| 1. |
- Crous, P. W., et al.
(författare)
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Fungal Planet description sheets : 951-1041
- 2019
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Ingår i: Persoonia. - : RIJKSHERBARIUM. - 0031-5850 .- 1878-9080. ; 43, s. 223-425
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Tidskriftsartikel (refereegranskat)abstract
- Novel species of fungi described in this study include those from various countries as follows: Antarctica,Apenidiella antarctica from permafrost, Cladosporium fildesense from an unidentified marine sponge. Argentina,Geastrum wrightii on humus in mixed forest. Australia, Golovinomyces glandulariae on Glandularia aristigera,Neoanungitea eucalyptorum on leaves of Eucalyptus grandis, Teratosphaeria corymbiicola on leaves of Corymbiaficifolia, Xylaria eucalypti on leaves of Eucalyptus radiata. Brazil, Bovista psammophila on soil, Fusarium awaxy onrotten stalks of Zea mays, Geastrum lanuginosum on leaf litter covered soil, Hermetothecium mikaniae-micranthae(incl. Hermetothecium gen. nov.) on Mikania micrantha, Penicillium reconvexovelosoi in soil, Stagonosporopsis vannacciifrom pod of Glycine max. British Virgin Isles, Lactifluus guanensis on soil. Canada, Sorocybe oblongisporaon resin of Picea rubens. Chile, Colletotrichum roseum on leaves of Lapageria rosea. China, Setophoma cavernafrom carbonatite in Karst cave. Colombia, Lareunionomyces eucalypticola on leaves of Eucalyptus grandis. CostaRica, Psathyrella pivae on wood. Cyprus, Clavulina iris on calcareous substrate. France, Chromosera ambiguaand Clavulina iris var. occidentalis on soil. French West Indies, Helminthosphaeria hispidissima on dead wood.Guatemala, Talaromyces guatemalensis in soil. Malaysia, Neotracylla pini (incl. Tracyllales ord. nov. and Neotracyllagen. nov.) and Vermiculariopsiella pini on needles of Pinus tecunumanii. New Zealand, Neoconiothyriumviticola on stems of Vitis vinifera, Parafenestella pittospori on Pittosporum tenuifolium, Pilidium novae-zelandiaeon Phoenix sp. Pakistan, Russula quercus-floribundae on forest floor. Portugal, Trichoderma aestuarinum fromsaline water. Russia, Pluteus liliputianus on fallen branch of deciduous tree, Pluteus spurius on decaying deciduous wood or soil. South Africa, Alloconiothyrium encephalarti, Phyllosticta encephalarticola and Neothyrostromaencephalarti (incl. Neothyrostroma gen. nov.) on leaves of Encephalartos sp., Chalara eucalypticola on leaf spots ofEucalyptus grandis x urophylla, Clypeosphaeria oleae on leaves of Olea capensis, Cylindrocladiella postalofficiumon leaf litter of Sideroxylon inerme, Cylindromonium eugeniicola (incl. Cylindromonium gen. nov.) on leaf litter ofEugenia capensis, Cyphellophora goniomatis on leaves of Gonioma kamassi, Nothodactylaria nephrolepidis (incl.Nothodactylaria gen. nov. and Nothodactylariaceae fam. nov.) on leaves of Nephrolepis exaltata, Falcocladiumeucalypti and Gyrothrix eucalypti on leaves of Eucalyptus sp., Gyrothrix oleae on leaves of Olea capensis subsp.macrocarpa, Harzia metro-sideri on leaf litter of Metrosideros sp., Hippopotamyces phragmitis (incl. Hippopotamycesgen. nov.) on leaves of Phragmites australis, Lectera philenopterae on Philenoptera violacea, Leptosilliamayteni on leaves of Maytenus heterophylla, Lithohypha aloicola and Neoplatysporoides aloes on leaves of Aloesp., Millesimomyces rhoicissi (incl. Millesimomyces gen. nov.) on leaves of Rhoicissus digitata, Neodevriesiastrelitziicola on leaf litter of Strelitzia nicolai, Neokirramyces syzygii (incl. Neokirramyces gen. nov.) on leaf spots of Syzygium sp., Nothoramichloridium perseae (incl. Nothoramichloridium gen. nov. and Anungitiomycetaceae fam.nov.) on leaves of Persea americana, Paramycosphaerella watsoniae on leaf spots of Watsonia sp., Penicilliumcuddlyae from dog food, Podocarpomyces knysnanus (incl. Podocarpomyces gen. nov.) on leaves of Podocarpusfalcatus, Pseudocercospora heteropyxidicola on leaf spots of Heteropyxis natalensis, Pseudopenidiella podocarpi,Scolecobasidium podocarpi and Ceramothyrium podocarpicola on leaves of Podocarpus latifolius, Scolecobasidiumblechni on leaves of Blechnum capense, Stomiopeltis syzygii on leaves of Syzygium chordatum, Strelitziomycesknysnanus (incl. Strelitziomyces gen. nov.) on leaves of Strelitzia alba, Talaromyces clemensii from rotting wood ingoldmine, Verrucocladosporium visseri on Carpobrotus edulis. Spain, Boletopsis mediterraneensis on soil, Calycinacortegadensisi on a living twig of Castanea sativa, Emmonsiellopsis tuberculata in fluvial sediments, Mollisia cortegadensison dead attached twig of Quercus robur, Psathyrella ovispora on soil, Pseudobeltrania lauri on leaf litterof Laurus azorica, Terfezia dunensis in soil, Tuber lucentum in soil, Venturia submersa on submerged plant debris.Thailand, Cordyceps jakajanicola on cicada nymph, Cordyceps kuiburiensis on spider, Distoseptispora caricis onleaves of Carex sp., Ophiocordyceps khonkaenensis on cicada nymph. USA, Cytosporella juncicola and Davidiellomycesjuncicola on culms of Juncus effusus, Monochaetia massachusettsianum from air sample, Neohelicomycesmelaleucae and Periconia neobrittanica on leaves of Melaleuca styphelioides x lanceolata, Pseudocamarosporiumeucalypti on leaves of Eucalyptus sp., Pseudogymnoascus lindneri from sediment in a mine, Pseudogymnoascusturneri from sediment in a railroad tunnel, Pulchroboletus sclerotiorum on soil, Zygosporium pseudomasonii onleaf of Serenoa repens. Vietnam, Boletus candidissimus and Veloporphyrellus vulpinus on soil. Morphological andculture characteristics are supported by DNA barcodes.
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| 2. |
- De Costa, A., et al.
(författare)
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Study protocol for WHO and UNICEF estimates of global, regional, and national preterm birth rates for 2010 to 2019
- 2021
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Ingår i: PLoS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 16:10
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Tidskriftsartikel (refereegranskat)abstract
- Background Preterm birth is a leading cause of death among children under five years. Previous estimates indicated global preterm birth rate of 10.6% (14.8 million neonates) in 2014. We aim to update preterm birth estimates at global, regional, and national levels for the period 2010 to 2019. Methods Preterm birth is defined as a live birth occurring before 37 completed gestational weeks, or <259 days since a woman's last menstrual period. National administrative data sources for WHO Member States with facility birth rates of >= 80% in the most recent year for which data is available will be searched. Administrative data identified for these countries will be considered if >= 80% of UN estimated live births include gestational age information to define preterm birth. For countries without eligible administrative data, a systematic review of studies will be conducted. Research studies will be eligible if the reported outcome is derived from an observational or intervention study conducted at national or sub-national level in population- or facility-based settings. Risk of bias assessments will focus on gestational age measurement method and coverage, and inclusion of special subgroups in published estimates. Covariates for inclusion will be selected a priori based on a conceptual framework of plausible associations with preterm birth, data availability, and quality of covariate data across many countries and years. Global, regional and national preterm birth rates will be estimated using a Bayesian multilevel-mixed regression model. Discussion Accurate measurement of preterm birth is challenging in many countries given incomplete or unavailable data from national administrative sources, compounded by limited gestational age assessment during pregnancy to define preterm birth. Up-to-date modelled estimates will be an important resource to measure the global burden of preterm birth and to inform policies and programs especially in settings with a high burden of neonatal mortality.
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| 4. |
- Ohuma, Eric O., et al.
(författare)
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National, regional, and global estimates of preterm birth in 2020, with trends from 2010 : a systematic analysis
- 2023
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Ingår i: The Lancet. - : Elsevier. - 0140-6736 .- 1474-547X. ; 402:10409, s. 1261-1271
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Tidskriftsartikel (refereegranskat)abstract
- BackgroundPreterm birth is the leading cause of neonatal mortality and is associated with long-term physical, neurodevelopmental, and socioeconomic effects. This study updated national preterm birth rates and trends, plus novel estimates by gestational age subgroups, to inform progress towards global health goals and targets, and aimed to update country, regional, and global estimates of preterm birth for 2020 in addition to trends between 2010 and 2020.MethodsWe systematically searched population-based, nationally representative data on preterm birth from Jan 1, 2010, to Dec 31, 2020 and study data (26 March–14 April, 2021) for countries and areas with no national-level data. The analysis included 679 data points (86% nationally representative administrative data [582 of 679 data points]) from 103 countries and areas (62% of countries and areas having nationally representative administrative data [64 of 103 data points]). A Bayesian hierarchical regression was used for estimating country-level preterm rates, which incoporated country-specific intercepts, low birthweight as a covariate, non-linear time trends, and bias adjustments based on a data quality categorisation, and other indicators such as method of gestational age estimation.FindingsAn estimated 13·4 million (95% credible interval [CrI] 12·3–15·2 million) newborn babies were born preterm (<37 weeks) in 2020 (9·9% of all births [95% CrI 9·1–11·2]) compared with 13·8 million (12·7–15·5 million) in 2010 (9·8% of all births [9·0–11·0]) worldwide. The global annual rate of reduction was estimated at –0·14% from 2010 to 2020. In total, 55·6% of total livebirths are in southern Asia (26·8% [36 099 000 of 134 767 000]) and sub-Saharan Africa (28·7% [38 819 300 of 134 767 000]), yet these two regions accounted for approximately 65% (8 692 000 of 13 376 200) of all preterm births globally in 2020. Of the 33 countries and areas in the highest data quality category, none were in southern Asia or sub-Saharan Africa compared with 94% (30 of 32 countries) in high-income countries and areas. Worldwide from 2010 to 2020, approximately 15% of all preterm births occurred at less than 32 weeks of gestation, requiring more neonatal care (<28 weeks: 4·2%, 95% CI 3·1–5·0, 567 800 [410 200–663 200 newborn babies]); 28–32 weeks: 10·4% [9·5–10·6], 1 392 500 [1 274 800–1 422 600 newborn babies]).InterpretationThere has been no measurable change in preterm birth rates over the last decade at global level. Despite increasing facility birth rates and substantial focus on routine health data systems, there remain many missed opportunities to improve preterm birth data. Gaps in national routine data for preterm birth are most marked in regions of southern Asia and sub-Saharan Africa, which also have the highest estimated burden of preterm births. Countries need to prioritise programmatic investments to prevent preterm birth and to ensure evidence-based quality care when preterm birth occurs. Investments in improving data quality are crucial so that preterm birth data can be improved and used for action and accountability processes.
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| 5. |
- Ohuma, Eric O., et al.
(författare)
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National, regional, and global estimates of preterm birth in 2020, with trends from 2010: a systematic analysis
- 2023
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Ingår i: The Lancet. - : Elsevier. - 0140-6736 .- 1474-547X. ; 402, s. 1261-1271
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Tidskriftsartikel (refereegranskat)abstract
- Background: Preterm birth is the leading cause of neonatal mortality and is associated with long-term physical, neurodevelopmental, and socioeconomic effects. This study updated national preterm birth rates and trends, plus novel estimates by gestational age subgroups, to inform progress towards global health goals and targets, and aimed to update country, regional, and global estimates of preterm birth for 2020 in addition to trends between 2010 and 2020. Methods: We systematically searched population-based, nationally representative data on preterm birth from Jan 1, 2010, to Dec 31, 2020 and study data (26 March–14 April, 2021) for countries and areas with no national-level data. The analysis included 679 data points (86% nationally representative administrative data [582 of 679 data points]) from 103 countries and areas (62% of countries and areas having nationally representative administrative data [64 of 103 data points]). A Bayesian hierarchical regression was used for estimating country-level preterm rates, which incoporated country-specific intercepts, low birthweight as a covariate, non-linear time trends, and bias adjustments based on a data quality categorisation, and other indicators such as method of gestational age estimation. Findings: An estimated 13·4 million (95% credible interval [CrI] 12·3–15·2 million) newborn babies were born preterm (<37 weeks) in 2020 (9·9% of all births [95% CrI 9·1–11·2]) compared with 13·8 million (12·7–15·5 million) in 2010 (9·8% of all births [9·0–11·0]) worldwide. The global annual rate of reduction was estimated at –0·14% from 2010 to 2020. In total, 55·6% of total livebirths are in southern Asia (26·8% [36 099 000 of 134 767 000]) and sub-Saharan Africa (28·7% [38 819 300 of 134 767 000]), yet these two regions accounted for approximately 65% (8 692 000 of 13 376 200) of all preterm births globally in 2020. Of the 33 countries and areas in the highest data quality category, none were in southern Asia or sub-Saharan Africa compared with 94% (30 of 32 countries) in high-income countries and areas. Worldwide from 2010 to 2020, approximately 15% of all preterm births occurred at less than 32 weeks of gestation, requiring more neonatal care (<28 weeks: 4·2%, 95% CI 3·1–5·0, 567 800 [410 200–663 200 newborn babies]); 28–32 weeks: 10·4% [9·5–10·6], 1 392 500 [1 274 800–1 422 600 newborn babies]). Interpretation: There has been no measurable change in preterm birth rates over the last decade at global level. Despite increasing facility birth rates and substantial focus on routine health data systems, there remain many missed opportunities to improve preterm birth data. Gaps in national routine data for preterm birth are most marked in regions of southern Asia and sub-Saharan Africa, which also have the highest estimated burden of preterm births. Countries need to prioritise programmatic investments to prevent preterm birth and to ensure evidence-based quality care when preterm birth occurs. Investments in improving data quality are crucial so that preterm birth data can be improved and used for action and accountability processes. Funding: The Children's Investment Fund Foundation and the UNDP, United Nations Population Fund-UNICEF-WHO-World Bank Special Programme of Research, Development and Research Training in Human Reproduction.
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