Tech

OAK BROOK, Ill. - Anxiety is associated with an increased rate of progression from mild cognitive impairment to Alzheimer's disease, according to a study being presented at the annual meeting of the Radiological Society of North America (RSNA).

Alzheimer's disease represents a major public health crisis worldwide. The number of deaths from the disease has more than doubled since 2000, and it is currently the fifth-leading cause of death among individuals over 65 in the U.S.

Many people with Alzheimer's disease first suffer from mild cognitive impairment, a decline in cognitive abilities like memory and thinking skills that is more rapid than normally associated with aging. Anxiety has been frequently observed in patients with mild cognitive impairment, although its role in disease progression is not well understood.

"We know that volume loss in certain areas of the brain is a factor that predicts progression to Alzheimer's disease," said study senior author Maria Vittoria Spampinato, M.D., professor of radiology at the Medical University of South Carolina (MUSC) in Charleston. "In this study, we wanted to see if anxiety had an effect on brain structure, or if the effect of anxiety was independent from brain structure in favoring the progression of disease."

The study group included 339 patients, average age of 72 years, from the Alzheimer's Disease Neuroimaging Initiative 2 cohort. Each person had a baseline diagnosis of mild cognitive impairment; 72 progressed to Alzheimer's disease while 267 remained stable.

The researchers obtained brain MRIs to determine the baseline volumes of the hippocampus and the entorhinal cortex, two areas important to forming memories. They also tested for the presence of the ApoE4 allele, the most prevalent genetic risk factor for Alzheimer's disease. Anxiety was measured with established clinical surveys.

As expected, patients who progressed to Alzheimer's disease had significantly lower volumes in the hippocampus and the entorhinal cortex and greater frequency of the ApoE4 allele. Most notably though, the researchers found that anxiety was independently associated with cognitive decline.

"Mild cognitive impairment patients with anxiety symptoms developed Alzheimer's disease faster than individuals without anxiety, independently of whether they had a genetic risk factor for Alzheimer's disease or brain volume loss," said study first author Jenny L. Ulber, a medical student at MUSC.

The link between anxiety symptoms and a faster progression to Alzheimer's disease presents an opportunity for improving the screening and management of patients with early mild cognitive impairment, the researchers said.

"We need to better understand the association between anxiety disorders and cognitive decline," Dr. Spampinato said. "We don't know yet if the anxiety is a symptom--in other words, their memory is getting worse and they become anxious--or if anxiety contributes to cognitive decline. If we were able in the future to find that anxiety is actually causing progression, then we should more aggressively screen for anxiety disorders in the elderly."

"The geriatric population is routinely screened for depression in many hospitals, but perhaps this vulnerable population should also be assessed for anxiety disorders," Ulber added. "Middle-aged and elderly individuals with high level of anxiety may benefit from intervention, whether it be pharmacological or cognitive behavioral therapy, with the goal of slowing cognitive decline."

The study was based on MRI scans done at one point in time. For future research, the team would like to study MRIs obtained after the initial scan to better understand the connection between anxiety and brain structure.

"We're now interested in looking at changes over time to see if anxiety has an effect one way or the other on how fast the brain damage progresses," Dr. Spampinato said. "We will also take a closer look at gender differences in the association between anxiety and cognitive decline."

When the words "artificial intelligence" (AI) come to mind, your first thoughts may be of super-smart computers, or robots that perform tasks without needing any help from humans. Now, a multi-institutional team including researchers from the National Institute of Standards and Technology (NIST) has accomplished something not too far off: They developed an AI algorithm called CAMEO that discovered a potentially useful new material without requiring additional training from scientists. The AI system could help reduce the amount of trial-and-error time scientists spend in the lab, while maximizing productivity and efficiency in their research.

The research team published their work on CAMEO in Nature Communications.

In the field of materials science, scientists seek to discover new materials that can be used in specific applications, such as a "metal that's light but also strong for building a car, or one that can withstand high stresses and temperatures for a jet engine," said NIST researcher Aaron Gilad Kusne.

But finding such new materials usually takes a large number of coordinated experiments and time-consuming theoretical searches. If a researcher is interested in how a material's properties vary with different temperatures, then the researcher may need to run 10 experiments at 10 different temperatures. But temperature is just one parameter. If there are five parameters, each with 10 values, then that researcher must run the experiment 10 x 10 x 10 x 10 x 10 times, a total of 100,000 experiments. It's nearly impossible for a researcher to run that many experiments due to the years or decades it may take, Kusne said.

That's where CAMEO comes in. Short for Closed-Loop Autonomous System for Materials Exploration and Optimization, CAMEO can ensure that each experiment maximizes the scientist's knowledge and understanding, skipping over experiments that would give redundant information. Helping scientists reach their goals faster with fewer experiments also enables labs to use their limited resources more efficiently. But how is CAMEO able to do this?

The Method Behind the Machine

Machine learning is a process in which computer programs can access data and process it themselves, automatically improving on their own instead of relying on repeated training. This is the basis for CAMEO, a self-learning AI that uses prediction and uncertainty to determine which experiment to try next.

As implied by its name, CAMEO looks for a useful new material by operating in a closed loop: It determines which experiment to run on a material, does the experiment, and collects the data. It can also ask for more information, such as the crystal structure of the desired material, from the scientist before running the next experiment, which is informed by all past experiments performed in the loop.

"The key to our experiment was that we were able to unleash CAMEO on a combinatorial library where we had made a large array of materials with all different compositions," said Ichiro Takeuchi, a materials science and engineering researcher and professor at the University of Maryland. In a usual combinatorial study, every material in the array would be measured sequentially to look for the compound with the best properties. Even with a fast measurement setup, that takes a long time. With CAMEO, it took only a small fraction of the usual number of measurements to home in on the best material.

The AI is also designed to contain knowledge of key principles, including knowledge of past simulations and lab experiments, how the equipment works, and physical concepts. For example, the researchers armed CAMEO with the knowledge of phase mapping, which describes how the arrangement of atoms in a material changes with chemical composition and temperature.

Understanding how atoms are arranged in a material is important in determining its properties such as how hard or how electrically insulating it is, and how well it is suited for a specific application.

"The AI is unsupervised. Many types of AI need to be trained or supervised. Instead of asking it to learn physical laws, we encode them into the AI. You don't need a human to train the AI," said Kusne.

One of the best ways to figure out the structure of a material is by bombarding it with X-rays, in a technique called X-ray diffraction. By identifying the angles at which the X-rays bounce off, scientists can determine how atoms are arranged in a material, enabling them to figure out its crystal structure. However, a single in-house X-ray diffraction experiment can take an hour or more. At a synchrotron facility where a large machine the size of a football field accelerates electrically charged particles at close to the speed of light, this process can take 10 seconds because the fast-moving particles emit large numbers of X-rays. This is the method used in the experiments, which were performed at the Stanford Synchrotron Radiation Lightsource (SSRL).

The algorithm is installed on a computer that connects to the X-ray diffraction equipment over a data network. CAMEO decides which material composition to study next by choosing which material the X-rays focus on to investigate its atomic structure. With each new iteration, CAMEO learns from past measurements and identifies the next material to study. This allows the AI to explore how a material's composition affects its structure and identify the best material for the task.

"Think of this process as trying to make the perfect cake," Kusne said. "You're mixing different types of ingredients, flour, eggs, or butter, using a variety of recipes to make the best cake." With the AI, it's searching through the "recipes" or experiments to determine the best composition for the material.

That approach is how CAMEO discovered the material ?Ge?_4 ?Sb?_6 ?Te?_(7,) which the group shortened to GST467. CAMEO was given 177 potential materials to investigate, covering a large range of compositional recipes. To arrive at this material, CAMEO performed 19 different experimental cycles, which took 10 hours, compared with the estimated 90 hours it would have taken a scientist with the full set of 177 materials.

The New Material

The material is composed of three different elements (germanium, antimony and tellurium, Ge-Sb-Te) and is a phase-change memory material, that is, it changes its atomic structure from crystalline (solid material with atoms in designated, regular positions) to amorphous (solid material with atoms in random positions) when quickly melted by applying heat. This type of material is used in electronic memory applications such as data storage. Although there are infinite composition variations possible in the Ge-Sb-Te alloy system, the new material GST467 discovered by CAMEO is optimal for phase-change applications.

Researchers wanted CAMEO to find the best Ge-Sb-Te alloy, one that had the largest difference in "optical contrast" between the crystalline and amorphous states. On a DVD or Blu-ray disc, for example, optical contrast allows a scanning laser to read the disc by distinguishing between regions that have high or low reflectivity. They found that GST467 has twice the optical contrast of ?Ge?_2 ?Sb?_2 ?Te?_5, a well-known material that's commonly used for DVDs. The larger contrast enables the new material to outperform the old material by a significant margin.

GST467 also has applications for photonic switching devices, which control the direction of light in a circuit. They can also be applied in neuromorphic computing, a field of study focused on developing devices that emulate the structure and function of neurons in the brain, opening possibilities for new kinds of computers as well as other applications such as extracting useful data from complex images.

CAMEO's Wider Applications

The researchers believe CAMEO can be used for many other materials applications. The code for CAMEO is open source and will be freely available for use by scientists and researchers. And unlike similar machine-learning approaches, CAMEO discovered a useful new compound by focusing on the composition-structure-property relationship of crystalline materials. In this way, the algorithm navigated the course of discovery by tracking the structural origins of a material's functions.

One benefit of CAMEO is minimizing costs, since proposing, planning and running experiments at synchrotron facilities requires time and money. Researchers estimate a tenfold reduction in time for experiments using CAMEO, since the number of experiments performed can be cut by one tenth. Because the AI is running the measurements, collecting data and performing the analysis, this also reduces the amount of knowledge a researcher needs to run the experiment. All the researcher must focus on is running the AI.

Another benefit is providing the ability for scientists to work remotely. "This opens up a wave of scientists to still work and be productive without actually being in the lab," said Apurva Mehta, a researcher at the SLAC National Accelerator Laboratory. This could mean that if scientists wanted to work on research involving contagious diseases or viruses, such as COVID-19, they could do so safely and remotely while relying on the AI to conduct the experiments in the lab.

For now, researchers will continue to improve the AI and try to make the algorithms capable of solving ever more complex problems. "CAMEO has the intelligence of a robot scientist, and it's built to design, run and learn from experiments in a very efficient way," said Kusne.

Durham, NC - A new treatment for atherosclerosis, commonly known as hardening of the arteries, may be on the horizon, according to a study released today in STEM CELLS Translational Medicine (SCTM). The study demonstrates how injecting mice with early outgrowth cells (EOCs), after first treating the cells with chemicals to activate a type of protein called liver x receptor (LXR), slows the development of this disease.

Atherosclerosis is a leading cause of heart attack, stroke and other cardiopulmonary disorders. It results when plaque buildup in the arteries causes them to narrow and blocks blood flow. Many researchers believe this plaque begins when an artery's inner lining, called the endothelium, is damaged. Since EOCs are a type of endothelial progenitor cell that contributes to vascular repair, this makes them a promising candidate for treating atherosclerosis and other cardiovascular diseases, too.

This study published in SCTM was conducted as a follow-up to an earlier investigation in which these researchers showed how LXRs, which are known to regulate inflammation and cholesterol in the body, play a crucial role in preventing cholesterol-induced defects in EOCs. "This time around, we wanted to see if activating LXR in EOCs could be beneficial in treating atherosclerosis," explained corresponding author Carolyn Cummins, Ph.D., a member of the University of Toronto's Leslie Dan Faculty of Pharmacy.

"Other animal studies had already shown that administration of EOCs promotes plaque stabilization and decreases its formation, partially through endothelial engraftment," she added. "However, those studies were all performed when the animals were in the later stages of atherosclerosis. We believe our current study is the first to explore EOC intervention in atherosclerosis' earlier stages."

The researchers began by differentiating EOCs from the bone marrow of wildtype (normal) mice and exposing the EOCs to a chemical called GW3965 hydrochloride, which is a potent activator of LXR, or a control vehicle (ethanol) for a period of seven days. They then injected each mouse with either the GW3965-treated EOCs, the conditioned media (CM) in which the EOCs had been cultivated or the control vehicle. Injections were given twice a week, over an eight-week period.

At the end of the treatments, results showed that LXR activation led to the secretion of factors that reduced binding of inflammatory cells to the endothelial cells, which in turn slowed the development of atherosclerosis, compared to the group that received the control vehicle only. This enhanced secretion occurred in both the EOC- and CM-injected animals, indicating that the secreted components alone were sufficient for the therapeutic benefit of EOCs. "Identifying the components of the secretome that mediate these positive effects of EOCs is a current area of focus and will potentially lead to new avenues to treat atherosclerosis," Dr. Cummins commented.

This multi-institutional team led by Dr. Cummins, with clinical colleagues at the University of Ottawa Heart Institute, also confirmed that, just as with the mouse-derived EOCs, EOCs derived from the blood of human coronary artery disease patients and pre-treated with the GW3965 hydrochloride LXR agonist produced similar results in cell culture. "While LXR activation in patients can cause unwanted side effects, this type of therapy of treating one's own cells in culture with this drug is a way to circumvent these problems," said first author Adil Rasheed, Ph.D.

"Further experiments are needed to examine the long-term efficacy and any potential toxicity prior to human studies; however, our findings suggest that treating patient-derived EOCs with LXR agonists before administering them to the patient could represent a novel therapy to lessen the effects of atherosclerosis and reduce plaque buildup," Dr. Cummins concluded.

"These early pre-clinical results are certainly encouraging and demonstrate the need to further pursue this therapy that could lead to a potential treatment for vascular diseases," said Anthony Atala, M.D., Editor-in-Chief of STEM CELLS Translational Medicine and director of the Wake Forest Institute for Regenerative Medicine. "We look forward to seeing this work continue."

New research has demonstrated how, in contrast to encroachment by the invasive alien tree species Prosopis julifora (known as `Mathenge` -in Kenya or `Promi` in Baringo), restoration of grasslands in tropical semi-arid regions can both mitigate the impacts of climate change and restore key benefits usually provided by healthy grasslands for pastoralists and agro-pastoralist communities.

A team of Kenyan and Swiss scientists, including lead author Ms.Purity Rima Mbaabu, affiliated to Kenya Forestry Research Institute, Institute for Climate Change and Adaptation of University of Nairobi and Chuka University and Dr Urs Schaffner from CABI's Swiss Centre in Delémont, assessed how invasion by P. julifora and the restoration of degraded grasslands affected soil organic carbon (SOC), biodiversity and fodder availability.

The study, published in Scientific Reports, revealed that degradation of grasslands in Baringo County, Kenya, has led to a loss of approximately 40% of SOC, the most important carbon pool in soils. These findings confirm that grassland degradation significantly contributes to the release of greenhouse gases and thus to climate change. The authors also showed that 30 years of grassland restoration replenished SOC to a soil depth of 1 metre at a rate of 1.4% per year and also restored herbaceous biomass to levels of pristine grasslands, while plant biodiversity remained low. Invasion by P. julifora, on the other hand, increased SOC primarily in the upper 30cm of the soil and suppressed herbaceous vegetation.

Grasslands comprise 40% of the Earth's natural vegetation and contain a substantial amount of the world's SOC. In supporting the livelihoods of over one billion people worldwide, they provide a home to a wide variety of animals and plants and support other ecosystem services such as the regulation and storage of water flows, forage for livestock production and tourism.

However, grasslands are under severe threat from degradation, conversion to other land uses as well as encroachment by P. julifora which has accounted for the disappearance of over 30% of grasslands in Baringo County.

The scientists say that efforts to reverse land degradation in Baringo County and other parts of Sub-Saharan Africa should consider restoration of historical grasslands and their associated ecosystem services. To meet the needs of wood, planting of native trees should be promoted on land which historically used to be forested.

Ms. Mbaabu said, “The importance of managing grasslands to optimise carbon sequestration for climate change mitigation is widely recognised. Soils are the largest terrestrial carbon reservoir containing more carbon than the vegetation and the atmosphere combined.

"Yet, soil organic carbon, which makes up about two thirds of global soil carbon, is sensitive to land degradation with significant negative consequences for soil quality and productivity and an exacerbation of greenhouse gas emissions."

Prof Daniel Olago from the Institute for Climate Change and Adaptation of the University of Nairobi emphasized that: "Halting and reversing land degradation and restoring degraded soils and their associated services in rangelands is essential for climate change mitigation and for ensuring resilient agro-ecological systems that underpin sustainable rural livelihoods and that meet medium to long-term sustainable development objectives such as the 2030 global sustainable development goals (SDGs) and Africa’s Agenda 2063. The current choices on how to manage our soil resources will have wide-ranging consequences for human wellbeing for generations to come.”

Dr Schaffner said, "Our results provide evidence that the replenishment of the soil organic carbon stocks through restoration of degraded grasslands can be achieved within 20-30 years and does not lead to multiple trade-offs with fodder for livestock and other ecosystem services.

"The extent to which grassland restoration will increase primary productivity and soil organic carbon, however, will depend on socio-economic factors including land tenure systems and enforcement of land use rights affecting the level and type of grazing management."

Prosopis was introduced into Baringo County in the early 1980s through the Fuelwood Afforestation Extension Project which aimed to mitigate firewood scarcity and desertification. However, soon after its introduction Prosopis started to escape from the plantations and to invade the surrounding ecosystems. Today, the costs of Prosopis and other invasive trees and shrubs, such as Lantana camara and Chromolaena odorata, in South Africa alone are estimated to cost USD$1 billion a year.

WEST LAFAYETTE, Ind. - A new therapy for influenza virus infections that may also prove effective against many other pathogenic virus infections, including HIV and COVID-19, has been developed by Purdue University scientists.

In an average year, more than 2 million people in the United States are hospitalized with the flu, and 30,000 to 80,000 of them die from the flu or related complications.

The Purdue team's work is detailed in Nature Communications and uses a targeted therapy approach against the virus infections.

"We target all of the antiviral drugs we develop specifically to virus-infected cells," said Philip S. Low, the Purdue Ralph C. Corley Distinguished Professor of Chemistry. "That way, we treat the diseased cells without harming healthy cells. We use this capability to deliver immune-activating drugs selectively into flu-infected cells. There is also the potential that this therapy will prove efficacious in people infected with COVID-19."

The flu virus, like many other pathogenic viruses, exports its proteins into its host cell surface and then buds off nascent viruses in the process of spreading to adjacent host cells. Because these exported viral proteins are not present in the membranes of healthy host cells, the Purdue team has exploited the presence of viral proteins in infected cells by designing homing molecules that target drugs specifically to virus-infected cells, thereby avoiding the collateral toxicity that occurs when antiviral drugs are taken up by uninfected cells.

"We chose to start our tests with influenza virus because the results can often be applied to other enveloped viruses," Low said. "Our lab tests show that our process works in influenza infected mice that are inoculated with 100 times the lethal dose of virus."

Low said the new therapy may prove effective against other pathogenic virus infections such as hepatitis B, HIV and respiratory syncytial virus (RSV).

In a noisy room with many speakers, hearing aids can suppress background noise, but they have difficulties isolating one voice - that of the person you're talking to at a party, for instance. KU Leuven researchers have now addressed that issue with a technique that uses brainwaves to determine within one second whom you're listening to.

Having a casual conversation at a cocktail party is a challenge for someone with a hearing aid, says Professor Tom Francart from the Department of Neurosciences at KU Leuven: "A hearing aid may select the loudest speaker in the room, for instance, but that is not necessarily the person you're listening to. Alternatively, the system may take into account your viewing direction, but when you're driving a car, you can't look at the passenger sitting next to you."

Researchers have been working on solutions that take into account what the listener wants. "An electroencephalogram (EEG) can measure brainwaves that develop in response to sounds. This technique allows us to determine which speaker someone wants to listen to. The system separates the sound signals produced by different speakers and links them to the brainwaves. The downside is that you have to take into account a delay of ten to twenty seconds to get it right with reasonable certainty."

Artificial intelligence to speed up the process

A new technique makes it possible to step up the pace, Professor Alexander Bertrand from the Department of Electrical Engineering at KU Leuven continues: "Using artificial intelligence, we found that it is possible to directly decode the listening direction from the brainwaves alone, without having to link them to the actual sounds."

"We trained our system to determine whether someone is listening to a speaker on their left or their right. Once the system has identified the direction, the acoustic camera redirects its aim, and the background noise is suppressed. On average, this can now be done within less than one second. That's a big leap forward, as one second constitutes a realistic timespan to switch from one speaker to the other."

From lab to real life

However, it will take at least another five years before we have smart hearing aids that work with brainwaves, Professor Francart continues. "To measure someone's brainwaves in the lab, we make them wear a cap with electrodes. This method is obviously not feasible in real life. But research is already being done into hearing aids with built-in electrodes."

The new technique will be further improved as well, PhD student Simon Geirnaert adds. "We're already conducting further research, for instance into the problem of combining multiple speaker directions at once. The current system simply chooses between two directions. While first experiments show that we can expand that to other possible directions, we need to refine our artificial intelligence system by feeding the system with more brainwave data from users who are also listening to speakers from other directions."

We rely on water to quench our thirst and to irrigate bountiful farmland. But what do you do when that once pristine water is polluted with wastewater from abandoned copper mines?

A promising solution relies on materials that capture heavy metal atoms, such as copper ions, from wastewater through a separation process called adsorption. But commercially available copper-ion-capture products still lack the chemical specificity and load capacity to precisely separate heavy metals from water.

Now, a team of scientists led by the Department of Energy's Lawrence Berkeley National Laboratory (Berkeley Lab) has designed a new material - called ZIOS (zinc imidazole salicylaldoxime) - that targets and traps copper ions from wastewater with unprecedented precision and speed. In a paper recently published in the journal Nature Communications, the scientists say that ZIOS offers the water industry and the research community the first blueprint for a water-remediation technology that scavenges specific heavy metal ions with a measure of control at the atomic level that far surpasses the current state of the art.

"ZIOS has a high adsorption capacity and the fastest copper adsorption kinetics of any material known so far - all in one," said senior author Jeff Urban , who directs the Inorganic Nanostructures Facility in Berkeley Lab's Molecular Foundry.

This research embodies the Molecular Foundry's signature work - the design, synthesis, and characterization of materials that are optimized at the nanoscale (billionths of a meter) for sophisticated new applications in medicine, catalysis, renewable energy, and more.

For example, Urban has focused much of his research on the design of superthin materials from both hard and soft matter for a variety of applications, from cost-effective water desalination to self-assembling 2D materials for renewable energy applications.

"And what we tried to mimic here are the sophisticated functions performed by nature," such as when proteins that make up a bacterial cell select certain metals to regulate cellular metabolism, said lead author Ngoc Bui, a former postdoctoral researcher in Berkeley Lab's Molecular Foundry who is now an assistant professor in chemical, biological, and materials engineering at the University of Oklahoma.

"ZIOS helps us to choose and remove only copper, a contaminant in water that has been linked to disease and organ failure, without removing desirable ions, such as nutrients or essential minerals," she added.

Such specificity at the atomic level could also lead to more affordable water treatment techniques and aid the recovery of precious metals. "Today's water treatment systems are 'bulk separation technologies' - they pull out all solutes, irrespective of their hazard or value," said co-author Peter Fiske, director of the National Alliance for Water Innovation (NAWI) and the Water-Energy Resilience Institute (WERRI) at Berkeley Lab. "Highly selective, durable materials that can capture specific trace constituents without becoming loaded down with other solutes, or falling apart with time, will be critically important in lowering the cost and energy of water treatment. They may also enable us to 'mine' wastewater for valuable metals or other trace constituents."

Scavenging heavy metals at the atomic level

Urban, Bui, and co-authors report that ZIOS crystals are highly stable in water - up to 52 days. And unlike metal-organic frameworks, the new material performs well in acidic solutions with the same pH range of acid mine wastewater. In addition, ZIOS selectively captures copper ions 30-50 times faster than state-of-the-art copper adsorbents, the researchers say.

These results caught Bui by surprise. "At first I thought it was a mistake, because the ZIOS crystals have a very low surface area, and according to conventional wisdom, a material should have a high specific surface area, like other families of adsorbents, such as metal-organic frameworks, or porous aromatic frameworks, to have a high adsorption capacity and an extremely fast adsorption kinetic," she said. "So I wondered, 'Perhaps something more dynamic is going on inside the crystals.'"

To find out, she recruited the help of co-lead author Hyungmook Kang to perform molecular dynamics simulations at the Molecular Foundry. Kang is a graduate student researcher in the Urban Lab at Berkeley Lab's Molecular Foundry and a Ph.D. student in the department of mechanical engineering at UC Berkeley.

Kang's models revealed that ZIOS, when immersed in an aqueous environment, "works like a sponge, but in a more structured way," said Bui. "Unlike a sponge that absorbs water and expands its structure in random directions, ZIOS expands in specific directions as it adsorbs water molecules."

X-ray experiments at Berkeley Lab's Advanced Light Source revealed that the material's tiny pores or nanochannels - just 2-3 angstroms, the size of a water molecule - also expand when immersed in water. This expansion is triggered by a "hydrogen bonding network," which is created as ZIOS interacts with the surrounding water molecules, Bui explained.

This expansion of the nanochannels allows water molecules carrying copper ions to flow at a larger scale, during which a chemical reaction called "coordination bonding" between copper ions and ZIOS takes place.

Additional X-ray experiments showed that ZIOS is highly selective to copper ions at a pH below 3 - a significant finding, as the pH of acidic mine drainage is typically a pH of 4 or lower.

Furthermore, the researchers said that when water is removed from the material, its crystal lattice structure contracts to its original size within less than 1 nanosecond (billionth of a second).

Co-author Robert Kostecki attributed the team's success to their interdisciplinary approach. "The selective extraction of elements and minerals from natural and produced waters is a complex science and technology problem," he said. "For this study, we leveraged Berkeley Lab's unique capabilities across nanoscience, environmental sciences, and energy technologies to transform a basic materials sciences discovery into a technology that has great potential for real-world impact." Kostecki is the director of the Energy Storage and Distributed Resources Division in Berkeley Lab's Energy Technologies Area, and Materials and Manufacturing R&D topic area lead in NAWI.

The researchers next plan to explore new design principles for the selective removal of other pollutants.

"In water science and the water industry, numerous families of materials have been designed for decontaminating wastewater, but few are designed for heavy metal removal from acidic mine drainage. We hope that ZIOS can help to change that," said Urban.

Evapotranspiration (ET), the phenomenon of the loss of water to the atmosphere from the land surface through evaporation and transpiration, is an important part of water and energy cycles. ET is a key variable used in applications such as drought monitoring, climate prediction, water resources management, and agricultural planning. The importance of a high-resolution ET estimation has also been well identified for agricultural applications where site-specific monitoring is needed, which is highly relevant for a country like Nepal that relies on agriculture for the majority share of its GDP and employment workforces.

Due to its importance, Prof. Weiqiang MA from the Institute of Tibetan Plateau Research, Chinese Academy of Sciences, and his group, used the METRIC model to simulate and evaluate the surface evapotranspiration in Nepal. The results have been recently published in Atmospheric and Oceanic Science Letters.

According to the study by Prof. Ma and colleagues, the evapotranspiration simulated by the METRIC model has a smaller error than the actual observation under the complex underlying surface in Nepal, which illustrates good applicability of this model.

"Meanwhile, we have increased the resolution of the simulation from 5 km to 30 m without affecting the accuracy. High-resolution ET estimation can be used for agricultural planning and monitoring in Nepal," states Prof. Ma.

Besides, the remote sensing-based METRIC model has been implemented for the estimation of land surface ET in a topographically diverse region, i.e., Nepal. The obtained evapotranspiration results from the model were found to be close to the field measurement data. Therefore, the model is applicable in Nepal, where the landscape within a small region varies from flat plains to high land. Furthermore, Prof. Ma and his team also studied the elevation-wise variation from 57 m to 7782 m above mean sea level. The pattern analysis of estimation of ET revealed its inverse relation to elevation in general over the study area.

"Compared to previous work using the resolution of 5 km, our study is the first in Nepal that has utilized such fine spatial resolution data, i.e., 30 m, afforded by Landsat 8 without compromising the accuracy," adds Prof. Ma. "ET profiling, such as across elevations in a mountainous region such as Nepal helps in irrigation management and large-scale soil moisture assessment for agriculture, which is important because many people in Nepal still rely on agriculture for their daily livelihoods," concludes Prof. Ma.

For decades, scientists have known that plants protect themselves from the devastation of hungry caterpillars and other plant-munching animals through sophisticated response systems, the product of millions of years of evolution.

The biological mechanisms underlying this attack-counter defense paradigm have been vigorously pursued by plant biologists given that such details will help unlock a trove of new strategies for improved plant health. From countering crop pest damage to engineering more robust global food webs, such information is valuable for ensuring sustainable and reliable yields.

Now, researchers at the University of California San Diego and their colleagues have identified the first key biological switch, or receptor, that sounds an alarm in plants specifically when herbivores attack. The discovery is described in the online publication of the Proceedings of the National Academy of Sciences.

Animals such as humans, cows and insects are heterotrophs that derive their energy either directly or indirectly through the consumption of autotrophs, such as photosynthetic plants. This basic foundation shapes biological interactions across planet Earth. More than 30 years ago plant biologists came to understand that plants can sense an attack from herbivorous animals in a way that is distinct from damage caused by hail storms or falling tree branches.

Similar to how human immune defenses counter an attack from viruses, plants have been shown to respond to danger from plant-eating animals through an intricate immune system of receptors. Using a method of pinpointing genetic variants, called forward genetics, research led by Adam Steinbrenner, Alisa Huffaker and Eric Schmelz of UC San Diego's Division of Biological Sciences enabled discovery the inceptin receptor, termed INR, in bean plants. The receptor detects conserved plant protein fragments accidently released as digestive products during caterpillar munching, thereby enabling plant recognition of attack.

"INR represents the first documented mechanism of a plant cell surface receptor responsible for perceiving animals," said Schmelz, whose work was accomplished by deconstructing and leveraging the active evolutionary arms race between plants and herbivores. "Our work provides some of the earliest defined mechanistic insights into the question of how plants recognize different attacking herbivores and activate immunity to animals. It is a fundamental question in biology that has been pursued for 30 years."

Beyond beans, the finding raises interest in using INR, and potentially other receptors that remain to be discovered, as a way to boost defenses in essential agricultural crops.

"A key lesson is that plant perception mechanisms for herbivores can be precisely defined and moved into crops to afford enhanced protection," said Schmelz. "We have shown one example but it's clear that hundreds if not thousands of opportunities exist to identify and stack key traits to enhance crop plant immunity to herbivores."

Forest-dwelling bacteria known for forming slimy swarms that prey on other microbes can also cooperate to construct mushroom-like survival shelters known as fruiting bodies when food is scarce. Now a team at Princeton University has discovered the physics behind how these rod-shaped bacteria, which align in patterns like those on fingerprint whorls and liquid crystal displays, build the layers of these fruiting bodies. The study was published in Nature Physics.

"In some ways, these bacteria are teaching us new kinds of physics," said Joshua Shaevitz, professor of physics and the Lewis-Sigler Institute for Integrative Genomics. "These questions exist at the intersection of physics and biology. And you need to understand both to understand these organisms."

Myxococcus xanthus, or Myxo for short, is a bacterial species capable of surprisingly cooperative behaviors. For example, large numbers of Myxo cells come together to hunt other bacteria by swarming toward their prey in a single undulating mass.

When food is scarce, however, the rod-like cells stack atop one another to form squishy growths called fruiting bodies, which are hideaways in which some of the Myxo cells transform into spores capable of rebooting the population when fresh nutrients arrive. But until now, scientists haven't understood how the rods acquire the ability to begin climbing on top of each other to build the droplet-like structures.

To find out more about how these bacteria behave, the researchers set up a microscope capable of tracking Myxo's actions in three dimensions. The scientists recorded videos of the rod-shaped microbes, which pack closely together like stampeding wildebeest, rushing across the microscope dish in swaths that swirl around each other, forming fingerprint-like patterns.

When two swaths meet, the researchers observed, the point of intersection was exactly where the new layer of cells started to form. The bacteria started to pile up and created a situation where the only direction to go was up.

"We found that these bacteria are exploiting particular points of the cell alignment where stresses build that enable the colony to construct new cell layers, one on top of the other," said Ricard Alert, a postdoctoral research fellow in the Princeton Center for Theoretical Science and one of the study's co-first authors. "And that's ultimately how this colony responds to starvation."

Researchers call the points where the massing cells collide "topological defects," a term that refers to the mathematics that describe these singular points. Topology is the branch of mathematics that finds similarities between objects such as teacups and donuts, because one can be stretched or deformed into the other.

"We call these points topological because if you want to get rid of a single one of these defects, you cannot do it by a smooth transformation - you cannot just perturb the alignment of the cells to get rid of that point where alignment is lost," Alert said. "Topology is about what you can and cannot do via smooth transformations in mathematics."

Myxo bacterial cells behave much like liquid crystals, the fluids found in smartphone screens, which are made of rod-shaped molecules. Unlike passive liquid crystals, however, Myxo rods are alive and can crawl. The bacteria most likely have evolved to take advantage of both passive and active factors to build the fruiting bodies, the researchers said.

Katherine Copenhagen, associate research scholar in the Lewis-Sigler Institute, and a co-first author on the study, took videos of the cells under the microscope and analyzed the results. She said that at first the team was not sure what they were looking at.

"We were trying to study layer formation in bacteria to find out how these cells build these droplets, and we had just gotten a new microscope, so I put a sample of the bacteria from another project that had nothing to do with layer formation under the microscope and imaged it for a few hours," Copenhagen said. "The next time our group got together, I said 'I have this video, so let's take a look at it.' And we were mesmerized by what we saw."

The combination of physics and biology training among the researchers enabled them to recognize new theoretical insights into how the vertical layers form. "It says something about the value of the collaborative culture at Princeton," said Ned Wingreen, the Howard A. Prior Professor in the Life Sciences, professor of molecular biology and the Lewis-Sigler Institute. "We chat with each other and share crazy ideas and show interesting data to each other."

"A moment that I remember quite vividly," Alert said, "is watching these videos at the very beginning of this project and starting to realize, wait, do layers form exactly where the topological defects are? Could it be true?" To explore the results, he followed up the studies by confirming them with numerical and analytical calculations.

"The initial realization that came just by watching these movies, that was a cool moment," he said.

WASHINGTON --- Immune-system T cells have been reprogrammed into regenerative stem cell-like memory (TSCM) cells that are long-lived, highly active "super immune cells" with strong antitumor activity, according to new research from Georgetown Lombardi Comprehensive Cancer Center.

The reprogramming involves a novel approach the researchers developed that inhibits the activity of proteins known as MEK1/2. Currently, several MEK inhibitors are used to effectively treat melanoma, but this study demonstrates that MEK inhibitors don't just target certain types of cancer cells, but rather, more broadly, reprogram T cells to fight many types of cancer.

The finding appears November 23, 2020, in Nature Immunology.

"Although immunotherapies have improved survival for cancer patients over recent years, survival rates remain sub-optimal. Therefore, there is an urgent need to develop novel, more effective anti-cancer immunotherapies," says Samir N. Khleif, MD, director of The Jeannie and Tony Loop Immuno-Oncology Laboratory and head of the team that conducted this research. "Our research shows that using drugs that have already been approved for human use may significantly enhance currently available immune therapeutic approaches, thereby leading to better and more durable anti-cancer responses."

The researchers performed experiments with human cells in the lab and then confirmed the effects of such an approach in mice. The investigators were able to not only identify a novel strategy to reprogram T cells into TSCM cells by using MEK1/2 inhibition, they were able to identify a novel molecular mechanism by which the TSCMs were induced.

The scientists found that reprograming T cells into TSCM can significantly improve T cell therapies for cancer patients. T cell therapy is a process that is widely used in specific cancers and in clinical trials, where immune-system T cells are separated out from a patient's blood, engineered and expanded with special tumor-targeting capabilities and infused back into the patient to fight cancer. In their experiments, human T cells were reprogrammed with MEK inhibitors into TSCM; additionally, when treating mice with MEK inhibitors, the reprogramming of T cells was also found to induce effective TSCMs.

"Stem cell research has played a vital role this century in enhancing the progress against many diseases. Recent public and private support for stem cell therapy is very gratifying," says Khleif. "Having stem cell research-specific funding from both governmental and private funders will greatly help accelerate the development of this under-utilized area of research."

Now that MEK inhibitors have been shown to enhance an anti-tumor immune response, the researchers are starting to look into designing clinical trials to test their research approach in cancer patients. "Our approach is quite novel and we're anxious to see it put to use in the clinical arena as soon as possible," concludes Khleif.

HOUSTON -- Researchers at The University of Texas MD Anderson Cancer Center have developed a novel targeted therapy, called POMHEX, which blocks critical metabolic pathways in cancer cells with specific genetic defects. Preclinical studies found the small-molecule enolase inhibitor to be effective in killing brain cancer cells that were missing ENO1, one of two genes encoding the enolase enzyme.

The study results, published today in Nature Metabolism, provide proof of principle for a treatment strategy known as collateral lethality, in which an important protein is lost through genetic deletion as a bystander near a tumor suppressor gene, and a redundant protein is blocked therapeutically.

"Collateral lethality could expand the scope of precision oncology beyond activated oncogenes, and allow targeting of genomic deletions, largely considered un-actionable," said corresponding author Florian Muller, Ph.D., assistant professor of Cancer Systems Imaging and Neuro-Oncology. "Our work provides proof of principle that this approach can actually work with a drug in animal models."

Enolase is an essential enzyme involved in glycolysis, a metabolic pathway that is elevated in many cancers to fuel their increased cell growth. Two genes, ENO1 and ENO2, encode slightly different but redundant versions of enolase, and several cancers, such as glioblastoma, are missing the ENO1 gene because of chromosomal loss. This leaves the cancer cells with only ENO2 to continue glycolysis, making them highly sensitive to enolase inhibitors, Muller explained.

Therapies that target both forms of enolase have previously been developed, but blocking ENO1 can have unwanted side effects in normal cells. Targeting ENO2 specifically is attractive because it allows for the selective treatment of cancer cells missing ENO1.

The research team therefore worked to generate an enolase inhibitor, called HEX, that preferentially targets ENO2 over ENO1. To improve the drug's ability to enter cells, the team created the prodrug POMHEX, which is biologically inactive until it is metabolized into HEX within cells.

In cancer cell lines lacking ENO1, treatment with POMHEX blocked glycolysis, inhibited cell growth and stimulated cell death. Conversely, treatment of cells with normal ENO1 showed minimal effects.

Further, in animal models of ENO1-deficient tumors, both HEX and POMHEX treatment was well- tolerated and effectively blocked tumor growth relative to controls, with some instances of complete tumor eradication. Taking the work one step further, the team demonstrated that the therapeutically effective dose could be safely given in multiple models, suggesting favorable future translation to the clinical studies.

"We were encouraged by the promising preclinical activity of these novel enolase inhibitors and that the safety profile extends to higher models. While there could be further refinements, I am optimistic that even HEX would show significant clinical activity against ENO1-deleted cancers," Muller said.

ENO1 deletions also occur in liver cancer, bile duct cancer and large-cell neuroendocrine lung cancers, all of which share poor prognosis and limited treatment options, Muller explained. Thus, once an optimal therapy candidate has been developed, there is potential to evaluate the ENO2 inhibitor in treating patients with multiple cancer types.

HOUSTON - (Nov. 23, 2020) - Knowing precisely where proteins are frustrated could go a long way toward making better drugs.

That's one result of a new study by Rice University scientists looking for the mechanisms that stabilize or destabilize key sections of biomolecules.

Atom-scale models by Rice theorist Peter Wolynes, lead author and alumnus Mingchen Chen and their colleagues at the Center for Theoretical Biological Physics show that not only are some specific frustrated sequences in proteins necessary to allow them to function, locating them also offers clues to achieve better specificity for drugs.

That knowledge could also help design drugs with fewer side effects, Wolynes said.

The team's open-access study appears in Nature Communications.

The atom-scale models zero in on the interactions within possible binding sites rather than the vast majority of the interactions in proteins that guide their folding. The finer resolution models allow the incorporation of co-factors like chemically active ligands, including drug molecules. The researchers say this ability gives new insight into why ligands are best captured only by specific proteins and not by others.

"Unnatural ligands," aka drugs, tend to bind best with those frustrated pockets in proteins that become minimally frustrated once the drugs bind, Wolynes said. Having a way to find and then learn the details of these minimally frustrated sites would help pharmaceutical companies eliminate a lot of trial and error.

"The standard way of doing drug design is to try out 10,000 binding sites on a protein to find ones that fit," Wolynes said. "We're saying you don't have to sample all possible binding sites, just a reasonably fair number to understand the statistics of what could work in local environments.

"It's the difference between taking a poll and actually having an election," he said. "The poll is cheaper, but you still will need to check things out."

The Rice researchers are known for their energy landscape theory of how proteins fold. It usually employs coarse-grained models in which amino acids are represented by just a few sites.

That strategy takes less computing power than trying to determine the positions over time of every atom in every residue, and yet it has proven highly accurate in predicting how proteins fold based on their sequences. But for this study, the researchers modeled proteins and protein-ligand complexes at the atomic level to see if they could find how frustration gives some parts of a protein the flexibility required to bind to other molecules.

"One of the great things about modeling at all-atom resolution is that it allows us to evaluate whether drug molecules fit well into binding sites or not," Wolynes said. "This method is able to quickly show whether a binding site for a certain drug will be minimally frustrated or will remain a frustrated region. If after the molecule binds the site remains frustrated, the protein could rearrange or the drug could change its orientation in such a way that it could give rise to side effects."

Modeling the frustrated sites -- and sometimes altering them to see what would happen -- lets the researchers see how drug specificity correlates with binding pockets. Frustration analysis, they wrote, provides "a route for screening for more specific compounds for drug discovery."

"This concept of frustration was there at the very beginning of our work on protein folding," Wolynes said. "When we applied it to real protein molecules, we found some examples where the mechanism of folding violated what we would predict from a perfect funnel. Then we discovered these deviations from the funnel picture occurred where the protein was, in fact, somewhat frustrated.

"It was like the exception that proves the rule," he said. "Something that's true all the time might be trivial. But if it's not true 1% of the time, it's a problem to be solved, and we've been able to do that with AWSEM, our structure-prediction software."

Extending the software to analyze frustration on the atomic level is possible, as described by the group in another recent paper. But the computational cost of tracking every atom in a protein is so high that the researchers needed a way to sample the motions of specific regions where frustration might confuse the folding route.

"Mingchen realized there was an efficient algorithm to sample the local environments in binding sites but keep the atomistic resolution," said Wolynes, who noted he and Chen, now in private industry, are using the models to investigate possible therapeutics, including COVID-19-related drugs.

A new approach to treating cancers and other diseases that uses a mechanically interlocked molecule as a 'magic bullet' has been designed by researchers at the University of Birmingham.

Called rotaxanes, the molecules are tiny nanoscale structures that resemble a dumbbell with a ring trapped around the central post. Scientists have been experimenting with rotaxanes based on thin, thread-like central posts for a number of years, but this new design uses instead a much larger cylindrical-shaped supramolecular 'helicate' molecule - around 2nm long and 1nm wide - which have remarkable ability to bind Y-shaped junctions or forks in DNA and RNA.

These forks are created when DNA replicates and, in laboratory tests, the Birmingham researchers have shown that, when they bind to the junctions, the cylinder molecules are able to stop cancer cells, bacteria and viruses from reproducing.

To gain control over that binding, the team from the University's Schools of Chemistry and Biosciences, collaborated with researchers in Wuhan, in China, and Marseille, in France, to solve the challenge of identifying a ring structure large enough to fit around this central cylinder molecule. They have now shown that a giant pumpkin-shaped molecule, called a cucurbit[10]uril) is able to host the cylinder. When the ring is present, the rotaxane molecule is unable to bind.

To prevent the cylinder from slipping out of the pumpkin-shaped ring, the researchers added branches to each end of the cylinder. They demonstrated that the cylinder then becomes mechanically locked inside the ring and that they can use this to control the way the supramolecular cylinder interacts with RNA and DNA.

The results, published in the Journal of the American Chemical Society, show not only how these complex molecules can be produced simply and efficiently, but also how the number of branches can be used to regulate the speed at which the cylinder can escape from the pumpkin-shaped ring - from quickly to not at all.This allows temporal control of the fork-recognition and thus the biological activity.

Lead researcher, Professor Mike Hannon, explains: "This is a really promising new approach that harnesses robust and proven chemistry in an entirely new way that has potential for targeted treatment of cancers and other diseases.

"Our approach is very different to leading cancer drugs which commonly affect all cells in the body, not just the cancer cells. The rotaxane molecule holds the promise that, by turning it on and off as required, it can specifically target and inhibit cancer cells with a high degree of accuracy."

University of Birmingham Enterprise has a filed patent application covering the structure and design of these novel rotaxanes, and the team has already started work to explore a variety of applications for the approach.

Oscillatory behaviors are ubiquitous in Nature, ranging from the orbits of planets to the periodic motion of a swing. In pure crystalline systems, presenting a perfect spatially-periodic structure, the fundamental laws of quantum physics predict a remarkable and counter-intuitive oscillatory behavior: when subjected to a weak electric force, the electrons in the material do not undergo a net drift, but rather oscillate in space, a phenomenon known as Bloch oscillations. Ultracold atoms immersed in a light crystal, also known as optical lattices, are one of the many systems where Bloch oscillations have been observed.

In general, the motion of particles is affected by the presence of forces, such as those generated by electromagnetic fields. In certain crystals, emergent fields reminiscent of electromagnetic fields can also exist as an intrinsic property of the material and they can potentially affect Bloch oscillations. From a mathematical point of view, these intrinsic fields can take various forms. Of particular interest are those fields represented by mathematical quantities that do not commute, namely for which the product 'a x b' is not equal to 'b x a'. These mathematical quantities, and the corresponding physical properties, are commonly called "non-Abelian". In Nature, generalized non-Abelian forces are required to describe the weak or strong nuclear forces, whereas electromagnetism is more simply described by Abelian (commuting) ones.

Writing in Nature Communications, M. Di Liberto, N. Goldman and G. Palumbo (Science Faculty, ULB) demonstrate that intrinsic non-Abelian fields can generate a novel type of Bloch oscillations in crystals. This exotic oscillatory phenomenon is characterized by a multiplication of the oscillation period, as compared to the fundamental period set by the crystal geometry. This multiplication factor has a profound origin, as it stems from the symmetries of the crystal and can be attributed to a topological invariant (a numerical quantity that is robust under small deformations of the crystal). Furthermore, these exotic Bloch oscillations are shown to be perfectly synchronized with a beating of internal states of the crystal. This work sheds new light on topological quantum matter with non-Abelian properties.