Institution
University of Southern Denmark
Education•Odense, Syddanmark, Denmark•
About: University of Southern Denmark is a education organization based out in Odense, Syddanmark, Denmark. It is known for research contribution in the topics: Population & Randomized controlled trial. The organization has 11928 authors who have published 37918 publications receiving 1258559 citations. The organization is also known as: SDU.
Papers published on a yearly basis
Papers
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TL;DR: This work uses the sub-parts per million mass accuracy of a new ion trap Fourier transform mass spectrometer to achieve more than a 100-fold increased confidence in peptide identification compared with typical ion trap experiments and shows that trypsin cleaves solely C-terminal to arginine and lysine.
1,114 citations
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TL;DR: The determinants most consistently supported by evidence are gender, age, socio-economic position, preferences, parental intake and home availability/accessibility.
Abstract: In order to more effectively promote fruit and vegetable intake among children and adolescents, insight into determinants of intake is necessary. We conducted a review of the literature for potential determinants of fruit and vegetable intake in children and adolescents. Papers were identified from Medline and PsycINFO by using all combinations of the search terms: "fruit(s) or vegetable(s)" and "children or adolescents". Quantitative research examining determinants of fruit and/or vegetable intake among children and adolescents aged 6–18 years were included. The selection and review process was conducted according to a four-step protocol resulting in information on country, population, design, methodology, theoretical basis, instrument used for measuring intake, statistical analysis, included independent variables, and effect sizes. Ninety-eight papers were included. A large number of potential determinants have been studied among children and adolescents. However, for many presumed determinants convincing evidence is lacking, mostly because of paucity of studies. The determinants best supported by evidence are: age, gender, socio-economic position, preferences, parental intake, and home availability/accessibility. Girls and younger children tend to have a higher or more frequent intake than boys and older children. Socio-economic position, preferences, parental intake, and home availability/accessibility are all consistently positively associated with intake. The determinants most consistently supported by evidence are gender, age, socio-economic position, preferences, parental intake and home availability/accessibility. There is a need for internationally comparative, longitudinal, theory-based and multi-level studies taking both personal and environmental factors into account. This paper is published as part of the special Pro Children series in the International Journal of Behavioral Nutrition and Physical Activity. Please see [
http://www.ijbnp.org/content/3/1/26
] for the relevant editorial.
1,114 citations
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TL;DR: The data establish a quantitative proteomic approach for the temporal characterization of protein flux through cellular organelles and demonstrate that the nucleolar proteome changes significantly over time in response to changes in cellular growth conditions.
Abstract: The nucleolus is a key organelle that coordinates the synthesis and assembly of ribosomal subunits and forms in the nucleus around the repeated ribosomal gene clusters. Because the production of ribosomes is a major metabolic activity, the function of the nucleolus is tightly linked to cell growth and proliferation, and recent data suggest that the nucleolus also plays an important role in cell-cycle regulation, senescence and stress responses. Here, using mass-spectrometry-based organellar proteomics and stable isotope labelling, we perform a quantitative analysis of the proteome of human nucleoli. In vivo fluorescent imaging techniques are directly compared to endogenous protein changes measured by proteomics. We characterize the flux of 489 endogenous nucleolar proteins in response to three different metabolic inhibitors that each affect nucleolar morphology. Proteins that are stably associated, such as RNA polymerase I subunits and small nuclear ribonucleoprotein particle complexes, exit from or accumulate in the nucleolus with similar kinetics, whereas protein components of the large and small ribosomal subunits leave the nucleolus with markedly different kinetics. The data establish a quantitative proteomic approach for the temporal characterization of protein flux through cellular organelles and demonstrate that the nucleolar proteome changes significantly over time in response to changes in cellular growth conditions.
1,102 citations
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TL;DR: A keyword analysis identifies the most popular subjects covered by bibliometric analysis, and multidisciplinary articles are shown to have the highest impact.
Abstract: Bibliometric methods or "analysis" are now firmly established as scientific specialties and are an integral part of research evaluation methodology especially within the scientific and applied fields. The methods are used increasingly when studying various aspects of science and also in the way institutions and universities are ranked worldwide. A sufficient number of studies have been completed, and with the resulting literature, it is now possible to analyse the bibliometric method by using its own methodology. The bibliometric literature in this study, which was extracted from Web of Science, is divided into two parts using a method comparable to the method of Jonkers et al. (Characteristics of bibliometrics articles in library and information sciences (LIS) and other journals, pp. 449---551, 2012: The publications either lie within the Information and Library Science (ILS) category or within the non-ILS category which includes more applied, "subject" based studies. The impact in the different groupings is judged by means of citation analysis using normalized data and an almost linear increase can be observed from 1994 onwards in the non-ILS category. The implication for the dissemination and use of the bibliometric methods in the different contexts is discussed. A keyword analysis identifies the most popular subjects covered by bibliometric analysis, and multidisciplinary articles are shown to have the highest impact. A noticeable shift is observed in those countries which contribute to the pool of bibliometric analysis, as well as a self-perpetuating effect in giving and taking references.
1,098 citations
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TL;DR: The analyses suggest the existence of an industry bias that cannot be explained by standard 'Risk of bias' assessments.
Abstract: Background
Clinical research affecting how doctors practice medicine is increasingly sponsored by companies that make drugs and medical devices. Previous systematic reviews have found that pharmaceutical industry sponsored studies are more often favorable to the sponsor’s product compared with studies with other sources of sponsorship. This review is an update using more stringent methodology and also investigating sponsorship of device studies.
Objectives
To investigate whether industry sponsored drug and device studies have more favorable outcomes and differ in risk of bias, compared with studies having other sources of sponsorship.
Search methods
We searched MEDLINE (1948 to September 2010), EMBASE (1980 to September 2010), the Cochrane Methodology Register (Issue 4, 2010) and Web of Science (August 2011). In addition, we searched reference lists of included papers, previous systematic reviews and author files.
Selection criteria
Cross-sectional studies, cohort studies, systematic reviews and meta-analyses that quantitatively compared primary research studies of drugs or medical devices sponsored by industry with studies with other sources of sponsorship. We had no language restrictions.
Data collection and analysis
Two assessors identified potentially relevant papers, and a decision about final inclusion was made by all authors. Two assessors extracted data, and we contacted authors of included papers for additional unpublished data. Outcomes included favorable results, favorable conclusions, effect size, risk of bias and whether the conclusions agreed with the study results. Two assessors assessed risk of bias of included papers. We calculated pooled risk ratios (RR) for dichotomous data (with 95% confidence intervals).
Main results
Forty-eight papers were included. Industry sponsored studies more often had favorable efficacy results, risk ratio (RR): 1.32 (95% confidence interval (CI): 1.21 to 1.44), harms results RR: 1.87 (95% CI: 1.54 to 2.27) and conclusions RR: 1.31 (95% CI: 1.20 to 1.44) compared with non-industry sponsored studies. Ten papers reported on sponsorship and effect size, but could not be pooled due to differences in their reporting of data. The results were heterogeneous; five papers found larger effect sizes in industry sponsored studies compared with non-industry sponsored studies and five papers did not find a difference in effect size. Only two papers (including 120 device studies) reported separate data for devices and we did not find a difference between drug and device studies on the association between sponsorship and conclusions (test for interaction, P = 0.23). Comparing industry and non-industry sponsored studies, we did not find a difference in risk of bias from sequence generation, allocation concealment and follow-up. However, industry sponsored studies more often had low risk of bias from blinding, RR: 1.32 (95% CI: 1.05 to 1.65), compared with non-industry sponsored studies. In industry sponsored studies, there was less agreement between the results and the conclusions than in non-industry sponsored studies, RR: 0.84 (95% CI: 0.70 to 1.01).
Authors' conclusions
Sponsorship of drug and device studies by the manufacturing company leads to more favorable results and conclusions than sponsorship by other sources. Our analyses suggest the existence of an industry bias that cannot be explained by standard 'Risk of bias' assessments.
1,095 citations
Authors
Showing all 12150 results
Name | H-index | Papers | Citations |
---|---|---|---|
Paul M. Ridker | 233 | 1242 | 245097 |
George Davey Smith | 224 | 2540 | 248373 |
Matthias Mann | 221 | 887 | 230213 |
Eric Boerwinkle | 183 | 1321 | 170971 |
Gang Chen | 167 | 3372 | 149819 |
Jun Wang | 166 | 1093 | 141621 |
Harvey F. Lodish | 165 | 782 | 101124 |
Jens J. Holst | 160 | 1536 | 107858 |
Rajesh Kumar | 149 | 4439 | 140830 |
J. Fraser Stoddart | 147 | 1239 | 96083 |
Debbie A Lawlor | 147 | 1114 | 101123 |
Børge G. Nordestgaard | 147 | 1047 | 95530 |
Oluf Pedersen | 135 | 939 | 106974 |
Rasmus Nielsen | 135 | 556 | 84898 |
Torben Jørgensen | 135 | 883 | 86822 |