An AI model reveals how the body’s defense system recognizes skin cancer

Boosting the body’s own defense system has proven to be a particularly effective therapy for skin cancer.
Photo credit: National Cancer Institute

The artificial intelligence model could be utilized to enable more effective care for skin cancer patients and could lead to similar breakthroughs in the diagnosis and treatment of other cancers.

Researchers from the University of Helsinki, HUS Comprehensive Cancer Center, Aalto University and Stanford University have developed an artificial intelligence model that predicts which skin cancer patients will benefit from a treatment that activates the immune defense system. In practice, the AI model makes it possible to diagnose skin cancer with a blood test, determine the prognosis and target therapies increasingly accurately.

The skin cancer–related study was published in the esteemed Nature Communications journal.

The right medication for the right patient

Boosting the body’s own defense system has proven to be a particularly effective therapy for skin cancer. The problem with therapies that activate the immune system are the differences between patient groups: while some patients can be said to be cured, others gain no benefit from the treatment at all.

“Prior research has been unable to provide doctors with tools that would predict who will benefit from treatment that activates the defense system. The correct targeting of therapies is extremely important, since drug therapies are expensive and serious adverse effects fairly common,” says doctor and Doctoral Researcher Jani Huuhtanen from the University of Helsinki and Aalto University.

Scientists Improve Inexpensive Perovskite Photocells

Simulated atomic structure of perovskite after calcium doping.
Illustration: Danil Bukhvalov

UrFU scientists have found a way to protect perovskite solar cells based on lead-methylammonium iodide (a promising alternative to traditional silicon photovoltaic cells) from degradation by water, such as rain. They found that partial replacement of lead with other alkaline earth metals protects them from such degradation, and also increases the parts of the visible spectrum of radiation involved in the process of generating electrons. An article on the results of the study was published in the Journal of Solid State Chemistry. The research was financially supported by the Ministry of Education and Science of Russia under the Priority 2030 development program of Ural Federal University.

Perovskite solar cells based on lead-methylammonium iodide are superior to silicon cells in performance and ease of synthesis. They are also capable of effectively generating electricity in cloudy or foggy conditions, so they are ideal for use in Russia or countries with similar climates. However, a complete switch to perovskite solar panels is not possible due to a number of reasons causing instability of such photovoltaic cells.

One of the causes of instability is that the compound is unstable to contact with water or other organic solvents. If it rains on the photocell, the compound begins to degrade rapidly, destroying its structure. Scientists determined that replacing lead with metals such as calcium, barium, or strontium would protect the compound from rapid degradation.

Graphene Boosts Flexible and Wearable Electronics

At 200 times stronger than steel, graphene has been hailed as a super material of the future since its discovery in 2004. The ultrathin carbon material is an incredibly strong electrical and thermal conductor, making it a perfect ingredient to enhance semiconductor chips found in many electrical devices.

But while graphene-based research has been fast-tracked, the nanomaterial has hit roadblocks: in particular, manufacturers have not been able to create large, industrially relevant amounts of the material. New research from the laboratory of Nai-Chang Yeh, the Thomas W. Hogan Professor of Physics, is reinvigorating the graphene craze.

In two new studies, the researchers demonstrate that graphene can greatly improve electrical circuits required for wearable and flexible electronics such as smart health patches, bendable smartphones, helmets, large folding display screens, and more.

In one study, published in ACS Applied Materials & Interfaces, the researchers grew graphene directly onto thin two-dimensional copper lines commonly used in electronics. The results showed that the graphene not only improved the lines' conducting properties but also protected the copper-based structures from usual wear and tear. For instance, they showed that graphene-coated copper structures could be folded 200,000 times without damage, as compared to the original copper structures, which started cracking after 20,000 folds. The results demonstrate that graphene can help create flexible electronics with longer lifetimes.

How farmers could fertilize more efficiently

A scheme showing the relationships of biological nitrification inhibition in the rhizisphere, improved nitrogen use efficiency and plant productivity, resistance, yield and quality.
Credit: Wolfram Weckwerth

Crops can directly contribute to improved nitrogen fertilization efficiency and reduced greenhouse gas emissions in agriculture

Nitrous oxide is a powerful greenhouse gas. Its global warming potential can be up to 300 times that of CO2 over a 100-year period. Globally, more than half of man-made nitrogen oxide emissions come from agriculture. A reduction in the nitrogen fertilizer used and an improvement in the nitrogen use efficiency of crops are therefore important measures in climate protection. An international team, coordinated by the Vienna Metabolomics Center (VIME) of the University of Vienna, is now presenting a new concept in the scientific journal "Trends in Plant Science" with which the efficiency of nitrogen fertilization is increased and the emission of nitrogen oxide (N2O) reduced.

The main goal of these new studies, building on many years of research, is to offer farmers a better economical alternative, where they can use crop plant derived biological inhibitors instead of highly polluting chemical fertilizers. An important task of the research is to better understand the complex root-soil microbiome ecosystem and to develop technological platforms that can use a root-soil balance for sustainable next-generation agriculture. The international team led by the University of Vienna has now taken an important step in this direction.

Engineering Duckweed to Produce Oil for Biofuels, Bioproducts

Brookhaven biochemists engineered duckweed, an aquatic plant, to produce large quantities of oil. If scaled up the approach could produce sustainable bio-based fuel without competing for high-value croplands while also potentially cleaning up agricultural wastewater.
Credit: Brookhaven National Laboratory

Scientists at the U.S. Department of Energy’s Brookhaven National Laboratory and collaborators at Cold Spring Harbor Laboratory (CSHL) have engineered duckweed to produce high yields of oil. The team added genes to one of nature’s fastest growing aquatic plants to “push” the synthesis of fatty acids, “pull” those fatty acids into oils, and “protect” the oil from degradation. As the scientists explain in a paper published in Plant Biotechnology Journal, such oil-rich duckweed could be easily harvested to produce biofuels or other bioproducts.

The paper describes how the scientists engineered a strain of duckweed, Lemna japonica, to accumulate oil at close to 10 percent of its dry weight biomass. That’s a dramatic, 100-fold increase over such plants growing in the wild—with yields more than seven times higher than soybeans, today’s largest source of biodiesel.

“Duckweed grows fast,” said Brookhaven Lab biochemist John Shanklin, who led the team. “It has only tiny stems and roots—so most of its biomass is in leaf-like fronds that grow on the surface of ponds worldwide. Our engineering creates high oil content in all that biomass.

“Growing and harvesting this engineered duckweed in batches and extracting its oil could be an efficient pathway to renewable and sustainable oil production,” he said.

It’s raining harder in the U.S.

Just like the old adage says: When it rains, it pours.

That turns out to be increasingly true for much of the United States, according to Northwestern University researchers.

In a new study, researchers compared observed rainfall from two climatologically distinct time periods and across 17 different climate regions in the U.S. They found that when it’s rained in recent decades, it’s rained more. In most regions, the intensity of the rainfall has shifted from lighter to more moderate and often heavy deluges.

When it rained east of the Rocky Mountains in recent decades, about 5% more precipitation fell. When it rained over the Pacific Coast or Rocky Mountains, however, no intensity changes were observed. Climate model simulations have previously predicted increases in precipitation intensity, particularly during extreme events, but the Northwestern study examined historically observed precipitation data across all intensities — and found a systematic shift in precipitation intensity in many parts of the country.

The study was published in the Geophysical Research Letters.

50% of Earth’s coral reefs face climate change threat by 2035

Photo credit: joakant

Under a worst-case scenario, half of coral reef ecosystems worldwide will permanently face unsuitable conditions in just over a dozen years, if climate change continues unabated. That is one of the findings from new research published on October 11, in PLOS Biology by University of Hawaiʻi at Mānoa researchers. Unsuitable conditions will likely lead to the corals dying off and other marine life will struggle to survive due to disruptions in the food chain.

“While the negative impacts of climate change on coral reefs are well known, this research shows that they are actually worse than anticipated due to a broad combination of climate change-induced stressors,” said lead author Renee O. Setter, a doctoral student in the Department of Geography and Environment in the College of Social Sciences. “It was surprising to find that so many global coral reefs would be overwhelmed by unsuitable environmental conditions so soon due to multiple stressors.”

Using an ensemble of global climate change models, the researchers compared scenarios of five environmental stressors projected from the 1950s through the year 2100. These stressors included sea surface temperature, ocean acidification, tropical storms, land use and human population. From prior studies, threshold values for the stressors that led to unsuitable environmental conditions for coral reefs were identified.

Team uses digital cameras, machine learning to predict neurological disease

From left, Richard Sowers, Rachneet Kaur and Manuel Hernandez led the development of a new approach for identifying people with multiple sclerosis or Parkinson’s disease. Their method involves videotaping the hips and lower extremities of individuals walking on a treadmill and allowing a machine-learning algorithm to differentiate gait abnormalities associated with each of these neurological conditions.
Photo credit: Fred Zwicky

In an effort to streamline the process of diagnosing patients with multiple sclerosis and Parkinson’s disease, researchers used digital cameras to capture changes in gait – a symptom of these diseases – and developed a machine-learning algorithm that can differentiate those with MS and PD from people without those neurological conditions.

Their findings are reported in the IEEE Journal of Biomedical and Health Informatics.

The goal of the research was to make the process of diagnosing these diseases more accessible, said Manuel Hernandez, a University of Illinois Urbana-Champaign professor of kinesiology and community health who led the work with graduate student Rachneet Kaur and industrial and enterprise systems engineering and mathematics professor Richard Sowers.

Currently, patients must wait – sometimes for years – to get an appointment with a neurologist to make a diagnosis, Hernandez said. And people in rural communities often must travel long distances to a facility where their condition can be assessed. To be able to gather gait information using nothing more than a digital camera and have that data assessed online could allow clinicians to do a quick screening that sends to a specialist only those deemed likely to have a neurological condition.

Ink flows to meet surging demand for national security research

Student interns are introduced to Sandia National Laboratories’ superfuge by test operations engineer Orlando Abeyta during a tour. Several new agreements signed this year are expected to increase the numbers of students and faculty partnering with Sandia to support its growing national security workload.
Photo credit: Craig Fritz

The nation’s largest national laboratory is embarking on a major expansion of its network of academic partners to meet the surging demand for national security science and engineering.

This year, Sandia National Laboratories inked memoranda of understanding with Texas A&M University; the University of California, Berkeley; North Carolina State University and the University of Texas at El Paso. It is finalizing agreements with Arizona State University and the University of Washington. When those are signed, Sandia will have formal ties with 27 universities, including 13 minority serving institutions.

Work at Sandia, which is performed almost entirely for federal agencies, has been rising steadily. From fiscal year 2015 to fiscal year 2021, the Labs’ budget increased more than 50%, from $2.9 billion to $4.5 billion. Over the same period, the Labs increased its workforce by more than 25%, from 11,700 to 15,000.

But Sandia won’t meet its obligations just by hiring staff.

“Partnering with universities keeps Sandia science at the state of the art and enables us to do more research for our national security mission than we can on our sites alone,” said Diane Peebles, Sandia’s senior manager of academic programs.

Bristol researchers make important breakthrough in quantum computing

Researchers from the University of Bristol, quantum start-up, Phasecraft and Google Quantum AI have revealed properties of electronic systems that could be used for the development of more efficient batteries and solar cells.

The findings, published in Nature Communications today, describes how the team has taken an important first step towards using quantum computers to determine low-energy properties of strongly-correlated electronic systems that cannot be solved by classical computers. They did this by developing the first truly scalable algorithm for observing ground-state properties of the Fermi-Hubbard model on a quantum computer. The Fermi-Hubbard model is a way of discovering crucial insights into electronic and magnetic properties of materials.

Modeling quantum systems of this form has significant practical implications, including the design of new materials that could be used in the development of more effective solar cells and batteries, or even high-temperature superconductors. However, doing so remains beyond the capacity of the world’s most powerful supercomputers. The Fermi-Hubbard model is widely recognized as an excellent benchmark for near-term quantum computers because it is the simplest materials system that includes non-trivial correlations beyond what is captured by classical methods. Approximately producing the lowest-energy (ground) state of the Fermi-Hubbard model enables the user to calculate key physical properties of the model.

In the past, researchers have only succeeded in solving small, highly simplified Fermi-Hubbard instances on a quantum computer. This research shows that much more ambitious results are possible. Leveraging a new, highly efficient algorithm and better error-mitigation techniques, they successfully ran an experiment that is four times larger – and consists of 10 times more quantum gates – than anything previously recorded.