1,722,192 research outputs found
Brain Imaging Correlates of Immediate Response to Chronotherapeutics: Effects on Glutamate, White Matter Microstructure, and Functional Connectivity
No full textNEUROIMAGING AND GENETICS OF ANTIDEPRESSANT RESPONSE TO SLEEP DEPRIVATION: IMPLICATIONS FOR DRUG DEVELOPMENT
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Antidepressant light therapy for bipolar patients: A meta-analyses
No full textBackgrounds: Bipolar depression is still a very difficult to treat condition with low success rates of antidepressant drugs, high rates of morbidity and suicide risk and antidepressant-emergent mania risk. Despite a growing body of evidence has been generated over the last decade about Light Therapy (LT) as an effective treatment for depression the management of it continues to be a point of debate for Bipolar Disorder especially when considering non-seasonal pattern. Methods: We systematically screened current literature using the PubMed electronic platform. We considered “mood disorder”, “depression” and “light therapy” as keywords for the search. Results: We retrieved 1907 papers. After the screening, we selected 11 papers to be included in the analysis, treating 195 patients affected by bipolar depression. 5 studies were RCT studies. The overall analysis, including non-RCTs, showed a positive effect of the treatment in all the included studies (ESs: -1.46, 95% CI:-1.677 to -1.242; p<0.001). A significant effect of LT compared to placebo was found also in RCTs (ESs: -0.501, 95% CI: - 0.777 to -0.225; p<0.001). Limitations: A high heterogeneity between the studies was found when including non-RCTs and the number of RCTs was small Conclusion: We confirmed the –efficacy of LT as antidepressant non-pharmacological therapy also in bipolar depressio
A model for visual building SPARQL queries
No full textLODeX is a Semantic Web tool that, leveraging a summarized representation of a LOD source structure (i.e. Schema Summary), helps users explore and query SPARQL endpoints by hiding the complexity of Semantic Web technologies. By leveraging Schema Summary of a LOD source, LODeX guides the user in composing visual queries that are automatically translated in correct SPARQL queries through a SPARQL compiler. In this work we inspected how LODeX can deal with the high expressivity of SPARQL. In particular, we propose a formal model that allow to define queries over the Schema Summary (i.e. Basic Query) and we analyze how this model can handle different join patterns used in SPARQL queries. Finally, we inspect how LODeX can satisfy real world users necessities by analyzing the query logs contained in the LSQ dataset. We show that LODeX could be able to generate the 77.6% of the 5 million queries contained in LSQ dataset
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