Impacto de los errores de medicación en una unidad de curas intensivas y grado de implicación de los profesionales de enfermería

El presente estudio identifica los errores de medicación y valora el grado de notificación de estos errores por parte del personal de enfermería en el Servicio de Medicina Intensiva (SMI), del Hospital Universitario Doctor Josep Trueta.Se realizará un estudio observacional, descriptivo y transversal en el hospital de referencia de las comarcas gerundenses durante el año 2013 y 2014.Los sujetos a estudio serán los profesionales enfermeros y los pacientes ingresados en la unidad. Las variables principales son, por un lado, el error de medicación y por otro la notificación del error.El procedimiento de recogida de datos se basará en proporcionar un cuestionario auto administrado al personal de enfermería, caracterizado por seis preguntas con respuestas cerradas, dos de las cuales tienen la opción de ser abiertas.Para el análisis estadístico se utilizará el programa SPSS. Para la obtención de los resultados se realizará un análisis descriptivo univariante. La variable “error de medicación” se expresará como número de casos y en 1.000 pacientes / día. Las demás variables se presentarán mediante frecuencias

Automatic filtering and substantiation of drug safety signals

Drug safety issues pose serious health threats to the population and constitute a major cause of mortality worldwide. Due to the prominent implications to both public health and the pharmaceutical industry, it is of great importance to unravel the molecular mechanisms by which an adverse drug reaction can be potentially elicited. These mechanisms can be investigated by placing the pharmaco-epidemiologically detected adverse drug reaction in an information-rich context and by exploiting all currently available biomedical knowledge to substantiate it. We present a computational framework for the biological annotation of potential adverse drug reactions. First, the proposed framework investigates previous evidences on the drug-event association in the context of biomedical literature (signal filtering). Then, it seeks to provide a biological explanation (signal substantiation) by exploring mechanistic connections that might explain why a drug produces a specific adverse reaction. The mechanistic connections include the activity of the drug, related compounds and drug metabolites on protein targets, the association of protein targets to clinical events, and the annotation of proteins (both protein targets and proteins associated with clinical events) to biological pathways. Hence, the workflows for signal filtering and substantiation integrate modules for literature and database mining, in silico drug-target profiling, and analyses based on gene-disease networks and biological pathways. Application examples of these workflows carried out on selected cases of drug safety signals are discussed. The methodology and workflows presented offer a novel approach to explore the molecular mechanisms underlying adverse drug reactions

Gene-disease network analysis reveals functional modules in mendelian, complex and environmental diseases

AbstractBACKGROUND: Scientists have been trying to understand the molecular mechanisms of diseases to design preventive and therapeutic strategies for a long time. For some diseases, it has become evident that it is not enough to obtain a catalogue of the disease-related genes but to uncover how disruptions of molecular networks in the cell give rise to disease phenotypes. Moreover, with the unprecedented wealth of information available, even obtaining such catalogue is extremely difficult.PRINCIPAL FINDINGS: We developed a comprehensive gene-disease association database by integrating associations from several sources that cover different biomedical aspects of diseases. In particular, we focus on the current knowledge of human genetic diseases including mendelian, complex and environmental diseases. To assess the concept of modularity of human diseases, we performed a systematic study of the emergent properties of human gene-disease networks by means of network topology and functional annotation analysis. The results indicate a highly shared genetic origin of human diseases and show that for most diseases, including mendelian, complex and environmental diseases, functional modules exist. Moreover, a core set of biological pathways is found to be associated with most human diseases. We obtained similar results when studying clusters of diseases, suggesting that related diseases might arise due to dysfunction of common biological processes in the cell.CONCLUSIONS: For the first time, we include mendelian, complex and environmental diseases in an integrated gene-disease association database and show that the concept of modularity applies for all of them. We furthermore provide a functional analysis of disease-related modules providing important new biological insights, which might not be discovered when considering each of the gene-disease association repositories independently. Hence, we present a suitable framework for the study of how genetic and environmental factors, such as drugs, contribute to diseases.AVAILABILITY: The gene-disease networks used in this study and part of the analysis are available at http://ibi.imim.es/DisGeNET/DisGeNETweb.html#Download

Gorilla genome structural variation reveals evolutionary parallelisms with chimpanzee

Structural variation has played an important role in the evolutionary restructuring of human and great ape genomes. Recent analyses have suggested that the genomes of chimpanzee and human have been particularly enriched for this form of genetic variation. Here, we set out to assess the extent of structural variation in the gorilla lineage by generating 10-fold genomic sequence coverage from a western lowland gorilla and integrating these data into a physical and cytogenetic framework of structural variation. We discovered and validated over 7665 structural changes within the gorilla lineage, including sequence resolution of inversions, deletions, duplications, and mobile element insertions. A comparison with human and other ape genomes shows that the gorilla genome has been subjected to the highest rate of segmental duplication. We show that both the gorilla and chimpanzee genomes have experienced independent yet convergent patterns of structural mutation that have not occurred in humans, including the formation of subtelomeric heterochromatic caps, the hyperexpansion of segmental duplications, and bursts of retroviral integrations. Our analysis suggests that the chimpanzee and gorilla genomes are structurally more derived than either orangutan or human genomes.

Sequencing human-gibbon breakpoints of synteny reveals mosaic new insertions at rearrangement sites

The gibbon genome exhibits extensive karyotypic diversity with an increased rate of chromosomal rearrangements during evolution. In an effort to understand the mechanistic origin and implications of these rearrangement events, we sequenced 24 synteny breakpoint regions in the white-cheeked gibbon (Nomascus leucogenys, NLE) in the form of high-quality BAC insert sequences (4.2 Mbp). While there is a significant deficit of breakpoints in genes, we identified seven human gene structures involved in signaling pathways (DEPDC4, GNG10), phospholipid metabolism (ENPP5, PLSCR2), beta-oxidation (ECH1), cellular structure and transport (HEATR4), and transcription (ZNF461), that have been disrupted in the NLE gibbon lineage. Notably, only three of these genes show the expected evolutionary signatures of pseudogenization. Sequence analysis of the breakpoints suggested both nonclassical nonhomologous end-joining (NHEJ) and replication-based mechanisms of rearrangement. A substantial number (11/24) of human-NLE gibbon breakpoints showed new insertions of gibbon-specific repeats and mosaic structures formed from disparate sequences including segmental duplications, LINE, SINE, and LTR elements. Analysis of these sites provides a model for a replication-dependent repair mechanism for double-strand breaks (DSBs) at rearrangement sites and insights into the structure and formation of primate segmental duplications at sites of genomic rearrangements during evolution.

Motivic analysis and its relevance to raga identification in carnatic music

A raga is a collective melodic expression consisting of motifs. A raga can be identified using motifs which areunique to it. Motifs can be thought of as signature prosodic phrases. Different ragas may be composed of the same setof notes, or even phrases, but the prosody may be completely different. In this paper, an attempt is made to determinethe characteristic motifs that enable identification of a raga and distinguish between them. To determine this, motifs are first manually marked for a set of five popular raga by a professional musician. The motifs are then normalisedwith respect to the tonic. HMMs are trained for each motif using 80% of the data and about 20% are used for testing. The results do indicate that about 80% of the motifs are identified as belonging to a specific raga accurately.

A knowledge based signal processing approach to tonic identification in indian classical music

In this paper, we describe several techniques for detecting tonic pitch value in Indian classical music. In Indian music, the raga is the basic melodic framework and it is built on the tonic. Tonic detection is therefore fundamental for any melodic analysis in Indian classical music. This workexplores detection of tonic by processing the pitch histograms of Indian classic music. Processing of pitch histograms using group delay functions and its ability to amplify certain traits of Indian music in the pitch histogram, is discussed. Three different strategies to detect tonic, namely, the concert method, the template matching and segmented histogram method are proposed. The concert method exploits the fact that the tonic is constant over a piece/concert.templatematchingmethod and segmented histogrammethodsuse the properties: (i) the tonic is always present in the background, (ii) some notes are less inflected and dominant, to detect the tonic of individual pieces. All the three methods yield good results for Carnatic music (90−100% accuracy), while for Hindustanimusic, the templatemethod works best, provided the v¯adi samv¯adi notes for a given piece are known (85%).

Metrical strength and contradiction in turkish Makam music

In this paper we investigate how note onsets in Turkish Makam music compositions are distributed, and in how far this distribution supports or contradicts the metrical structure of the pieces, the usul. We use MIDI data to derive the distributions in the form of onset histograms, and comparethem with metrical weights that are applied to describe the usul in theory. We compute correlation and syncopation values to estimate the degrees of support and contradiction, respectively. While the concept of syncopation is rarelymentioned in the context of this music, we can gain interesting insight into the structure of a piece using such a measure.We show that metrical contradiction is systematically applied in some metrical structures. We will compare thedifferences between Western music and Turkish Makam music regarding metrical support and contradiction. Such a study can help avoiding pitfalls in later attempts to perform audio processing tasks such as beat tracking or rhythmic similarity measurements.

Features for analysis of Makam music

For computational studies of makam music, it is essential to gather a list of characteristics that constitute a makam and explore corresponding quantitative features for automaticanalysis. This study is such an attempt where we address the characteristics for makams as defined in theory books and deduce a list of quantitative features. The target here is to evoke discussions on some measurable features other than providing complete analysis on thediscriminative potentials of each proposed feature which could be the subject of a few larger studies.

Width and serialization of classical planning problems

We introduce a width parameter that bounds the complexity of classical planning problems and domains, along with a simple but effective blind-search procedure that runs in time that is exponential in the problem width. We show that many benchmark domains have a bounded and small width provided thatgoals are restricted to single atoms, and hence that such problems are provably solvable in low polynomial time. We then focus on the practical value of these ideas over the existing benchmarks which feature conjunctive goals. We show that the blind-search procedure can be used for both serializing the goal into subgoals and for solving the resulting problems, resulting in a ‘blind’ planner that competes well with a best-first search planner guided by state-of-the-art heuristics. In addition, ideas like helpful actions and landmarks can be integrated as well, producing a planner with state-of-the-art performance.

Interoperability and Technology for a Language Resources Factory

This document describes some of the technological aspects of a project devoted to the creation of a factory for language resources. The project’s objectives are explained, as well as the idea to create a distributed infrastructure of web services. This document focuses on two main topics of the factory: (1) the technological approaches chosen to develop the factory, i.e. software, protocols, servers, etc. (2) and Interoperability as the main challenge is to permit different NLP tools work together in the factory. This document explains why XCES and GrAF are chosen as the main formats used for the linguistic data exchange.

Language Resources Factory: case study on the acquisition of Translation Memories

This paper demonstrates a novel distributed architecture to facilitate the acquisition of Language Resources. We build a factory that automates the stages involved in the acquisition, production, updating and maintenance of these resources. The factory is designed as a platform where functionalities are deployed as web services, which can be combined in complex acquisition chains using workflows. We show a case study, which acquires a Translation Memory for a given pair of languages and a domain using web services for crawling, sentence alignment and conversion to TMX.

La depressió major i els esdeveniments estressants vitals

Introducció: La Depressió Major (DM) és una malaltia psiquiàtrica freqüent en la societat actual. Cada vegada més, es relaciona la DM amb els esdeveniments estressants vitals (EEV) i un d’aquests EEV és l’actual situació de crisis econòmica que afegeix un risc degut a la desigualtat que representa per la persona en termes econòmics.Metodologia: S’ha dut a terme una revisió de la literatura a les bases de dades Pubmed, ElSevier i PsycInfo en els últims 15 anys utilitzant les paraules clau “major depressive disorder”, “depression”, “stressful events” i “life events”.Resultats: Es troben 11 articles que relacionen la depressió major amb els esdeveniments estressants vitals. Tots els articles revisats coincideixen en que els EEV tenen una relació amb la DM i a partir d’aquí s’estableixen altres variables com els EEV dependents i independents, la influència del gènere, l’edat, del factor genètic i la de la història depressiva prèvia.Conclusions: L’exposició als EEV augmenta el risc de desenvolupar una DM. Altres variables com el factor genètic i l’edat també es relacionen amb els EEV. Hi ha certa evidència que aquells entre 41 i 57 anys tenen major incidència d’EEV com a causant d’una DM. També s’ha descrit una relació directe entre el risc genètic i la incidència d’EEV. Ara bé, quants més episodis depressius previs menys probabilitats de patir una DM degut als EEV

GSVA: gene set variation analysis for microarray and RNA-seq data

Gene set enrichment (GSE) analysis is a popular framework for condensing information from gene expression profiles into a pathway or signature summary. The strengths of this approach over single gene analysis include noise and dimension reduction, as well as greater biological interpretability. As molecular profiling experiments move beyond simple case-control studies, robust and flexible GSE methodologies are needed that can model pathway activity within highly heterogeneous data sets. To address this challenge, we introduce Gene Set Variation Analysis (GSVA), a GSE method that estimates variation of pathway activity over a sample population in an unsupervised manner. We demonstrate the robustness of GSVA in a comparison with current state of the art sample-wise enrichment methods. Further, we provide examples of its utility in differential pathway activity and survival analysis. Lastly, we show how GSVA works analogously with data from both microarray and RNA-seq experiments. GSVA provides increased power to detect subtle pathway activity changes over a sample population in comparison to corresponding methods. While GSE methods are generally regarded as end points of a bioinformatic analysis, GSVA constitutes a starting point to build pathway-centric models of biology. Moreover, GSVA contributes to the current need of GSE methods for RNA-seq data. GSVA is an open source software package for R which forms part of the Bioconductor project and can be downloaded at http://www.bioconductor.org.

Cognición, emoción y aprendizaje

Qué significa aprender? ¿Cómo aprendemos? Si partimos de la etimología de la palabra “aprender”, nos damos cuenta de que proviene del concepto de “apoderarse”. Realmente aprendemos algo cuando nos apoderamos de ello. La neurociencia nos confirma la extrema plasticidad del cerebro. Según sus postulados, el cerebro se construye a sí mismo. Esto significa que para que realmente aprendamos algo, debe de producirse un “cambio” en el cerebro, es decir, en las conexiones que configuran las múltiples redes neuronales