Understanding cobalt’s human cost

Miners at a cobalt cleaning site in Lualaba Province, the Democratic Republic of the Congo. Credit Northwestern University

While driving an electric car has fewer environmental impacts than gasoline-powered cars, the production of the parts necessary for these green technologies can have dire effects on human well-being.

After studying the impacts of mining cobalt — a common ingredient in lithium-ion batteries — on communities in Africa’s Democratic Republic of the Congo (DRC), an interdisciplinary team of researchers led by Northwestern University is calling for more data into how emerging technologies affect human health and livelihoods.

Such data can inform policymakers, industry leaders and consumers to make more socially and ethically responsible decisions when developing, funding and using green technologies.

The case study and perspective paper were published today (Dec. 17) in the journal One Earth.

Using sparse data to predict lab quakes

Stick-slip events in the earth cause damage like this,
but limited data from these relatively rare earthquakes makes them
difficult to model with machine learning. Transfer learning may provide
a path to understanding when such deep faults slip.
Credit: Dreamstime

A machine-learning approach developed for sparse data reliably predicts fault slip in laboratory earthquakes and could be key to predicting fault slip and potentially earthquakes in the field. The research by a Los Alamos National Laboratory team builds on their previous success using data-driven approaches that worked for slow-slip events in earth but came up short on large-scale stick-slip faults that generate relatively little data—but big quakes.

“The very long timescale between major earthquakes limits the data sets, since major faults may slip only once in 50 to 100 years or longer, meaning seismologists have had little opportunity to collect the vast amounts of observational data needed for machine learning,” said Paul Johnson, a geophysicist at Los Alamos and a co-author on a new paper, “Predicting Fault Slip via Transfer Learning,” in Nature Communications.

To compensate for limited data, Johnson said, the team trained a convolutional neural network on the output of numerical simulations of laboratory quakes as well as on a small set of data from lab experiments. Then they were able to predict fault slips in the remaining unseen lab data.

This research was the first application of transfer learning to numerical simulations for predicting fault slip in lab experiments, Johnson said, and no one has applied it to earth observations.

New Device Advances Commercial Viability of Solar Fuels

A model solar fuels device called a photoelectrochemical cell. A research team led by Francesca Toma, a staff scientist at the Liquid Sunlight Alliance in Berkeley Lab’s Chemical Sciences Division, designed the model.
Credit: Thor Swift/Berkeley Lab

A research team has developed a new artificial photosynthesis device with remarkable stability and longevity as it converts sunlight and carbon dioxide into two promising sources of renewable fuels – ethylene and hydrogen.

The researchers’ findings, which they recently reported in the journal Nature Energy, reveal how the device degrades with use, then demonstrate how to mitigate it. The authors also provide new insight into how electrons and charge carriers called “holes” contribute to degradation in artificial photosynthesis.

“By understanding how materials and devices transform under operation, we can design approaches that are more durable and thus reduce waste,” said senior author Francesca Toma, a staff scientist in the Liquid Sunlight Alliance (LiSA) and Berkeley Lab’s Chemical Sciences Division.

Drug could more effectively treat patients hospitalized with COVID-19 pneumonia

A proof-of-concept trial led by the University of Birmingham and University Hospitals Birmingham NHS Foundation Trust has identified a drug that may benefit some patients hospitalized with COVID-19 pneumonia.

The CATALYST trial tested UK-based bio-pharmaceutical company Izana Bioscience’s namilumab (IZN-101) as a potential therapeutic to treat patients who are hospitalized with COVID-19 pneumonia, and receiving ‘usual’ care, as well as having high levels in their blood of a marker of inflammation known as C reactive protein (CRP). CRP levels rise when there is inflammation in the body, and elevated levels of CRP have been found to be a potential early marker to predict risk for severity of COVID-19.

An antibody already in late-stage trials to treat rheumatoid arthritis, namilumab targets a ‘cytokine’ which is naturally secreted by immune cells in the body but, in uncontrolled levels, is believed to be a key driver of the excessive and dangerous lung inflammation seen in COVID-19 patients.

The trial, carried out in collaboration with the University of Oxford and funded by the Medical Research Council and carried out between June 2020 and February 2021, involved patients aged over 16 with COVID-19 pneumonia either being treated on a ward or Intensive Care Unit (ICU) at nine NHS hospitals across the UK.

The study, published today in The Lancet Respiratory Medicine, involved 54 patients receiving ‘usual care’ (steroids and oxygen or ventilation, depending on the severity of disease) and 57 patients given usual care as well as a single intravenous dose of 150mg of namilumab.

Gene mutation leads to epileptic encephalopathy symptoms, neuron death in mice

A study led by Illinois postdoctoral researcher Eung Chang Kim and professor Hee Jung Chung found that mice with a genetic mutation associated with epileptic encephalopathy exhibit not only the seizure and behavioral symptoms of the disorder, but also neural degeneration and inflammation in the brain.  Photo by L. Brian Stauffer

Mice with a genetic mutation that’s been observed in patients with epileptic encephalopathy, a severe form of congenital epilepsy, exhibit not only the seizure, developmental and behavioral symptoms of the disorder, but also neural degeneration and inflammation in the brain, University of Illinois Urbana-Champaign researchers found in a new study. The findings highlight the mutation as an important part of the disease’s pathology and a potential target for treatment.

Patients with epileptic encephalopathy begin having seizures when they are born, and display progressive developmental delay, intellectual disability and autismlike behavior, said study leader Hee Jung Chung, a professor of molecular and integrative physiology.

“The dogma regarding epileptic encephalopathy has been that the epileptic seizures are driving the pathogenesis of intellectual disability and developmental delay. But we wanted to answer the question, is it really just the seizures driving the intellectual disability and developmental delay?” Chung said. “This study is the first to show that expressing this human epileptic encephalopathy mutation in mice can cause not only spontaneous seizure and intellectual disability, but also neural degeneration.”

Previous work from Chung’s group found that epileptic encephalopathy is correlated with a mutation in a gene that codes for a potassium channel essential to regulating neuron activity. The mutation prevented the potassium channel from properly embedding in the cell membranes of neurons, causing it to build up inside the neuronal cells instead. Yet, whether and how the mutation played a role in the pathology of epileptic encephalopathy remained unknown.

Room-temperature crystallography aids new study of photosynthetic bacteria

Researchers at SLAC, Stanford University and Washington University
studied a protein that helps transport electrons during bacterial photosynthesis.
Jared Weaver/Stanford University

Chemists have come to a deeper understanding of how photosynthetic bacteria convert light into chemical energy and discovered why one step in the process may be more robust than previously realized, according to a new study published this week in Proceedings of the National Academy of Sciences.

The study focused on proteins called reaction centers in a bacterium called Rhodobacter sphaeroides that help transport electrons in its cell membrane during the first steps of photosynthesis. Although these proteins, which reside in the cell membrane, have been studied for decades, many details of how they work remain unclear. To try to fill in some of those details, Stanford University's Jared Weaver, a graduate student in chemist Steven Boxer's laboratory, worked with fellow Stanford chemist Chi-Yun Lin and Washington University researchers Kaitlyn Fairies, Dewey Holten, and Chris Kirmaier, who have been studying R. sphaeroides reaction centers for over a decade. Their apporach was to replace part of the protein with amino acids – protein building blocks – that do not naturally appear in that part of the protein structure. The results could help researchers better understand how the electron-transporting protein works under normal operation.

As part of those investigations, Weaver teamed up with Irimpan Mathews, a staff scientist at the Stanford Synchrotron Radiation Lightsource (SSRL) at the Department of Energy's SLAC National Accelerator Laboratory. There, the pair worked to crystallize the modified photosynthetic proteins and study them with X-ray macromolecular crystallography at one of SSRL's beamlines.

Engineers and physicists study quantum characteristics of ‘combs’ of light

The silicon carbide microrings developed by the Vučković Lab, as seen through a scanning electron microscope at the Stanford Nano Shared Facilities. 
Image credit: Vučković Lab

Frequency microcombs are specialized light sources that can function as light-based clocks, rulers and sensors to measure time, distance and molecular composition with high precision. New Stanford research presents a novel tool for investigating the quantum characteristics of these sources.

Unlike the jumble of frequencies produced by the light that surrounds us in daily life, each frequency of light in a specialized light source known as a “soliton” frequency comb oscillates in unison, generating solitary pulses with consistent timing.

Each “tooth” of the comb is a different color of light, spaced so precisely that this system is used to measure all manner of phenomena and characteristics. Miniaturized versions of these combs – called microcombs – that are currently in development have the potential to enhance countless technologies, including GPS systems, telecommunications, autonomous vehicles, greenhouse gas tracking, spacecraft autonomy and ultra-precise timekeeping.

Theropod dinosaur jaws became stronger as they evolved

Life reconstruction of the Late Cretaceous Iren Dabasu Formation fauna, showing theropod dinosaurs of various diets
Credit: Gabriel Ugueto

Theropod dinosaurs evolved more robust jaws through time allowing them to consume tougher food, a new study reveals.

Researchers used digital modelling and computer simulation to uncover a common trend of jaw strengthening in theropods - expanding the rear jaw portion in all groups, as well as evolving an upturned jaw in carnivores and a downturned jaw in herbivores.

Publishing their findings today in Current Biology, scientists revealed that biomechanical analysis showed these form changes made jaws mechanically more stable when biting - minimizing the chance of bone fracture.

The international team, led by scientists at the University of Birmingham, created digital models of more than 40 lower jaws from five different theropod dinosaur groups, including typical carnivores like Tyrannosaurus and Velociraptor, and lesser-known herbivores like ornithomimosaurs, therizinosaurs and oviraptorosaurs.

Fion Waisum Ma, PhD researcher at the University of Birmingham, who led the study, said: “Although theropod dinosaurs are always depicted as fearsome predators in popular culture, they are in fact very diverse in terms of diets. It is interesting to observe the jaws becoming structurally stronger over time, in both carnivores and herbivores. This gives them the capacity to exploit a wider range of food items.

Shark antibody-like proteins neutralize COVID-19 virus, help prepare for future coronaviruses

“What we’re doing is preparing an arsenal of shark VNAR therapeutics that could be used down the road for future SARS outbreaks," says researcher Aaron LeBeau.
Photo by: Bryce Richter

Small, unique antibody-like proteins known as VNARs — derived from the immune systems of sharks — can prevent the virus that causes COVID-19, its variants, and related coronaviruses from infecting human cells, according to a new study published Dec. 16.

The new VNARs will not be immediately available as a treatment in people, but they can help prepare for future coronavirus outbreaks. The shark VNARs were able to neutralize WIV1-CoV, a coronavirus that is capable of infecting human cells but currently circulates only in bats, where SARS-CoV-2, the virus that causes COVID-19, likely originated.

Developing treatments for such animal-borne viruses ahead of time can prove useful if those viruses make the jump to people.

“The big issue is there are a number of coronaviruses that are poised for emergence in humans,” says Aaron LeBeau, a University of Wisconsin–Madison professor of pathology who helped lead the study. “What we’re doing is preparing an arsenal of shark VNAR therapeutics that could be used down the road for future SARS outbreaks. It’s a kind of insurance against the future.”

Extreme weather changes predicted by unprecedented model simulations

California fire. (Photo credit: Patrick Perkins via Unsplash)

There is growing public awareness that climate change will impact society not only through changes in mean temperatures and rainfall over the 21st century, but also in the occurrence of more pronounced extreme events, and more generally in natural variability in the Earth system. Such changes could also have large impacts on vulnerable ecosystems in both terrestrial and marine habitats.

A team of researchers including Malte Stuecker from the University of Hawaiʻi at Mānoa School of Ocean and Earth Science and Technology (SOEST), explored projected future changes in climate and ecosystem variability and reported that the impact of climate change is apparent in nearly all aspects of climate variability. The study, led by the IBS Center for Climate Physics (ICCP) at Pusan National University in South Korea and published in Earth System Dynamics, emphasized that the impacts range from temperature and rainfall extremes over land to increased number of fires in California, to changes in bloom amplitude for phytoplankton in the North Atlantic Ocean.

Model simulations over 250 years

The team conducted a set of 100 global Earth system model simulations over 1850–2100, working with a “business-as-usual” scenario for relatively strong emissions of greenhouse gases over the 21st century. The runs were given different initial conditions, and, by virtue of the butterfly effect (a property of chaotic systems by which small changes in initial conditions can lead to large-scale and unpredictable variation in the future state of the system), they were able to represent a broad envelope of possible climate states over 1850-2100, enabling sophisticated analyses of changes in the variability of the Earth system over time.