Optical Spectra of SNR Candidates in NGC 300

We present moderate-resolution (<5A) long-slit optical spectra of 51 nebular objects in the nearby Sculptor Group galaxy NGC 300 obtained with the 2.3 meter Advanced Technology Telescope at Siding Spring Observatory, Australia. Adopting the criterion of [SII]/Ha>=0.4 to confirm supernova remnants (SNRs) from optical spectra, we find that of 28 objects previously proposed as SNRs from optical observations, 22 meet this criterion with six showing [SII]/Ha of less than 0.4. Of 27 objects suggested as SNRs from radio data, four are associated with the 28 previously proposed SNRs. Of these four, three (included in the 22 above) meet the criterion. In all, 22 of the 51 nebular objects meet the [SII]/Ha criterion as SNRs while the nature of the remaining 29 objects remains undetermined by these observations.Comment: Accepted for publication in Astrophysics & Space Scienc

Fungal Planet description sheets : 1182–1283

Novel species of fungi described in this study include those from various countries as follows: Algeria, Phaeoacremonium adelophialidum from Vitis vinifera. Antarctica, Comoclathris antarctica from soil. Australia, Coniochaeta salicifolia as endophyte from healthy leaves of Geijera salicifolia, Eremothecium peggii in fruit of Citrus australis, Microdochium ratticaudae from stem of Sporobolus natalensis, Neocelosporium corymbiae on stems of Corymbia variegata, Phytophthora kelmanii from rhizosphere soil of Ptilotus pyramidatus, Pseudosydowia backhousiae on living leaves of Backhousia citriodora, Pseudosydowia indooroopillyensis, Pseudosydowia louisecottisiae and Pseudosydowia queenslandica on living leaves of Eucalyptus sp. Brazil, Absidia montepascoalis from soil. Chile, Ilyonectria zarorii from soil under Maytenus boaria. Costa Rica, Colletotrichum filicis from an unidentified fern. Croatia, Mollisia endogranulata on deteriorated hardwood. Czech Republic, Arcopilus navicularis from tea bag with fruit tea, Neosetophoma buxi as endophyte from Buxus sempervirens, Xerochrysium bohemicum on surface of biscuits with chocolate glaze and filled with jam. France, Entoloma cyaneobasale on basic to calcareous soil, Fusarium aconidiale from Triticum aestivum, Fusarium juglandicola from buds of Juglans regia. Germany, Tetraploa endophytica as endophyte from Microthlaspi perfoliatum roots. India, Castanediella ambae on leaves of Mangifera indica, Lactifluus kanadii on soil under Castanopsis sp., Penicillium uttarakhandense from soil. Italy, Penicillium ferraniaense from compost. Namibia, Bezerromyces gobabebensis on leaves of unidentified succulent, Cladosporium stipagrostidicola on leaves of Stipagrostis sp., Cymostachys euphorbiae on leaves of Euphorbia sp., Deniquelata hypolithi from hypolith under a rock, Hysterobrevium walvisbayicola on leaves of unidentified tree, Knufia hypolithi and Knufia walvisbayicola from hypolith under a rock, Lapidomyces stipagrostidicola on leaves of Stipagrostis sp., Nothophaeotheca mirabibensis (incl. Nothophaeotheca gen. nov.) on persistent inflorescence remains of Blepharis obmitrata, Paramyrothecium salvadorae on twigs of Salvadora persica, Preussia procaviicola on dung of Procavia sp., Sordaria equicola on zebra dung, Volutella salvadorae on stems of Salvadora persica. Netherlands, Entoloma ammophilum on sandy soil, Entoloma pseudocruentatum on nutrient poor (acid) soil, Entoloma pudens on plant debris, amongst grasses. New Zealand, Amorocoelophoma neoregeliae from leaf spots of Neoregelia sp., Aquilomyces metrosideri and Septoriella callistemonis from stem discolouration and leaf spots of Metrosideros sp., Cadophora neoregeliae from leaf spots of Neoregelia sp., Flexuomyces asteliae (incl. Flexuomyces gen. nov.) and Mollisia asteliae from leaf spots of Astelia chathamica, Ophioceras freycinetiae from leaf spots of Freycinetia banksii, Phaeosphaeria caricis-sectae from leaf spots of Carex secta. Norway, Cuphophyllus flavipesoides on soil in semi-natural grassland, Entoloma coracis on soil in calcareous Pinus and Tilia forests, Entoloma cyaneolilacinum on soil semi-natural grasslands, Inocybe norvegica on gravelly soil. Pakistan, Butyriboletus parachinarensis on soil in association with Quercus baloot. Poland, Hyalodendriella bialowiezensis on debris beneath fallen bark of Norway spruce Picea abies. Russia, Bolbitius sibiricus on а moss covered rotting trunk of Populus tremula, Crepidotus wasseri on debris of Populus tremula, Entoloma isborscanum on soil on calcareous grasslands, Entoloma subcoracis on soil in subalpine grasslands, Hydropus lecythiocystis on rotted wood of Betula pendula, Meruliopsis faginea on fallen dead branches of Fagus orientalis, Metschnikowia taurica from fruits of Ziziphus jujube, Suillus praetermissus on soil, Teunia lichenophila as endophyte from Cladonia rangiferina. Slovakia, Hygrocybe fulgens on mowed grassland, Pleuroflammula pannonica from corticated branches of Quercus sp. South Africa, Acrodontium burrowsianum on leaves of unidentified Poaceae, Castanediella senegaliae on dead pods of Senegalia ataxacantha, Cladophialophora behniae on leaves of Behnia sp., Colletotrichum cliviigenum on leaves of Clivia sp., Diatrype dalbergiae on bark of Dalbergia armata, Falcocladium heteropyxidicola on leaves of Heteropyxis canescens, Lapidomyces aloidendricola as epiphyte on brown stem of Aloidendron dichotomum, Lasionectria sansevieriae and Phaeosphaeriopsis sansevieriae on leaves of Sansevieria hyacinthoides, Lylea dalbergiae on Diatrype dalbergiae on bark of Dalbergia armata, Neochaetothyrina syzygii (incl. Neochaetothyrina gen. nov.) on leaves of Syzygium chordatum, Nothophaeomoniella ekebergiae (incl. Nothophaeomoniella gen. nov.) on leaves of Ekebergia pterophylla, Paracymostachys euphorbiae (incl. Paracymostachys gen. nov.) on leaf litter of Euphorbia ingens, Paramycosphaerella pterocarpi on leaves of Pterocarpus angolensis, Paramycosphaerella syzygii on leaf litter of Syzygium chordatum, Parateichospora phoenicicola (incl. Parateichospora gen. nov.) on leaves of Phoenix reclinata, Seiridium syzygii on twigs of Syzygium chordatum, Setophoma syzygii on leaves of Syzygium sp., Starmerella xylocopis from larval feed of an Afrotropical bee Xylocopa caffra, Teratosphaeria combreti on leaf litter of Combretum kraussii, Teratosphaericola leucadendri on leaves of Leucadendron sp., Toxicocladosporium pterocarpi on pods of Pterocarpus angolensis. Spain, Cortinarius bonachei with Quercus ilex in calcareus soils, Cortinarius brunneovolvatus under Quercus ilex subsp. ballota in calcareous soil, Extremopsis radicicola (incl. Extremopsis gen. nov.) from root-associated soil in a wet heathland, Russula quintanensis on acidic soils, Tubaria vulcanica on volcanic lapilii material, Tuber zambonelliae in calcareus soil. Sweden, Elaphomyces borealis on soil under Pinus sylvestris and Betula pubescens. Tanzania, Curvularia tanzanica on inflorescence of Cyperus aromaticus. Thailand, Simplicillium niveum on Ophiocordyceps camponoti-leonardi on underside of unidentified dicotyledonous leaf. USA, Calonectria californiensis on leaves of Umbellularia californica, Exophiala spartinae from surface sterilised roots of Spartina alterniflora, Neophaeococcomyces oklahomaensis from outside wall of alcohol distillery. Vietnam, Fistulinella aurantioflava on soil. Morphological and culture characteristics are supported by DNA barcodes.http://www.ingentaconnect.com/content/nhn/pimjBiochemistryForestry and Agricultural Biotechnology Institute (FABI)GeneticsMicrobiology and Plant PathologyPlant Production and Soil Scienc

Global age-sex-specific fertility, mortality, healthy life expectancy (HALE), and population estimates in 204 countries and territories, 1950–2019: a comprehensive demographic analysis for the Global Burden of Disease Study 2019

Background: Accurate and up-to-date assessment of demographic metrics is crucial for understanding a wide range of social, economic, and public health issues that affect populations worldwide. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 produced updated and comprehensive demographic assessments of the key indicators of fertility, mortality, migration, and population for 204 countries and territories and selected subnational locations from 1950 to 2019. Methods: 8078 country-years of vital registration and sample registration data, 938 surveys, 349 censuses, and 238 other sources were identified and used to estimate age-specific fertility. Spatiotemporal Gaussian process regression (ST-GPR) was used to generate age-specific fertility rates for 5-year age groups between ages 15 and 49 years. With extensions to age groups 10–14 and 50–54 years, the total fertility rate (TFR) was then aggregated using the estimated age-specific fertility between ages 10 and 54 years. 7417 sources were used for under-5 mortality estimation and 7355 for adult mortality. ST-GPR was used to synthesise data sources after correction for known biases. Adult mortality was measured as the probability of death between ages 15 and 60 years based on vital registration, sample registration, and sibling histories, and was also estimated using ST-GPR. HIV-free life tables were then estimated using estimates of under-5 and adult mortality rates using a relational model life table system created for GBD, which closely tracks observed age-specific mortality rates from complete vital registration when available. Independent estimates of HIV-specific mortality generated by an epidemiological analysis of HIV prevalence surveys and antenatal clinic serosurveillance and other sources were incorporated into the estimates in countries with large epidemics. Annual and single-year age estimates of net migration and population for each country and territory were generated using a Bayesian hierarchical cohort component model that analysed estimated age-specific fertility and mortality rates along with 1250 censuses and 747 population registry years. We classified location-years into seven categories on the basis of the natural rate of increase in population (calculated by subtracting the crude death rate from the crude birth rate) and the net migration rate. We computed healthy life expectancy (HALE) using years lived with disability (YLDs) per capita, life tables, and standard demographic methods. Uncertainty was propagated throughout the demographic estimation process, including fertility, mortality, and population, with 1000 draw-level estimates produced for each metric. Findings: The global TFR decreased from 2•72 (95% uncertainty interval [UI] 2•66–2•79) in 2000 to 2•31 (2•17–2•46) in 2019. Global annual livebirths increased from 134•5 million (131•5–137•8) in 2000 to a peak of 139•6 million (133•0–146•9) in 2016. Global livebirths then declined to 135•3 million (127•2–144•1) in 2019. Of the 204 countries and territories included in this study, in 2019, 102 had a TFR lower than 2•1, which is considered a good approximation of replacement-level fertility. All countries in sub-Saharan Africa had TFRs above replacement level in 2019 and accounted for 27•1% (95% UI 26•4–27•8) of global livebirths. Global life expectancy at birth increased from 67•2 years (95% UI 66•8–67•6) in 2000 to 73•5 years (72•8–74•3) in 2019. The total number of deaths increased from 50•7 million (49•5–51•9) in 2000 to 56•5 million (53•7–59•2) in 2019. Under-5 deaths declined from 9•6 million (9•1–10•3) in 2000 to 5•0 million (4•3–6•0) in 2019. Global population increased by 25•7%, from 6•2 billion (6•0–6•3) in 2000 to 7•7 billion (7•5–8•0) in 2019. In 2019, 34 countries had negative natural rates of increase; in 17 of these, the population declined because immigration was not sufficient to counteract the negative rate of decline. Globally, HALE increased from 58•6 years (56•1–60•8) in 2000 to 63•5 years (60•8–66•1) in 2019. HALE increased in 202 of 204 countries and territories between 2000 and 2019. Interpretation: Over the past 20 years, fertility rates have been dropping steadily and life expectancy has been increasing, with few exceptions. Much of this change follows historical patterns linking social and economic determinants, such as those captured by the GBD Socio-demographic Index, with demographic outcomes. More recently, several countries have experienced a combination of low fertility and stagnating improvement in mortality rates, pushing more populations into the late stages of the demographic transition. Tracking demographic change and the emergence of new patterns will be essential for global health monitoring. Funding: Bill & Melinda Gates Foundation. © 2020 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 licens

Global burden of 87 risk factors in 204 countries and territories, 1990�2019: a systematic analysis for the Global Burden of Disease Study 2019

Background: Rigorous analysis of levels and trends in exposure to leading risk factors and quantification of their effect on human health are important to identify where public health is making progress and in which cases current efforts are inadequate. The Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019 provides a standardised and comprehensive assessment of the magnitude of risk factor exposure, relative risk, and attributable burden of disease. Methods: GBD 2019 estimated attributable mortality, years of life lost (YLLs), years of life lived with disability (YLDs), and disability-adjusted life-years (DALYs) for 87 risk factors and combinations of risk factors, at the global level, regionally, and for 204 countries and territories. GBD uses a hierarchical list of risk factors so that specific risk factors (eg, sodium intake), and related aggregates (eg, diet quality), are both evaluated. This method has six analytical steps. (1) We included 560 risk�outcome pairs that met criteria for convincing or probable evidence on the basis of research studies. 12 risk�outcome pairs included in GBD 2017 no longer met inclusion criteria and 47 risk�outcome pairs for risks already included in GBD 2017 were added based on new evidence. (2) Relative risks were estimated as a function of exposure based on published systematic reviews, 81 systematic reviews done for GBD 2019, and meta-regression. (3) Levels of exposure in each age-sex-location-year included in the study were estimated based on all available data sources using spatiotemporal Gaussian process regression, DisMod-MR 2.1, a Bayesian meta-regression method, or alternative methods. (4) We determined, from published trials or cohort studies, the level of exposure associated with minimum risk, called the theoretical minimum risk exposure level. (5) Attributable deaths, YLLs, YLDs, and DALYs were computed by multiplying population attributable fractions (PAFs) by the relevant outcome quantity for each age-sex-location-year. (6) PAFs and attributable burden for combinations of risk factors were estimated taking into account mediation of different risk factors through other risk factors. Across all six analytical steps, 30 652 distinct data sources were used in the analysis. Uncertainty in each step of the analysis was propagated into the final estimates of attributable burden. Exposure levels for dichotomous, polytomous, and continuous risk factors were summarised with use of the summary exposure value to facilitate comparisons over time, across location, and across risks. Because the entire time series from 1990 to 2019 has been re-estimated with use of consistent data and methods, these results supersede previously published GBD estimates of attributable burden. Findings: The largest declines in risk exposure from 2010 to 2019 were among a set of risks that are strongly linked to social and economic development, including household air pollution; unsafe water, sanitation, and handwashing; and child growth failure. Global declines also occurred for tobacco smoking and lead exposure. The largest increases in risk exposure were for ambient particulate matter pollution, drug use, high fasting plasma glucose, and high body-mass index. In 2019, the leading Level 2 risk factor globally for attributable deaths was high systolic blood pressure, which accounted for 10·8 million (95 uncertainty interval UI 9·51�12·1) deaths (19·2% 16·9�21·3 of all deaths in 2019), followed by tobacco (smoked, second-hand, and chewing), which accounted for 8·71 million (8·12�9·31) deaths (15·4% 14·6�16·2 of all deaths in 2019). The leading Level 2 risk factor for attributable DALYs globally in 2019 was child and maternal malnutrition, which largely affects health in the youngest age groups and accounted for 295 million (253�350) DALYs (11·6% 10·3�13·1 of all global DALYs that year). The risk factor burden varied considerably in 2019 between age groups and locations. Among children aged 0�9 years, the three leading detailed risk factors for attributable DALYs were all related to malnutrition. Iron deficiency was the leading risk factor for those aged 10�24 years, alcohol use for those aged 25�49 years, and high systolic blood pressure for those aged 50�74 years and 75 years and older. Interpretation: Overall, the record for reducing exposure to harmful risks over the past three decades is poor. Success with reducing smoking and lead exposure through regulatory policy might point the way for a stronger role for public policy on other risks in addition to continued efforts to provide information on risk factor harm to the general public. Funding: Bill & Melinda Gates Foundation. © 2020 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY 4.0 licens