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

Radiological Decision Aid to determine suitability for medial unicompartmental knee arthroplasty: development and preliminary validation

Aims: An evidence-based radiographic Decision Aid for meniscal-bearing unicompartmental knee arthroplasty (UKA) has been developed and this study investigates its performance at an independent centre. Patients: and Methods Pre-operative radiographs, including stress views, from a consecutive cohort of 550 knees undergoing arthroplasty (UKA or total knee arthroplasty; TKA) by a single-surgeon were assessed. Suitability for UKA was determined using the Decision Aid, with the assessor blinded to treatment received, and compared with actual treatment received, which was determined by an experienced UKA surgeon based on history, examination, radiographic assessment including stress radiographs, and intra-operative assessment in line with the recommended indications as described in the literature. Results: The sensitivity and specificity of the Decision Aid was 92% and 88%, respectively. Excluding knees where a clear pre-operative plan was made to perform TKA, i.e. patient request, the sensitivity was 93% and specificity 96%. The false-positive rate was low (2.4%) with all affected patients readily identifiable during joint inspection at surgery. In patients meeting Decision Aid criteria and receiving UKA, the five-year survival was 99% (95% confidence intervals (CI) 97 to 100). The false negatives (3.5%), who received UKA but did not meet the criteria, had significantly worse functional outcomes (flexion p < 0.001, American Knee Society Score - Functional p < 0.001, University of California Los Angeles score p = 0.04), and lower implant survival of 93.1% (95% CI 77.6 to 100). Conclusion: The radiographic Decision Aid safely and reliably identifies appropriate patients for meniscal-bearing UKA and achieves good results in this population. The widespread use of the Decision Aid should improve the results of UKA

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

Resistance to penicillin of Staphylococcus aureus isolates from cows with high somatic cell counts in organic and conventional dairy herds in Denmark

BACKGROUND: Quarter milk samples from cows with high risk of intramammary infection were examined to determine the prevalence of Staphylococcus aureus (SA) and penicillin resistant SA (SAr) in conventional and organic dairy herds and herds converting to organic farming in a combined longitudinal and cross-sectional study. METHODS: 20 conventional herds, 18 organic herds that converted before 1995, and 19 herds converting to organic farming in 1999 or 2000 were included in the study. Herds converting to organic farming were sampled three times one year apart; the other herds were sampled once. Risk of infection was estimated based on somatic cell count, milk production, breed, age and lactation stage. RESULTS: The high-risk cows represented about 49 % of the cows in the herds. The overall prevalence of SA and SAr among these cows was 29% (95% confidence interval: 24%–34%) and 4% (95% confidence interval: 2%–5%) respectively. The prevalence of penicillin resistance among SA infected cows was 12% (95% confidence interval: 6%–19%) when calculated from the first herd visits. No statistically significant differences were observed in the prevalence of SAr or the proportion of isolates resistant to penicillin between herd groups. CONCLUSION: The proportion of isolates resistant to penicillin was low compared to studies in other countries except Norway and Sweden. Based on the low prevalence of penicillin resistance of SA, penicillin should still be the first choice of antimicrobial agent for treatment of bovine intramammary infection in Denmark

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

Transcriptional interaction-assisted identification of dynamic nucleosome positioning

<p>Abstract</p> <p>Background</p> <p>Nucleosomes regulate DNA accessibility and therefore play a central role in transcription control. Computational methods have been developed to predict static nucleosome positions from DNA sequences, but nucleosomes are dynamic in vivo.</p> <p>Results</p> <p>Motivated by our observation that transcriptional interaction is discriminative information for nucleosome occupancy, we developed a novel computational approach to identify dynamic nucleosome positions at promoters by combining transcriptional interaction and genomic sequence information. Our approach successfully identified experimentally determined nucleosome positioning dynamics available in three cellular conditions, and significantly improved the prediction accuracy which is based on sequence information alone. We then applied our approach to various cellular conditions and established a comprehensive landscape of dynamic nucleosome positioning in yeast.</p> <p>Conclusion</p> <p>Analysis of this landscape revealed that the majority of nucleosome positions are maintained during most conditions. However, nucleosome occupancy at most promoters fluctuates with the corresponding gene expression level and is reduced specifically at the phase of peak expression. Further investigation into properties of nucleosome occupancy identified two gene groups associated with distinct modes of nucleosome modulation. Our results suggest that both the intrinsic sequence and regulatory proteins modulate nucleosomes in an altered manner.</p

Combined treatment of adenoid cystic carcinoma with cetuximab and IMRT plus C12 heavy ion boost: ACCEPT [ACC, Erbitux® and particle therapy]

<p>Abstract</p> <p>Background</p> <p>Local control in adjuvant/definitive RT of adenoid cystic carcinoma (ACC) is largely dose-dependent leading to the establishment of particle therapy in this indication. However, even modern techniques leave space for improvement of local control by intensification of local treatment. Radiation sensitization by exploitation of high EGFR-expression in ACC with the EGFR receptor antibody cetuximab seems promising.</p> <p>Methods/design</p> <p>The ACCEPT trial is a prospective, mono-centric, phase I/II trial evaluating toxicity (primary endpoint: acute and late effects) and efficacy (secondary endpoint: local control, distant control, disease-free survival, overall survival) of the combined treatment with IMRT/carbon ion boost and weekly cetuximab in 49 patients with histologically proven (≥R1-resected, inoperable or Pn+) ACC. Patients receive 18 GyE carbon ions (6 fractions) and 54 Gy IMRT (2.0 Gy/fraction) in combination with weekly cetuximab throughout radiotherapy.</p> <p>Discussion</p> <p>The primary objective of ACCEPT is to evaluate toxicity and feasibility of cetuximab and particle therapy in adenoid cystic carcinoma.</p> <p>Trial Registration</p> <p>Clinical Trial Identifier: <a href="http://www.clinicaltrials.gov/ct2/show/NCT01192087">NCT 01192087</a></p> <p>EudraCT number: 2010 - 022425 - 15</p

Jet energy measurement with the ATLAS detector in proton-proton collisions at root s=7 TeV

The jet energy scale and its systematic uncertainty are determined for jets measured with the ATLAS detector at the LHC in proton-proton collision data at a centre-of-mass energy of √s = 7TeV corresponding to an integrated luminosity of 38 pb-1. Jets are reconstructed with the anti-kt algorithm with distance parameters R=0. 4 or R=0. 6. Jet energy and angle corrections are determined from Monte Carlo simulations to calibrate jets with transverse momenta pT≥20 GeV and pseudorapidities {pipe}η{pipe}<4. 5. The jet energy systematic uncertainty is estimated using the single isolated hadron response measured in situ and in test-beams, exploiting the transverse momentum balance between central and forward jets in events with dijet topologies and studying systematic variations in Monte Carlo simulations. The jet energy uncertainty is less than 2. 5 % in the central calorimeter region ({pipe}η{pipe}<0. 8) for jets with 60≤pT<800 GeV, and is maximally 14 % for pT<30 GeV in the most forward region 3. 2≤{pipe}η{pipe}<4. 5. The jet energy is validated for jet transverse momenta up to 1 TeV to the level of a few percent using several in situ techniques by comparing a well-known reference such as the recoiling photon pT, the sum of the transverse momenta of tracks associated to the jet, or a system of low-pT jets recoiling against a high-pT jet. More sophisticated jet calibration schemes are presented based on calorimeter cell energy density weighting or hadronic properties of jets, aiming for an improved jet energy resolution and a reduced flavour dependence of the jet response. The systematic uncertainty of the jet energy determined from a combination of in situ techniques is consistent with the one derived from single hadron response measurements over a wide kinematic range. The nominal corrections and uncertainties are derived for isolated jets in an inclusive sample of high-pT jets. Special cases such as event topologies with close-by jets, or selections of samples with an enhanced content of jets originating from light quarks, heavy quarks or gluons are also discussed and the corresponding uncertainties are determined. © 2013 CERN for the benefit of the ATLAS collaboration

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

Upper extremity impairments in women with or without lymphedema following breast cancer treatment

Breast-cancer-related lymphedema affects ∼25% of breast cancer (BC) survivors and may impact use of the upper limb during activity. The purpose of this study is to compare upper extremity (UE) impairment and activity between women with and without lymphedema after BC treatment. 144 women post BC treatment completed demographic, symptom, and Disability of Arm-Shoulder-Hand (DASH) questionnaires. Objective measures included Purdue pegboard, finger-tapper, Semmes-Weinstein monofilaments, vibration perception threshold, strength, range of motion (ROM), and volume. Women with lymphedema had more lymph nodes removed (p &lt; .001), more UE symptoms (p &lt; .001), higher BMI (p = .041), and higher DASH scores (greater limitation) (p &lt; .001). For all participants there was less strength (elbow flexion, wrist flexion, grip), less shoulder ROM, and decreased sensation at the medial upper arm (p &lt; .05) in the affected UE. These differences were greater in women with lymphedema, particularly in shoulder abduction ROM (p &lt; .05). Women with lymphedema had bilaterally less elbow flexion strength and shoulder ROM (p &lt; .05). Past diagnosis of lymphedema, grip strength, shoulder abduction ROM, and number of comorbidities contributed to the variance in DASH scores (R 2 of 0.463, p &lt; .001). UE impairments are found in women following treatment for BC. Women with lymphedema have greater UE impairment and limitation in activities than women without. Many of these impairments are amenable to prevention measures or treatment, so early detection by health care providers is essential