131,150 research outputs found
NCAM1, TACR1 and NOS Genes and Temperament: A Study on Suicide Attempters and Controls
No full textSuicide, one of the leading causes of death among young adults, seems to be plausibly modulated by both genetic and personality factors. The aim of this study was to dissect the potential association between genetics and temperament in a sample of 111 suicide attempters and 289 healthy controls. We focused on 4 genes previously investigated in association with suicide on the same sample: the nitric oxide synthase 1 and 3 (NOS1 and NOS3), the neuronal cell adhesion molecule 1 (NCAM1), and the tachykinin receptor 1 (TACR1) genes. In particular, we investigated whether a set of genetic variants in these genes (NOS1 : rs2682826, rs1353939, rs693534; NOS3 : rs2070744, rs1799983, rs891512; NCAM1 : rs2301228, rs1884, rs1245113, rs1369816, rs2196456, rs584427; TACR1 : rs3771810, rs3771825, rs726506, rs1477157) were associated with temperamental traits at the Temperament and Character Inventory (TCI). No strong evidence was found for the association between TCI personality traits and the polymorphisms considered in the 4 genes, with the exception of an association between reward dependence trait and the rs2682826 SNP in NOS1 in the healthy sample. However, this result could be plausibly interpreted as a false-positive finding. In conclusion, our study did not support the thesis of a direct modulation of these genes on temperament; however, further studies on larger samples are clearly required in order to confirm our preliminary findings and to exclude any possible minor influence. Copyright (C) 2011 S. Karger AG, Base
Serotonergic genes and suicide: a systematic review.
No full textSuicide is one of the leading causes of death in the world. Its aetiology is complex and diverse, however, epidemiological studies show that suicidal behavior is partly heritable. Neurobiological evidence implicates serotonergic dysfunction in suicidality, stimulating genetic research to focus on genes related to the serotonergic system. In this paper, we review evidence from studies examining the association between various serotonergic genes (Tryptophan Hydroxylase genes: TPH1; TPH2, Serotonin Transporter gene: 5-HTTLPR in SLC6A4, Serotonin Receptor genes: HTR1A, HTR2A, HTR1B, HTR2C and Monoamine Oxidase A gene: MAOA) and suicidal behavior. The data show associations between variation on the TPH1 gene and 5-HTTLPR gene and violent suicidal behavior in Caucasian populations, with the least inconsistencies. Results are mixed for the TPH2 gene and serotonin receptor genes, but for some genes, studies that include haplotypic analyses or that examine a larger coding region of the genes tend to provide more reliable results. Findings on endophenotypes of suicidality, such as aggression and impulsivity traits, show positive associations for the TPH1, HTR2A, and MAOA genes, but need further replication, since negative associations are also occasionally reported. Since genes can only partially explain suicidal risk, several studies during the past decade have tried to incorporate environmental factors in the susceptibility model. Studies to date show that variation on the 5-HTTLPR, MAOA and HTR2A gene can interact with stressful life events to increase risk for suicidal behavior. Limitations of case-control studies are discussed and future considerations are put forward with regard to endophenotypic measurements and gene-environment interactions
S24-01 - Neuroticism: an Intermediate Phenotype for Major Depression
No full textThere is strong evidence for a heritability of major depression as shown by family, twin- and adoption studies. Several studies suggest a heritability for unipolar depression between 35 and 75% which is much lower than the heritability of bipolar disorder or schizophrenia. There is no doubt, that major depression is not caused by any single gene but it is a disease with complex genetic features. Furthermore, some subtypes, as early-onset or recurrent depression may have a higher heritability than other forms of depression. Neuroticism as an intermediate phenotype of MDD, which is a trait that reflects a tendency toward negative mood states, and has been linked to internalizing depressive conditions. For these reasons Dan Rujescu will present genome-wide and candidate gene studies, demonstrating a genetic approach for discovering potentially important pathogenic pathways for which clinically powerful (bio)markers may eventually be developed. He will discuss neuroticism as an intermediate phenotype of MDD, which is a trait that reflects a tendency toward negative mood states and has been linked to internalizing depressive conditions.</jats:p
Electroencephalographic risk markers of suicidal behaviour
No full textSince its inception nearly 100 years ago, EEG (electroencephalography) has offered a non-invasive approach to recording the intrinsic electrical activity of the brain. Despite its limitations and the advent of brain imaging techniques with superior spatial resolution, the millisecond temporal resolution of EEG makes it a valuable diagnostic tool in many clinical disciplines, including psychiatry. In this chapter, we review its use in the assessment of suicide risk in psychiatric patients. After a general introduction to the technique itself, the first section considers the findings from numerous studies that have investigated paroxysmal EEG dysrhythmias such as small sharp spikes and other abnormal sleep parameters (rapid-eye movement latency and duration) in relation to suicidal behaviour. We then outline why changes in EEG patterns in response to a range of aural and visual stimuli (event-related potentials) might offer the most robust means of detecting facets of personality such as impulsiveness/aggressiveness that often underpin suicidal behaviour. Finally, we look at the wider aspects of using EEG data as a predictor of suicidal behaviour and why this is problematic at the moment. ln the chapter summary, we draw together the findings into these three areas of EEG research and consider whether there is a case for extending the use of EEG as a routine adjunct to other diagnostic approaches for identifying suicidal behaviour in psychiatric patients close to release from inpatient care
MeSH term explosion and author rank improve expert recommendations
No full textInformation overload is an often-cited phenomenon that reduces the productivity, efficiency and efficacy of scientists. One challenge for scientists is to find appropriate collaborators in their research. The literature describes various solutions to the problem of expertise location, but most current approaches do not appear to be very suitable for expert recommendations in biomedical research. In this study, we present the development and initial evaluation of a vector space model-based algorithm to calculate researcher similarity using four inputs: 1) MeSH terms of publications; 2) MeSH terms and author rank; 3) exploded MeSH terms; and 4) exploded MeSH terms and author rank. We developed and evaluated the algorithm using a data set of 17,525 authors and their 22,542 papers. On average, our algorithms correctly predicted 2.5 of the top 5/10 coauthors of individual scientists. Exploded MeSH and author rank outperformed all other algorithms in accuracy, followed closely by MeSH and author rank. Our results show that the accuracy of MeSH term-based matching can be enhanced with other metadata such as author rank
Going Beyond Counting First Authors in Author Co-citation Analysis
No full textThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
"Closing the R&D Gap, Evaluating the Sources of R&D Spending"
No full textBoth spending and tax policies have been implemented in the United States with the goal of stimulating private sector research and development (R&D). Karier questions whether current R&D policy, especially the research and experimentation tax credit, can contribute to closing the gap between nondefense expenditures on R&D in the United States and such expenditures in other countries, such as Japan and Germany. He also explores possible changes to our current R&D policy to make it more effective.
Dispelling the Myths Behind First-author Citation Counts
No full textWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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