NO adsorption and thermal behavior on Pd surfaces. A detailed comparative study

The adsorption and thermal behavior of NO on `flat¿ Pd(111) and `stepped¿ Pd(112) surfaces has been investigated by temperature programmed desorption (TPD), high resolution electron energy loss spectroscopy (HREELS), and electron stimulated desorption ion angular distribution (ESDIAD) techniques. NO is shown to molecularly adsorb on both Pd(111) and Pd(112) in the temperature range 100¿373 K. NO thermally desorbs predominantly molecularly from Pd(111) near 500 K with an activation energy and pre-exponential factor of desorption which strongly depend on the initial NO surface coverage. In contrast, NO decomposes substantially on Pd(112) upon heating, with relatively large amounts of N2 and N2O desorbing near 500 K, in addition to NO. The fractional amount of NO dissociation on Pd(112) during heating is observed to be a strong function of the initial NO surface coverage. HREELS results indicate that the thermal dissociation of NO on both Pd(111) and Pd(112) occurs upon annealing to 490 K, forming surface-bound O on both surfaces. Evidence for the formation of sub-surface O via NO thermal dissociation is found only on Pd(112), and is verified by dissociative O2 adsorption experiments. Both surface-bound O and sub-surface O dissolve into the Pd bulk upon annealing of both surfaces to 550 K. HREELS and ESDIAD data consistently indicate that NO preferentially adsorbs on the (111) terrace sites of Pd(112) at low coverages, filling the (001) step sites only at high coverage. This result was verified for adsorption temperatures in the range 100¿373 K. In addition, the thermal dissociation of NO on Pd(112) is most prevalent at low coverages, where only terrace sites are occupied by NO. Thus, by direct comparison to NO/Pd(111), this study shows that the presence of steps on the Pd(112) surface enhances the thermal dissociation of NO, but that adsorption at the step sites is not the criterion for this decomposition

Associations between alcohol use and accelerated biological ageing

Harmful alcohol use is a leading cause of premature death and is associated with age-related disease. Biological ageing is highly variable between individuals and may deviate from chronological ageing, suggesting that biomarkers of biological ageing (derived from DNA methylation or brain structural measures) may be clinically relevant. Here, we investigated the relationships between alcohol phenotypes and both brain and DNA methylation age estimates. First, using data from UK Biobank and Generation Scotland, we tested the association between alcohol consumption (units/week) or hazardous use (Alcohol Use Disorders Identification Test [AUDIT] scores) and accelerated brain and epigenetic ageing in 20,258 and 8051 individuals, respectively. Second, we used Mendelian randomisation (MR) to test for a causal effect of alcohol consumption levels and alcohol use disorder (AUD) on biological ageing. Alcohol use showed a consistent positive association with higher predicted brain age (AUDIT-C: β = 0.053, p = 3.16 × 10−13; AUDIT-P: β = 0.052, p = 1.6 × 10−13; total AUDIT score: β = 0.062, p = 5.52 × 10−16; units/week: β = 0.078, p = 2.20 × 10−16), and two DNA methylation-based estimates of ageing, GrimAge (units/week: β = 0.053, p = 1.48 × 10−7) and PhenoAge (units/week: β = 0.077, p = 2.18x10−10). MR analyses revealed limited evidence for a causal effect of AUD on accelerated brain ageing (β = 0.118, p = 0.044). However, this result should be interpreted cautiously as the significant effect was driven by a single genetic variant. We found no evidence for a causal effect of alcohol consumption levels on accelerated biological ageing. Future studies investigating the mechanisms associating alcohol use with accelerated biological ageing are warranted

Preservation of the optic radiations based on comparative analysis of diffusion tensor imaging tractographyand anatomical dissection

Background Visualization of the precise course of the visual pathways is relevant to prevent damage that may inflict visual field deficits during neurosurgical resections. In particular the optic radiations (OR) are susceptible to such damage during neurosurgery. Cortical pathways can be mapped in vivo, by using Diffusion Tensor Imaging (DTI). Visualization of these pathways would be potentially helpful to prevent neurosurgical visual morbidity. In this study an anatomical dissection of the visual pathways was compared to DTI fiber tractography (DTI-FT) data of four human brains. The feasibility of a definition of a Safety Zone is investigated.Methods Four adult brains were dissected using Klingler’s fiber dissection method, which allowed preparation of the OR. Measurements before and after dissection were used to establish distances from the cortex to the OR. DTI-scans were also obtained from these brains to determine the same distances.Results Measurements from specific landmark points on the cortex to the lateral border of the OR were performed in four brains. Analysis through DTI tractography corresponded with the dissection results. Based on the combined results of both dissection and DTI-FT, we defined a quantitative surgical Safety Zone with respect to various anatomical landmarks (in particular the ventricle system)Conclusion We conclude that there is a good correlation between the visualizations of the optic pathways based on dissection and DTI. Furthermore, we conclude that defining a neurosurgical Safety Zone which could preserve the integrity of the OR during surgery, based on the combination of DTI-FT images and dissection is feasible

Automated Classification of Depression from Structural Brain Measures across Two Independent Community-based Cohorts

ACKNOWLEDGEMENTS: This study was supported and funded by the Wellcome Trust Strategic Award ‘Stratifying Resilience and Depression Longitudinally’ (STRADL) (Reference 104036/Z/14/Z), and the Medical Research Council Mental Health Pathfinder Award ‘Leveraging routinely collected and linked research data to study the causes and consequences of common mental disorders’ (Reference MRC-MC_PC_17209). MAH is supported by research funding from the Dr Mortimer and Theresa Sackler Foundation. The research was conducted using the UK Biobank resource, with application number 4844. Structural brain imaging data from the UK Biobank was processed at the University of Edinburgh Centre for Cognitive Ageing and Cognitive Epidemiology (CCACE) http://www.ccace.ed.ac.uk/), which is a part of the crosscouncil Lifelong Health and Wellbeing Initiative (MR/K026992/1). CCACE received funding from Biotechnology and Biological Sciences Research Council (BBSRC), Medical Research Council (MRC), and was also supported by Age UK as part of The Disconnected Mind project. This work has made use of the resources provided by the Edinburgh Compute and Data Facility (ECDF) (http://www.ecdf.ed.ac.uk/)Peer reviewedPublisher PD

Infrastructure for Detector Research and Development towards the International Linear Collider

The EUDET-project was launched to create an infrastructure for developing and testing new and advanced detector technologies to be used at a future linear collider. The aim was to make possible experimentation and analysis of data for institutes, which otherwise could not be realized due to lack of resources. The infrastructure comprised an analysis and software network, and instrumentation infrastructures for tracking detectors as well as for calorimetry.Comment: 54 pages, 48 picture

Associations of negative affective biases and depressive symptoms in a community-based sample

Acknowledgements. We thank professor Jonathan Roiser (University College London, UK) and professor emeritus Ian Deary (University of Edinburgh, UK) for their input on task selection and statistical analysis. We also acknowledge all researchers who have contributed to the collection of data for the current study. Most importantly, we would like to thank all participants of Generation Scotland, and particularly those of the STRADL subcohort, for their participation in the research. Financial support. Stratifying Resilience and Depression Longitudinally is supported by the Wellcome Trust through a Strategic Award (Grant No. 104036/Z/14/Z) and through an Investigator Award (Grant No. 220857/Z/ 20/Z). The Chief Scientist Office of the Scottish Government Health Department (Grant No. CZD/16/6), Scottish Funding Council (Grant No. HR03006) and Wellcome Trust (Grant No. 216767/Z/19/Z) provided core support for Generation Scotland.Peer reviewedPublisher PD

Associations of negative affective biases and depressive symptoms in a community-based sample

Background: Major depressive disorder (MDD) was previously associated with negative affective biases. Evidence from larger population-based studies, however, is lacking, including whether biases normalise with remission. We investigated associations between affective bias measures and depressive symptom severity across a large community-based sample, followed by examining differences between remitted individuals and controls. Methods: Participants from Generation Scotland (N = 1109) completed the: (i) Bristol Emotion Recognition Task (BERT), (ii) Face Affective Go/No-go (FAGN), and (iii) Cambridge Gambling Task (CGT). Individuals were classified as MDD-current (n = 43), MDD-remitted (n = 282), or controls (n = 784). Analyses included using affective bias summary measures (primary analyses), followed by detailed emotion/condition analyses of BERT and FAGN (secondary analyses). Results: For summary measures, the only significant finding was an association between greater symptoms and lower risk adjustment for CGT across the sample (individuals with greater symptoms were less likely to bet more, despite increasingly favourable conditions). This was no longer significant when controlling for non-affective cognition. No differences were found for remitted-MDD v. controls. Detailed analysis of BERT and FAGN indicated subtle negative biases across multiple measures of affective cognition with increasing symptom severity, that were independent of non-effective cognition [e.g. greater tendency to rate faces as angry (BERT), and lower accuracy for happy/neutral conditions (FAGN)]. Results for remitted-MDD were inconsistent. Conclusions: This suggests the presence of subtle negative affective biases at the level of emotion/condition in association with depressive symptoms across the sample, over and above those accounted for by non-affective cognition, with no evidence for affective biases in remitted individuals