Culture

With the rise of genomic sequencing, health technology companies are promising parents they can detect rare metabolic disorders in newborns who, despite a healthy appearance, may need immediate treatment.

Now, scientists from UC San Francisco, UC Berkeley and Tata Consultancy Services are offering the first comprehensive assessment of how sequencing stacks up to the older screening technology, tandem mass spectrometry (MS/MS), that California uses to analyze the blood spots taken at birth for rare disorders, known as inborn errors of metabolism. They found that, when used alone, sequencing comes up short, missing some sick babies, while flagging many healthy ones for unnecessary follow-up testing. But sequencing can still be useful in cases that look suspicious but were not clearly identified by MS/MS.

"There has been a lot of publicity about universal sequencing for newborns," said Jennifer Puck, MD, professor of pediatrics at UC San Francisco and co-senior author of the study, published Aug. 10, 2020, in Nature Medicine. "But claims that sequencing is the key to health have been made without the support of rigorous studies."

Accuracy is essential when it comes to newborn screening. If cases are missed, seriously ill babies will go without prompt treatment for diseases that require urgent attention, such as phenylketonuria (PKU), which causes cognitive impairment when left untreated. But referring healthy babies for expert care is wasteful and puts families through unnecessary stress.

This study used a technique called whole-exome sequencing to look for mutations in 78 genes that are known to be involved in the 48 metabolic disorders for which every California newborn is screened. These diseases are rare, affecting about 150 of the estimated half a million babies born each year in California, and there are no signs when babies are born that they are going to get sick.

Since screening is meant for asymptomatic individuals, in this case newborns, it's very different from using sequencing as a diagnostic aid for patients with a medical problem that has already been detected.

"All of the prior studies of the utility of exome sequencing have started with a patient already in front of a doctor--in other words, a patient with a problem," Puck said. "You start with a clue in hand, a person with a particular difficulty, and you're trying to see if there's an underlying genetic reason for that. When you switch to screening mode, you don't have any clues. Most newborns look perfectly healthy."

Inborn metabolic disorders provided a unique opportunity to benchmark the performance of whole-exome sequencing, because it could be compared with California's well-established newborn screening program, which has been using MS/MS since 2005. These disorders have been well studied, and they are known to be caused by changes in a limited set of genes, most of which have been identified. So when they embarked on the study, the team had expected that sequencing technology might do better than the state's MS/MS screening method.

The state's current method looks for clues in babies' blood that something is wrong. The team found that the dried blood spots, which are taken at birth and then stored, could be used years later to analyze DNA. This provided a comprehensive view of nearly all the babies born in California with inborn errors of metabolism--about 1,334 of the nearly 4.5 million babies who were born in the period under study, from July of 2005 to December of 2013.

The team found that the standard MS/MS screening found 99 percent of babies with metabolic disorders, with a false positive rate of just 0.2 percent. But whole-exome sequencing would have found only 88 percent, missing about 160 of the 1,334 California babies who were ultimately diagnosed with metabolic disorders, while incorrectly identifying about 8,000 babies each year as being in need of urgent evaluation by a metabolic disease specialist.

The scientists said the shortcomings of the sequencing approach could have several causes.

"These are well-studied single-gene conditions, but that does not mean we have found all the genes associated with them," said first author Aashish Adhikari, PhD, a member of UCSF's Institute for Human Genetics and UC Berkeley's Department of Plant and Microbial Biology. "Additional genes could be involved, as well as additional biological and environmental factors that may limit our ability to predict disease from DNA sequences alone."

Another problem is that these diseases are so rare that scientists haven't had many sequences to examine. Also, California's newborns are from highly diverse genetic backgrounds, with many variants that have never before been analyzed, since previous studies have emphasized people of Northern European ancestry. To analyze these new variants and predict their impact, the team had to develop a special computational pipeline.

But if whole-exome sequencing has limited use as a standalone primary screen, the study demonstrated that it still can be used to make a definitive diagnosis in cases where MS/MS showed something might be wrong, but doctors were unsure of what it was. And sequencing may yet prove useful in identifying newborns with treatable conditions that current screening methods cannot find.

"If the current mass spectrometry testing comes out unclear, sequencing could reveal a gene variant that solves the mystery," said Steven Brenner, PhD, professor at UC Berkeley, a member of UCSF's Institute for Human Genetics, and co-senior author of the study. "Sequencing to screen additional carefully vetted disorders could enable timely treatment of some children with conditions that presently go unrecognized until it's too late for optimal intervention."

(Boston)-- Although macrophages (cells involved in the detection and destruction of bacteria and other harmful organisms as well as dead cells) are classified as immune cells functioning in the activation and resolution of tissue inflammation, it is now clear that they are critically involved in a variety of disease processes, such as chronic inflammatory diseases, tumor growth and metastasis and tissue fibrosis.

For the first time, researchers from Boston University School of Medicine (BUSM) have characterized the origins, gene expression and diverse functions of resident macrophages in normal skeletal muscle. The findings they believe will provide a knowledge base for future studies of the roles of skeletal muscle resident macrophages in skeletal muscle diseases such as muscular dystrophies as well as muscular injuries such as muscle trauma.

People frequently suffer muscle injuries caused by accidents or sports, while others develop muscle diseases such as muscular dystrophies that display prominent muscle inflammation. Duchenne muscular dystrophy is the most common genetic muscle disease. It causes severe disability and premature death caused by breathing and heart muscle weakness. Currently, the disease has no cure.

"Macrophages are important effectors and regulators of muscle inflammation, fibrosis and regeneration. Our findings build a knowledge base for future studies of resident macrophages in skeletal muscle development, injury repair and diseases with prominent muscle inflammation," explained corresponding author Lan Zhou, MD, PhD, professor of neurology at BUSM. "Understanding their respective origins, tissue-specific characteristics and disease-related functions is absolutely essential to harness their therapeutic potential."

Zhou and her team used experimental models to allow macrophage lineage tracing and performed bone marrow transplant experiments to study the origins of skeletal muscle resident macrophages. They also performed single cell-based transcriptome analyses to analyze subsets of skeletal muscle resident macrophages and their functions.

In a publication in Nature Communications last Friday, NIOZ scientists Nina Dombrowski and Anja Spang and their collaboration partners describe a previously unknown phylum of aquatic Archaea that are likely dependent on partner organisms for growth while potentially being able to conserve some energy by fermentation. In contrast to initial analyses, this study shows that the new phylum is part of a group of Archaea that are believed to mainly comprise symbionts. Further, the study yields new insights into the diversity and evolutionary history of the Archaea.

Archaea make up one of the main divisions of life, next to the Bacteria and the Eukaryotes, the latter of which comprise for example fungi, plants and animals. Archaea are a large group of microorganisms that live in all habitats on Earth ranging from soils and sediments to marine and freshwater environments as well as from human-made to host-associated habitats including the gut. In turn, Archaea are now thought to play a major role in biogeochemical nutrient cycles.

In a publication in Nature Communications last Friday, evolutionary microbiologists Nina Dombrowski and Anja Spang from the Royal Netherlands Institute of Sea Research (NIOZ) describe a previously unknown archaeal lineage (phylum). The authors named them the Undinarchaeota, in reference to the female water spirit or nymph Undina. For the study, Dombrowski and Spang cooperated with partners from Bristol University, the University of Queensland and the Australian National University.

Diverse symbionts and parasites

Because of their great resemblance to Bacteria, Archaea were only described as a separate lineage about 40 years ago and were not studied intensely until very recently, when it became possible to sequence DNA directly from environmental samples and to reconstruct genomes from uncultivated organisms. This field of genetic research, generally referred to as metagenomics (Figure 1), has not only revealed that microbial life including the Archaea is much more diverse than originally thought, but also provided data needed to shed light on the function of these microbes in their environments.

The newly described Undinarchaeota were discovered in genetic material from marine (Indian, Mediterranean and Atlantic ocean) and aquifer (Rifle aquiver, Colorado River) environments. The authors could show that they belong to a very diverse and until recently unknown group of so-called DPANN archaea. Members of the DPANN include organisms with very small genomes and limited metabolic capabilities, which suggests that these organisms depend on other microbes for growth and survival1,2,3. In fact, the few so far cultivated DPANN archaea are obligate symbionts or parasites that cannot live on their own4.

"In line with this, the Undinarchaeota seem to lack several anabolic pathways, indicating that they are, too, depend on various metabolites from so far unknown partner organisms", says research leader Anja Spang. "However, Undinarchaeota seem to have certain metabolic pathways that lack in some of the most parasitic DPANN archaea and may be able to conserve energy by fermentation."

Complex evolutionary history

While DPANN have only been discovered recently, it becomes increasingly clear that they are widespread and that representatives inhabit all thinkable environments on Earth. Yet, little is known about their evolutionary and ecological role. "In some way, some of the DPANN archaea resemble viruses, needing a host organism, likely other archaea or bacteria, for survival", says Spang. "However, and in contrast to viruses, we currently know very little about the DPANN archaea and how they affect food webs and host evolution. It is also unclear whether DPANN are an ancient archaeal lineage that resembles early cellular life or have evolved later or in parallel with their hosts."

With their study, the authors could shed more light on the complex evolution of Archaea. "Our work revealed that many DPANN archaea frequently exchange genes with their hosts, which makes it very challenging to reconstruct their evolutionary history", says first author Nina Dombrowski. Tom Williams (Bristol University) adds: "However, we could show that DPANN have probably evolved in parallel with their hosts over a long evolutionary time scale, by identifying and studying those genes that were inherited from parent-to-offspring instead of having been transferred between host and symbiont".

Role in marine biogeochemical cycles

Spang expects that certain DPANN including the Undinarchaeota, may be important for biogeochemical nutrient cycles within the oceans and sediments. "One reason that DPANN were discovered relatively recently, is that they were not retained on the filters originally used for concentrating cells from environmental samples due to their small cell sizes." But since their discovery, DPANN turned out to be much more widespread than originally anticipated. Chris Rinke from the University of Queensland: "Prospective research on the Undinarchaeota and other DPANN archaea will be essential to obtain a better understanding of marine biogeochemical cycles and the role symbionts play in the transformation of organic matter."

These questions drive some of the prospective projects of Anja Spang. In particular, in collaboration with their NIOZ colleagues Laura Villanueva, Pierre Offre and Julia Engelmann, the authors of the publication Anja Spang and Nina Dombrowski have just sequenced new DNA from water samples from the Black Sea, revealing that Undinarchaeota are present in almost all anoxic depth layers of this basin. Spang says: "These data are a gold mine for the future exploration of the ecology and evolution of these potentially symbiotic Archaea, allowing us to identify their interaction partners and to unravel further secrets about the biology of the Undinarchaeota."

The world's 'best of the last' tropical forests are at significant risk of being lost, according to a paper released today in Nature Ecology and Evolution. Of these pristine forests that provide key services--including carbon storage, prevention of disease transmission and water provision--only a mere 6.5 percent are formally protected.

In the study, the United Nations Development Programme (UNDP), the National Aeronautics and Space Administration (NASA), Wildlife Conservation Society and scientists from eight leading research institutions--including professor Scott Goetz, research professor Patrick Jantz and research associate Pat Burns of Northern Arizona University' School of Informatics, Computing, and Cyber Systems--identified significant omissions in international forest conservation strategies. Current global targets focus solely on forest extent and fail to acknowledge the importance of forest intactness, or structural condition, creating a critical gap in action to safeguard ecosystems essential for human and planetary well-being.

New targets that recognize forest quality are urgently needed to safeguard the Earth's precious humid tropical forests. Of the 1.9 million hectares of humid tropical forests globally, the study advocated for new protections in 41 percent of these areas, active restoration in 7 percent and reduction of human pressure in 19 percent to promote coordinated strategies to sustain forests of high ecological value.

"By serving as a convener to bring together the world's best scientists with governments, UNDP plays a critical role in ensuring that cutting-edge research is relevant for the development of key international agreements and implementation at the national level," commented Haoliang Xu, UN Assistant Secretary-General and UNDP Director of Bureau for Policy and Programme Support.

Collaborating with UNDP Country Offices and key stakeholders in Brazil, Colombia, Costa Rica, the Democratic Republic of the Congo, Ecuador, Indonesia, Peru, and Viet Nam, researchers mapped the location of high-quality forests using recently developed high-resolution maps of forest structure and human pressure across the global humid tropics.

The paper reveals that the Earth's humid tropical forests, only half of which have high ecological integrity, are largely limited to the Amazon and Congo Basins. The vast majority of these forests have no formal protection and, given recent rates of loss, are at significant risk.

With the rapid disappearance of these 'best of the last' forests at stake, the paper provides a policy-driven framework for their conservation and restoration, recommending locations to maintain protections, add new protections, restore forest structure, and mitigate human pressure.

The coming year is a so-called 'super year' for biodiversity, in which the world will agree on a new deal for nature that will shape global action for the next 30 years. Countries will also have a final chance to revise their contributions to reduce carbon emissions before the Paris Climate Agreement goes into effect. Both these milestones will impact efforts to advance the nature-based Sustainable Development Goals of the 2030 Agenda.

"The work reported in this paper is the result of a long process assessing the condition of the world's tropical forests," said Goetz, a co-author of the paper. "The breakthrough here was being able to use spaceborne satellite data to provide the first robust estimates of the structural condition of forests in three dimensions, not just forest canopy cover."

"Advances in earth observation instruments and methodologies developed by NASA and partner institutions, coupled with the use of incredibly powerful computing systems like NAU's Monsoon and Google Earth Engine, enabled a near-global mapping of tropical forest quality. We synthesized the best available earth observation datasets to map the changing condition of the Earth's tropical forests, finding that only 6.5 percent of the highest quality tropical forests are formally protected. We hope that the conservation strategies proposed as part of this international effort will be a step towards conserving high quality forests and restoring those that have been degraded," said Burns.

"Every year, research reveals new ways that old, structurally complex forests contribute to biodiversity, carbon storage, water resources, and many other ecosystem services. That we can now map such forests in great detail is an important step forward in efforts to conserve them," said Jantz.

Army researchers developed a reinforcement learning approach that will allow swarms of unmanned aerial and ground vehicles to optimally accomplish various missions while minimizing performance uncertainty.

Swarming is a method of operations where multiple autonomous systems act as a cohesive unit by actively coordinating their actions.

Army researchers said future multi-domain battles will require swarms of dynamically coupled, coordinated heterogeneous mobile platforms to overmatch enemy capabilities and threats targeting U.S. forces.

The Army is looking to swarming technology to be able to execute time-consuming or dangerous tasks, said Dr. Jemin George of the U.S. Army Combat Capabilities Development Command's Army Research Laboratory.

"Finding optimal guidance policies for these swarming vehicles in real-time is a key requirement for enhancing warfighters' tactical situational awareness, allowing the U.S. Army to dominate in a contested environment," George said.

Reinforcement learning provides a way to optimally control uncertain agents to achieve multi-objective goals when the precise model for the agent is unavailable; however, the existing reinforcement learning schemes can only be applied in a centralized manner, which requires pooling the state information of the entire swarm at a central learner. This drastically increases the computational complexity and communication requirements, resulting in unreasonable learning time, George said.

In order to solve this issue, in collaboration with Prof. Aranya Chakrabortty from North Carolina State University and Prof. He Bai from Oklahoma State University, George created a research effort to tackle the large-scale, multi-agent reinforcement learning problem. The Army funded this effort through the Director's Research Award for External Collaborative Initiative, a laboratory program to stimulate and support new and innovative research in collaboration with external partners.

The main goal of this effort is to develop a theoretical foundation for data-driven optimal control for large-scale swarm networks, where control actions will be taken based on low-dimensional measurement data instead of dynamic models.

The current approach is called Hierarchical Reinforcement Learning, or HRL, and it decomposes the global control objective into multiple hierarchies - namely, multiple small group-level microscopic control, and a broad swarm-level macroscopic control.

"Each hierarchy has its own learning loop with respective local and global reward functions," George said. "We were able to significantly reduce the learning time by running these learning loops in parallel."

According to George, online reinforcement learning control of swarm boils down to solving a large-scale algebraic matrix Riccati equation using system, or swarm, input-output data.

The researchers' initial approach for solving this large-scale matrix Riccati equation was to divide the swarm into multiple smaller groups and implement group-level local reinforcement learning in parallel while executing a global reinforcement learning on a smaller dimensional compressed state from each group.

Their current HRL scheme uses a decupling mechanism that allows the team to hierarchically approximate a solution to the large-scale matrix equation by first solving the local reinforcement learning problem and then synthesizing the global control from local controllers (by solving a least squares problem) instead of running a global reinforcement learning on the aggregated state. This further reduces the learning time.

Experiments have shown that compared to a centralized approach, HRL was able to reduce the learning time by 80% while limiting the optimality loss to 5%.

"Our current HRL efforts will allow us to develop control policies for swarms of unmanned aerial and ground vehicles so that they can optimally accomplish different mission sets even though the individual dynamics for the swarming agents are unknown," George said.

George stated that he is confident that this research will be impactful on the future battlefield, and has been made possible by the innovative collaboration that has taken place.

"The core purpose of the ARL science and technology community is to create and exploit scientific knowledge for transformational overmatch," George said. "By engaging external research through ECI and other cooperative mechanisms, we hope to conduct disruptive foundational research that will lead to Army modernization while serving as Army's primary collaborative link to the world-wide scientific community."

The team is currently working to further improve their HRL control scheme by considering optimal grouping of agents in the swarm to minimize computation and communication complexity while limiting the optimality gap.

They are also investigating the use of deep recurrent neural networks to learn and predict the best grouping patterns and the application of developed techniques for optimal coordination of autonomous air and ground vehicles in Multi-Domain Operations in dense urban terrain.

George, along with the ECI partners, recently organized and chaired an invited virtual session on Multi-Agent Reinforcement Learning at the 2020 American Control Conference, where they presented their research findings.

Highlights:

Previously autism diagnosed by symptoms only

Subtype characterized by abnormal lipid levels

Autism affects estimated 1 in 54 children in U.S.

CHICAGO ---A novel precision medicine approach enhanced by artificial intelligence (AI) has laid the groundwork for what could be the first biomedical screening and intervention tool for a subtype of autism, reports a new study from Northwestern University, Ben Gurion University, Harvard University and the Massachusetts Institute of Technology.

The approach is believed to be the first of its kind in precision medicine.

"Previously, autism subtypes have been defined based on symptoms only -- autistic disorder, Asperger syndrome, etc. -- and they can be hard to differentiate as it is really a spectrum of symptoms," said study co-first author Dr. Yuan Luo, associate professor of preventive medicine: health and biomedical informatics at the Northwestern University Feinberg School of Medicine. "The autism subtype characterized by abnormal levels identified in this study is the first multidimensional evidenced-based subtype that has distinct molecular features and an underlying cause."

Luo is also chief AI officer at the Northwestern University Clinical and Translational Sciences Institute and the Institute of Augmented Intelligence in Medicine. He also is a member of the McCormick School of Engineering.

The findings were published August 10 in Nature Medicine.

Autism affects an estimated 1 in 54 children in the United States, according to the Centers for Disease Control and Prevention. Boys are four times more likely than girls to be diagnosed. Most children are diagnosed after age 4, although autism can be reliably diagnosed based on symptoms as early as age 2.

The subtype of the disorder studied by Luo and colleagues is known as dyslipidemia-associated autism, which represents 6.55% of all diagnosed autism spectrum disorders in the U.S.

"Our study is the first precision medicine approach to overlay an array of research and health care data -- including genetic mutation data, sexually different gene expression patterns, animal model data, electronic health record data and health insurance claims data --and then use an AI-enhanced precision medicine approach to attempt to define one of the world's most complex inheritable disorders," said Luo.

The idea is similar to that of today's digital maps. In order to get a true representation of the real world, the team overlaid different layers of information on top of one another.

"This discovery was like finding a needle in a haystack, as there are thousands of variants in hundreds of genes thought to underlie autism, each of which is mutated in less than 1% of families with the disorder. We built a complex map, and then needed to develop a magnifier to zoom in," said Luo.

To build that magnifier, the research team identified clusters of gene exons that function together during brain development. They then used a state-of-the-art AI algorithm graph clustering technique on gene expression data. Exons are the parts of genes that contain information coding for a protein. Proteins do most of the work in our cells and organs, or in this case, the brain.

"The map and magnifier approach showcases a generalizable way of using multiple data modalities for subtyping autism and it holds the potential for many other genetically complex diseases to inform targeted clinical trials," said Luo.

Using the tool, the research team also identified a strong association of parental dyslipidemia with autism spectrum disorder in their children. They further saw altered blood lipid profiles in infants later diagnosed with autism spectrum disorder. These findings have led the team to pursue subsequent studies, including clinical trials that aim to promote early screening and early intervention of autism.

"Today, autism is diagnosed based only on symptoms, and the reality is when a physician identifies it, it's often when early and critical brain developmental windows have passed without appropriate intervention," said Luo. "This discovery could shift that paradigm."

Scientists have tracked a 'boomerang' earthquake in the ocean for the first time, providing clues about how they could cause devastation on land.

Earthquakes occur when rocks suddenly break on a fault - a boundary between two blocks or plates. During large earthquakes, the breaking of rock can spread down the fault line. Now, an international team of researchers have recorded a 'boomerang' earthquake, where the rupture initially spreads away from initial break but then turns and runs back the other way at higher speeds.

The strength and duration of rupture along a fault influences the among of ground shaking on the surface, which can damage buildings or create tsunamis. Ultimately, knowing the mechanisms of how faults rupture and the physics involved will help researchers make better models and predictions of future earthquakes, and could inform earthquake early-warning systems.

The team, led by scientists from the University of Southampton and Imperial College London, report their results today in Nature Geoscience.

While large (magnitude 7 or higher) earthquakes occur on land and have been measured by nearby networks of monitors (seismometers), these earthquakes often trigger movement along complex networks of faults, like a series of dominoes. This makes it difficult to track the underlying mechanisms of how this 'seismic slip' occurs.

Under the ocean, many types of fault have simple shapes, so provide the possibility get under the bonnet of the 'earthquake engine'. However, they are far from large networks of seismometers on land. The team made use of a new network of underwater seismometers to monitor the Romanche fracture zone, a fault line stretching 900km under the Atlantic near the equator.

In 2016, they recorded a magnitude 7.1 earthquake along the Romanche fracture zone and tracked the rupture along the fault. This revealed that initially the rupture travelled in one direction before turning around midway through the earthquake and breaking the 'seismic sound barrier', becoming an ultra-fast earthquake.

Only a handful of such earthquakes have been recorded globally. The team believe that the first phase of the rupture was crucial in causing the second, rapidly slipping phase.

First author of the study Dr Stephen Hicks, from the Department of Earth Sciences and Engineering at Imperial, said: "Whilst scientists have found that such a reversing rupture mechanism is possible from theoretical models, our new study provides some of the clearest evidence for this enigmatic mechanism occurring in a real fault.

"Even though the fault structure seems simple, the way the earthquake grew was not, and this was completely opposite to how we expected the earthquake to look before we started to analyse the data."

However, the team say that if similar types of reversing or boomerang earthquakes can occur on land, a seismic rupture turning around mid-way through an earthquake could dramatically affect the amount of ground shaking caused.

Given the lack of observational evidence before now, this mechanism has been unaccounted for in earthquake scenario modelling and assessments of the hazards from such earthquakes. The detailed tracking of the boomerang earthquake could allow researchers to find similar patterns in other earthquakes and to add new scenarios into their modelling and improve earthquake impact forecasts.

The ocean bottom seismometer network used was part of the PI-LAB and EUROLAB projects, a million-dollar experiment funded by the Natural Environment Research Council in the UK, the European Research Council, and the National Science Foundation in the US.

PROVIDENCE, R.I. [Brown University] -- Critical access hospitals (CAHs) provide care to Americans living in remote rural areas. As important health care access points, these hospitals serve a population that is disproportionately older, impoverished and burdened by chronic disease. In 1997, with small rural hospitals under increasing financial strain and closing in large numbers, the federal CAH designation was established to increase their viability and to ensure that rural communities have adequate access to health care.

Prior research studies comparing the quality of care provided by CAHs and non-CAHs have found that risk-adjusted mortality rates at CAHs were higher, and the hospitals' quality of care, therefore, lower. But a new study led by investigators at the Center for Gerontology and Healthcare Research in Brown's School of Public Health suggests that standard risk-adjustment methodologies have been unfairly penalizing CAHs.

According to the study, for Medicare beneficiaries in rural areas who were hospitalized during the period of 2007 to 2017, CAHs submitted significantly fewer hospital diagnosis codes than did non-CAHs. The primary reason for the relative under-reporting of diagnoses at CAHs has to do with differences in Medicare reimbursements -- while non-CAHs are incentivized by Medicare to complete diagnosis coding, CAHs, which receive cost-based reimbursements, are not.

"When payments for episodes of care are tied to the acuity of patients, health care providers have the incentive to fully report or even overstate acuity," said study senior author Momotazur Rahman, an associate professor of health services, policy and practice at Brown. "Since payments for non-CAHs are dependent on reported acuity while payments for CAHs are not, non-CAH patients will appear comparatively sicker than they actually are."

Because mortality rates are adjusted per severity of illness -- acuity, in Rahman's words -- the result is that CAHs appear to have higher mortality rates for patients with similar conditions, when in reality their patients may in fact be sicker than those in non-CAHs, from the standpoint of risk adjustment.

The study was published in the Journal of the American Medical Association on Tuesday, Aug. 4.

How did the researchers determine that CAHs tend to overreport diagnoses? In 2010, Medicare increased the allowable number of billing codes for hospitalizations from 10 to 25.

"We observed a large jump in reported acuity among non-CAH patients in 2010," Rahman said, "but we saw a much smaller jump for CAH patients. We found that due to this difference in acuity reporting, when compared to non-CAHs, the risk-adjusted performance of CAHs on short-term mortality measures looks much worse than it actually is."

The CAH program, created to prevent rural hospitals from closing, has repeatedly come under threat. Given that in many parts of the U.S., CAHs serve as sole health care providers, Rahman said that examining differences in quality of care is important for understanding the value of the CAH program and informing decisions about the allocation of funding for rural health care.

The finding that short-term mortality outcomes at rural CAHs may not differ from those of non-CAHs after accounting for different coding practices, he added, is essential knowledge for ensuring timely access to acute care for vulnerable rural communities.

Personality varies widely. There are bold and reserved individuals, who behave very differently when faced with the same environmental stimulus. What is true for humans also applies to fish: their behavior shows a range of individual differences. By selectively breeding zebrafish, scientists from the Max Planck Institute of Neurobiology were able to show that distinct personality traits rapidly emerge and manifest not only in the behavior, but also through far-reaching changes in the brain.

Young zebrafish are just five millimeters long and almost transparent. Nevertheless, the tiny fish display a spectrum of behavior in response to external stimuli. While some animals flee in panic at a loud sound, other fish remain calm. If the sound is repeated, fish in one group learn to ignore it quickly, while others never really get used to it. Between these two extremes - relaxed or skittish - there is a whole range of behavioral expressions.

Carlos Pantoja and colleagues in Herwig Baier's team were now able to show that selection for a specific behavioral trait can also change the fishes' brain activity surprisingly quickly. The researchers mated animals only within the extremely relaxed and the extremely skittish groups. After just two generations, the brains of the fry selected for skittishness differed significantly from the brains of the calm offspring.

In the transparent fish larvae, the scientists were able to observe which brain regions were activated by the loud sound. The offspring of the two behavioral extremes showed clear differences in neuronal activity in a part of the hypothalamus and in the so-called dorsal raphe nucleus. A noticeable difference between these two brain regions is that the plastic part of the hypothalamus contains neurons that secrete dopamine, while the raphe nucleus mainly produces serotonin. Dopamine and serotonin are two prominent neuromodulators that have also been associated with personality differences and even psychiatric conditions in humans.

"The ratio of cell activity in these two brain regions could regulate the sensitivity of an individual fish's reaction to the sound and how quickly it gets used to it," explains Carlos Pantoja. "However, this is certainly only one component, as there are also differences in a whole range of other brain areas."

Interestingly, the offspring of the two fish groups not only showed the expected differences in their startle response. While in the larval stage, the more relaxed fish fry was also significantly less spontaneously active. As adults, these fish then adapted much slower to a new environment than adult jumpy fish. "At first glance, this sounds paradoxical. But it could be that the early tendency to fearful overreactions tends to dampen the later stress response," says Pantoja. Similar long-term effects of early stress processing have been reported in mammals.

In both groups of fish, the dopamine-releasing part of the hypothalamus was activated during the startle reaction. However, while this region was only switched on by the sound in the relaxed fish, it was permanently active in the skittish fish. After a mere two generations of behavioral selection, these animals already seemed to be constantly prepared to escape.

"The pace at which personality traits can be shifted and fixed in evolution is remarkable," reflects Herwig Baier. "The process might be similarly rapid in populations of Homo sapiens." The zebrafish could perhaps reveal some of the involved brain structures and the genetic basis of this plasticity.

AMHERST, Mass. - One of the new realities in biomedical research is that it's increasingly difficult to use a general approach to score advances. Now, investigations into disease mechanisms, for example, are often conducted at the molecular level by specialists who dedicate years to interrogating a single protein or signaling pathway.

One such scientist is biochemist Margaret Stratton at the University of Massachusetts Amherst, whose lab reports how they used advanced sequencing technology to clear up uncertainty and determine all variants of a single protein/enzyme known as calcium/calmodulin-dependent protein kinase II (CaMKII) in the hippocampus, the brain's memory center.

It plays a central role in calcium signaling throughout the body, Stratton explains. In the hippocampus, CaMKII is required for learning and memory, and when mutations occur they contribute to conditions such as autism spectrum disorders and developmental disabilities, or problems in other systems relating to cardiac pacing and fertility.

Stratton and first authors Roman Sloutsky and Noelle Dziedzic, with others, report in Science Signaling that they found an unexpected new role for the hub domain, or organizational center of the CaMKII molecular complex. Stratton says, "In addition to this known role, we show that this domain affects how sensitive CaMKII is to calcium; it acts like a tuner for sensitivity. This was a surprise. It opens a whole new area for investigation. We also show evidence for how we think it works at the molecular level."

Kinases are quite prevalent in biology, she adds, with more than 500 kinds in humans, but CaMKII is unique with its hub domain. Their unexpected discovery that "the hub actually plays a role in regulating activity gives us a unique handle on CaMKII to potentially control its activity with high specificity."

In vertebrates and humans, genomes encode for four CaMKII variants, and each is associated with many different proteins.

"We collaborated with Luke Chao, a structural biologist at Mass General Hospital, and a postdoc in his lab, Sivakumar Boopathy, to use cutting-edge techniques to structurally characterize the different flavors of CaMKII to understand how they may react differently to calcium." They hoped to identify any that have a modulatory or regulatory role and might serve as a new therapeutic target for controlling it or correcting mutations, she notes.

"All CaMKIIs consist of a catalytic kinase domain, a regulatory segment, a variable linker and a hub domain," Stratton explains. When called upon, this molecule adds phosphates where they are needed for cell function. "When calcium levels rise, CaMKII turns on. When they drop, CaMKII activity does too. Our goal was to unravel the differences to better understand how CaMKII does its job in memory formation."

In the CaMKII structure, the hub domain's job is to gather the other domains around it. A kidney bean-shaped kinase domain is attached to the hub by a spaghetti-like linker. When subunits are assembled into a working complex it looks like a flower, where the kinase domains are petals around the central hub domain, she points out.

In their sequencing experiments, Stratton explains, "We found something quite surprising. We discovered that there are more than 70 different CaMKII variants present in hippocampus. That's an extraordinary number."

Chao's group used cryo-electron microscopy to make images of purified CaMKII, allowing the researchers to see that CaMKII's "action" domain adopts different conformations relative to the hub, Stratton says, "In the 70 or so different variants, the petals are likely in a different orientation around the hub. It still looks like a flower, but all the petals are not exactly the same. This orientation we think is dependent on the hub identity, which is dictated by the sequence of the gene."

PITTSBURGH, Aug. 10, 2020 - In the first large, multicenter analysis of its kind, the 40-hospital UPMC health system today reported its findings on clinician-directed retesting of patients for presence of SARS-CoV-2, the virus that causes COVID-19, in the journal Infection Control & Hospital Epidemiology.

While retesting was uncommon, the UPMC analysis found that patients positive for COVID-19 stayed positive for an average of three weeks and repeating tests in patients who were initially negative very rarely led to a positive result.

"In the U.S., COVID-19 testing capacity is limited -- not everyone who wants a test can get one -- so we have to be judicious in how we use it," said co-author Graham Snyder, M.D., M.S., medical director of infection prevention and hospital epidemiology at UPMC. "Often, testing decisions are left to individual clinicians, which leads to questions about when and whom to retest for COVID-19, how often false positives or negatives might occur, and the duration of positivity. So, it is important that we understand the value of retesting and what information it can, and cannot, provide."

UPMC uses a nucleic acid polymerase chain reaction (PCR) test for SARS-CoV-2 and specimen collection is done with a nasopharyngeal swab by trained clinicians. The health system developed its COVID-19 test in early March 2020 in anticipation of the tremendous need for diagnostic capabilities.

Snyder and his colleagues worked with the Wolff Center at UPMC -- the health system's quality care and improvement center -- to review the results of more than 30,000 COVID-19 tests performed on adult patients who received care through one of UPMC's 40 academic, community and specialty hospitals, or 700 doctors' offices and outpatient sites in Pennsylvania, New York and Maryland. The tests were performed between March 3 and May 3, 2020. Of those tests, 485 were repeated at least once.

Among 74 patients who initially tested positive and were retested, about half were still positive and half were negative. The median time between an initial positive and a repeat positive was 18 days, whereas the median time from initial positive to a negative test was 23 days, suggesting that PCR tests may remain positive until some point in between, around 21 days. The most common reason for repeat testing on someone who initially tested positive was to determine if infection prevention protocols needed to be continued when the patient was discharged.

Among the 418 patients who initially tested negative and were retested, 96.4% were still negative on retesting. Pre-operative asymptomatic screening was the most common reason negative patients were retested, followed by clinical suspicion that the first test was a false negative. For the 15 patients who went from negative to positive, the median time between tests was eight days.

The researchers noted that the data was not collected as part of a formal study and testing was done at each clinician's discretion, so they were unable to calculate a true false negative rate.

"Although our analysis cannot provide definitive clinical guidance regarding retesting for COVID-19, it does point to several interesting areas for further research," said lead author Amy Kennedy, M.D., M.S., a clinical research fellow in Pitt's Department of Medicine at the time the analysis was performed. "These include identifying predictors of initial false negatives and providing a better estimate for how long someone who tests positive could transmit the virus to others."

SASKATOON - An international team led by the Plant Phenotyping and Imaging Research Centre (P2IRC) at the University of Saskatchewan (USask) and researchers at Agriculture and Agri-Food Canada (AAFC) has decoded the full genome for the black mustard plant--research that will advance breeding of oilseed mustard crops and provide a foundation for improved breeding of wheat, canola and lentils.

The team, co-led by P2IRC researchers Andrew Sharpe and Isobel Parkin, used a new genome sequencing technology (Nanopore) that results in very long "reads" of DNA and RNA sequences, providing information for crop breeding that was previously not available. The results are published today in Nature Plants.

"This work provides a new model for building other genome assemblies for crops such as wheat, canola and lentils. Essentially, it's a recipe for generating a genome sequence that works for any crop," said Sharpe, director of P2IRC.

"We now know that we can get the same quality of genomic data and level of information about genetic variation for these important national and international crops. This means we can make breeding more efficient because we can more easily select genes for specific desired traits."

Sharpe said his team is already using this software platform in the Omics and Precision Agriculture Lab (OPAL) at the USask Global Institute for Food Security (GIFS) to sequence larger and more complex crop genomes.

Black mustard (Brassica nigra), commonly used in seed form as a cooking spice, is grown on the Indian sub-continent and is closely related to mustard and canola crops grown in Canada. The research provides a clearer, "higher resolution" view of the plant's genes and gives researchers and breeders a more defined view of which genes are responsible for which traits.

The resulting gene assembly for black mustard also helps explain how the black mustard genome differs from those of its close crop relatives--such as cabbage, turnip and canola.

The team also uncovered the first direct evidence of functional centromeres, structures on chromosomes essential for plant fertility, and detected other previously hard to identify regions of the genome. This knowledge provides a foundation for improving crop production.

Parkin, a USask adjunct professor and P2IRC member, said the use of long-read sequence data has enabled unprecedented access to previously hidden features of plant genomes.

"This provides not only insights into how crops evolve but enables the identification of novel structural variation--now known to play an important role in the control of many key agronomic traits," said Parkin, also the lead research scientist with AAFC Saskatoon Research Centre.

They also found in the sequence multiple copies of certain genes that express specific traits. This could mean that certain traits, such as fungal resistance, could be expressed more strongly through several genes.

Other USask members of the team include GIFS researcher Zahra-Katy Navabi and bioinformatics specialist Chu Shin Koh. Other team members include Sampath Perumal, a post-doctoral fellow with Parkin, as well as others from the University of Ottawa, Thompson River University, the National Research Council, and researchers from the United Kingdom and China.

"The genome assembly for black mustard that we have developed is a great example of how new Nanopore sequencing technology quickly reveals important genome biology," Sharpe said, noting that this advanced sequencing technology and capability is available to public and private plant breeding organizations through the OPAL at GIFS.

A new study, revisiting fossil specimens from the enormous crocodylian, Deinosuchus, has confirmed that the beast had teeth “the size of bananas”, capable to take down even the very largest of dinosaurs.

And, it wasn’t alone!

TThe research, published in the Journal of Vertebrate Paleontology, also reveals various kinds of “terror crocodile”. Two species, entitled Deinosuchus hatcheri and Deinosuchus riograndensis lived in the west of America, ranging from Montana to northern Mexico. Another, Deinosuchus schwimmeri, lived along the Atlantic coastal plain from New Jersey to Mississippi. At the time, North America was cut in half by a shallow sea extending from the Arctic Ocean south to the present-day Gulf of Mexico.

Ranging in up to 33 feet in length Deinosuchus, though, has been known to be one of the largest, if not the largest, crocodylian genera ever in existence. It was the largest predator in its ecosystem, outweighing even the largest predatory dinosaurs living alongside them between 75 and 82 million years ago.

From previous studies of cranial remains and bite marks on dinosaur fossil bones, paleontologists have long speculated that the massive beasts preyed on dinosaurs.

Now this new study, led by Dr Adam Cossette sheds new light on the monstrous creature and has further confirmed that Deinosuchus most certainly had the head size and crushing jaw strength to do just that.

“Deinosuchus was a giant that must have terrorized dinosaurs that came to the water’s edge to drink,” says Dr Cossette, from the New York Institute of Technology College of Osteopathic Medicine at Arkansas State University. “Until now, the complete animal was unknown. These new specimens we’ve examined reveal a bizarre, monstrous predator with teeth the size of bananas.”

C. Deinosuchus seems to have been an opportunistic predator, and given that it was so enormous, almost everything in its habitat was on the menu.

There are multiple examples of bite marks made by D. riograndensis and a species newly described in this study, D. schwimmeri, on turtle shells and dinosaur bones.

In spite of the genus’s name, which means “terror crocodile,” they were actually more closely related to alligators. Based on its enormous skull, it looked like neither an alligator nor a crocodile. Its snout was long and broad, but inflated at the front around the nose in a way not seen in any other crocodylian, living or extinct. The reason for its enlarged nose is unknown.

“It was a strange animal,” says co-author Professor Christopher Brochu a palaeontologist, from the University of Iowa. “It shows that crocodylians are not ‘living fossils’ that haven’t changed since the age of dinosaurs. They’ve evolved just as dynamically as any other group.”

Deinosuchus disappeared before the main mass extinction at the end of the age of dinosaurs (Meozoic). The reason for its extinction remains unknown. From here, the authors call for more studies to further understand Deinosuchus.

“It had two large holes are present at the tip of the snout in front of the nose,” Dr Cossette says.

“These holes are unique to Deinosuchus and we do not know what they were for, further research down the line will hopefully help us unpick this mystery and we can learn further about this incredible creature.”

Analysis of meteorite content has been crucial in advancing our knowledge of the origin and evolution of our solar system. Some meteorites also contain grains of stardust. These grains predate the formation of our solar system and are now providing important insights into how the elements in the universe formed.

Working in collaboration with an international team, nuclear physicists at the U.S. Department of Energy’s (DOE’s) Argonne National Laboratory have made a key discovery related to the analysis of “presolar grains” found in some meteorites. This discovery has shed light on the nature of stellar explosions and the origin of chemical elements. It has also provided a new method for astronomical research.

“Tiny presolar grains, about one micron in size, are the residue from stellar explosions in the distant past, long before our solar system existed,” said Dariusz Seweryniak, experimental nuclear physicist in Argonne’s Physics division. The stellar debris from the explosions eventually became wedged into meteorites that crashed into the Earth.

“In turn, we were able to calculate the ratios of various sulfur isotopes produced in stellar explosions, which will allow astrophysicists to determine whether a particular presolar grain is of nova or supernova origin.” — Dariusz Seweryniak, experimental physicist in the Physics division

The major stellar explosions are of two types. One called a “nova” involves a binary star system, where a main star is orbiting a white dwarf star, an extremely dense star that can be the size of Earth but have the mass of our sun. Matter from the main star is continually being pulled away by the white dwarf because of its intense gravitational field. This deposited material initiates a thermonuclear explosion every 1,000 to 100,000 years, and the white dwarf ejects the equivalent of the mass of more than thirty Earths into interstellar space. In a “supernova,” a single collapsing star explodes and ejects most of its mass.

Nova and supernova are the sources of the most frequent and violent stellar eruptions in our Galaxy, and for that reason, they have been the subject of intense astronomical investigations for decades. Much has been learned from them, for example, about the origin of the heavier elements.

“A new way of studying these phenomena is analyzing the chemical and isotopic composition of the presolar grains in meteorites,” explained Seweryniak. “Of particular importance to our research is a specific nuclear reaction that occurs in nova and supernova — proton capture on an isotope of chlorine — which we can only indirectly study in the lab.”

In conducting their research, the team pioneered a new approach for astrophysics research. It entails use of the Gamma-Ray Energy Tracking In-beam Array (GRETINA) coupled to the Fragment Mass Analyzer at the Argonne Tandem Linac Accelerator System (ATLAS), a DOE Office of Science User Facility for nuclear physics. GRETINA is a state-of-the-art detection system able to trace the path of gamma rays emitted from nuclear reactions. It is one of only two such systems in the world.

Using GRETINA, the team completed the first detailed gamma-ray spectroscopy study of an astronomically important nucleus of an isotope, argon-34. From the data, they calculated the nuclear reaction rate involving proton capture on a chlorine isotope (chlorine-33).

“In turn, we were able to calculate the ratios of various sulfur isotopes produced in stellar explosions, which will allow astrophysicists to determine whether a particular presolar grain is of nova or supernova origin,” said Seweryniak. The team also applied their acquired data to gain deeper understanding of the synthesis of elements in stellar explosions.

The team is planning to continue their research with GRETINA as part of a worldwide effort to reach a comprehensive understanding of nucleosynthesis of the elements in stellar explosions.

All life is subject to evolution in the form of mutations that change the DNA sequence of an organism's offspring, after which natural selection allows the 'fittest' mutants to survive and pass on their genes to future generations. These mutations can generate new abilities in a species, but another common driving force for evolution is horizontal gene transfer (HGT) - the acquisition of DNA from a creature other than a parent, and even of a different species. For example, a significant amount of the human genome is actually viral DNA. Genetic engineering techniques now allow humans to intentionally induce HGT in various species to create 'designer organisms' capable of things like renewable chemical production, but it's often difficult to get foreign DNA working in a new host.

Bioengineers at the University of California San Diego used genetic engineering and laboratory evolution to test the functionality of DNA placed into a new species and study how it can mutate to become functional if given sufficient evolutionary time. They published their results on August 10 in Nature Ecology and Evolution.

Using the model bacterium Escherichia coli as a host, bioengineers in Professor Bernhard Palsson's Systems Biology Research Group used CRISPR to generate gene-swapped strains with donor DNA from species across the tree of life -- from close bacterial relatives, to a microbe that lives in boiling hotsprings, to humans. The genes pgi or tpiA were replaced, two enzymes involved in sugar metabolism that cripple E. coli when removed, causing them to grow about 5 times slower. They then used an 'evolution machine,' robotic systems to study how the engineered bacteria adapted to replacement of such important genes with foreign versions. The automated systems enabled a large-scale study, generating hundreds of mutant strains evolved for more than 50,000 cumulative generations, something that would take decades rather than months if performed manually. Moreover, culture growth rates could be tracked in real-time as the populations evolved, allowing mutant strains to be isolated immediately after they took over the population from the ancestral strain. This high temporal resolution regularly allowed strains to be isolated that differed across their entire genome by only single mutations of interest, revealing not only order of acquisition but also providing an easy way to test the effect of mutations without laborious rounds of additional genetic engineering of the ancestral strains.

Although at first E. coli couldn't use most of the foreign genes it was given, they quickly and frequently found an evolutionary way around this, often in a matter of days recovering from their crippled state to grow just as fast as before they were engineered. Notably, the foreign genes were not codon optimized before insertion into E. coli - this is regularly performed during synthetic HGT, relying on the fact that DNA codes for the string of amino acids that composes a protein via 3 letter codons that contain redundancy (e.g., Lysine is coded for by AAA or AAG). Different species have different genome-wide trends in codon usage that codon optimization minimizes for a gene inserted into a foreign species, but this was unnecessary to enable functionality - even for human DNA which has been evolutionarily diverging from E. coli for billions of years.

For every strain that successfully evolved use of the foreign DNA the critical factor was one or more mutations increasing gene expression level. Most of these mutations did not even occur within the foreign gene but rather in regions of E. coli's DNA controlling regulation of the gene, with their nature depending sensitively on the gene's specific DNA sequence and location in the chromosome. Some of these mutations occurred with shocking regularity, including one observed independently more than 20 times, demonstrating that evolutionary outcomes can be (probabilistically) predicted to the single DNA basepair.

Of the few mutations occurring within the foreign DNA, most were at the beginning of the gene and 'silent' in nature, changing the codon but not the resulting amino acid. These are often assumed to have negligible impact on cell fitness (at least when in a single codon rather than across the entire gene as in codon optimization), but we found them to have significant impact. Thermodynamic modeling revealed that these mutations serve to prevent binding of the gene's mRNA transcript into knotted structures, which limits the amount of protein that ribosomes can produce from the transcript. Finally, our hundreds of evolved strains contained >90 distinct mutations in the RNA Polymerase complex that produces mRNA transcripts from the DNA sequence. Such mutations are common in laboratory evolution experiments, but our large dataset revealed clustering of mutations into distinct regions depending on how the strain containing it evolved. This points to evolutionarily conserved regulatory strategies for rapidly adapting to metabolic perturbations such as the ones we induced.

"This result shows the importance of systems biology," said UC San Diego bioengineering professor Bernhard Palsson, the principal investigator of the study. "Namely, biological function, in this case, is not so much about the parts of the cell, but how the parts come together to function as a system."

Overall, this study establishes the influence of various DNA and protein features on cross-species genetic interchangeability and evolutionary outcomes, with implications for both natural HGT and strain design via genetic engineering.