Temperature- and Field Dependent Characterization of a Twisted Stacked-Tape Cable

The Twisted Stacked-Tape Cable (TSTC) is one of the major high temperature superconductor cable concepts combining scalability, ease of fabrication and high current density making it a possible candidate as conductor for large scale magnets. To simulate the boundary conditions of such a magnets as well as the temperature dependence of Twisted Stacked-Tape Cables a 1.16 m long sample consisting of 40, 4 mm wide SuperPower REBCO tapes is characterized using the "FBI" (force - field - current) superconductor test facility of the Institute for Technical Physics (ITEP) of the Karlsruhe Institute of Technology (KIT). In a first step, the magnetic background field is cycled while measuring the current carrying capabilities to determine the impact of Lorentz forces on the TSTC sample performance. In the first field cycle, the critical current of the TSTC sample is tested up to 12 T. A significant Lorentz force of up to 65.6 kN/m at the maximal magnetic background field of 12 T result in a 11.8 % irreversible degradation of the current carrying capabilities. The degradation saturates (critical cable current of 5.46 kA at 4.2 K and 12 T background field) and does not increase in following field cycles. In a second step, the sample is characterized at different background fields (4-12 T) and surface temperatures (4.2-37.8 K) utilizing the variable temperature insert of the "FBI" test facility. In a third step, the performance along the length of the sample is determined at 77 K, self-field. A 15 % degradation is obtained for the central part of the sample which was within the high field region of the magnet during the in-field measurements

Role of Dopamine D2 Receptors in Human Reinforcement Learning

Influential neurocomputational models emphasize dopamine (DA) as an electrophysiological and neurochemical correlate of reinforcement learning. However, evidence of a specific causal role of DA receptors in learning has been less forthcoming, especially in humans. Here we combine, in a between-subjects design, administration of a high dose of the selective DA D2/3-receptor antagonist sulpiride with genetic analysis of the DA D2 receptor in a behavioral study of reinforcement learning in a sample of 78 healthy male volunteers. In contrast to predictions of prevailing models emphasizing DA's pivotal role in learning via prediction errors, we found that sulpiride did not disrupt learning, but rather induced profound impairments in choice performance. The disruption was selective for stimuli indicating reward, while loss avoidance performance was unaffected. Effects were driven by volunteers with higher serum levels of the drug, and in those with genetically-determined lower density of striatal DA D2 receptors. This is the clearest demonstration to date for a causal modulatory role of the DA D2 receptor in choice performance that might be distinct from learning. Our findings challenge current reward prediction error models of reinforcement learning, and suggest that classical animal models emphasizing a role of postsynaptic DA D2 receptors in motivational aspects of reinforcement learning may apply to humans as well.Neuropsychopharmacology accepted article peview online, 09 April 2014; doi:10.1038/npp.2014.84

A global analysis of Y-chromosomal haplotype diversity for 23 STR loci

In a worldwide collaborative effort, 19,630 Y-chromosomes were sampled from 129 different populations in 51 countries. These chromosomes were typed for 23 short-tandem repeat (STR) loci (DYS19, DYS389I, DYS389II, DYS390, DYS391, DYS392, DYS393, DYS385ab, DYS437, DYS438, DYS439, DYS448, DYS456, DYS458, DYS635, GATAH4, DYS481, DYS533, DYS549, DYS570, DYS576, and DYS643) and using the PowerPlex Y23 System (PPY23, Promega Corporation, Madison, WI). Locus-specific allelic spectra of these markers were determined and a consistently high level of allelic diversity was observed. A considerable number of null, duplicate and off-ladder alleles were revealed. Standard single-locus and haplotype-based parameters were calculated and compared between subsets of Y-STR markers established for forensic casework. The PPY23 marker set provides substantially stronger discriminatory power than other available kits but at the same time reveals the same general patterns of population structure as other marker sets. A strong correlation was observed between the number of Y-STRs included in a marker set and some of the forensic parameters under study. Interestingly a weak but consistent trend toward smaller genetic distances resulting from larger numbers of markers became apparent.Peer reviewe

Analysis of shared heritability in common disorders of the brain

ience, this issue p. eaap8757 Structured Abstract INTRODUCTION Brain disorders may exhibit shared symptoms and substantial epidemiological comorbidity, inciting debate about their etiologic overlap. However, detailed study of phenotypes with different ages of onset, severity, and presentation poses a considerable challenge. Recently developed heritability methods allow us to accurately measure correlation of genome-wide common variant risk between two phenotypes from pools of different individuals and assess how connected they, or at least their genetic risks, are on the genomic level. We used genome-wide association data for 265,218 patients and 784,643 control participants, as well as 17 phenotypes from a total of 1,191,588 individuals, to quantify the degree of overlap for genetic risk factors of 25 common brain disorders. RATIONALE Over the past century, the classification of brain disorders has evolved to reflect the medical and scientific communities' assessments of the presumed root causes of clinical phenomena such as behavioral change, loss of motor function, or alterations of consciousness. Directly observable phenomena (such as the presence of emboli, protein tangles, or unusual electrical activity patterns) generally define and separate neurological disorders from psychiatric disorders. Understanding the genetic underpinnings and categorical distinctions for brain disorders and related phenotypes may inform the search for their biological mechanisms. RESULTS Common variant risk for psychiatric disorders was shown to correlate significantly, especially among attention deficit hyperactivity disorder (ADHD), bipolar disorder, major depressive disorder (MDD), and schizophrenia. By contrast, neurological disorders appear more distinct from one another and from the psychiatric disorders, except for migraine, which was significantly correlated to ADHD, MDD, and Tourette syndrome. We demonstrate that, in the general population, the personality trait neuroticism is significantly correlated with almost every psychiatric disorder and migraine. We also identify significant genetic sharing between disorders and early life cognitive measures (e.g., years of education and college attainment) in the general population, demonstrating positive correlation with several psychiatric disorders (e.g., anorexia nervosa and bipolar disorder) and negative correlation with several neurological phenotypes (e.g., Alzheimer's disease and ischemic stroke), even though the latter are considered to result from specific processes that occur later in life. Extensive simulations were also performed to inform how statistical power, diagnostic misclassification, and phenotypic heterogeneity influence genetic correlations. CONCLUSION The high degree of genetic correlation among many of the psychiatric disorders adds further evidence that their current clinical boundaries do not reflect distinct underlying pathogenic processes, at least on the genetic level. This suggests a deeply interconnected nature for psychiatric disorders, in contrast to neurological disorders, and underscores the need to refine psychiatric diagnostics. Genetically informed analyses may provide important "scaffolding" to support such restructuring of psychiatric nosology, which likely requires incorporating many levels of information. By contrast, we find limited evidence for widespread common genetic risk sharing among neurological disorders or across neurological and psychiatric disorders. We show that both psychiatric and neurological disorders have robust correlations with cognitive and personality measures. Further study is needed to evaluate whether overlapping genetic contributions to psychiatric pathology may influence treatment choices. Ultimately, such developments may pave the way toward reduced heterogeneity and improved diagnosis and treatment of psychiatric disorders