1,194 research outputs found

    Development of a National Anthropogenic Heating Database with an Extrapolation for International Cities

    Get PDF
    Given increasing utility of numerical models to examine urban impacts on meteorology and climate, there exists an urgent need for accurate representation of seasonally and diurnally varying anthropogenic heating data, an important component of the urban energy budget for cities across the world. Incorporation of anthropogenic heating data as inputs to existing climate modeling systems has direct societal implications ranging from improved prediction of energy demand to health assessment, but such data are lacking for most cities. To address this deficiency we have applied a standardized procedure to develop a national database of seasonally and diurnally varying anthropogenic heating profiles for 61 of the largest cities in the United Stated (U.S.). Recognizing the importance of spatial scale, the anthropogenic heating database developed includes the city scale and the accompanying greater metropolitan area. Our analysis reveals that a single profile function can adequately represent anthropogenic heating during summer but two profile functions are required in winter, one for warm climate cities and another for cold climate cities. On average, although anthropogenic heating is 40% larger in winter than summer, the electricity sector contribution peaks during summer and is smallest in winter. Because such data are similarly required for international cities where urban climate assessments are also ongoing, we have made a simple adjustment accounting for different international energy consumption rates relative to the U.S. to generate seasonally and diurnally varying anthropogenic heating profiles for a range of global cities. The methodological approach presented here is flexible and straightforwardly applicable to cities not modeled because of presently unavailable data. Because of the anticipated increase in global urban populations for many decades to come, characterizing this fundamental aspect of the urban environment – anthropogenic heating – is an essential element toward continued progress in urban climate assessment

    Measurement errors in body size of sea scallops (Placopecten magellanicus) and their effect on stock assessment models

    Get PDF
    Body-size measurement errors are usually ignored in stock assessments, but may be important when body-size data (e.g., from visual sur veys) are imprecise. We used experiments and models to quantify measurement errors and their effects on assessment models for sea scallops (Placopecten magellanicus). Errors in size data obscured modes from strong year classes and increased frequency and size of the largest and smallest sizes, potentially biasing growth, mortality, and biomass estimates. Modeling techniques for errors in age data proved useful for errors in size data. In terms of a goodness of model fit to the assessment data, it was more important to accommodate variance than bias. Models that accommodated size errors fitted size data substantially better. We recommend experimental quantification of errors along with a modeling approach that accommodates measurement errors because a direct algebraic approach was not robust and because error parameters were diff icult to estimate in our assessment model. The importance of measurement errors depends on many factors and should be evaluated on a case by case basis

    Bibliometric and authorship trends over a 30 year publication history in two representative US sports medicine journals

    Get PDF
    Bibliometric studies are important to understand changes and improvement opportunities in academia. This study compared bibliometric trends for two major sports medicine/arthroscopy journals, the American Journal of Sports Medicine® (AJSM®) and Arthroscopy® over the past 30 years. Trends over time and comparisons between both journals were noted for common bibliometric variables (number of authors, references, pages, citations, and corresponding author position) as well as author gender and continental origin. Appropriate statistical analyses were performed. A p < 0.001 was considered statistically significant. One representative year per decade was used. There were 814 manuscripts from AJSM® and 650 from Arthroscopy®. For AJSM® the number of manuscripts steadily increased from 86 in 1986 to 350 in 2016; for Arthroscopy® the number of manuscripts increased from 73 in 1985/1986, to 267 in 2006, but then dropped to 229 in 2016. There were significant increases in all bibliometric variables, except for the number of citations which decreased in Arthroscopy®. There were significant differences in manuscript region of origin by journal (p = 0.000002). Arthroscopy® had a greater percentage of manuscripts from Asia than AJSM® (19.3% vs 11.5%) while AJSM® had a greater percentage from North America (70.3% vs 59.2%); both journals had similar percentages from Europe (18.2% for AJSM® and 21.6% for Arthroscopy®). For AJSM® the average percentage of female first authors was 13.3%, increasing from 4.7% in 1986 to 19.3% in 2016; the average percentage of female corresponding authors was 7.3%. For Arthroscopy®, the average percentage of female first authors was 8.1%, increasing from 2.8% in 1985/1986 to 15.7% in 2016 (p = 0.00007). In conclusion, AJSM® and Arthroscopy® showed an increase in most variables analyzed. Although Arthroscopy® is climbing at a higher rate than AJSM® for female authors, AJSM® has an overall greater percentage of female authors

    Trade-offs between sociality and gastrointestinal parasite infection in the context of a natural disaster

    Get PDF
    This work was supported by ANID-Chilean scholarship [number 72190290], the National Institutes of Health Grants [R01AG060931] to N.S-M., L.J.N.B. and J.P.H., [R00AG051764] to N.S-M, [R01MH118203] to M.L.P., M.J.M, L.J.N.B. and N.S-M., [R01MH096875] to M.L.P., L.J.N.B. and M.J.M., [U01MH121260] to N.S-M., M.L.P. and M.J.M., a European Research Council Consolidator Grant to L.J.N.B. [Friend Origins - 864461].Parasites and infectious diseases constitute important challenges particularly for group-living animals. Social contact and shared space can both increase parasite transmission risk, while individual differences in social capital can help prevent infections. For example, high social status individuals and those with more or stronger affiliative partnerships may have better immunity and, thus, lower parasitic burden. To test for health trade-offs in the costs and benefits of sociality, we quantified how parasitic load varied with an individual's social status, as well as with their affiliative relationships with weakly and strongly bonded partners, in a free-ranging population of rhesus macaques, Macaca mulatta. We found that high status was associated with a lower risk of protozoa infection at older ages compared to younger and low-status animals. Social resources can also be protective against infection under environmentally challenging situations, such as natural disasters. Using cross-sectional data, we additionally examined the impact of a major hurricane on the sociality - parasite relationship in this system and found that the hurricane influenced the prevalence of specific parasites independent of sociality. Overall, our study adds to the growing evidence for social status as a strong predictor of infection risk and highlights how extreme environmental events could shape vulnerability and resistance to infection.Peer reviewe

    Framework for a Community Health Observing System for the Gulf of Mexico Region: Preparing for Future Disasters

    Get PDF
    © Copyright © 2020 Sandifer, Knapp, Lichtveld, Manley, Abramson, Caffey, Cochran, Collier, Ebi, Engel, Farrington, Finucane, Hale, Halpern, Harville, Hart, Hswen, Kirkpatrick, McEwen, Morris, Orbach, Palinkas, Partyka, Porter, Prather, Rowles, Scott, Seeman, Solo-Gabriele, Svendsen, Tincher, Trtanj, Walker, Yehuda, Yip, Yoskowitz and Singer. The Gulf of Mexico (GoM) region is prone to disasters, including recurrent oil spills, hurricanes, floods, industrial accidents, harmful algal blooms, and the current COVID-19 pandemic. The GoM and other regions of the U.S. lack sufficient baseline health information to identify, attribute, mitigate, and facilitate prevention of major health effects of disasters. Developing capacity to assess adverse human health consequences of future disasters requires establishment of a comprehensive, sustained community health observing system, similar to the extensive and well-established environmental observing systems. We propose a system that combines six levels of health data domains, beginning with three existing, national surveys and studies plus three new nested, longitudinal cohort studies. The latter are the unique and most important parts of the system and are focused on the coastal regions of the five GoM States. A statistically representative sample of participants is proposed for the new cohort studies, stratified to ensure proportional inclusion of urban and rural populations and with additional recruitment as necessary to enroll participants from particularly vulnerable or under-represented groups. Secondary data sources such as syndromic surveillance systems, electronic health records, national community surveys, environmental exposure databases, social media, and remote sensing will inform and augment the collection of primary data. Primary data sources will include participant-provided information via questionnaires, clinical measures of mental and physical health, acquisition of biological specimens, and wearable health monitoring devices. A suite of biomarkers may be derived from biological specimens for use in health assessments, including calculation of allostatic load, a measure of cumulative stress. The framework also addresses data management and sharing, participant retention, and system governance. The observing system is designed to continue indefinitely to ensure that essential pre-, during-, and post-disaster health data are collected and maintained. It could also provide a model/vehicle for effective health observation related to infectious disease pandemics such as COVID-19. To our knowledge, there is no comprehensive, disaster-focused health observing system such as the one proposed here currently in existence or planned elsewhere. Significant strengths of the GoM Community Health Observing System (CHOS) are its longitudinal cohorts and ability to adapt rapidly as needs arise and new technologies develop

    Framework for a Community Health Observing System for the Gulf of Mexico Region: Preparing for Future Disasters

    Get PDF
    © Copyright © 2020 Sandifer, Knapp, Lichtveld, Manley, Abramson, Caffey, Cochran, Collier, Ebi, Engel, Farrington, Finucane, Hale, Halpern, Harville, Hart, Hswen, Kirkpatrick, McEwen, Morris, Orbach, Palinkas, Partyka, Porter, Prather, Rowles, Scott, Seeman, Solo-Gabriele, Svendsen, Tincher, Trtanj, Walker, Yehuda, Yip, Yoskowitz and Singer. The Gulf of Mexico (GoM) region is prone to disasters, including recurrent oil spills, hurricanes, floods, industrial accidents, harmful algal blooms, and the current COVID-19 pandemic. The GoM and other regions of the U.S. lack sufficient baseline health information to identify, attribute, mitigate, and facilitate prevention of major health effects of disasters. Developing capacity to assess adverse human health consequences of future disasters requires establishment of a comprehensive, sustained community health observing system, similar to the extensive and well-established environmental observing systems. We propose a system that combines six levels of health data domains, beginning with three existing, national surveys and studies plus three new nested, longitudinal cohort studies. The latter are the unique and most important parts of the system and are focused on the coastal regions of the five GoM States. A statistically representative sample of participants is proposed for the new cohort studies, stratified to ensure proportional inclusion of urban and rural populations and with additional recruitment as necessary to enroll participants from particularly vulnerable or under-represented groups. Secondary data sources such as syndromic surveillance systems, electronic health records, national community surveys, environmental exposure databases, social media, and remote sensing will inform and augment the collection of primary data. Primary data sources will include participant-provided information via questionnaires, clinical measures of mental and physical health, acquisition of biological specimens, and wearable health monitoring devices. A suite of biomarkers may be derived from biological specimens for use in health assessments, including calculation of allostatic load, a measure of cumulative stress. The framework also addresses data management and sharing, participant retention, and system governance. The observing system is designed to continue indefinitely to ensure that essential pre-, during-, and post-disaster health data are collected and maintained. It could also provide a model/vehicle for effective health observation related to infectious disease pandemics such as COVID-19. To our knowledge, there is no comprehensive, disaster-focused health observing system such as the one proposed here currently in existence or planned elsewhere. Significant strengths of the GoM Community Health Observing System (CHOS) are its longitudinal cohorts and ability to adapt rapidly as needs arise and new technologies develop

    BRCA2 polymorphic stop codon K3326X and the risk of breast, prostate, and ovarian cancers

    Get PDF
    Background: The K3326X variant in BRCA2 (BRCA2*c.9976A&gt;T; p.Lys3326*; rs11571833) has been found to be associated with small increased risks of breast cancer. However, it is not clear to what extent linkage disequilibrium with fully pathogenic mutations might account for this association. There is scant information about the effect of K3326X in other hormone-related cancers. Methods: Using weighted logistic regression, we analyzed data from the large iCOGS study including 76 637 cancer case patients and 83 796 control patients to estimate odds ratios (ORw) and 95% confidence intervals (CIs) for K3326X variant carriers in relation to breast, ovarian, and prostate cancer risks, with weights defined as probability of not having a pathogenic BRCA2 variant. Using Cox proportional hazards modeling, we also examined the associations of K3326X with breast and ovarian cancer risks among 7183 BRCA1 variant carriers. All statistical tests were two-sided. Results: The K3326X variant was associated with breast (ORw = 1.28, 95% CI = 1.17 to 1.40, P = 5.9x10- 6) and invasive ovarian cancer (ORw = 1.26, 95% CI = 1.10 to 1.43, P = 3.8x10-3). These associations were stronger for serous ovarian cancer and for estrogen receptor–negative breast cancer (ORw = 1.46, 95% CI = 1.2 to 1.70, P = 3.4x10-5 and ORw = 1.50, 95% CI = 1.28 to 1.76, P = 4.1x10-5, respectively). For BRCA1 mutation carriers, there was a statistically significant inverse association of the K3326X variant with risk of ovarian cancer (HR = 0.43, 95% CI = 0.22 to 0.84, P = .013) but no association with breast cancer. No association with prostate cancer was observed. Conclusions: Our study provides evidence that the K3326X variant is associated with risk of developing breast and ovarian cancers independent of other pathogenic variants in BRCA2. Further studies are needed to determine the biological mechanism of action responsible for these associations

    Rapid and iterative genome editing in the malaria parasite Plasmodium knowlesi provides new tools for P. vivax research.

    Get PDF
    Tackling relapsing Plasmodium vivax and zoonotic Plasmodium knowlesi infections is critical to reducing malaria incidence and mortality worldwide. Understanding the biology of these important and related parasites was previously constrained by the lack of robust molecular and genetic approaches. Here, we establish CRISPR-Cas9 genome editing in a culture-adapted P. knowlesi strain and define parameters for optimal homology-driven repair. We establish a scalable protocol for the production of repair templates by PCR and demonstrate the flexibility of the system by tagging proteins with distinct cellular localisations. Using iterative rounds of genome-editing we generate a transgenic line expressing P. vivax Duffy binding protein (PvDBP), a lead vaccine candidate. We demonstrate that PvDBP plays no role in reticulocyte restriction but can alter the macaque/human host cell tropism of P. knowlesi. Critically, antibodies raised against the P. vivax antigen potently inhibit proliferation of this strain, providing an invaluable tool to support vaccine development

    The Consensus Coding Sequence (Ccds) Project: Identifying a Common Protein-Coding Gene Set for the Human and Mouse Genomes

    Get PDF
    Effective use of the human and mouse genomes requires reliable identification of genes and their products. Although multiple public resources provide annotation, different methods are used that can result in similar but not identical representation of genes, transcripts, and proteins. The collaborative consensus coding sequence (CCDS) project tracks identical protein annotations on the reference mouse and human genomes with a stable identifier (CCDS ID), and ensures that they are consistently represented on the NCBI, Ensembl, and UCSC Genome Browsers. Importantly, the project coordinates on manually reviewing inconsistent protein annotations between sites, as well as annotations for which new evidence suggests a revision is needed, to progressively converge on a complete protein-coding set for the human and mouse reference genomes, while maintaining a high standard of reliability and biological accuracy. To date, the project has identified 20,159 human and 17,707 mouse consensus coding regions from 17,052 human and 16,893 mouse genes. Three evaluation methods indicate that the entries in the CCDS set are highly likely to represent real proteins, more so than annotations from contributing groups not included in CCDS. The CCDS database thus centralizes the function of identifying well-supported, identically-annotated, protein-coding regions.National Human Genome Research Institute (U.S.) (Grant number 1U54HG004555-01)Wellcome Trust (London, England) (Grant number WT062023)Wellcome Trust (London, England) (Grant number WT077198
    corecore