Attachment styles and personal growth following romantic breakups: The mediating roles of distress, rumination, and tendency to rebound

© 2013 Marshall et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.This article has been made available through the Brunel Open Access Publishing Fund.The purpose of this research was to examine the associations of attachment anxiety and avoidance with personal growth following relationship dissolution, and to test breakup distress, rumination, and tendency to rebound with new partners as mediators of these associations. Study 1 (N = 411) and Study 2 (N = 465) measured attachment style, breakup distress, and personal growth; Study 2 additionally measured ruminative reflection, brooding, and proclivity to rebound with new partners. Structural equation modelling revealed in both studies that anxiety was indirectly associated with greater personal growth through heightened breakup distress, whereas avoidance was indirectly associated with lower personal growth through inhibited breakup distress. Study 2 further showed that the positive association of breakup distress with personal growth was accounted for by enhanced reflection and brooding, and that anxious individuals’ greater personal growth was also explained by their proclivity to rebound. These findings suggest that anxious individuals’ hyperactivated breakup distress may act as a catalyst for personal growth by promoting the cognitive processing of breakup-related thoughts and emotions, whereas avoidant individuals’ deactivated distress may inhibit personal growth by suppressing this cognitive work

H1-antihistamines for chronic spontaneous urticaria

Background Chronic spontaneous urticaria (CSU) is characterised by the development of crops of red, itchy, raised weals or hives with no identifiable external cause. Objectives To assess the effects of H1-antihistamines for CSU. Search methods We searched the following databases up to June 2014: Cochrane Skin Group Specialised Register, CENTRAL (2014, Issue 5), MEDLINE (from 1946), EMBASE (from 1974) and PsycINFO (from 1806). We searched five trials registers and checked articles for references to relevant randomised controlled trials. Selection criteria We included randomised controlled trials of H1-antihistamines for CSU. Interventions included single therapy or a combination of H1-antihistamines compared with no treatment (placebo) or another active pharmacological compound at any dose. Data collection and analysis We used standard methodological procedures as expected by The Cochrane Collaboration. Our primary outcome measures were proportion of participants with complete suppression of urticaria: 'good or excellent' response, 50% or greater improvement in quality of life measures, and adverse events. We present risk ratios (RR) with 95% confidence intervals (CIs). Main results We identified 73 studies (9759 participants); 34 studies provided data for 23 comparisons. The duration of the intervention was up to two weeks (short-term) or longer than two weeks and up to three months (intermediate-term). Cetirizine 10 mg once daily in the short term and in the intermediate term led to complete suppression of urticaria by more participants than was seen with placebo (RR 2.72, 95% CI 1.51 to 4.91). For this same outcome, comparison of desloratadine versus placebo in the intermediate term (5 mg) (RR 37.00, 95% CI 2.31 to 593.70) and in the short term (20 mg) (RR 15.97, 95% CI 1.04 to 245.04) favoured desloratadine, but no differences were seen between 5 mg and 10 mg for short-term treatment. Levocetirizine 20 mg per day (short-term) was more effective for complete suppression of urticaria compared with placebo (RR 20.87, 95% CI 1.37 to 317.60), and at 5 mg was effective in the intermediate term (RR 52.88, 95% CI 3.31 to 843.81) but not in the short term, nor was 10 mg effective in the short term. Rupatadine at 10 mg and 20 mg in the intermediate term achieved a 'good or excellent response' compared with placebo (RR 1.35, 95% CI 1.03 to 1.77). Loratadine (10 mg) versus placebo (RR 1.86, 95% CI 0.91 to 3.79) and loratadine (10 mg) versus cetirizine (10 mg) (RR 1.05, 95% CI 0.76 to 1.43) over short-term and intermediate-term treatment showed no significant difference for 'good or excellent response' or for complete suppression of urticaria, respectively. Loratadine (10 mg) versus desloratadine (5 mg) (intermediate-term) showed no statistically significant difference for complete suppression of urticaria (RR 0.91, 95% CI 0.78 to 1.06) or for 'good or excellent response' (RR 1.04, 95% CI 0.64 to 1.71). For loratadine (10 mg) versus mizolastine (10 mg) (intermediate-term), no statistically significant difference was seen for complete suppression of urticaria (RR 0.86, 95% CI 0.64 to 1.16) or for 'good or excellent response' (RR 0.88, 95% CI 0.55 to 1.42). Loratadine (10 mg) versus emedastine (2 mg) (intermediate-term) showed no statistically significant difference for complete suppression (RR 1.04, 95% CI 0.78 to 1.39) or for 'good or excellent response' (RR 1.09, 95% CI 0.96 to 1.24); the quality of the evidence was moderate for this comparison. No difference in short-term treatment was noted between loratadine (10 mg) and hydroxyzine (25 mg) in terms of complete suppression (RR 1.00, 95% CI 0.32 to 3.10). When desloratadine (5 to 20 mg) was compared with levocetirizine (5 to 20 mg), levocetirizine appeared to be the more effective (P value <0.02). In a comparison of fexofenadine versus cetirizine, more participants in the cetirizine group showed complete suppression of urticaria (P value <0.001). Adverse events leading to withdrawals were not significantly different in the following comparisons: cetirizine versus placebo at 10 mg and 20 mg (RR 3.00, 95% CI 0.68 to 13.22); desloratadine 5 mg versus placebo (RR 1.46, 95% CI 0.42 to 5.10); loratadine 10 mg versus mizolastine 10 mg (RR 0.38, 95% CI 0.04 to 3.60); loratadine 10 mg versus emedastine 2 mg (RR 1.09, 95% CI 0.07 to 17.14); cetirizine 10 mg versus hydroxyzine 25 mg (RR 0.78, 95% CI 0.25 to 2.45); and hydroxyzine 25 mg versus placebo (RR 3.64, 95% CI 0.77 to 17.23), all intermediate term. No difference was seen between loratadine 10 mg versus mizolastine 10 mg in the proportion of participants with at least 50% improvement in quality of life (RR 3.21, 95% CI 0.32 to 32.33). Authors' conclusions Although the results of our review indicate that at standard doses of treatment, several antihistamines are effective when compared with placebo, all results were gathered from a few studies or, in some cases, from single-study estimates. The quality of the evidence was affected by the small number of studies in each comparison and the small sample size for many of the outcomes, prompting us to downgrade the quality of evidence for imprecision (unless stated for each comparison, the quality of the evidence was low). No single H1-antihistamine stands out as most effective. Cetirizine at 10 mg once daily in the short term and in the intermediate term was found to be effective in completely suppressing urticaria. Evidence is limited for desloratadine given at 5 mg once daily in the intermediate term and at 20 mg in the short term. Levocetirizine at 5 mg in the intermediate but not short term was effective for complete suppression. Levocetirizine 20 mg was effective in the short term, but 10 mg was not. No difference in rates of withdrawal due to adverse events was noted between active and placebo groups. Evidence for improvement in quality of life was insufficient

Quantum Convolutional Neural Networks

We introduce and analyze a novel quantum machine learning model motivated by convolutional neural networks. Our quantum convolutional neural network (QCNN) makes use of only $O(\log(N))$ variational parameters for input sizes of $N$ qubits, allowing for its efficient training and implementation on realistic, near-term quantum devices. The QCNN architecture combines the multi-scale entanglement renormalization ansatz and quantum error correction. We explicitly illustrate its potential with two examples. First, QCNN is used to accurately recognize quantum states associated with 1D symmetry-protected topological phases. We numerically demonstrate that a QCNN trained on a small set of exactly solvable points can reproduce the phase diagram over the entire parameter regime and also provide an exact, analytical QCNN solution. As a second application, we utilize QCNNs to devise a quantum error correction scheme optimized for a given error model. We provide a generic framework to simultaneously optimize both encoding and decoding procedures and find that the resultant scheme significantly outperforms known quantum codes of comparable complexity. Finally, potential experimental realization and generalizations of QCNNs are discussed.Comment: 12 pages, 11 figures. v2: New application to optimizing quantum error correction codes, added sample complexity analysis, more details for experimental realizations, and other minor revision

Experimental annotation of post-translational features and translated coding regions in the pathogen Salmonella Typhimurium

<p>Abstract</p> <p>Background</p> <p>Complete and accurate genome annotation is crucial for comprehensive and systematic studies of biological systems. However, determining protein-coding genes for most new genomes is almost completely performed by inference using computational predictions with significant documented error rates (> 15%). Furthermore, gene prediction programs provide no information on biologically important post-translational processing events critical for protein function.</p> <p>Results</p> <p>We experimentally annotated the bacterial pathogen <it>Salmonella </it>Typhimurium 14028, using "shotgun" proteomics to accurately uncover the translational landscape and post-translational features. The data provide protein-level experimental validation for approximately half of the predicted protein-coding genes in <it>Salmonella </it>and suggest revisions to several genes that appear to have incorrectly assigned translational start sites, including a potential novel alternate start codon. Additionally, we uncovered 12 non-annotated genes missed by gene prediction programs, as well as evidence suggesting a role for one of these novel ORFs in <it>Salmonella </it>pathogenesis. We also characterized post-translational features in the <it>Salmonella </it>genome, including chemical modifications and proteolytic cleavages. We find that bacteria have a much larger and more complex repertoire of chemical modifications than previously thought including several novel modifications. Our <it>in vivo </it>proteolysis data identified more than 130 signal peptide and N-terminal methionine cleavage events critical for protein function.</p> <p>Conclusion</p> <p>This work highlights several ways in which application of proteomics data can improve the quality of genome annotations to facilitate novel biological insights and provides a comprehensive proteome map of <it>Salmonella </it>as a resource for systems analysis.</p

Gene expression patterns in the hippocampus and amygdala of endogenous depression and chronic stress models

The etiology of depression is still poorly understood, but two major causative hypotheses have been put forth: the monoamine deficiency and the stress hypotheses of depression. We evaluate these hypotheses using animal models of endogenous depression and chronic stress. The endogenously depressed rat and its control strain were developed by bidirectional selective breeding from the Wistar–Kyoto (WKY) rat, an accepted model of major depressive disorder (MDD). The WKY More Immobile (WMI) substrain shows high immobility/despair-like behavior in the forced swim test (FST), while the control substrain, WKY Less Immobile (WLI), shows no depressive behavior in the FST. Chronic stress responses were investigated by using Brown Norway, Fischer 344, Lewis and WKY, genetically and behaviorally distinct strains of rats. Animals were either not stressed (NS) or exposed to chronic restraint stress (CRS). Genome-wide microarray analyses identified differentially expressed genes in hippocampi and amygdalae of the endogenous depression and the chronic stress models. No significant difference was observed in the expression of monoaminergic transmission-related genes in either model. Furthermore, very few genes showed overlapping changes in the WMI vs WLI and CRS vs NS comparisons, strongly suggesting divergence between endogenous depressive behavior- and chronic stress-related molecular mechanisms. Taken together, these results posit that although chronic stress may induce depressive behavior, its molecular underpinnings differ from those of endogenous depression in animals and possibly in humans, suggesting the need for different treatments. The identification of novel endogenous depression-related and chronic stress response genes suggests that unexplored molecular mechanisms could be targeted for the development of novel therapeutic agents

Stress System Dynamics during “Life As It Is Lived”: An Integrative Single-Case Study on a Healthy Woman

Little is known about the dynamic characteristics of stress system activity during “life as it is lived”. Using as representative a study design as possible, this investigation sought to gain insights into this area. A healthy 25-year-old woman collected her entire urine over a period of 63 days in 12-h intervals (126 measurements) to determine cortisol and neopterin (immune activation marker) levels. In addition, she filled out questionnaires on emotional state and daily routine in 12-h intervals, and was interviewed weekly to identify emotionally negative and positive everyday incidents. Adjusted cross-correlational analyses revealed that stressful incidents were associated with cyclic response patterns in both urinary cortisol and urinary neopterin concentrations. Urinary cortisol levels first decreased 12–24 h after stressful incidents occurred (lag 1: −.178; p = 0.048) and then increased a total of 72–84 h later (lag 6: +.224; p = 0.013). Urinary neopterin levels first increased 0–12 h before the occurrence of stressful incidents (−lag 1: +.185; p = 0.040) and then decreased a total of 48–60 h following such stressors (lag 4: −.181; p = 0.044). Decreases in urinary neopterin levels were also found 24–36 and 48–60 h after increases in pensiveness (lag 2: −.215; p = 0.017) and depressiveness (lag 4: −.221; p = 0.014), respectively. Findings on emotionally positive incidents sharply contrasted with those dealing with negative experiences. Positive incidents were followed first by urinary cortisol concentration increases within 12 h (lag 0: +.290; p = 0.001) and then by decreases after a total of 60–72 h (lag 5: −.186; p = 0.039). Urinary neopterin levels first decreased 12–24 h before positive incidents occurred (−lag 2: −.233; p = 0.010) and then increased a total of 12–24 h following these incidents (lag 1: +.222; p = 0.014). As with previous investigations on patients with systemic lupus erythematosus (SLE), this study showed that stress system response can be considerably longer and more complex and differentiated than findings from conventional group studies have suggested. Further integrative single-case studies will need to be conducted in order to draw firm conclusions about stress system dynamics under real-life conditions

A framework for evolutionary systems biology

<p>Abstract</p> <p>Background</p> <p>Many difficult problems in evolutionary genomics are related to mutations that have weak effects on fitness, as the consequences of mutations with large effects are often simple to predict. Current systems biology has accumulated much data on mutations with large effects and can predict the properties of knockout mutants in some systems. However experimental methods are too insensitive to observe small effects.</p> <p>Results</p> <p>Here I propose a novel framework that brings together evolutionary theory and current systems biology approaches in order to quantify small effects of mutations and their epistatic interactions <it>in silico</it>. Central to this approach is the definition of fitness correlates that can be computed in some current systems biology models employing the rigorous algorithms that are at the core of much work in computational systems biology. The framework exploits synergies between the realism of such models and the need to understand real systems in evolutionary theory. This framework can address many longstanding topics in evolutionary biology by defining various 'levels' of the adaptive landscape. Addressed topics include the distribution of mutational effects on fitness, as well as the nature of advantageous mutations, epistasis and robustness. Combining corresponding parameter estimates with population genetics models raises the possibility of testing evolutionary hypotheses at a new level of realism.</p> <p>Conclusion</p> <p>EvoSysBio is expected to lead to a more detailed understanding of the fundamental principles of life by combining knowledge about well-known biological systems from several disciplines. This will benefit both evolutionary theory and current systems biology. Understanding robustness by analysing distributions of mutational effects and epistasis is pivotal for drug design, cancer research, responsible genetic engineering in synthetic biology and many other practical applications.</p