Culture

Several different kinds of bacteria can cause lung infections in people with cystic fibrosis (CF). Pseudomonas aeruginosa, which can cause pneumonia, typically infects infants or young children and persists for life, while Burkholderia cepacia complex species only infect teenagers and adults. Although Burkholderia infections are rare, when they do take hold, they are deadly. Now, UNC School of Medicine scientists led by Peggy Cotter, PhD, professor in the UNC Department of Microbiology and Immunology, have discovered a reason for this pathogen's apparent age discrimination.

This research, published in the journal Cell Host & Microbe, shows that both Pseudomonas and Burkholderia use toxic weaponry, called Type VI Secretion Systems (T6SS), to compete with and establish dominance over each other. It's possible that scientists could target, or mimic, this weaponry to defeat the bacteria before they cause irreparable harm to lungs of patients.

Scientists have wondered for a long time why Burkholderia does not infect infants and young children. First author and former Cotter Lab graduate student Andrew Perault, MPH, PhD, designed and conducted experiments to show that Pseudomonas bacteria isolated from infants and young children use their harpoon-like T6SS to fire toxins at, and kill, competitor bacteria, including Burkholderia.

"This may be one of the reasons Burkholderia does not take root in young patients," Cotter said. "Andy showed that although Burkholderia also produce T6SSs, they cannot effectively compete with Pseudomonas isolates taken from young CF patients."

However, as those Pseudomonas bacteria adapt to living in the lungs of CF patients, they lose their ability to produce T6SSs and to fight with Burkholderia. The Burkholderia, using their own T6SSs, are then able to kill the Pseudomonas and establish infection.

"We believe the findings of our study, at least in part, may explain why Burkholderia infections are limited to older CF patients," Perault said. "It appears that as at least some strains of Pseudomonas evolve to persist in the CF lung, they also evolve to lose their T6SSs, and hence their competitive edge over Burkholderia, which are then free to colonize the respiratory tract."

The scientists think the Burkholderia T6SS is an important factor promoting the ability of these pathogens to infect CF patients. Therefore, researchers could potentially develop therapeutics to target these secretion systems to prevent infections.

Moreover, assessing the T6SS potential of resident Pseudomonas populations within the CF respiratory tract may predict susceptibility of patients to potentially fatal Burkholderia infections.

What do you think of when you hear the word "refugee"? For many people, what comes to mind is vulnerability--you might imagine the grim conditions of a refugee camp or the dangers of the desperate journey to safety. So perhaps it's unsurprising that refugees are widely perceived to be especially needy or dependent on public assistance.

But in their search for opportunity and community, refugees in the United States actually look just as resourceful as other immigrants. That's according to a new study from the Immigration Policy Lab (IPL) , which included researchers at Stanford University, Dartmouth College, and the Department of Homeland Security's Office of Immigration Statistics (OIS).

As they build a new life in the country, many refugees move to a different state soon after arrival, according to a new dataset on nearly 450,000 people who were resettled between 2000 and 2014. And when they move, they are primarily looking for better job markets and helpful social networks of others from their home country--not more generous welfare benefits.

"These findings counter the stereotype that refugees are destined to become a drain on state resources over the long run," says study co-author Jeremy Ferwerda. "When choosing where to live in the United States, refugees do not move to states where welfare benefits are highest. Instead, they leave states with high unemployment rates and move to states with booming economies and employment opportunities. "

Harnessing the Data

Part of the reason we haven't had a clear picture of refugees' lives in the United States is that it isn't easy to connect different data sets in a way that allows you to follow each refugee over time. The U.S. Department of State keeps the records on new arrivals, including their country of origin, education, and ties to family or friends already living here. Records of milestones in their integration process, including becoming legal permanent residents and, later, citizens, are the province of U.S. Citizenship and Immigration Services.

Making this information useful calls for new partnerships between researchers and government agencies. "We are grateful to the Office of Immigration Statistics for providing this invaluable opportunity for collaboration between IPL and OIS researchers," says Duncan Lawrence, IPL executive director and study co-author. "This work would not have been possible without this partnership and input from knowledgeable, dedicated leaders in this office."

Before this, researchers have had to use small samples, either fielding a survey that asks people whether they entered the country as refugees, or using existing surveys and guessing at refugee status. Now, the IPL team had a sample of unprecedented size, accuracy, and detail.

"The law suggests that secondary migration should be monitored to help inform policymaking," says IPL co-director and study co-author Jens Hainmueller. "Our study helps with that, since we have captured secondary migration for the full population, for the first time."

Push And Pull Factors

One of the first things the researchers wanted to know was where refugees were living. U.S. refugee resettlement agencies assign each incoming refugee to a particular place, and their local offices receive federal funding to help the newcomers get settled. Until now, we haven't known how many of them leave their assigned location or what motivates them to move.

Because refugees are required to apply for permanent resident status a year after arrival, the researchers could note how many had a different address by then, and the numbers were surprising. Of the 447,747 refugees they observed, 17 percent had moved to a different state around the one-year mark. For other noncitizens during the same period, only an estimated 3.4 percent move out of state within the same time period after arrival.

Not only were the refugees highly mobile; there were distinct patterns in their movement. Some states were much more likely than others to see their refugees leave. In Louisiana, New Jersey, and Connecticut, more than 30 percent of refugees quickly relocated, while in California and Nebraska, only 10 percent did. Midwestern states had the greatest gain in refugees from other states, with Minnesota receiving the most.

With information on so many refugees, the researchers also were able to uncover patterns among people from the same country. Those from Somalia and Ethiopia left their assigned states in the greatest numbers. Congolese refugees, who were among the most likely to stay put, were 34 percentage points less likely to move than Somalis.

So what were the refugees looking for in a home? To find out, the researchers looked at the states in pairs and counted the number of arrivals and departures on each side. The greatest movement happened between state pairs that had the greatest difference in the share of the population who were from a refugee's home country. In other words, states where co-nationals are a higher share of the population tended to receive refugees from states with a lower share, and the numbers increase as the gap between the two states widens.

Economic opportunity was another strong pull factor. Refugees were especially likely to leave states with high unemployment in favor of states with low unemployment. Housing costs were another factor, though their influence was not as strong.

These findings echo research on migration patterns among recent immigrants, who have settled in different places than the traditional destinations that attracted earlier waves of newcomers. Immigrants as a whole highly value places that offer them a chance to make a good living and establish a supportive community--and refugees are no different.

U.S. refugees do stand out from other immigrants in at least one way: In an earlier study using the same dataset, the researchers found that they become citizens at much higher rates. Among refugees who arrived between 2000 and 2010, 66 percent had become citizens by 2015. And here again, opportunity, community, and place make a difference. Refugees placed in urban areas with lower unemployment and a larger share of co-nationals were more likely to naturalize.

Making a Better Match

Overall, these findings suggest that the U.S. refugee resettlement system is working relatively well, since most refugees do stay and build new lives in the places where they are sent. Still, one might look at all this movement and lament a certain inefficiency: The system devotes resources to helping refuges get situated in a given place, and they don't travel with the refugees who move.

So there's plenty of room to improve the match between refugees and local destinations, and the IPL team has a solution to offer: a data-driven tool called GeoMatch that makes personalized location recommendations for each refugee. The tool can also help economic immigrants decide where to live within a new country. For both groups, it puts vast amounts of previously unused data to good use, informing decisions that can alter the course of people's lives.

AUSTIN, Texas -- The "invisible" words that shaped Dickens classics also lead audiences through Spielberg dramas. And according to new research, these small words can be found in a similar pattern across most storylines, no matter the length or format.

When telling a story, common but invisible words -- a, the, it -- are used in certain ways and at certain moments. In a study published in Science Advances, researchers from The University of Texas at Austin and Lancaster University in Lancaster, United Kingdom, recorded the use of such words across thousands of fictional and nonfictional stories, mapping a universal blueprint for storytelling.

"We all have an intuitive sense of what defines a story. Until now, no one has been able to objectively see or measure a story's components," said study co-author and UT Austin psychology researcher Jamie Pennebaker.

In a computer analysis of nearly 40,000 fictional narratives, including novels and movie dialogues, the researchers tracked authors' use of pronouns (she, they), articles (a, the), and other short words, unveiling a consistent "narrative curve:"

1. Staging: Stories begin with a lot of prepositions and articles like "a" and "the." For example, "The house was next to the lake, below a cliff." These words help authors set the scene and convey the most basic information the audience needs to understand concepts and relationships throughout the story.

2. Plot progression: Once the stage is set, authors incorporate more and more interactional language, including auxiliary verbs, adverbs and pronouns. For example, "the house" becomes "her home" or "it."

3. Cognitive tension: As a story progresses toward its climax, cognitive-processing words rise -- action-type words, such as "think," "believe," "understand" and "cause," that reflect a person's thought process while working through a conflict.

This combined linguistic pattern in stories may reflect how humans optimally process information, the researchers said. Prior studies have shown that young children can easily assign names to people and things; ascribing action, however, proves more difficult.

"If we want to connect with an audience, we have to appreciate what information they need, but don't yet have," said study lead author Ryan Boyd, a UT Austin alum and an assistant professor of behavioral analytics at Lancaster University. "At the most fundamental level, humans need a flood of 'logic language' at the beginning of a story to make sense of it, followed by a rising stream of 'action' information to convey the actual plot of the story."

The research team compared the established fictional story structure to more than 30,000 factual texts, including 28,664 New York Times articles, 2,226 TED Talks and 1,580 Supreme Court opinions. Though many shared striking similarities, each genre had unique structures that reflected the different relationships between the authors and their audiences.

"Take TED Talks, for example. They mostly show the same pattern, except at the end where the cognitive tension aspect of stories continues to climb with words like 'think' or 'because,'" said study co-author Kate Blackburn, a post-doctoral research fellow at UT Austin. "This makes perfect sense. The goal of the TED Talk is to inspire, and leave the audience questioning what they have just heard from the speaker. In this sense, we seem to be able to tap into the structure of other forms of storytelling, as if we can identify that story's fingerprint."

Enzymes are molecules that catalyze metabolisms. Discovery and mining of enzymes, such as those producing oils or fixing carbon dioxide, have been a key mission of the biotechnology industry. However, this mission can be very slow and tedious.

To tackle this key challenge, Chinese scientists have now developed a flow mode Raman-activated cell sorter (RACS), called FlowRACS, to support high-throughput discovery of enzymes and their cell factories, at the precision of just one microbial cell. The study was published in Science Advances on August 7.

Microbial cells and their enzyme products mediate numerous biological processes. The mining of useful enzymes and microbial cells that produce them has dated back nearly one century. However, such endeavors can be very slow and difficult, due to the tiny size of microbes - 1000 times smaller than a human cell. Moreover, most of the microbial cells cannot be readily cultured - for this reason, they are called by microbiologists as the "biological dark matter".

To address these challenges, a team of scientists from Single-Cell Center in Qingdao Institute of Bioenergy and Bioprocess Technology (QIBEBT), Chinese Academy of Sciences (CAS), introduced a novel instrument called FlowRACS. "This is a flow-mode Raman-activated Cell Sorter that can sort microbial cells and enzymes they produced, based on Single-cell Raman Spectrum and in a high-throughput manner," said Prof. MA Bo, Deputy Director of Single-Cell Center and a senior author of the study.

Single-cell Raman Spectrum can reveal the metabolic function of a cell, such as the kind of oils produced or the rate of carbon dioxide fixed, without destroying the cell. Based on these signals, cells are sorted in RACS. If the cells are sitting still during sorting, this would be easier, but very slow. To speed up the sorting, cells can be lined up and moved rapidly through a spectrum detection point one by one. However, such flow-mode RACS can be much more difficult, due to the very small size of microbial cells and the very weak Raman signal.

To improve the process, researchers applied positive dielectrophoresis (pDEP), which can capture or mobilize particles. This allows trapping fast-moving single microbial cells, processing them precisely yet rapidly through a Raman detection point to recognize those cells that produce particular enzymes or metabolites, and then packaging cells into droplets. In the end, the droplets that harbor target cells are sorted. In this pDEP Raman-activated droplet sorting, or pDEP-RADS, the cells do not require culturing, labeling or invasive action in order to be sorted and identified at a high speed.

Diacylglycerol acyltransferases, or DGATs, are enzymes that produce triacylglycerols (TAGs) which are main ingredient of human and animal fats as well as plant oils. However, traditionally, screening of DGATs has been extremely tedious. For each sample, culture of DGAT-producing cells can take days and subsequent analysis of the cells for oil ingredients can also take days.

Using FlowRACS, the researchers screened yeasts that express DGAT candidates for its TAG content and profile, at about 120 cells per minute, equivalent to 120 of the traditional "samples" per minute. They also sorted cells for the degree of unsaturation, a key characteristic of TAG that determines its nutritional value, with about 82% accuracy and at 40 cells per minute.

A single run of FlowRACS, which takes just ten minutes, revealed all our previously reported DGAT variants. In contrast, discovering and characterizing these enzymes would have either taken months for culture-based methods, or simply been not possible due to insufficient sensitivity of fluorescence-activated cell sorting.

"Such culture-free, label-free and non-invasive sorting of enzyme activity in vivo can save time, consumable and labor by one to two orders of magnitude, as compared to conventional approaches," said, Dr. WANG Xixian, first author of the paper.

"To our knowledge, this is the first demonstration of RACS for enzyme discovery," added Prof. XU Jian, Director of Single-Cell Center and the other senior author of the study, "The birth of FlowRACS greatly expands the application of RACS. The community is now equipped with a new instrument for the discovery and mining of the 'biological dark matter' for not just cells but enzymes, both wonderful gifts from Mother Nature."

Dr Steven Truxal, a Reader in The City Law School, says the COVID-19 crisis has exposed an imbalance in EU state aid for the aviation sector.

In his article, "State Aid and Air Transport in the Shadow of COVID-19", published in a special issue of Air & Space Law, Dr Truxal investigates legal issues in the context of temporary state aid measures applied to different air transport stakeholders (airlines, airports, air navigation service providers and aircraft manufacturers) in the current crisis. He gives a general overview of EU state aid law as applied in the sector before discussing specific measures taken in regard to coronavirus.

The article identifies the extent to which individual EU states extend support to stakeholders, and under what circumstances. In conclusion, Dr Truxal reflects on the role of the State and the flexibility of EU state aid law in a time of unprecedented crisis.

Dr Truxal argues that given the unavailability of private recapitalisation in this time of great uncertainty, state grants, loans or other guarantees may offer the only means of support for hard-hit European airlines to survive in a market which the International Air Transport Association (IATA) estimates will suffer a loss of €314bn.

He writes that "when times are good, fewer airlines in liberalised and deregulated markets will be protected at all costs from the risks and opportunities associated with the free market, while states may seek to protect some air carriers at any cost in times of crisis".

Citing examples of Germany's support for Lufthansa and France's aid for Air France, Dr Truxal has identified examples of public support that come with strings attached. As conditions of state aid, Lufthansa must divest in airport slots and Air France should become environmentally friendly.

Dr Truxal notes that States can be seen as seizing "the opportunity to promote the green agenda with climate targets attached as conditions to state aid, whereby accelerating green innovation in air transport".

Dr Truxal suggests that "if airlines do not become 'greener', they could risk being replaced by other forms of transport on short haul markets. States may choose to invest in high-speed rail links."

Dr Truxal's specialist research focuses on competition and environmental regulation of air transport, and the link between market competition and the environment.

In the first billion years, there was no oxygen on Earth. Life developed in an anoxic environment. Early bacteria probably obtained their energy by breaking down various substances by means of fermentation. However, there also seems to have been a kind of "oxygen-free respiration". This was suggested by studies on primordial microbes that are still found in anoxic habitats today.

"We already saw ten years ago that there are genes in these microbes that perhaps encode for a primordial respiration enzyme. Since then, we - as well as other groups worldwide - have attempted to prove the existence of this respiratory enzyme and to isolate it. For a long time unsuccessfully because the complex was too fragile and fell apart at each attempt to isolate it from the membrane. We found the fragments, but were unable to piece them together again," explains Professor Volker Müller from the Department of Molecular Microbiology and Bioenergetics at Goethe University.

Through hard work and perseverance, his doctoral researchers Martin Kuhns and Dragan Trifunovic then achieved a breakthrough in two successive doctoral theses. "In our desperation, we at some point took a heat-loving bacterium, Thermotoga maritima, which grows at temperatures between 60 and 90°C," explains Dragan Trifunovic, who will shortly complete his doctorate. "Thermotoga also contains Rnf genes, and we hoped that the Rnf enzyme in this bacterium would be a bit more stable. Over the years, we then managed to develop a method for isolating the entire Rnf enzyme from the membrane of these bacteria."

As the researchers report in their current paper, the enzyme complex functions a bit like a pumped-storage power plant that pumps water into a lake higher up and produces electricity via a turbine from the water flowing back down again.

Only in the bacterial cell the Rnf enzyme (biochemical name = ferredoxin:NAD-oxidoreductase) transports sodium ions out of the cell's interior via the cell membrane to the outside and in so doing produces an electric field. This electric field is used to drive a cellular "turbine" (ATP synthase): It allows the sodium ions to flow back along the electric field into the cell's interior and in so doing it obtains energy in the form of the cellular energy currency ATP.

The biochemical proof and the bioenergetic characterization of this primordial Rnf enzyme explains how first forms of life produced the central energy currency ATP. The Rnf enzyme evidently functions so well that it is still contained in many bacteria and some archaea today, in some pathogenic bacteria as well where the role of the Rnf enzyme is still entirely unclear.

"Our studies thus radiate far beyond the organism Thermotoga maritima under investigation and are extremely important for bacterial physiology in general," explains Müller, adding that it is important now to understand exactly how the Rnf enzyme works and what role the individual parts play. "I'm happy to say that we're well on the way here, since we're meanwhile able to produce the Rnf enzyme ourselves using genetic engineering methods," he continues.

Research has shown that a mutation in the ATAXIN-1 gene leads to accumulation of Ataxin-1 (ATXN1) protein in brain cells and is the root cause of a rare genetic neurodegenerative disease known as spinocerebellar ataxia type 1 (SCA1). How healthy cells maintain a precise level of ATXN1 has remained a mystery, but now a study led by researchers at Baylor College of Medicine and the Jan and Dan Duncan Neurological Research Institute at Texas Children's Hospital reveals a novel mechanism that regulates ATXN1 levels.

Manipulating this mechanism in animal models of SCA1 reduced ATXN1 levels and improved some of the symptoms of the condition. The findings, published in the journal Genes & Development, offer the possibility of developing treatments that could improve the condition, for which there is no cure.

"SCA1 is characterized by progressive problems with movement, including loss of coordination, and balance (ataxia) and muscle weakness. People with SCA1 typically survive 15 to 20 years after symptoms first appear," said first author Larissa Nitschke, doctoral candidate in the lab of Dr. Huda Zoghbi at Baylor and Texas Children's.

"SCA1 is one of the adult-onset neurodegenerative diseases for which we know the genetic cause, in this case the gene ATXN1," said Zoghbi, corresponding author of the work and professor of molecular and human genetics, pediatrics and neuroscience, and Ralph D. Feigin, M.D. Endowed Chair at Baylor. "When we identified the gene, we learned that mutations can cause the ATXN1 protein to remain in cells longer than normally. This is bad news for neurons as too much ATXN1 leads to their death."

The findings suggested that lowering the levels of ATXN1 might result in improved symptoms, so Nitschke and her colleagues looked for mechanisms that cells use to control the levels of ATXN1.

How cells regulate ATXN1 levels

As with other genes, part of the ATXN1 gene codes for the protein itself and the rest is involved in regulating the expression of the RNA and protein encoded by the gene.

"We looked at a regulatory region known as 5-prime untranslated region (5' UTR), which is unusually long for the ATXN1 gene, and found that it keeps the protein in check so it does not accumulate to reach toxic levels," Nitschke said.

The researchers studied this region in great detail, piece by piece, looking to identify individual sequences or elements that might control the amount of ATXN1 that cells produce. They found several elements that fulfilled that function.

Nitschke and her colleagues focused on one regulatory element that seemed important because it is conserved in many species. They discovered that this short piece could regulate ATXN1 levels.

"We also found that we could reduce the amount of ATXN1 produced with a microRNA called miR760 that binds specifically to the conserved small piece in the 5'UTR region. MicroRNAs are tiny RNA molecules that cells use to regulate the production of specific proteins by interacting with regulatory regions," Nitschke said. "This finding encouraged us to test whether miR760 could reduce the amount of ATXN1 in animal models of SCA1."

Reducing ATXN1 in the cerebellum improves SCA1 symptoms in animal models

Testing the effect of miR760 on animal models of SCA1 had to be planned carefully.

"The role of ATXN1 in the brain is complex," said Zoghbi, director of the Jan and Dan Duncan Neurological Research Institute and member of the Howard Hughes Medical Institute. "Having too much ATXN1 in the back of the brain, the region called the cerebellum, which is involved in balance and coordination, results in balance problems. Having too little ATXN1 in the part of the brain for learning and memory increases the risk of Alzheimer's disease."

The researchers designed their experiments to reduce the levels of ATXN1 only in the cerebellum using gene therapy directed just at this brain region. The results were encouraging. Providing miR760 lowered the levels of ATXN1 and, importantly, improved motor and coordination deficits in the animal models of SCA1.

"The most exciting part of our findings was that we could reduce some of the symptoms of SCA1 in the animal models," Nitschke said. "Although we only lowered the levels of ATXN1 by about 25 percent, the mice significantly improved their movements. This result strongly supports further studies to explore the effectiveness of this approach to treat the human condition."

The findings not only highlight the importance of ATXN1 gene regulatory regions in SCA1, but also bring up the possibility that mutations in these DNA elements could lead to increased levels of ATXN1 and in turn increase the risk for balance problems. Identifying and analyzing the sequences of such elements in people with balance problems might have a potential to help provide a diagnosis.

When fast-moving ions cross paths with large biomolecules, the resulting collisions produce many low-energy electrons which can go on to ionise the molecules even further. To fully understand how biological structures are affected by this radiation, it is important for physicists to measure how electrons are scattered during collisions. So far, however, researchers' understanding of the process has remained limited. In new research published in EPJ D, researchers in India and Argentina, led by Lokesh Tribedi at the Tata Institute of Fundamental Research, have successfully determined the characteristics of electron emission when high-velocity ions collide with adenine - one of the four key nucleobases of DNA.

Since high-energy ions can break strands of DNA as they collide with them, the team's findings could improve our understanding of how radiation damage increases the risk of cancer developing within cells. In their experiment, they considered the 'double differential cross section' (DDCS) of adenine ionisation. This value defines the probability that electrons with specific energies and scattering angles will be produced when ions and molecules collide head-on, and is critical for understanding the extent to which biomolecules will be ionised by the electrons they emit.

To measure the value, Tribedi and colleagues carefully prepared a jet of adenine molecule vapour, which they crossed with a beam of high-energy carbon ions. They then measured the resulting ionisation through the technique of electron spectroscopy, which allowed them to determine the adenine's electron emissions over a wide range of energies and scattering angles. Subsequently, the team could characterise the DDCS of adenine-ion collision; producing a result which largely agreed with predictions made by computer models based on previous theories. Their findings could now lead to important advances in our knowledge of how biomolecules are affected by high-velocity ion radiation; potentially leading to a better understanding of how cancer in cells can arise following radiation damage.

Nowadays, agriculture is going to become AI-native: Skoltech researchers have used the Zhores supercomputer to perform a very precise sensitivity analysis to reveal crucial parameters for different crop yields in the chernozem region. Their paper was published in the proceedings of the International Conference on Computational Science 2020.

Farmers all over the world use digital crop models to predict crop yields; these models describe soil processes, climate, and crop properties and require environmental and agricultural management input data to calibrate them and improve the forecasts. In some countries, however, agrochemical data is not freely available for users of these models, and this calibration can become expensive and time-consuming.

A Skoltech team led by full professor Ivan Oseledets and assistant professor Maria Pukalchik used one of the popular open-source process-based model called MONICA and figured out a way to reveal only the most important parameters for crop yield based on historical data and process-modeling. Moreover, they sped up computational efficiency from one simulation per day to half a million model simulations per hour using Zhores, the flagship Skoltech supercomputer.

This stunning amount of simulations is necessary to perform high-quality sensitivity analysis that helps determine how the changes in certain input factors (such as soil parameters or fertilizer) influenced the output crop yield prediction.

The research team used field data from an experiment in the Russian chernozem region, with seasonal crop-rotation of sugar beet (Beta vulgaris), spring barley (Hordeum vulgare), and soybean (Glycine max) observed from 2011 to 2017. They picked six main soil parameters for sensitivity analysis and performed what's called Sobol sensitivity analysis (named after Ilya Sobol, a Russian mathematician who proposed it in 2001).

"Soil is a very complicated issue in this country. Unfortunately, the data about soil properties and crop yield are not published. We have found an opportunity to overcome this barrier and set up the Zhores supercomputer to solve this issue. Now we can simulate all possible variants and reveal the most crucial parameters without time-consuming and costly work. We hope that our achievements will help farmers digitalize their crop growth," said Maria Pukalchik.

Materials science researchers, led by electrical engineering professor Shui-Qing "Fisher" Yu, have demonstrated the first electrically injected laser made with germanium tin.

Used as a semiconducting material for circuits on electronic devices, the diode laser could improve micro-processing speed and efficiency at much lower costs.

In tests, the laser operated in pulsed conditions up to 100 kelvins, or 279 degrees below zero Fahrenheit.

"Our results are a major advance for group-IV-based lasers," Yu said. "They could serve as the promising route for laser integration on silicon and a major step toward significantly improving circuits for electronics devices."

The research is sponsored by the Air Force Office of Scientific Research, and the findings have been published in Optica, the journal of The Optical Society. Yiyin Zhou, a U of A doctoral student in the microelectronics-photonics program authored the article. Zhou and Yu worked with colleagues at several institutions, including Arizona State University, the University of Massachusetts Boston, Dartmouth College in New Hampshire and Wilkes University in Pennsylvania. The researchers also collaborated with Arktonics, an Arkansas semiconductor equipment manufacturer.

The alloy germanium tin is a promising semiconducting material that can be easily integrated into electronic circuits, such as those found in computer chips and sensors. The material could lead to the development of low-cost, lightweight, compact and low power-consuming electronic components that use light for information transmission and sensing.

Yu has worked with germanium tin for many years. Researchers in his laboratory have demonstrated the material's efficacy as a powerful semiconducting alloy. After reporting the fabrication of a first-generation, "optically pumped" laser, meaning the material was injected with light, Yu and researchers in his laboratory continue to refine the material.

PHILADELPHIA -- (August 4, 2020) -- Scientists at The Wistar Institute may have discovered a new way of identifying and targeting hidden HIV viral reservoirs during treatment with antiretroviral therapy (ART). These findings were published today in Cell Reports and may have translational implications for improving the long-term care of HIV positive people.

ART has dramatically increased the health and life expectancy of HIV-infected individuals, suppressing virus replication in the host immune cells and stopping disease progression; however, low yet persistent amounts of virus remain in the blood and tissues despite therapy. Virus persistency limits immune recovery and is associated with chronic levels of inflammation so that treated HIV-infected individuals have higher risk of developing a number of diseases.

This persistent infection stems from the ability of HIV to hide in a rare population of CD4 T cells. Finding new markers to identify the virus reservoir is of paramount importance to achieve HIV eradication.

"With recent advances that we are making in the fields of glycobiology and glycoimmunology, it has become clear that the sugar molecules present on the surface of immune cells play a critical role in regulating their functions and fate," said corresponding author Mohamed Abdel-Mohsen, Ph.D., assistant professor in The Wistar Institute Vaccine & Immunotherapy Center. "However, the relevance of host cell-surface glycosylation in HIV persistence remained largely unexplored, making it a 'dark matter' in our understanding of HIV latency. For the first time, we described a cell-surface glycomic signature that can impact HIV persistence."

Persistently infected cells can be divided into two groups: cells where the virus is completely silent and does not produce any RNA (i.e., silent HIV reservoir); and cells where the virus produces low levels of RNA (i.e., active HIV reservoir). Targeting and eliminating both types of reservoirs is the focus of the quest for an HIV cure. A main challenge in this quest is that we do not have a clear understanding of how these two types of infected cells are different from each other and from HIV-uninfected cells. Therefore, identifying markers that can distinguish these cells from each other is critical.

For their studies, Abdel-Mohsen and colleagues used a primary cell model of HIV latency to characterize the cell-surface glycomes of HIV-infected cells. They confirmed their results in CD4 cells directly isolated from HIV-infected individuals on ART.

They identified a process called fucosylation as a feature of persistently infected T cells in which the viral genome is actively being transcribed. Fucosylation is the attachment of a sugar molecule called fucose to proteins present on the cell surface and is critical for T-cell activation.

Researchers also found that the expression of a specific fucosylated antigen called Sialyl-LewisX (SLeX) identifies persistent HIV transcription in vivo and that primary CD4 T cells with high levels of SLeX have higher levels of T-cell pathways and proteins known to drive HIV transcription during ART. Such glycosylation patterns were not found on HIV-infected cells in which the virus is transcriptionally inactive, providing a distinguishing feature between these two cell compartments. Interestingly, researchers also found that HIV itself promotes these cell-surface glycomic changes.

Importantly, having a high level of SLeX is a feature of some cancer cells that allow them to metastasize (spread to other sites in the body). Indeed, researchers found that HIV-infected cells with high levels of SLeX are enriched with molecular pathways involved in trafficking between blood and tissues. These differential levels of trafficking might play an important role in the persistence of HIV in tissues, which are the main sites where HIV hides during ART.

Based on these findings, the role of fucosylation in HIV persistence warrants further studies to identify how it contributes to HIV persistence and how it could be used to target HIV reservoirs in blood and tissues.

Experts from the Center for Diagnostics and Telemedicine have developed a platform for self-testing services which is based on artificial intelligence and designed for medical tasks, such as for analyzing diagnostic images. The first working prototype of the platform is hosted on the popular GitHub service, and developers from all over the world can take part in its improvement by adding verification criteria depending on the purpose of the services. Sergey Morozov, CEO of the Center for Diagnostics and Telemedicine, spoke about this at the thematic week dedicated to artificial intelligence which was part of the program of the European Congress of Radiology (ECR 2020).

Before implementing a service based on artificial intelligence (AI) into routine clinical practice, it is necessary to test it for technical readiness, as well as to verify whether it meets the stated characteristics. It is called analytical validation of the algorithm. The services that have passed it are allowed to be integrated into medical systems, including city healthcare.

Integration is a complex and expensive process, so it becomes a barrier for many teams that cannot guarantee the required accuracy and speed of the algorithm processing data of the system into which they are integrated. Currently analytical validation is performed manually. Manual validation allows accidental or deliberate deviations from the approved test program, as well as manipulation of datasets, and also can potentially put different test participants in unequal conditions.

To solve these problems and automate the verification process, ensuring trust of users, specialists of the Center for Diagnostic and Telemedicine have developed a platform that allows developers of AI-based services to independently conduct preliminary tests (analytical validation) of their algorithms. A prototype of the platform has been hosted on the GitHub, and the first version of the service for exchanging datasets and data analysis results has already been uploaded.

The platform provides an opportunity for the unlimited number of accesses to single samples of data instances from the test set in order to fine-tune algorithms. It has uniform rules of use, and it is possible to test several services simultaneously. At the same time, the platform records the time that the software spends on data processing (time-study), and the developers receive an automatic report on the results of testing, - explains Sergey Morozov, CEO of the Center for Diagnostic and Telemedicine.

By automating the entire process on the self-testing platform, the human factor is minimized, which makes data manipulation (to improve results) impossible. In addition, the comparison of the service's verification results with the reference data is absolutely transparent - the developer can see what metrics were used, and how the final result reflected in the report was calculated.

Anyone can take part in improving the platform and add necessary metrics to it, which will be used to evaluate the algorithm's performance for certain medical purposes (for example, for analyzing radiographs or mammograms). However, the addition of the platform will be monitored - the only metrics that have scientific justification will be included in the platform operating on the basis of the Center, - notes Nikolai Pavlov, the developer of the platform, Head of Dataset Labeling Conveyor of the Medical Informatics, Radiomics and Radiogenomics Sector, Center for Diagnostics and Telemedicine.

The creators of the platform invite developers of AI algorithms, programmers and researchers to take part in updating and improving the platform in order to develop a uniform, universal, and user-friendly tool for self-testing of artificial intelligence algorithms intended for medical purposes in the international community. At the moment, there is no such tool aimed specifically at the clinical implementation of services based on AI technologies.

For years, scientists have attributed animal behavior to the coordinated activities of neuronal cells and its circuits of neurons, known as the neuronal network (NN). However, researchers are pushing the boundaries in understanding animal behavior through the integration of gene regulation.

Fueled by a long-time collaboration with Carl R. Woese Institute for Genomic Biology (IGB) Director and entomology professor Gene Robinson at the University of Illinois Urbana-Champaign, incoming IGB Director of Computational Genomics and computer science professor Saurabh Sinha helped organize a workshop on "Cis-Regulatory Evolution in Development and Behavior" in 2018 to push a new line of thinking.

"One of the remarkable findings from a study led by Gene and his collaborators was that more eusocial insects seemed to have something different about their regulatory genome," said Sinha. "It seemed that there was some sort of evolutionary signature of complex social behavior that we hadn't really expected and was one of those findings that really made you re-think the implications."

The two-day workshop brought together people from a diverse set of skillsets where ideas were exchanged and challenged during discussions on various topics. Two years later, the results of those discussions culminated in a perspective article published in the Proceedings of the National Academy of Science.

"The starting point for this perspective is that the NN is the de facto standard for understanding what goes on in the brain as pertinent to behavior," said Sinha. "Our goal was to highlight another level of dynamics that accompany behavior and not just the dynamics of the NN."

The authors of the perspective synthesized current evidence on the role of the gene regulatory networks (GRNs) - a collection of regulatory interactions between genes - in the context of animal behavior along with the NN. Behavior-associated GRNs (bGRNs) impact gene expression changes associated with a certain animal behavior while developmental GRNs (dGRNs) influence development of new cells and connections in the brain. The integration of NNs, bGRNs and dGRNs across multiple scales holds potential in understanding how these networks work in concert to regulate animal behavior.

"Our first goal was to simply emphasize the significance of the GRN in the behavioral context, before speculating on how the GRN might interact with the NN since current research is lacking," said Sinha. "One example of an interaction between the NN and GRN could be the modulation of neuronal transmission activity through control of protein or peptide expression by the GRN."

Through experimental mapping of these networks, the changes in gene expression can be corresponded with behaviors in different cell types. Emerging technologies will play a key role in these efforts. "Measuring gene expression in the brain has been fraught with the heterogeneity of the brain where you have so many different cell types," said Sinha. "The fact that we have single-cell technology really taking off means that we can have a proper resolution of GRNs in the brain and therefore, examine how cell type-specific GRNs interact with signal transmission through the NN."

The perspective also touches on how environmental factors and social behavior affect GRNs, which then go on to modulate NN function and behavior. "The environment can induce epigenetic and longer-lasting changes that then lead to the GRN becoming different," said Sinha. "Looking at brain function not only through the lens of the NN but also through GRNs allows us to bring in the environment in a credible way. In regard to social behavior, there is probably a difference in the GRN of more eusocial bees and that is a starting point for the intriguing possibility that social behavior has some unique characteristics in its GRNs."

With the emergence of technologies, future analyses of bGRNs and the interchange between bGRNs, dGRNs and NNs in various behavioral contexts will provide a deeper understanding of animal behavior.

DURHAM, N.C. - Duke physician Eric Westman was one of the first champions of masking as a means to curtail the spread of coronavirus, working with a local non-profit to provide free masks to at-risk and under-served populations in the greater Durham community.

But he needed to know whether the virus-blocking claims mask suppliers made were true, to assure he wasn't providing ineffective masks that spread viruses along with false security. So he turned to colleagues in the Duke Department of Physics: Could someone test various masks for him?

Martin Fischer, Ph.D., a chemist and physicist, stepped up. As director of the Advanced Light Imaging and Spectroscopy facility, he normally focuses on exploring new optical contrast mechanisms for molecular imaging, but for this task, he MacGyvered a relatively inexpensive apparatus from common lab materials that can easily be purchased online. The setup consisted of a box, a laser, a lens, and a cell phone camera.

In a proof-of-concept study appearing online Aug. 7 in the journal Science Advances, Fischer, Westman and colleagues report that the simple, low-cost technique provided visual proof that face masks are effective in reducing droplet emissions during normal wear.

"We confirmed that when people speak, small droplets get expelled, so disease can be spread by talking, without coughing or sneezing," Fischer said. "We could also see that some face coverings performed much better than others in blocking expelled particles."

Notably, the researchers report, the best face coverings were N95 masks without valves - the hospital-grade coverings that are used by front-line health care workers. Surgical or polypropylene masks also performed well.

But hand-made cotton face coverings provided good coverage, eliminating a substantial amount of the spray from normal speech.

On the other hand, bandanas and neck fleeces such as balaclavas didn't block the droplets much at all.

"This was just a demonstration - more work is required to investigate variations in masks, speakers, and how people wear them - but it demonstrates that this sort of test could easily be conducted by businesses and others that are providing masks to their employees or patrons," Fischer said.

"Wearing a mask is a simple and easy way to reduce the spread of COVID-19," Westman said. "About half of infections are from people who don't show symptoms, and often don't know they're infected. They can unknowingly spread the virus when the cough, sneeze and just talk.

"If everyone wore a mask, we could stop up to 99% of these droplets before they reach someone else," Westman said. "In the absence of a vaccine or antiviral medicine, it's the one proven way to protect others as well as yourself."

Westman and Fischer said it's important that businesses supplying masks to the public and employees have good information about the products they're providing to assure the best protection possible.

"We wanted to develop a simple, low-cost method that we could share with others in the community to encourage the testing of materials, masks prototypes and fittings," Fischer said. "The parts for the test apparatus are accessible and easy to assemble, and we've shown that they can provide helpful information about the effectiveness of masking."

Westman said he put the information immediately to use: "We were trying to make a decision on what type of face covering to purchase in volume, and little information was available on these new materials that were being used."

The masks that he was about to purchase for the "Cover Durham" initiative?

"They were no good," Westman said. "The notion that 'anything is better than nothing' didn't hold true."

Artificial molecules could one day form the information unit of a new type of computer or be the basis for programmable substances. The information would be encoded in the spatial arrangement of the individual atoms - similar to how the sequence of base pairs determines the information content of DNA, or sequences of zeros and ones form the memory of computers.

Researchers at the University of California, Berkeley, and Ruhr-Universität Bochum (RUB) have taken a step towards this vision. They showed that atom probe tomography can be used to read a complex spatial arrangement of metal ions in multivariate metal-organic frameworks.

Metal-organic frameworks (MOFs) are crystalline porous networks of multi-metal nodes linked together by organic units to form a well-defined structure. To encode information using a sequence of metals, it is essential to be first able to read the metal arrangement. However, reading the arrangement was extremely challenging. Recently, the interest in characterizing metal sequences is growing because of the extensive information such multivariate structures would be able to offer.

Fundamentally, there was no method to read the metal sequence in MOFs. In the current study, the research team has successfully done so by using atom probe tomography (APT), in which the Bochum-based materials scientist Tong Li is an expert. The researchers chose MOF-74, made by the Yaghi group in 2005, as an object of interest. They designed the MOFs with mixed combinations of cobalt, cadmium, lead, and manganese, and then decrypted their spatial structure using APT.

Li, professor and head of the Atomic-Scale Characterisation research group at the Institute for Materials at RUB, describes the method together with Dr. Zhe Ji and Professor Omar Yaghi from UC Berkeley in the journal Science, published online on August 7, 2020.

Just as sophisticated as biology

In the future, MOFs could form the basis of programmable chemical molecules: for instance, an MOF could be programmed to introduce an active pharmaceutical ingredient into the body to target infected cells and then break down the active ingredient into harmless substances once it is no longer needed. Or MOFs could be programmed to release different drugs at different times.

"This is very powerful, because you are basically coding the behavior of molecules leaving the pores," Yaghi said.

They could also be used to capture CO2 and, at the same time, convert the CO2 into a useful raw material for the chemical industry.

"In the long term, such structures with programmed atomic sequences can completely change our way of thinking about material synthesis," write the authors. "The synthetic world could reach a whole new level of precision and sophistication that has previously been reserved for biology."