Showing papers by "San Diego State University published in 2018"
Gregory A. Roth1, Gregory A. Roth2, Degu Abate3, Kalkidan Hassen Abate4 +1025 more•Institutions (333)
TL;DR: Non-communicable diseases comprised the greatest fraction of deaths, contributing to 73·4% (95% uncertainty interval [UI] 72·5–74·1) of total deaths in 2017, while communicable, maternal, neonatal, and nutritional causes accounted for 18·6% (17·9–19·6), and injuries 8·0% (7·7–8·2).
5,211 citations
Jeffrey D. Stanaway1, Ashkan Afshin1, Emmanuela Gakidou1, Stephen S Lim1 +1050 more•Institutions (346)
TL;DR: This study estimated levels and trends in exposure, attributable deaths, and attributable disability-adjusted life-years (DALYs) by age group, sex, year, and location for 84 behavioural, environmental and occupational, and metabolic risks or groups of risks from 1990 to 2017 and explored the relationship between development and risk exposure.
2,910 citations
Institute for Health Metrics and Evaluation1, University of Louisville2, Karolinska Institutet3, Kermanshah University of Medical Sciences4, Centre for Mental Health5, University of Queensland6, Tehran University of Medical Sciences7, University of KwaZulu-Natal8, South African Medical Research Council9, University of Colorado Boulder10, University of California, Irvine11, Fred Hutchinson Cancer Research Center12, Montefiore Medical Center13, Northeastern University14, University of Alabama at Birmingham15, Brown University16, San Diego State University17, University of Melbourne18, Albert Einstein College of Medicine19, Cambridge Health Alliance20, University of Pittsburgh21, Johns Hopkins University22, University of Cape Town23, Case Western Reserve University24, Marshall University25, University of London26, University of Illinois at Urbana–Champaign27, National Drug and Alcohol Research Centre28, Harvard University29, University of California, San Diego30, Yale University31, Veterans Health Administration32, Georgetown University33, Jackson State University34, University of Massachusetts Boston35, State University of New York System36, Simmons College37, Charles R. Drew University of Medicine and Science38, University of California, Los Angeles39, University of Oxford40, Norwegian Institute of Public Health41, Pacific Institute42, Curtin University43, Heidelberg University44, Jimma University45, Northwestern University46, Washington University in St. Louis47, Howard University48, University of New Mexico49, University at Buffalo50, University of Washington51, University of South Florida52, Tufts University53, University of Rochester Medical Center54, Kosin University55, Central South University56, Michigan State University57, Ball State University58, Nova Southeastern University59, Dalhousie University60, Mayo Clinic61, University of British Columbia62, Ohio State University63, Baylor University64, Jagiellonian University Medical College65, Wrocław Medical University66, Dartmouth College67, University of Western Ontario68, Oregon Health & Science University69, Virginia Commonwealth University70, Columbia University71, University of Canberra72, Aga Khan University73
TL;DR: There are wide differences in the burden of disease at the state level and specific diseases and risk factors, such as drug use disorders, high BMI, poor diet, high fasting plasma glucose level, and alcohol use disorders are increasing and warrant increased attention.
Abstract: Introduction Several studies have measured health outcomes in the United States, but none have provided a comprehensive assessment of patterns of health by state. Objective To use the results of the Global Burden of Disease Study (GBD) to report trends in the burden of diseases, injuries, and risk factors at the state level from 1990 to 2016. Design and Setting A systematic analysis of published studies and available data sources estimates the burden of disease by age, sex, geography, and year. Main Outcomes and Measures Prevalence, incidence, mortality, life expectancy, healthy life expectancy (HALE), years of life lost (YLLs) due to premature mortality, years lived with disability (YLDs), and disability-adjusted life-years (DALYs) for 333 causes and 84 risk factors with 95% uncertainty intervals (UIs) were computed. Results Between 1990 and 2016, overall death rates in the United States declined from 745.2 (95% UI, 740.6 to 749.8) per 100 000 persons to 578.0 (95% UI, 569.4 to 587.1) per 100 000 persons. The probability of death among adults aged 20 to 55 years declined in 31 states and Washington, DC from 1990 to 2016. In 2016, Hawaii had the highest life expectancy at birth (81.3 years) and Mississippi had the lowest (74.7 years), a 6.6-year difference. Minnesota had the highest HALE at birth (70.3 years), and West Virginia had the lowest (63.8 years), a 6.5-year difference. The leading causes of DALYs in the United States for 1990 and 2016 were ischemic heart disease and lung cancer, while the third leading cause in 1990 was low back pain, and the third leading cause in 2016 was chronic obstructive pulmonary disease. Opioid use disorders moved from the 11th leading cause of DALYs in 1990 to the 7th leading cause in 2016, representing a 74.5% (95% UI, 42.8% to 93.9%) change. In 2016, each of the following 6 risks individually accounted for more than 5% of risk-attributable DALYs: tobacco consumption, high body mass index (BMI), poor diet, alcohol and drug use, high fasting plasma glucose, and high blood pressure. Across all US states, the top risk factors in terms of attributable DALYs were due to 1 of the 3 following causes: tobacco consumption (32 states), high BMI (10 states), or alcohol and drug use (8 states). Conclusions and Relevance There are wide differences in the burden of disease at the state level. Specific diseases and risk factors, such as drug use disorders, high BMI, poor diet, high fasting plasma glucose level, and alcohol use disorders are increasing and warrant increased attention. These data can be used to inform national health priorities for research, clinical care, and policy.
962 citations
Northern Arizona University1, University of Minnesota2, University of California, Davis3, Woods Hole Oceanographic Institution4, Massachusetts Institute of Technology5, University of Copenhagen6, University of Trento7, Chinese Academy of Sciences8, University of California, San Francisco9, Children's Hospital of Philadelphia10, Pacific Northwest National Laboratory11, North Carolina State University12, University of Montana13, Dalhousie University14, University of British Columbia15, Shedd Aquarium16, University of Colorado Denver17, University of California, San Diego18, Michigan State University19, Stanford University20, Broad Institute21, Harvard University22, Australian National University23, University of Düsseldorf24, Sookmyung Women's University25, San Diego State University26, Howard Hughes Medical Institute27, Max Planck Society28, Cornell University29, University of Washington30, Colorado State University31, Google32, Syracuse University33, Webster University34, United States Department of Agriculture35, University of Arkansas for Medical Sciences36, Colorado School of Mines37, Atlantic Oceanographic and Meteorological Laboratory38, University of Southern Mississippi39, University of California, Merced40, Wageningen University and Research Centre41, University of Arizona42, Environment Agency43, University of Florida44, Merck & Co.45
TL;DR: QIIME 2 provides new features that will drive the next generation of microbiome research, including interactive spatial and temporal analysis and visualization tools, support for metabolomics and shotgun metagenomics analysis, and automated data provenance tracking to ensure reproducible, transparent microbiome data science.
Abstract: We present QIIME 2, an open-source microbiome data science platform accessible to users spanning the microbiome research ecosystem, from scientists and engineers to clinicians and policy makers. QIIME 2 provides new features that will drive the next generation of microbiome research. These include interactive spatial and temporal analysis and visualization tools, support for metabolomics and shotgun metagenomics analysis, and automated data provenance tracking to ensure reproducible, transparent microbiome data science.
875 citations
TL;DR: In two nationally representative surveys of U.S. adolescents in grades 8 through 12 (N = 506,820) and national statistics on suicide deaths for those ages 13 to 18, adolescents’ depressive symptoms, suicide-related outcomes, and suicide rates increased between 2010 and 2015, especially among females as discussed by the authors.
Abstract: In two nationally representative surveys of U.S. adolescents in grades 8 through 12 (N = 506,820) and national statistics on suicide deaths for those ages 13 to 18, adolescents’ depressive symptoms, suicide-related outcomes, and suicide rates increased between 2010 and 2015, especially among females. Adolescents who spent more time on new media (including social media and electronic devices such as smartphones) were more likely to report mental health issues, and adolescents who spent more time on nonscreen activities (in-person social interaction, sports/exercise, homework, print media, and attending religious services) were less likely. Since 2010, iGen adolescents have spent more time on new media screen activities and less time on nonscreen activities, which may account for the increases in depression and suicide. In contrast, cyclical economic factors such as unemployment and the Dow Jones Index were not linked to depressive symptoms or suicide rates when matched by year.
819 citations
TL;DR: A method for transplanting human brain organoids into the adult mouse brain is established and progressive neuronal differentiation and maturation, gliogenesis, integration of microglia, and growth of axons to multiple regions of the host brain are shown.
Abstract: Differentiation of human pluripotent stem cells to small brain-like structures known as brain organoids offers an unprecedented opportunity to model human brain development and disease. To provide a vascularized and functional in vivo model of brain organoids, we established a method for transplanting human brain organoids into the adult mouse brain. Organoid grafts showed progressive neuronal differentiation and maturation, gliogenesis, integration of microglia, and growth of axons to multiple regions of the host brain. In vivo two-photon imaging demonstrated functional neuronal networks and blood vessels in the grafts. Finally, in vivo extracellular recording combined with optogenetics revealed intragraft neuronal activity and suggested graft-to-host functional synaptic connectivity. This combination of human neural organoids and an in vivo physiological environment in the animal brain may facilitate disease modeling under physiological conditions.
755 citations
University of California, San Diego1, University of Montana2, San Diego State University3, North Carolina State University4, University of Oregon5, University of Queensland6, Harvard University7, Broad Institute8, King's College London9, University of Minnesota10, University of California, San Francisco11, Saint Petersburg State University12, Colorado State University13, Carnegie Mellon University14, University of Nantes15, University of Pittsburgh16, University of Colorado Boulder17, Argonne National Laboratory18, Atlantic Oceanographic and Meteorological Laboratory19, University of Southern Mississippi20, Duke University21
TL;DR: The utility of the living data resource and cross-cohort comparison is demonstrated to confirm existing associations between the microbiome and psychiatric illness and to reveal the extent of microbiome change within one individual during surgery, providing a paradigm for open microbiome research and education.
Abstract: Although much work has linked the human microbiome to specific phenotypes and lifestyle variables, data from different projects have been challenging to integrate and the extent of microbial and molecular diversity in human stool remains unknown. Using standardized protocols from the Earth Microbiome Project and sample contributions from over 10,000 citizen-scientists, together with an open research network, we compare human microbiome specimens primarily from the United States, United Kingdom, and Australia to one another and to environmental samples. Our results show an unexpected range of beta-diversity in human stool microbiomes compared to environmental samples; demonstrate the utility of procedures for removing the effects of overgrowth during room-temperature shipping for revealing phenotype correlations; uncover new molecules and kinds of molecular communities in the human stool metabolome; and examine emergent associations among the microbiome, metabolome, and the diversity of plants that are consumed (rather than relying on reductive categorical variables such as veganism, which have little or no explanatory power). We also demonstrate the utility of the living data resource and cross-cohort comparison to confirm existing associations between the microbiome and psychiatric illness and to reveal the extent of microbiome change within one individual during surgery, providing a paradigm for open microbiome research and education. IMPORTANCE We show that a citizen science, self-selected cohort shipping samples through the mail at room temperature recaptures many known microbiome results from clinically collected cohorts and reveals new ones. Of particular interest is integrating n = 1 study data with the population data, showing that the extent of microbiome change after events such as surgery can exceed differences between distinct environmental biomes, and the effect of diverse plants in the diet, which we confirm with untargeted metabolomics on hundreds of samples.
538 citations
TL;DR: Titration gas chromatography is developed as an analytical method of distinguishing between lithium metal and lithium compounds within a cycled battery and assessing the amount of unreacted metallic Li0, the dominant source of inactive lithium and capacity loss.
Abstract: Inactive lithium (Li) formation is the immediate cause of capacity loss and catastrophic failure of Li metal batteries. However, the chemical component and the atomic level structure of inactive Li have rarely been studied due to the lack of effective diagnosis tools to accurately differentiate and quantify Li+ in solid electrolyte interphase (SEI) components and the electrically isolated unreacted metallic Li0, which together comprise the inactive Li. Here, by introducing a new analytical method, Titration Gas Chromatography (TGC), we can accurately quantify the contribution from metallic Li0 to the total amount of inactive Li. We uncover that the Li0, rather than the electrochemically formed SEI, dominates the inactive Li and capacity loss. Using cryogenic electron microscopies to further study the microstructure and nanostructure of inactive Li, we find that the Li0 is surrounded by insulating SEI, losing the electronic conductive pathway to the bulk electrode. Coupling the measurements of the Li0 global content to observations of its local atomic structure, we reveal the formation mechanism of inactive Li in different types of electrolytes, and identify the true underlying cause of low Coulombic efficiency in Li metal deposition and stripping. We ultimately propose strategies to enable the highly efficient Li deposition and stripping to enable Li metal anode for next generation high energy batteries.
500 citations
Richard A. Klein1, Michelangelo Vianello2, Fred Hasselman3, Byron G. Adams4 +187 more•Institutions (118)
TL;DR: This paper conducted preregistered replications of 28 classic and contemporary published findings, with protocols that were peer reviewed in advance, to examine variation in effect magnitudes across samples and settings, and found that very little heterogeneity was attributable to the order in which the tasks were performed or whether the task were administered in lab versus online.
Abstract: We conducted preregistered replications of 28 classic and contemporary published findings, with protocols that were peer reviewed in advance, to examine variation in effect magnitudes across samples and settings. Each protocol was administered to approximately half of 125 samples that comprised 15,305 participants from 36 countries and territories. Using the conventional criterion of statistical significance (p < .05), we found that 15 (54%) of the replications provided evidence of a statistically significant effect in the same direction as the original finding. With a strict significance criterion (p < .0001), 14 (50%) of the replications still provided such evidence, a reflection of the extremely high-powered design. Seven (25%) of the replications yielded effect sizes larger than the original ones, and 21 (75%) yielded effect sizes smaller than the original ones. The median comparable Cohen’s ds were 0.60 for the original findings and 0.15 for the replications. The effect sizes were small (< 0.20) in 16 of the replications (57%), and 9 effects (32%) were in the direction opposite the direction of the original effect. Across settings, the Q statistic indicated significant heterogeneity in 11 (39%) of the replication effects, and most of those were among the findings with the largest overall effect sizes; only 1 effect that was near zero in the aggregate showed significant heterogeneity according to this measure. Only 1 effect had a tau value greater than .20, an indication of moderate heterogeneity. Eight others had tau values near or slightly above .10, an indication of slight heterogeneity. Moderation tests indicated that very little heterogeneity was attributable to the order in which the tasks were performed or whether the tasks were administered in lab versus online. Exploratory comparisons revealed little heterogeneity between Western, educated, industrialized, rich, and democratic (WEIRD) cultures and less WEIRD cultures (i.e., cultures with relatively high and low WEIRDness scores, respectively). Cumulatively, variability in the observed effect sizes was attributable more to the effect being studied than to the sample or setting in which it was studied.
495 citations
University of North Carolina at Chapel Hill1, University of New Mexico2, Boston Children's Hospital3, University of California, San Diego4, Stanford University5, State University of New York System6, University of Washington7, University of Nebraska Medical Center8, Wake Forest University9, Emory University10, National Institutes of Health11, San Diego State University12, VA Boston Healthcare System13, Harvard University14, Boston University15, University of South Dakota16, University of Arizona17
TL;DR: Estimated prevalence of fetal alcohol spectrum disorders among first-graders in 4 US communities ranged from 1.1% to 5.0% using a conservative approach, which may represent more accurate US prevalence estimates than previous studies but may not be generalizable to all communities.
Abstract: Importance Fetal alcohol spectrum disorders are costly, life-long disabilities. Older data suggested the prevalence of the disorder in the United States was 10 per 1000 children; however, there are few current estimates based on larger, diverse US population samples. Objective To estimate the prevalence of fetal alcohol spectrum disorders, including fetal alcohol syndrome, partial fetal alcohol syndrome, and alcohol-related neurodevelopmental disorder, in 4 regions of the United States. Design, Setting, and Participants Active case ascertainment methods using a cross-sectional design were used to assess children for fetal alcohol spectrum disorders between 2010 and 2016. Children were systematically assessed in the 4 domains that contribute to the fetal alcohol spectrum disorder continuum: dysmorphic features, physical growth, neurobehavioral development, and prenatal alcohol exposure. The settings were 4 communities in the Rocky Mountain, Midwestern, Southeastern, and Pacific Southwestern regions of the United States. First-grade children and their parents or guardians were enrolled. Exposures Alcohol consumption during pregnancy. Main Outcomes and Measures Prevalence of fetal alcohol spectrum disorders in the 4 communities was the main outcome. Conservative estimates for the prevalence of the disorder and 95% CIs were calculated using the eligible first-grade population as the denominator. Weighted prevalences and 95% CIs were also estimated, accounting for the sampling schemes and using data restricted to children who received a full evaluation. Results A total of 6639 children were selected for participation from a population of 13 146 first-graders (boys, 51.9%; mean age, 6.7 years [SD, 0.41] and white maternal race, 79.3%). A total of 222 cases of fetal alcohol spectrum disorders were identified. The conservative prevalence estimates for fetal alcohol spectrum disorders ranged from 11.3 (95% CI, 7.8-15.8) to 50.0 (95% CI, 39.9-61.7) per 1000 children. The weighted prevalence estimates for fetal alcohol spectrum disorders ranged from 31.1 (95% CI, 16.1-54.0) to 98.5 (95% CI, 57.5-139.5) per 1000 children. Conclusions and Relevance Estimated prevalence of fetal alcohol spectrum disorders among first-graders in 4 US communities ranged from 1.1% to 5.0% using a conservative approach. These findings may represent more accurate US prevalence estimates than previous studies but may not be generalizable to all communities.
487 citations
Space Telescope Science Institute1, Search for extraterrestrial intelligence2, Ames Research Center3, California Institute of Technology4, Massachusetts Institute of Technology5, Bishop's University6, Harvard University7, Space Science Institute8, University of Texas at Austin9, Villanova University10, Princeton University11, Goddard Space Flight Center12, Aarhus University13, University of Birmingham14, Principia College15, Lowell Observatory16, University of California, Berkeley17, Brigham Young University18, University of Nevada, Las Vegas19, San Diego State University20, Pennsylvania State University21
TL;DR: The Robovetter and the metrics it uses to decide which TCEs are called planet candidates in the DR25 KOI catalog are discussed and a value called the disposition score is discussed which provides an easy way to select a more reliable, albeit less complete, sample of candidates.
Abstract: We present the Kepler Object of Interest (KOI) catalog of transiting exoplanets based on searching 4 yr of Kepler time series photometry (Data Release 25, Q1–Q17). The catalog contains 8054 KOIs, of which 4034 are planet candidates with periods between 0.25 and 632 days. Of these candidates, 219 are new, including two in multiplanet systems (KOI-82.06 and KOI-2926.05) and 10 high-reliability, terrestrial-size, habitable zone candidates. This catalog was created using a tool called the Robovetter, which automatically vets the DR25 threshold crossing events (TCEs). The Robovetter also vetted simulated data sets and measured how well it was able to separate TCEs caused by noise from those caused by low signal-to-noise transits. We discuss the Robovetter and the metrics it uses to sort TCEs. For orbital periods less than 100 days the Robovetter completeness (the fraction of simulated transits that are determined to be planet candidates) across all observed stars is greater than 85%. For the same period range, the catalog reliability (the fraction of candidates that are not due to instrumental or stellar noise) is greater than 98%. However, for low signal-to-noise candidates between 200 and 500 days around FGK-dwarf stars, the Robovetter is 76.7% complete and the catalog is 50.5% reliable. The KOI catalog, the transit fits, and all of the simulated data used to characterize this catalog are available at the NASA Exoplanet Archive.
TL;DR: High users of screens among 14- to 17-year-olds were more than twice as likely to ever have been diagnosed with depression, diagnosed with anxiety, treated by a mental health professional, or taken medication for a psychological or behavioral issue in the last 12 months.
Abstract: Previous research on associations between screen time and psychological well-being among children and adolescents has been conflicting, leading some researchers to question the limits on screen time suggested by physician organizations. We examined a large (n = 40,337) national random sample of 2- to 17-year-old children and adolescents in the U.S. in 2016 that included comprehensive measures of screen time (including cell phones, computers, electronic devices, electronic games, and TV) and an array of psychological well-being measures. After 1 h/day of use, more hours of daily screen time were associated with lower psychological well-being, including less curiosity, lower self-control, more distractibility, more difficulty making friends, less emotional stability, being more difficult to care for, and inability to finish tasks. Among 14- to 17-year-olds, high users of screens (7+ h/day vs. low users of 1 h/day) were more than twice as likely to ever have been diagnosed with depression (RR 2.39, 95% CI 1.54, 3.70), ever diagnosed with anxiety (RR 2.26, CI 1.59, 3.22), treated by a mental health professional (RR 2.22, CI 1.62, 3.03) or have taken medication for a psychological or behavioral issue (RR 2.99, CI 1.94, 4.62) in the last 12 months. Moderate use of screens (4 h/day) was also associated with lower psychological well-being. Non-users and low users of screens generally did not differ in well-being. Associations between screen time and lower psychological well-being were larger among adolescents than younger children.
Proceedings Article•
27 Apr 2018
TL;DR: This paper proposes a pose grammar to tackle the problem of 3D human pose estimation, which takes 2D pose as input and learns a generalized 2D-3D mapping function and enforces high-level constraints over human poses.
Abstract: In this paper, we propose a pose grammar to tackle the problem of 3D human pose estimation. Our model directly takes 2D pose as input and learns a generalized 2D-3D mapping function. The proposed model consists of a base network which efficiently captures pose-aligned features and a hierarchy of Bi-directional RNNs (BRNN) on the top to explicitly incorporate a set of knowledge regarding human body configuration (i.e., kinematics, symmetry, motor coordination). The proposed model thus enforces high-level constraints over human poses. In learning, we develop a pose sample simulator to augment training samples in virtual camera views, which further improves our model generalizability. We validate our method on public 3D human pose benchmarks and propose a new evaluation protocol working on cross-view setting to verify the generalization capability of different methods. We empirically observe that most state-of-the-art methods encounter difficulty under such setting while our method can well handle such challenges.
TL;DR: Surveys of United States 8th, 10th, and 12th graders 1991–2016 suggest that the Great Recession was not the cause of the decrease in psychological well-being, which may instead be at least partially due to the rapid adoption of smartphones and the subsequent shift in adolescents’ time use.
Abstract: In nationally representative yearly surveys of United States 8th, 10th, and 12th graders 1991-2016 (N = 1.1 million), psychological well-being (measured by self-esteem, life satisfaction, and happiness) suddenly decreased after 2012. Adolescents who spent more time on electronic communication and screens (e.g., social media, the Internet, texting, gaming) and less time on nonscreen activities (e.g., in-person social interaction, sports/exercise, homework, attending religious services) had lower psychological well-being. Adolescents spending a small amount of time on electronic communication were the happiest. Psychological well-being was lower in years when adolescents spent more time on screens and higher in years when they spent more time on nonscreen activities, with changes in activities generally preceding declines in well-being. Cyclical economic indicators such as unemployment were not significantly correlated with well-being, suggesting that the Great Recession was not the cause of the decrease in psychological well-being, which may instead be at least partially due to the rapid adoption of smartphones and the subsequent shift in adolescents' time use. (PsycINFO Database Record
TL;DR: A global attainment analysis of the feasibility of attaining SDG targets on the basis of past trends and a estimates of health-related SDG index values in countries assessed at the subnational level varied substantially, particularly in China and India, although scores in Japan and the UK were more homogeneous.
TL;DR: A holistic review with multiple hypotheses might facilitate to devise better PCOS management approaches.
TL;DR: A new multispecies and dynamic approach that uses daily satellite data to track ocean features and aligns scales of management, species movement, and fisheries is introduced, finding that dynamic closures could be 2 to 10 times smaller than existing static closures while still providing adequate protection of endangered nontarget species.
Abstract: Seafood is an essential source of protein for more than 3 billion people worldwide, yet bycatch of threatened species in capture fisheries remains a major impediment to fisheries sustainability. Management measures designed to reduce bycatch often result in significant economic losses and even fisheries closures. Static spatial management approaches can also be rendered ineffective by environmental variability and climate change, as productive habitats shift and introduce new interactions between human activities and protected species. We introduce a new multispecies and dynamic approach that uses daily satellite data to track ocean features and aligns scales of management, species movement, and fisheries. To accomplish this, we create species distribution models for one target species and three bycatch-sensitive species using both satellite telemetry and fisheries observer data. We then integrate species-specific probabilities of occurrence into a single predictive surface, weighing the contribution of each species by management concern. We find that dynamic closures could be 2 to 10 times smaller than existing static closures while still providing adequate protection of endangered nontarget species. Our results highlight the opportunity to implement near real-time management strategies that would both support economically viable fisheries and meet mandated conservation objectives in the face of changing ocean conditions. With recent advances in eco-informatics, dynamic management provides a new climate-ready approach to support sustainable fisheries.
TL;DR: A comprehensive search of genomic and metagenomic databases with sensitive methods for protein sequence analysis identifies an expansive, diverse group of bacteriophages related to crAssphage and predicts the functions of the majority of phage proteins, in particular those that comprise the structural, replication and expression modules.
Abstract: Metagenomic sequence analysis is rapidly becoming the primary source of virus discovery
1–3
. A substantial majority of the currently available virus genomes come from metagenomics, and some of these represent extremely abundant viruses, even if never grown in the laboratory. A particularly striking case of a virus discovered via metagenomics is crAssphage, which is by far the most abundant human-associated virus known, comprising up to 90% of sequences in the gut virome
4
. Over 80% of the predicted proteins encoded in the approximately 100 kilobase crAssphage genome showed no significant similarity to available protein sequences, precluding classification of this virus and hampering further study. Here we combine a comprehensive search of genomic and metagenomic databases with sensitive methods for protein sequence analysis to identify an expansive, diverse group of bacteriophages related to crAssphage and predict the functions of the majority of phage proteins, in particular those that comprise the structural, replication and expression modules. Most, if not all, of the crAss-like phages appear to be associated with diverse bacteria from the phylum Bacteroidetes, which includes some of the most abundant bacteria in the human gut microbiome and that are also common in various other habitats. These findings provide for experimental characterization of the most abundant but poorly understood members of the human-associated virome.
TL;DR: In this paper, the authors provide a review of the PDDR studies and provide detailed evaluations on advantages and disadvantages of each PDDR and discuss the concerns and future research challenges on PDDR.
Abstract: Smart grid enables the two-way communication between the suppliers and consumers. Price-driven demand response (PDDR) is one of the important demand response categories that uses price of the energy as control signals to affect consumers’ electricity consumption. The current PDDR programs include critical peak pricing (CPP), time-of-use (TOU) pricing, and real-time pricing. In this paper, we provide a review of the PDDR studies. Detailed evaluations on advantages and disadvantages of each PDDR are provided. Concerns and future research challenges on PDDR are also addressed. It is believed that with the installation of smart meter infrastructures at residential households, price signal can be an efficient market tool for peak demand shaving, risk and reliability management, carbon emission reduction, and energy cost reduction.
TL;DR: In this survey paper, a systematic categorization method for the hybrid UAV's platform designs is introduced, first presenting the technical features and representative examples, and next explaining the flight dynamics model and flight control strategies.
TL;DR: An in-depth procedure is provided showing how to effectively navigate and use the systems biology workflow within XCMS Online without a priori knowledge of the platform, including uploading liquid chromatography–mass spectrometry data from metabolite-extracted biological samples and performing predictive metabolic pathway analysis.
Abstract: Systems biology is the study of complex living organisms, and as such, analysis on a systems-wide scale involves the collection of information-dense data sets that are representative of an entire phenotype. To uncover dynamic biological mechanisms, bioinformatics tools have become essential to facilitating data interpretation in large-scale analyses. Global metabolomics is one such method for performing systems biology, as metabolites represent the downstream functional products of ongoing biological processes. We have developed XCMS Online, a platform that enables online metabolomics data processing and interpretation. A systems biology workflow recently implemented within XCMS Online enables rapid metabolic pathway mapping using raw metabolomics data for investigating dysregulated metabolic processes. In addition, this platform supports integration of multi-omic (such as genomic and proteomic) data to garner further systems-wide mechanistic insight. Here, we provide an in-depth procedure showing how to effectively navigate and use the systems biology workflow within XCMS Online without a priori knowledge of the platform, including uploading liquid chromatography (LC)-mass spectrometry (MS) data from metabolite-extracted biological samples, defining the job parameters to identify features, correcting for retention time deviations, conducting statistical analysis of features between sample classes and performing predictive metabolic pathway analysis. Additional multi-omics data can be uploaded and overlaid with previously identified pathways to enhance systems-wide analysis of the observed dysregulations. We also describe unique visualization tools to assist in elucidation of statistically significant dysregulated metabolic pathways. Parameter input takes 5-10 min, depending on user experience; data processing typically takes 1-3 h, and data analysis takes ∼30 min.
TL;DR: Examples of atropisomerism in drug discovery as well as challenges and opportunities moving forward are discussed.
Abstract: Atropisomerism is a dynamic type of axial chirality that is ubiquitous in medicinal chemistry There are several examples of stable atropisomeric US FDA-approved drugs and experimental compounds, and in each case the atropisomers of these compounds possess drastically different biological activities Rapidly interconverting atropisomerism is even more prevalent, and while such compounds are typically considered achiral, they bind their protein targets in an atroposelective fashion, with the nonrelevant atropisomer contributing little to the desired activities It has been recently demonstrated that various properties of an interconverting atropisomer can be modulated through the synthesis of atropisomer stable and pure analogs Herein we discuss examples of atropisomerism in drug discovery as well as challenges and opportunities moving forward
TL;DR: The results suggest that hyperandrogenism may play a critical role in altering the gut microbiome in women with PCOS, which is an increased risk of developing type 2 diabetes and heart disease.
Abstract: Context A majority of women with polycystic ovary syndrome (PCOS) have metabolic abnormalities that result in an increased risk of developing type 2 diabetes and heart disease. Correlative studies have shown an association between changes in the gut microbiome and metabolic disorders. Two recent studies reported a decrease in α diversity of the gut microbiome in women with PCOS compared with healthy women. Objective We investigated whether changes in the gut microbiome correlated with specific clinical parameters in women with PCOS compared with healthy women. We also investigated whether there were changes in the gut microbiome in women with polycystic ovarian morphology (PCOM) who lacked the other diagnostic criteria of PCOS. Participants Subjects were recruited at the Poznan University of Medical Sciences. Fecal microbial diversity profiles of healthy women (n = 48), women with PCOM (n = 42), and women diagnosed with PCOS using the Rotterdam criteria (n = 73) were analyzed using 16S ribosomal RNA gene sequencing. Results Lower α diversity was observed in women with PCOS compared with healthy women. Women with PCOM had a change in α diversity that was intermediate between that of the other two groups. Regression analyses showed that hyperandrogenism, total testosterone, and hirsutism were negatively correlated with α diversity. Permutational multivariate analysis of variance in UniFrac distances showed that hyperandrogenism was also correlated with β diversity. A random forest identified bacteria that discriminated between healthy women and women with PCOS. Conclusion These results suggest that hyperandrogenism may play a critical role in altering the gut microbiome in women with PCOS.
TL;DR: It is demonstrated that even in pristine environments, above the atmospheric boundary layer, the downward flux of viruses varies widely, implying that viruses could have longer residence times in the atmosphere and, consequently, will be dispersed further.
Abstract: Aerosolization of soil-dust and organic aggregates in sea spray facilitates the long-range transport of bacteria, and likely viruses across the free atmosphere. Although long-distance transport occurs, there are many uncertainties associated with their deposition rates. Here, we demonstrate that even in pristine environments, above the atmospheric boundary layer, the downward flux of viruses ranged from 0.26 × 109 to >7 × 109 m−2 per day. These deposition rates were 9–461 times greater than the rates for bacteria, which ranged from 0.3 × 107 to >8 × 107 m−2 per day. The highest relative deposition rates for viruses were associated with atmospheric transport from marine rather than terrestrial sources. Deposition rates of bacteria were significantly higher during rain events and Saharan dust intrusions, whereas, rainfall did not significantly influence virus deposition. Virus deposition rates were positively correlated with organic aerosols 0.7 μm, implying that viruses could have longer residence times in the atmosphere and, consequently, will be dispersed further. These results provide an explanation for enigmatic observations that viruses with very high genetic identity can be found in very distant and different environments.
01 Jul 2018
TL;DR: Consumers are using CBD as a specific therapy for multiple diverse medical conditions—particularly pain, anxiety, depression, and sleep disorders, and these data provide a compelling rationale for further research to better understand the therapeutic potential of CBD.
Abstract: Introduction: Preclinical and clinical studies suggest that cannabidiol (CBD) found in Cannabis spp. has broad therapeutic value. CBD products can currently be purchased online, over the c...
TL;DR: This review deals with various plant-derived flavonoids, their preclinical potential as AChE inhibitors, in established assays, possible mechanisms of action, and structural activity relationship (SAR).
University of California, San Diego1, University of California, Berkeley2, University of Montana3, San Diego State University4, North Carolina State University5, University of Oregon6, University of Queensland7, Broad Institute8, Harvard University9, King's College London10, University of Minnesota11, Gladstone Institutes12, Saint Petersburg State University13, Colorado State University14, Carnegie Mellon University15, University of Nantes16, University of Pittsburgh17, University of Colorado Boulder18, Argonne National Laboratory19, National Oceanic and Atmospheric Administration20, Duke University21
TL;DR: It is shown that a citizen-science, self-selected cohort shipping samples through the mail at room temperature recaptures many known microbiome results from clinically collected cohorts and reveals new ones, and that the extent of microbiome change after events such as surgery can exceed differences between distinct environmental biomes.
Abstract: Although much work has linked the human microbiome to specific phenotypes and lifestyle variables, data from different projects have been challenging to integrate and the extent of microbial and molecular diversity in human stool remains unknown. Using standardized protocols from the Earth Microbiome Project and sample contributions from over 10,000 citizen-scientists, together with an open research network, we compare human microbiome specimens primarily from the USA, UK, and Australia to one another and to environmental samples. Our results show an unexpected range of beta-diversity in human stool microbiomes as compared to environmental samples, demonstrate the utility of procedures for removing the effects of overgrowth during room-temperature shipping for revealing phenotype correlations, uncover new molecules and kinds of molecular communities in the human stool metabolome, and examine emergent associations among the microbiome, metabolome, and the diversity of plants that are consumed (rather than relying on reductive categorical variables such as veganism, which have little or no explanatory power). We also demonstrate the utility of the living data resource and cross-cohort comparison to confirm existing associations between the microbiome and psychiatric illness, and to reveal the extent of microbiome change within one individual during surgery, providing a paradigm for open microbiome research and education. Importance We show that a citizen-science, self-selected cohort shipping samples through the mail at room temperature recaptures many known microbiome results from clinically collected cohorts and reveals new ones. Of particular interest is integrating n=1 study data with the population data, showing that the extent of microbiome change after events such as surgery can exceed differences between distinct environmental biomes, and the effect of diverse plants in the diet which we confirm with untargeted metabolomics on hundreds of samples.
TL;DR: In this article, a double-sided LC-compensation circuit for a loosely coupled, long-distance capacitive power transfer (CPT) system was proposed, where the compensation circuit resonates with the coupler to generate high voltages, and corresponding electric fields, to transfer power.
Abstract: This paper proposes a double-sided LC -compensation circuit for a loosely coupled, long-distance capacitive power transfer (CPT) system. A CPT system usually contains two pairs of metal plates as the capacitive coupler. An LC -compensation circuit resonates with the coupler to generate high voltages, and corresponding electric fields, to transfer power. When the compensation circuit is used on both the primary and secondary sides, it results in a double-sided LC -compensated CPT system. The working principle and frequency properties of the CPT system are analyzed. The results show a similarity with the series–series-compensated inductive power transfer system, which has both constant-voltage (CV) and constant-current (CC) working modes. LC -compensation is also compared with LCLC -compensation in terms of power, frequency properties, and output efficiency. A 150-W double-sided LC -compensated CPT prototype is designed and implemented to demonstrate a loosely coupled CPT system with 2.16% coupling coefficient. For both CC and CV working modes, the experimental results achieve dc–dc efficiencies higher than 70% across an air-gap distance of 180 mm with a switching frequency of 1.5 MHz.
United States Geological Survey1, San Diego State University2, Texas A&M University3, California Institute of Technology4, GNS Science5, Ludwig Maximilian University of Munich6, Stanford University7, Southern University of Science and Technology8, Indian Institutes of Technology9, Munich Re10, National Autonomous University of Mexico11, Naval Postgraduate School12, University of Memphis13, National Institute of Advanced Industrial Science and Technology14
TL;DR: In this paper, the authors describe a set of benchmark exercises that are designed to test if computer codes that simulate dynamic earthquake rupture are working as intended, and they produce simulation results that include earthquake size, amounts of fault slip, and the patterns of ground shaking and crustal deformation.
Abstract: We describe a set of benchmark exercises that are designed to test if computer codes that simulate dynamic earthquake rupture are working as intended. These types of computer codes are often used to understand how earthquakes operate, and they produce simulation results that include earthquake size, amounts of fault slip, and the patterns of ground shaking and crustal deformation. The benchmark exercises examine a range of features that scientists incorporate in their dynamic earthquake rupture simulations. These include implementations of simple or complex fault geometry, off‐fault rock response to an earthquake, stress conditions, and a variety of formulations for fault friction. Many of the benchmarks were designed to investigate scientific problems at the forefronts of earthquake physics and strong ground motions research. The exercises are freely available on our website for use by the scientific community.
TL;DR: It was found that doubling the number of trials recommended by previous studies led to more than a doubling of statistical power under many conditions, rather than relying solely on general recommendations about thenumber of trials needed to obtain a "stable" ERP waveform.
Abstract: In designing an ERP study, researchers must choose how many trials to include, balancing the desire to maximize statistical power and the need to minimize the length of the recording session. Recent studies have attempted to quantify the minimum number of trials needed to obtain reliable measures for a variety of ERP components. However, these studies have largely ignored other variables that affect statistical power in ERP studies, including sample size and effect magnitude. The goal of the present study was to determine whether and how the number of trials, number of participants, and effect magnitude interact to influence statistical power, thus providing a better guide for selecting an appropriate number of trials. We used a Monte Carlo approach to measure the probability of obtaining a statistically significant result when testing for (a) the presence of an ERP effect, (b) within-participant condition differences in an ERP effect, and (c) between-participants group differences in an ERP effect. Each of these issues was examined in the context of the error-related negativity and the lateralized readiness potential. We found that doubling the number of trials recommended by previous studies led to more than a doubling of statistical power under many conditions. Thus, when determining the number of trials that should be included in a given study, researchers must consider the sample size, the anticipated effect magnitude, and the noise level, rather than relying solely on general recommendations about the number of trials needed to obtain a "stable" ERP waveform.