Monash researchers on the front line in fight against fungal infections

The fungal pathogen Candida albicans transformed with a green fluorescence protein (GFP) tagged iron sensor is engulfed by macrophages. Upon iron starvation induced by macrophages Candida will express GFP and make hyphal projections thereby escaping immune cells.
Source: Monash University

With fungal infections killing 1.5 million people each year, Monash University researchers are playing an important role as the World Health Organization recognizes this growing threat.

The world-leading Monash experts are among a small but determined group of researchers working to curb the growing impact of potentially dangerous fungal infections.

In late October, 2022, WHO published a report highlighting the first list of fungal "priority pathogens" – a catalogue of the 19 fungi that represent the greatest threat to public health.

The premise behind the publication is twofold: fungi are a significant and increasing threat to public health, and because there is little global research and development into fungi or their treatment.

Professor Ana Traven, from the Monash Biomedicine Discovery Institute, said fungi could range from benign (skin and nail infections and vaginal thrush) to the deadly (Candida, Aspergillus).

Researchers kick goals with soccer findings

Photo Credit: Joshua Hoehne

University of Queensland scientists have developed a model that gives soccer players their best chance of kicking a penalty goal.

After analyzing strategies used by penalty shot kickers and goalkeepers, researchers developed a model that coaches can use to identify the best shooting strategy against a particular goalkeeper.

Professor Robbie Wilson, head of the UQ Football Research Group at UQ’s School of Biological Sciences, said the outcome of a penalty shot was determined by a complex interaction between the shooter and the goalkeeper.

“Usually, a player’s performance is constrained by biomechanical trade-offs but each player has a range of strategies to overcome these,” Professor Wilson said.

“For example, if a shooter kicks at a high speed, accuracy is decreased, and if a goalkeeper moves early, the probability they’ll move in the correct direction is reduced.”

He said every player, including international stars like Cristiano Ronaldo and Lionel Messi, had a range of kicking speeds and areas of the goal in which they were naturally better or worse.

Hummingbird flight could provide insights for biomimicry in aerial vehicles

Hummingbirds have extreme aerial agility and flight forms, which is why many drones and other aerial vehicles are designed to mimic hummingbird movement. Using a novel modeling method, researchers gained new insights into how hummingbirds produce wing movement, which could lead to design improvements in flying robots.
Photo Credit: Zdeněk Macháček

Hummingbirds occupy a unique place in nature: They fly like insects but have the musculoskeletal system of birds. According to Bo Cheng, the Kenneth K. and Olivia J. Kuo Early Career Associate Professor in Mechanical Engineering at Penn State, hummingbirds have extreme aerial agility and flight forms, which is why many drones and other aerial vehicles are designed to mimic hummingbird movement. Using a novel modeling method, Cheng and his team of researchers gained new insights into how hummingbirds produce wing movement, which could lead to design improvements in flying robots.

Their results were published this week in the Proceedings of Royal Society B.

“We essentially reverse-engineered the inner working of the wing musculoskeletal system — how the muscles and skeleton work in hummingbirds to flap the wings,” said first author and Penn State mechanical engineering graduate student Suyash Agrawal. “The traditional methods have mostly focused on measuring activity of a bird or insect when they are in natural flight or in an artificial environment where flight-like conditions are simulated. But most insects and, among birds specifically, hummingbirds are very small. The data that we can get from those measurements are limited.”

Prostate cancer risk prediction algorithm could help target testing at men at greatest risk

Prostate cancer is the most common type of cancer in men
Photo Credit: Shawnee D

Cambridge scientists have created a comprehensive tool for predicting an individual’s risk of developing prostate cancer, which they say could help ensure that those men at greatest risk will receive the appropriate testing while reducing unnecessary – and potentially invasive – testing for those at very low risk.

CanRisk-Prostate, developed by researchers at the University of Cambridge and The Institute of Cancer Research, London, will be incorporated into the group’s CanRisk web tool, which has now recorded almost 1.2 million risk predictions. The free tool is already used by healthcare professionals worldwide to help predict the risk of developing breast and ovarian cancers.

Prostate cancer is the most common type of cancer in men. According to Cancer Research UK, over 52,000 men are diagnosed with the disease each year and there are more than 12,000 deaths. Over three-quarters (78%) of men diagnosed with prostate cancer survive for over ten years, but this proportion has barely changed over the past decade in the UK.

Testing for prostate cancer involves a blood test that looks for a protein known as a prostate-specific antigen (PSA) that is made only by the prostate gland; however, it is not always accurate. According to the NHS website, around three in four men with a raised PSA level will not have cancer. Further tests, such as tissue biopsies or MRI scans, are therefore required to confirm a diagnosis.

Aging is driven by unbalanced genes

Northwestern University researchers have discovered a previously unknown mechanism that drives aging.

In a new study, researchers used artificial intelligence to analyze data from a wide variety of tissues, collected from humans, mice, rats and killifish. They discovered that the length of genes can explain most molecular-level changes that occur during aging.

All cells must balance the activity of long and short genes. The researchers found that longer genes are linked to longer lifespans, and shorter genes are linked to shorter lifespans. They also found that aging genes change their activity according to length. More specifically, aging is accompanied by a shift in activity toward short genes. This causes the gene activity in cells to become unbalanced.

Surprisingly, this finding was near universal. The researchers uncovered this pattern across several animals, including humans, and across many tissues (blood, muscle, bone and organs, including liver, heart, intestines, brain and lungs) analyzed in the study.

The new finding potentially could lead to interventions designed to slow the pace of — or even reverse — aging.

How a viral toxin may exacerbate severe COVID-19

In a new study, University of California, Berkeley, researchers find that portions of the SARS-CoV-2 “spike” protein, shown in the foreground, can damage the cell barriers that line the inside of blood vessels, contributing to some of COVID-19’s most dangerous symptoms, including acute respiratory distress syndrome (ARDS).
Image Credit: National Institutes of Health

In a new study, University of California, Berkeley, researchers find that portions of the SARS-CoV-2 “spike” protein, shown in the foreground, can damage the cell barriers that line the inside of blood vessels, contributing to some of COVID-19’s most dangerous symptoms, including acute respiratory distress syndrome (ARDS). (National Institutes of Health photo via Flickr)

A study published today in the journal Nature Communications reveals how a viral toxin produced by the SARS-CoV-2 virus may contribute to severe COVID-19 infections.

The study shows how a portion of the SARS-CoV-2 “spike” protein can damage cell barriers that line the inside of blood vessels within organs of the body, such as the lungs, contributing to what is known as vascular leak. Blocking the activity of this protein may help prevent some of COVID-19’s deadliest symptoms, including pulmonary edema, which contributes to acute respiratory distress syndrome (ARDS).

“In theory, by specifically targeting this pathway, we could block pathogenesis that leads to vascular disorder and acute respiratory distress syndrome without needing to target the virus itself,” said study lead author Scott Biering, a postdoctoral scholar at the University of California, Berkeley. “In light of all the different variants that are emerging and the difficulty in preventing infection from each one individually, it might be beneficial to focus on these triggers of pathogenesis in addition to blocking infection altogether.”

Smilodon's saber teeth

Life-size reconstruction of three different species studied with their stress thermal maps at the three different angles for a right lower canine bite. The colder colors on the thermal maps of saber-toothed species indicate lower stress and higher force, especially when biting at larger angles.
Illustration Credit: Massimo Molinero

A team of researchers led by Narimane Chatar, doctoral student at EDDyLab at the University of Liège, tested the bite effectiveness of the Smilodon, an extinct species of carnivore close to current felines. Thanks to high precision 3D scans and simulation methods, the team has just revealed how these animals managed to bite despite the impressive length of their teeth. This study is the subject of a publication in the journal Proceedings of the Royal Society B

ancient carnivorous mammals have developed a wide range of skulls and teeth throughout their evolution. However, few of these developments have yet equaled those of the felidated saber-toothed emblematic Smilodon. Other groups of mammals, such as the now extinct nimravids, have also evolved into a similar morphology, with species with saber teeth but also much shorter canines, similar to those of lions, tigers, caracals, domestic cats, etc. that we know today. This phenomenon of the appearance of similar morphologies in different groups of organisms is known as convergent evolution; felines and nimravids being an astonishing example of convergence. As there are no modern animal equivalents with such saber-shaped teeth, the hunting method. Smilodon and other similar species remained obscure and the subject of heated debate. It was initially suggested that all saber-toothed species hunted in the same way, regardless of the length of their canines, a hypothesis which is today controversial. From then on, the question remained suspended ... How did this variety of "saber-toothed cats" hunt?

SARS-CoV-2 protein caught severing critical immunity pathway

This image shows the SARS-CoV-2 virus's main protease, Mpro, and two strands of a human protein, called NEMO. One NEMO strand (blue) has been cut by Mpro, and the other NEMO strand (red) is in the process of being cut by Mpro. Without NEMO, an immune system is slower to respond to increasing viral loads or new infections. Seeing how Mpro attacks NEMO at the molecular level could inspire new therapeutic approaches. 
Illustration Credit: Greg Stewart/SLAC National Accelerator Laboratory

Over the past two years, scientists have studied the SARS-CoV-2 virus in great detail, laying the foundation for developing COVID-19 vaccines and antiviral treatments. Now, for the first time, scientists at the Department of Energy’s SLAC National Accelerator Laboratory have seen one of the virus’s most critical interactions, which could help researchers develop more precise treatments.

The team caught the moment when a virus protein, called Mpro, cuts a protective protein, known as NEMO, in an infected person. Without NEMO, an immune system is slower to respond to increasing viral loads or new infections. Seeing how Mpro attacks NEMO at the molecular level could inspire new therapeutic approaches.

To see how Mpro cuts NEMO, researchers funneled powerful X-rays from SLAC’s Stanford Synchrotron Radiation Lightsource (SSRL) onto crystallized samples of the protein complex. The X-rays struck the protein samples, revealing what Mpro looks like when it dismantles NEMO’s primary function of helping our immune system communicate.

New findings on how to avert excessive weight loss from COVID-19

Professor Yihai Cao.
Photo Credit: Dr. Muyi Yang.

Losing too much weight when infected with COVID-19 has been linked to worse outcomes. Now, researchers at Karolinska Institutet have discovered that SARS-CoV-2 infection fuels blood vessel formation in fat tissues, thus revving up the body’s thermogenic metabolism. Blocking this process by using an existing drug curbed weight loss in mice and hamsters that were infected with the virus, according to the study published in the journal Nature Metabolism.

“Our study proposes a completely new concept for treating COVID-19 associated weight loss by targeting the blood vessels in the fat tissues,” says Yihai Cao, professor at the Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet, and the study’s corresponding author.

The researchers examined how different types of fat, including brown fat and visceral and subcutaneous white fat, reacted when exposed to SARS-CoV-2 and how it impacted weight in mice and hamsters. They found that the animals lost significant amounts of weight in four days and that this weight loss was preceded by the activation of brown fat and the browning of both types of white fat. These fat tissues also contained more microvessels and high levels of a signaling protein called vascular endothelial growth factor (VEGF), which promotes the growth of new blood vessels.

Neural Network Learned to Create a Molecular Dynamics Model of Liquid Gallium

The melt viscosity determines the choice of casting mode, ingot formation conditions and other parameters.
Photo Credit: Ilya Safarov

Scientists at the Institute of Metallurgy, Ural Branch of the Russian Academy of Sciences, and Ural Federal University have developed a method for theoretically high-precision determination of the viscosity of liquid metals using a trained artificial neural network. The method was successfully tested in the process of building the deep learning potential of the neural network on the example of liquid gallium. Scientists were able to significantly increase the spatiotemporal scale of the simulation. The results of molecular dynamics modeling of liquid gallium are particularly accurate. Previous calculations were notoriously inaccurate, especially in the low temperature range. An article describing the research was published in the journal Computational Materials Science.

"First, liquids are in principle difficult to be described theoretically. The reason, in our opinion, lies in the absence of a simple initial approximation for this class of systems (for example, the initial approximation for gases is the ideal gas model). Secondly, the atomistic calculation of viscosity requires processing of a large volume of statistical data and, at the same time, a large accuracy of description of the potential energy surface and forces acting on atoms. Direct calculations cannot achieve such an effect. Thirdly, gallium in the liquid state is difficult to describe theoretically, because, due to certain features, its structure differs from that of most other metals," explains Vladimir Filippov, Senior Researcher at the Department of Rare Metals and Nanomaterials at UrFU, research participant and co-author of the article.