Tech

Imaging techniques enable a detailed look inside an organism. But interpreting the data is time-consuming and requires a great deal of experience. Artificial neural networks open up new possibilities: They require just seconds to interpret whole-body scans of mice and to segment and depict the organs in colors, instead of in various shades of gray. This facilitates the analysis considerably.

How big is the liver? Does it change if medication is taken? Is the kidney inflamed? Is there a tumor in the brain and did metastases already develop? In order to answer such questions, bioscientists and doctors to date had to screen and interpret a wealth of data.

"The analysis of three-dimensional imaging processes is very complicated," explains Oliver Schoppe. Together with an interdisciplinary research team, the TUM researcher has now developed self-learning algorithms to in future help analyze bioscientific image data.

At the core of the AIMOS software - the abbreviation stands for AI-based Mouse Organ Segmentation - are artificial neural networks that, like the human brain, are capable of learning. "You used to have to tell computer programs exactly what you wanted them to do," says Schoppe. "Neural networks don't need such instructions:" It's sufficient to train them by presenting a problem and a solution multiple times. Gradually, the algorithms start to recognize the relevant patterns and are able to find the right solutions themselves."

Training self-learning algorithms

In the AIMOS project, the algorithms were trained with the help of images of mice. The objective was to assign the image points from the 3D whole-body scan to specific organs, such as stomach, kidneys, liver, spleen, or brain. Based on this assignment, the program can then show the exact position and shape.

"We were lucky enough to have access to several hundred image of mice from a different research project, all of which had already been interpreted by two biologists," recalls Schoppe. The team also had access to fluorescence microscopic 3D scans from the Institute for Tissue Engineering and Regenerative Medicine at the Helmholtz Zentrum München.

Through a special technique, the researchers were able to completely remove the dye from mice that were already deceased. The transparent bodies could be imaged with a microscope step by step and layer for layer. The distances between the measuring points were only six micrometers - which is equivalent to the size of a cell. Biologists had also localized the organs in these datasets.

Artificial intelligence improves accuracy

At the TranslaTUM the information techs presented the data to their new algorithms. And these learned faster than expected, Schoppe reports: "We only needed around ten whole-body scans before the software was able to successfully analyze the image data on its own - and within a matter of seconds. It takes a human hours to do this."

The team then checked the reliability of the artificial intelligence with the help of 200 further whole-body scans of mice. "The result shows that self-learning algorithms are not only faster at analyzing biological image data than humans, but also more accurate," sums up Professor Bjoern Menze, head of the Image-Based Biomedical Modeling group at TranslaTUM at the Technical University of Munich.

The intelligent software is to be used in the future in particular in basic research: "Images of mice are vital for, for example, investigating the effects of new medication before they are given to humans. Using self-learning algorithms to analyze image data in the future will save a lot of time in the future," emphasizes Menze.

Two new studies from the University of Rochester Medical Center (URMC) have uncovered an association between vaping and mental fog. Both adults and kids who vape were more likely to report difficulty concentrating, remembering, or making decisions than their non-vaping, non-smoking peers. It also appeared that kids were more likely to experience mental fog if they started vaping before the age of 14.

While other studies have found an association between vaping and mental impairment in animals, the URMC team is the first to draw this connection in people. Led by Dongmei Li, Ph.D., associate professor in the Clinical and Translational Science Institute at URMC, the team mined data from two major national surveys.

"Our studies add to growing evidence that vaping should not be considered a safe alternative to tobacco smoking," said study author Li.

The studies, published in the journals Tobacco Induced Diseases and Plos One, analyzed over 18,000 middle and high school student responses to the National Youth Tobacco Survey and more than 886,000 responses to the Behavioral Risk Factor Surveillance System phone survey from U.S. adults. Both surveys ask similar questions about smoking and vaping habits as well as issues with memory, attention and mental function.

Both studies show that people who smoke and vape - regardless of age - are most likely to report struggling with mental function. Behind that group, people who only vape or only smoke reported mental fog at similar rates, which were significantly higher than those reported by people who don't smoke or vape.

The youth study also found that students who reported starting to vape early - between eight and 13 years of age - were more likely to report difficulty concentrating, remembering, or making decisions than those who started vaping at 14 or older.

"With the recent rise in teen vaping, this is very concerning and suggests that we need to intervene even earlier," said Li. "Prevention programs that start in middle or high school might actually be too late."

Adolescence is a critical period for brain development, especially for higher-order mental function, which means tweens and teens may be more susceptible to nicotine-induced brain changes. While e-cigarettes lack many of the dangerous compounds found in tobacco cigarettes, they deliver the same amount or even more nicotine.

While the URMC studies clearly show an association between vaping and mental function, it's not clear which causes which. It is possible that nicotine exposure through vaping causes difficulty with mental function. But it is equally possible that people who report mental fog are simply more likely to smoke or vape - possibly to self-medicate.

Li and her team say that further studies that follow kids and adults over time are needed to parse the cause and effect of vaping and mental fog.

Researchers from Yokohama National University in Japan have developed a prototype microprocessor using superconductor devices that are about 80 times more energy efficient than the state-of-the-art semiconductor devices found in the microprocessors of today's high-performance computing systems.

As today's technologies become more and more integrated in our daily lives, the need for more computational power is ever increasing. Because of this increase, the energy use of that increasing computational power is growing immensely. For example, so much energy is used by modern day data centers that some are built near rivers so that the flowing water can be used to cool the machinery.

"The digital communications infrastructure that supports the Information Age that we live in today currently uses approximately 10% of the global electricity. Studies suggest that in the worst case scenario, if there is no fundamental change in the underlying technology of our communications infrastructure such as the computing hardware in large data centers or the electronics that drive the communication networks, we may see its electricity usage rise to over 50% of the global electricity by 2030," says Christopher Ayala, an associate professor at Yokohama National University, and lead author of the study.

The team's research, published in Journal: IEEE Journal of Solid-State Circuits, details an effort to develop a more energy efficient microprocessor architecture using superconductors, devices that are incredibly efficient, but require certain environmental conditions to operate.

To tackle this power problem, the team explored the use of an extremely energy-efficient superconductor digital electronic structure, called the adiabatic quantum-flux-parametron (AQFP), as a building block for ultra-low-power, high-performance microprocessors, and other computing hardware for the next generation of data centers and communication networks.

"In this paper, we wanted to prove that the AQFP is capable of practical energy-efficient high-speed computing, and we did this by developing and successfully demonstrating a prototype 4-bit AQFP microprocessor called MANA (Monolithic Adiabatic iNtegration Architecture), the world's first adiabatic superconductor microprocessor," said Ayala.

"The demonstration of our prototype microprocessor shows that the AQFP is capable of all aspects of computing, namely: data processing and data storage. We also show on a separate chip that the data processing part of the microprocessor can operate up to a clock frequency of 2.5 GHz making this on par with today's computing technologies. We even expect this to increase to 5-10 GHz as we make improvements in our design methodology and our experimental setup," Ayala said.

However, superconductors require extremely cool temperatures to operate successfully. One would think that if you factor in the cooling required for a superconductor microprocessor, the energy requirement would become undesirable and surpass current day microprocessors. But according to the research team this, surprisingly, was not the case:

"The AQFP is a superconductor electronic device, which means that we need additional power to cool our chips from room temperature down to 4.2 Kelvin to allow the AQFPs to go into the superconducting state. But even when taking this cooling overhead into account, the AQFP is still about 80 times more energy-efficient when compared to the state-of-the-art semiconductor electronic devices found in high-performance computer chips available today."

Now that the team has proven the concept of this superconductor chip architecture, they plan to optimize the chip and determine the chip's scalability and speed post optimization.

"We are now working towards making improvements in the technology, including the development of more compact AQFP devices, increasing the operation speed, and increasing the energy-efficiency even further through reversible computation," Ayala said. "We are also scaling our design approach so that we can fit as many devices as possible in a single chip and operate all of them reliably at high clock frequencies."

In addition to building standard microprocessors, the team is also interested in examining how AQFPs could assist in other computing applications such as neuromorphic computing hardware for artificial intelligence as well as quantum computing applications.

COLUMBUS, Ohio - A single positive experience on a psychedelic drug may help reduce stress, depression and anxiety symptoms in Black, Indigenous and people of color whose encounters with racism have had lasting harm, a new study suggests.

The participants in the retrospective study reported that their trauma-related symptoms linked to racist acts were lowered in the 30 days after an experience with either psilocybin (Magic Mushrooms), LSD or MDMA (Ecstasy).

"Their experience with psychedelic drugs was so powerful that they could recall and report on changes in symptoms from racial trauma that they had experienced in their lives, and they remembered it having a significant reduction in their mental health problems afterward," said Alan Davis, co-lead author of the study and an assistant professor of social work at The Ohio State University.

Overall, the study also showed that the more intensely spiritual and insightful the psychedelic experience was, the more significant the recalled decreases in trauma-related symptoms were.

A growing body of research has suggested psychedelics have a place in therapy, especially when administered in a controlled setting. What previous mental health research has generally lacked, Davis noted, is a focus on people of color and on treatment that could specifically address the trauma of chronic exposure to racism.

Davis partnered with co-lead author Monnica Williams, Canada Research Chair in Mental Health Disparities at the University of Ottawa, to conduct the research.

"Currently, there are no empirically supported treatments specifically for racial trauma. This study shows that psychedelics can be an important avenue for healing," Williams said.

The study is published online in the journal Drugs: Education, Prevention and Policy.

The researchers recruited participants in the United States and Canada using Qualtrics survey research panels, assembling a sample of 313 people who reported they had taken a dose of a psychedelic drug in the past that they believed contributed to "relief from the challenging effects of racial discrimination." The sample comprised adults who identified as Black, Asian, Hispanic, Native American/Indigenous Canadian, Native Hawaiian and Pacific Islander.

Once enrolled, participants completed questionnaires collecting information on their past experiences with racial trauma, psychedelic use and mental health symptoms, and were asked to recall a memorable psychedelic experience and its short-term and enduring effects. Those experiences had occurred as recently as a few months before the study and as long ago as at least 10 years earlier.

The discrimination they had encountered included unfair treatment by neighbors, teachers and bosses, false accusations of unethical behavior and physical violence. The most commonly reported issues involved feelings of severe anger about being subjected to a racist act and wanting to "tell someone off" for racist behavior, but saying nothing instead.

Researchers asked participants to recall the severity of symptoms of anxiety, depression and stress linked to exposure to racial injustice in the 30 days before and 30 days after the experience with psychedelic drugs. Considering the probability that being subjected to racism is a lifelong problem rather than a single event, the researchers also assessed symptoms characteristic of people suffering from discrimination-related post-traumatic stress disorder (PTSD).

"Not everybody experiences every form of racial trauma, but certainly people of color are experiencing a lot of these different types of discrimination on a regular basis," said Davis, who also is an adjunct faculty member in the Johns Hopkins University Center for Psychedelic and Consciousness Research. "So in addition to depression and anxiety, we were asking whether participants had symptoms of race-based PTSD."

Participants were also asked to report on the intensity of three common kinds of experiences people have while under the influence of psychedelic drugs: a mystical, insightful or challenging experience. A mystical experience can feel like a spiritual connection to the divine, an insightful experience increases people's awareness and understanding about themselvess, and a challenging experience relates to emotional and physical reactions such as anxiety or difficulty breathing.

All participants recalled their anxiety, depression and stress symptoms after the memorable psychedelic experience were lower than they had been before the drug use. The magnitude of the positive effects of the psychedelics influenced their reduction in symptoms.

"What this analysis showed is that a more intense mystical experience and insightful experience, and a less intense challenging experience, is what was related to mental health benefits," Davis said.

The researchers noted in the paper that the study had limitations because the findings were based on participant recall and the entire sample of recruited research volunteers had reported benefits they associated with their psychedelic experience - meaning it cannot be assumed that psychedelics will help all people of color with racial trauma. Davis and Williams are working on proposals for clinical trials to further investigate the effects of psychedelics on mental health symptoms in specific populations, including Black, Indigenous and people of color.

"This was really the first step in exploring whether people of color are experiencing benefits of psychedelics and, in particular, looking at a relevant feature of their mental health, which is their experience of racial trauma," Davis said. "This study helps to start that conversation with this emerging treatment paradigm."

Cancer cells are known for spreading genetic chaos. As cancer cells divide, DNA segments and even whole chromosomes can be duplicated, mutated, or lost altogether. This is called chromosomal instability, and scientists at Memorial Sloan Kettering have learned that it is associated with cancer's aggressiveness. The more unstable chromosomes are, the more likely that bits of DNA from these chromosomes will end up where they don't belong: outside of a cell's central nucleus and floating in the cytoplasm.

Cells interpret these rogue bits of DNA as evidence of viral invaders, which sets off their internal alarm bells and leads to inflammation. Immune cells travel to the site of the tumor and churn out defensive chemicals. A mystery has been why this immune reaction, triggered by the cancer cells, does not spell their downfall.

"The elephant in the room is that we didn't really understand how cancer cells were able to survive and thrive in this inflammatory environment," says Samuel Bakhoum, a physician-scientist at MSK and a member of the Human Oncology and Pathogenesis Program.

According to a new study from Dr. Bakhoum's lab published December 28 in the journal Cancer Discovery, the reason has to do, in part, with a molecule sitting on the outside of the cancer cells that destroys the warning signals before they ever reach neighboring immune cells.

The findings help to explain why some tumors do not respond to immunotherapy, and -- equally important -- suggest ways to sensitize them to immunotherapy.

Detecting Dangerous DNA

The warning system Dr. Bakhoum studies is called cGAS-STING. When DNA from a virus (or an unstable cancer chromosome) lands in a cell's cytoplasm, cGAS binds to it, forming a compound molecule called cGAMP, which serves as a warning signal. Inside the cell, this warning signal activates an immune response called STING, which addresses the immediate problem of a potential viral invader.

In addition, much of the cGAMP also travels outside the cell where it serves as a warning signal to neighboring immune cells. It activates their STING pathway and unleashes an immune attack against the virally infected cell.

Previous work from the Bakhoum lab had shown that cGAS-STING signaling inside of cancer cells causes them to adopt features of immune cells -- in particular, the capacity to crawl and migrate -- which aids their ability to metastasize. This provided part of the answer to the question of how cancer cells survive inflammation and aid metastasis in the process. The new research shows how the cancer cells cope with the warning signals that activated cGAS-STING releases into the environment. A scissor-like protein shreds the signals, providing a second way the cells can thwart the threat of immune destruction.

Examples of human triple negative breast cancer staining negative (left) and positive (right) for ENPP1 expression.
Examples of human triple negative breast cancer staining negative (left) and positive (right) for ENPP1.

The scissor-like protein that coats cancer cells is called ENPP1. When cGAMP finds its way outside the cell, ENPP1 chops it up and prevents the signal from reaching immune cells. At the same time, this chopping releases an immune-suppressing molecule called adenosine, which also quells inflammation.

Through a battery of experiments conducted in mouse models of breast, lung, and colorectal cancers, Dr. Bakhoum and his colleagues showed that ENPP1 acts like a control switch for immune suppression and metastasis. Turning it on suppresses immune responses and increases metastasis; turning it off enables immune responses and reduces metastasis.

The scientists also looked at ENPP1 in samples of human cancers. ENPP1 expression correlated with both increased metastasis and resistance to immunotherapy.

Empowering Immunotherapy

From a treatment perspective, perhaps the most notable finding of the study is that flipping the ENPP1 switch off could increase the sensitivity of several different cancer types to immunotherapy drugs called checkpoint inhibitors. The researchers showed that this approach was effective in mouse models of cancer.

Several companies -- including one that Dr. Bakhoum and colleagues founded -- are now developing drugs to inhibit ENPP1 on cancer cells.

Dr. Bakhoum says it's fortunate that ENPP1 is located on the surface of cancer cells since this makes it an easier target for drugs designed to block it.

It's also relatively specific. Since most other tissues in a healthy individual are not inflamed, drugs targeting ENPP1 primarily affect cancer.

Finally, targeting ENPP1 undercuts cancer in two separate ways: "You're simultaneously increasing cGAMP levels outside the cancer cells, which activates STING in neighboring immune cells, while you're also preventing the production of the immune-suppressive adenosine. So, you're hitting two birds with one stone," Dr. Bakhoum explains.

The pace of the research has been incredibly fast, he says. "One of the things I would be really proud of is if this research ends up helping patients soon, given that we only just started this work in 2018."

He hopes there will be a phase I clinical trial of ENPP1 inhibitors within a year.

Scripps Institution of Oceanography at UC San Diego researchers have uncovered how rain and waves act on different parts of coastal cliffs.

Following three years of cliff surveys in and near the coastal city of Del Mar, Calif., they determined that wave impacts directly affect the base, and rain mostly impacts the upper region of the cliffs.

The study appears in the journal Geomorphology and was funded by California State Parks. California's State Parks Oceanography program supports climate adaptation and resilience efforts through coastal and cliff erosion observations and modeling, measuring and predicting storm surge and wave variability, and establishing wave condition baselines for use in the design and operation of coastal projects.

"It's something that I've been trying to quantify for a long time, which is exciting," said coastal geomorphologist Adam Young, who is the lead author on the paper. "We've always known that waves were an important part of the cliff erosion process, but we haven't been able to separate the influence of waves and rain before."

After decades of debate over the differing roles that waves and rain play in cliff erosion, the findings provide a new opportunity to improve forecasts, which is a pressing issue both in Del Mar and across the California coast. For example, neighborhoods and a railroad line the cliff edge in Del Mar. Past episodes of cliff failures have resulted in several train derailments and landslides, which trigger temporary rail closures and emergency repairs. The consequences can be costly.

Prior to Young's study, the exact relationship between waves, rain, and cliff failures were unclear, mostly because it is difficult to measure the impacts of waves on the cliff base.

"Anytime a study involves sensors in the coastal zone, it's a challenge," said Young. For example, his team at Scripps Oceanography's Center for Climate Change Impacts and Adaptation buries sensors in the sand that measure wave energy. Big surf and erosion can shift the sensors and prevent scientists from collecting reliable measurements.

The key to their success, according to Young, was to visit and measure the cliffs every week for three years -- an effort that was among the most detailed ever undertaken for studying coastal cliffs. These records along the 1.5 mile-long stretch in Del Mar allowed Young's team to untangle the effects of rainfall and groundwater runoff from wave impacts.

"We can now better predict how much erosion will occur during a particular storm using the wave and rainfall erosion relationship that we've identified here," said Young.

Young's group combined measurements from the sensors buried in the sand with computer models of wave energy, as well as with three-dimensional maps of the beach and cliffs collected using a LiDAR device - a laser mapping tool - that was mounted onto trucks driven along the beach. The team also analyzed rainfall data from a local Del Mar weather station.

Because rainfall and associated elevated groundwater levels trigger larger landslides, cliff erosion generally appears to be more correlated with rain. Teasing out the wave-driven cliff erosion is a more subtle and difficult process, but important because the wave-driven erosion weakens the cliff base and sets the stage for those rain-driven landslides.

Understanding the way that cliffs and waves behave together will help improve short-term models that forecast cliff retreat, but the researchers will need more information to predict how future rainfall and waves will drive cliff erosion in the long term.

Young and his group plan to continue to collect data in Del Mar, and are developing a website to make the information about the conditions leading to coastal landslides readily available.

A study by a team of Nanyang Technological University, Singapore (NTU Singapore) psychologists has found a link between extraverts and their word choices.

The finding highlights the need for stronger linguistic indicators to be developed for use in online personality prediction tools, which are being rapidly adopted by companies to improve digital marketing strategies.

Today, marketing companies use predictive algorithms to help them forecast what consumers want based on their online behaviours. Companies are also keen to leverage data and machine learning to understand the psychological aspects of consumer behaviour, which cannot be observed directly, but can provide valuable insights about how to improve targeted advertising.

For example, an 'extravert consumer' might be attracted to marketing messages that match their personality, and retail brands could then choose to target such consumers by using more extraverted and creative language to advertise their products.

However, personality prediction tools available today that are used by marketing firms are not entirely accurate due to a lack of theoretically sound designs.

Principal investigator of the study, Associate Professor Lin Qiu from the Psychology programme at the NTU School of Social Sciences said, "Current machine learning algorithms for personality prediction can seem like a black box - there are many linguistic indicators that can be included in their design, but many of them are dependent on the type of computer application used. This may lead to biases and overfitting, an error affecting the performance of the machine learning algorithms. This begs the question - how should we create robust and accurate personality predictions?"

The study found a corelation between extraverts and their tendency to use certain categories of words. The results showed a small strength of relationship between extraversion and the use of "positive emotion words" and "social process words".

Positive emotion words are defined by psychologists - using text analysis tools - as words that describe a pleasant emotional state, such as 'love', 'happy', or 'blessed', or that indicate positivity or optimism, such as 'beautiful' or 'nice'. Social process words include words containing personal pronouns except 'I', and words showing social intentions, such as 'meet', 'share' and 'talk'.

"This is the first time a relationship has been established between extraverts and their tendency to use the two categories of words. As it is a small correlation, we believe that stronger linguistic indicators are needed to improve machine learning approaches, amid rising interest in such tools in consumer marketing," Assoc Prof Qiu said.

The NTU team said the findings, which was published in the Journal of Research in Personality in December 2020, can provide marketers with well-founded linguistic predictors for the design of machine learning algorithms, improving the performance of software tools for personality prediction.

How the study was conducted

Previous individual studies reviewed by the NTU team have shown that extraversion, or the general tendency to experience positive emotions and enjoy social interactions, is related to the use of words described by psychologists as "positive emotion" or "social process" words. But the strength of this reported relationship has varied substantially between the different studies exploring it.

To establish the effectiveness of such linguistic predictors, the NTU team reviewed 37 studies looking at the same topic to conduct a meta-analysis. Extraversion was determined using internationally recognised personality type questionnaires.

Moving forward, the NTU research team will investigate the relationship between extraversion and other word categories.

While machine learning and predictive analytics can provide companies and marketers with an added advantage in their business strategies, more thought must be put into the design of such analytical models, the NTU research team said.

They hope their work will provide clarity on the types of words that can help guide the development of more accurate machine learning tools for personality prediction.

Using genetic data from nearly 30,000 people, Mount Sinai researchers have built risk scores from a combination of datasets representing distinct ancestral populations that improve prediction of risk for inflammatory bowel diseases (IBD) including Crohn's disease and ulcerative colitis. The study was published in Gastroenterology on December 24.

The researchers found that polygenic risk scores, built using association data from multiple populations in Mount Sinai's multi-ethnic BioMe Biobank, maximized IBD predictions for every population in the biobank. BioMe is a system-wide effort at Mount Sinai that is revolutionizing diagnosis and classification of diseases according to the patient's molecular profile. The study showed that risk scores calculated from integrating data significantly improved predictions among individuals with European, Ashkenazi Jewish, and Hispanic ancestry in BioMe, as well as European individuals in the UK Biobank, which contains biological and medical data on half a million people between ages 40 and 69 living in the UK. Predictive power was lower for patients with African ancestry, likely due to substantially smaller reference datasets and substantially greater genetic diversity within populations of African descent.

"The ability to accurately predict genetic disease risk in individuals across ancestries is a critical avenue that may positively affect patient outcomes, as early interventions and even preventive measures are being considered and developed," says the study's senior author Judy H. Cho, MD, Dean of Translational Genetics and Director of The Charles Bronfman Institute for Personalized Medicine at the Icahn School of Medicine at Mount Sinai. "These findings support a need for greater genetic diversity, including more data on African American populations, to enhance disease risk predictions and reduce health disparities for all populations."

These polygenic risk scores--representing an estimate of overall risk based on the sum of an individual's many, mostly common, genetic variants--were calculated using IBD association data from cohorts with European, African American, and Ashkenazi Jewish backgrounds. Additionally, researchers assessed rare variants in genes associated with very-early-onset IBD within each population and found that African American carriers of uncommon LRBA variants showed reduced expression of both proteins LRBA and CTLA-4. LRBA deficiency increases susceptibility to IBD and results in lower CTLA-4 expression, which can be reversed with the commonly prescribed antimalarial drug chloroquine. Future studies by the Cho Laboratory will focus on predicting which subsets of patients might benefit from targeting this pathway.

"Since lowered LRBA and CTLA-4 expression can lead to IBD, it's encouraging that chloroquine is able to partially recover expression," says the study's first author Kyle Gettler, PhD, postdoctoral fellow in the Department of Genetics and Genomic Sciences at the Icahn School of Medicine at Mount Sinai.

Large-scale global forecasting and on-the-ground observations need to meld into one system to better predict and prevent wide-spread flooding disasters, according to an international research team who published a short view in Advances in Atmospheric Sciences on Dec. 23.

"A 'glocal' -- global to local -- hydrometeorological solution for floods is considered to be critical for better preparedness, mitigation, and management of different types of significant precipitation-caused flooding, which happen extensively almost every year and in many countries, such as China, India and the United States," said paper author Huan Wu, professor and deputy director in the Guangdong Province Key Laboratory for Climate Change and Natural Disaster Studies and School of Atmospheric Sciences, Sun Yat-sen University.

Such a solution, dubbed GHS-F by the researchers, is necessary for both scientific research and operational logistics, according to Wu. A GHS-F could combine wide-spread weather predictions with the deep understanding of how forecasted rain could affect river basins to produce highly detailed and consistent rain-flood information.

Wu pointed to the complex relationship between rain and floods, making the argument that if the meteorological and hydrological communities shared more observations, techniques, measurements and modeled data, as well as lessons learned, some flooding damage might be avoided.

The researchers specifically examined the flood events from May 20 to July 18 of 2020 in central-eastern and southern China. In those two months, the Yangtze River -- the longest river in Asia at a length of almost 4,000 miles -- had 49% more rain than the average amounts for the same time period over the last 60 years. The seven major rain events of this period affected almost 40 million people in 27 provinces, with 141 people reported dead or missing, according to the researchers.

"An encompassing view of flood occurrences, evolution, extent dynamics, and spatial distribution of areas at high risk from flooding over a global or national scale with local detail is highly desirable and, yet, missing for international and national agencies with a mandate in flood response and management," Wu said.

A GHS-F was first suggested about 10 years ago, Wu said, but the unprecedented computing capability and timely data availability, as well as model and data interoperability of the current era mean such a solution is now more practical.

The researchers plan to demonstrate feasibility in a GHS-F by assessing water level observations from ground and remote-sensing instruments in real time, with the goal of increasing the confidence of emergency management decision makers in using this tool for information and risk estimation.

Since CO2 has been recognized as the most important anthropogenic greenhouse gas owing to its significant impact on global warming and climate change, there have been a substantial number of studies that have focused on investigating the status of CO2 in the atmosphere in the past and present, and how it will change in the future.

The United Nations Climate Change Conference (24th Conference of the Parties, COP24) will conduct a climate change action global stock-take for each of five years starting in 2023. Therefore, in support of these efforts, we need a new method to verify how much human emissions impact the global carbon cycle and climate change.

The 1st Chinese Carbon Dioxide Monitoring Satellite Mission, known as TanSat, which was supported by the Ministry of Science and Technology of China, the Chinese Academy of Sciences, and the China Meteorological Administration, launched in December 2016 for the purpose of monitoring CO2 concentrations in the atmosphere over the globe. The 1st TanSat global map of CO2 dry-air mixing ratio (XCO2) measurements over land was released as a version-1 data product with an accuracy of 2.11 ppmv (parts per million by volume).

"Unfortunately, it is not accurate enough to support estimation of anthropogenic CO2 emissions in cities due to it having a 1-1.5 ppm gradient across urban areas, as shown from ground-based measurement in Paris," explains Dongxu Yang, a scientist with the Institute of Atmospheric Physics, Chinese Academy of Sciences (IAP/CAS), who is closely involved in TanSat data retrieval. "On TanSat's 4th birthday coming this year, we will introduce a new version [version 2] of the TanSat global XCO2 product."

The new TanSat global XCO2 product is retrieved by IAPCAS (the Institute of Atmospheric Physics Carbon Dioxide Retrieval Algorithm for Satellite Remote Sensing), and the European Space Agency (ESA) Climate Change Initiative plus (CCI+) TanSat XCO2 product is retrieved by the University of Leicester Full Physics (UoL-FP) retrieval algorithm. The new TanSat XCO2 data product is now retrieved by IAP/CAS using the O2 A-band and CO2 weak band together, after a new approach has been developed to improve the retrieval accuracy by optimizing the TanSat measured spectrum. The TanSat v2 XCO2 data product can be obtained from the CASA (the Cooperation on the Analysis of carbon SAtellites data) TanSat data and science service.

Intercomparison of TanSat XCO2 retrieval between the two algorithms shows good agreement for global Total Column Carbon Observing Network (TCCON) overpass measurements with 34,699 individual measurements. The dispersion between the two data products has a standard deviation of 1.28 ppmv, and there is also a -0.35 ppmv overall bias between both. These intercomparison results are introduced in a recently published paper in Advances in Atmospheric Sciences.

In January 2020, a protocol was signed between the National Remote Sensing Center of the China Ministry of Science and Technology of China (MOST/NRSCC) and ESA regarding the intended coordination of their activities in the Remote Sensing of Greenhouse Gases and Related Missions. MOST/NRSCC and ESA intend TanSat to be a third-party mission of ESA, and TanSat data have been included in key ESA programs such as the Climate Change Initiative plus (CCI+) and Earthnet Data Assessment Pilot (EDAP).

The new dataset will be involved in global carbon flux estimations and climate studies in the near future. The TanSat mission will never stop, and developments are required in future generations of TanSat missions to contribute further to global stock-take and carbon-neutral research.

A soil scientist from RUDN University studied the decomposition of organic matter in rice paddies--the sources of CO2 and methane emissions. Both gases add to the greenhouse effect and affect climate warming in subtropical regions. The emissions increase when the roots of plants influence microbial communities in the soil. This influence, in turn, depends on temperature changes. Therefore, climate warming can lead to more greenhouse gas emissions. The results of the study were published in the Applied Soil Ecologyclimate change. The intensity of this process depends on the temperature of the environment and soil microorganisms. In the soils of rice paddies, methane is produced by single-cell organisms called archaea. However, to make methane, they require intermediary substances that come from plant roots. This is how the so-called priming effect occurs: the life of microorganisms is supported by organic substances released by plants through their roots. It is this effect that determines the number and activity of microorganisms in the soil. A soil scientist from RUDN University was the first to discover a correlation between the priming effect and greenhouse gas emissions and to describe the dynamics of these processes in view of global warming.

The team took soil samples from rice paddies located in the Hunan province in South-Eastern China. The samples were sifted to remove soil fauna and bits of plants. After that, water was added to them to model the conditions of a submerged rice paddy. After that, the samples were kept in plastic containers in a dark room for 75 days. To imitate different seasons, the scientists maintained different temperatures in the containers: 5 °C (winter), 15 °C (spring), 25 °C (autumn), and 35 °C (summer). The team wanted to measure how methane and CO2 emissions would vary under the influence of the priming effect in different temperature regimes. Sodium acetate, the simplest form of organic carbon produced by plant roots, was added to the soil to support the archaea.

The team measured the levels of greenhouse gas emissions every 2 to 5 days. On the 75th day, methane emissions from primed soils turned out to have increased 153 times compared to the samples without sodium acetate. The scientists also learned that the priming effect depended on the temperature. The soils demonstrated the highest sensitivity at 15 °C: in these samples, a 10? increase in temperature caused methane emission volumes to grow 25 times. As for CO2 emissions, they directly correlated with temperature levels. According to the team, this is because microorganisms become more active in a warm environment.

"The priming effect determined the correlation between the temperature and the process of organic matter decomposition in the soil. At 5-15 °C, temperature fluctuations had a huge effect on methane emissions: they increased almost 25 times. One could conclude that in warm winters methane emissions from the soil could be the main reason for the greenhouse effect. The results of other studies that do not take the priming effect into account should be interpreted with caution," said Yakov Kuzyakov, a Ph.D. in Biology, and the Head of the Center for Mathematical Modeling and Design of Sustainable Ecosystems at the Agrarian and Technological Institute, RUDN University.

Tokyo, Japan - Researchers from Tokyo Metropolitan University have discovered a way to make self-assembled nanowires of transition metal chalcogenides at scale using chemical vapor deposition. By changing the substrate where the wires form, they can tune how these wires are arranged, from aligned configurations of atomically thin sheets to random networks of bundles. This paves the way to industrial deployment in next-gen industrial electronics, including energy harvesting, and transparent, efficient, even flexible devices.

Electronics is all about making things smaller. Smaller features on a chip, for example, means more computing power in the same amount of space and better efficiency, essential to feeding the increasingly heavy demands of a modern IT infrastructure powered by machine learning and artificial intelligence. And as devices get smaller, the same demands are made of the intricate wiring that ties everything together. The ultimate goal would be a wire that is only an atom or two in thickness. Such nanowires would begin to leverage completely different physics as the electrons that travel through them behave more and more as if they live in a one-dimensional world, not a 3D one.

In fact, scientists already have materials like carbon nanotubes and transition metal chalcogenides (TMCs), mixtures of transition metals and group 16 elements which can self-assemble into atomic-scale nanowires. The trouble is making them long enough, and at scale. A way to mass produce nanowires would be a game changer.

Now, a team led by Dr. Hong En Lim and Associate Professor Yasumitsu Miyata from Tokyo Metropolitan University has come up with a way of making long wires of transition metal telluride nanowires at unprecedentedly large scales. Using a process called chemical vapor deposition (CVD), they found that they could assemble TMC nanowires in different arrangements depending on the surface or substrate that they use as a template. Examples are shown in Figure 2; in (a), nanowires grown on a silicon/silica substrate form a random network of bundles; in (b), the wires assemble in a set direction on a sapphire substrate, following the structure of the underlying sapphire crystal. By simply changing where they are grown, the team now have access to centimeter-sized wafers covered in the arrangement they desired, including monolayers, bilayers and networks of bundles, all with different applications. They also found that the structure of the wires themselves were highly crystalline and ordered, and that their properties, including their excellent conductivity and 1D-like behavior, matched those found in theoretical predictions.

Having large amounts of long, highly crystalline nanowires is sure to help physicists characterize and study these exotic structures in more depth. Importantly, it's an exciting step towards seeing real-world applications of atomically-thin wires, in transparent and flexible electronics, ultra-efficient devices and energy harvesting applications.

Archeologists from Kemerovo State University are exploring the Tepsei site of Minusinsk Basin, located in Krasnoturansky district (Krasnoyarsk region). Their research objective is to describe the culture and history of the site, covering over 27 square kilometers. The territory includes Mount Tepsei (630 m high) and the river valley below. The site has already revealed numerous archeological artifacts, burial grounds, and ancient villages of the Yenisey culture. The local rock art ranges from the Stone Age to ethnographic times and is represented by numerous petroglyphs on rocks, horizontal stone plates, and Tagar burrows.

The Tepsei cave art first attracted the attention of our Department of Archeology in 1980s, when a team of archeologists, led by Dr. B.N Pyatkin, explored the local petroglyphs. In 1995, Tepsei rock art became the subject of an international French and Russian program supervised by Yakov Sher and Henry-Paul Frankfor. The team studied the effect of the artificial lake on the local petroglyphs. Eight years ago, Kemerovo State University returned to Tepsei and resumed the research on a new level: Olga Sovetova, the Director of the Institute of History and International Relations, and her team of archeologists use 3D modeling and UAV drones to study the local rock art.

In 2018 the team obtained a grant support to catalog the prehistoric rock art of Mount Tepsei using both traditional and innovative methods. They employed a Garmin GPS device to record each surface. By marking each individual site on Google Maps, the archeologists identified the largest clusters of petroglyphs and revealed the areas that needed additional in situ research. The GPS technology made it possible to define the approximate boundaries of the Tepsei archaeological site. A UAV survey of inaccessible mountain areas helped to identify some new rock art clusters. The petroglyphs were cataloged and copied using both contact and non-contact methods, e.g. mica-coated paper, various shooting modes, etc.

The graphic sources database of the Tepsei site is almost complete. The scientists have already copied and cataloged the prehistoric art of the river valley near Mount Tepsei and its upper areas, including two ravines, as well as petroglyphs made on burial stones and slabs at the foot of the mountain. Two expeditions took place in July and September of 2020. The archeologists performed an aerial survey of the terrain, mapped the territory, and explored some hard-to-reach areas using drones. They completed 3D models of fifteen rock art surfaces.

The scientists worked in cooperation with specialists from the RSSDA laboratory (Moscow). Together, they completed a 3D virtual model of one of the clusters. This model will show the exact location of each rock art site, burial stone, or stone slab. The map will also show excavation sites. The research will define the precise boundaries of the whole Tepsei cluster and give a more accurate picture of the ancient history of southern Siberia: the gradual change of cultures, migration routes, the time when various settlements were set up, the worldview of the peoples that etched the petroglyphs, etc. In addition, the historians found some new rock paintings, including that of a wild horse (approx. the 3rd BC) and Scythian figures of animals made with delicate engraved lines (the 8th-3rd BC).

Children struggle to discern emotions for mask-wearing faces, though masks are "unlikely to dramatically impair" their everyday interactions.

For the first time, scientists have recorded how our brains navigate physical space and keep track of others' location. Researchers used a special backpack to wirelessly monitor the brain waves of epilepsy patients as each one walked around an empty room hunting for a hidden, two-foot spot. In an article published in Nature, the scientists report that the waves flowed in a distinct pattern suggesting that each individual's brain had mapped out the walls and other boundaries. Interestingly, each participant's brain waves flowed in a similar manner when they sat in the corner of the room and watched someone else walk around, suggesting these waves were also used to track other people's movements. The study was part of the NIH's Brain Research through Advancing Innovative Neurotechnologies® (BRAIN) Initiative.

"We were able to directly study for the first time how a person's brain navigates an actual physical space that is shared with others," said Nanthia Suthana, Ph.D., an assistant professor of neurosurgery and psychiatry at the David Geffen School of Medicine at the University of California, Los Angeles (UCLA) and senior author. "Our results suggest that our brains may use a common code for knowing where we and others are in social settings."

Dr. Suthana's lab studies how the brain controls learning and memory. In this study, her team worked with a group of participants with drug-resistant epilepsy, 31-52 years old, whose brains have been surgically implanted with electrodes to control their seizures.

The electrodes reside in a memory center in the brain called the medial temporal lobe, which is also thought to control navigation, at least in rodents. Over the past half century, scientists, including three Nobel Prize winners, discovered - in experiment after experiment - that neurons in this lobe, known as grid cells and place cells, act like a global positioning system. Moreover, the scientists found that low frequency waves of neural activity by these cells, called theta rhythms, help rodents know where they and others are while running through a maze or swimming around a shallow pool of water.

"Several pieces of indirect evidence support the medial temporal lobe's role in how we navigate. But testing these ideas any further has been technically difficult," said Matthias Stangl, Ph.D., a postdoctoral scholar at UCLA and the lead author of the article.

This study provides the most direct evidence to date supporting these ideas in humans and it was made possible by a special backpack which Dr. Suthana's team invented as part of an NIH BRAIN Initiative project.

"Many of the most important breakthroughs in brain research have been sparked by technological advances. This is what the NIH BRAIN Initiative is all about. It challenges researchers to create new tools and then use those tools to revolutionize our understanding of the brain and brain disorders," said John Ngai, Ph.D., director of the NIH's BRAIN Initiative.

At its core, the backpack contained a computer system which can wirelessly connect to the electrodes surgically implanted in a patient's head. Recently, the researchers showed that the computer can simultaneously be hooked up to several other devices including virtual reality goggles, eye trackers, and heart, skin, and breathing monitors.

"Until now the only ways to directly study human brain activity required a subject to be still, either lying in a massive brain scanner or hooked up to an electrical recording device. In 2015, Dr. Suthana came to me with an idea for solving this problem and so we took a chance on making a backpack," said Uros Topalovic, M.S., a graduate student at UCLA and an author of the study. "The backpack frees the patient and allows us to study how the brain works during natural movements."

To examine the role the medial temporal lobe plays in navigation the researchers asked the research participants to put on the backpack and enter an empty 330-square-foot room.

Each wall was lined with a row of five colored signs numbered 1 through 5, one color per wall. Through a ceiling mounted speaker, a computerized voice asked the patient to walk to one of the signs. Once they arrived at the sign the voice then asked them to search for a two-foot in diameter spot hidden somewhere in the room. Meanwhile the backpack recorded the patient's brain waves, paths through the room, and eye movements.

Initially, each person needed several minutes to find the spot. During subsequent trials, the time shortened as their memory of the spot's location improved.

The electrical recordings revealed a distinct pattern in brain activity. The theta rhythms flowed stronger - with higher peaks and lower valleys - when the participants approached a wall than when they wandered in the middle of room. This happened exclusively when they were searching for the spot. In contrast, the researchers saw no correlation between theta rhythm strength and location when the participants followed directions for walking to the colored signs on the wall.

"These results support the idea that under certain mental states theta rhythms may help the brain know where boundaries are located. In this case it's when we are focused and searching for something," said Dr. Stangl.

Further analysis supported this conclusion and helped rule out the possibility that the results were caused by other factors, such as activity associated with different eye, body, or head movements.

Curiously, they saw similar results when the participants watched someone else search for a spot. In these experiments, the participants would sit on a chair in the corner of the room with their backpacks on and their hands resting near a keyboard. The patients knew the location of the hidden spot and they pressed a button on the keyboard whenever the other person arrived at it.

Again, the participant's brain waves flowed strongest when the other person either neared a wall or the spot and this pattern only appeared when the person was on the hunt rather than following specific directions.

"Our results support the idea that our brains may use these wave patterns to put ourselves in another person's shoes," said Dr. Suthana. "The results open the door to helping us understand how our brains control navigation and, possibly, other social interactions."

Dr. Suthana's team plans to explore these ideas in greater depth. In addition, the team has made the backpack available to other researchers who want to learn more about the brain and brain disorders.

This year more than 175 research groups have received funding from the NIH in support of a wide variety of projects ranging from mapping the neural circuits that control what an octopus sees to helping people paralyzed by spinal cord injuries regain movements by upgrading computer programs that drive neural stimulation devices.