Absolute values of the London penetration depth in YBa2Cu3O6+y measured by zero field ESR spectroscopy on Gd doped single crystals

Zero-field electron spin resonance (ESR) of dilute Gd ions substituted for Y in the cuprate superconductor YBa$_2$Cu$_3$O$_{\rm 6+y}$ is used as a novel technique for measuring the absolute value of the low temperature magnetic penetration depth $\lambda(T\to 0)$. The Gd ESR spectrum of samples with $\approx 1$ substitution was obtained with a broadband microwave technique that measures power absorption bolometrically from 0.5 GHz to 21 GHz. This ESR spectrum is determined by the crystal field that lifts the level degeneracy of the spin 7/2 Gd$^{3+}$ ion and details of this spectrum provide information concerning oxygen ordering in the samples. The magnetic penetration depth is obtained by relating the number of Gd ions exposed to the microwave magnetic field to the frequency-integrated intensity of the observed ESR transitions. This technique has allowed us to determine precise values of $\lambda$ for screening currents flowing in the three crystallographic orientations ($\hat a$, $\hat b$ and $\hat c$) in samples of Gd$_{\rm x}$Y$_{\rm 1-x}$Ba$_2$Cu$_3$O$_{6+{\rm y}}$ of three different oxygen contents ${\rm y}=0.993$ ($T_c = 89$ K), ${\rm y}=0.77$ ($T_c=75$ K) and ${\rm y}=0.52$ ($T_c=56$ K). The in-plane values are found to depart substantially from the widely reported relation $T_c\propto 1/\lambda^2$.Comment: 14 pages, 12 figures; version to appear in PR

Time evolution of in vivo articular cartilage repair induced by bone marrow stimulation and scaffold implantation in rabbits

Purpose: Tissue engineering techniques were used to study cartilage repair over a 12-month period in a rabbit model. Methods: A full-depth chondral defect along with subchondral bone injury were originated in the knee joint, where a biostable porous scaffold was implanted, synthesized of poly(ethyl acrylate-co-hydroxyethyl acrylate) copolymer. Morphological evolution of cartilage repair was studied 1 and 2 weeks, and 1, 3, and 12 months after implantation by histological techniques. The 3-month group was chosen to compare cartilage repair to an additional group where scaffolds were preseeded with allogeneic chondrocytes before implantation, and also to controls, who underwent the same surgery procedure, with no scaffold implantation. Results: Neotissue growth was first observed in the deepest scaffold pores 1 week after implantation, which spread thereafter; 3 months later scaffold pores were filled mostly with cartilaginous tissue in superficial and middle zones, and with bone tissue adjacent to subchondral bone. Simultaneously, native chondrocytes at the edges of the defect started to proliferate 1 week after implantation; within a month those edges had grown centripetally and seemed to embed the scaffold, and after 3 months, hyaline-like cartilage was observed on the condylar surface. Preseeded scaffolds slightly improved tissue growth, although the quality of repair tissue was similar to non-preseeded scaffolds. Controls showed that fibrous cartilage was mainly filling the repair area 3 months after surgery. In the 12-month group, articular cartilage resembled the untreated surface. Conclusions: Scaffolds guided cartilaginous tissue growth in vivo, suggesting their importance in stress transmission to the cells for cartilage repair.This study was supported by the Spanish Ministry of Science and Innovation through MAT2010-21611-C03-00 project (including the FEDER financial support), by Conselleria de Educacion (Generalitat Valenciana, Spain) PROMETEO/2011/084 grant, and by CIBER-BBN en Bioingenieria, Biomateriales y Nanomedicina. The work of JLGR was partially supported by funds from the Generalitat Valenciana, ACOMP/2012/075 project. CIBER-BBN is an initiative funded by the VI National R&D&i Plan 2008-2011, Iniciativa Ingenio 2010, Consolider Program, CIBER Actions and financed by the - Instituto de Salud Carlos III with assistance from the European Regional Development Fund.Sancho-Tello Valls, M.; Forriol, F.; Gastaldi, P.; Ruiz Sauri, A.; Martín De Llano, JJ.; Novella-Maestre, E.; Antolinos Turpín, CM.... (2015). 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Criterion A of the AMPD in HiTOP

The categorical model of personality disorder classification in the American Psychiatric Association's Diagnostic and Statistical Manual of Mental Disorders (5th ed. [DSM-5]; American Psychiatric Association, 2013) is highly and fundamentally problematic. Proposed for DSM-5 and provided within Section III (for Emerging Measures and Models) was the Alternative Model of Personality Disorder (AMPD) classification, consisting of Criterion A (self-interpersonal deficits) and Criterion B (maladaptive personality traits). A proposed alternative to the DSM-5 more generally is an empirically based dimensional organization of psychopathology identified as the Hierarchical Taxonomy of Psychopathology (HiTOP; Kotov etal., 2017). HiTOP currently includes, at the highest level, a general factor of psychopathology. Further down are the five domains of detachment, antagonistic externalizing, disinhibited externalizing, thought disorder, and internalizing (along with a provisional sixth somatoform dimension) that align with Criterion B. The purpose of this article is to discuss the potential inclusion and placement of the self-interpersonal deficits of the DSM-5 Section III Criterion A within HiTOP

The PHENIX Experiment at RHIC

The physics emphases of the PHENIX collaboration and the design and current status of the PHENIX detector are discussed. The plan of the collaboration for making the most effective use of the available luminosity in the first years of RHIC operation is also presented.Comment: 5 pages, 1 figure. Further details of the PHENIX physics program available at http://www.rhic.bnl.gov/phenix

Improving Genetic Prediction by Leveraging Genetic Correlations Among Human Diseases and Traits

Genomic prediction has the potential to contribute to precision medicine. However, to date, the utility of such predictors is limited due to low accuracy for most traits. Here theory and simulation study are used to demonstrate that widespread pleiotropy among phenotypes can be utilised to improve genomic risk prediction. We show how a genetic predictor can be created as a weighted index that combines published genome-wide association study (GWAS) summary statistics across many different traits. We apply this framework to predict risk of schizophrenia and bipolar disorder in the Psychiatric Genomics consortium data, finding substantial heterogeneity in prediction accuracy increases across cohorts. For six additional phenotypes in the UK Biobank data, we find increases in prediction accuracy ranging from 0.7 for height to 47 for type 2 diabetes, when using a multi-trait predictor that combines published summary statistics from multiple traits, as compared to a predictor based only on one trait. © 2018 The Author(s)

Identification of common genetic risk variants for autism spectrum disorder

Autism spectrum disorder (ASD) is a highly heritable and heterogeneous group of neurodevelopmental phenotypes diagnosed in more than 1% of children. Common genetic variants contribute substantially to ASD susceptibility, but to date no individual variants have been robustly associated with ASD. With a marked sample-size increase from a unique Danish population resource, we report a genome-wide association meta-analysis of 18,381 individuals with ASD and 27,969 controls that identified five genome-wide-significant loci. Leveraging GWAS results from three phenotypes with significantly overlapping genetic architectures (schizophrenia, major depression, and educational attainment), we identified seven additional loci shared with other traits at equally strict significance levels. Dissecting the polygenic architecture, we found both quantitative and qualitative polygenic heterogeneity across ASD subtypes. These results highlight biological insights, particularly relating to neuronal function and corticogenesis, and establish that GWAS performed at scale will be much more productive in the near term in ASD.Peer reviewe

Genome-wide association study identifies 30 Loci Associated with Bipolar Disorder

This paper is dedicated to the memory of Psychiatric Genomics Consortium (PGC) founding member and Bipolar disorder working group co-chair Pamela Sklar. We thank the participants who donated their time, experiences and DNA to this research, and to the clinical and scientific teams that worked with them. We are deeply indebted to the investigators who comprise the PGC. The views expressed are those of the authors and not necessarily those of any funding or regulatory body. Analyses were carried out on the NL Genetic Cluster Computer (http://www.geneticcluster.org ) hosted by SURFsara, and the Mount Sinai high performance computing cluster (http://hpc.mssm.edu).Bipolar disorder is a highly heritable psychiatric disorder. We performed a genome-wide association study including 20,352 cases and 31,358 controls of European descent, with follow-up analysis of 822 variants with P<1x10-4 in an additional 9,412 cases and 137,760 controls. Eight of the 19 variants that were genome-wide significant (GWS, p < 5x10-8) in the discovery GWAS were not GWS in the combined analysis, consistent with small effect sizes and limited power but also with genetic heterogeneity. In the combined analysis 30 loci were GWS including 20 novel loci. The significant loci contain genes encoding ion channels, neurotransmitter transporters and synaptic components. Pathway analysis revealed nine significantly enriched gene-sets including regulation of insulin secretion and endocannabinoid signaling. BDI is strongly genetically correlated with schizophrenia, driven by psychosis, whereas BDII is more strongly correlated with major depressive disorder. These findings address key clinical questions and provide potential new biological mechanisms for BD.This work was funded in part by the Brain and Behavior Research Foundation, Stanley Medical Research Institute, University of Michigan, Pritzker Neuropsychiatric Disorders Research Fund L.L.C., Marriot Foundation and the Mayo Clinic Center for Individualized Medicine, the NIMH Intramural Research Program; Canadian Institutes of Health Research; the UK Maudsley NHS Foundation Trust, NIHR, NRS, MRC, Wellcome Trust; European Research Council; German Ministry for Education and Research, German Research Foundation IZKF of Münster, Deutsche Forschungsgemeinschaft, ImmunoSensation, the Dr. Lisa-Oehler Foundation, University of Bonn; the Swiss National Science Foundation; French Foundation FondaMental and ANR; Spanish Ministerio de Economía, CIBERSAM, Industria y Competitividad, European Regional Development Fund (ERDF), Generalitat de Catalunya, EU Horizon 2020 Research and Innovation Programme; BBMRI-NL; South-East Norway Regional Health Authority and Mrs. Throne-Holst; Swedish Research Council, Stockholm County Council, Söderström Foundation; Lundbeck Foundation, Aarhus University; Australia NHMRC, NSW Ministry of Health, Janette M O'Neil and Betty C Lynch

Track A Basic Science

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/138319/1/jia218438.pd

Integrated analysis of environmental and genetic influences on cord blood DNA methylation in new-borns

Epigenetic processes, including DNA methylation (DNAm), are among the mechanisms allowing integration of genetic and environmental factors to shape cellular function. While many studies have investigated either environmental or genetic contributions to DNAm, few have assessed their integrated effects. Here we examine the relative contributions of prenatal environmental factors and genotype on DNA methylation in neonatal blood at variably methylated regions (VMRs) in 4 independent cohorts (overall n = 2365). We use Akaike’s information criterion to test which factors best explain variability of methylation in the cohort-specific VMRs: several prenatal environmental factors (E), genotypes in cis (G), or their additive (G + E) or interaction (GxE) effects. Genetic and environmental factors in combination best explain DNAm at the majority of VMRs. The CpGs best explained by either G, G + E or GxE are functionally distinct. The enrichment of genetic variants from GxE models in GWAS for complex disorders supports their importance for disease risk