Current anti-COVID pills work well against omicron, but antibody drugs are less effective

Yoshihiro Kawaoka

The drugs behind the new pills to treat COVID-19 remain very effective against the omicron variant of the virus in lab tests, according to a new study.

However, lab tests also showed that the available antibody therapies — typically given intravenously in hospitals — are substantially less effective against omicron than against earlier variants of the virus. The antibody treatments by Lilly and Regeneron have entirely lost their ability to neutralize omicron at realistic dosages. The Food and Drug Administration recently removed these two drugs from approved treatment lists because they are ineffective against the variant.

If the ability of the antiviral pills to combat omicron is confirmed in human patients, it would be welcome news. Public health officials expect the pills to become an increasingly common treatment for COVID-19 that will reduce the severity of the disease in at-risk patients and decrease the burden of the pandemic.

For now, the pills remain in short supply during the current omicron wave, which has broken case records in the U.S. and other countries.

The findings corroborate other studies that show most available antibody treatments are less effective against omicron. Drug makers could design, test and produce new antibody drugs targeted at the omicron variant to overcome the limitations of current therapies, but this process would take months.

“The bottom line is we have countermeasures to treat omicron. That’s good news,” says Yoshihiro Kawaoka, the University of Wisconsin–Madison lead of the study and virologist at the UW School of Veterinary Medicine and the University of Tokyo. “However, this is all in laboratory studies. Whether this translates into humans, we don’t know yet.”

Studying the Big Bang with Artificial Intelligence

A quark gluon plasma after the collision of two heavy nuclei
Credit: Technische Universität Wien

Can machine learning be used to uncover the secrets of the quark-gluon plasma? Yes - but only with sophisticated new methods.

It could hardly be more complicated: tiny particles whir around wildly with extremely high energy, countless interactions occur in the tangled mess of quantum particles, and this results in a state of matter known as "quark-gluon plasma". Immediately after the Big Bang, the entire universe was in this state; today it is produced by high-energy atomic nucleus collisions, for example at CERN.

Such processes can only be studied using high-performance computers and highly complex computer simulations whose results are difficult to evaluate. Therefore, using artificial intelligence or machine learning for this purpose seems like an obvious idea. Ordinary machine-learning algorithms, however, are not suitable for this task. The mathematical properties of particle physics require a very special structure of neural networks. At TU Wien (Vienna), it has now been shown how neural networks can be successfully used for these challenging tasks in particle physics.

Scientists Regrow Frog’s Lost Leg

A normal African clawed frog. “It’s exciting to see that the drugs we selected were helping to create an almost complete limb,” said Nirosha Murugan.
Photo: Pouzin Olivier, via Creative Commons

For millions of patients who have lost limbs for reasons ranging from diabetes to trauma, the possibility of regaining function through natural regeneration remains out of reach. Regrowth of legs and arms is the province of salamanders and superheroes.

But in a study published in the journal Science Advances, scientists at Tufts and Harvard University’s Wyss Institute have brought us a step closer to the goal of regenerative medicine.

On adult frogs, which are naturally unable to regenerate limbs, the researchers were able to trigger regrowth of a lost leg using a five-drug cocktail applied in a silicone wearable bioreactor dome that seals in the elixir over the stump for just 24 hours. That brief treatment sets in motion an 18-month period of regrowth that restores a functional leg.

Many creatures have the capability of full regeneration of at least some limbs, including salamanders, starfish, crabs, and lizards. Flatworms can even be cut up into pieces, with each piece reconstructing an entire organism. Humans are capable of closing wounds with new tissue growth, and our livers have a remarkable, almost flatworm-like capability of regenerating to full size after a 50% loss.

Future forests will have smaller trees and soak up less carbon, study suggests

There is no crystal ball to tell ecologists how forests of the future will respond to the changing climate, but a University of Arizona-led team of researchers may have created the next best thing.

By combining tree-ring data with U.S. Forest Service inventory data on Arizona's ponderosa pines, the team captured a more complete picture than traditional models have provided of what drives future tree growth. The researchers predict a 56 to 91% decline in individual tree growth, according to a new study published in Global Change Biology.

"The growth declines we're forecasting will mean less uptake of atmospheric carbon dioxide in the future by Arizona's forests," said lead study author Kelly Heilman, a postdoctoral research associate in the UArizona Laboratory of Tree-Ring Research. "While Arizona's forests are relatively small in terms of their contribution to the total U.S. carbon sequestration, our approach can be used to make the same predictions for forests around the world."

Forests remove carbon dioxide from the atmosphere, which offsets some greenhouse gas emissions globally and helps to mitigate climate change.

"It's a free service that forests provide, so forests have been touted as one of the many natural climate solutions that countries rely on to offset their emissions," Heilman said. "But competition between trees, droughts and disturbances can reduce forest carbon uptake. Knowing how much carbon forests take up globally is essential to addressing the climate crisis and planning for a resilient future."

Many countries, including the U.S., maintain national forest inventory programs in which foresters take a census of trees in 1/6-acre plots to track forest status and change. These censuses are taken as frequently as every five years, but in the western U.S. they're done every 10 years. Among the data collected is the number of trees, their diameters and soil quality.

Southern Ocean storms cause outgassing of carbon dioxide

Researchers have examined the inaccessible waters around Antarctica using unique robot technology, and find that ocean storms in the region lead to outgassing of carbon dioxide into the atmosphere. Credit: Fred Fouri

Storms over the waters around Antarctica drive an outgassing of carbon dioxide into the atmosphere, according to a new international study with researchers from the University of Gothenburg. The research group used advanced ocean robots for the study, which provides a better understanding of climate change and can lead to better global climate models.

The world's southernmost ocean, the Southern Ocean that surrounds Antarctica, plays an important role in the global climate because its waters contain large amounts of carbon dioxide. A new international study, in which researchers from the University of Gothenburg participated, has examined the complex processes driving air-sea fluxes of gasses, such as carbon dioxide.

Storms bring carbon dioxide-rich waters to the surface

The research group is now delivering new findings that shed light on the area's important role in climate change.

“We show how the intense storms that often occur in the region increase ocean mixing and bring carbon dioxide-rich waters from the deep to the surface. This drives an outgassing of carbon dioxide from the ocean to the atmosphere. There has been a lack of knowledge about these complex processes, so the study is an important key to understanding the Southern Ocean's significance for the climate and the global carbon budget”, says Sebastiaan Swart, professor of oceanography at the University of Gothenburg and co-author of the study.

Technique Improves AI Ability to Understand 3D Space Using 2D Images

This image shows how MonoCon places objects in a "bounding box" for use in navigating the street.

Researchers have developed a new technique, called MonoCon, that improves the ability of artificial intelligence (AI) programs to identify three-dimensional (3D) objects, and how those objects relate to each other in space, using two-dimensional (2D) images. For example, the work would help the AI used in autonomous vehicles navigate in relation to other vehicles using the 2D images it receives from an onboard camera.

“We live in a 3D world, but when you take a picture, it records that world in a 2D image,” says Tianfu Wu, corresponding author of a paper on the work and an assistant professor of electrical and computer engineering at North Carolina State University.

“AI programs receive visual input from cameras. So if we want AI to interact with the world, we need to ensure that it is able to interpret what 2D images can tell it about 3D space. In this research, we are focused on one part of that challenge: how we can get AI to accurately recognize 3D objects – such as people or cars – in 2D images, and place those objects in space.”

While the work may be important for autonomous vehicles, it also has applications for manufacturing and robotics.

Supercomputing exposes potential pathways for inhibiting COVID-19

SARS-CoV-2 spike protein in the trimer state, shown here, to pinpoint structural transitions that could be disrupted to destabilize the protein and negate its harmful effects.
Credit: Debsindhu Bhowmik/ORNL, U.S. Dept. of Energy

To explore the inner workings of severe acute respiratory syndrome coronavirus 2, or SARS-CoV-2, researchers from the Department of Energy’s Oak Ridge National Laboratory developed a novel technique.

The team — including computational scientists Debsindhu Bhowmik, Serena Chen and John Gounley — ran molecular dynamics simulations of the novel virus that caused the COVID-19 disease pandemic on ORNL’s Summit supercomputer, an IBM AC922 system. The researchers then analyzed the output with a customized deep learning approach to produce a complete molecular picture of the “spike” protein on the virus’s surface.

This method enabled them to pinpoint specific flexible regions, which they studied in extreme detail to reveal promising therapeutic targets. Aiming for these targets could create more reliable treatment avenues that interrupt key structural transitions in the virus’s lifecycle while also supporting the body’s natural immune response.

“A better understanding of the spike protein could complement current COVID-19 vaccines by informing new treatments and providing insights into potential drug design,” Bhowmik said.

Nearly 1,000 mysterious strands revealed in Milky Way’s center

An image showing the spectral index for filaments.
Credit: Northwestern University/SAORO/Oxford University

An unprecedented new telescope image of the Milky Way galaxy’s turbulent center has revealed nearly 1,000 mysterious strands, inexplicably dangling in space.

Stretching up to 150 light years long, the one-dimensional strands (or filaments) are found in pairs and clusters, often stacked equally spaced, side by side like strings on a harp. Using observations at radio wavelengths, Northwestern University’s Farhad Yusef-Zadeh discovered the highly organized, magnetic filaments in the early 1980s. The mystifying filaments, he found, comprise cosmic ray electrons gyrating the magnetic field at close to the speed of light. But their origin has remained an unsolved mystery ever since.

Now, the new image has exposed 10 times more filaments than previously discovered, enabling Yusef-Zadeh and his team to conduct statistical studies across a broad population of filaments for the first time. This information potentially could help them finally unravel the long-standing mystery.

The study is now available online and has been accepted for publication by The Astrophysical Journal Letters.

“We have studied individual filaments for a long time with a myopic view,” said Yusef-Zadeh, the paper’s lead author. “Now, we finally see the big picture — a panoramic view filled with an abundance of filaments. Just examining a few filaments makes it difficult to draw any real conclusion about what they are and where they came from. This is a watershed in furthering our understanding of these structures.”

Yusef-Zadeh is a professor of physics and astronomy at Northwestern’s Weinberg College of Arts and Sciences and a member of the Center for Interdisciplinary Exploration and Research in Astrophysics (CIERA).

Omicron genetics and early transmission patterns are characterized in new study

The Omicron variant was first detected in Botswana
in October 2021 and has quickly spread throughout the world
Credit: Justice Hubane / Unsplash

The Omicron variant of SARS-CoV-2 diverged from previous SARS-CoV-2 variants as a result of adaptive evolution, in which beneficial mutations are passed on to future generations through natural selection, rather than through recombination between previous variants, according to a large international team of researchers. The study, which published recently in Nature, is the first to describe the genomic profile of Omicron and explore the origins of the variant.

“We have seen SARS-CoV-2 generate three major variants — Alpha, Delta and Omicron — in about 16 months, which is very surprising because other viruses do not make such repeated big evolutionary leaps,” said Maciej Boni, associate professor of biology, Penn State, who led the recombination analysis for this global collaboration. “The latest variant — Omicron — is extraordinary because of the even bigger jump it made in the evolution of its spike protein.”

Boni noted that compared to previous variants, Omicron’s spike protein has more than 30 mutations, many of which are known to influence host antibody neutralization.

“Given that Omicron made such a big leap forward evolutionarily speaking, we wanted to investigate why and how this may have happened,” he said.

To do that, the team — which was led by the Centre for Epidemic Response and Innovation in South Africa — analyzed all 686 Omicron sequences that were available by Dec. 7, 2021. They found that Omicron falls within the B.1.1 lineage, which also includes the Alpha variant. Interestingly, the team found that Omicron is genetically distinct from Alpha, as well as any other known variants of interest.

Kirigami Robotic Grippers Are Delicate Enough to Lift Egg Yolks

Engineering researchers from North Carolina State University have demonstrated a new type of flexible, robotic grippers that are able to lift delicate egg yolks without breaking them, and that are precise enough to lift a human hair. The work has applications for both soft robotics and biomedical technologies.

The work draws on the art of kirigami, which involves both cutting and folding two-dimensional (2D) sheets of material to form three-dimensional (3D) shapes. Specifically, the researchers have developed a new technique that involves using kirigami to convert 2D sheets into curved 3D structures by cutting parallel slits across much of the material. The final shape of the 3D structure is determined in large part by the outer boundary of the material. For example, a 2D material that has a circular boundary would form a spherical 3D shape.

“We have defined and demonstrated a model that allows users to work backwards,” says Yaoye Hong, first author of a paper on the work and a Ph.D. student at NC State. “If users know what sort of curved, 3D structure they need, they can use our approach to determine the boundary shape and pattern of slits they need to use in the 2D material. And additional control of the final structure is made possible by controlling the direction in which the material is pushed or pulled.”