996 resultados para perpetration trait anger


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We report the identification of quantitative trait loci (QTL) affecting carcass composition, carcass length, fat deposition and lean meat content using a genome scan across 462 animals from a combined intercross and backcross between Hampshire and Landrace pigs. Data were analysed using multiple linear regression fitting additive and dominance effects. This model was compared with a model including a parent-of-origin effect to spot evidence of imprinting. Several precisely defined muscle phenotypes were measured in order to dissect body composition in more detail. Three significant QTL were detected in the study at the 1% genome-wide level, and twelve significant QTL were detected at the 5% genome-wide level. These QTL comprise loci affecting fat deposition and lean meat content on SSC1, 4, 9, 10, 13 and 16, a locus on SSC2 affecting the ratio between weight of meat and bone in back and weight of meat and bone in ham and two loci affecting carcass length on SSC12 and 17. The well-defined phenotypes in this study enabled us to detect QTL for sizes of individual muscles and to obtain information of relevance for the description of the complexity underlying other carcass traits.

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This meta-analysis synthesizes the available data on the strength of association between anger and posttraumatic stress disorder (PTSD) and between hostility and PTSD, covering 39 studies with trauma-exposed adults. Effect sizes did not differ for anger and hostility, which could therefore be combined; effect sizes for anger expression variables were analyzed separately. The analyses revealed large effects. The weighted mean effect size (r) was .48 for anger–hostility, .29 for anger out, .53 for anger in, and -.44 for anger control. Moderator analyses were conducted for anger–hostility, showing that effect sizes were substantially larger with increasing time since the event and that effect sizes were larger in samples with military war experience than in samples that had experienced other types of traumatic events.

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The aim of many genetic studies is to locate the genomic regions (called quantitative trait loci, QTLs) that contribute to variation in a quantitative trait (such as body weight). Confidence intervals for the locations of QTLs are particularly important for the design of further experiments to identify the gene or genes responsible for the effect. Likelihood support intervals are the most widely used method to obtain confidence intervals for QTL location, but the non-parametric bootstrap has also been recommended. Through extensive computer simulation, we show that bootstrap confidence intervals are poorly behaved and so should not be used in this context. The profile likelihood (or LOD curve) for QTL location has a tendency to peak at genetic markers, and so the distribution of the maximum likelihood estimate (MLE) of QTL location has the unusual feature of point masses at genetic markers; this contributes to the poor behavior of the bootstrap. Likelihood support intervals and approximate Bayes credible intervals, on the other hand, are shown to behave appropriately.

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The etiology of complex diseases is heterogeneous. The presence of risk alleles in one or more genetic loci affects the function of a variety of intermediate biological pathways, resulting in the overt expression of disease. Hence, there is an increasing focus on identifying the genetic basis of disease by sytematically studying phenotypic traits pertaining to the underlying biological functions. In this paper we focus on identifying genetic loci linked to quantitative phenotypic traits in experimental crosses. Such genetic mapping methods often use a one stage design by genotyping all the markers of interest on the available subjects. A genome scan based on single locus or multi-locus models is used to identify the putative loci. Since the number of quantitative trait loci (QTLs) is very likely to be small relative to the number of markers genotyped, a one-stage selective genotyping approach is commonly used to reduce the genotyping burden, whereby markers are genotyped solely on individuals with extreme trait values. This approach is powerful in the presence of a single quantitative trait locus (QTL) but may result in substantial loss of information in the presence of multiple QTLs. Here we investigate the efficiency of sequential two stage designs to identify QTLs in experimental populations. Our investigations for backcross and F2 crosses suggest that genotyping all the markers on 60% of the subjects in Stage 1 and genotyping the chromosomes significant at 20% level using additional subjects in Stage 2 and testing using all the subjects provides an efficient approach to identify the QTLs and utilizes only 70% of the genotyping burden relative to a one stage design, regardless of the heritability and genotyping density. Complex traits are a consequence of multiple QTLs conferring main effects as well as epistatic interactions. We propose a two-stage analytic approach where a single-locus genome scan is conducted in Stage 1 to identify promising chromosomes, and interactions are examined using the loci on these chromosomes in Stage 2. We examine settings under which the two-stage analytic approach provides sufficient power to detect the putative QTLs.

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BACKGROUND: It is well known that there are specific peripheral activation patterns associated with the emotional valence of sounds. However, it is unclear how these effects adapt over time. The personality traits influencing these processes are also not clear. Anxiety disorders influence the autonomic activation related to emotional processing. However, personality anxiety traits have never been studied in the context of affective auditory stimuli. METHODS: Heart rate, skin conductance, zygomatic muscle activity and subjective rating of emotional valence and arousal were recorded in healthy subjects during the presentation of pleasant, unpleasant, and neutral sounds. Recordings were repeated 1 week later to examine possible time-dependent changes related to habituation and sensitization processes. RESULTS AND CONCLUSION: There was not a generalized habituation or sensitization process related to the repeated presentation of affective sounds, but rather, specific adaptation processes for each physiological measure. These observations are consistent with previous studies performed with affective pictures and simple tones. Thus, the measures of skin conductance activity showed the strongest changes over time, including habituation during the first presentation session and sensitization at the end of the second presentation session, whereas the facial electromyographic activity habituated only for the neutral stimuli and the heart rate did not habituate at all. Finally, we showed that the measure of personality trait anxiety influenced the orienting reaction to affective sounds, but not the adaptation processes related to the repeated presentation of these sounds.

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The aim of this study was to identify quantitative trait loci (QTL) for osteochondrosis (OC) and palmar/plantar osseous fragments (POF) in fetlock joints in a whole-genome scan of 219 South German Coldblood horses. Symptoms of OC and POF were checked by radiography in 117 South German Coldblood horses at a mean age of 17 months. The radiographic examination comprised the fetlock and hock joints of all limbs. The genome scan included 157 polymorphic microsatellite markers. All microsatellite markers were equally spaced over the 31 autosomes and the X chromosome, with an average distance of 17.7 cM and a mean polymorphism information content (PIC) of 63%. Sixteen chromosomes harbouring putative QTL regions were further investigated by genotyping the animals with 93 additional markers. QTL that had chromosome-wide significance by non-parametric Z-means and LOD scores were found on 10 chromosomes. This included seven QTL for fetlock OC and one QTL on ECA18 associated with hock OC and fetlock OC. Significant QTL for POF in fetlock joints were located on equine chromosomes 1, 4, 8, 12 and 18. This genome scan is an important step towards the identification of genes responsible for OC in horses.

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Arabidopsis thaliana has emerged as a leading model species in plant genetics and functional genomics including research on the genetic causes of heterosis. We applied a triple testcross (TTC) design and a novel biometrical approach to identify and characterize quantitative trait loci (QTL) for heterosis of five biomass-related traits by (i) estimating the number, genomic positions, and genetic effects of heterotic QTL, (ii) characterizing their mode of gene action, and (iii) testing for presence of epistatic effects by a genomewide scan and marker x marker interactions. In total, 234 recombinant inbred lines (RILs) of Arabidopsis hybrid C24 x Col-0 were crossed to both parental lines and their F1 and analyzed with 110 single-nucleotide polymorphism (SNP) markers. QTL analyses were conducted using linear transformations Z1, Z2, and Z3 calculated from the adjusted entry means of TTC progenies. With Z1, we detected 12 QTL displaying augmented additive effects. With Z2, we mapped six QTL for augmented dominance effects. A one-dimensional genome scan with Z3 revealed two genomic regions with significantly negative dominance x additive epistatic effects. Two-way analyses of variance between marker pairs revealed nine digenic epistatic interactions: six reflecting dominance x dominance effects with variable sign and three reflecting additive x additive effects with positive sign. We conclude that heterosis for biomass-related traits in Arabidopsis has a polygenic basis with overdominance and/or epistasis being presumably the main types of gene action.

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OBJECTIVE: Define links between psychosocial parameters and metabolic variables in obese females before and after a low-calorie diet. METHOD: Nine female obese patients (age 36.1 +/- 7.1 years, body mass index [BMI] > 30 kg/m2) were investigated before and after a 6-week low-calorie diet accompanied by behavior therapy. Blood lipids, insulin sensitivity (Bergman protocol), fat distribution (by dual-energy X-ray absorptiometry [DEXA]), as well as psychological parameters such as depression, anger, anxiety, symptom load, and well-being, were assessed before and after the dieting period. RESULTS: The females lost 9.6 +/- 2.8 kg (p < .0001) of body weight, their BMI was reduced by 3.5 +/- 0.3 kg/m2 (p < .0001), and insulin sensitivity increased from 3.0 +/- 1.8 to 4.3 +/- 1.5 mg/kg (p = .05). Their abdominal fat content decreased from 22.3 +/- 5.5 to 18.9 +/- 4.5 kg (p < .0001). In parallel, psychological parameters such as irritability (p < .05) and cognitive control (p < .0001) increased, whereas feelings of hunger (p < .05), externality (p < .05), interpersonal sensitivity (p < .01), paranoid ideation (p < .05), psychoticism (p < .01), and global severity index (p < .01) decreased. Prospectively, differences in body fat (percent) were correlated to nervousness (p < .05). Waist-to-hip ratio (WHR) differences were significantly correlated to sociability (p < .05) and inversely to emotional instability (p < .05), whereas emotional instability was inversely correlated to differences in insulin sensitivity (p < .01). DISCUSSION: Weight reduction may lead to better somatic risk factor control. Women with more nervousness and better sociability at the beginning of a diet period may lose more weight than others.

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Aims Phenotypic optimality models neglect genetics. However, especially when heterozygous genotypes ire fittest, evolving allele, genotype and phenotype frequencies may not correspond to predicted optima. This was not previously addressed for organisms with complex life histories. Methods Therefore, we modelled the evolution of a fitness-relevant trait of clonal plants, stolon internode length. We explored the likely case of air asymmetric unimodal fitness profile with three model types. In constant selection models (CSMs), which are gametic, but not spatially explicit, evolving allele frequencies in the one-locus and five-loci cases did not correspond to optimum stolon internode length predicted by the spatially explicit, but not gametic, phenotypic model. This deviation was due to the asymmetry of the fitness profile. Gametic, spatially explicit individual-based (SEIB) modeling allowed us relaxing the CSM assumptions of constant selection with exclusively sexual reproduction. Important findings For entirely vegetative or sexual reproduction, predictions. of the gametic SEIB model were close to the ones of spatially explicit CSMs gametic phenotypic models, hut for mixed modes of reproduction they appoximated those of gametic, not spatially explicit CSMs. Thus, in contrast to gametic SEIB models, phenotypic models and, especially for few loci, also CSMs can be very misleading. We conclude that the evolution of trails governed by few quantitative trait loci appears hardly predictable by simple models, that genetic algorithms aiming at technical optimization may actually, miss the optimum and that selection may lead to loci with smaller effects, in derived compared with ancestral lines.