Institution
University of Lisbon
Education•Lisbon, Lisboa, Portugal•
About: University of Lisbon is a education organization based out in Lisbon, Lisboa, Portugal. It is known for research contribution in the topics: Population & European union. The organization has 19122 authors who have published 48503 publications receiving 1102623 citations. The organization is also known as: Universidade de Lisboa & Lisbon University.
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TL;DR: In this article, both resonant and nonresonant Higgs boson pair production were performed in the hh -> bb tau tau, gamma gamma WW* final states using 20.3 fb(-1) of collision data at a center-of-m...
Abstract: Searches for both resonant and nonresonant Higgs boson pair production are performed in the hh -> bb tau tau, gamma gamma WW* final states using 20.3 fb(-1) of pp collision data at a center-of-m ...
188 citations
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TL;DR: A distinct pattern of bile acids in the liver of patients with steatohepatitis is shown, which suggests an association of specific biles acids and disease progression, possibly through bile acid-induced liver injury.
Abstract: Background/aimsThe pathogenesis of steatohepatitis remains largely unknown; however, bile acids may play a role as potential mediators of liver damage. The aim of this study was to characterize bile acid profiles in liver tissue of patients with steatohepatitis.MethodsBile acid composition was deter
188 citations
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TL;DR: Current views on the origins of nuclear compartments and their roles in gene expression are discussed in this article.
188 citations
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University of Bern1, ETH Zurich2, Complutense University of Madrid3, University of Barcelona4, University of Almería5, University of Zaragoza6, University of Vigo7, Pablo de Olavide University8, Rovira i Virgili University9, University of Bonn10, Alfred Wegener Institute for Polar and Marine Research11, University of Bremen12, Augsburg College13, University of Würzburg14, Centre national de la recherche scientifique15, Çanakkale Onsekiz Mart University16, University of Lisbon17, University of Sunderland18, Met Office19, Pennsylvania State University20, University of Arizona21, Columbia University22, National Research Council23, ENEA24, University of Milan25, National and Kapodistrian University of Athens26, University of Padua27, University of Évora28, RWTH Aachen University29, St. Francis Xavier University30, University of Caen Lower Normandy31, Collège de France32
TL;DR: In this paper, a necessary task for assessing to which degree the industrial period is unusual against the background of pre-industrial climate variability is discussed, which is the reconstruction and interpretation of temporal and spatial patterns of climate in earlier centuries.
Abstract: Publisher Summary This chapter discusses a necessary task for assessing to which degree the industrial period is unusual against the background of pre-industrial climate variability. It is the reconstruction and interpretation of temporal and spatial patterns of climate in earlier centuries. There are distinct differences in the temporal resolution among the various proxies. Some of the proxy records are annually or even higher resolved and hence record year-by-year patterns of climate in past centuries. Several of the temperature reconstructions reveal that the late twentieth century warmth is unprecedented at hemispheric scales and is explained by anthropogenic, greenhouse gas (GHG) forcing. The chapter discusses the availability and potential of long, homogenized instrumental data, documentary, and natural proxies to reconstruct aspects of past climate at local- to regional-scales within the larger Mediterranean area, which includes climate extremes and the incidence of natural disasters. The chapter describes the role of external forcing, including natural and anthropogenic influences, and natural, internal variability in the coupled ocean–atmosphere system at subcontinental scale.
188 citations
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University of Oxford1, Institute for Health Metrics and Evaluation2, University of Melbourne3, Pasteur Institute4, Centre national de la recherche scientifique5, Harvard University6, Centers for Disease Control and Prevention7, Johns Hopkins University8, Robert Koch Institute9, University of Lisbon10, Instituto Superior de Ciências da Saúde Egas Moniz11, ETH Zurich12, University of California, San Francisco13, University Health Network14, St. Michael's Hospital15, University of Southampton16, University of KwaZulu-Natal17
TL;DR: The findings show the contributions of ecological and demographic factors to the ongoing spread of the yellow fever outbreak and provide estimates of the areas that could be prioritised for vaccination, although other constraints such as vaccine supply and delivery need to be accounted for before such insights can be translated into policy.
Abstract: Summary Background Since late 2015, an epidemic of yellow fever has caused more than 7334 suspected cases in Angola and the Democratic Republic of the Congo, including 393 deaths. We sought to understand the spatial spread of this outbreak to optimise the use of the limited available vaccine stock. Methods We jointly analysed datasets describing the epidemic of yellow fever, vector suitability, human demography, and mobility in central Africa to understand and predict the spread of yellow fever virus. We used a standard logistic model to infer the district-specific yellow fever virus infection risk during the course of the epidemic in the region. Findings The early spread of yellow fever virus was characterised by fast exponential growth (doubling time of 5–7 days) and fast spatial expansion (49 districts reported cases after only 3 months) from Luanda, the capital of Angola. Early invasion was positively correlated with high population density (Pearson's r 0·52, 95% CI 0·34–0·66). The further away locations were from Luanda, the later the date of invasion (Pearson's r 0·60, 95% CI 0·52–0·66). In a Cox model, we noted that districts with higher population densities also had higher risks of sustained transmission (the hazard ratio for cases ceasing was 0·74, 95% CI 0·13–0·92 per log-unit increase in the population size of a district). A model that captured human mobility and vector suitability successfully discriminated districts with high risk of invasion from others with a lower risk (area under the curve 0·94, 95% CI 0·92–0·97). If at the start of the epidemic, sufficient vaccines had been available to target 50 out of 313 districts in the area, our model would have correctly identified 27 (84%) of the 32 districts that were eventually affected. Interpretation Our findings show the contributions of ecological and demographic factors to the ongoing spread of the yellow fever outbreak and provide estimates of the areas that could be prioritised for vaccination, although other constraints such as vaccine supply and delivery need to be accounted for before such insights can be translated into policy. Funding Wellcome Trust.
188 citations
Authors
Showing all 19716 results
Name | H-index | Papers | Citations |
---|---|---|---|
Joao Seixas | 153 | 1538 | 115070 |
A. Gomes | 150 | 1862 | 113951 |
Marco Costa | 146 | 1458 | 105096 |
António Amorim | 136 | 1477 | 96519 |
Osamu Jinnouchi | 135 | 885 | 86104 |
P. Verdier | 133 | 1111 | 83862 |
Andy Haas | 132 | 1096 | 87742 |
Wendy Taylor | 131 | 1252 | 89457 |
Steve McMahon | 130 | 878 | 78763 |
Timothy Andeen | 129 | 1069 | 77593 |
Heather Gray | 129 | 966 | 80970 |
Filipe Veloso | 128 | 887 | 75496 |
Nuno Filipe Castro | 128 | 960 | 76945 |
Oliver Stelzer-Chilton | 128 | 1141 | 79154 |
Isabel Marian Trigger | 128 | 974 | 77594 |