Determination of RET Sequence Variation in an MEN2 Unaffected Cohort Using Multiple-Sample Pooling and Next-Generation Sequencing

Multisample, nonindexed pooling combined with next-generation sequencing (NGS) was used to discover RET proto-oncogene sequence variation within a cohort known to be unaffected by multiple endocrine neoplasia type 2 (MEN2). DNA samples (113 Caucasians, 23 persons of other ethnicities) were amplified for RET intron 9 to intron 16 and then divided into 5 pools of <30 samples each before library prep and NGS. Two controls were included in this study, a single sample and a pool of 50 samples that had been previously sequenced by the same NGS methods. All 59 variants previously detected in the 50-pool control were present. Of the 61 variants detected in the unaffected cohort, 20 variants were novel changes. Several variants were validated by high-resolution melting analysis and Sanger sequencing, and their allelic frequencies correlated well with those determined by NGS. The results from this unaffected cohort will be added to the RET MEN2 database

DNA methylation of FKBP5 and response to exposure-based psychological therapy

Differential DNA methylation of the HPA-axis related gene FKBP5 has recently been shown to be associated with varying response to environmental influences, and may play a role in how well people respond to psychological treatments. Participants (n=111) received exposure-based CBT for agoraphobia with or without panic disorder, or specific phobias. Percentage DNA methylation levels were measured for the promoter region and intron 7 of FKBP5. The association between percentage reduction in clinical severity and change in DNA methylation was tested using linear mixed models. The effect of genotype (rs1360780) was tested by the inclusion of an interaction term. The association between change in DNA methylation and FKBP5 expression was examined. Change in percentage DNA methylation at one CpG site of intron 7 was associated with percentage reduction in severity (β=-4.26, p=3.90x10-4), where a decrease in DNA methylation was associated with greater response to therapy. An interaction was detected between rs1360780 and changes in DNA methylation in the promoter region of FKBP5 on treatment outcome (p=0.045), but did not survive correction for multiple testing. Changes in DNA methylation were not associated with FKBP5 expression. Decreasing DNA methylation at one CpG site of intron 7 of FKBP5 was strongly associated with decreasing anxiety severity following exposure-based CBT. In addition, there was suggestive evidence that allele-specific methylation at the promoter region may also be associated with treatment response. The results of this study add to the growing literature demonstrating the role of biological processes such as DNA methylation in response to environmental influences

Mapping Materials and Molecules

The visualization of data is indispensable in scientific research, from the early stages when human insight forms to the final step of communicating results. In computational physics, chemistry and materials science, it can be as simple as making a scatter plot or as straightforward as looking through the snapshots of atomic positions manually. However, as a result of the “big data” revolution, these conventional approaches are often inadequate. The widespread adoption of high-throughput computation for materials discovery and the associated community-wide repositories have given rise to data sets that contain an enormous number of compounds and atomic configurations. A typical data set contains thousands to millions of atomic structures, along with a diverse range of properties such as formation energies, band gaps, or bioactivities. It would thus be desirable to have a data-driven and automated framework for visualizing and analyzing such structural data sets. The key idea is to construct a low-dimensional representation of the data, which facilitates navigation, reveals underlying patterns, and helps to identify data points with unusual attributes. Such data-intensive maps, often employing machine learning methods, are appearing more and more frequently in the literature. However, to the wider community, it is not always transparent how these maps are made and how they should be interpreted. Furthermore, while these maps undoubtedly serve a decorative purpose in academic publications, it is not always apparent what extra information can be garnered from reading or making them. This Account attempts to answer such questions. We start with a concise summary of the theory of representing chemical environments, followed by the introduction of a simple yet practical conceptual approach for generating structure maps in a generic and automated manner. Such analysis and mapping is made nearly effortless by employing the newly developed software tool ASAP. To showcase the applicability to a wide variety of systems in chemistry and materials science, we provide several illustrative examples, including crystalline and amorphous materials, interfaces, and organic molecules. In these examples, the maps not only help to sift through large data sets but also reveal hidden patterns that could be easily missed using conventional analyses. The explosion in the amount of computed information in chemistry and materials science has made visualization into a science in itself. Not only have we benefited from exploiting these visualization methods in previous works, we also believe that the automated mapping of data sets will in turn stimulate further creativity and exploration, as well as ultimately feed back into future advances in the respective fields

Mapping Materials and Molecules.

The visualization of data is indispensable in scientific research, from the early stages when human insight forms to the final step of communicating results. In computational physics, chemistry and materials science, it can be as simple as making a scatter plot or as straightforward as looking through the snapshots of atomic positions manually. However, as a result of the "big data" revolution, these conventional approaches are often inadequate. The widespread adoption of high-throughput computation for materials discovery and the associated community-wide repositories have given rise to data sets that contain an enormous number of compounds and atomic configurations. A typical data set contains thousands to millions of atomic structures, along with a diverse range of properties such as formation energies, band gaps, or bioactivities.It would thus be desirable to have a data-driven and automated framework for visualizing and analyzing such structural data sets. The key idea is to construct a low-dimensional representation of the data, which facilitates navigation, reveals underlying patterns, and helps to identify data points with unusual attributes. Such data-intensive maps, often employing machine learning methods, are appearing more and more frequently in the literature. However, to the wider community, it is not always transparent how these maps are made and how they should be interpreted. Furthermore, while these maps undoubtedly serve a decorative purpose in academic publications, it is not always apparent what extra information can be garnered from reading or making them.This Account attempts to answer such questions. We start with a concise summary of the theory of representing chemical environments, followed by the introduction of a simple yet practical conceptual approach for generating structure maps in a generic and automated manner. Such analysis and mapping is made nearly effortless by employing the newly developed software tool ASAP. To showcase the applicability to a wide variety of systems in chemistry and materials science, we provide several illustrative examples, including crystalline and amorphous materials, interfaces, and organic molecules. In these examples, the maps not only help to sift through large data sets but also reveal hidden patterns that could be easily missed using conventional analyses.The explosion in the amount of computed information in chemistry and materials science has made visualization into a science in itself. Not only have we benefited from exploiting these visualization methods in previous works, we also believe that the automated mapping of data sets will in turn stimulate further creativity and exploration, as well as ultimately feed back into future advances in the respective fields

Nuclear Scissors Mode with Pairing

The coupled dynamics of the scissors mode and the isovector giant quadrupole resonance are studied using a generalized Wigner function moments method taking into account pair correlations. Equations of motion for angular momentum, quadrupole moment and other relevant collective variables are derived on the basis of the time dependent Hartree-Fock-Bogoliubov equations. Analytical expressions for energy centroids and transitions probabilities are found for the harmonic oscillator model with the quadrupole-quadrupole residual interaction and monopole pairing force. Deformation dependences of energies and $B(M1)$ values are correctly reproduced. The inclusion of pair correlations leads to a drastic improvement in the description of qualitative and quantitative characteristics of the scissors mode.Comment: 36 pages, 5 figures, the results of calculation by another method and the section concerning currents are adde

First observation of scissors mode states in an odd-mass nucleus

Nuclear resonance fluorescence experiments are reported to search for enhanced M1 scissors mode states in the deformed odd-mass nucleus Dy163. A concentration of dipole strengths near 3 MeV excitation energy is found, which fits nicely into the systematics observed for M1 excitations in the neighboring even-even Dy isotopes. The observed strength distribution and the decay branching ratios are discussed in the context of the interacting boson-fermion model.Dirección General de Investigación Científica y Técnica PB89-063

Effect of maternal panic disorder on mother-child interaction and relation to child anxiety and child self-efficacy

To determine whether mothers with panic disorder with or without agoraphobia interacted differently with their children than normal control mothers, 86 mothers and their adolescents (aged between 13 and 23 years) were observed during a structured play situation. Maternal as well as adolescent anxiety status was assessed according to a structured diagnostic interview. Results showed that mothers with panic disorder/agoraphobia showed more verbal control, were more criticizing and less sensitive during mother-child interaction than mothers without current mental disorders. Moreover, more conflicts were observed between mother and child dyadic interactions when the mother suffered from panic disorder. The comparison of parenting behaviors among anxious and non-anxious children did not reveal any significant differences. These findings support an association between parental over-control and rejection and maternal but not child anxiety and suggest that particularly mother anxiety status is an important determinant of parenting behavior. Finally, an association was found between children’s perceived self-efficacy, parental control and child anxiety symptoms

Task force consensus on nosology and cut-off values for axial postural abnormalities in parkinsonism

Background: There is no consensus with regard to the nosology and cut-off values for postural abnormalities in parkinsonism. Objective: To reach a consensus regarding the nosology and cut-off values. Methods: Using a modified Delphi panel method, multiple rounds of questionnaires were conducted by movement disorder experts to define nosology and cut-offs of postural abnormalities. Results: After separating axial from appendicular postural deformities, a full agreement was found for the following terms and cut-offs: camptocormia, with thoracic fulcrum (&gt;45°) or lumbar fulcrum (&gt;30°), Pisa syndrome (&gt;10°), and antecollis (&gt;45°). "Anterior trunk flexion," with thoracic (≥25° to ≤45°) or lumbar fulcrum (&gt;15° to ≤30°), "lateral trunk flexion" (≥5° to ≤10°), and "anterior neck flexion" (&gt;35° to ≤45°) were chosen for milder postural abnormalities. Conclusions: For axial postural abnormalities, we recommend the use of proposed cut-offs and six unique terms, namely camptocormia, Pisa syndrome, antecollis, anterior trunk flexion, lateral trunk flexion, anterior neck flexion, to harmonize clinical practice and future research. Keywords: Parkinson's disease; Pisa syndrome; antecollis; atypical parkinsonisms; camptocormia; diagnostic criteria.; postural abnormalities

Assessment of industrial nitriding processes for fusion steel applications

The 9Cr steels EUROFER and F82H-mod are the candidate materials for future fusion reactors. The extension of the operation limits including temperature, strength and toughness are still the scope of ongoing research. In a pulsed reactor operation, fatigue lifetime is one of the major properties for the steels. While the oxide dispersion strengthened EUROFER-ODS variant showed significant improvements in this area, the production costs and availability of large quantities of materials drastically limits its applications. In the present study, different surface nitriding treatments of EUROFER972 have been performed and the impact on microstructure, dynamic fracture toughness and high temperature fatigue has been analysed. Four different states of EUROFER including different heat treatments, nitriding of the surface and the ODS variant are tested and compared in this work. Low cycle fatigue tests show the improvements after certain treatments. Charpy impact tests and microstructural investigation by scanning electron microscopy and analytical transmission electron microscopy are also performed to compare the materials against the reference (EUROFER97). While conventional gas nitriding showed no beneficial effect on the material, the Hard-Inox-P treatment showed a significant improvement in the cycles to failure while retaining an acceptable toughness. Microstructural investigations showed the presence of very small chromium- and nitrogen-rich precipitates in the area close to the surface