Carbamazepine augmentation in depressive patients non-responding to citalopram: a pharmacokinetic and clinical pilot study

Citalopram is a chiral antidepressant drug. Its eutomer, S-citalopram (escitalopram), has recently been introduced as an antidepressant. In an open pilot study, four outpatients and two inpatients with a major depressive episode (ICD-10), and who were nonresponders to a 4-week pretreatment with 40-60 mg/day citalopram, were comedicated for another 4-week period with carbamazepine (200-400 mg/day). Some of the patients suffered also from comorbidities: Phobic anxiety disorder with panic attacks (n=2), generalised anxiety disorder, alcohol abuse, dependent personality disorder, hypertension (n=1). After a 4-week augmentation therapy with carbamazepine, a significant (P<0.03) decrease of the plasma concentrations of S-citalopram and R-citalopram, by 27 and 31%, respectively, was observed. Apparently, the probable induction of CYP3A4 by carbamazepine results in a nonstereoselective increase in N-demethylation of citalopram. Moreover, there was a significant (P<0.03) decrease of the ratio S/R-citalopram propionic acid derivative, the formation of it being partly regulated by MAO-A and MAO-B. Already, within 1 week after addition of carbamazepine, there was a slight but significant (P<0.03) decrease of the MADRS depression scores, from 27.0+/-7.7 (mean+/-S.D.) to 23.3+/-6.6, and the final score on day 56 was 18.8+/-10.9. The treatment was generally well tolerated. There was no evidence of occurrence of a serotonin syndrome. After augmentation with carbamazepine, treatment related adverse events were: Nausea in one case, diarrhea in one case, and rash in two cases. In conclusion, the results of this pilot study suggest that carbamazepine augmentation of a citalopram treatment in previous nonresponders to citalopram may be clinically useful, but that in addition carbamazepine can lead to a decrease of the plasma concentrations of the active enantiomer escitalopram.

Ecological assembly rules in plant communities--approaches, patterns and prospects.

Understanding how communities of living organisms assemble has been a central question in ecology since the early days of the discipline. Disentangling the different processes involved in community assembly is not only interesting in itself but also crucial for an understanding of how communities will behave under future environmental scenarios. The traditional concept of assembly rules reflects the notion that species do not co-occur randomly but are restricted in their co-occurrence by interspecific competition. This concept can be redefined in a more general framework where the co-occurrence of species is a product of chance, historical patterns of speciation and migration, dispersal, abiotic environmental factors, and biotic interactions, with none of these processes being mutually exclusive. Here we present a survey and meta-analyses of 59 papers that compare observed patterns in plant communities with null models simulating random patterns of species assembly. According to the type of data under study and the different methods that are applied to detect community assembly, we distinguish four main types of approach in the published literature: species co-occurrence, niche limitation, guild proportionality and limiting similarity. Results from our meta-analyses suggest that non-random co-occurrence of plant species is not a widespread phenomenon. However, whether this finding reflects the individualistic nature of plant communities or is caused by methodological shortcomings associated with the studies considered cannot be discerned from the available metadata. We advocate that more thorough surveys be conducted using a set of standardized methods to test for the existence of assembly rules in data sets spanning larger biological and geographical scales than have been considered until now. We underpin this general advice with guidelines that should be considered in future assembly rules research. This will enable us to draw more accurate and general conclusions about the non-random aspect of assembly in plant communities.

The Brazilian electronic theses and dissertations digital library: providing open access for scholarly information

This paper describes a project led by the Instituto Brasileiro de Informações em Ciência e Tecnologia (Ibict), a government institution, to build a national digital library for electronic theses and dissertations - Bibliteca Digital de Teses e Dissertações (BDTD). The project has been a collaborative effort among Ibict, universities and other research centers in Brazil. The developers adopted a system architecture based on the Open Archives Initiative (OAI) in which universities and research centers act as data providers and Ibict as a service provider. A Brazilian metadata standard for electronic theses and dissertations was developed for the digital library. A toolkit including open source package was also developed by Ibict to be distributed to potential data providers. BDTD has been integrated with the international initiative: the Networked Digital Library of Thesis and Dissertation (NDLTD). Discussions in the paper address various issues related to project design, development and management as well as the role played by Ibict. Conclusions highlight some important lessons learned to date and challenges for the future in expanding the BDTD project.

The connectome viewer toolkit: an open source framework to manage, analyze, and visualize connectomes.

Advanced neuroinformatics tools are required for methods of connectome mapping, analysis, and visualization. The inherent multi-modality of connectome datasets poses new challenges for data organization, integration, and sharing. We have designed and implemented the Connectome Viewer Toolkit - a set of free and extensible open source neuroimaging tools written in Python. The key components of the toolkit are as follows: (1) The Connectome File Format is an XML-based container format to standardize multi-modal data integration and structured metadata annotation. (2) The Connectome File Format Library enables management and sharing of connectome files. (3) The Connectome Viewer is an integrated research and development environment for visualization and analysis of multi-modal connectome data. The Connectome Viewer's plugin architecture supports extensions with network analysis packages and an interactive scripting shell, to enable easy development and community contributions. Integration with tools from the scientific Python community allows the leveraging of numerous existing libraries for powerful connectome data mining, exploration, and comparison. We demonstrate the applicability of the Connectome Viewer Toolkit using Diffusion MRI datasets processed by the Connectome Mapper. The Connectome Viewer Toolkit is available from http://www.cmtk.org/

ConnectomeViewer - Multi-Modal Multi-Level Network Visualization and Analysis.

Introduction: The field of Connectomic research is growing rapidly, resulting from methodological advances in structural neuroimaging on many spatial scales. Especially progress in Diffusion MRI data acquisition and processing made available macroscopic structural connectivity maps in vivo through Connectome Mapping Pipelines (Hagmann et al, 2008) into so-called Connectomes (Hagmann 2005, Sporns et al, 2005). They exhibit both spatial and topological information that constrain functional imaging studies and are relevant in their interpretation. The need for a special-purpose software tool for both clinical researchers and neuroscientists to support investigations of such connectome data has grown. Methods: We developed the ConnectomeViewer, a powerful, extensible software tool for visualization and analysis in connectomic research. It uses the novel defined container-like Connectome File Format, specifying networks (GraphML), surfaces (Gifti), volumes (Nifti), track data (TrackVis) and metadata. Usage of Python as programming language allows it to by cross-platform and have access to a multitude of scientific libraries. Results: Using a flexible plugin architecture, it is possible to enhance functionality for specific purposes easily. Following features are already implemented: * Ready usage of libraries, e.g. for complex network analysis (NetworkX) and data plotting (Matplotlib). More brain connectivity measures will be implemented in a future release (Rubinov et al, 2009). * 3D View of networks with node positioning based on corresponding ROI surface patch. Other layouts possible. * Picking functionality to select nodes, select edges, get more node information (ConnectomeWiki), toggle surface representations * Interactive thresholding and modality selection of edge properties using filters * Arbitrary metadata can be stored for networks, thereby allowing e.g. group-based analysis or meta-analysis. * Python Shell for scripting. Application data is exposed and can be modified or used for further post-processing. * Visualization pipelines using filters and modules can be composed with Mayavi (Ramachandran et al, 2008). * Interface to TrackVis to visualize track data. Selected nodes are converted to ROIs for fiber filtering The Connectome Mapping Pipeline (Hagmann et al, 2008) processed 20 healthy subjects into an average Connectome dataset. The Figures show the ConnectomeViewer user interface using this dataset. Connections are shown that occur in all 20 subjects. The dataset is freely available from the homepage (connectomeviewer.org). Conclusions: The ConnectomeViewer is a cross-platform, open-source software tool that provides extensive visualization and analysis capabilities for connectomic research. It has a modular architecture, integrates relevant datatypes and is completely scriptable. Visit www.connectomics.org to get involved as user or developer.

Tarvitaanko verkkodokumenttien kuvailussa käsityötä? : osa 1: kontekstuaalinen metadata

Summary

Improving Searching and Browsing Capabilities of Learning Object Repositories

Learning object repositories are a basic piece of virtual learning environments used for content management. Nevertheless, learning objects have special characteristics that make traditional solutions for content management ine ective. In particular, browsing and searching for learning objects cannot be based on the typical authoritative meta-data used for describing content, such as author, title or publicationdate, among others. We propose to build a social layer on top of a learning object repository, providing nal users with additional services fordescribing, rating and curating learning objects from a teaching perspective. All these interactions among users, services and resources can be captured and further analyzed, so both browsing and searching can be personalized according to user pro le and the educational context, helping users to nd the most valuable resources for their learning process. In this paper we propose to use reputation schemes and collaborative filtering techniques for improving the user interface of a DSpace based learning object repository.

Fluoxetine augmentation in citalopram non-responders: pharmacokinetic and clinical consequences.

In an open trial 11 in-patients with a major depressive episode (ICD-10), extensive metabolizers of mephenytoin (CYP2C19) and dextromethorphan (CYP2D6) and who were non-responders to a 3-wk pretreatment with 40 mg/d citalopram (Cit), were co-medicated for 7 wk (days 0-49) with fluoxetine (Fluox) (10 mg/d). Plasma concentrations of S-Cit and R-Cit significantly increased from day 0 (means+/-S.D.: 28+/-9 and 47+/-11 &mgr;g/l, respectively) to day 49 (58+/-12 and 72+/-21 &mgr;g/l, respectively) (p & 0.01 for each comparison), and the S-Cit/R-Cit ratio increased from 0.61+/-0.16 to 0.82+/-0.12 (p & 0.01). Therefore, Fluox increases the pharmacologically more active S-Cit (in comparison with R-Cit) with some stereoselectivity, most probably by inhibition of CYP2D6 and CYP3A4. Eight of the 11 patients showed clinical improvement (reduction > 50% of the MADRS score) and the combined treatment was generally well tolerated.

Building a usable and accessible semantic web interaction platform

Semantic Web applications take off is being slower than expected, at least with respect to “real-world” applications and users. One of the main reasons for this lack of adoption is that most Semantic Web user interfaces are still immature from the usability and accessibility points of view. This is due to the novelty of these technologies, but this also motivates the exploration of alternative interaction paradigms, different from the “traditional” Web or Desktop applications ones. Our proposal is realized in the Rhizomer platform, which explores the possibilities of the object–action interaction paradigm at the Web scale. This paradigm is well suited for heterogeneous resource spaces such as those common in the Semantic Web. Resources, described by metadata, correspond to the objects in the paradigm. Semantic web services, which are dynamically associated to these objects, correspond to the actions. The platform is being put into practice in the context of a research project in order to build an open application for media distribution based on Semantic Web technologies. Moreover, its usability and accessibility have been evaluated in this real setting and compared to similar systems.

Code Generator for Key Management Protocols - Design and Implementation

Key management has a fundamental role in secure communications. Designing and testing of key management protocols is tricky. These protocols must work flawlessly despite of any abuse. The main objective of this work was to design and implement a tool that helps to specify the protocol and makes it possible to test the protocol while it is still under development. This tool generates compile-ready java code from a key management protocol model. A modelling method for these protocols, which uses Unified Modeling Language (UML) was also developed. The protocol is modelled, exported as an XMI and read by the code generator tool. The code generator generates java code that is immediately executable with a test software after compilation.

A systematic review and meta-analysis of lithium augmentation of tricyclic and second generation antidepressants in major depression.

BACKGROUND: Lithium augmentation of antidepressants for treatment of unipolar major depression was one of the first adjunctive strategies based on a neuropharmacologic rationale. Randomized controlled trials supported its efficacy but most trials added lithium to tricyclic antidepressants (TCAs). Despite its efficacy, use of lithium augmentation remains infrequent. The current systematic review and meta-analysis examines the efficacy of lithium augmentation as an adjunct to second generation antidepressants as well as to TCAs and considers reasons for its infrequent use. METHOD: A systematic search of Medline and the Cochrane Clinical Trials database was performed. Randomized, placebo-controlled trials of lithium augmentation were selected. A fixed-effects meta-analysis was performed. Odds ratios for response were calculated for each treatment-control contrast, for the trials grouped by type of initial antidepressant (TCA or second generation antidepressant), and as a meta-analytic summary for all treatments combined. RESULTS: Nine trials that included 237 patients were selected. The odds ratio for response to lithium vs. placebo in all contrasts combined was 2.89 (95% CI 1.65, 5.05, z=3.72, p=0.0002). Heterogeneity was very low, I(2)=0%. Adjunctive lithium was effective with TCAs (7 contrasts) and with second generation agents (3 contrasts). Discontinuation due to adverse events was infrequent and did not differ between lithium and placebo. LIMITATIONS: The meta-analysis is limited by the small size and number of trials and limited data for treatment resistant patients. CONCLUSIONS: Adjunctive lithium appears to be as effective for second generation antidepressants as it was for the tricyclics.