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Trigo J.M.,University Pompeu Fabra | Martin-Garcia E.,University Pompeu Fabra | Berrendero F.,University Pompeu Fabra | Robledo P.,University Pompeu Fabra | And 2 more authors.
Drug and Alcohol Dependence | Year: 2010

Drug addiction is a chronic brain disorder leading to complex adaptive changes within the brain reward circuits that involve several neurotransmitters. One of the neurochemical systems that plays a pivotal role in different aspects of addiction is the endogenous opioid system (EOS). Opioid receptors and endogenous opioid peptides are largely distributed in the mesolimbic system and modulate dopaminergic activity within these reward circuits. Chronic exposure to the different prototypical drugs of abuse, including opioids, alcohol, nicotine, psychostimulants and cannabinoids has been reported to produce significant alterations within the EOS, which seem to play an important role in the development of the addictive process. In this review, we will describe the adaptive changes produced by different drugs of abuse on the EOS, and the current knowledge about the contribution of each component of this neurobiological system to their addictive properties. © 2009 Elsevier Ireland Ltd. Source


Muntasell A.,University Pompeu Fabra | Magri G.,University Pompeu Fabra | Pende D.,Istituto Nazionale per la Ricerca sul Cancro | Angulo A.,Institute dinvestigacions Biomediques August Pi i Sunyer IDIBAPS | Lopez-Botet M.,Institute Municipal dInvestigacio Medica IMIM
Blood | Year: 2010

The NKG2D receptor activates natural killer (NK) cell cytotoxicity and cytokine production on recognition of self-molecules induced by cellular stress under different conditions such as viral infections. The importance of NKG2D in the immune response to human cytomegalovirus (HCMV) is supported by the identification of several viral molecules that prevent the expression of NKG2D ligands by infected cells. In this study we report that, paradoxically, a significant, selective, and transient reduction of NKG2D expression on NK cells is detected during HCMV infection of peripheral blood mononuclear cells if needed. Antagonizing type I interferon (IFN), interleukin-12 (IL-12), and IFNγ prevented HCMV-induced down-regulation of surface NKG2D. Moreover, treatment of purified NK cells with recombinant IFNβ1 and IL-12 mimicked the effect, supporting a direct role of these cytokines in regulating NKG2D surface expression in NK cells. The loss of NKG2D expression selectively impaired NK-cell cytotoxicity against cells expressing NKG2D ligands but preserved the response triggered through other activating receptors. These results support that down-regulation of NKG2D expression on NK cells by cytokines with a key role in antiviral immune response may constitute a physiologic mechanism to control NK-cell reactivity against normal cells expressing NKG2D ligands in the context of inflammatory responses to viral infections. © 2010 by The American Society of Hematology. Source


Pique-Regi R.,University of Southern California | Caceres A.,Center for Research in Environmental Epidemiology | Caceres A.,Institute Municipal dInvestigacio Medica IMIM | Gonzalez J.R.,Center for Research in Environmental Epidemiology | And 2 more authors.
BMC Bioinformatics | Year: 2010

Background: Genome-wide association studies (GWAS) using Copy Number Variation (CNV) are becoming a central focus of genetic research. CNVs have successfully provided target genome regions for some disease conditions where simple genetic variation (i.e., SNPs) has previously failed to provide a clear association.Results: Here we present a new R package, that integrates: (i) data import from most common formats of Affymetrix, Illumina and aCGH arrays; (ii) a fast and accurate segmentation algorithm to call CNVs based on Genome Alteration Detection Analysis (GADA); and (iii) functions for displaying and exporting the Copy Number calls, identification of recurrent CNVs, multivariate analysis of population structure, and tools for performing association studies. Using a large dataset containing 270 HapMap individuals (Affymetrix Human SNP Array 6.0 Sample Dataset) we demonstrate a flexible pipeline implemented with the package. It requires less than one minute per sample (3 million probe arrays) on a single core computer, and provides a flexible parallelization for very large datasets. Case-control data were generated from the HapMap dataset to demonstrate a GWAS analysis.Conclusions: The package provides the tools for creating a complete integrated pipeline from data normalization to statistical association. It can effciently handle a massive volume of data consisting of millions of genetic markers and hundreds or thousands of samples with very accurate results. © 2010 Pique-Regi et al; licensee BioMed Central Ltd. Source


Caceres A.,Institute Municipal dInvestigacio Medica IMIM | Sindi S.S.,Brown University | Raphael B.J.,Brown University | Caceres M.,Autonomous University of Barcelona | And 3 more authors.
BMC Bioinformatics | Year: 2012

Background: Polymorphic inversions are a source of genetic variability with a direct impact on recombination frequencies. Given the difficulty of their experimental study, computational methods have been developed to infer their existence in a large number of individuals using genome-wide data of nucleotide variation. Methods based on haplotype tagging of known inversions attempt to classify individuals as having a normal or inverted allele. Other methods that measure differences between linkage disequilibrium attempt to identify regions with inversions but unable to classify subjects accurately, an essential requirement for association studies.Results: We present a novel method to both identify polymorphic inversions from genome-wide genotype data and classify individuals as containing a normal or inverted allele. Our method, a generalization of a published method for haplotype data 1, utilizes linkage between groups of SNPs to partition a set of individuals into normal and inverted subpopulations. We employ a sliding window scan to identify regions likely to have an inversion, and accumulation of evidence from neighboring SNPs is used to accurately determine the inversion status of each subject. Further, our approach detects inversions directly from genotype data, thus increasing its usability to current genome-wide association studies (GWAS).Conclusions: We demonstrate the accuracy of our method to detect inversions and classify individuals on principled-simulated genotypes, produced by the evolution of an inversion event within a coalescent model 2. We applied our method to real genotype data from HapMap Phase III to characterize the inversion status of two known inversions within the regions 17q21 and 8p23 across 1184 individuals. Finally, we scan the full genomes of the European Origin (CEU) and Yoruba (YRI) HapMap samples. We find population-based evidence for 9 out of 15 well-established autosomic inversions, and for 52 regions previously predicted by independent experimental methods in ten (9+1) individuals 34. We provide efficient implementations of both genotype and haplotype methods as a unified R package inveRsion. © 2012 Cáceres et al; licensee BioMed Central Ltd. Source


Farriols C.,Institute Municipal dInvestigacio Medica IMIM | Ferrandez O.,Institute Municipal dInvestigacio Medica IMIM | Planas J.,Institute Municipal dInvestigacio Medica IMIM | Ortiz P.,Institute Municipal dInvestigacio Medica IMIM | And 3 more authors.
Journal of Pain and Symptom Management | Year: 2012

Context: Psychiatric disorders are frequently underdiagnosed and undertreated in advanced cancer patients. Objectives: To assess changes in the prescription of psychotropic drugs in terminally ill patients. Methods: All patients with advanced disease receiving palliative care between 2002 and 2009 were eligible. The consumption of benzodiazepines, antipsychotics, and antidepressants for the years 2002, 2006, and 2009 was compared. Data on the percentage and profile of psychotropic drugs prescribed were collected. Results: The study population included 840 patients (241 in 2002, 274 in 2006, and 325 in 2009). The percentage of patients treated with psychotropic drugs increased from 82.2% in 2002 to 90.2% in 2009 (P = 0.006) and the mean number of drugs per patient from 1.66 in 2002 to 2.16 in 2006 (P = 0.003), and to 2.35 in 2009 (P < 0.001). Benzodiazepines were prescribed to 72.6% of patients in 2002 and 84% in 2009 (P = 0.001), with lorazepam and midazolam as the most frequently used medications. The use of antipsychotics increased from 26.1% in 2002 to 37.2% in 2006 (P = 0.007) and to 40% in 2009 (P = 0.001), with haloperidol and risperidone as the most commonly prescribed. Antidepressants were prescribed to 17.8% in 2002, 28.1% in 2006 (P = 0.006), and 27.1% in 2009 (P = 0.010), with mirtazapine, citalopram, escitalopram, and duloxetine as the most frequent. Conclusion: Between 2002 and 2009, there was a significant increase in the use of psychotropic drugs and a change in the profile of drugs prescribed. © 2012 U.S. Cancer Pain Relief Committee Published by Elsevier Inc. All rights reserved. Source

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