Culture

Experiencing a variety of positive emotions--or emodiversity--may benefit high school students, according to a study published in the British Journal of Educational Psychology.

Positive emodiversity was associated with greater engagement (which has cognitive, behavioral, and emotional components) and academic achievement.

The diversity of negative emotions, such as experiencing anxiety and frustration, did not seem to provide any motivational benefits.

"Students with greater positive emodiversity have a more diverse emotional life, which perhaps helps them respond and adapt specifically to various school situations," said corresponding author Cherry Eron Frondozo, of The Education University of Hong Kong.

Integrated Assessment Models (IAMs) connect trends in future socio-economic and technological development with impacts on the environment, such as global climate change. Critics have taken issue with the transparency of IAM methods and assumptions as well as the transparency of assessments of IAMs by the Intergovernmental Panel on Climate Change (IPCC), the United Nations body for assessing the science related to climate change.

An article published in WIREs Climate Change that's co-authored by officials at the IPCC documents various activities underway to enhance the transparency of IAMs and their assessments.

"The purpose of this paper is to document how both the IAM community and IPCC are working to enhance transparency and to suggest some criteria for judging the success of these efforts," the authors wrote. "Transparency does not in itself guarantee scientific closure, but it facilitates debate and provides a clearer evidence base for policymakers."

Using single cell technology, a new study sheds light on the significance of genetic risk factors for, and the diversity of cells involved in, the development of coronary artery disease. The researchers analysed human atherosclerotic lesions to map the chromatin accessibility of more than 7,000 cells. The chromatin accessibility is known to reflect active regions and genes in the genome. The findings were published in Circulation Research.

Genome-wide association studies of the human genome have identified over 200 loci associated with coronary artery disease. More than 90% of them are located outside protein-coding genes, in so called cis-regulatory elements, whose significance in the pathogenesis of coronary artery disease remains unclear.

Previous research has demonstrated that the development of coronary artery disease involves a variety of different cells and their subtypes. The now-published study is the first to use single cell technology to map epigenetic changes in these cells. The researchers used the ATAC-seq sequencing method to discover the nuclear chromatin structure of endothelial cells and smooth muscle cells, as well as immune system monocytes, macrophages, NK/T and B cells, providing a unique resource to study the cell-type specific activity of the cis-regulatory elements in the disease affected vessel wall.

The study demonstrated that genetic risk variants associated with coronary artery disease are particularly enriched in cis-regulatory elements specific to endothelial and smooth muscle cells, indicating that these cells play a significant role in transmitting susceptibility to the disease. Based on chromatin accessibility mapping and gene expression data, the researchers were able to identify putative target genes for approximately 30% of all known loci associated with coronary artery disease. In addition, the researchers performed genome-wide experimental fine-mapping of the variants, allowing them to identify potential causal single-nucleotide polymorphisms and the associated target gene for over 30 loci that have been linked to coronary artery disease. The study also presented a number of examples of how the chromatin accessibility and gene expression data can be used to predict target cells via which the function of the genetic changes associated with the disease is transmitted in the tissue. This is a significant step forward that helps to understand the real functional significance of risk variants in the pathophysiology of coronary artery disease. In the future, this information can be used to develop more effective, safer and more individualised treatments for coronary artery disease.

If you've watched Netflix, shopped online, or run your robot vacuum cleaner, you've interacted with artificial intelligence, AI. AI is what allows computers to comb through an enormous amount of data to detect patterns or solve problems. The European Union says AI is set to be a "defining future technology."

And yet, as much as AI is already interwoven into our everyday lives, there's one area of the globe where AI and its applications are in their infancy, says Ekaterina Kim, an associate professor at the Norwegian University of Science and Technology's (NTNU) Department of Marine Technology. That area is the Arctic, an area where she has specialized in studying sea ice, among other topics.

"It's used a lot in marketing, in medicine, but not so much in Arctic (research) communities," she said. "Although they have a lot of data, there is not enough AI attention in the field. There's a lot of data out there, waiting for people to do something with them."

So Kim and her colleagues Ole-Magnus Pedersen, a PhD candidate from the Department of Marine Technology and Nabil Panchi, from the Indian Institute of Technology Kharagpur, decided to see if they could develop an app that used artificial intelligence to identify sea ice in the Arctic.

You may think there's not much difference between one chunk of sea ice and another, but that's just not so.

In addition to icebergs, there's deformed ice, level ice, broken ice, ice floes, floe bergs, floe bits, pancake ice and brash ice.

The researchers wanted the app to be able to distinguish between the different kinds of ice and other white and blue objects out there, like sky, open water and underwater ice.

Different kinds of ice really matter to ship captains, for example, who might be navigating in icy waters.  Actual icebergs are nothing like brash ice, the floating bits of ice that are 2 metres in diameter or less. Think of it --the Titanic wouldn't have sunk if it had just blundered into a patch of brash ice instead of a big iceberg.

Another factor that adds urgency to the situation is climate change, which is dramatically altering sea ice as oceans warm. Even with the help of satellite images and onboard ship technologies, knowing what's in icy waters ahead can be a difficult challenge, especially in fogs or storms.

"Ice can be very difficult for navigation," Kim said. "From the water (at the ship level) It can be hard to detect where there is strong ice, multiyear ice, and different ice.  Some ice is much more dangerous than other types.

The team began teaching their app's AI system using a comprehensive collection of photographs taken by another NTNU ice researcher, Sveinung Løset.

But an AI system is like a growing child -- if it is to learn, it needs to be exposed to lots of information. That's where turning the AI into an app made sense. Although the COVID-19 pandemic has shut down most cruise operations, as the pandemic wains, people will begin to take cruises again -- including to the Arctic and Antarctic.

Kim envisions tourists using the app to take pictures of different kinds of ice to see who finds the most different kinds of ice. And every one of those pictures helps the app learn.

"If the app is used for 'infotainment,'  accuracy isn't that important," Kim said.  "It can even be fun when the model makes mistakes."

As the AI learns, Kim says, the increasingly complex dataset could be taken into the classroom, where navigators could learn about ice in a much more sophisticated way.

Currently, students just look at pictures or listen to a PowerPoint presentation, where lecturers describe the different kinds of ice.

"So this could revolutionize how you learn about ice," she said. "You could have it in 3-D, you could emerge yourself and explore this digital image all around you, with links to different kinds of ice types."

The researchers are planning an AI in the Arctic workshop in September to explore AI applications in these remote areas.

"There are extreme challenges unique to the Arctic, from human activities and impacts in remote Arctic locations to Arctic data acquisition, sharing, and quality," Kim said. "We need to direct AI applications towards solving Arctic challenges that are important for the world as well as to highlight the 'black holes' or knowledge gaps and raise awareness on what does not work, needs improvements."

Researchers from University of Mannheim published a new paper in the Journal of Marketing that examines the effect of wage inequality on customer satisfaction and firm performance.

The study, forthcoming in the Journal of Marketing, is titled "Wage Inequality: Its Impact on Customer Satisfaction and Firm Performance" and is authored by Boas Bamberger, Christian Homburg, and Dominik M. Wielgos.

Irrespective of wage cuts and employee layoffs, the wages of top managers rose to record levels during the pandemic and wage inequality continues to grow worldwide. However, according to a 2015 OECD report, "wage inequality is harmful to long-term economic growth and undermines societal cohesion." This situation raises the question: Do firms have an incentive to raise wage inequality?

This new study addresses this question by examining the impact of wage inequality on customer satisfaction and firm performance. The researchers surveyed more than 100 top sales and marketing managers in public firms selling to businesses in three countries. They analyzed the responses and company financial data to understand how wage inequality impacts customer satisfaction and firm performance.

Results show that unequal wages between top managers and employees can boost the short-term profitability of a firm. As Bamberger explains, "In the long run, however, this benefit fades. What persists is that wage inequality motivates employees to opportunistically exploit customers and weakens a firm's customer-oriented culture, thereby harming customer satisfaction.

How does this happen? Suppose a firm has high wage inequality. Thus, the ultimate prize in a tournament setting, to gradually rise to top management, is a strong incentive for employees at all levels. But in the process, they may engage in opportunistic behaviors and also collaborate less with coworkers.

For example, to enhance her chances for promotion, an employee might show more effort by interacting with customers more frequently to better understand and fulfill their needs to boost sales. By contrast, she could also distort facts about products to close deals more quickly.

Non-customer-facing employees could also be affected. Take, for instance, an R&D employee. He could interact with customers more often to learn and adapt innovations to their needs to increase sales. Conversely, he could also design products to fail to force customers to buy a product over and over again.

"Through customer-directed effort or opportunism, employees may improve their chances of getting promoted to the next higher level. Our results show that wage inequality does raise customer-directed effort and opportunism," says Homburg.

At the same time, wage inequality might also weaken collaboration among coworkers. An employee who worries about advancing to the next higher level is less concerned about their coworkers. But less collaboration impairs the flows of information and knowledge about customers throughout the firm. This, in turn, can lead to worse coordination between departments. Ultimately, the firm becomes less responsive to the changing needs of customers. Thus, wage inequality weakens the customer-oriented culture of a firm.

The adverse impact wage inequality has on opportunism and customer-oriented culture extends to customer satisfaction and reduces the short-term profitability of a firm. At the same time, wage inequality also raises a firm's short-run profits through a direct path. Despite the harm through the customer path, the total impact of wage inequality on short-term profitability is slightly positive.

This slightly positive effect on short-term profitability holds in a different sample with more than 500 observations of U.S. firms selling to consumers. Wielgos explains that "When we analyzed how wage inequality plays out in the long run, the situation reverses. The harm that wage inequality causes to customer satisfaction leads to long-term performance decline. In sum, a firm sees no profitability lift from wage inequality in the long run."

Do firms have an incentive to raise wage inequality? In terms of bottom-line impact, the answer is: "Yes" in the short run and "No" in the long run. However, when looking at the customer impact, the answer is "No" because of the negative impact of wage inequality on customer satisfaction, which weakens firm profits.

What can managers learn? If the goal is short-term profitability, go with higher wage inequality, but keep an eye on customer satisfaction. If managers are interested in the long-term success of the firm, consider reducing wage inequality to help employees orient toward customers.

What can shareholders learn? Suppose that you care about the long-term profitability of your investment. In that case, make sure to reward top managers for achieving sustainable profitability and good customer relationships.

What can policymakers learn? Wage inequality is not in a firm's long-term interest. This argument can help to create a consensus with managers to restrain wage inequality. However, short-term-oriented managers might care little about the damage wage inequality does to society. It thus might be necessary to disincentivize them from raising wage inequality.

PULLMAN, Wash. - Even before the pandemic made Zoom ubiquitous, Washington State University researchers were using the video conferencing app to research a type of cannabis that is understudied: the kind people actually use.

For the study, published in Scientific Reports, researchers observed cannabis users over Zoom as they smoked high-potency cannabis flower or vaped concentrates they purchased themselves from cannabis dispensaries in Washington state, where recreational cannabis use is legal. They then gave the subjects a series of cognitive tests.

The researchers found no impact on the users' performance on decision-making tests in comparison to a sober control group but did find some memory impairments related to free recall, source memory and false memories.

While the findings are in line with previous research on low-potency cannabis, this study is one of the few to investigate cannabis that contains much more than 10% tetrahydrocannabinol (THC), the plant's main psychoactive ingredient. This is only the second known study to examine the effect of cannabis concentrates.

"Because of federal restrictions to researchers, it was just not possible to study the acute effects of these high-potency products," said Carrie Cuttler, WSU psychologist and lead researcher on the study. "The general population in states where cannabis is legal has very easy access to a wide array of high- potency cannabis products, including extremely high-potency cannabis concentrates which can exceed 90% THC, and we've been limited to studying the whole plant with under 10% THC."

While 19 states and Washington D.C. have legalized cannabis for recreational use, the U.S. federal government still classifies it as a Schedule 1 drug, implying it has a high potential for abuse and no medicinal benefits. Until recently, researchers interested in studying cannabis were limited to using low-potency plants of around 6% THC supplied by the National Institute of Drug Abuse. In June, the U.S. Drug Enforcement Administration indicated it may allow some companies to start growing cannabis for research purposes.

For this study, which began in 2018, Cuttler and her colleagues found a way to study the effects of high-potency cannabis while still complying with federal guidelines. The study participants bought their own products and used them in their own homes. They were never in a laboratory on federal property, and the researchers never handled the cannabis themselves. Participants were not reimbursed for their purchase. Instead they were compensated for their time with Amazon gift cards. All participants were over 21 and experienced cannabis users who reported no past negative reactions to cannabis like panic attacks. The study's method was cleared by WSU Division of the Office of the Attorney General and the university's research ethics board.

The 80 participants were divided into four groups: two groups used cannabis flower with more than 20% THC but one containing cannabidiol (CBD), a non-psychoactive component of cannabis, and the other without CBD. Another group vaped cannabis concentrates with more than 60% THC that included CBD. A fourth group remained sober.

For all cannabis using groups, the researchers found no effect on a range of decision-making tests including risk perception and confidence in knowledge. On a few memory tests there were also no significant differences between the cannabis-using and sober groups, including prospective memory, the ability to remember to do things at a later time, such as attend an appointment. The cannabis-using participants also did well on temporal order memory, the ability to remember the sequence of previous events.

However, the groups that smoked cannabis flower with CBD did worse on verbal free recall trials- they were unable to recall as many words or pictures that were shown to them compared to the sober group. This finding was contrary to a small number of previous studies indicating CBD might have a protective effect on memory. The groups that used cannabis without CBD and the group that used concentrates, performed worse on a measure of source memory which means being able to distinguish the way previously learned information was presented.

Finally, all three cannabis-using groups did poorly on a false memory test - when given a new word and asked if it had been presented before, they were more likely to say it had when it had not.

There was also an unexpected finding: people who vaped the high-potency concentrates with more than 60% THC performed comparably to those who smoked cannabis flower. This may have been because they tended to self-titrate - using less of the drug to achieve a similar level of intoxication and impairment as the people who smoked the less-potent cannabis flower.

Cuttler said this was cause for cautious optimism on the little-studied but widely available concentrates.

"There's been a lot of speculation that these really high-potency cannabis concentrates might magnify detrimental consequences, but there's been almost zero research on cannabis concentrates which are freely available for people to use," said Cuttler. "I want to see way more research before we come to any general conclusion, but it is encouraging to see that the concentrates didn't increase harms."

Mandatory covid-19 vaccination for care home workers is unnecessary, disproportionate and misguided, warn experts

And is based on unreliable data

In The BMJ today, experts argue that mandatory vaccination is "unnecessary, disproportionate, and misguided."

The government decision to remove the right of care home staff in England to choose whether or not to be vaccinated against covid-19 is a profound departure from public health norms. The intended next step is a rapid and massive expansion of compulsory vaccination to legally require covid-19 and flu vaccination of all frontline health and social care workers, subject to consultation.

But Lydia Hayes, Professor of Law at Kent University and Allyson Pollock, Professor of public health at Newcastle University, say vaccination "is not a panacea for safety" and "will not remedy the serious shortcomings of the care sector in England."

They note government consultation documents and subsequent media reports have claimed that mandatory vaccination is necessary because of low vaccination take up rates in some care homes.

But figures show that by 20 June 2021, over 90% of care home residents in England had received two doses of a covid-19 vaccine, 84% of care workers in England had received a first dose, and 72% of care workers had received a second dose - in line with Scientific Advisory Group recommendations.

Their closer scrutiny of the data shows that uptake of the first dose of covid-19 vaccination among care workers is below 80% (68-74%) in only three English local authorities but these numbers are an artefact of very low numbers of staff employed by care homes in these London areas.

Moreover, they highlight that the government's own methodology note warns that reliable information on vaccination uptake cannot be directly derived from the data the government is using.

According to regulatory law, safety in care homes "is achieved through adequate staffing levels, training, equipment, cleanliness, personal protective equipment, risk assessment, and consultation with staff and residents," they write.

Vaccination protects individuals from covid-19 and reduces the risk of transmission of disease to others, but neither duration of protection nor efficacy against new variants are known.

Wales and Scotland have rejected compulsory vaccination for care workers and invested in systems of mandatory registration for care workers designed to professionalise the sector, increase access to training, and embed a culture of continuous professional development, they add.

But in England, successive ministers have rejected national care worker registration. "Hence, the Department of Health and Social Care and the CQC don't know who England's care workers are and training of the care workforce is woefully inadequate."

"Civil liberty is a necessary component of strong public health. Mandatory vaccination is unnecessary, disproportionate and misguided, they warn. "Safety can be assured only by taking steps to build trust and to mitigate outbreaks."

"Care workers need paid time in which to access vaccination and good training, decent wages (including sick pay), personal protective equipment, and strong infection control measures," they conclude.

When blood flow to the brain is somehow reduced or restricted, a person can suffer what we know as a stroke (from "ischemic stroke" in medical jargon). Stroke is one of those conditions that seems fairly common. This isn't a misperception: just in Europe, there are over 1.5 million new cases each year.

Some strokes can be lethal, and when they're not they often result in serious damage to the victim's ability to move. In fact, stroke is one of the major causes of long-term disability today. Recovery can be a long and arduous road. Again, in Europe, under 15% of the patients achieve full recovery, leaving 3.7 million patients with persistent impairments. Clearly, this is a medical problem that needs urgent addressing.

But rehabilitation is a complicated problem to solve. Strokes can occur in different parts of the brain, affecting different brain systems, and patients who undergo rehabilitation show a "heterogeneity in outcome", which is the medical way of saying that recovery can be very different between individual stroke victims.

"The key is to find the optimal neuro-rehabilitative strategy to maximize individual treatment outcome," says Professor Friedhelm Hummel, a neuroscientist and Director of the Defitech Chair for Clinical Neuroengineering at EPFL's School of Life Sciences. "If we want to address these challenges in everyday clinical practice, we have to first enhance our ability to predict the individual courses of recovery" adds Dr Philipp J. Koch, the study's first author.

Hummel has now led an international team of scientists into a new approach for outcome prediction that can significantly improve stroke treatment. Publishing in the journal Brain, they demonstrate a predictive method based on two powerful, cutting-edge tools: connectomes and machine learning.

The team included scientists from Sungkyunkwan University School of Medicine (Professor Y.-H. Kim), University Medical School of Geneva (Professor A. Guggisberg), Inserm Paris (Professor C. Rosso), Santa Lucia Foundation IRCCS, Rome (Professor G. Koch), and EPFL (Professor Thiran).

What is a connectome? Simply put, it's a map of a brain's wiring. The term itself was coined independently in 2005 by two scientists (one from Lausanne's University Hospital) to describe the "blueprint" of how a brain's neurons connect to each other, evoking the concept of the genome - hence, "connectome".

Connectomes are generated by analyzing multiple images taken from magnetic resonance imaging and reconstructing the brain's structural or functional wiring non-invasively and in vivo. Today, connectomes are indispensable tools for neuroscientists, especially when they want to interpret structural or dynamic brain data and associate them with functions, functional deficits, or recovery processes. In short, the connectome shows how the brain is wired to control the body and its functions, which makes them important for working out the best recovery approach for a stroke victim.

In the study, Hummel's group analyzed connectomes from 92 patients two weeks after the stroke, tracking connectome changes up to three months later while assessing motor impairment with a standardized scale. This allowed them to monitor connection changes in the individual brains of the patients while they underwent recovery.

The scientists input the connectome information into a "support-vector machine", or SVM, which is a type of machine-learning model that uses examples to map an input onto an output. SVMs are particularly useful for classification, where they tell things apart and categorize them appropriately, e.g. spam and non-spam email.

In this study, the researchers trained the SVMs to distinguish between patients with natural recovery from those without based on their whole-brain structural connectomes. The SVMs then defined the underlying brain-network pattern of each patient, focusing on those who were severely impaired to make predictions about their recovery potential, with the accuracy of each prediction cross-validated internally and externally with independent datasets.

The result is a cutting-edge tool of personalized medicine: a machine-learning system that can identify neuronal network patterns to make high-accuracy predictions on the outcome of recovery for stroke patients. "This tool can support the prediction of individual courses of recovery early on and will have an important impact on clinical management, translational research, and treatment choice," says Hummel.

(Boston)--High-risk neuroblastoma is an aggressive childhood cancer with poor treatment outcomes. Despite intensive chemotherapy and radiotherapy, less than 50 percent of these children survive for five years. While the genetics of human neuroblastoma have been extensively studied, actionable therapeutics are limited.

Now researchers in the Feng lab at Boston University School of Medicine (BUSM), in collaboration with scientists in the Simon lab at the Perelman School of Medicine at the University of Pennsylvania (Penn), have not only discovered why this cancer is so aggressive but also reveal a promising therapeutic approach to treat these patients. These findings appear online in the journal Cancer Research, a journal of the American Association for Cancer Research.

"Our work pinpoints a targeted therapy for treating this group of at-risk patients, likely leading to improved survival," said corresponding author Hui Feng, MD, PhD, associate professor of pharmacology and medicine at BUSM.

The research, led by Nicole M. Anderson, PhD, a former postdoc in the Feng lab and a current fellow in the Simon lab, combined patient sample analysis with genetic analysis of a zebrafish model of high-risk neuroblastoma and cell culture gene inactivation studies to understand the contribution of Dihydrolipoamide S-Succinyltransferase (DLST), a metabolic enzyme, and found that it promotes metastatic spread of this type of cancer.

"We show that elevated DLST expression not only predicts poor patient outcomes, but also disease aggression in human neuroblastoma. In the zebrafish model of neuroblastoma even a modest increase in DLST protein levels can accelerate neuroblastoma onset, increase tumor burden, and promote metastasis," explains Celeste Simon, PhD, co-corresponding author and scientific director and investigator at Abramson Family Cancer Research Institute, UPenn at Penn. Conversely, they found a 50 percent reduction in DLST impairs neuroblastoma initiation and suppresses tumor aggression. DLST depletion in human neuroblastoma cells decreases cell growth and induces apoptosis (cell death).

The researchers utilized cell lines together with zebrafish and mouse neuroblastoma models to test the therapeutic efficacy of IACS-010759, a drug that is in clinical trials for treating other cancers. "Our studies revealed that human neuroblastoma cells are sensitive to IACS treatment, which slowed tumor cell growth in all models tested," said Feng.

She hopes that this study will provide IACS-010759 as a targeted therapy for children with this aggressive disease.

Metastatic tumors originating from notoriously aggressive triple-negative breast cancer that emerge in the lungs contain a more diverse array of cancer cells than those that arise in the liver, according to a new study in mice and organs from deceased cancer patients. The study also identified a set of genes that distinguish lung and liver metastases; together, the findings may inform future research on how targeted therapies impact tumors across various microenvironments. While scientists have known that the presence of distinct tumor cell populations within the same tumor drives breast cancer progression, it has not been fully understood why this dangerous cellular diversity develops within some tumors and not others. To investigate how metastases vary based on host tissue type, Jean Berthelet and colleagues optimized a new optical barcoding strategy and analyzed 31 triple-negative breast cancer subclones (subpopulations of cells descended from cancer cells). The researchers injected fluorescently labeled cells into the mammary fat pads of mice with cancer and mapped the clonal composition of thousands of metastases in the lungs and liver, where triple-negative breast cancer cells tend to spread. They found that the inflammatory tumor necrosis factor alpha (TNF-? ) pathway was particularly upregulated in metastases in the lungs compared with those in the liver, with some genes in this pathway potentially responsible for the success of lung metastases. Berthelet et al. also collected 4 lung and 7 liver metastases from autopsies of 3 patients with breast cancer, confirming that the genes they identified were also expressed differently between the lungs and liver in humans.

Hamilton, ON (July 7, 2021) - A McMaster University team of researchers recently discovered how, exactly, the COVID-19 vaccines that use adenovirus vectors trigger a rare but sometimes fatal blood clotting reaction called vaccine-induced immune thrombotic thrombocytopenia or VITT.

The findings will put scientists on the path of finding a way to better diagnose and treat VITT, possibly prevent it and potentially make vaccines safer.

The researchers' article was fast-tracked for publication today by the prestigious journal Nature in its accelerated article preview because of the importance of the research.

"Our work also answers important questions about the connection between antibodies and clotting," said Ishac Nazy, principal investigator and corresponding author of the study. He added it will have both diagnostic and therapeutic implications.

Nazy is the scientific director of the McMaster Platelet Immunology Laboratory and an associate professor of medicine for the Michael G. DeGroote School of Medicine at McMaster.

The COVID-19 vaccines using adenoviral vectors, such as those from AstraZeneca and Johnson and Johnson, are associated with the VITT clotting disorder caused by unusual antibodies to blood platelets that are triggered by the vaccine.

The study shows, at a molecular level, how those unusual antibodies stick to components from blood platelets causing them to trigger clot formation.

"The antibodies stick to the platelet protein called platelet factor 4 (PF4) in a very unique and specific orientation, which allows them to align with other antibodies and platelets in the precise formation that leads to a self-perpetuating vicious cycle of clotting events," said Nazy.

"These disease-causing aggregates quickly activate platelets, creating a highly intense clotting environment in patients," he added.

The dangerous reaction to the adenovirus vector vaccines has been found to occur in one in 60,000 of people receiving the vaccine in Canada.

"The intention of our study was to better understand how the severe clots which characterize VITT develop," said Donald Arnold, study co-investigator and co-medical director of the McMaster Platelet Immunology Laboratory.

"A basic principle of medical care is to understand how the disorder happens and, in doing so, develop better treatments."

John Kelton, co-investigator of the study and co-medical director of the McMaster Platelet Immunology Laboratory, added: "We believe that this study is important because it clarifies how the clotting ensues, and because we have been able to identify the molecules involved.

"The next step is to develop a rapid diagnostic and accurate test to diagnose VITT. Our major interest is now to move upstream from how the clots happen to preventing them from occurring."

Current rapid tests yield false-negative results, and testing relies on more time-consuming tests to confirm VITT. This study now explains why the rapid tests frequently fail and allows for new strategies to improve diagnostic testing.

The investigators altered the molecular composition of the PF4 protein and, using this technology, were able to identify the binding region on the protein.

As society moves towards a renewable energy future, it's crucial that solar panels convert light into electricity as efficiently as possible. Some state-of-the-art solar cells are close to the theoretical maximum of efficiency--and physicists from the University of Utah and Helmholtz-Zentrum Berlin have figured out a way to make them even better.

In a new study, physicists used a technique known as cross-correlation noise spectroscopy to measure miniscule fluctuations in electrical current flowing between materials inside silicon solar cells. The researchers identified crucial electrical noise signals that are completely invisible to conventional noise-measuring methods. They were also able to pinpoint the likely physical processes causing the noise, which often results in a loss of energy and lower efficiency.

"Measuring noise on an object is relatively simple. You can just buy devices that do it. But the problem that plagues us is that these devices also have noise," said Kevin Davenport, associate instructor of physics at the U and lead author of the paper. "This cross-correlation technique allows us to not only measure the noise of the device, but to also measure the noise of our detector and remove it so that we can see much, much smaller noise signals."

The technique, that was published on June 24 in the journal Scientific Reports, is an important new tool to improve material interfaces for a better solar cell, or to analyze inefficiencies in other complicated devices.

"It's surprising how important tiny improvements in efficiency is for industry. Just a fraction of a percent improvement translates into billions of dollars because of the scale of production," said co-author Klaus Lips, professor of physics at Freie Universität Berlin and department head at Helmholtz-Zentrum Berlin where the solar cells have been designed and fabricated.

"In the past, we have used the cross-correlation technique to study fairly simple research-grade light emitting diodes, but advantages of the method truly came into the light in this work," said Andrey Rogachev, professor of physics at the U and co-author of the study. "And it goes beyond the solar industry. In any device with many layers, each interface between materials can diminish efficiency in some way. It's so complicated, you have to be really discreet to be able to say what's going on and, more importantly, where the particular noise is happening. It turns out that this technique allows us to do just that."

As often happens in modern research, a single method was not enough to understand complex devices. Interpretation of the noise date have been heavily helped by solar cell simulations carried out by C.T. Trinh, a postdoctoral researcher at Helmholtz-Zentrum Berlin and co-author of the study. The final co-author is Mark Hayward, then an undergraduate research at the U and now a graduate student at University of California, Irvine.

Analyzing noise

The study analyzed silicon heterojunction solar cells (HSCs), a high-end type of single-material solar cell and currently the most efficient of its kind on the market--26.7% of light that hits the cell is converted into electricity. In contrast, the cells that make up solar panels on a residential house range between 15% and 20% efficiency.

In an HSC, electricity generation starts when individual particles of light called photons are absorbed by the photo-active layer made of crystalline silicon and creates pairs of negatively charged electrons and positively charged holes, which are charges caused by missing electrons. Electrons and holes are then pulled in opposite directions by an electrical field created by two selective contacts made of hydrogenated amorphous silicon modified with impurities. This process produces current that we use as electricity. The problem is that the selective electrode and photo-active silicon do not match together perfectly, creating defects that trap electrons. To eliminate these defects in research-grade solar cells like the ones in the study, the scientists place between them an ultrathin layer of pure amorphous silicon. Finally, all of these five layers are sandwiched between two layers of transparent conducting material, known as ITO, and gold electrodes.

The efficiency of HSCs depends on how well the different layers are connected together. A slight mismatch between two layers can make it difficult for the electrons to get where they need to go--a problem that will produce a noise signal.

"That problem is kind of hidden inside these interfaces, and it's really difficult to be able to detect any kind of signal. But the noise technique that we use is very sensitive to really, really small individual signals," said Davenport. It's like listening to a note played by different instruments, he continued. A C-note on a violin is the same as a C-note on a cello, but they sound different. If you were to analyze that note, you can pull out information to learn something about the instrument that produced it, like the length or material of the strings.

"We do something similar to that. We see this wide spectrum of different noise signals and different positions along the frequency axis. We can say, 'OK, this part of the note that we see, we can attribute to this physical process and this part is a different physical process,'" said Davenport. "But the device is full of these processes that all generate noise and it's really difficult to un-entangle them--like pulling out a single voice in a 200-person chorus. This technique allows us to remove a lot of the unwanted portion of the signal."

Mapping inefficiencies

The silicon HSCs are excellent as they are, but they still have limits. The research team's new technique identified key areas in the device where specific physical processes are producing electrical signals. In the future, small adjustments at these stages could improve the efficiency of these cells, and solar cells of the future. After sifting through the electrical cacophony to discover the relevant signals, the physicists ran a simulation to pinpoint what physical processes were happening at the location of the signal.

The next generation of solar cells are known as tandem cells, which are stacks of different photovoltaic materials that are each sensitive to a different part of the sun's light, giving such a device an ability to generate more energy. One proposed device layer is the hot-ticket perovskite material.

"Together, the new solar cell can break through the limit of the silicon device by itself, beyond 30% efficiency," said Lips.

At this edge of efficiency, small losses matter. One such loss has been observed by material scientists; the deposition of the transparent ITO somehow modifies the underlying silicon layers, creating defects which reduce the device's efficiency. One of the major electrical noise signals that the researchers identified in this study was at this interface, where the charges are trapped and released. Another major signal occurred as holes passed through a similar barrier on the back side of the device.

"The ability to detect these signals means that we can understand their sources and mitigate them," said Davenport.

Dr Bock, under the mentorship of Distinguished Professor Dietmar Hutmacher, from QUT Centre for Biomedical Technologies, has focused her research on bone metastases from breast and prostate cancers.

She developed 3D miniature bone-like tissue models in which 3D printed biomimetic scaffolds are seeded with patient-derived bone cells and tumour cells to be used as clinical and preclinical drug testing tools.

The research team investigated their hypothesis that traditional anti-androgen therapy had limited effect in the microenvironment of prostate cancer bone tumours. The team's findings are published in Science Advances.

"We wanted to see if the therapy could be a contributor of cancer cells' adaptive responses that fuelled bone metastasis," Professor Hutmacher said.

"We developed an all-human, microtissue-engineered model of metastatic tissue using human bone-forming cells, prostate cancer cells and 3D printing."

Cancer biologist Distinguished Professor Judith Clements said the team bioengineered the microenvironment of a bone tumour to assess the effects of two clinically routinely used anti-androgen therapies - enzalutamide and bicalutamide - on the tumour cells.

"We found that the interactions between the cancer cells, the bone and the anti-androgens significantly impacted the progress of cancer in the mineralised microenvironment of bone tumours," Professor Clements said.

"This means that the efficacy of these therapies is compromised in the presence of the bone microenvironment."

Professor Hutmacher said an important outcome of the study was the need to upscale the bone tumour microenvironment model platform and make it available to other research groups.

"This would enable the prostate cancer research community to develop therapies for a more effective treatment of advanced prostate cancer."

In future, Dr Bock will use her model with patient-derived cells from patients undergoing prostatectomy, so that it could be used as a personalised preclinical diagnostic and drug testing tool.

"By screening existing and novel drugs using the bone tumour model in the laboratory, doctors will be able to treat individual patients with an anti-cancer therapy that can best suit their clinical need," Dr Bock said.

"This has the potential to considerably improve the quality of life of patients, because patients will not have to trial a succession of drugs, each of which carry the potential of severe side-effects, and which may not work for them."

This research was supported by the National Health & Medical Research Council of Australia, Australian Research Council and the Prostate Cancer Foundation of Australia.

Prostate Cancer Foundation of Australia CEO Professor Jeff Dunn AO said the findings were significant.

"This is an important discovery that will help us to better target treatments for men with different types of prostate cancer," he said.

"The findings also demonstrate the importance of ongoing research to improve our understanding of how different treatments impact disease progression and spread.

"Notably, Australia has one of the highest incidence rates of prostate cancer internationally, with 1 in every 6 Australian men likely to be diagnosed during their lifetime and around 17,000 men diagnosed each year.

"While survival rates for prostate cancer are high, with over 95% of men likely to survive at least five years, we must keep up the pace of work to find curative treatments, especially for advanced disease in the bone.

"There can be no doubt that this research will build on previous discoveries to help us save lives by stopping cancer from spreading and claiming the lives of more than 3,000 men a year, as is currently the case.

"We commend the research team and congratulate PCFA grant recipient Dr Nathalie Bock for her research achievements.

"This is Australian research excellence at its finest," he said.

QUT PhD researcher Zachariah Schuurs said the research team had identified a new binding site on the SARS-CoV-2 spike protein.

"Binding of the CoV-2 spike protein to heparan sulphate (HS) on cell surfaces is generally the first step in a cascade of interactions the virus needs to initiate an infection and enter the cell.

"Most research has focused on understanding how HS interacts on the receptor-binding domain (RBD) and furin cleavage site of the SARS-CoV-2 virus's spike protein, as these typically bind different types of drugs, vaccines and antibodies.

"We have identified a novel binding site on the N-terminal domain (NTD), a different area of the virus's spike that facilitates the binding of HS. This helps to better understand how the virus infects cells. The NTD is also a part of the spike protein that frequently mutates.

"Some antibodies in the blood that neutralise the viruses bind to the same region of the NTD.

"Therefore, targeting the NTD site with molecules like heparin (or heparin mimetics), a known anti-coagulant drug similar to HS, is a possible strategy to stop the virus binding to cells and infecting them."

Dr Neha Gandhi, from the QUT Centre for Genomics and Personalised Health, said COVID19 vaccines, although achieving success worldwide, were still far from being widely accessible.

"We need alternative antiviral strategies to prevent the spread of COVID-19 and treat infected people," Dr Gandhi said.

"Epidemiologists believe that persistent low-vaccine coverage in many countries will make it more likely for vaccine-resistant mutations to appear.

"Variants of concern have already emerged in South Africa, the US, India and Brazil. In this regard, alternate antiviral strategies are strongly needed to prevent the spread of COVID-19 and to treat people with COVID-19.

"Most SARS-CoV-2 variants have acquired a positively charged mutation in the spike protein. Molecules like heparin and its mimetics are negatively charged and therefore, these molecules could be used to treat people with severe effects of the virus and any emerging variants.

"Our research indicates that molecules that mimic the 3D structure of heparin with different sulphur chemistry, might be potential broad-spectrum antiviral drugs for COVID-19 and other emerging viral threats via direct interaction with the virus itself."

The multi-national study, "Evidence of a putative glycosaminoglycan binding site on the glycosylated SARS-CoV-2 spike protein N-terminal domain" published in the Computational and Structural Biotechnology Journal, used both computational and experimental techniques to confirm their finding.

The researchers used NCI Gadi and QUT Lyra supercomputers to model how HS and its inhibitor like heparin would interact with the spike protein.

Various researchers from the University of Queensland (Glycochemistry), Curtin University (Immunology), Zucero Pharmaceuticals and QUT conceptualised the study. These computational molecular simulations run by the QUT research team tested and confirmed the hypothesis that heparan sulphate could form a bridge between the newly identified binding site and another site on the spike important in the virus's infection.

A new study of lithium production in a classical nova found a production rate of only a couple of percent that seen in other examples. This shows that there is a large diversity within classical novae and implies that nova explosions alone cannot explain the amount of lithium seen in the current Universe. This is an important result for understanding both the explosion mechanism of classical novae and the overall chemical evolution of the Universe.

In the modern world, lithium is used in the rechargeable batteries powering smartphones and other devices. It was thought that most of the lithium found on Earth, and the rest of the Universe, was originally produced in classical nova explosions. Observations of the classical nova V339 Del using the Subaru Telescope supported this theory, providing the first observational evidence of large amounts of lithium being produced and ejected into space (Classical Nova Explosions are Major Lithium Factories in the Universe on February 18, 2015).

Now, a team led by Akira Arai, a researcher at Koyama Astronomical Observatory of Kyoto Sangyo University, used the Subaru Telescope's open-use observation program to study V5669 Sgr, a classical nova that appeared in Sagittarius in 2015. This was only the eighth time this type of study has been successfully conducted. Four of those eight, including the first, were conducted using the Subaru Telescope. This time is remarkable because the estimated lithium production is only a few percent of the production seen in the others. This indicates that there is a large diversity in novae. The fact that some novae produce only a small amount of lithium suggests that other objects, such as supernovae, may make important contributions to lithium production in the Universe.