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Zirconium alloys are common fuel claddings in nuclear fission reactors and are susceptible to the effects of hydrogen embrittlement. There is a need to be able to detect and image hydrogen at the atomic scale to gain the experimental evidence necessary to fully understand hydrogen embrittlement. Through the use of deuterium tracers, atom probe tomography (APT) is able to detect and spatially locate hydrogen at the atomic scale. Previous works have highlighted issues with quantifying deuterium concentrations using APT due to complex peak overlaps in the mass-to-charge-state ratio spectrum between molecular hydrogen and deuterium (H2 and D). In this work, we use new methods to analyze historic and simulated atom probe data, by applying currently available data analysis tools, to optimize solving peak overlaps to improve the quantification of deuterium. This method has been applied to literature data to quantify the deuterium concentrations in a concentration line profile across an α-Zr/deuteride interface.
Current reconstruction methodologies for atom probe tomography (APT) contain serious geometric artifacts that are difficult to address due to their reliance on empirical factors to generate a reconstructed volume. To overcome this limitation, a reconstruction technique is demonstrated where the analyzed volume is instead defined by the specimen geometry and crystal structure as determined by transmission electron microscopy (TEM) and diffraction acquired before and after APT analysis. APT data are reconstructed using a bottom-up approach, where the post-APT TEM image is used to define the substrate upon which APT detection events are placed. Transmission electron diffraction enables the quantification of the relationship between atomic positions and the evaporated specimen volume. Using an example dataset of ZnMgO:Ga grown epitaxially on c-plane sapphire, a volume is reconstructed that has the correct geometry and atomic spacings in 3D. APT data are thus reconstructed in 3D without using empirical parameters for the reverse projection reconstruction algorithm.
Treatment resistant schizophrenia (TRS) is one of the most disabling of psychiatric disorders, affecting about 1/3 of patients. First-line treatments include both atypical and typical antipsychotics. The original atypical, clozapine, is a final option, and although it has been shown to be the only effective treatment for TRS, many patients do not respond well to clozapine. Clozapine use is related to adverse events, most notably agranulocytosis, a potentially fatal blood disorder which affects about 1% of those prescribed clozapine and requires regular blood monitoring. This as a barrier to prescription and there is a long delay in access for TRS patients, of five or more years, from first antipsychotic prescription. Better tools to predict treatment resistance and to identify risk of adverse events would allow faster and safer access to clozapine for patients who are likely to benefit from it. The CRESTAR project (www.crestar-project.eu) is a European Framework 7 collaborative project that aims to develop tools to predict i) treatment response, particularly patients who are less likely to respond to usual antipsychotics, indicating treatment with clozapine as early as possible, ii) patients who are at high or low risk of adverse events and side effects, iii) extreme TRS patients so that they can be stratified in clinical trials for novel treatments. CRESTAR has addressed these questions by examining genome-wide association data, genome sequence, epigenetic biomarkers and epidemiological data in European patient cohorts characterized for treatment response, and adverse drug reaction using data from clozapine therapeutic drug monitoring and linked National population medical and pharmacy databases, to identify predictive factors. In parallel CRESTAR will perform health economic research on potential benefits, and ethics and patient-centred research with stakeholders.
We present multi–epoch VLBI observations of the methanol and water masers in the high–mass star formation region G 339.884−1.259, made using the Australian Long Baseline Array (LBA). Our sub–milliarcsecond precision measurements trace the proper motions of individual maser features in the plane of the sky. When combined with the direct line–of–sight radial velocity (vlsr), these measure the 3 D gas kinematics of the associated high–mass star formation region, allowing us to probe the dynamical processes to within 1000 AU of the core.
As part of the ongoing development of small unmanned air systems by the University of Southampton, an all laser sintered aircraft has been test flown from the Royal Navy's ice patrol ship HMS Protector to assist with navigating through the Antarctic. These flights were carried out with pre-planned autopilot control with oversight from Andrew Lock, acting as the pilot embarked on HMS Protector. This is the first time the Royal Navy has used unmanned aerial vehicles in this part of the world. In this paper, we set out the trial reports and lessons learnt from this series of test flights.
Correlative microscopy approaches offer synergistic solutions to many research problems. One such combination, that has been studied in limited detail, is the use of atom probe tomography (APT) and transmission Kikuchi diffraction (TKD) on the same tip specimen. By combining these two powerful microscopy techniques, the microstructure of important engineering alloys can be studied in greater detail. For the first time, the accuracy of crystallographic measurements made using APT will be independently verified using TKD. Experimental data from two atom probe tips, one a nanocrystalline Al–0.5Ag alloy specimen collected on a straight flight-path atom probe and the other a high purity Mo specimen collected on a reflectron-fitted instrument, will be compared. We find that the average minimum misorientation angle, calculated from calibrated atom probe reconstructions with two different pole combinations, deviate 0.7° and 1.4°, respectively, from the TKD results. The type of atom probe and experimental conditions appear to have some impact on this accuracy and the reconstruction and measurement procedures are likely to contribute further to degradation in angular resolution. The challenges and implications of this correlative approach will also be discussed.
Major depressive disorder (MDD) is a common and disabling condition with well-established heritability and environmental risk factors. Gene–environment interaction studies in MDD have typically investigated candidate genes, though the disorder is known to be highly polygenic. This study aims to test for interaction between polygenic risk and stressful life events (SLEs) or childhood trauma (CT) in the aetiology of MDD.
Method
The RADIANT UK sample consists of 1605 MDD cases and 1064 controls with SLE data, and a subset of 240 cases and 272 controls with CT data. Polygenic risk scores (PRS) were constructed using results from a mega-analysis on MDD by the Psychiatric Genomics Consortium. PRS and environmental factors were tested for association with case/control status and for interaction between them.
Results
PRS significantly predicted depression, explaining 1.1% of variance in phenotype (p = 1.9 × 10−6). SLEs and CT were also associated with MDD status (p = 2.19 × 10−4 and p = 5.12 × 10−20, respectively). No interactions were found between PRS and SLEs. Significant PRSxCT interactions were found (p = 0.002), but showed an inverse association with MDD status, as cases who experienced more severe CT tended to have a lower PRS than other cases or controls. This relationship between PRS and CT was not observed in independent replication samples.
Conclusions
CT is a strong risk factor for MDD but may have greater effect in individuals with lower genetic liability for the disorder. Including environmental risk along with genetics is important in studying the aetiology of MDD and PRS provide a useful approach to investigating gene–environment interactions in complex traits.
Strategies to dissect phenotypic and genetic heterogeneity of major depressive disorder (MDD) have mainly relied on subphenotypes, such as age at onset (AAO) and recurrence/episodicity. Yet, evidence on whether these subphenotypes are familial or heritable is scarce. The aims of this study are to investigate the familiality of AAO and episode frequency in MDD and to assess the proportion of their variance explained by common single nucleotide polymorphisms (SNP heritability).
Method
For investigating familiality, we used 691 families with 2–5 full siblings with recurrent MDD from the DeNt study. We fitted (square root) AAO and episode count in a linear and a negative binomial mixed model, respectively, with family as random effect and adjusting for sex, age and center. The strength of familiality was assessed with intraclass correlation coefficients (ICC). For estimating SNP heritabilities, we used 3468 unrelated MDD cases from the RADIANT and GSK Munich studies. After similarly adjusting for covariates, derived residuals were used with the GREML method in GCTA (genome-wide complex trait analysis) software.
Results
Significant familial clustering was found for both AAO (ICC = 0.28) and episodicity (ICC = 0.07). We calculated from respective ICC estimates the maximal additive heritability of AAO (0.56) and episodicity (0.15). SNP heritability of AAO was 0.17 (p = 0.04); analysis was underpowered for calculating SNP heritability of episodicity.
Conclusions
AAO and episodicity aggregate in families to a moderate and small degree, respectively. AAO is under stronger additive genetic control than episodicity. Larger samples are needed to calculate the SNP heritability of episodicity. The described statistical framework could be useful in future analyses.
Atom probe is a powerful technique for studying the composition of nano-precipitates, but their morphology within the reconstructed data is distorted due to the so-called local magnification effect. A new technique has been developed to mitigate this limitation by characterizing the distribution of the surrounding matrix atoms, rather than those contained within the nano-precipitates themselves. A comprehensive chemical analysis enables further information on size and chemistry to be obtained. The method enables new insight into the morphology and chemistry of niobium carbonitride nano-precipitates within ferrite for a series of Nb-microalloyed ultra-thin cast strip steels. The results are supported by complementary high-resolution transmission electron microscopy.
Obesity has been shown to be associated with depression and it has been suggested that higher body mass index (BMI) increases the risk of depression and other common mental disorders. However, the causal relationship remains unclear and Mendelian randomisation, a form of instrumental variable analysis, has recently been employed to attempt to resolve this issue.
Aims
To investigate whether higher BMI increases the risk of major depression.
Method
Two instrumental variable analyses were conducted to test the causal relationship between obesity and major depression in RADIANT, a large case–control study of major depression. We used a single nucleotide polymorphism (SNP) in FTO and a genetic risk score (GRS) based on 32 SNPs with well-established associations with BMI.
Results
Linear regression analysis, as expected, showed that individuals carrying more risk alleles of FTO or having higher score of GRS had a higher BMI. Probit regression suggested that higher BMI is associated with increased risk of major depression. However, our two instrumental variable analyses did not support a causal relationship between higher BMI and major depression (FTO genotype: coefficient −0.03, 95% CI −0.18 to 0.13, P = 0.73; GRS: coefficient −0.02, 95% CI −0.11 to 0.07, P = 0.62).
Conclusions
Our instrumental variable analyses did not support a causal relationship between higher BMI and major depression. The positive associations of higher BMI with major depression in probit regression analyses might be explained by reverse causality and/or residual confounding.
The Millimetre Astronomy Legacy Team 90 GHz (MALT90) survey aims to characterise the physical and chemical evolution of high-mass star-forming clumps. Exploiting the unique broad frequency range and on-the-fly mapping capabilities of the Australia Telescope National Facility Mopra 22 m single-dish telescope1, MALT90 has obtained 3′ × 3′ maps towards ~2 000 dense molecular clumps identified in the ATLASGAL 870 μm Galactic plane survey. The clumps were selected to host the early stages of high-mass star formation and to span the complete range in their evolutionary states (from prestellar, to protostellar, and on to $\mathrm{H\,{\scriptstyle {II}}}$ regions and photodissociation regions). Because MALT90 mapped 16 lines simultaneously with excellent spatial (38 arcsec) and spectral (0.11 km s−1) resolution, the data reveal a wealth of information about the clumps’ morphologies, chemistry, and kinematics. In this paper we outline the survey strategy, observing mode, data reduction procedure, and highlight some early science results. All MALT90 raw and processed data products are available to the community. With its unprecedented large sample of clumps, MALT90 is the largest survey of its type ever conducted and an excellent resource for identifying interesting candidates for high-resolution studies with ALMA.
We characterise the Millimetre Astronomy Legacy Team 90 GHz Survey (MALT90) and the Mopra telescope at 90 GHz. We combine repeated position-switched observations of the source G300.968+01.145 with a map of the same source in order to estimate the pointing reliability of the position-switched observations and, by extension, the MALT90 survey; we estimate our pointing uncertainty to be 8 arcsec. We model the two strongest sources of systematic gain variability as functions of elevation and time-of-day and quantify the remaining absolute flux uncertainty. Corrections based on these two variables reduce the scatter in repeated observations from 12%–25% down to 10%–17%. We find no evidence for intrinsic source variability in G300.968+01.145. For certain applications, the corrections described herein will be integral for improving the absolute flux calibration of MALT90 maps and other observations using the Mopra telescope at 90 GHz.
To examine the use of vitamin D supplements during infancy among the participants in an international infant feeding trial.
Design
Longitudinal study.
Setting
Information about vitamin D supplementation was collected through a validated FFQ at the age of 2 weeks and monthly between the ages of 1 month and 6 months.
Subjects
Infants (n 2159) with a biological family member affected by type 1 diabetes and with increased human leucocyte antigen-conferred susceptibility to type 1 diabetes from twelve European countries, the USA, Canada and Australia.
Results
Daily use of vitamin D supplements was common during the first 6 months of life in Northern and Central Europe (>80 % of the infants), with somewhat lower rates observed in Southern Europe (>60 %). In Canada, vitamin D supplementation was more common among exclusively breast-fed than other infants (e.g. 71 % v. 44 % at 6 months of age). Less than 2 % of infants in the USA and Australia received any vitamin D supplementation. Higher gestational age, older maternal age and longer maternal education were study-wide associated with greater use of vitamin D supplements.
Conclusions
Most of the infants received vitamin D supplements during the first 6 months of life in the European countries, whereas in Canada only half and in the USA and Australia very few were given supplementation.
Although usually thought of as external environmental stressors, a significant heritable component has been reported for measures of stressful life events (SLEs) in twin studies.
Method
We examined the variance in SLEs captured by common genetic variants from a genome-wide association study (GWAS) of 2578 individuals. Genome-wide complex trait analysis (GCTA) was used to estimate the phenotypic variance tagged by single nucleotide polymorphisms (SNPs). We also performed a GWAS on the number of SLEs, and looked at correlations between siblings.
Results
A significant proportion of variance in SLEs was captured by SNPs (30%, p = 0.04). When events were divided into those considered to be dependent or independent, an equal amount of variance was explained for both. This ‘heritability’ was in part confounded by personality measures of neuroticism and psychoticism. A GWAS for the total number of SLEs revealed one SNP that reached genome-wide significance (p = 4 × 10−8), although this association was not replicated in separate samples. Using available sibling data for 744 individuals, we also found a significant positive correlation of R2 = 0.08 in SLEs (p = 0.03).
Conclusions
These results provide independent validation from molecular data for the heritability of reporting environmental measures, and show that this heritability is in part due to both common variants and the confounding effect of personality.
We review properties of all known collisionally pumped (class I) methanol maser series based on observations with the Australia Telescope Compact Array (ATCA) and the Mopra radio telescope. Masers at 36, 84, 44 and 95 GHz are most widespread, while 9.9, 25, 23.4 and 104 GHz masers are much rarer, tracing the most energetic shocks. A survey of many southern masers at 36 and 44 GHz suggests that these two transitions are highly complementary. The 23.4 GHz maser is a new type of rare class I methanol maser, detected only in two high-mass star-forming regions, G357.97-0.16 and G343.12-0.06, and showing a behaviour similar to 9.9, 25 and 104 GHz masers. Interferometric positions suggest that shocks responsible for class I masers could arise from a range of phenomena, not merely an outflow scenario. For example, some masers might be caused by interaction of an expanding Hii region with its surrounding molecular cloud. This has implications for evolutionary sequences incorporating class I methanol masers if they appear more than once during the evolution of the star-forming region. We also make predictions for candidate maser transitions in the ALMA frequency range.
Atom probe tomography (APT) represents a significant step toward atomic resolution microscopy, analytically imaging individual atoms with highly accurate, though imperfect, chemical identity and three-dimensional (3D) positional information. Here, a technique to retrieve crystallographic information from raw APT data and restore the lattice-specific atomic configuration of the original specimen is presented. This lattice rectification technique has been applied to a pure metal, W, and then to the analysis of a multicomponent Al alloy. Significantly, the atoms are located to their true lattice sites not by an averaging, but by triangulation of each particular atom detected in the 3D atom-by-atom reconstruction. Lattice rectification of raw APT reconstruction provides unprecedented detail as to the fundamental solute hierarchy of the solid solution. Atomic clustering has been recognized as important in affecting alloy behavior, such as for the Al-1.1Cu-1.7Mg (at. %) investigated here, which exhibits a remarkable rapid hardening reaction during the early stages of aging, linked to clustering of solutes. The technique has enabled lattice-site and species-specific radial distribution functions, nearest-neighbor analyses, and short-range order parameters, and we demonstrate a characterization of solute-clustering with unmatched sensitivity and precision.