Institution
University of Naples Federico II
Education•Naples, Campania, Italy•
About: University of Naples Federico II is a education organization based out in Naples, Campania, Italy. It is known for research contribution in the topics: Population & Cancer. The organization has 29291 authors who have published 68803 publications receiving 1920149 citations. The organization is also known as: Università degli Studi di Napoli Federico II & Naples University.
Topics: Population, Cancer, Large Hadron Collider, European Prospective Investigation into Cancer and Nutrition, Blood pressure
Papers published on a yearly basis
Papers
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University of Southampton1, University of Paris2, Nestlé3, French Institute of Health and Medical Research4, The Coca-Cola Company5, University of Naples Federico II6, University of Düsseldorf7, Spanish National Research Council8, University of Crete9, Kraft Foods10, Sapienza University of Rome11, Maastricht University12, University of Helsinki13, University of Graz14
TL;DR: Potential mechanisms are described and research gaps, which limit the understanding of the interaction between diet and postprandial and chronic low-grade inflammation, are identified.
Abstract: Low-grade inflammation is a characteristic of the obese state, and adipose tissue releases many inflammatory mediators. The source of these mediators within adipose tissue is not clear, but infiltrating macrophages seem to be especially important, although adipocytes themselves play a role. Obese people have higher circulating concentrations of many inflammatory markers than lean people do, and these are believed to play a role in causing insulin resistance and other metabolic disturbances. Blood concentrations of inflammatory markers are lowered following weight loss. In the hours following the consumption of a meal, there is an elevation in the concentrations of inflammatory mediators in the bloodstream, which is exaggerated in obese subjects and in type 2 diabetics. Both high-glucose and high-fat meals may induce postprandial inflammation, and this is exaggerated by a high meal content of advanced glycation end products (AGE) and partly ablated by inclusion of certain antioxidants or antioxidant-containing foods within the meal. Healthy eating patterns are associated with lower circulating concentrations of inflammatory markers. Among the components of a healthy diet, whole grains, vegetables and fruits, and fish are all associated with lower inflammation. AGE are associated with enhanced oxidative stress and inflammation. SFA and trans-MUFA are pro-inflammatory, while PUFA, especially long-chain n-3 PUFA, are anti-inflammatory. Hyperglycaemia induces both postprandial and chronic low-grade inflammation. Vitamin C, vitamin E and carotenoids decrease the circulating concentrations of inflammatory markers. Potential mechanisms are described and research gaps, which limit our understanding of the interaction between diet and postprandial and chronic low-grade inflammation, are identified.
872 citations
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01 Jan 2010TL;DR: The authors introduce the development of new estimation modes and schemes for multidimen- sional (formative) constructs, i.e. the use of PLS Regression for formative indicators, and the uses of path analysis on latent variable scores to estimate path coefficients.
Abstract: In this chapter the authors first present the basic algorithm of PLS Path Modeling by discussing some recently proposed estimation options. Namely, they introduce the development of new estimation modes and schemes for multidimen- sional (formative) constructs, i.e. the use of PLS Regression for formative indicators, and the use of path analysis on latent variable scores to estimate path coefficients Furthermore, they focus on the quality indexes classically used to assess the perfor- mance of the model in terms of explained variances. They also present some recent developments in PLS Path Modeling framework for model assessment and improve- ment, including a non-parametric GoF-based procedure for assessing the statistical significance of path coefficients. Finally, they discuss the REBUS-PLS algorithm that enables to improve the prediction performance of the model by capturing unob- served heterogeneity. The chapter ends with a brief sketch of open issues in the area that, in the Authors' opinion, currently represent major research challenges.
866 citations
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TL;DR: In this article, a combination of machine learning and social network analysis was used to classify users as Democrats or as Republicans based on the political content shared by them and investigate political homophily both in the network of reciprocated and non-reciprocated ties.
Abstract: This paper investigates political homophily on Twitter. Using a combination of machine learning and social network analysis we classify users as Democrats or as Republicans based on the political content shared. We then investigate political homophily both in the network of reciprocated and nonreciprocated ties. We find that structures of political homophily differ strongly between Democrats and Republicans. In general, Democrats exhibit higher levels of political homophily. But Republicans who follow official Republican accounts exhibit higher levels of homophily than Democrats. In addition, levels of homophily are higher in the network of reciprocated followers than in the nonreciprocated network. We suggest that research on political homophily on the Internet should take the political culture and practices of users seriously.
855 citations
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TL;DR: The data show for the first time that the prevalence of autoimmune disorders in celiac disease is related to the duration of exposure to gluten.
850 citations
Queen Mary University of London1, University of Groningen2, Utrecht University3, University of Debrecen4, National Institutes of Health5, University of Milan6, University Medical Center Utrecht7, Hungarian Academy of Sciences8, Casa Sollievo della Sofferenza9, King's College London10, Wellcome Trust Sanger Institute11, University of Tampere12, Trinity College, Dublin13, Mater Misericordiae University Hospital14, Sapienza University of Rome15, Leiden University16, Mayo Clinic17, University of California, Los Angeles18, University of Helsinki19, University of Naples Federico II20, Beckman Research Institute21, University of Milano-Bicocca22
TL;DR: Variants from 13 new regions reached genome-wide significance and most contain genes with immune functions, with ETS1, RUNX3, THEMIS and TNFRSF14 having key roles in thymic T-cell selection.
Abstract: We performed a second-generation genome-wide association study of 4,533 individuals with celiac disease (cases) and 10,750 control subjects. We genotyped 113 selected SNPs with P(GWAS) < 10(-4) and 18 SNPs from 14 known loci in a further 4,918 cases and 5,684 controls. Variants from 13 new regions reached genome-wide significance (P(combined) < 5 x 10(-8)); most contain genes with immune functions (BACH2, CCR4, CD80, CIITA-SOCS1-CLEC16A, ICOSLG and ZMIZ1), with ETS1, RUNX3, THEMIS and TNFRSF14 having key roles in thymic T-cell selection. There was evidence to suggest associations for a further 13 regions. In an expression quantitative trait meta-analysis of 1,469 whole blood samples, 20 of 38 (52.6%) tested loci had celiac risk variants correlated (P < 0.0028, FDR 5%) with cis gene expression.
845 citations
Authors
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Name | H-index | Papers | Citations |
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D. M. Strom | 176 | 3167 | 194314 |
Yang Gao | 168 | 2047 | 146301 |
Robert Stone | 160 | 1756 | 167901 |
Elio Riboli | 158 | 1136 | 110499 |
Barry J. Maron | 155 | 792 | 91595 |
H. Eugene Stanley | 154 | 1190 | 122321 |
Paul Elliott | 153 | 773 | 103839 |
Robert O. Bonow | 149 | 808 | 114836 |
Kai Simons | 147 | 426 | 93178 |
Peter Buchholz | 143 | 1181 | 92101 |
Martino Margoni | 141 | 2059 | 107829 |
H. A. Neal | 141 | 1903 | 115480 |
Luca Lista | 140 | 2044 | 110645 |
Pierluigi Paolucci | 138 | 1965 | 105050 |
Ari Helenius | 137 | 298 | 64789 |