Institution
University of São Paulo
Education•São Paulo, Brazil•
About: University of São Paulo is a education organization based out in São Paulo, Brazil. It is known for research contribution in the topics: Population & Health care. The organization has 136513 authors who have published 272320 publications receiving 5127869 citations. The organization is also known as: USP & Universidade de São Paulo.
Topics: Population, Health care, Transplantation, Immune system, Poison control
Papers published on a yearly basis
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Theo Vos1, Amanuel Alemu Abajobir, Kalkidan Hassen Abate2, Cristiana Abbafati3 +775 more•Institutions (305)
TL;DR: The Global Burden of Diseases, Injuries, and Risk Factors Study 2016 (GBD 2016) provides a comprehensive assessment of prevalence, incidence, and years lived with disability (YLDs) for 328 causes in 195 countries and territories from 1990 to 2016.
10,401 citations
University of Barcelona1, University of Pisa2, University of Duisburg-Essen3, Auckland City Hospital4, University of São Paulo5, European University6, Icahn School of Medicine at Mount Sinai7, Goethe University Frankfurt8, University of Bologna9, Hannover Medical School10, University of Mainz11, Aix-Marseille University12, Université catholique de Louvain13, University of Düsseldorf14, Bayer15, Bayer Corporation16
TL;DR: In patients with advanced hepatocellular carcinoma, median survival and the time to radiologic progression were nearly 3 months longer for patients treated with sorafenib than for those given placebo.
Abstract: Background No effective systemic therapy exists for patients with advanced hepatocellular carcinoma. A preliminary study suggested that sorafenib, an oral multikinase inhibitor of the vascular endothelial growth factor receptor, the platelet-derived growth factor receptor, and Raf may be effective in hepatocellular carcinoma. Methods In this multicenter, phase 3, double-blind, placebo-controlled trial, we randomly assigned 602 patients with advanced hepatocellular carcinoma who had not received previous systemic treatment to receive either sorafenib (at a dose of 400 mg twice daily) or placebo. Primary outcomes were overall survival and the time to symptomatic progression. Secondary outcomes included the time to radiologic progression and safety. Results At the second planned interim analysis, 321 deaths had occurred, and the study was stopped. Median overall survival was 10.7 months in the sorafenib group and 7.9 months in the placebo group (hazard ratio in the sorafenib group, 0.69; 95% confidence interval, 0.55 to 0.87; P<0.001). There was no significant difference between the two groups in the median time to symptomatic progression (4.1 months vs. 4.9 months, respectively, P=0.77). The median time to radiologic progression was 5.5 months in the sorafenib group and 2.8 months in the placebo group (P<0.001). Seven patients in the sorafenib group (2%) and two patients in the placebo group (1%) had a partial response; no patients had a complete response. Diarrhea, weight loss, hand-foot skin reaction, and hypophosphatemia were more frequent in the sorafenib group. Conclusions In patients with advanced hepatocellular carcinoma, median survival and the time to radiologic progression were nearly 3 months longer for patients treated with sorafenib than for those given placebo.
10,074 citations
TL;DR: In this article, a search for the Standard Model Higgs boson in proton-proton collisions with the ATLAS detector at the LHC is presented, which has a significance of 5.9 standard deviations, corresponding to a background fluctuation probability of 1.7×10−9.
9,282 citations
University of Washington1, Sapienza University of Rome2, Mekelle University3, University of Texas at San Antonio4, King Saud bin Abdulaziz University for Health Sciences5, Debre markos University6, Emory University7, University of Oxford8, University of Cartagena9, United Nations Population Fund10, University of Birmingham11, Stanford University12, Aga Khan University13, University of Melbourne14, National Taiwan University15, University of Cambridge16, University of California, San Diego17, Public Health Foundation of India18, Public Health England19, University of Peradeniya20, Harvard University21, National Institutes of Health22, Tehran University of Medical Sciences23, Auckland University of Technology24, University of Sheffield25, University of Western Australia26, Karolinska Institutet27, Birzeit University28, Brandeis University29, American Cancer Society30, Ochsner Medical Center31, Yonsei University32, University of Bristol33, Heidelberg University34, Vanderbilt University35, South African Medical Research Council36, Jordan University of Science and Technology37, New Generation University College38, Northeastern University39, Simmons College40, Norwegian Institute of Public Health41, Boston University42, Chinese Center for Disease Control and Prevention43, University of Bari44, University of São Paulo45, University of Otago46, University of Crete47, International Centre for Diarrhoeal Disease Research, Bangladesh48, Fred Hutchinson Cancer Research Center49, Teikyo University50, Bhabha Atomic Research Centre51, University of Tokyo52, Finnish Institute of Occupational Health53, Heriot-Watt University54, University of Alabama at Birmingham55, Griffith University56, National Center for Disease Control and Public Health57, University of California, Irvine58, Johns Hopkins University59, New York University60, University of Queensland61, Universidade Federal de Minas Gerais62, National Research University – Higher School of Economics63, University of Bergen64, Columbia University65, Shandong University66, University of North Carolina at Chapel Hill67, Fujita Health University68, Korea University69, Chongqing Medical University70, Zhejiang University71
TL;DR: The global, regional, and national prevalence of overweight and obesity in children and adults during 1980-2013 is estimated using a spatiotemporal Gaussian process regression model to estimate prevalence with 95% uncertainty intervals (UIs).
9,180 citations
University of Melbourne1, Stony Brook University2, City University of New York3, Princeton University4, University of Lausanne5, University of California, Berkeley6, University of Alaska Fairbanks7, National Institute of Water and Atmospheric Research8, Commonwealth Scientific and Industrial Research Organisation9, University of São Paulo10, University of Missouri11, Consejo Nacional de Ciencia y Tecnología12, University of Kansas13, Landcare Research14, AT&T15, McGill University16, James Cook University17, Swiss Federal Institute for Forest, Snow and Landscape Research18
TL;DR: This work compared 16 modelling methods over 226 species from 6 regions of the world, creating the most comprehensive set of model comparisons to date and found that presence-only data were effective for modelling species' distributions for many species and regions.
Abstract: Prediction of species' distributions is central to diverse applications in ecology, evolution and conservation science. There is increasing electronic access to vast sets of occurrence records in museums and herbaria, yet little effective guidance on how best to use this information in the context of numerous approaches for modelling distributions. To meet this need, we compared 16 modelling methods over 226 species from 6 regions of the world, creating the most comprehensive set of model comparisons to date. We used presence-only data to fit models, and independent presence-absence data to evaluate the predictions. Along with well-established modelling methods such as generalised additive models and GARP and BIOCLIM, we explored methods that either have been developed recently or have rarely been applied to modelling species' distributions. These include machine-learning methods and community models, both of which have features that may make them particularly well suited to noisy or sparse information, as is typical of species' occurrence data. Presence-only data were effective for modelling species' distributions for many species and regions. The novel methods consistently outperformed more established methods. The results of our analysis are promising for the use of data from museums and herbaria, especially as methods suited to the noise inherent in such data improve.
7,589 citations
Authors
Showing all 138091 results
| Name | H-index | Papers | Citations |
|---|---|---|---|
| Anthony A. Grace | 102 | 352 | 41469 |
| José A. Teixeira | 101 | 1414 | 47329 |
| Carlos A. Peres | 101 | 434 | 33582 |
| Oliver G. Pybus | 100 | 447 | 45313 |
| José N. Onuchic | 99 | 426 | 38621 |
| Steven D. Wexner | 98 | 785 | 37856 |
| Dante Minniti | 98 | 813 | 37860 |
| Ryan White | 97 | 462 | 35782 |
| Jay L. Zweier | 96 | 523 | 41225 |
| José M. C. Ribeiro | 95 | 489 | 33417 |
| Muhammad Imran | 94 | 3053 | 51728 |
| Alvaro Avezum | 93 | 279 | 48888 |
| Paolo Pelosi | 93 | 852 | 37918 |
| Christian Mueller | 92 | 673 | 52585 |
| David M. Glover | 92 | 301 | 24620 |