University of Amsterdam

About: University of Amsterdam is a education organization based out in Amsterdam, Noord-Holland, Netherlands. It is known for research contribution in the topics: Population & Randomized controlled trial. The organization has 59309 authors who have published 140894 publications receiving 5984137 citations. The organization is also known as: UvA & Universiteit van Amsterdam.

Framing European politics: a content analysis of press and television news

Abstract: We investigated the prevalence of 5 news frames identified in earlier studies on framing and framing effects: attribution of responsibility, conflict, human interest, economic consequences, and morality We content analyzed 2,601 newspaper stories and 1,522 television news stories in the period surrounding the Amsterdam meetings of European heads of state in 1997 Our results showed that, overall, the attribution of responsibility frame was most commonly used in the news, followed by the conflict, economic consequences, human interest, and morality frames, respectively The use of news frames depended on both the type of outlet and the type of topic Most significant differences were not between media (television vs the press) but between sensationalist vs serious types of news outlets Sober and serious newspapers and television news programs more often used the responsibility and conflict frames in the presentation of news, whereas sensationalist outlets more often used the human interest frame

Infliximab Maintenance Therapy for Fistulizing Crohn's Disease

Abstract: BACKGROUND: Infliximab, a monoclonal antibody against tumor necrosis factor, is an effective maintenance therapy for patients with Crohn's disease without fistulas. It is not known whether infliximab is an effective maintenance therapy for patients with fistulas. METHODS: We performed a multicenter, double-blind, randomized, placebo-controlled trial to evaluate the efficacy of infliximab maintenance therapy in 306 adult patients with Crohn's disease and one or more draining abdominal or perianal fistulas of at least three months' duration. Patients received 5 mg of infliximab per kilogram of body weight intravenously on weeks 0, 2, and 6. A total of 195 patients who had a response at weeks 10 and 14 and 87 patients who had no response were then randomly assigned to receive placebo or 5 mg of infliximab per kilogram every eight weeks and to be followed to week 54. The primary analysis was the time to the loss of response among patients who had a response at week 14 and underwent randomization. RESULTS: The time to loss of response was significantly longer for patients who received infliximab maintenance therapy than for those who received placebo maintenance (more than 40 weeks vs. 14 weeks, P<0.001). At week 54, 19 percent of patients in the placebo maintenance group had a complete absence of draining fistulas, as compared with 36 percent of patients in the infliximab maintenance group (P=0.009). CONCLUSIONS: Patients with fistulizing Crohn's disease who have a response to induction therapy with infliximab have an increased likelihood of a sustained response over a 54-week period if infliximab treatment is continued every 8 weeks.

The Classification of Glomerulonephritis in Systemic Lupus Erythematosus Revisited

Abstract: The currently used classification reflects our understanding of the pathogenesis of the various forms of lupus nephritis, but clinicopathologic studies have revealed the need for improved categorization and terminology. Based on the 1982 classification published under the auspices of the World Health Organization (WHO) and subsequent clinicopathologic data, we propose that class I and II be used for purely mesangial involvement (I, mesangial immune deposits without mesangial hypercellularity; II, mesangial immune deposits with mesangial hypercellularity); class III for focal glomerulonephritis (involving or = 50% of total number of glomeruli) either with segmental (class IV-S) or global (class IV-G) involvement, and also with subdivisions for active and sclerotic lesions; class V for membranous lupus nephritis; and class VI for advanced sclerosing lesions]. Combinations of membranous and proliferative glomerulonephritis (i.e., class III and V or class IV and V) should be reported individually in the diagnostic line. The diagnosis should also include entries for any concomitant vascular or tubulointerstitial lesions. One of the main advantages of the current revised classification is that it provides a clear and unequivocal description of the various lesions and classes of lupus nephritis, allowing a better standardization and lending a basis for further clinicopathologic studies. We hope that this revision, which evolved under the auspices of the International Society of Nephrology and the Renal Pathology Society, will contribute to further advancement of the WHO classification.

Centering, scaling, and transformations: improving the biological information content of metabolomics data

Abstract: Extracting relevant biological information from large data sets is a major challenge in functional genomics research. Different aspects of the data hamper their biological interpretation. For instance, 5000-fold differences in concentration for different metabolites are present in a metabolomics data set, while these differences are not proportional to the biological relevance of these metabolites. However, data analysis methods are not able to make this distinction. Data pretreatment methods can correct for aspects that hinder the biological interpretation of metabolomics data sets by emphasizing the biological information in the data set and thus improving their biological interpretability. Different data pretreatment methods, i.e. centering, autoscaling, pareto scaling, range scaling, vast scaling, log transformation, and power transformation, were tested on a real-life metabolomics data set. They were found to greatly affect the outcome of the data analysis and thus the rank of the, from a biological point of view, most important metabolites. Furthermore, the stability of the rank, the influence of technical errors on data analysis, and the preference of data analysis methods for selecting highly abundant metabolites were affected by the data pretreatment method used prior to data analysis. Different pretreatment methods emphasize different aspects of the data and each pretreatment method has its own merits and drawbacks. The choice for a pretreatment method depends on the biological question to be answered, the properties of the data set and the data analysis method selected. For the explorative analysis of the validation data set used in this study, autoscaling and range scaling performed better than the other pretreatment methods. That is, range scaling and autoscaling were able to remove the dependence of the rank of the metabolites on the average concentration and the magnitude of the fold changes and showed biologically sensible results after PCA (principal component analysis). In conclusion, selecting a proper data pretreatment method is an essential step in the analysis of metabolomics data and greatly affects the metabolites that are identified to be the most important.