Outbreak of Tinea capitis by Trichophyton tonsurans and Microsporum canis in Niterói, RJ, Brazil

18 girls from an orphanage (Orfanato Santo Antônio) in Niterói presented tinea capitis due to Trichophyton tonsurans (15 cases - 83.3%) and Microsporum canis (3 cases - 26.7%). Comments are made about clinical, mycological and therapeutic aspects of this microepidem

Fungal Planet description sheets : 320–370

Novel species of fungi described in the present study include the following from Malaysia: Castanediella eucalypti from Eucalyptus pellita, Codinaea acacia from Acacia mangium, Emarcea eucalyptigena from Eucalyptus brassiana, Myrtapenidiella eucalyptorum from Eucalyptus pellita, Pilidiella eucalyptigena from Eucalyptus brassiana and Strelitziana malaysiana from Acacia mangium. Furthermore, Stachybotrys sansevieriicola is described from Sansevieria ehrenbergii (Tanzania), Phacidium grevilleae from Grevillea robusta (Uganda), Graphium jumulu from Adansonia gregorii and Ophiostoma eucalyptigena from Eucalyptus marginata (Australia), Pleurophoma ossicola from bone and Plectosphaerella populi from Populus nigra (Germany), Colletotrichum neosansevieriae from Sansevieria trifasciata, Elsinoë othonnae from Othonna quinquedentata and Zeloasperisporium cliviae (Zeloasperisporiaceae fam. nov.) from Clivia sp. (South Africa), Neodevriesia pakbiae, Phaeophleospora hymenocallidis and Phaeophleospora hymenocallidicola on leaves of a fern (Thailand), Melanconium elaeidicola from Elaeis guineensis (Indonesia), Hormonema viticola from Vitis vinifera (Canary Islands), Chlorophyllum pseudoglobossum from a grassland (India), Triadelphia disseminata from an immunocompromised patient (Saudi Arabia), Colletotrichum abscissum from Citrus (Brazil), Polyschema sclerotigenum and Phialemonium limoniforme from human patients (USA), Cadophora vitícola from Vitis vinifera (Spain), Entoloma flavovelutinum and Bolbitius aurantiorugosus from soil (Vietnam), Rhizopogon granuloflavus from soil (Cape Verde Islands), Tulasnella eremophila from Euphorbia officinarum subsp. echinus (Morocco), Verrucostoma martinicensis from Danaea elliptica (French West Indies), Metschnikowia colchici from Colchicum autumnale (Bulgaria), Thelebolus microcarpus from soil (Argentina) and Ceratocystis adelpha from Theobroma cacao (Ecuador). Myrmecridium iridis (Myrmecridiales ord. nov., Myrmecridiaceae fam. nov.) is also described from Iris sp. (The Netherlands). Novel genera include (Ascomycetes): Budhanggurabania from Cynodon dactylon (Australia), Soloacrosporiella, Xenocamarosporium, Neostrelitziana and Castanediella from Acacia mangium and Sabahriopsis from Eucalyptus brassiana (Malaysia), Readerielliopsis from basidiomata of Fuscoporia wahlbergii (French Guyana), Neoplatysporoides from Aloe ferox (Tanzania), Wojnowiciella, Chrysofolia and Neoeriomycopsis from Eucalyptus (Colombia), Neophaeomoniella from Eucalyptus globulus (USA), Pseudophaeomoniella from Olea europaea (Italy), Paraphaeomoniella from Encephalartos altensteinii, Aequabiliella, Celerioriella and Minutiella from Prunus (South Africa). Tephrocybella (Basidiomycetes) represents a novel genus from wood (Italy). Morphological and culture characteristics along with ITS DNA barcodes are provided for all taxa.Alina V. Alexandrova was supported by the Russian Science Foundation (project N 14-50-00029). Ekaterina F. Malysheva, Olga V. Morozova, Alexander E. Kovalenko and Eugene S. Popov acknowledge financial support from the Russian Foundation for Basic Research (project 13-04-00838a and 15-04-04645a). Margarita Dueñas, María P. Martín and M. Teresa Telleria acknowledge financial support from the Plan Nacional I+D+I projects No. CGL2009-07231 and CGL2012-3559. Cony Decock gratefully acknowledges the financial support received from the FNRS / FRFC (convention FRFC 2.4544.10), the CNRS-French Guiana and the Nouragues staff, which enabled fieldwork in French Guiana, and the Belgian State – Belgian Federal Science Policy through the BCCMTM research programme.http://www.ingentaconnect.com/content/nhn/pimjam201

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

Search for the Zγ decay mode of new high-mass resonances in pp collisions at √s = 13 TeV with the ATLAS detector

This letter presents a search for narrow, high-mass resonances in the Zγ final state with the Z boson decaying into a pair of electrons or muons. The √s = 13 TeV pp collision data were recorded by the ATLAS detector at the CERN Large Hadron Collider and have an integrated luminosity of 140 fb−1. The data are found to be in agreement with the Standard Model background expectation. Upper limits are set on the resonance production cross section times the decay branching ratio into Zγ. For spin-0 resonances produced via gluon–gluon fusion, the observed limits at 95% confidence level vary between 65.5 fb and 0.6 fb, while for spin-2 resonances produced via gluon–gluon fusion (or quark–antiquark initial states) limits vary between 77.4 (76.1) fb and 0.6 (0.5) fb, for the mass range from 220 GeV to 3400 GeV

Search for single production of vector-like T quarks decaying into Ht or Zt in pp collisions at s√ = 13 TeV with the ATLAS detector

This paper describes a search for the single production of an up-type vector-like quark (T) decaying as T → Ht or T → Zt. The search utilises a dataset of pp collisions at s√ = 13 TeV collected with the ATLAS detector during the 2015–2018 data-taking period of the Large Hadron Collider, corresponding to an integrated luminosity of 139 fb−1. Data are analysed in final states containing a single lepton with multiple jets and b-jets. The presence of boosted heavy resonances in the event is exploited to discriminate the signal from the Standard Model background. No significant excess above the Standard Model expectation is observed, and 95% CL upper limits are set on the production cross section of T quarks in different decay channels. The results are interpreted in several benchmark scenarios to set limits on the mass and universal coupling strength (κ) of the vector-like quark. For singlet T quarks, κ values above 0.53 are excluded for all masses below 2.3 TeV. At a mass of 1.6 TeV, κ values as low as 0.35 are excluded. For T quarks in the doublet scenario, where the production cross section is much lower, κ values above 0.72 are excluded for all masses below 1.7 TeV, and this exclusion is extended to κ above 0.55 for low masses around 1.0 TeV