Tech

URBANA, Ill. - Corn growers can choose from a wide array of products to make the most of their crop, but the latest could bring seaweed extract to a field near you. The marine product is just one class in a growing market of crop biostimulants marketed for corn.

Biostimulants benefit crops and soil, but the dizzying array of products has farmers confused, according to Fred Below, corn and soybean researcher at the University of Illinois.

"Farmers hear the term 'plant biostimulant' and think they all do the same thing, and can be used in the same way at the same time. But that's not the case. There's huge confusion over what these products do, and when and how they should be used," says Below, professor in the Department of Crop Sciences at Illinois.

To quell the confusion, Below, along with doctoral student Connor Sible and research specialist Juliann Seebauer, categorized available biostimulant products into eight classes based on their modes of action. Their review, which includes summaries of product composition, mechanisms, efficacy, and application considerations, is published in the journal Agronomy.

Generally, plant biostimulants enhance natural processes in plants or soil that, in turn, boost crop quality and yield through enhanced nutrient uptake, nutrient efficiency, or stress tolerance.

According to the researchers' classification system, half of the products are live microorganisms, including nitrogen-fixing bacteria, mycorrhizal fungi, phosphorus-solubilizing microbes, or other beneficial microbes. The other half are chemistries or chemical byproducts from "formerly living" organisms, as Sible puts it. These include seaweed extracts, humic and fulvic acids, concentrated enzymes, and biochar.

It's not always completely clear how or why biostimulants work the way they do, but Sible and Below say there's a time and a place for each. It's up to the grower to consider which biostimulant fits their goal.

"When we talk to growers, that's the first thing we say. What is the problem you're having, and what is it you're trying to accomplish? Then we can suggest which product from this or that biostimulant category might be your best bet," Below says.

Sible adds, "Sometimes farmers will try these products because the sales pitch sounds good, but they won't get the response they want in the field. So they'll walk away from all biostimulants. Those kinds of poor outcomes could be prevented with more information. That's why we felt this was important. We're actively researching these products to help growers understand what they are and how they work, so they can select the right one for their production system."

Many of the products target nutrient management, with an eye toward reducing or replacing application of synthetic fertilizers. For example, soybean growers are familiar with nitrogen-fixing microorganisms, but Sible says new technologies, including gene editing, are enabling these microbes to thrive in the corn root zone as well.

"We see in our research that these products can help you be more efficient with your fertilizer," he says. "It's all about better management and stewardship of nutrients. If we can add something to our fertilizer plan to make that happen, it's a win-win."

Plant biostimulants aren't new. Specialty growers have applied nitrogen-fixing bacteria, mycorrhizal fungus, seaweed extracts, and similar products for years. But as start-up companies have scaled up production or partnered with big seed and fertilizer companies, they've started eyeing the row crop market.

"All the big companies have partnerships in the biological world now, because it's viewed as part of sustainability or regenerative ag. Some of these products purport to have soil health benefits, and that's all the rage," Below says.

Sible adds that some of the big seed companies are already coating seeds with live inoculants to give seedlings a solid start. "A lot of growers are actually using biostimulants without necessarily knowing it."

Seed coatings are only one method of application. Below says including biostimulant application with standard management practices, such as in-furrow application at seeding or during an herbicide or fungicide pass, provides a free ride for the products.

"When biostimulants can go in with practices that are already being done, that makes their application cost-effective," he says.

Sible notes the average cost of biostimulants is $8 to $12 per acre, but some of the microbial products push $20 to $25. Despite the expense, Below says a lot of farmers are willing to invest this year.

"Commodity prices are really quite high right now, so farmers might be thinking, 'Why don't I try something I normally wouldn't try?' We just want to have them try something that has a greater likelihood to be worthwhile," he says.

Researchers from Skoltech have found a way to help computer vision algorithms process satellite images of the Earth more accurately even with very limited data for training. This will make various remote sensing tasks easier for machines and ultimately the people who use their data. The paper outlining the new results was published in the journal Remote Sensing.

Researchers have been using computer vision and machine learning techniques to help with environmental monitoring for a while now. Tasks that may seem tedious and prone to human error are normally a piece of cake for algorithms. But before a neural network can successfully, say, discriminate between the kinds of trees in a forested area, it needs to be trained, and therein lies a challenge.

Satellite images are not your average cell phone photos, which you can take by the dozen in a moment: There are only so many shots available per orbit, the resolution is limited, and clouds can always get in the way. So, getting enough well-labeled images to train a neural network can be a nuisance, and scientists and engineers have created workarounds in the form of image augmentation.

"While they are very powerful, neural networks demand a lot of training data to achieve top results. Unfortunately, in practical tasks, we usually don't have enough data. To overcome this issue, data scientists apply various techniques that artificially increase datasets. One of the most popular methods is called image augmentation. It transforms images to add variability," Sergei Nesteruk, Skoltech PhD student and co-author of the paper, explains.

Skoltech Professor Ivan Oseledets and his colleagues developed an augmentation method called MixChannel for multispectral satellite images. This method is based on substituting bands from original images with the same bands from images of another date covering the same area.

"It is easy to use image augmentation for generic RGB images. But multispectral data is very complicated, and there was no efficient way to augment it. MixChannel is the novel augmentation technique designed to work specifically with multispectral data," Svetlana Illarionova, another co-author of the paper and Skoltech PhD student, says.

To test their approach, the team used Sentinel-2 satellite images of conifer and deciduous boreal forests in the Arkhangelsk region of northern European Russia to train a convolutional neural network to classify these forests. "A straightforward approach for training a CNN classification model is to take a set of available satellite images for a given territory during a period of active vegetation. The training set is constructed by taking a random patch of a large image. ... However, if we test the obtained model on an image taken on a date that was not included in the training set, the accuracy can drop dramatically," the authors write.

Since it is normally quite cloudy in the Arkhangelsk region, the number of satisfactory satellite images was severely limited - to just six, in fact. But despite the small sample size, the new approach outperformed state-of-the-art solutions when tested with three neural networks, and, as the authors note, it can be combined with other augmentation methods for even more training data.

Other remote sensing-related tasks this approach can help with include various environmental studies and precision agriculture - basically whenever you have medium spatial resolution data and not a lot of images available. In further work, scientists will expand the method to deal with more land cover types and larger areas with different environmental conditions.

Scientists on the hunt for an unconventional kind of superconductor have produced the most compelling evidence to date that they've found one. In a pair of papers, researchers at the University of Maryland's (UMD) Quantum Materials Center (QMC) and colleagues have shown that uranium ditelluride (or UTe2 for short) displays many of the hallmarks of a topological superconductor--a material that may unlock new ways to build quantum computers and other futuristic devices.

"Nature can be wicked," says Johnpierre Paglione, a professor of physics at UMD, the director of QMC and senior author on one of the papers. "There could be other reasons we're seeing all this wacky stuff, but honestly, in my career, I've never seen anything like it."

All superconductors carry electrical currents without any resistance. It's kind of their thing. The wiring behind your walls can't rival this feat, which is one of many reasons that large coils of superconducting wires and not normal copper wires have been used in MRI machines and other scientific equipment for decades.

But superconductors achieve their super-conductance in different ways. Since the early 2000s, scientists have been looking for a special kind of superconductor, one that relies on an intricate choreography of the subatomic particles that actually carry its current.

This choreography has a surprising director: a branch of mathematics called topology. Topology is a way of grouping together shapes that can be gently transformed into one another through pushing and pulling. For example, a ball of dough can be shaped into a loaf of bread or a pizza pie, but you can't make it into a donut without poking a hole in it. The upshot is that, topologically speaking, a loaf and a pie are identical, while a donut is different. In a topological superconductor, electrons perform a dance around each other while circling something akin to the hole in the center of a donut.

Unfortunately, there's no good way to slice a superconductor open and zoom in on these electronic dance moves. At the moment, the best way to tell whether or not electrons are boogieing on an abstract donut is to observe how a material behaves in experiments. Until now, no superconductor has been conclusively shown to be topological, but the new papers show that UTe2 looks, swims and quacks like the right kind of topological duck.

One study, by Paglione's team in collaboration with the group of Aharon Kapitulnik at Stanford University, reveals that not one but two kinds of superconductivity exist simultaneously in UTe2. Using this result, as well as the way light is altered when it bounces off the material (in addition to previously published experimental evidence), they were able to narrow down the types of superconductivity that are present to two options, both of which theorists believe are topological. They published their findings on July 15, 2021, in the journal Science.

In another study, a team led by Steven Anlage, a professor of physics at UMD and a member of QMC, revealed unusual behavior on the surface of the same material. Their findings are consistent with the long-sought-after phenomenon of topologically protected Majorana modes. Majorana modes, exotic particles that behave a bit like half of an electron, are predicted to arise on the surface of topological superconductors. These particles particularly excite scientists because they might be a foundation for robust quantum computers. Anlage and his team reported their results in a paper published May 21, 2021 in the journal Nature Communications.

Superconductors only reveal their special characteristics below a certain temperature, much like water only freezes below zero Celsius. In normal superconductors, electrons pair up into a two-person conga line, following each other through the metal. But in some rare cases, the electron couples perform a circular dance around each other, more akin to a waltz. The topological case is even more special--the circular dance of the electrons contains a vortex, like the eye amidst the swirling winds of a hurricane. Once electrons pair up in this way, the vortex is hard to get rid of, which is what makes a topological superconductor distinct from one with a simple, fair-weather electron dance.

Back in 2018, Paglione's team, in collaboration with the team of Nicholas Butch, an adjunct associate professor of physics at UMD and a physicist at the National Institute of Standards and Technology (NIST), unexpectedly discovered that UTe2 was a superconductor. Right away, it was clear that it wasn't your average superconductor. Most notably, it seemed unphased by large magnetic fields, which normally destroy superconductivity by splitting up the electron dance couples. This was the first clue that the electron pairs in UTe2 hold onto each other more tightly than usual, likely because their paired dance is circular. This garnered a lot of interest and further research from others in the field.

"It's kind of like a perfect storm superconductor," says Anlage. "It's combining a lot of different things that no one's ever seen combined before."

In the new Science paper, Paglione and his collaborators reported two new measurements that reveal the internal structure of UTe2. The UMD team measured the material's specific heat, which characterizes how much energy it takes to heat it up by one degree. They measured the specific heat at different starting temperatures and watched it change as the sample became superconducting.

"Normally there's a big jump in specific heat at the superconducting transition," says Paglione. "But we see that there's actually two jumps. So that's evidence of actually two superconducting transitions, not just one. And that's highly unusual."

The two jumps suggested that electrons in UTe2 can pair up to perform either of two distinct dance patterns.

In a second measurement, the Stanford team shone laser light onto a piece of UTe2 and noticed that the light reflecting back was a bit twisted. If they sent in light bobbing up and down, the reflected light bobbed mostly up and down but also a bit left and right. This meant something inside the superconductor was twisting up the light and not untwisting it on its way out.

Kapitulnik's team at Stanford also found that a magnetic field could coerce UTe2 into twisting light one way or the other. If they applied a magnetic field pointing up as the sample became superconducting, the light coming out would be tilted to the left. If they pointed the magnetic field down, the light tilted to the right. This told that researchers that, for the electrons dancing inside the sample, there was something special about the up and down directions of the crystal.

To sort out what all this meant for the electrons dancing in the superconductor, the researchers enlisted the help of Daniel F. Agterberg, a theorist and professor of physics at the University of Wisconsin-Milwaukee and a co-author of the Science paper. According to the theory, the way uranium and tellurium atoms are arranged inside the UTe2 crystal allows electron couples to team up in eight different dance configurations. Since the specific heat measurement shows that two dances are going on at the same time, Agterberg enumerated all the different ways to pair these eight dances together. The twisted nature of the reflected light and the coercive power of a magnetic field along the up-down axis cut the possibilities down to four. Previous results showing the robustness of UTe2's superconductivity under large magnetic fields further constrained it to only two of those dance pairs, both of which form a vortex and indicate a stormy, topological dance.

"What's interesting is that given the constraints of what we've seen experimentally, our best theory points to a certainty that the superconducting state is topological," says Paglione.

If the nature of superconductivity in a material is topological, the resistance will still go to zero in the bulk of the material, but on the surface something unique will happen: Particles, known as Majorana modes, will appear and form a fluid that is not a superconductor. These particles also remain on the surface despite defects in the material or small disruptions from the environment. Researchers have proposed that, thanks to the unique properties of these particles, they might be a good foundation for quantum computers. Encoding a piece of quantum information into several Majoranas that are far apart makes the information virtually immune to local disturbances that, so far, have been the bane of quantum computers.

Anlage's team wanted to probe the surface of UTe2 more directly to see if they could spot signatures of this Majorana sea. To do that, they sent microwaves towards a chunk UTe2, and measured the microwaves that came out on the other side. They compared the output with and without the sample, which allowed them to test properties of the bulk and the surface simultaneously.

The surface leaves an imprint on the strength of the microwaves, leading to an output that bobs up and down in sync with the input, but slightly subdued. But since the bulk is a superconductor, it offers no resistance to the microwaves and doesn't change their strength. Instead, it slows them down, causing delays that make the output bob up and down out of sync with the input. By looking at the out-of-sync parts of the response, the researchers determined how many of the electrons inside the material participate in the paired dance at various temperatures. They found that the behavior agreed with the circular dances suggested by Paglione's team.

Perhaps more importantly, the in-sync part of the microwave response showed that the surface of UTe2 isn't superconducting. This is unusual, since superconductivity is usually contagious: Putting a regular metal close to a superconductor spreads superconductivity to the metal. But the surface of UTe2 didn't seem to catch superconductivity from the bulk--just as expected for a topological superconductor--and instead responded to the microwaves in a way that hasn't been seen before.

"The surface behaves differently from any superconductor we've ever looked at," Anlage says. "And then the question is 'What's the interpretation of that anomalous result?' And one of the interpretations, which would be consistent with all the other data, is that we have this topologically protected surface state that is kind of like a wrapper around the superconductor that you can't get rid of."

It might be tempting to conclude that the surface of UTe2 is covered with a sea of Majorana modes and declare victory. However, extraordinary claims require extraordinary evidence. Anlage and his group have tried to come up with every possible alternative explanation for what they were observing and systematically ruled them out, from oxidization on the surface to light hitting the edges of the sample. Still, it is possible a surprising alternative explanation is yet to be discovered.

"In the back of your head you're always thinking 'Oh, maybe it was cosmic rays', or 'Maybe it was something else,'" says Anlage. "You can never 100% eliminate every other possibility."

For Paglione's part, he says the smoking gun will be nothing short of using surface Majorana modes to perform a quantum computation. However, even if the surface of UTe2 truly has a bunch of Majorana modes, there's currently no straightforward way to isolate and manipulate them. Doing so might be more practical with a thin film of UTe2 instead of the (easier to produce) crystals that were used in these recent experiments.

"We have some proposals to try to make thin films," Paglione says. "Because it's uranium and it's radioactive, it requires some new equipment. The next task would be to actually try to see if we can grow films. And then the next task would be to try to make devices. So that would require several years, but it's not crazy."

Whether UTe2 proves to be the long-awaited topological superconductor or just a pigeon that learned to swim and quack like a duck, both Paglione and Anlage are excited to keep finding out what the material has in store.

"It's pretty clear though that there's a lot of cool physics in the material," Anlage says. "Whether or not it's Majoranas on the surface is certainly a consequential issue, but it's exploring novel physics which is the most exciting stuff."

WINSTON-SALEM, NC, July 15, 2021 - Answering a charge from the National Science Board, the RegenMed Development Organization (ReMDO), through its RegeneratOR Workforce Development Initiative, has released the results of a national survey of regenerative medicine biomanufacturing knowledge, skills, and abilities needed for successful employment in the regenerative medicine field.

The National Science Board called for the creation of a skilled technical workforce driven by science and engineering in its 2019 report, "The Skilled Technical Workforce: Crafting America's Science and Engineering Enterprise."

"The RegeneratOR initiative has undertaken a necessary early step with its survey by articulating the knowledge, skills and abilities needed to align education and workforce development programs with employer needs," said Gary Green, EdD, Chief Workforce Development Officer for the Wake Forest Institute for Regenerative Medicine (WFIRM), which is working closely with ReMDO on this effort.

Green and colleagues published their findings recently in STEM CELLS Translational Medicine journal. The purpose of the article is to outline the knowledge, skills, and abilities necessary for regenerative medicine biomanufacturing, quantify the skills gap that currently exists between skills required by employers and those acquired by employees and available in the labor market, and make recommendations for the application of these findings.

"Regenerative medicine biomanufacturing represents one of the emerging technology-driven growth sectors. With recent and projected future growth in regenerative medicine, the availability of a knowledgeable and skilled workforce is a critical success factor for business and academic organizations," said Josh Hunsberger, PhD, chief technology officer for ReMDO. "As the field progresses from research to clinical translation and from translation to biomanufacturing, the skill requirements are evolving."
Three levels of preparation are articulated in the research: basic employability skills, core bioscience skills, and regenerative medicine biomanufacturing technical skills. Fifteen skill sets addressing the specialized needs of regenerative medicine and related biotechnology sectors are identified in the survey.

Overall survey results indicate that while regenerative medicine biomanufacturing is experiencing rapid growth, there exists a pronounced lack of needed skills sets in the workforce and an inability to hire for those skills in the labor market.

Based on the survey results, the ReMDO team made five recommendations to develop the workforce development ecosystem.

1. Provide faculty development opportunities in regenerative medicine for kindergarten through 12th grade, community college, and universities (including 4-year colleges) that are aligned with industry needs that support grade/level appropriate learning.
2. Incorporate regenerative medicine principles and applications in STEM-related academic curricula, recognizing the multidisciplinary nature of the field.
3. Provide progressive levels of work-based learning in regenerative medicine, kindergarten through 12th grade to university.
4. Pursue a diverse and inclusive skilled technical workforce in regenerative medicine.
5. Advocate for policy and investments in regenerative medicine and convergent technology workforce development.

"The insights provided by these survey results are an essential starting point to help us prepare for the future of regenerative medicine biomanufacturing," said co-author Anthony Atala, MD, who serves as director of WFIRM. "It is crucial to have a trained and highly skilled work force in place to advance the important research now reaching patients."

A screening tool used to evaluate the need for endometrial cancer biopsies in women frequently misses the signs of this cancer in Black women, according to a new study released today in JAMA Oncology.

Dr. Kemi Doll, the lead researcher, and a gynecologic oncologist with the University of Washington School of Medicine, says that the results of the study suggest that the current non-invasive option of transvaginal ultrasound, or TVUS, to determine the appropriateness of a biopsy is not sufficiently accurate or racially equitable with regards to Black women.

"Black women have an over 90% higher mortality rate after diagnosis of endometrial cancer when compared with White women in the U.S.," Doll said. "This is a long-standing disparity that we have yet to make meaningful progress to address. Although we have focused before on evaluating access to healthcare, in this study we sought to evaluate the guidelines themselves."

In this study using a simulated cohort, TVUS endometrial thickness screening missed over four times more cases of endometrial cancer among Black women versus White women owing to the greater prevalence of fibroids and non-endometrioid histology type that occurs among Black women.

"This puts Black women at a higher risk of false-negative results," Doll said. "That is unacceptable in a group that is already the most vulnerable to the worst outcomes of endometrial cancer."

TVUS is a procedure where an ultrasound probe is inserted about two or three inches into the vagina to thoroughly examine the female reproductive organs, including the uterus, fallopian tubes, ovaries, cervix, and the pelvic area. One clinical pathway for determining whether a biopsy is needed is to do a TVUS to measure the thickness of the endometrium or uterine lining, Doll noted. Usually, a biopsy is then scheduled if the lining is 4 mm or greater, she said.

"But not all endometrial cancer increase the lining thickness," Doll said. "In addition, non-cancerous fibroids can make the lining harder to measure."

The TVUS strategy using a test of endometrial thickness for further biopsies and testing was developed on large population-based studies from Scandinavia, Italy and Hong Kong. Black women were not included in these studies.

With an estimated 61,880 newly diagnosed cases and 12,160 cancer deaths in 2019, endometrial cancer is the fourth most common cancer in the United States and is increasing in incidence each year.

The magnitude of the racial inequity in survival is larger than that within cervical, breast, or colon cancers and is increasing, the report notes. Two independent factors in excess death among Black women are the higher likelihood of advanced stage at diagnosis and the greater prevalence of high risk endometrial cancer among Black women compared with White women.

The research used a simulated retrospective cohort study, based on data from the Surveillance, Epidemiology, and End Results (SEER) national cancer registry 2012-2016 and the U.S. Census data. Another cohort was constructed (again using SEER data), from February 2, 2020 to August 31, 2020, while analysis of the data occurred from September of last year through March 2021.

In all, a total of 367,073 simulated Black and White women with postmenopausal bleeding were evaluated, including 36,708 with endometrial cancer, for this study.

The next step is to do a real-world study to confirm these results, Doll said. But clinicians should realize the potential for missed diagnoses by using only TVUS. Black women with fibroids should discuss a biopsy, instead of relying only on the less-invasive TVUS screening, she added.

BOSTON - New research in humans and mice identifies a particular signaling molecule that can help modify inflammation and the immune system to protect against Alzheimer's disease. The work, which was led by investigators at Massachusetts General Hospital (MGH), is published in Nature.

Cognitive decline associated with Alzheimer's disease develops when neurons begin to die. "Neuron death can be caused by improper immune responses and excessive neuroinflammation--or inflammation in the brain--triggered by high levels of amyloid beta deposits and tau tangles, two hallmarks of Alzheimer's disease," explains the paper's co-senior author Filip Swirski, PhD, who conducted the work while a principal investigator in the Center for Systems Biology at MGH.

"Once neurons start dying in increasing amounts, brain cells called microglia and astrocytes--which are normally nurturing cells that clean up debris--become activated to cause neuroinflammation in an attempt to protect the brain. They are evolutionarily programmed to wipe out a brain region where there is excess neuronal cell death because it may be due to an infection, which must be stopped from spreading," explains co-senior author Rudolph Tanzi, PhD, co-director of the McCance Center for Brain Health at MGH.

In the case of Alzheimer's disease, the neuronal cell death brought on by amyloid beta deposits and tau tangles activates this response. "As neuroinflammation ensues, the amount of cell death is at least 10 times higher than that which was caused by plaques and tangles," says Tanzi. "In fact, without the induction of neuroinflammation, there would be no symptoms of dementia. We know this from 'resilient' brains, in which there are lots of plaques and tangles in an individual's brain but no symptoms at death because there was minimal or no neuroinflammation." Tanzi provides an analogy, noting that amyloid beta is the "match" that lights the spreading "brushfires" of tangles, but only when this leads to increasing numbers of "forest fires" through neuroinflammation that is activated by microglia and astrocytes does one lose enough neurons to suffer cognitive decline and dementia.

This new study in Nature revealed that a subset of astrocytes actually tries to put out the fire by releasing a molecule called interleukin-3 (IL-3), which then converts killer microglial cells back into nurturing and protective cells that no longer wipe out neurons and instead focus on cleaning out amyloid beta deposits and tau tangles.

"There may be important clinical implications to knowing that astrocytes talk to microglia via IL-3 to educate the microglia and help them decrease the severity of Alzheimer's disease," says Swirski. "We can now think about how to use IL-3 to not only help curb the neuroinflammation that carries out the bulk of neuronal cell death in Alzheimer's disease, but also to entice microglia to once again take on the beneficial task of clearing away the deposits and tangles that are the initiating pathology of Alzheimer's disease."

"It was surprising to find IL-3 in the brain," says first author Cameron McAlpine, PhD, then an instructor in the Center for Systems Biology. "Our findings suggest that communication between astrocytes and microglia, via IL-3, is an important mechanism that wards off Alzheimer's disease by instructing microglia to adapt protective functions. With further study, IL-3 signaling may provide a new therapeutic opportunity to combat neurological diseases."

An analysis of the tone used in pandemic-related social media posts from U.S. Congress members over an 8-month period in 2020 finds clear partisan differences, with Democrats using a slightly negative tone compared with Republicans, who appeared to use more strongly positive language in their COVID-19 messaging. Democrats were also far more likely than Republicans to use neutral language. The study also indicates that tone plays a critical role in elite communications, finding that the public engages more with content that has a negative tone. The study authors note that messaging from political elites during a crisis such as the COVID-19 pandemic holds a heightened significance for public health, information sharing, and personal behavior, with a message's tone either boosting public confidence in the provided information or fueling anxieties. Heightened political polarization can lead to fractured messaging around the issue. To investigate differences in the tone of pandemic-related social media messages from elite Democrat and Republican politicians, Janet Box-Steffensmeier and Laura Moses collected posts about COVID-19 generated by members of Congress between March 1 and October 30, 2020 using a public insights tool called CrowdTangle, which is owned and operated by Facebook. The researchers then used the VADER (Valence Aware Dictionary and sEntiment Reasoner) sentiment analysis tool to evaluate the tone of the messages. The findings revealed partisan differences in tone for pandemic-related messages, with Democrats far more likely to use neutral language than Republicans and employing a comparatively more negative tone, although both parties used a more positive tone overall. Democrats also posted about COVID-19 more than Republicans, averaging 26 posts per member compared to 18 during the study period. The findings also suggest that the more conservative a Congress member is, the more the public engaged with their social media content, although posts from liberal members were more likely to be shared.

New York, NY--July 14, 2021-- A previously unknown kind of human brain cell appears to help people center themselves in their personal maps of the world, according to a new study from neuroscientists at Columbia Engineering. This discovery sheds light on the cellular mechanisms underlying navigation and memory in humans, as well as what parts of the brain might get disrupted during the kinds of memory impairments common in neurodegenerative diseases such as Alzheimer's.

There are two strategies with which humans and animals navigate and orient themselves. One involves locating places, distances and directions in "allocentric" or other-centered frames of reference rooted in the external world. The other strategy involves "egocentric" frames of reference that are centered on the self.

Whenever you use a mobile phone app to find driving directions, it will likely employ both these modes of navigation. When you first type in an address, it will normally show you the address on a map from an allocentric perspective, with 'north' at the top and 'south' at the bottom. When you then go to route view, it will switch to an egocentric perspective where 'ahead' is at the top and 'behind' is at the bottom.

Scientists first discovered brain cells linked with allocentric frames of reference in rats in 1971 -- "place cells" that may, for example, indicate that one is located in the northeast corner of an area. Other allocentric spatial cell types include head-direction cells that may activate whenever one is navigating south, or border cells that may respond when a boundary is located to the west.

In the past decade, researchers began investigating how rat brains mapped egocentric frames of reference. Two years ago, scientists at Dartmouth College in Hanover, New Hampshire, identified a brain region in rats called the postrhinal cortex in which egocentrically tuned cells are abundant. However, it remained poorly understood what brain cells formed the basis of egocentric spatial maps in humans.

"In humans it is only rarely possible to directly record the activity of single neurons from the brain, due to ethical reasons," said Lukas Kunz, a postdoctoral research scientist at Columbia University's Department of Biomedical Engineering and first author of the new study. "There are techniques like fMRI or EEG, which allow us to indirectly measure neural activity from healthy human brains, but this neural activity reflects the sum activity of millions of neurons, which does not allow for direct conclusions about the working principles of single neurons."

In the new study, neuroscientists from the United States and Germany investigated 15 epilepsy patients at the University of Freiburg's Medical Center in Germany. These volunteers were implanted with electrodes to help doctors monitor their disorder.

The researchers asked the volunteers to perform computer tasks that explored their ability to navigate through virtual environments and to remember where many different objects were located there. At the same time, the scientists recorded the activity of more than 1,400 single neurons in multiple brain regions across all the participants.

The scientists identified more than 160 neurons that behaved like egocentric spatial cell types, activating when specific parts of the virtual environment were ahead, behind, to the left, or to the right of the patients, or when points in space were close to or far away from the patients.

"We are now the first to report egocentric spatial cell types in humans," Kunz said. The scientists published their study, "A neural code for egocentric spatial maps in the human medial temporal lobe," in the journal Neuron on July 14, 2021.

These "egocentric bearing cells" likely encode spatial information on a mental map centered on each person. "This is presumably important for everyday life, when humans try to orient themselves in their environments and when they navigate along routes," said Joshua Jacobs, associate professor of biomedical engineering at Columbia Engineering and senior author of the study.

These egocentric bearing cells were particularly ample in the parahippocampal cortex, a region located deep within the brain that prior work suggested is the human equivalent of the rodent postrhinal cortex. Egocentric bearing cells comprised about 25% of all neurons in the parahippocampal cortex. "Previous studies had shown that patients with damage to this brain region are disoriented, presumably because their egocentric bearing cells were affected," Kunz said.

The researchers also found these egocentric bearing cells showed increases in activity when the patients used their memory to successfully recall the locations of objects they had found in the virtual environments. "This suggests these cells are not only relevant for navigation, but also play a role in correctly remembering past experiences," Kunz said.

"Memories consist of multiple different elements, such as a specific event, the place where the event happened, and the time when the event happened," Kunz said. "We believe that there are different neural systems for the different components of these memories. Egocentric bearing cells are presumably particularly involved in processing the spatial information of the memories."

These findings may illuminate what might go wrong in people with memory deficits, including patients with neurodegenerative diseases such as Alzheimer's. "Their egocentric bearing cells may not function correctly, or may have been destroyed for some reason, such as a stroke, a brain tumor, or dementia," Jacobs said.

These new findings do not answer how one might deal with such memory impairments. "There is still a lot of research to do before memory impairments can be treated successfully," Kunz cautioned.

In the future, the researchers want to see why exactly any given egocentric bearing cell is tuned to whatever point in space it is focused on. Currently, Kunz and his colleagues assume that multiple different spatial cues, such as objects, spatial boundaries and landmarks, combine to influence the position of these reference points. The scientists can examine the influence these cues have on the location of these reference points by removing these cues from environments during experiments.

"Another important question is how egocentric bearing cells interact with allocentric spatial cell types, Kunz said. "We currently hypothesize that egocentric bearing cells provide essential input to allocentric spatial cell types. By understanding this, future studies could explain how the tuning of allocentric spatial cell types is influenced by the functioning of egocentric bearing cells."

A football is not a quantum particle. There are crucial differences between the things we know from everyday life and tiny quantum objects. Quantum phenomena are usually very fragile. To study them, one normally uses only a small number of particles, well shielded from the environment, at the lowest possible temperatures.

Through a collaboration between the University of Vienna, the Austrian Academy of Sciences and TU Wien, however, it has now been possible to measure a hot glass sphere consisting of about one billion atoms with unprecedented precision and to control it at the quantum level. Its movement was deliberately slowed down until it assumed the ground state of lowest possible energy. The measurement method almost reached the limit set by Heisenberg's uncertainty principle - physics just does not allow for any more precision than that. This was made possible by applying special methods from control engineering to quantum systems. The results have now been published in the scientific journal "Nature".

Perfect precision is impossible

The measurement influences the measured object - this is one of the most basic principles of quantum theory. "Werner Heisenberg came up with a famous thought experiment - the so-called Heisenberg microscope" explains physicist Lorenzo Magrini, the first author of the study from the University of Vienna. "If you want to measure the position of an object very precisely under a microscope, you have to use light with the shortest possible wavelength. But short wavelength means higher energy, so the movement of the particle is disturbed more strongly." You just cannot accurately measure the location and the state of motion of a particle at the same time. The product of their uncertainties is always limited by Planck's constant - this is the so-called Heisenberg uncertainty principle. However, it is possible to find out how close one can get to this limit set by nature.

Prof. Markus Aspelmeyer's team at the University of Vienna is investigating this using a glass sphere with a diameter of less than 200 nanometres, consisting of about one billion particles - very small by our everyday standards, but still very large compared to objects usually studied in quantum physics.

The glass sphere can be kept in place with a laser beam. The atoms of the sphere are heated up by the laser, and the internal temperature of the sphere rises to several hundred degrees Celsius. This means that the atoms of the glass sphere are wobbling around violently. In the experiment, however, it was not the wobbling movements of the individual atoms that were studied, but the collective motion of the sphere in the laser trap. "These are two completely different things, just as the movement of a pendulum in a pendulum clock is something different from the movement of the individual atoms inside the pendulum," says Markus Aspelmeyer.

Quantum control technology

The goal was to precisely control the pendulum motion of the glass sphere on a quantum level, even though the glass sphere is actually a macroscopic object. This can only be achieved using a perfectly designed control system, carefully adjusted to the experiment. This task was taken on by the team of Prof. Andreas Kugi at TU Wien.

"Control engineering is about influencing systems in such a way that they exhibit a desired behaviour independent of disturbances and parameter fluctuations," says Andreas Kugi. "This can be a robot arm, for example, a production line in a factory, or even the temperature of a blast furnace." Applying modern methods of control engineering to quantum systems opens up new possibilities. "However, one also has to face challenges that do not exist in classical system theory and control engineering," explains Kugi. "In classical control engineering, the measurement has no or negligible influence on the system. In quantum physics, however, this influence cannot be avoided, for very fundamental reasons. We therefore also have to develop novel control engineering methods."

This was a success: the light backscattered by the glass sphere was detected as thoroughly as possible, using a sophisticated microscopy technique. By analyzing the scattered light, the position of the sphere was determined in real time, and then an electric field was continuously adjusted in such a way that it permanently counteracted the movement of the glass sphere. In this way, it was possible to slow down the entire sphere and put it into a state of motion that corresponds to the quantum-physical ground state, i.e. the state of the smallest possible kinetic energy - despite the fact that it is a relatively large object at high temperatures, whose atoms wobble vigorously.

Promising cooperation between physics and control engineering

"You always have to consider spatial and kinetic uncertainty together. Overall, the quantum uncertainty of the glass sphere was only 1.7 times Planck's quantum of action," says Lorenzo Magrini. Planck's constant would be the absolute theoretical lower limit, never before has an experiment come that close to the absolute quantum limit using an object of this size. The kinetic energy measured in the experiment corresponded to a temperature of just 5 micro-Kelvin, i.e. 5 millionths of a degree above absolute zero. The movement of the glass sphere as a whole can therefore be assigned an extremely low temperature even if the atoms that make up the sphere are very hot.

This success shows the great potential of this new combination of quantum physics and control engineering: both research groups want to continue working in this direction and exploit know-how from control engineering to enable even better and more precisely controlled quantum experiments. There are many possible applications for this, ranging from quantum sensors to technologies from the field of quantum information.

Mitotic Catastrophe Database (MCDB) is a proprietary, standard, and comprehensive database for Mitotic catastrophe (MC) related data facilitating the exploration of MC for all researchers in the fields of medicinal chemistry, molecular biology, bioinformatics and oncology.

MC is a form of programmed cell death induced by mitotic process disorders, which is important in tumor prevention, development, and drug resistance. As availability of MC data underpins tumor-related biomedical and clinical studies, the development of a professional and comprehensive database to curate MC-related data is a matter of increasing priority.

MCDB consists of 1214 genes/proteins and 5014 compounds collected and organized from more than 8000 research articles. MCDB defines the confidence level, classification criteria, and uniform naming rules for MC-related data, which greatly improves data reliability and retrievability. MCDB also develops protein sequence alignment and target prediction functions. The former can be used to predict new potential MC-related genes and proteins, and the latter can facilitate the identification of potential target proteins of unknown MC-related compounds.

Forest fires are already a global threat. "But considering how climate change is progressing, we are probably only at the beginning of a future that will see more and bigger forest fires," explains Rupert Seidl, Professor of Ecosystem Dynamics and Forest Management in Mountain Landscapes at TUM.

In many places, fire is part of the natural environment, and many tree species have become naturally adapted to recurrent fires. These adaptations range from particularly thick bark, which protects the sensitive cambium in the trunk from the fire, to the cones of certain types of pine, which open only due to the heat of fire, allowing a quick regeneration and recovery of affected woodland .

AI is accelerating ecosystem models

"The interaction between climate, forest fires, and other processes in the forest ecosystem is very complex, and sophisticated process-based simulation models are required to take account of the different interactions appropriately," explains Prof. Seidl. A method that has been developed at TUM is using artificial intelligence to significantly expand the field of use of these complex models.

This method involves the training of a deep neural network in order to imitate the behavior of a complex simulation model as effectively as possible. The neural network learns on the basis of how the ecosystem responds to differing environmental influences, but does so using only a fraction of the computing power that would otherwise be necessary for large-scale simulation models. "This allows us to carry out spatially high-resolution simulations of areas of forest that stretch across several million hectares," explains scientist Dr. Werner Rammer.

Forecast for the forests in Yellowstone National Park

The simulations completed by the team of scientists include simulations for the "Greater Yellowstone Ecosystem", which has the world-famous Yellowstone National Park at its heart. This area, which is approximately 8 million hectares in size, is situated in the Rocky Mountains and is largely untouched. The researchers at the TUM have worked with American colleagues to determine how different climate scenarios could affect the frequency of forest fires in this region in the 21st century, and which areas of forest cannot regenerate successfully following a forest fire.

Depending on the climate change scenario, the study has found that by the end of the century, the current forest coverage will have disappeared in 28 to 59 percent of the region. Particularly affected were the forests in the sub-alpine zone near the tree line, where the species of tree are naturally less adapted to fire, and the areas on the Yellowstone Plateau, where the relatively flat topography is mostly unable to stop the fire from spreading.

Climate change is causing significant changes to forest ecosystems

The regeneration of the forest in the region under investigation is at threat for several reasons: If the fires get bigger and the distances between the surviving trees also increase, too few seeds will make their way onto the ground. If the climate gets hotter and drier in the future, the vulnerable young trees won't survive, and if there are too many fires, the trees won't reach the age at which they themselves yield seeds.

"By 2100, the Greater Yellowstone Ecosystem is expected to have changed more than it has in the last 10,000 years, and will therefore look significantly different than it does today," explains Rammer. "The loss of today's forest vegetation is leading to a reduction in the carbon which is stored in the ecosystem, and will also have a profound impact on the biodiversity and recreational value of this iconic landscape."

The potential developmental trends identified in the study are also intended to help visitors to the national park understand the consequences of climate change and the urgency of the climate protection measures. In the next step, the research team will be using AI to estimate the long-term impact of the problems caused by climate change in the forests of Europe.

Skoltech researchers and their colleagues from the U.S. and Singapore have created a neural network that can help tweak semiconductor crystals in a controlled fashion to achieve superior properties for electronics. This enables a new direction of development of next-generation chips and solar cells by exploiting a controllable deformation that may change the properties of a material on the fly. The paper was published in the journal npj Computational Materials.

Materials at the nanoscale can withstand major deformation. In what's called the strained state, they can exhibit remarkable optical, thermal, electronic, and other properties due to a change in interatomic distances. The intrinsic properties of a strained material may change, with the semiconducting silicon, for instance, transforming into a material that conducts the electric current freely.

Moreover, by varying the strain level, one can change these properties on demand. That notion has given rise to an entire field of inquiry: elastic strain engineering, or ESE. The approach can be used, for example, to modify the performance of semiconductors, providing a potential workaround for the impending Moore's law limit, when we exhaust our other options for increasing chip performance. Another possible application lies within the field of solar cell development. As study co-author Alexander Shapeev from Skoltech explains, one can design a solar cell with tunable properties that can be changed on demand in order to maximize performance and adapt to external circumstances.

In their previous work, Skoltech PhD graduate Evgenii Tsymbalov, Associate Professor Alexander Shapeev, and their colleagues used ESE to turn nanoscale diamond needles from insulating to highly conductive and metal-like, providing an insight into the range of possibilities with this technology. Now, the team has introduced a convolutional neural network architecture that can guide ESE efforts for semiconductors.

"The neural network we have designed takes the strain tensor as an input and predicts the electronic band structure -- a physical 'snapshot' that describes the electronic properties of a strained material. It may then be used to calculate any properties of interest, including the bandgap, its properties, and electron effective mass tensor," Shapeev said.

This work continues prior research and expands on it. "We go beyond the previously used approaches by designing and implementing a tailored model based on the convolutional neural network architecture, for the ESE task," Tsymbalov said. "We also take the physical properties and symmetries into account in order to improve the model."

The approach combines various data sources, for example, the computationally cheap yet inaccurate with the precise but expensive ones in order to boost the accuracy and convergence of the model. "Another distinct feature is active learning - we allow the model to guess what data may be the most useful to obtain in the next training stage, and use it for training. In the final stage, the network is trained on a set of computationally expensive data from the very accurate GW-based calculations, and this procedure allows us to reduce the amount of computations needed," Tsymbalov added.

The team notes that its new neural network is "more versatile, accurate, and efficient in its capacity to facilitate autonomous deep learning of the electronic band structure of crystalline solids" than state-of-the-art solutions. This makes it faster and more accurate at search and optimization within the strain space, which leads to the optimal strain values for given figures of merit.

In their earlier work, the researchers tested a previous iteration of the model in the scenario of a repeating in situ experiment on diamond. "Alas, for now there is no device that can deform the diamond with an arbitrary 6D deformation tensor, yet there are teams and labs pursuing this direction from the experimental point of view," Tsymbalov commented.

This study is part of a yearslong collaboration between Skoltech, the Massachusetts Institute of Technology, and Nanyang Technological University, with the Skoltech scientists focused on the computational and machine learning aspect and their colleagues in charge of the physical component of the work. "We are currently working on our next paper, which is devoted to the boundaries of admissible elastic strains. It is an important topic since the theoretical limits of safe elastic deformation for ESE are yet to be discovered," the researcher concluded.

Community Health Workers Can Play a Role in Identifying Health-Related Social Needs in Patients

Addressing patients' health-related social needs, like housing and food security, is integral to patient care. Federally Qualified Health Centers are leaders in screening for and addressing patients' health-related social needs. However, screening practices vary. This variation is relatively unexplored, particularly with regards to organizational and state policy influences. Study authors conducted in-person, qualitative interviews at Michigan FQHCs to examine how screening approaches vary in the context of statewide social needs screening initiatives and structural factors. They identified four themes:

1) Statewide initiatives and local leadership drove variation in screening practices.

2) Community health workers played an integral role in identifying patients' needs and their roles often shifted from "screener" to "implementer."

3) Social needs screening data was variably integrated into electronic health records and infrequently used for population health management and

4) Sites experienced barriers to social needs screening that limited their perceived impact and sustainability.

FQHCs placed value on the role of community health workers, on sustainable initiatives and on funding to support continued social needs screening in primary care settings, according to the study. Determining the optimal approaches to screening is important to advancing community health.

The Earth contains about one trillion species of microbes -- only about one-tenth of which have been identified. A single human can house 100 trillion microbes, creating a single microbiome that serves an ecosystem of microbes.

Microbes connect and transform in myriad ways, creating and combining and separating microbiomes anew. How can we begin to parse out how microbiomes differ, how they are similar, how they evolved and how they may change in the future?

An international team of researchers may have the answer. They published a scale-free, fully connected search-based network to explore the connectedness of microbiomes across the world on July 13 in mSystems.

"The microbiome composition, a fundamental feature of all microbiota -- microbes sharing a particular characteristic such as site or geological period -- is shaped by a plethora of environmental factors," said co-first author JING Gongchao, a researcher in the Single-Cell Center in Qingdao Institute of BioEnergy and Bioprocess Technology (QIBEBT) of the Chinese Academy of Sciences (CAS). "However, it remains unclear whether and how compositional changes at the 'community-to-community' level among microbiomes are linked to the origin and evolution of global microbiome diversity."

To better understand how the vast number of varying microbe species evolved, JING and ZHANG Yufeng, a graduate student from Qingdao University, built a global "microbiome transition network" (MTN) that connects, based on their composition similarities, 177,022 microbiomes from 20 diverse ecosystems that include the plethora of ecological niches on human body and in the environment.

They used the Microbiome Search Engine (MSE; http://mse.ac.cn), a software developed by the team. MSE can construct the global transition network of microbiomes under three hours, and return the closest neighbors of a query microbiome in less than 0.5 second.

Interestingly, the global MTN is scale-free, which is similar to the Internet or the social network among human individuals. In this kind of networks, most nodes are each connected to a small number of other nodes, yet a small portion of nodes are connected to many other nodes. Such network structure ensures a strong degree of tolerance of the network against accidental perturbation.

"We drew the first global microbiome transition roadmap to illustrate the potential yet most likely paths to explain the evolution process of global microbiomes," explained SU Xiaoquan, a professor at Qingdao University and one senior author of the study, noting that the roadmap traces high similarities between microbiomes. "Although the compositions are distinct by habitat, each microbiome is, on average, only six "relatives" (or seven "steps") from any other microbiome on Earth, indicating the inherent homology and common origin of the microbiomes at the global scale."

On the other hand, information from the global MTN can indicate important information, such as evolvement or interaction of microbiomes. For example, the roadmap revealed that, the oceans are the most likely microbiomes that interact with beach sands and marine fishes, while soil and fresh water are the gateway of microbial exchange between the environment and plants or humans.

With the rapid change in climate as well as civilization on Earth, numerous microbiomes are disappearing, and emerging, every day. Although only a tiny proportion of them were recorded via metagenome sequencing, to construct and update the global MTN can be a "mission impossible", without powerful search engines and standardized databases for microbiomes such as those in MSE.

"Such search-based global microbiome networks, reconstructed within hours on just one computing mode via MSE, provide a readily expanded reference for tracing the origin and evolution of existing microbiomes, and perhaps for guiding the design of new microbiomes" said XU Jian, Director of Single-Cell Center at QIBEBT and the other senior author of the study.

Kumara Raja Sundar, MD, a family physician at Kaiser Permanente of Washington, uses two media synchronicity theory principles - conveyance and convergence - as a framework for choosing the right medium of care for his patients. In this essay, Sundar discusses how operating within this framework changed his own practice and decision making during the COVID-19 pandemic, particularly with the use of telemedicine versus in-person clinic visits. The theory of conveyance focuses on transmitting and processing diverse information to understand a situation. It requires time to analyze data, create patterns and make conclusions. Convergence focuses on discussing pre-processed information to achieve a mutual understanding of it. It often requires a rapid exchange of information to allow immediate feedback to test and verify each person's knowledge. Sundar writes that patients benefit from telehealth's convenience when they have access to the right technology but that they must have access to all care options. "We must guide patients towards the right care medium for them and in the correct order and use all of our tools efficiently and effectively," he adds. "It is the only way we will be able to achieve our mission of healing."