Shared cognition in childhood anxiety: interpretation bias in preschool children and their parents

Although interpretation bias has been associated with the development and/or maintenance of childhood anxiety, its origins remain unclear. The present study is the first to examine intergenerational transmission of this bias from parents to their preschool-aged children via the verbal information pathway. A community sample of fifty parent–child pairs was recruited. Parents completed measures of their own trait anxiety and interpretation bias, their child’s anxiety symptoms, and a written story-stem measure, to capture the way parents tell their children stories. Interpretation bias was assessed in preschool-aged children (aged between 2 years 7 months and 5 years 8 months) using an extended story-stem paradigm. Young children’s interpretation bias was not significantly associated with their own anxiety symptoms. Neither was there evidence for a significant association between parent and child interpretation bias. However, parents who reported they would tell their child one or more threatening story endings in the written story-stem task had significantly higher anxiety than those who did not include any threatening story endings. In turn, children whose parents did not include any threatening endings in their written stories had significantly lower threat interpretations on the child story-stem paradigm, compared to those with parents who included at least one threatening story ending. The results suggest that parental verbal information could play a role in the development of interpretation bias in young children

Measurement of the inclusive and dijet cross-sections of b-jets in pp collisions at sqrt(s) = 7 TeV with the ATLAS detector

The inclusive and dijet production cross-sections have been measured for jets containing b-hadrons (b-jets) in proton-proton collisions at a centre-of-mass energy of sqrt(s) = 7 TeV, using the ATLAS detector at the LHC. The measurements use data corresponding to an integrated luminosity of 34 pb^-1. The b-jets are identified using either a lifetime-based method, where secondary decay vertices of b-hadrons in jets are reconstructed using information from the tracking detectors, or a muon-based method where the presence of a muon is used to identify semileptonic decays of b-hadrons inside jets. The inclusive b-jet cross-section is measured as a function of transverse momentum in the range 20 < pT < 400 GeV and rapidity in the range |y| < 2.1. The bbbar-dijet cross-section is measured as a function of the dijet invariant mass in the range 110 < m_jj < 760 GeV, the azimuthal angle difference between the two jets and the angular variable chi in two dijet mass regions. The results are compared with next-to-leading-order QCD predictions. Good agreement is observed between the measured cross-sections and the predictions obtained using POWHEG + Pythia. MC@NLO + Herwig shows good agreement with the measured bbbar-dijet cross-section. However, it does not reproduce the measured inclusive cross-section well, particularly for central b-jets with large transverse momenta.Comment: 10 pages plus author list (21 pages total), 8 figures, 1 table, final version published in European Physical Journal

Observation of associated near-side and away-side long-range correlations in √sNN=5.02 TeV proton-lead collisions with the ATLAS detector

Two-particle correlations in relative azimuthal angle (Δϕ) and pseudorapidity (Δη) are measured in √sNN=5.02  TeV p+Pb collisions using the ATLAS detector at the LHC. The measurements are performed using approximately 1  μb-1 of data as a function of transverse momentum (pT) and the transverse energy (ΣETPb) summed over 3.1<η<4.9 in the direction of the Pb beam. The correlation function, constructed from charged particles, exhibits a long-range (2<|Δη|<5) “near-side” (Δϕ∼0) correlation that grows rapidly with increasing ΣETPb. A long-range “away-side” (Δϕ∼π) correlation, obtained by subtracting the expected contributions from recoiling dijets and other sources estimated using events with small ΣETPb, is found to match the near-side correlation in magnitude, shape (in Δη and Δϕ) and ΣETPb dependence. The resultant Δϕ correlation is approximately symmetric about π/2, and is consistent with a dominant cos⁡2Δϕ modulation for all ΣETPb ranges and particle pT

Impacts of climate change on plant diseases – opinions and trends

There has been a remarkable scientific output on the topic of how climate change is likely to affect plant diseases in the coming decades. This review addresses the need for review of this burgeoning literature by summarizing opinions of previous reviews and trends in recent studies on the impacts of climate change on plant health. Sudden Oak Death is used as an introductory case study: Californian forests could become even more susceptible to this emerging plant disease, if spring precipitations will be accompanied by warmer temperatures, although climate shifts may also affect the current synchronicity between host cambium activity and pathogen colonization rate. A summary of observed and predicted climate changes, as well as of direct effects of climate change on pathosystems, is provided. Prediction and management of climate change effects on plant health are complicated by indirect effects and the interactions with global change drivers. Uncertainty in models of plant disease development under climate change calls for a diversity of management strategies, from more participatory approaches to interdisciplinary science. Involvement of stakeholders and scientists from outside plant pathology shows the importance of trade-offs, for example in the land-sharing vs. sparing debate. Further research is needed on climate change and plant health in mountain, boreal, Mediterranean and tropical regions, with multiple climate change factors and scenarios (including our responses to it, e.g. the assisted migration of plants), in relation to endophytes, viruses and mycorrhiza, using long-term and large-scale datasets and considering various plant disease control methods

Drug Repurposing: A Systematic Approach to Evaluate Candidate Oral Neuroprotective Interventions for Secondary Progressive Multiple Sclerosis

Objective: To develop and implement an evidence based framework to select, from drugs already licenced, candidate oral neuroprotective drugs to be tested in secondary progressive multiple sclerosis. Design: Systematic review of clinical studies of oral putative neuroprotective therapies in MS and four other neurodegenerative diseases with shared pathological features, followed by systematic review and meta-analyses of the in vivo experimental data for those interventions. We presented summary data to an international multi-disciplinary committee, which assessed each drug in turn using pre-specified criteria including consideration of mechanism of action. Results: We identified a short list of fifty-two candidate interventions. After review of all clinical and pre-clinical evidence we identified ibudilast, riluzole, amiloride, pirfenidone, fluoxetine, oxcarbazepine, and the polyunsaturated fatty-acid class (Linoleic Acid, Lipoic acid; Omega-3 fatty acid, Max EPA oil) as lead candidates for clinical evaluation. Conclusions: We demonstrate a standardised and systematic approach to candidate identification for drug rescue and repurposing trials that can be applied widely to neurodegenerative disorders

Identification of metabolic pathways influenced by the G-protein coupled receptors GprB and GprD in Aspergillus nidulans

Heterotrimeric G-protein-mediated signaling pathways play a pivotal role in transmembrane signaling in eukaryotes. Our main aim was to identify signaling pathways regulated by A. nidulans GprB and GprD G-protein coupled receptors (GPCRs). When these two null mutant strains were compared to the wild-type strain, the DeltagprB mutant showed an increased protein kinase A (PKA) activity while growing in glucose 1% and during starvation. In contrast, the DeltagprD has a much lower PKA activity upon starvation. Transcriptomics and (1)H NMR-based metabolomics were performed on two single null mutants grown on glucose. We noted modulation in the expression of 11 secondary metabolism gene clusters when the DeltagprB and DeltagprD mutant strains were grown in 1% glucose. Several members of the sterigmatocystin-aflatoxin gene cluster presented down-regulation in both mutant strains. The genes of the NR-PKS monodictyphenone biosynthesis cluster had overall increased mRNA accumulation in DeltagprB, while in the DeltagprD mutant strain the genes had decreased mRNA accumulation. Principal component analysis of the metabolomic data demonstrated that there was a significant metabolite shift in the DeltagprD strain. The (1)H NMR analysis revealed significant expression of essential amino acids with elevated levels in the DeltagprD strain, compared to the wild-type and DeltagprB strains. With the results, we demonstrated the differential expression of a variety of genes related mainly to secondary metabolism, sexual development, stress signaling, and amino acid metabolism. We propose that the absence of GPCRs triggered stress responses at the genetic level. The data suggested an intimate relationship among different G-protein coupled receptors, fine-tune regulation of secondary and amino acid metabolisms, and fungal development

Search for R-parity-violating supersymmetry in events with four or more leptons in sqrt(s) =7 TeV pp collisions with the ATLAS detector

A search for new phenomena in final states with four or more leptons (electrons or muons) is presented. The analysis is based on 4.7 fb−1 of $\sqrt{s}=7\;\mathrm{TeV}$ proton-proton collisions delivered by the Large Hadron Collider and recorded with the ATLAS detector. Observations are consistent with Standard Model expectations in two signal regions: one that requires moderate values of missing transverse momentum and another that requires large effective mass. The results are interpreted in a simplified model of R-parity-violating supersymmetry in which a 95% CL exclusion region is set for charged wino masses up to 540 GeV. In an R-parity-violating MSUGRA/CMSSM model, values of m 1/2 up to 820 GeV are excluded for 10 < tan β < 40

Study of hadronic event-shape variables in multijet final states in pp collisions at √s=7 TeV

Peer reviewe

Constraints on parton distribution functions and extraction of the strong coupling constant from the inclusive jet cross section in pp collisions at √s=7 TeV

Peer reviewe

Segmentation and intensity estimation for microarray images with saturated pixels

<p>Abstract</p> <p>Background</p> <p>Microarray image analysis processes scanned digital images of hybridized arrays to produce the input spot-level data for downstream analysis, so it can have a potentially large impact on those and subsequent analysis. Signal saturation is an optical effect that occurs when some pixel values for highly expressed genes or peptides exceed the upper detection threshold of the scanner software (2¹⁶- 1 = 65, 535 for 16-bit images). In practice, spots with a sizable number of saturated pixels are often flagged and discarded. Alternatively, the saturated values are used without adjustments for estimating spot intensities. The resulting expression data tend to be biased downwards and can distort high-level analysis that relies on these data. Hence, it is crucial to effectively correct for signal saturation.</p> <p>Results</p> <p>We developed a flexible mixture model-based segmentation and spot intensity estimation procedure that accounts for saturated pixels by incorporating a censored component in the mixture model. As demonstrated with biological data and simulation, our method extends the dynamic range of expression data beyond the saturation threshold and is effective in correcting saturation-induced bias when the lost information is not tremendous. We further illustrate the impact of image processing on downstream classification, showing that the proposed method can increase diagnostic accuracy using data from a lymphoma cancer diagnosis study.</p> <p>Conclusions</p> <p>The presented method adjusts for signal saturation at the segmentation stage that identifies a pixel as part of the foreground, background or other. The cluster membership of a pixel can be altered versus treating saturated values as truly observed. Thus, the resulting spot intensity estimates may be more accurate than those obtained from existing methods that correct for saturation based on already segmented data. As a model-based segmentation method, our procedure is able to identify inner holes, fuzzy edges and blank spots that are common in microarray images. The approach is independent of microarray platform and applicable to both single- and dual-channel microarrays.</p