overcome the restraint, multifocal OR-PA computed tomography (MFOR-PACT) had been developed by utilizing a microlens array with multiple optical foci and an ultrasonic transducer array to detect PA signals in parallel. However, previous MFOR-PACT systems are complex and costly due to the use of an ultrasonic array and the associated multi-channel data acquisition system.

In a new paper published in Light: Science & Applications, a team of scientists, led by Professor Lihong Wang from Caltech Optical Imaging Laboratory (COIL), Andrew & Peggy Cherng Department of Medical Engineering and Department of Electrical Engineering, California Institute of Technology, Pasadena, USA, have developed a two-dimensional (2D) MFOR-PAM system utilizing a 2D microlens array for optical excitation and an acoustic ergodic relay to simultaneously detect the PA responses to the multifocal optical illuminations with a single-element ultrasonic transducer. This system, referred to as multifocal optical-resolution photoacoustic microscopy through an ergodic relay (MFOR-PAMER), can shorten the scanning time by at least 400 times compared to conventional OR-PAM systems at the same imaging resolution, while maintaining a simple and economic setup.

This novel MFOR-PAM system is centered around a key enabling element known as the acoustic ergodic relay (ER). For PA imaging, an ER--such as a light-transparent prism--can be used as an encoder to transform PA signals from different input positions into unique temporal signals. By recording the system impulse response of each input position in advance, the PA signals from the entire field-of-view can be detected in parallel upon a single laser shot. Then, the encoded PA signals can be decoded mathematically to reconstruct a 2D projection image of the object.

In addition, the system uses a microlens array to focus a wide-field laser beam into multiple optical focal spots. Unlike a conventional focusing lens that needs to scan a single optical focal spot across the entire FOV, the microlens array can reduce the time required to form an image by scanning multiple optical focal spots altogether.

These scientists summarize the operational principle of their system:

"Since the excitation pattern through the microlens array is known, each optical focal spot can be computationally localized. By combining the microlens array with the ergodic relay, we can improve the acoustically defined image resolution of the system to the optically defined image resolution, and improve the imaging speed by a factor equal to the number of microlens elements."

"Our MFOR-PAMER system has promising potential for many biomedical applications, such as utilizing ultra-violet (UV) illumination for high-speed, label-free histological study of biological tissues. This design can reduce the imaging time from several hours (with a conventional UV OR-PAM system) to less than a minute, significantly improving the efficiency of clinical histology and diagnostics." the scientists forecast.

The more democratic a country is, the greater the probability that its politicians decide in the same way as in neighbouring countries, without further analysis. This is according a research group that has studied political decision-making during the beginning of the Corona crisis.

Karl Wennberg and Abiel Sebhatu, professor and post-doctoral student, respectively, at the Institute for Analytical Sociology at Linköping University, together with colleagues in Uppsala and Gothenburg, have studied political decision-making in the OECD countries during the Corona crisis. Their results have now been published in the respected journal PNAS, Proceedings of the National Academy of Sciences.

The starting point for the research is that the majority of OECD countries introduced the same or similar restrictions (no large gatherings, school closures, travel restrictions, curfews and lockdowns) during a few weeks in March, although the circumstances in the countries themselves were very different.

"We found that the decisions were not based on, or had a very weak correlation to, standard epidemiological indicators such as number of cases, number of deaths, ICU capacity etc. More important has been how many neighbouring countries have already implemented measures", says Karl Wennberg.

The phenomenon whereby political measures spread without further analysis is called diffusion, and it usually appears when decisions are to be made in a highly uncertain environment.

It's true that during the pandemic, political decisions were made amidst considerable uncertainty. However the researchers conclude that timing, i.e. when measures are implemented, is important. Waiting too long leads to uncontrolled spread and overloaded healthcare, while acting too early or in the same way as others has disadvantages such as higher social and economic costs for mental ill-health and low economic activity, as well as the risk of a second wave when restrictions are eased. Also, restrictions are reliant on the population's willingness, ability and tenacity to follow them.

"One could expect that each country would conduct a detailed review of its own situation, and make decisions based on that. Considering how different the countries are, the phase of the pandemic they were in during the spring, their healthcare capacity, demographics, and how far the pandemic had advanced in each country, the homogeneity of the decision-making is striking", says Karl Wennberg.

The researchers also discuss the fact that the politicians are subject to internal pressure; they do not want to be blamed for being passive or behind the curve. They want to show decisiveness.

The research group also expresses concern about how the decision-making affects democracy. They have studied the degree of democracy in the country, in relation to the timing, i.e., when the restrictions were implemented. They conclude that the higher the level of democracy in a country, the slower the closure of schools and workplaces - all other things being equal. In democratic countries, however, it is more probable that they copy each other.

"Our analysis also shows us that legislation can limit people's freedom and rights. In May 2020, more than 100 countries had introduced variations of legislation which negatively affect democratic processes. The V-Dem Institute in Gothenburg estimates that up to 82 of the countries face considerable or medium risk of continued damage to democracy", says Karl Wennberg.

The Norwegian competitive athlete Birgit Skarstein is known in Norway for her participation in an expedition for the Lars Monsen TV series "Uten Grenser" (a remake of BBC's Beyond Boundaries). She is paralyzed from the waist down as the result of an accident. But a few years ago she walked onto the stage at the annual Sports Gala in Hamar.

An exoskeleton - an advanced robot technology - enabled this feat.

Exoskeletons are a type of outer framework, a wearable robotic device, that are used both in rehabilitation and to facilitate work tasks for people who need to do heavy lifting.

In rehabilitation, an exoskeleton can be used to help the user rebuild their body after an illness or accident, such as a spinal cord injury.

In work situations, exoskeletons are used as a supportive technology to make the job simpler or easier and to promote safer and more correct movement to prevent injuries and accidents. In other words, it's a useful, smart technology.

But as of today, this technology is primarily adapted for a western adult human being of average height and weight - and thus far from suitable for everyone.

Clear goal for the research

The average exoskeleton can accommodate a maximum height of 190 cm and a weight limit of 100 kg.

These parametres exclude many people from using this technology, whether for rehabilitation or to perform work tasks.

Norway has one of the world's tallest populations (approx. 180 cm for men, 168 cm for women). Indonesia has the shortest population in the world, with an average height of 157 cm. In countries like Bangladesh and Madagascar, women's average weight is 49 kg, while in the United States there are areas and states with many very overweight individuals. In Mississippi, for example, 40 per cent of the population is overweight.

"Technology is often developed for the average adult male, and being overweight is particularly challenging," says Roger A. Søraa. He studies robot technology and users at the Department of Interdisciplinary Studies of Culture and the Department of Neuromedicine and Movement Science at the Norwegian University of Science and Technology (NTNU).

Exoskeletons are often designed according to a one-size-fits-all principle. Søraa is focused on encouraging design that accommodates different heights and weights.

Søraa has a clear goal for robot technology research:

"We want to get exoskeleton designers to think more inclusively and develop robot technology that works for more people," he says.

"This is a glimpse into a future that we want to make inclusive. That includes adapting health technology that can contribute to a better life for the user to be more widely accessible," he said

Together with researcher Eduard Fosch-Villaronga at Leiden University in the Netherlands, Søraa recently published the article: Exoskeletons for all: The interplay between exoskeletons, inclusion, gender, and intersectionality in Paladyn, Journal of Behavioral Robotics.

Not fair to end users

Søraa and Villaronga have investigated three of the largest exoskeleton manufacturers and looked at their user criteria: the US-based Ekso Bionics and Indego, and Cyberdyne from Japan.

The researchers point out in the study that robot technology was historically regarded as part of a male sphere, and the criteria used to develop new technology reflect the biases that existed at the time. But these criteria shouldn't still be used today.

"Exoskeleton users come in many different shapes, sizes and genders. However, designers tend to resort to the one-size-fits-all principle. From an investment point of view, this may be cost effective, but it does not do justice to end users who risk being excluded from accessing the technology," the researchers said.

Making the technology accessible

To make this technology accessible to all, the researchers are proposing some tools for designers and manufacturers to help them become more inclusive. These are:

Make sure that exoskeletons can support both overweight and underweight people.

Be aware of the physical differences between men and women.

Make the exoskeleton as easy as possible to put on, even for users who lack upper body strength.

Create buttons in different patterns so that colour blind people can easily operate them without fear of pressing the wrong button.

Create buttons with different textures for the blind, and add auditory response sensors.

Involve a diverse group of employees and users at all levels in the development - think of the end user.

Think about the importance of including typically marginalized segments of society such as LGBTQ (different sexual orientations).

Remember that not everyone has grandchildren who can "teach them how to use digital technology."

Søraa has had research stays in both Japan and South Korea, and robotic technology is far more widespread there than here.

"In Japan you see robots being used more often, including at airports for carrying luggage and in the shipping industry where there's a lot of unloading and loading of goods. This type of robot technology is getting more and more common, so it's important for it to be adapted to different users," he says.

We will probably see more exoskeletons in the future, both in the health and labour sectors. But it's important that as many people as possible be able to use them, he says.

A trusting therapeutic relationship and outcome-oriented collaboration between therapist and patient are critical for the successful treatment of mental illness. And it pays to start early in therapy, a series of meta-studies by a task force of the American Psychological Association (APA) led by UZH psychology professor Christoph Flueckiger shows.

Depression, anxiety, addiction - 30 percent of the world's population experience mental illness at least once in their lifetime. Times of uncertainty and isolation such as the current coronavirus pandemic bear a particular risk. According to the World Health Organization (WHO), mental illness is one of the greatest and most stigmatized problems of modern societies. Intense efforts are under way in the healthcare sector to improve the relevant treatment options and make them as cost-efficient as possible. Psychotherapy has been shown to be a flexible and low-threshold primary treatment option.

International meta-analyses of 400 studies

The relationship between therapist and patient and how it influences treatment success has long been neglected in medicine. In recent years, however, this topic has received more and more attention. "The therapist-patient relationship is especially significant when it comes to treating mental disorders," says Christoph Flueckiger, professor of psychological interventions and psychotherapy at the University of Zurich. "The therapeutic process can trigger unpleasant emotions and require patients to consciously confront their experiences and behaviors."

Led by Flueckiger and featuring researchers from 17 countries, a task force of the American Psychological Association (APA) has now conducted a series of meta-analyses. They investigated almost 400 empirical studies with regard to how the therapeutic relationship affects treatment outcome. Their analyses show that in practically all of the included studies, it was possible to predict the outcome of the therapy from the quality of the therapeutic relationship, and that held true across all treatment approaches, outcome measurements, patient characteristics and countries.

Significance of working alliance more than mere side effect

"Treatments for mental disorders are particularly successful when the therapist and the patient work together in a trusting, outcome-oriented relationship," summarizes Flueckiger. Within this so-called working alliance, both parties agree on the tasks, approach and goals of therapy, and collaborate to reach them.

Some voices in the scientific discourse have suspected that the working alliance between therapist and patient and the accompanying treatment success were merely a side effect brought about by other factors. Some of the factors believed to play a role include previous treatment experience, symptom severity, therapeutic approach or progress made during the therapeutic process. However, the task force led by Christoph Flueckiger found no evidence whatsoever that these factors detracted from the working alliance's significance for the outcome of therapy.

Early alliance is crucial

The findings highlight the importance of the early phase of treatment for the outcome. "Early in treatment, there is a positive reciprocal link between severity of symptoms and working alliance, and this often results in a positive upward spiral," explains Flueckiger. In other words, a strong mutual relationship between a therapist and a patient helps reduce symptoms, which in turn reinforces the therapeutic relationship.

"Our studies provide evidence that it is worth investing in a respectful, trusting therapeutic collaboration, especially when it comes to treating mental illness," says Flueckiger. While this idea is also demanded in other medical fields, implementation and training is often insufficient.

The question of how small, dwarf galaxies have sustained the formation of new stars over the course of the Universe has long confounded the world's astronomers. An international research team led by Lund University in Sweden has found that dormant small galaxies can slowly accumulate gas over many billions of years. When this gas suddenly collapses under its own weight, new stars are able to arise.

There are around 2 000 billion galaxies in our Universe and, while our own Milky-Way encompasses between 200 and 400 billion stars, small dwarf galaxies contain only a thousand times less. How stars are formed in these tiny galaxies has long been shrouded in mystery.

However, in a new study published in the research journal Monthly Notices of the Royal Astronomical Society, a research team led from Lund University has established that dwarf galaxies are capable of lying dormant for several billion years before starting to form stars again.

"It is estimated that these dwarf galaxies stopped forming stars around 12 billion years ago. Our study shows that this can be a temporary hiatus", says Martin Rey, an astrophysicist at Lund University and the leader of the study.

Through high-resolution computer simulations, the researchers demonstrate that star formation in dwarf galaxies ceased as a result of the heating and ionisation from the strong light of newborn stars. Explosions of so-called white dwarfs - small faint stars made of the core that remains when normal-sized stars die -further contribute in preventing the star formation process in dwarf galaxies.

"Our simulations show that dwarf galaxies are able to accumulate fuel in the form of gas, which eventually condenses and gives birth to stars. This explains the observed star formation in existing faint dwarf galaxies that has long puzzled astronomers," states Martin Rey.

The computer simulations used by the researchers in the study are amongst the most expensive that can be carried out within physics. Each simulation takes as long as two months and requires the equivalent of 40 laptop computers operating around the clock. The work is continuing with the development of methods to better explain the processes behind star formation in our Universe's smallest galaxies.

"By deepening our understanding of this subject, we gain new insights into the modelling of astrophysical processes such as star explosions, as well as the heating and cooling of cosmic gas. In addition, further work is underway to predict how many such star-forming dwarfs exist in our Universe, and could be discovered by astronomical telescopes" concludes Martin Rey.

Billions of tonnes of carbon dioxide risk being lost into the atmosphere due to tropical forest soils being significantly more sensitive to climate change than previously thought.

Carbon emissions from soils in tropical forests - which store one quarter of the world's soil carbon - could increase dramatically if temperatures continue to rise in line with current predictions, researchers say.

A new experiment conducted in Panama suggests these harmful emissions of soil carbon could rise by 55 per cent if the climate warms by four degrees Celsius.

Carbon dioxide is released naturally by soils through decomposition and plant root activity. However, the release of so much extra carbon dioxide - which the study found was coming from increased decomposition of soil organic matter - could trigger further global warming.

Previous research has shown that rising temperatures threaten to release carbon locked away in cooler or frozen soils - such as in the Arctic tundra. Until now, tropical soils were thought to be less sensitive to the effects of climate warming.

A team led by researchers from the University of Edinburgh conducted a large-scale experiment in a tropical forest on Barro Colorado Island in the Panama Canal.

They built heating devices and buried them one metre into the forest soil. Over a two-year period the equipment - fitted with heating cables and a thermostat - kept the experimental areas four degrees warmer than the surrounding soil.

The findings show that as much as an extra eight tonnes of soil carbon could be released as carbon dioxide from every hectare of tropical forest each year at the higher temperatures.

Researchers expect the rate of emissions will eventually decline in the experimentally warmed soils, but they do not yet know how long this will take, or the long-term impact of soil warming on climate change.

They will continue the experiment - known as the Soil Warming Experiment in Lowland Tropical Rainforest, or SWELTR - to better understand how tropical forests respond to a warming world.

Eating while doing something perceptually-demanding makes it more difficult to notice when you feel full, shows new research from the University of Sussex.

Professor Martin Yeomans, Dr Sophie Forster and colleagues found that when your senses are taken up by an engaging task, you are less likely to be able to adjust how much extra food or drink you consume. The team tested 120 participants, giving them lower and higher calorie drinks and giving them tasks which demanded both low and high amounts of their attention. The paper "Ingested but not perceived: response to satiety cues disrupted by perceptual load" is published today 12 August 2020 in the journal Appetite.

The team found that participants who were fully engaged in a perceptually-demanding task ate roughly the same amount of follow-up crisps regardless of whether or not they were initially given a high or low calorie drink. But the people who were engaged in a task which demanded less of them could adjust how much of the additional snack they ate. The people in this group ate 45% fewer crisps after the higher energy drink than after the lower energy drink.

Previous research has shown that when perceptual demand is high - so that's where the senses are engaged fully - then the brain filters out some of the sensory information. This is the first time that research has shown that sensory and nutrient cues associated with becoming full (satiety) could be filtered out in a similar way.

Professor Martin Yeomans from the School of Psychology at the University of Sussex, said:

"Our study suggests that if you're eating or drinking while your attention is distracted by a highly engaging task, you're less likely to be able to tell how full you feel. You're more likely to keep snacking than if you'd been eating while doing something less engaging. This is important for anyone wanting to stay a healthy weight: if you're a habitual TV-watching snacker - watching, say, an engaging thriller or mystery, or a film with a lot of audio or visual effects - you're not likely to notice when you feel full. Video-gamers and crossword solvers should also take note!

"We already knew that feeling full could be affected by the texture and appearance of food, as well as pre-existing expectations about how full we think a type of food should make us feel. Now we also know that feeling full depends on how much sensory information our brains are processing at the time."

About the research

One-hundred and twenty participants consumed either a low-satiety (75kcal) or high-satiety (272kcal and thicker texture) drink while simultaneously completing a task which was either low or high in perceptual demand. The participants who were given the low perceptual load task, and were given the high-satiety drink felt more full and ate 45% less of the snack offered to them afterwards. However, the participants who were given the higher load perception task were less able to tell when they felt full, and ate more of the snacks offered to them. The researchers conclude that a person's ability to notice when the body feels full depends on how much available attention there is 'left' in the brain.

The results provide the first evidence that Load Theory of attention (the idea that a person has a limited amount of sensory information they can notice) can be successfully applied to eating habits.

Nutritional information displayed prominently on food products which give consumers information on salt, sugar and calorie content play a significant role in nudging people towards better dietary choices, according to new research.

The study, from health economists at the universities of Bath and Bristol published in the Journal of Health Economics, is the first to evaluate the impact of Front-of-Pack nutritional labelling on retailers’ store-branded products, which was first introduced back in 2006.

Their results find a reduction in the quantity of labelled store-branded food purchased (for example ready meals, pizzas, burgers, etc.) and an overall improvement in the nutritional composition of consumers’ shopping baskets where labelling was displayed. Significantly, these improvements in food shopping habits were most prominently observed across poorer households.

In 2006, the UK Food Standards Agency (FSA) recommended retailers to introduce Front-of-Pack (FOP) labelling on their store-brand products on seven types of foods (ready meals, burgers/sausages, pies, breaded/coated meats, pizzas, sandwiches and cereal). The recommendation was taken up by several UK retailers (Waitrose, Co-Op, Marks & Spencer, and Asda) who each introduced it at different times between March 2006 and September 2007.

Retailers introduced two types of nutritional labelling. Some introduced a Traffic Light System, a colour-coded scheme denoting the amount of nutrients by the colours red (high), amber (medium) and green (low), whilst some others introduced a hybrid system incorporating both a traffic light system and Guideline Daily Amounts (GDAs), where both colours and the contribution that each of these nutrients make towards the adult GDA were displayed.

By drawing on differences observed in the food choices of consumers who shopped in stores where labelling was displayed, to changes for consumers shopping elsewhere, the results from the new study show that on average, as a result of labelling, households improved the quality of their diet by reducing the total monthly calories from labelled store-brand foods by 588 Kcal, saturated fats by 14g, sugars by 7g, and sodium by 0.8mg. Hybrid labelling was found to be most effective at shifting choices.

The research comes as the UK government sets out its new obesity strategy in response to covid-19, unveiling as part of it a number of measures including menu calorie labelling to help people make healthier choices when eating out. The team behind the study say these new results can help inform future policies in this area.

Lead researcher, Dr Eleonora Fichera from the Department of Economics at the University of Bath explains: “Our results suggest that nutritional labelling on food products can play an important role in starting to shift behaviours towards more healthier food choices whether that be during the weekly shop in a supermarket, or potentially through new healthier menu choice options. Labelling has a dual effect in better informing consumers about the nutritional value of the products they put in their shopping basket, but it may also incentivise manufactures towards better quality food products.

“This of course is not a panacea to solve the obesity problem, which is multi-faceted and needs to be tackled with a much more systemic approach. But these results provide policymakers with further evidence that such measures can make an important contribution.”

A new study shows that in addition to blood, endurance exercise induces changes in sweat biomolecule levels. These findings lay the groundwork for the development of future noninvasive exercise monitoring systems that utilize sweat as a biomarker source.

Sweating is an important part of thermoregulation during exercise, yet the potential for sweat as a biomarker source has not been established. Currently, the key limiting steps of using sweat as a biomarker source for exercise monitoring are the low abundance of biomarkers and variation in the volume of sweat in different environments and in different persons.

"Previously, sweat has been utilized in the diagnostics of certain diseases, such as cystic fibrosis. In addition, several drugs are secreted into sweat, enabling detection of the drug from sweat instead of blood," explains postdoctoral researcher Sira Karvinen from the Gerontology Research Center and Faculty of Sport and Health Sciences, University of Jyväskylä, Finland.

New finding: Extracellular vesicles in sweat contain microRNAs

Evaporation of sweat from the skin surface lowers body temperature preventing overheating of the body in hot environments as well as during strenuous exercise. Although sweat is a natural by-product of exercise and has been studied for several decades, a role for it as a biomarker source in the field of exercise has not been established.

It has previously been observed that similarly as blood and other body fluids, sweat contains extracellular vesicles. Extracellular vesicles are composed of a lipid bilayer and a core containing transported signal molecules, which cells release to facilitate communication between cells and tissues. A novel finding of the current study was that sweat extracellular vesicles contain microRNA molecules. MicroRNAs regulate several biological processes and have been identi?ed as essential mediators in exercise adaptations. Previously, endurance exercise has shown to change the level of several microRNAs in blood.

"In our study we examined how elevation in body temperature induced by sauna and endurance exercise protocols affect the abundance of microRNAs in sweat and serum extracellular vesicles. Endurance exercise protocols were carried out with a bicycle ergometer," says Urho Kujala, Professor of sports and exercise medicine, from the Faculty of Sport and Health Sciences, University of Jyväskylä, Finland. "Our aim was to reveal the potential of microRNAs in sweat extracellular vesicles in monitoring exercise performance."

In the present study sweat samples were harvested from the study subjects during sauna bathing and during three different endurance exercise tests: a maximal aerobic capacity test and high and low intensity endurance exercise tests. Sweat was collected during the entire duration of each test from both arms and blood samples were taken before and after each test.

Sweat may be used as a biomarker source for exercise monitoring in the future

The present study showed that the abundance of certain microRNAs changed in response to exercise of different intensity in sweat extracellular vesicles. In particular, the high-intensity endurance exercise test induced an increase in the studied microRNAs in serum and sweat.

"Our study is the first to show that sweat possesses unique miR carrier content that is different from that observed in blood," Karvinen explains. "This may partly explain the observation that sweat and serum microRNA levels are not similar."

Based on the results of the present study, sweat has a potential to serve as a biomarker source for future exercise monitoring systems. However, sweat possesses a unique miR carrier content that should be taken into account when planning analyses from sweat as a substitute for serum. There are currently no commercially available sweat-based monitoring systems, as first there is a need to invent new technologies to robustly detect very small amounts of biomarkers.

Did the man bite the dog, or was it the other way around? When processing an utterance, words need to be assembled into the correct interpretation within working memory. One aspect of comprehension is to establish 'who did what to whom'. This process of unification takes much longer than basic events in neurobiology, like neuronal spikes or synaptic signaling. Hartmut Fitz, lead investigator at the Neurocomputational Models of Language group at the Max Planck Institute for Psycholinguistics, and his colleagues propose an account where adaptive features of single neurons supply memory that is sufficiently long-lived to bridge this temporal gap and support language processing.

Model comparisons

Together with researchers Marvin Uhlmann, Dick van den Broek, Peter Hagoort, Karl Magnus Petersson (all Max Planck Institute for Psycholinguistics) and Renato Duarte (Jülich Research Centre, Germany), Fitz studied working memory in spiking networks through an innovative combination of experimental language research with methods from computational neuroscience.

In a sentence comprehension task, circuits of biological neurons and synapses were exposed to sequential language input which they had to map onto semantic relations that characterize the meaning of an utterance. For example, 'the cat chases a dog' means something different than 'the cat is chased by a dog' even though both sentences contain similar words. The various cues to meaning need to be integrated within working memory to derive the correct message. The researchers varied the neurobiological features in computationally simulated networks and compared the performance of different versions of the model. This allowed them to pinpoint which of these features implemented the memory capacity required for sentence comprehension.

Towards a computational neurobiology of language

They found that working memory for language processing can be provided by the down-regulation of neuronal excitability in response to external input. "This suggests that working memory could reside within single neurons, which contrasts with other theories where memory is either due to short-term synaptic changes or arises from network connectivity and excitatory feedback", says Fitz.

Their model shows that this neuronal memory is context-dependent, and sensitive to serial order which makes it ideally suitable for language. Additionally, the model was able to establish binding relations between words and semantic roles with high accuracy.

"It is crucial to try and build language models that are directly grounded in basic neurobiological principles," declares Fitz. "This work shows that we can meaningfully study language at the neurobiological level of explanation, using a causal modelling approach that may eventually allow us to develop a computational neurobiology of language."

CHAMPAIGN, Ill. -- Cratering job quality and weak wage growth in the U.S. have typically been attributed to a combination of technological change, waning worker bargaining power and increased pressures from trade and financial markets. But according to research co-written by a University of Illinois, Urbana-Champaign expert who studies economic sociology, increased industry concentration also has dire consequences for workers' wages and job quality.

Dominant firms in concentrated industries can effectively constrain downstream economic opportunities for buyers and suppliers because their transaction partners lack alternatives, thereby making profits for workers to bargain over all the more scarce, said Richard Benton, a professor of labor and employment relations at Illinois.

"When we think about wage stagnation, wage inequality and job quality in the U.S., we don't often think about the role firms play in the marketplace - both on the input side and on the output side," he said. "When you have a supply chain that's dominated by a very powerful firm, or you have entire industries or markets that are dominated by very powerful firms, that makes it more difficult for smaller firms that do business with them to be successful and turn a profit. And that, in turn, shrinks the economic surplus available for workers."

Benton and co-author Ki-Jung Kim, a U. of I. graduate student, calculated market-constraint measures for recent years - 1997, 2002, 2007 and 2012 - in the U.S. using data on interindustry transactions and linking them with data from the Current Population Survey on individuals' wages and employment benefits.

Market constraint captures the extent to which firms in an industry are heavily dependent on powerful suppliers and buyers in upstream or downstream industries, according to the paper.

"With this approach, we were able to identify the market-constraint effect using individuals' movement between more- and less-constrained industries," Benton said.

The analysis reveals that workers in more buyer-constrained industries - that is, industries at the mercy of the financial decisions of powerful buyers - experience lower wages and benefits. The paper also shows that market constraints reduce the economic surplus available for union bargaining, suggesting that industry concentration curbs wages and harms overall job quality, the researchers say.

"When you're in a market that's not dominated by a singular powerbroker, it's a lot easier for firms to generate profits," Benton said. "But over the last 20 years, we've seen dramatic growth in corporate profits, and part of the reason why is because when you're the singular behemoth in the market, you're in a position to dominate your supply chain. That's one of the reasons why big-box retail stores, for example, turn such a huge profit. It's not just because they control the retail industry. It's because they can exercise that power over their suppliers and effectively dictate their terms to ensure that their prices are as low as they can get it.

"That's great for consumers, but if you couple that with decreased unionization, you have a recipe for declining job quality and wage erosion for people who work at those supplier firms."

Since the 1960s, federal antitrust regulation and enforcement have overwhelmingly focused on protecting consumers against monopolistic practices from suppliers. However, courts have been more forgiving of "monopsonistic conduct" - when buyers engage in anticompetitive behavior and accumulate market power that disadvantages tangential businesses, Benton said.

"Federal antitrust regulation and enforcement have proved particularly ineffective at addressing dependency structures in economic value chains. As a result, concentrated power, particularly buyer power, has generally gone uncontested in the current regulatory framework," he said. "More broadly, our results strongly suggest that policymakers should consider labor market and inequality consequences of antitrust legislation and enforcement, not just the benefits to consumers."

The findings have important implications for policymakers, pointing to labor unions as "instrumental" to ensuring that profits are shared with workers, Kim said.

"When workers are in an industry that's dominated by very powerful buyers on the output side of the market, it reduces wages and employment benefits such as pensions and health care that would otherwise go to workers," he said. "They're more likely to be captured as profits that are returned to owners or shareholders than they are to workers."

"We need strong unions to make sure that workers are able to bargain for a slice of the pie - and also, perhaps, by focusing on antitrust efforts and competitive supply chains, to grow the pie itself," Benton said. "It's imperative that policymakers strengthen unions and pay attention to this other dimension of antitrust practices."

BEER-SHEVA, Israel...August 12, 2020 - A tuberculosis vaccine administered during the past 15 years is associated with significantly improved COVID-19 outcomes, according to a new study published in Vaccines.

Dr. Nadav Rappoport of the Ben-Gurion University of the Negev (BGU) Department of Software and Information Systems Engineering collaborated with colleagues Danille Klinger, Ido Blass and Prof. Michal Linial from The Hebrew University of Jerusalem to analyze the correlation between the Bacille Calmette-Guérin (BCG) vaccine for tuberculosis and COVID-19 outcomes.

The researchers discovered that BCG regimes are associated with better COVID-19 outcomes, both in reducing infection rates and death rates per million, especially for ages 24 or younger who had received the vaccination in the last 15 years. There was no effect among older adults who had received the BCG vaccine. Many countries have stopped inoculating their entire population, but some still use BCG widely.

"Our findings suggest exploring BCG vaccine protocols in the context of the current pandemic could be worthwhile," says Rappoport. "A growing number of clinical trials for testing the efficacy of BCG vaccination have been initiated."

Dr. Rappoport and his colleagues analyzed data from 55 countries with populations of more than 3 million people, which comprise some 63% of the world's population. As the pandemic reached different countries at different dates, they aligned countries by the first date at which the country reached a death rate of 0.5 deaths per million or higher. They controlled for 23 variables including demographic, economic, pandemic-restriction-related, and country health-based. BCG vaccine administration was shown to be constantly associated with COVID-19 outcomes across the 55 countries.

To ascertain whether other vaccines also influenced COVID-19 outcomes, they conducted the same analysis for the measles and rubella vaccines and found that those did not have a significant association with COVID-19 outcomes.

Other epidemiological studies have shown the effect of the BCG vaccine beyond tuberculosis, but scientists do not yet know why the vaccine has such an effect.

Although it has become increasingly accepted for medical and recreational use, cannabis is still considered among one of the most widely used illegal substances in the United States and in many European countries. A common assumption is that cannabis consumption before or during work hours causes substandard work performance, yet there has been very little scientific exploration regarding the impact of cannabis use after working hours.

Dr. Jeremy Bernerth, management professor at San Diego State University's Fowler College of Business and H. Jack Walker, management professor at Auburn University's Raymond J. Harbert College of Business set out to determine the effects of different types of cannabis use (before, during and after hours) on work performance, especially as it relates to core job requirements, helping colleagues or their organizations, and counterproductive behavior in the workplace. Their research titled "Altered States or Much to Do About Nothing? A Study of When Cannabis Is Used in Relation to the Impact It Has on Performance" was recently published in Group & Organization Management.

"Given the popularity of cannabis on a national level, it should be of little surprise that organizations spend billions of dollars each year addressing what many believe is a problem," explained Bernerth. "To our knowledge, this is the first study to research cannabis usage in relation to workplace behaviors in nearly 20 years. We hope this research can provide organizations with the necessary information to structure their substance policies."

Surveying Employees and Their Supervisors

The researchers studied key job requirements (called "task performance" in the study), the willingness to voluntarily help the organization or their colleagues (called "citizenship behavior"), and the counterproductive work behavior of employees by surveying 281 employees and their direct supervisors. Participating employees and managers were recruited through social media and with the help of university business students, though cannabis usage was not required of the survey participants.

Each employee was asked about the frequency and the timing of their cannabis use as it relates to their work shift (for example, how often over the past 12 months had they used cannabis within two hours before starting the workday). Their supervisors were asked to assess their employee's task performance, citizenship behavior and counterproductive work behavior.

The Results

After tabulating all the responses, the researchers found a negative correlation between those who used cannabis before and during work with task performance. This indicates a decline in performance when using cannabis prior to or while on the job. There was, however, no relationship between using cannabis after work and one's performance on the job.

They also found supervisors were more likely to report reduced citizenship behavior (or helpfulness) toward the organization and increased counterproductive work behaviors among employees who said that they used cannabis before and during work hours. However, the results showed no discernable effects for employees who used cannabis after work. The researchers also noted that there was no correlation between employee's willingness to engage in citizenship behavior aimed at their coworkers with cannabis usage regardless of the time of usage.

While the results of the study showed that supervisors reported that employee cannabis use before or on the job diminished most areas of their performance, there was no significant change in any of the work performance dimensions when employees used cannabis after work hours.

"The findings are obviously consequential for scholars and organizations who believe that all cannabis use negatively impacts workplace behaviors," said Bernerth. "Our research suggests there is no evidence that after-work usage compromises work performance as assessed by one's direct supervisor."

Cannabis Use May Offer Work-Related Benefits

Though the research doesn't offer direct evidence, Bernerth suggests that after-hours cannabis use, may offer some work-related benefits. "Individuals deciding to consume cannabis after finishing their work may be able to distract themselves from stressful on-the-job issues," said Bernerth. "The relaxation induced by cannabis may help employees restore energy spent during the day and they may subsequently return with more stamina to devote to their job once they are back on the clock."

However, one of the major challenges facing employers with substance policies is determining when employees consume cannabis. Bernerth noted that testing for cannabis consumption (through urinalysis, for example) can only detect the presence of metabolites in the system as opposed to the frequency or time of use. This may make it difficult for organizations to defend strict substance policies. Said Bererth: "Since our study shows that off-the-job cannabis use has little to no impact on workplace performance, organizations will be hard-pressed to provide legally defensible justifications for the continuation of policies prohibiting all forms of cannabis use."