Universidade Federal de Pernambuco

BACKGROUND: The Global Burden of Diseases, Injuries, and Risk Factors Study 2015 provides an up-to-date synthesis of the evidence for risk factor exposure and the attributable burden of disease. By providing national and subnational assessments spanning the past 25 years, this study can inform debates on the importance of addressing risks in context. METHODS: We used the comparative risk assessment framework developed for previous iterations of the Global Burden of Disease Study to estimate attributable deaths, disability-adjusted life-years (DALYs), and trends in exposure by age group, sex, year, and geography for 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks from 1990 to 2015. This study included 388 risk-outcome pairs that met World Cancer Research Fund-defined criteria for convincing or probable evidence. We extracted relative risk and exposure estimates from randomised controlled trials, cohorts, pooled cohorts, household surveys, census data, satellite data, and other sources. We used statistical models to pool data, adjust for bias, and incorporate covariates. We developed a metric that allows comparisons of exposure across risk factors-the summary exposure value. Using the counterfactual scenario of theoretical minimum risk level, we estimated the portion of deaths and DALYs that could be attributed to a given risk. We decomposed trends in attributable burden into contributions from population growth, population age structure, risk exposure, and risk-deleted cause-specific DALY rates. We characterised risk exposure in relation to a Socio-demographic Index (SDI). FINDINGS: Between 1990 and 2015, global exposure to unsafe sanitation, household air pollution, childhood underweight, childhood stunting, and smoking each decreased by more than 25%. Global exposure for several occupational risks, high body-mass index (BMI), and drug use increased by more than 25% over the same period. All risks jointly evaluated in 2015 accounted for 57·8% (95% CI 56·6-58·8) of global deaths and 41·2% (39·8-42·8) of DALYs. In 2015, the ten largest contributors to global DALYs among Level 3 risks were high systolic blood pressure (211·8 million [192·7 million to 231·1 million] global DALYs), smoking (148·6 million [134·2 million to 163·1 million]), high fasting plasma glucose (143·1 million [125·1 million to 163·5 million]), high BMI (120·1 million [83·8 million to 158·4 million]), childhood undernutrition (113·3 million [103·9 million to 123·4 million]), ambient particulate matter (103·1 million [90·8 million to 115·1 million]), high total cholesterol (88·7 million [74·6 million to 105·7 million]), household air pollution (85·6 million [66·7 million to 106·1 million]), alcohol use (85·0 million [77·2 million to 93·0 million]), and diets high in sodium (83·0 million [49·3 million to 127·5 million]). From 1990 to 2015, attributable DALYs declined for micronutrient deficiencies, childhood undernutrition, unsafe sanitation and water, and household air pollution; reductions in risk-deleted DALY rates rather than reductions in exposure drove these declines. Rising exposure contributed to notable increases in attributable DALYs from high BMI, high fasting plasma glucose, occupational carcinogens, and drug use. Environmental risks and childhood undernutrition declined steadily with SDI; low physical activity, high BMI, and high fasting plasma glucose increased with SDI. In 119 countries, metabolic risks, such as high BMI and fasting plasma glucose, contributed the most attributable DALYs in 2015. Regionally, smoking still ranked among the leading five risk factors for attributable DALYs in 109 countries; childhood underweight and unsafe sex remained primary drivers of early death and disability in much of sub-Saharan Africa. INTERPRETATION: Declines in some key environmental risks have contributed to declines in critical infectious diseases. Some risks appear to be invariant to SDI. Increasing risks, including high BMI, high fasting plasma glucose, drug use, and some occupational exposures, contribute to rising burden from some conditions, but also provide opportunities for intervention. Some highly preventable risks, such as smoking, remain major causes of attributable DALYs, even as exposure is declining. Public policy makers need to pay attention to the risks that are increasingly major contributors to global burden. FUNDING: Bill & Melinda Gates Foundation.

Abstract. This paper proposes a regression model where the response is beta distributed using a parameterization of the beta law that is indexed by mean and dispersion pa-rameters. The proposed model is useful for situations where the variable of interest is continuous and restricted to the interval (0, 1) and is related to other variables through a regression structure. The regression parameters of the beta regression model are inter-pretable in terms of the mean of the response and, when the logit link is used, of an odds ratio, unlike the parameters of a linear regression that employs a transformed response. Estimation is performed by maximum likelihood. We provide closed-form expressions for the score function, for Fisher’s information matrix and its inverse. Hypothesis testing is performed using approximations obtained from the asymptotic normality of the max-imum likelihood estimator. Some diagnostic measures are introduced. Finally, practical applications that employ real data are presented and discussed.

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives.

Functional traits offer a rich quantitative framework for developing and testing theories in evolutionary biology, ecology and ecosystem science. However, the potential of functional traits to drive theoretical advances and refine models of global change can only be fully realised when species-level information is complete. Here we present the AVONET dataset containing comprehensive functional trait data for all birds, including six ecological variables, 11 continuous morphological traits, and information on range size and location. Raw morphological measurements are presented from 90,020 individuals of 11,009 extant bird species sampled from 181 countries. These data are also summarised as species averages in three taxonomic formats, allowing integration with a global phylogeny, geographical range maps, IUCN Red List data and the eBird citizen science database. The AVONET dataset provides the most detailed picture of continuous trait variation for any major radiation of organisms, offering a global template for testing hypotheses and exploring the evolutionary origins, structure and functioning of biodiversity.

TEST 02 - Elsevier's Scopus, the largest abstract and citation database of peer-reviewed literature. Search and access research from the science, technology, medicine, social sciences and arts and humanities fields.

An analysis of everyday use of mathematics by working youngsters in commercial transactions in Recife, Brazil, revealed computational strategies different from those taught in schools. Performance on mathematical problems embedded in real‐life contexts was superior to that on school‐type word problems and context‐free computational problems involving the same numbers and operations. Implications for education are examined.

Universidade Federal de Goiás

New remote sensing data on vegetation cover and restoration opportunities bring hope to the Brazilian Atlantic Forest, one of the hottest of the 36 global biodiversity hotspots. Available estimates of remaining vegetation cover in the biome currently range from 11% to 16%. However, our new land-cover map, prepared at the highest resolution ever (5 m), reveals a current vegetation cover of 28%, or 32 million hectares (Mha) of native vegetation. Simultaneously, we found 7.2 Mha of degraded riparian areas, of which 5.2 Mha at least must be restored before 2038 by landowners for legislation compliance. Restoring the existing legal debt could increase native vegetation cover in the Atlantic Forest up to 35%. Such effort, if well planned and implemented, could reduce extinction processes by increasing connectivity of vegetation remnants and rising total native cover to above the critical biodiversity threshold established for different taxonomic groups. If undertaken, this process can be adaptive to climate change and boost sustainable development in this most populous biome in Brazil, turning it into a hopespot.

The Classical Algorithms. Reference Counting. Mark--Sweep Garbage Collection. Mark--Compact Garbage Collection. Copying Garbage Collection. Generational Garbage Collection. Incremental and Concurrent Garbage Collection. Garbage Collection for C. Garbage Collection for C++. Cache--Conscious Garbage Collection. Distributed Garbage Collection. Glossary. Bibliography. Index.

Capital to topological insulators, the bulk-boundary correspondence ties a topological invariant computed from the bulk (extended) states with those at the boundary, which are hence robust to disorder. Here we put forward a different ordering unique to non-Hermitian lattices whereby a pristine system becomes devoid of extended states, a property which turns out to be robust to disorder. This is enabled by a peculiar type of non-Hermitian degeneracy where a macroscopic fraction of the states coalesce at a single point with a geometrical multiplicity of 1.

International audience

Streptomyces is a genus of Gram-positive bacteria that grows in various environments, and its shape resembles filamentous fungi. The morphological differentiation of Streptomyces involves the formation of a layer of hyphae that can differentiate into a chain of spores. The most interesting property of Streptomyces is the ability to produce bioactive secondary metabolites, such as antifungals, antivirals, antitumorals, anti-hypertensives, immunosuppressants, and especially antibiotics. The production of most antibiotics is species specific, and these secondary metabolites are important for Streptomyces species in order to compete with other microorganisms that come in contact, even within the same genre. Despite the success of the discovery of antibiotics, and advances in the techniques of their production, infectious diseases still remain the second leading cause of death worldwide, and bacterial infections cause approximately 17 million deaths annually, affecting mainly children and the elderly. Self-medication and overuse of antibiotics is another important factor that contributes to resistance, reducing the lifetime of the antibiotic, thus causing the constant need for research and development of new antibiotics.

Dothideomycetes comprise a highly diverse range of fungi characterized mainly by asci with two wall layers (bitunicate asci) and often with fissitunicate dehiscence. Many species are saprobes, with many asexual states comprising important plant pathogens. They are also endophytes, epiphytes, fungicolous, lichenized, or lichenicolous fungi. They occur in terrestrial, freshwater and marine habitats in almost every part of the world. We accept 105 families in Dothideomycetes with the new families Anteagloniaceae, Bambusicolaceae, Biatriosporaceae, Lichenoconiaceae, Muyocopronaceae, Paranectriellaceae, Roussoellaceae, Salsugineaceae, Seynesiopeltidaceae and Thyridariaceae introduced in this paper. Each family is provided with a description and notes, including asexual and asexual states, and if more than one genus is included, the type genus is also characterized. Each family is provided with at least one figure-plate, usually illustrating the type genus, a list of accepted genera, including asexual genera, and a key to these genera. A phylogenetic tree based on four gene combined analysis add support for 64 of the families and 22 orders, including the novel orders, Dyfrolomycetales, Lichenoconiales, Lichenotheliales, Monoblastiales, Natipusillales, Phaeotrichales and Strigulales. The paper is expected to provide a working document on Dothideomycetes which can be modified as new data comes to light. It is hoped that by illustrating types we provide stimulation and interest so that more work is carried out in this remarkable group of fungi.

Regrowth of tropical secondary forests following complete or nearly complete removal of forest vegetation actively stores carbon in aboveground biomass, partially counterbalancing carbon emissions from deforestation, forest degradation, burning of fossil fuels, and other anthropogenic sources. We estimate the age and spatial extent of lowland second-growth forests in the Latin American tropics and model their potential aboveground carbon accumulation over four decades. Our model shows that, in 2008, second-growth forests (1 to 60 years old) covered 2.4 million km(2) of land (28.1% of the total study area). Over 40 years, these lands can potentially accumulate a total aboveground carbon stock of 8.48 Pg C (petagrams of carbon) in aboveground biomass via low-cost natural regeneration or assisted regeneration, corresponding to a total CO2 sequestration of 31.09 Pg CO2. This total is equivalent to carbon emissions from fossil fuel use and industrial processes in all of Latin America and the Caribbean from 1993 to 2014. Ten countries account for 95% of this carbon storage potential, led by Brazil, Colombia, Mexico, and Venezuela. We model future land-use scenarios to guide national carbon mitigation policies. Permitting natural regeneration on 40% of lowland pastures potentially stores an additional 2.0 Pg C over 40 years. Our study provides information and maps to guide national-level forest-based carbon mitigation plans on the basis of estimated rates of natural regeneration and pasture abandonment. Coupled with avoided deforestation and sustainable forest management, natural regeneration of second-growth forests provides a low-cost mechanism that yields a high carbon sequestration potential with multiple benefits for biodiversity and ecosystem services.

Abstract. The Surface Ocean CO2 Atlas (SOCAT) is a synthesis of quality-controlled fCO2 (fugacity of carbon dioxide) values for the global surface oceans and coastal seas with regular updates. Version 3 of SOCAT has 14.7 million fCO2 values from 3646 data sets covering the years 1957 to 2014. This latest version has an additional 4.6 million fCO2 values relative to version 2 and extends the record from 2011 to 2014. Version 3 also significantly increases the data availability for 2005 to 2013. SOCAT has an average of approximately 1.2 million surface water fCO2 values per year for the years 2006 to 2012. Quality and documentation of the data has improved. A new feature is the data set quality control (QC) flag of E for data from alternative sensors and platforms. The accuracy of surface water fCO2 has been defined for all data set QC flags. Automated range checking has been carried out for all data sets during their upload into SOCAT. The upgrade of the interactive Data Set Viewer (previously known as the Cruise Data Viewer) allows better interrogation of the SOCAT data collection and rapid creation of high-quality figures for scientific presentations. Automated data upload has been launched for version 4 and will enable more frequent SOCAT releases in the future. High-profile scientific applications of SOCAT include quantification of the ocean sink for atmospheric carbon dioxide and its long-term variation, detection of ocean acidification, as well as evaluation of coupled-climate and ocean-only biogeochemical models. Users of SOCAT data products are urged to acknowledge the contribution of data providers, as stated in the SOCAT Fair Data Use Statement. This ESSD (Earth System Science Data) "living data" publication documents the methods and data sets used for the assembly of this new version of the SOCAT data collection and compares these with those used for earlier versions of the data collection (Pfeil et al., 2013; Sabine et al., 2013; Bakker et al., 2014). Individual data set files, included in the synthesis product, can be downloaded here: doi:10.1594/PANGAEA.849770. The gridded products are available here: doi:10.3334/CDIAC/OTG.SOCAT_V3_GRID.

A significant number of drugs and drug candidates in clinical development are halogenated structures. For a long time, insertion of halogen atoms on hit or lead compounds was predominantly performed to exploit their steric effects, through the ability of these bulk atoms to occupy the binding site of molecular targets. However, halogens in drug - target complexes influence several processes rather than steric aspects alone. For example, the formation of halogen bonds in ligand-target complexes is now recognized as a kind of intermolecular interaction that favorably contributes to the stability of ligand-target complexes. This paper is aimed at introducing the fascinating versatility of halogen atoms. It starts summarizing the prevalence of halogenated drugs and their structural and pharmacological features. Next, we discuss the identification and prediction of halogen bonds in protein-ligand complexes, and how these bonds should be exploited. Interesting results of halogen insertions during the processes of hit-to-lead or lead-to-drug conversions are also detailed. Polyhalogenated anesthetics and protein kinase inhibitors that bear halogens are analyzed as cases studies. Thereby, this review serves as one guide for the virtual screening of libraries containing halogenated compounds and may be a source of inspiration for the medicinal chemists.

Old-growth tropical forests are being extensively deforested and fragmented worldwide. Yet forest recovery through succession has led to an expansion of secondary forests in human-modified tropical landscapes (HMTLs). Secondary forests thus emerge as a potential repository for tropical biodiversity, and also as a source of essential ecosystem functions and services in HMTLs. Such critical roles are controversial, however, as they depend on successional, landscape and socio-economic dynamics, which can vary widely within and across landscapes and regions. Understanding the main drivers of successional pathways of disturbed tropical forests is critically needed for improving management, conservation, and restoration strategies. Here, we combine emerging knowledge from tropical forest succession, forest fragmentation and landscape ecology research to identify the main driving forces shaping successional pathways at different spatial scales. We also explore causal connections between land-use dynamics and the level of predictability of successional pathways, and examine potential implications of such connections to determine the importance of secondary forests for biodiversity conservation in HMTLs. We show that secondary succession (SS) in tropical landscapes is a multifactorial phenomenon affected by a myriad of forces operating at multiple spatio-temporal scales. SS is relatively fast and more predictable in recently modified landscapes and where well-preserved biodiversity-rich native forests are still present in the landscape. Yet the increasing variation in landscape spatial configuration and matrix heterogeneity in landscapes with intermediate levels of disturbance increases the uncertainty of successional pathways. In landscapes that have suffered extensive and intensive human disturbances, however, succession can be slow or arrested, with impoverished assemblages and reduced potential to deliver ecosystem functions and services. We conclude that: (i) succession must be examined using more comprehensive explanatory models, providing information about the forces affecting not only the presence but also the persistence of species and ecological groups, particularly of those taxa expected to be extirpated from HMTLs; (ii) SS research should integrate new aspects from forest fragmentation and landscape ecology research to address accurately the potential of secondary forests to serve as biodiversity repositories; and (iii) secondary forest stands, as a dynamic component of HMTLs, must be incorporated as key elements of conservation planning; i.e. secondary forest stands must be actively managed (e.g. using assisted forest restoration) according to conservation goals at broad spatial scales.

Specialized computational chemistry packages have permanently reshaped the landscape of chemical and materials science by providing tools to support and guide experimental efforts and for the prediction of atomistic and electronic properties. In this regard, electronic structure packages have played a special role by using first-principle-driven methodologies to model complex chemical and materials processes. Over the past few decades, the rapid development of computing technologies and the tremendous increase in computational power have offered a unique chance to study complex transformations using sophisticated and predictive many-body techniques that describe correlated behavior of electrons in molecular and condensed phase systems at different levels of theory. In enabling these simulations, novel parallel algorithms have been able to take advantage of computational resources to address the polynomial scaling of electronic structure methods. In this paper, we briefly review the NWChem computational chemistry suite, including its history, design principles, parallel tools, current capabilities, outreach, and outlook.

BACKGROUND/OBJECTIVES: Psychiatry lacks the objective clinical tests routinely used in other specializations. Novel computerized methods to characterize complex behaviors such as speech could be used to identify and predict psychiatric illness in individuals. AIMS: In this proof-of-principle study, our aim was to test automated speech analyses combined with Machine Learning to predict later psychosis onset in youths at clinical high-risk (CHR) for psychosis. METHODS: Thirty-four CHR youths (11 females) had baseline interviews and were assessed quarterly for up to 2.5 years; five transitioned to psychosis. Using automated analysis, transcripts of interviews were evaluated for semantic and syntactic features predicting later psychosis onset. Speech features were fed into a convex hull classification algorithm with leave-one-subject-out cross-validation to assess their predictive value for psychosis outcome. The canonical correlation between the speech features and prodromal symptom ratings was computed. RESULTS: Derived speech features included a Latent Semantic Analysis measure of semantic coherence and two syntactic markers of speech complexity: maximum phrase length and use of determiners (e.g., which). These speech features predicted later psychosis development with 100% accuracy, outperforming classification from clinical interviews. Speech features were significantly correlated with prodromal symptoms. CONCLUSIONS: Findings support the utility of automated speech analysis to measure subtle, clinically relevant mental state changes in emergent psychosis. Recent developments in computer science, including natural language processing, could provide the foundation for future development of objective clinical tests for psychiatry.

Summary Competitor, stress‐tolerator, ruderal ( CSR ) theory is a prominent plant functional strategy scheme previously applied to local floras. Globally, the wide geographic and phylogenetic coverage of available values of leaf area ( LA ), leaf dry matter content ( LDMC ) and specific leaf area ( SLA ) (representing, respectively, interspecific variation in plant size and conservative vs . acquisitive resource economics) promises the general application of CSR strategies across biomes, including the tropical forests hosting a large proportion of Earth's diversity. We used trait variation for 3068 tracheophytes (representing 198 families, six continents and 14 biomes) to create a globally calibrated CSR strategy calculator tool and investigate strategy–environment relationships across biomes world‐wide. Due to disparity in trait availability globally, co‐inertia analysis was used to check correspondence between a ‘wide geographic coverage, few traits’ data set and a ‘restricted coverage, many traits’ subset of 371 species for which 14 whole‐plant, flowering, seed and leaf traits (including leaf nitrogen content) were available. CSR strategy/environment relationships within biomes were investigated using fourth‐corner and RLQ analyses to determine strategy/climate specializations. Strong, significant concordance ( RV = 0·597; P < 0·0001) was evident between the 14 trait multivariate space and when only LA , LDMC and SLA were used. Biomes such as tropical moist broadleaf forests exhibited strategy convergence (i.e. clustered around a CS / CSR median; C:S:R = 43:42:15%), with CS ‐selection associated with warm, stable situations (lesser temperature seasonality), with greater annual precipitation and potential evapotranspiration. Other biomes were characterized by strategy divergence: for example, deserts varied between xeromorphic perennials such as Larrea divaricata, classified as S‐selected (C:S:R = 1:99:0%) and broadly R‐selected annual herbs (e.g. Claytonia perfoliata ; R/ CR ‐selected; C:S:R = 21:0:79%). Strategy convergence was evident for several growth habits (e.g. trees) but not others (forbs). The CSR strategies of vascular plants can now be compared quantitatively within and between biomes at the global scale. Through known linkages between underlying leaf traits and growth rates, herbivory and decomposition rates, this method and the strategy–environment relationships it elucidates will help to predict which kinds of species may assemble in response to changes in biogeochemical cycles, climate and land use.