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The Navy's quest to power its ships by converting seawater into fuel is one step nearer fruition.

University of Rochester chemical engineers, in collaboration with researchers at the Naval Research Laboratory, the University of Pittsburgh, and OxEon Energy, have demonstrated that a potassium-promoted molybdenum carbide catalyst efficiently and reliably converts carbon dioxide to carbon monoxide, a critical step in the process.

"This is the first demonstration that this type of molybdenum carbide catalyst can be used on an industrial scale," says Marc Porosoff, assistant professor of chemical engineering at Rochester. In a paper in Energy & Environmental Science, the researchers describe an exhaustive series of experiments they conducted at molecular, laboratory and pilot scales to document the catalyst's suitability for scale-up.

If Navy ships could create their own fuel from the seawater they travel through, they could remain in continuous operation. Other than a few nuclear-powered aircraft carriers and submarines, most Navy ships must periodically align themselves alongside tanker ships to replenish their fuel oil, which can be difficult in rough weather. In 2014, a Naval Research Laboratory team led by Heather Willauer announced it had used a catalytic converter to extract carbon dioxide and hydrogen from seawater and then converted the gases into liquid hydrocarbons at a 92 percent efficiency rate.

Since then the focus has been on increasing the efficiency of the process and scaling it up to produce fuel in sufficient quantities.

The carbon dioxide extracted from seawater is extremely difficult to convert directly into liquid hydrocarbons with existing methods. So, it is necessary to first convert carbon dioxide into carbon monoxide via the reverse water-gas shift (RWGS) reaction, which can then be converted into liquid hydrocarbons via Fischer-Tropsch synthesis (FTS). Typically, catalysts for RWGS contain expensive precious metals and deactivate rapidly under reaction conditions. However, the potassium-modified molybdenum carbide catalyst is synthesized from low-cost components and did not show any signs of deactivation during continuous operation of the 10 day pilot-scale study.

That's why this demonstration of molybdenum carbide catalyst is important.

Porosoff, who first began working on the project while serving as a postdoctoral research associate with Willauer's team, discovered that adding potassium to a molybdenum carbide catalyst supported on a surface of gamma alumina could serve as a low-cost, stable, and highly selective catalyst for converting carbon dioxide into carbon monoxide during RWGS.

The potassium lowers the energy barrier associated with the RWGS reaction, while the gamma alumina - marked with grooves and pores, much like a sponge - helps ensure that the molybdenum carbide catalyst particles remain dispersed, maximizing the surface area available for reaction, Porosoff says.

To determine whether potassium-promoted molybdenum carbide might also be useful for capturing and converting carbon dioxide from power plants, the lab will conduct further experiments to test the catalyst's stability when exposed to common contaminants found in flue gas such as mercury, sulfur, cadmium and chlorine.

Homes infested by bed bugs appear to have different bacterial communities - often referred to as microbiomes - than homes without bed bugs, according to a first-of-its-kind study from North Carolina State University. In addition, once bed bug infestations were eradicated, home microbiomes became more similar to those in homes that never had bed bugs. The findings could be an important step in lifting the veil on the factors involved in indoor environmental quality and how to improve it.

Microbes can affect indoor air quality. So NC State entomologists Coby Schal and Madhavi Kakumanu wanted to learn more about the microbiomes of bed bugs, whether bed bugs can shape the microbial community in homes they infest, and whether eliminating bed bugs changes the microbiome of homes that were once infested.

The study, held in an apartment complex in Raleigh, compared the microbiomes of bed bugs with the microbiomes in the household dust of infested homes as well as the microbiomes in apartments that had no bed bugs. Nineteen infested homes were studied over the course of four months; seven were treated with heat to eliminate bed bugs after the initial sample was taken, while 12 infested homes were treated after one month. These homes were compared with 11 homes that had no bed bugs.

The results showed similarities between the microbiomes of bed bugs and the dust-associated microbiomes of infested homes, mostly through the presence of Wolbachia, a symbiotic bacterium that comprises the majority of the bacterial abundance in bed bugs. Bed bug and infested home microbiomes differed significantly from the microbial communities of uninfested homes.

"There is a link between the microbiome of bed bugs and the microbiome of household dust in bed bug infested homes," said Schal, the Blanton J. Whitmire Distinguished Professor of Entomology at NC State and co-corresponding author of the paper. "No previous study has reported the impact of chronic pest infestations on indoor microbial diversity."

The study also showed that, after bed bugs were eliminated, infested home microbiomes gradually became more like those in homes without bed bugs.

"The elimination of the bed bugs resulted in gradual shifts in the home microbial communities toward those of uninfested homes," Kakumanu, an NC State research scholar in Schal's lab and co-corresponding author of the study, said. "This paper is the first experimental demonstration that eliminating an indoor pest alters the indoor microbiome toward that of uninfested homes."

"Bed bug infestations are problematic in many homes in both developed and developing countries," Schal said. "There is a critical need to investigate infestations from the perspective of indoor environmental quality, and this paper represents a first step toward this end." 

Large-scale oceanic phenomena are complicated and often involve many natural processes. Tropical instability wave (TIW) is one of these phenomena.

Pacific TIW, a prominent prevailing oceanic event in the eastern equatorial Pacific Ocean, is featured with cusp-shaped waves propagating westward at both flanks of the tropical Pacific cold tongue.

The forecast of TIW has long been dependent on physical equation-based numerical models or statistical models. However, many natural processes need to be considered for understanding such complicated phenomena.

Recently, a research team led by Prof. LI Xiaofeng from the Institute of Oceanology of the Chinese Academy of Sciences (IOCAS) studied this type of complex oceanic phenomena through artificial intelligence (AI) technologies.

The team member includes ZHENG Gang from the Second Institute of Oceanology of Ministry of Natural Resources, ZHANG Ronghua from IOCAS, and LIU Bin from Shanghai Ocean University.

They used satellite data-driven deep learning model to forecast the complicated thousand-kilometer scale TIW for the first time in the world. Their study was published in Science Advances on July 15.

Basic rules governing the complicated oceanic phenomena are usually profoundly hidden in the fast-increasing satellite remote sensing big data itself. They need to be dug up by powerful information mining techniques such as deep learning in the AI field.

"AI technology may lead to a promising alternative for modeling complicated oceanic phenomena and circumventing the difficulties faced by traditional numerical models," said Prof. LI.

In this work, the researchers developed a deep learning model for forecasting sea surface temperature (SST) field associated with TIW based on current and previous satellite-derived SST data.

The long-term test of nine-year SST data showed that the model efficiently and accurately forecasted SST evolution and captured TIW propagation's spatial and temporal variation.

The study demonstrates that a purely data-driven and AI-based information mining paradigm can be a robust and promising way to model and forecast complicated oceanic phenomena in the satellite remote sensing Big Data Era.

"AI-based models, statistical models, and traditional numerical models can complement each other and provide a novel perspective for studying complicated oceanic features," said Prof. LI.

A review article by Prof. LI's group was published in National Science Review on March 19, which systematically reviewed deep-learning-based information mining from ocean remote-sensing imagery.

Every human body is unique, and the way in which a person's body naturally moves depends on myriad factors, including height, weight, size, and overall shape. A global team of computer scientists has developed a novel deep-learning framework that automates the precise translation of human motion, specifically accounting for the wide array of skeletal structures and joints.

The end result? A seamless, much more flexible and universal framework for replicating human motion in the virtual world.

The team of researchers hail from AICFVE, the Beijing Film Academy, ETH Zurich, Hebrew University of Jerusalem, Peking University, and Tel Aviv University, and plan to demonstrate their work during SIGGRAPH 2020. The conference, which will take place virtually this year starting 17 August, gathers a network of leading professionals who approach computer graphics and interactive techniques from different perspectives. SIGGRAPH continues to serve as the industry's premier venue for showcasing forward-thinking ideas and research. Registration for the virtual conference is now available.

Capturing the motion of humans remains a burgeoning and exciting field in computer animation and human-computer interaction. Motion capture (mocap) technology, particularly in filmmaking and visual effects, has made it possible to bring animated characters or digital actors to life. Mocap systems usually require the performer or actor to wear a set of markers or sensors that computationally capture their motions and 3D-skeleton poses. What remains a challenge in mocap is the ability to precisely transfer motion, also known as "motion retargeting," between human skeletons, where the skeletons might differ in their structure depending on the number of bones and joints involved.

To date, mocap systems have not been successful in retargeting skeletons with different structures in a fully automated way. Errors are typically introduced in positions where joint correspondence cannot be specified. The team set out to address this specific problem and demonstrate that the framework can accurately replicate motion retargeting without specifying explicit pairing between the varying data sets.

"Our development is essential for using data from multiple mocap datasets that are captured with different systems within a single model," Kfir Aberman, a senior author of the work and a researcher from AICFVE at the Beijing Film Academy, shared. "This enables the training of stronger, data-driven models that are setup-agnostic for various motion processing tasks."

The team's new motion processing framework contains special operators uniquely designed for motion data. The framework is general and can be used for various motion processing tasks. In particular, the researchers exploit its special properties to solve a practical problem in the mocap world, which makes their novel method widely applicable.

"I am particularly excited about the ability of our approach to encode motion into an abstract, skeleton-agnostic latent space," Dani Lischinski, a coauthor of the work and professor at the School of Computer Science and Engineering at the Hebrew University of Jerusalem, said. "A fascinating direction for future work would be to enable motion transfer between fundamentally different characters, such as bipeds and quadrupeds."

In addition to Aberman and Lischinski, the collaborators on "Skeleton-aware Networks for Deep Motion Retargeting" include Peizhuo Li, Olga Sorkine-Hornung, Daniel Cohen-Or, and Baoquan Chen. The team's paper and video can be found here and here.

Despite a general decline in U.S. tobacco use since the 1950’s, tobacco use is still prevalent and a significant threat to public health. Previous research has shown that flavored cigarettes largely appeal to and are disproportionately used by underage smokers. Nearly 90% of smokers begin smoking by age 18, according to the U.S. Department of Health and Human Services. To reduce long-term health consequences and improve public health, preventing smoking initiation is key as is reducing the draw of flavored tobacco products.

On September 22, 2009, the U.S. Food and Drug Administration’s national ban on flavored cigarettes products went into effect. This banned the sale of flavored cigarettes other than menthol, but there was little information about the potential impact of this ban on youth smoking.

New research led by George Mason University’s College of Health and Human Services found that the flavored cigarette ban was linked to a significant reduction in smoking among youth and young adults.

Dr. Matthew Rossheim, assistant professor of global and community health, led the study published in the Journal of Adolescent Health. Researchers found that the flavored cigarette ban reduced smoking among youth (ages 12-17 years) by 43% and young adults (ages 18-25 years) by 27%.

“Our study suggests that the ban of flavored cigarettes was extremely effective at reducing smoking among young people,” explains Rossheim. “This shows incredible promise for future comprehensive bans of flavored tobacco products, including those in e-cigarettes, which to-date have received significant exemptions. Policymakers should take note of the evidence from this study and pass legislation to extend flavor bans to other tobacco and nicotine products.”

Rossheim and colleagues examined cigarette use among young people and adults from the 2002-2017 National Survey on Drug Use and Health data. This included nationally representative data collected every quarter each year, providing a more sensitive measure to detect changes in smoking behaviors than previous research, as well as an adult comparison group to test whether there was an overall reduction in smoking that could have been a result of other factors.

Rossheim and colleagues did not see a similar reduction in smoking among older smokers, which suggests that this ban was effective at reducing smoking specifically among young people and that the reduction was caused by the ban and not by other influences.

“We observed an increase in smoking of menthol cigarettes among youth right after the ban took effect,” adds Rossheim. “It appears that young people smoke menthol cigarettes more when other flavor options are no longer available.”

Menthol flavor was excluded from the 2009 ban. Prior research has also shown that menthol-flavored tobacco products are disproportionately used by African Americans, which may explain observed health disparities.

Rossheim and colleagues suggest that, to maximize their effectiveness among young people and to avoid increasing health disparities among African Americans, flavor bans should include all flavors and tobacco products.

About George Mason University

George Mason University is Virginia's largest and most diverse public research university. Located near Washington, D.C., Mason enrolls 38,000 students from 130 countries and all 50 states. Mason has grown rapidly over the past half-century and is recognized for its innovation and entrepreneurship, remarkable diversity and commitment to accessibility. For more information, visit https://www2.gmu.edu/.

About the College of Health and Human Services

George Mason University's College of Health and Human Services prepares students to become leaders and shape the public's health through academic excellence, research of consequence and interprofessional practice. The College enrolls 1,917 undergraduate students and 950 graduate students in its nationally recognized offerings, including: 5 undergraduate degrees, 12 graduate degrees, and 11 certificate programs. The College is transitioning to a college public health in the near future. For more information, visit https://chhs.gmu.edu/.

Journal

Journal of Adolescent Health

DOI

10.1016/j.jadohealth.2020.06.022

TROY, N.Y. -- A common drug, already approved by the Food and Drug Administration (FDA), may also be a powerful tool in fighting COVID-19, according to research published this week in Antiviral Research.

SARS-CoV-2, the virus that causes COVID-19, uses a surface spike protein to latch onto human cells and initiate infection. But heparin, a blood thinner also available in non-anticoagulant varieties, binds tightly with the surface spike protein, potentially blocking the infection from happening. This makes it a decoy, which might be introduced into the body using a nasal spray or nebulizer and run interference to lower the odds of infection. Similar decoy strategies have already shown promise in curbing other viruses, including influenza A, Zika, and dengue.

"This approach could be used as an early intervention to reduce the infection among people who have tested positive, but aren't yet suffering symptoms. But we also see this as part of a larger antiviral strategy," said Robert Linhardt, lead author and a professor of chemistry and chemical biology at Rensselaer Polytechnic Institute. "Ultimately, we want a vaccine, but there are many ways to combat a virus, and as we've seen with HIV, with the right combination of therapies, we can control the disease until a vaccine is found."

To infect a cell, a virus must first latch onto a specific target on the cell surface, slice through the cell membrane, and insert its own genetic instructions, hijacking the cellular machinery within to produce replicas of the virus. But the virus could just as easily be persuaded to lock onto a decoy molecule, provided that molecule offers the same fit as the cellular target. Once bound to a decoy, the virus would be neutralized, unable to infect a cell or free itself, and would eventually degrade.

In humans, SARS-CoV-2 binds to an ACE2 receptor, and the researchers hypothesized that heparin would offer an equally attractive target. In a binding assay, the researchers found that heparin bound to the trimeric SARS-CoV-2 spike protein at 73 picomoles, a measure of the interaction between the two molecules.

"That's exceptional, extremely tight binding," said Jonathan Dordick, a chemical and biological engineering professor at Rensselaer who is collaborating with Linhardt to develop the decoy strategy. "It's hundreds of thousands of times tighter than a typical antibody antigen. Once it binds, it's not going to come off."

To hear Linhardt and Dordick discuss this research, watch this video.

Internationally recognized for his creation of synthetic heparin, Linhardt said that, in reviewing sequencing data for SARS-CoV-2, the team recognized certain motifs on the spike protein and strongly suspected it would bind to heparin. In addition to the direct binding assay, the team tested how strongly three heparin variants -- including a non-anticoagulant low molecular weight heparin -- bind to SARS-CoV-2, and used computational modeling to determine the specific sites where the compounds bind to the virus. All the results confirm heparin as a promising candidate for the decoy strategy. The researchers have subsequently initiated work on assessments of antiviral activity and cytotoxicity in mammalian cells.

"This isn't the only virus that we're going to confront in a pandemic," Dordick said. "We don't really have great antivirals, but this is a pathway forward. We need to be in a position where we understand how things like heparin and related compounds can block virus entry."

In previous work, a team led by Linhardt and Dordick demonstrated the decoy strategy on viruses with a mechanism similar to SARS-CoV-2. In 2019, the team created a trap for dengue virus, attaching specific aptamers -- molecules the viral latches will bind to -- precisely to the tips and vertices of a five-pointed star made of folded DNA. Floating in the bloodstream, the trap lights up when sprung, creating the world's most sensitive test for mosquito-borne diseases. In work prior to that, they created a synthetic polymer configured to match the sialic acid latch points on influenza virus, reducing influenza A mortality in mice from 100% to 25% over 14 days.

"This innovative approach to effectively trapping virusus is a prime example of how biotechnology approaches developed at Rensselaer are being brought forward to address challenging global health problems," said Deepak Vashishth, the director of the Center for Biotechnology and Interdisciplinary Studies at Rensselaer, of which both Dordick and Linhardt are a part. "Professors Dordick and Linhardt have worked collaboratively across disciplines, and their research shows promise even beyond this current pandemic."

"Characterization of glycosaminoglycan and novel coronavirus (SARS-CoV-2) spike glycoprotein binding interactions" was published in Antiviral Research. At Rensselaer, Linhardt and Dordick were joined on the research by Fuming Zhang, and also by researchers at the University of California San Diego, Duke University, and the University of George, Athens with support from the National Institutes of Health.

CLEVELAND - A new Cleveland Clinic study has identified genetic factors that may influence susceptibility to COVID-19. Published today in BMC Medicine, the study findings could guide personalized treatment for COVID-19.

While the majority of confirmed COVID-19 cases result in mild symptoms, the virus does pose a serious threat to certain individuals. Morbidity and mortality rates rise dramatically with age and co-existing health conditions, such as cancer and cardiovascular disease. However, even young and otherwise healthy individuals have unpredictably experienced severe illness and death. These clinical observations suggest that genetic factors may influence COVID-19 disease susceptibility, but these factors remain largely unknown.

In this study, a team of researchers led by Feixiong Cheng, PhD, Genomic Medicine Institute, investigated genetic susceptibility to COVID-19 by examining DNA polymorphisms (variations in DNA sequences) in the ACE2 and TMPRSS2 genes. ACE2 and TMPRSS2 produce enzymes (ACE2 and TMPRSS2, respectively) that enable the virus to enter and infect human cells.

Looking at 81,000 human genomes from three genomic databases, they found 437 non-synonymous single-nucleotide variants in the protein-coding regions of ACE2 and TMPRSS2. They identified multiple potentially deleterious polymorphisms in both genes (63 in ACE2; 68 in TMPRSS2) that offer potential explanations for different genetic susceptibility to COVID-19 as well as for risk factors. Several ACE2 variants were found to be associated with cardiovascular and pulmonary conditions by potentially altering the angiotensinogen-ACE2. In addition, germline deleterious variants in the coding region of TMPRSS2, a key gene in prostate cancer, were found to occur in different cancer types, suggesting that oncogenic roles of TMPRSS2 may be linked to poor outcomes with COVID-19.

These findings demonstrate a possible association between ACE2 and TMPRSS2 polymorphisms and COVID-19 susceptibility, and indicate that a systematic investigation of the functional polymorphisms these variants among different populations could pave the way for precision medicine and personalized treatment strategies for COVID-19. However, all investigations in this study were performed in general populations, not with COVID-19 patient genetic data. Therefore, Dr. Cheng calls for a human genome initiative to validate his findings and to identify new clinically actionable variants to accelerate precision medicine for COVID-19.

"Because we currently have no approved drugs for COVID-19, repurposing already approved drugs could be an efficient and cost-effective approach to developing prevention and treatment strategies," Dr. Cheng said. "The more we know about the genetic factors influencing COVID-19 susceptibility, the better we will be able to determine the clinical efficacy of potential treatments."

Swansea University researchers have discovered two new species of parasite, previously unknown to science, in crabs in Swansea Bay, during a study on disease in the Celtic and Irish Seas.

Both species are emerging pathogens, and were discovered infecting the common shore crab, so they could potentially have damaging effects on fisheries and other marine species. The researchers' discovery will help inform measures to reduce this risk.

The common European shore crab is native to the UK, Ireland and the north east Atlantic. It shares this habitat with many commercially important species such as the edible crab and several lobster species.

The shore crab is also an invasive species in other countries as it can survive in a wide range of different environments, potentially carrying diseases with it.

The discovery was made by researchers from the BlueFish project in the University's Biosciences department. They were carrying out a year-long, multi-disease monitoring survey over two locations in Swansea Bay: Mumbles Pier and Prince of Wales dock.

When they were examining the crabs, they noticed parasites in the blood which they had never seen before.

They used a range of methods, from analysing diseased tissue from the crabs, to examining the parasite DNA using a technique called Sanger sequencing. The sequences seemed to indicate a new species.

Collaborators at the Natural History Museum, London and CEFAS in Weymouth were able to generate a longer sequence of the parasite DNA, verifying the presence of two new parasite species.

The team have named the new species Haplosporidium carcini, after the host species, (Carcinus maenas) and Haplosporidium cranc, with 'Cranc' being Welsh for crab, a reference to both their Ireland-Wales funding, and the location of discovery, or 'Welsh' nature of the parasite.

The researchers also observed that:

Infections were found in only one of the two locations - Mumbles Pier, Swansea Bay

Infection levels were very low, around 1-2%

Dr Charlotte Eve Davies from Swansea University College of Science, Scientific Officer on the Bluefish project, said:

"It is so important to understand the role of the shore crab in hosting parasites and disease, and if they are passing these on to other commercially important crustaceans.

The systematic approach we used, employing different detection methods, is vital in getting the best possible picture of these new pathogens.

Our study and broader work also suggest that the overall habitat - physical surroundings and ecosystem -may be influencing the presence and prevalence of pathogens, depending on the location.

It's been really exciting to be able to characterise two new species and a real team effort. Professor Andrew Rowley first noticed these new parasites and named them parasites x, y and z for months before we realised that we really did have a new species!"

The research was published in the journal Parasitology.

[Wednesday, July 14th Fruita, Colorado] Top predators dinosaurs like the Allosaurus and Ceratosaurus devouring dinosaur remains isn't all that surprising, but the smaller creatures feasting on dinosaur remains may just give us a more complete picture of what life was like at Mygatt-Moore Quarry outside Fruita, Colorado 152 million years ago. A new study out in PeerJ on Wednesday, July 15th, 2020 authored by Museums of Western Colorado's Paleontologist Dr. Julia McHugh, looks at the insect species who feasted on decaying dinosaurs back in the Jurassic period.

Researchers Dr. Julia McHugh (Museums of Western Colorado, Colorado Mesa University), Dr. Stephanie K. Drumheller (University of Tennessee), Anja Riedel (Colorado Mesa University), and Miriam Kane (Colorado Mesa University) examined more than 2,300 fossil bones over a two-year study and found over 400 traces left by insects and snails, a surprisingly high number. The marks researchers found on the fossils also came from at least six different invertebrates. These findings are a huge step to understanding the long-lost paleo diversity, and paleo climate of the Jurassic period.

It also gave researchers a better understanding of just how stinky the Jurassic period was too. The abundance of traces meant that the dinosaur carcasses must have been unburied for a long time - 5 months to 6 years or more according to this new study. "Large carcasses take a long time to decompose. The smell from a dead mouse in your basement is bad enough, but then imagine that mouse was a 65-foot long animal! The stench of rotting meat would have been a magnet for carrion insects and other scavengers," Dr. McHugh explains.

In a clinical trial evaluating a novel immunotherapy option for cancer treatment, a child with rhabdomyosarcoma, a form of muscle cancer, that had spread to the bone marrow, showed no detectable cancer following treatment with chimeric antigen receptor (CAR) T cells that were engineered to target the HER2 protein on the surface of the cancer cells.

The trial, conducted by researchers at Baylor College of Medicine, Texas Children's Hospital and Houston Methodist Hospital, was recently published in the journal Nature Communications.

"This child's cancer was considered high risk because it had not responded to standard chemotherapy. As a result, this child was a candidate to receive a promising new CAR T cell therapy, a personalized form of immunotherapy that redirects the patient's own immune T cells to recognize and fight the tumor," said first and corresponding author Dr. Meenakshi Hegde, assistant professor of pediatric hematology-oncology at Baylor College of Medicine and Texas Children's.

About 75 percent of the tumor cells in this patient displayed a protein on their surface called HER2. The researchers reprogrammed the T cells to target the HER2 protein by genetically engineering them to express CAR molecules that recognize the HER2-expressing (HER2+) cancer cells.

In a previous clinical trial, the HEROS study, the researchers found that CAR T cells directed at HER2+ tumor cells had a favorable safety profile. This early generation CAR T cell treatment resulted in clinical benefit in a small subset of patients, but it did not eradicate their tumors.

"From the HEROS trial, we learned that HER2-CAR T cells expanded but did not persist in the patients, which could in part explain the lack of anti-tumor responses," said Hegde, who also is part of Baylor's Dan L Duncan Comprehensive Cancer Center.

To overcome this limitation, Hegde and her colleagues added successive HER2-CAR T cell infusions along with low-dose chemotherapy to delete normal T cells as a strategy to improve the expansion and persistence of the infused HER2-CAR T cells in a trial they called, HEROS 2.0. The lymphodepleting chemotherapy administered before transferring HER2-CAR T cells eliminated the patient's existing immune cells, creating a space for the engineered CAR T cells to expand in the patient.

"Although the child had a lasting response to HER2-CAR T cells with no tumor detected, the cancer returned six months after we stopped the T cell infusions. Fortunately, the child achieved a second remission after retreatment with HER2-CAR T cells," Hegde said. "Considering the several challenges in successfully treating solid tumors using CAR T cells, achieving this exceptional tumor response is very encouraging."

At the time of this report, the child is 19 months off T cell treatment and remains healthy and cancer free.

New insights into how this exceptional recovery occurred

The sustained tumor response in this child has provided the researchers important insights into how the cancer was eliminated. The CAR T cells were developed to recognize and attack HER2+ cancer cells. Although not all cancer cells expressed HER2 on the cell surface, the tumor was eliminated in its entirety prompting the question of how the HER2-negative cancer cells were eradicated.

"We found evidence suggesting that, following the infusion of HER2-specific CAR T cells, the patient's own immune system was recruited to act against the tumor, which might help explain the durable complete response," Hegde said. "We plan on conducting more detailed experiments in a larger group of patients treated with HER2 CAR T cells to better understand the involvement of the patient's immune system in eliminating the cancer."

"It is fascinating to see remodeling of the patient's T cell compartment and development of antibodies directed against proteins implicated in tumor survival and metastasis during the course of treatment in this child. The immune activation mechanisms and associated tumor targets unfolded during the acquired response, could inform novel approaches to fight difficult-to-treat cancers," said Dr. Sujith Joseph, senior scientist at Baylor's Center for Cell and Gene Therapy, who conducted the in depth evaluation of the patient's immune response.

"This study shows that CAR T cells could perhaps act as vaccines by exposing cancer proteins to the patient's immune system. With more understanding and further refinement of their design, CAR T cells could be effective against some incurable malignancies," said senior author Dr. Nabil Ahmed, associate professor of pediatrics and immunology at Baylor and Texas Children's Hospital.

By now, we’re all aware that COVID-19 is especially dangerous for older adults—the older you are, the higher your risk for serious illness and even death if you contract the virus. Because there is no treatment or a vaccine yet, it’s vitally important that we practice social distancing and wear masks to protect ourselves from disease.

But as we work to keep ourselves safe, we also need to be sure we’re not falling into physical inactivity. When we cut ourselves off from shopping, walking in malls, and going to the gym and other places where we can exercise, we can become sedentary. Older adults who don’t get regular exercise may become prone to chronic diseases, weakened muscles, and frailty.

Researchers from the University of Sao Paulo in Brazil recently reported on the dangers of physical inactivity for older adults during COVID-19. Their paper was published in the Journal of the American Geriatrics Society.

The researchers noted that it only takes five to 10 days of physical inactivity for your muscles to begin shrinking and wasting away. This can speed the progression of sarcopenia (muscle loss) and can lead to chronic diseases.

Studies also show that older adults who walk fewer than 1,500 steps a day can lose 4 percent of the muscle tissue in their legs in just two weeks.

Although it’s too soon to know how the COVID-19 pandemic will impact physical activity, researchers say that wearable trackers (such as Fitbit) provide early estimates. Information from 30 million users worldwide estimate a 12 percent step-count decline in the United States (comparing the week of March 22, between 2019 and 2020), and an even greater decline in other countries.

Having an adequate amount of muscle mass enables you to be strong; being weak or frail is a known risk factor for death in older adults. Two weeks of inactivity (a 75 percent daily step reduction) has been shown to decrease muscle strength by 8 percent—and studies show that two weeks of rehabilitation exercises did not help people rebuild their muscle strength. What’s more, in addition to its impact on muscle mass and function, reducing steps to between 1,000 to 1,500 steps per day has been shown to raise blood sugar and increase inflammation.

The researchers suggested that strategies to reduce the potential unhealthy effects of isolation are important. Resistance exercise is a classic and proven method to increase muscle mass, strength, and mobility, even for people in their 90s. Exercise programs you can do at home are especially important during isolation, and are a good way to maintain or even improve your muscle health and mobility. Exercise also helps prevent falls, a common cause of disability and hospitalization for older adults.

The researchers suggested that health education for older adults should include recommendations to introduce light activity into daily routines, focusing on sitting less and moving more, which is particularly important for people with mobility issues.

Good ways to work in more movement include:

Interrupting prolonged sitting time by taking strolling or standing breaks (such as moving around during commercials while watching TV).
Performing light household chores like cleaning and gardening and enjoying leisure activities such as dancing or short-distance walking.
Joining family members in-person (when safe) or remotely by FaceTime or Zoom to stay active and gain emotional support.

HealthinAging.org, maintained by the American Geriatrics Society, offers helpful suggestions for getting the right amount of physical activity.

This summary is from “Risk of Increased Physical Inactivity during COVID-19 Outbreak for the Elderly: A Call for Actions.” It appears online ahead of print in the Journal of the American Geriatrics Society. The study authors are Hamilton Roschel, PhD; Guilherme G. Artioli, PhD; and Bruno Gualano, PhD.

Journal

Journal of the American Geriatrics Society

DOI

10.1111/jgs.16550

Image: https://docs.google.com/document/d/1cpdYrtjo6mLDF5YCxmGmfyyKosNnrRfRefyaZWHyK8c/edit

Video: https://www.youtube.com/watch?v=GRT7FF2eVwU

A new robotic prosthetic leg prototype offers a more natural gait while also being quieter and more energy efficient than other designs.

The key is the use of new small and powerful motors, originally designed for a robotic arm on the International Space Station. The streamlined design offers a free-swinging knee and regenerative braking, which charges the battery with energy captured when the foot hits the ground. This feature enables the leg to more than double a typical prosthetic user's walking needs with one charge per day.

"Our prosthetic leg consumes approximately half the battery power of state-of-art robotic legs, yet can produce more force," said Robert Gregg, an associate professor of electrical and computer engineering at the University of Michigan and a member of the U-M Robotics Institute, who led the study while at the University of Texas at Dallas. Gregg moved to U-M last year.

Using conventional prosthetics, amputees must raise their hips to lift the prosthetic foot from the floor and swing the leg forward. This unnatural gait takes more energy than ordinary walking, causes extra stress and pain in the hips and lower back, and eventually damages the joints. Robotic legs have the potential to provide a much more comfortable gait, but one of their drawbacks is stiffness in the joints.

"We designed our joints to be as compliant, or flexible, as possible," said Toby Elery, first author of the study and recent doctoral graduate from UT Dallas. "Our robotic leg can perform and even react like a human joint would, enabling a naturally free-swinging knee and shock absorption when contacting the ground."

Motors in robotic legs need to fit into the space that an ordinary limb would take up. In the past, this has meant using small motors that spin quickly, and then using a series of gears to convert the fast spin into a more powerful force.

The problem is that the gears are noisy, inefficient, add weight and make it harder for the joints to swing. Gregg's group surmounted this by incorporating two of those stronger space station motors, one powering the knee and the other powering the ankle.

There are many benefits to using fewer gears. In addition to enabling the free-swinging knee, removing gears brought the noise level down from the scale of a vacuum cleaner to a refrigerator. Also, the regenerative braking absorbs some of the shock when the prosthetic foot hits the ground.

"If the joints are stiff or rigid, the force is transferred to the residual limb, and that can be painful," Gregg said. "Instead, we use that force to charge the battery."

The amputees who test drive the prosthetics in Gregg's lab say they can feel the leg helping them push off the ground as they walk.

"In some cases, they have observed that they feel like muscles in their hips and back are working less with our leg, compared to their conventional leg," Gregg said. "We're able to reduce compensations at the hips."

The team's next step is to improve the control algorithms that can help the leg automatically adjust to different terrain, changes in pace and transitions between different types of activity.

Wouldn't we all appreciate a little help around the house, especially if that help came in the form of a smart, adaptable, uncomplaining robot? Sure, there are the one-trick Roombas of the appliance world. But MIT engineers are envisioning robots more like home helpers, able to follow high-level, Alexa-type commands, such as "Go to the kitchen and fetch me a coffee cup."

To carry out such high-level tasks, researchers believe robots will have to be able to perceive their physical environment as humans do.

"In order to make any decision in the world, you need to have a mental model of the environment around you," says Luca Carlone, assistant professor of aeronautics and astronautics at MIT. "This is something so effortless for humans.

But for robots it's a painfully hard problem, where it's about transforming pixel values that they see through a camera, into an understanding of the world."
Now Carlone and his students have developed a representation of spatial perception for robots that is modeled after the way humans perceive and navigate the world.

The new model, which they call 3D Dynamic Scene Graphs, enables a robot to quickly generate a 3D map of its surroundings that also includes objects and their semantic labels (a chair versus a table, for instance), as well as people, rooms, walls, and other structures that the robot is likely seeing in its environment.

The model also allows the robot to extract relevant information from the 3D map, to query the location of objects and rooms, or the movement of people in its path.

"This compressed representation of the environment is useful because it allows our robot to quickly make decisions and plan its path," Carlone says. "This is not too far from what we do as humans. If you need to plan a path from your home to MIT, you don't plan every single position you need to take. You just think at the level of streets and landmarks, which helps you plan your route faster."

Beyond domestic helpers, Carlone says robots that adopt this new kind of mental model of the environment may also be suited for other high-level jobs, such as working side by side with people on a factory floor or exploring a disaster site for survivors.

He and his students, including lead author and MIT graduate student Antoni Rosinol, will present their findings this week at the Robotics: Science and Systems virtual conference.

A mapping mix

At the moment, robotic vision and navigation has advanced mainly along two routes: 3D mapping that enables robots to reconstruct their environment in three dimensions as they explore in real time; and semantic segmentation, which helps a robot classify features in its environment as semantic objects, such as a car versus a bicycle, which so far is mostly done on 2D images.

Carlone and Rosinol's new model of spatial perception is the first to generate a 3D map of the environment in real-time, while also labeling objects, people (which are dynamic, contrary to objects), and structures within that 3D map.

The key component of the team's new model is Kimera, an open-source library that the team previously developed to simultaneously construct a 3D geometric model of an environment, while encoding the likelihood that an object is, say, a chair versus a desk.

"Like the mythical creature that is a mix of different animals, we wanted Kimera to be a mix of mapping and semantic understanding in 3D," Carlone says.

Kimera works by taking in streams of images from a robot's camera, as well as inertial measurements from onboard sensors, to estimate the trajectory of the robot or camera and to reconstruct the scene as a 3D mesh, all in real-time.

To generate a semantic 3D mesh, Kimera uses an existing neural network trained on millions of real-world images, to predict the label of each pixel, and then projects these labels in 3D using a technique known as ray-casting, commonly used in computer graphics for real-time rendering.

The result is a map of a robot's environment that resembles a dense, three-dimensional mesh, where each face is color-coded as part of the objects, structures, and people within the environment.

A layered scene

If a robot were to rely on this mesh alone to navigate through its environment, it would be a computationally expensive and time-consuming task. So the researchers built off Kimera, developing algorithms to construct 3D dynamic "scene graphs" from Kimera's initial, highly dense, 3D semantic mesh.

Scene graphs are popular computer graphics models that manipulate and render complex scenes, and are typically used in video game engines to represent 3D environments.

In the case of the 3D dynamic scene graphs, the associated algorithms abstract, or break down, Kimera's detailed 3D semantic mesh into distinct semantic layers, such that a robot can "see" a scene through a particular layer, or lens. The layers progress in hierarchy from objects and people, to open spaces and structures such as walls and ceilings, to rooms, corridors, and halls, and finally whole buildings.

Carlone says this layered representation avoids a robot having to make sense of billions of points and faces in the original 3D mesh.

Within the layer of objects and people, the researchers have also been able to develop algorithms that track the movement and the shape of humans in the environment in real time.

The team tested their new model in a photo-realistic simulator, developed in collaboration with MIT Lincoln Laboratory, that simulates a robot navigating through a dynamic office environment filled with people moving around.

"We are essentially enabling robots to have mental models similar to the ones humans use," Carlone says. "This can impact many applications, including self-driving cars, search and rescue, collaborative manufacturing, and domestic robotics.

Another domain is virtual and augmented reality (AR). Imagine wearing AR goggles that run our algorithm: The goggles would be able to assist you with queries such as 'Where did I leave my red mug?' and 'What is the closest exit?'

You can think about it as an Alexa which is aware of the environment around you and understands objects, humans, and their relations."

"Our approach has just been made possible thanks to recent advances in deep learning and decades of research on simultaneous localization and mapping," Rosinol says. "With this work, we are making the leap toward a new era of robotic perception called spatial-AI, which is just in its infancy but has great potential in robotics and large-scale virtual and augmented reality."

Boston, MA -- More than 3 million people in the United States have been infected with COVID-19 and more than 130,000 have died. More people have died of COVID-19 in the U.S. than in any other country, but few studies offer national data on the factors that may contribute to outcomes for critically ill patients. To address this gap, investigators from more than 65 sites across the country, led by a team from Brigham and Women's Hospital, conducted the Study of the Treatment and Outcomes in critically ill Patients with COVID-19 (STOP-COVID), a multicenter cohort examination of the demographics, comorbidities, organ dysfunction, treatment, and outcomes of patients with COVID-19 admitted to intensive care units. The team studied over 2,000 critically ill adults with COVID-19, and found that 35 percent of patients died in the 28 days after ICU admission. They also found that treatment and outcomes varied greatly between hospitals. Results of their work are published in JAMA Internal Medicine.

"The U.S. is currently the epicenter of COVID-19, yet few national data are available on the epidemiologic factors, treatments, and outcomes of critically ill patients with COVID-19 in the U.S.," said corresponding author David E. Leaf, MD, MMSc, an associate physician in the Division of Renal Medicine at the Brigham. "We found that critically ill patients with COVID-19 have a greater than 1-in-3 chance of short-term death. We also found that treatment and outcomes varied considerably between hospitals, with a death rate more than three-fold higher in patients admitted to hospitals with fewer ICU beds."

The multicenter cohort study included Brigham and Women's Hospital and 64 other sites from the Northeast, South, Midwest and West regions of the U.S., including parts of the U.S. that were heavily affected by COVID-19. The study included 2,215 adults with laboratory-confirmed COVID-19 who were admitted to ICUs between March 4 and April 4, 2020.

Overall, 784 patients (35 percent) died within 28 days, with wide variation among hospitals. Factors independently associated with death included older age, male sex, higher body mass index, coronary artery disease, active cancer, and the presence of low oxygen levels, liver dysfunction, and kidney dysfunction at the time of ICU admission.

Even after adjusting for a variety of risk factors, death rates varied widely across hospitals, from 6 percent to 80 percent. The number of pre-COVID ICU beds in the hospital was strongly associated with death rate. Patients admitted to hospitals with less than 50 ICU beds had a more than three-fold higher risk of death than patients admitted to hospitals with 100 or more ICU beds.

In addition, hospitals varied widely in the proportion of patients who received medications and supportive therapy for COVID-19. During the time period studied, hydroxychloroquine, azithromycin, and anticoagulants were commonly prescribed, and interventions such as prone positioning were also being implemented. But the proportion of patients receiving these measures varied considerably -- for instance, the use of prone positioning ranged from 4 percent of patients at one hospital to 80 percent at another.

While the team adjusted for a large number of demographic and severity of illness characteristics, its estimates of differences in death rates across hospitals may be impacted by other confounders, such as the socioeconomic status of patients -- a risk factor increasingly recognized as important in health outcomes for COVID-19 patients. The team's models also do not account for varying degrees of strain across hospitals.

"This is the largest nationwide study of patients with COVID-19 admitted to ICUs across geographically diverse sites in the U.S.," said lead author Shruti Gupta, MD, MPH, a physician in the Brigham's Renal Division. "These are the patients with the highest mortality. Our study confirms that certain factors, such as older age and higher BMI, are associated with an increased risk of death. We also identified several novel risk factors for death, such as treatment at a hospital with fewer ICU beds. That's one of the most intriguing findings from our work, which, along with many other questions, we'll be pursuing in the future."

To catch a thief, the saying goes, you have to think like a thief. The same is true for invasive predators: to foil their depredations on native wildlife, scientists have to understand how they think.

A new study published in the Ecological Society of America's journal Ecological Applications examines how invasive mammalian predators both habituate to and generalize avian prey cues. Dr. Price and her team at Manaaki Whenua Landcare Research studied the behavior of ferrets and hedgehogs--invasive mammals in New Zealand--in an outdoor enclosure experiment to understand how they hunt avian prey. The discovery could have conservation applications for protecting native bird species.

Previous research has established that "chemical camouflage" could be an effective way to deter invasive species from harming vulnerable bird populations: scientists can distribute appealing bird odors near nests before eggs appear, so that the predator eventually starts ignoring the smell--even after tasty eggs become available.

This study goes a step further, showing that invasive predators not only learn to pinpoint (or ignore) certain smells that are associated with food--they can also classify similar smells into groups.

"We are trying to understand how these predators have been so effective at destroying the native fauna," says Catherine Price, a postdoctoral research associate at the University of Sydney and the study's lead author. "We are researching new ways to exploit behavioral patterns and traits to understand why native species are so vulnerable and how to protect them."

In New Zealand, invasive mammalian predators have devastated local bird populations, especially of the wrybill, double-banded plover, kak?, and black-fronted tern, whose populations nest at the same time and in similar locations. Such nesting colonies are the proverbial sitting duck: with no defenses, small numbers of predators like ferrets and hedgehogs can essentially wipe out nearly a generation with very little effort.

Hedgehogs and ferrets are generalists. Ferrets mainly hunt rabbits but will not turn down an easy meal of eggs or chicks. Hedgehogs eat mostly invertebrates and berries but also love eggs, especially right out of hibernation when they are especially hungry.

Price wanted to understand how the predators seek out bird colonies. While humans are primarily visual, many other animals--including ferrets and hedgehogs--draw more information from other senses, including their sense of smell.

"Because humans aren't olfactory species, we don't often think about odor," Price said. "But these predators are very sensitive to odor, and to the costs of odor. They respond very quickly if a hunting tactic--like following a certain odor--isn't working."

Price and her team captured local ferrets and hedgehogs and ran them through a series of controlled treatments in outdoor enclosures resembling their natural habitat to examine how these predators categorize smells--whether they group smells of similar types of birds together--and how and whether they habituate to smells. This is the first time this kind of research has been done on these predators in a controlled outdoor setting.

The question of categorization reveals a substantial amount about the hunting strategies and priorities of the predator. Separating smells into individual species requires an investment that might not always be merited. In some cases, it is sufficient for ferrets or hedgehogs to simply sniff out a broad category of prey, such as "ground-nesting bird with eggs this time of year," but knowing exactly what kind of bird they are smelling is irrelevant.

"The idea that animals are grouping prey together by smell is exciting," Price said. "We never assumed wild animals did that before, and now we've shown that they can do this using smell."

The team discovered that ferrets generalized the avian smells (in this case gulls and quail) but the hedgehogs did not. In many ways, this makes sense: ferrets consume lots of prey besides bird species, so distinguishing between bird smells may not be worth a ferret's time or energy. Seasonality may also have played a role. In the experiment, hedgehogs were getting ready to go into hibernation, making them especially motivated to find high-quality meals easily.

This finding indicates it might be possible to protect bird colonies by distributing bird smell around the area. If an entire area were saturated with the smell of a nesting ground species, it could protect a nesting colony. Predators would become accustomed to the smell and ignore it, seeking out other prey.

"Understanding how predators group smell is important because if they generalize, we don't have to actually put out the smell of the bird we're protecting; we can put out chicken or quail odors that we can easily get in abundance," Price said.

Understanding how invasive predators hunt and think gives scientists and conservationists an edge in protecting native prey. Further studies may reveal more ways to protect native populations by exploiting predators' behaviors.