Inclusion of Experimental Information in First Principles Modeling of Materials

We propose a novel approach to model amorphous materials using a first principles density functional method while simultaneously enforcing agreement with selected experimental data. We illustrate our method with applications to amorphous silicon and glassy GeSe$_2$. The structural, vibrational and electronic properties of the models are found to be in agreement with experimental results. The method is general and can be extended to other complex materials.Comment: 11 pages, 8 PostScript figures, submitted to J. Phys.: Condens. Matter in honor of Mike Thorpe's 60th birthda

Patterns of item nonresponse behaviour to survey questionnaires are systematic and associated with genetic loci

Peer reviewe

A Conditional Yeast E1 Mutant Blocks the Ubiquitin–Proteasome Pathway and Reveals a Role for Ubiquitin Conjugates in Targeting Rad23 to the Proteasome

E1 ubiquitin activating enzyme catalyzes the initial step in all ubiquitin-dependent processes. We report the isolation of uba1-204, a temperature-sensitive allele of the essential Saccharomyces cerevisiae E1 gene, UBA1. Uba1-204 cells exhibit dramatic inhibition of the ubiquitin–proteasome system, resulting in rapid depletion of cellular ubiquitin conjugates and stabilization of multiple substrates. We have employed the tight phenotype of this mutant to investigate the role ubiquitin conjugates play in the dynamic interaction of the UbL/UBA adaptor proteins Rad23 and Dsk2 with the proteasome. Although proteasomes purified from mutant cells are intact and proteolytically active, they are depleted of ubiquitin conjugates, Rad23, and Dsk2. Binding of Rad23 to these proteasomes in vitro is enhanced by addition of either free or substrate-linked ubiquitin chains. Moreover, association of Rad23 with proteasomes in mutant and wild-type cells is improved upon stabilizing ubiquitin conjugates with proteasome inhibitor. We propose that recognition of polyubiquitin chains by Rad23 promotes its shuttling to the proteasome in vivo

Reverse Monte Carlo modeling of amorphous silicon

An implementation of the Reverse Monte Carlo algorithm is presented for the study of amorphous tetrahedral semiconductors. By taking into account a number of constraints that describe the tetrahedral bonding geometry along with the radial distribution function, we construct a model of amorphous silicon using the reverse monte carlo technique. Starting from a completely random configuration, we generate a model of amorphous silicon containing 500 atoms closely reproducing the experimental static structure factor and bond angle distribution and in improved agreement with electronic properties. Comparison is made to existing Reverse Monte Carlo models, and the importance of suitable constraints beside experimental data is stressed.Comment: 6 pages, 4 PostScript figure

Morphological and allozyme variation in a collection of Cucumeropsis mannii Naudin (Cucurbitaceae) from Côte d'Ivoire

peer reviewe

Linguistic measures of chemical diversity and the "keywords" of molecular collections

Computerized linguistic analyses have proven of immense value in comparing and searching through large text collections ("corpora"), including those deposited on the Internet-indeed, it would nowadays be hard to imagine browsing the Web without, for instance, search algorithms extracting most appropriate keywords from documents. This paper describes how such corpus-linguistic concepts can be extended to chemistry based on characteristic "chemical words" that span more than traditional functional groups and, instead, look at common structural fragments molecules share. Using these words, it is possible to quantify the diversity of chemical collections/databases in new ways and to define molecular "keywords" by which such collections are best characterized and annotated

Risk variants and polygenic architecture of disruptive behavior disorders in the context of attention-deficit/hyperactivity disorder

Attention-Deficit/Hyperactivity Disorder (ADHD) is a childhood psychiatric disorder often comorbid with disruptive behavior disorders (DBDs). Here, we report a GWAS meta-analysis of ADHD comorbid with DBDs (ADHD + DBDs) including 3802 cases and 31,305 controls. We identify three genome-wide significant loci on chromosomes 1, 7, and 11. A meta-analysis including a Chinese cohort supports that the locus on chromosome 11 is a strong risk locus for ADHD + DBDs across European and Chinese ancestries (rs7118422, P = 3.15×10-10, OR = 1.17). We find a higher SNP heritability for ADHD + DBDs (h2SNP = 0.34) when compared to ADHD without DBDs (h2SNP = 0.20), high genetic correlations between ADHD + DBDs and aggressive (rg = 0.81) and anti-social behaviors (rg = 0.82), and an increased burden (polygenic score) of variants associated with ADHD and aggression in ADHD + DBDs compared to ADHD without DBDs. Our results suggest an increased load of common risk variants in ADHD + DBDs compared to ADHD without DBDs, which in part can be explained by variants associated with aggressive behavior

Risk variants and polygenic architecture of disruptive behavior disorders in the context of attention-deficit/hyperactivity disorder

Attention-Deficit/Hyperactivity Disorder (ADHD) is a childhood psychiatric disorder often comorbid with disruptive behavior disorders (DBDs). Here, we report a GWAS meta-analysis of ADHD comorbid with DBDs (ADHD + DBDs) including 3802 cases and 31,305 controls. We identify three genome-wide significant loci on chromosomes 1, 7, and 11. A meta-analysis including a Chinese cohort supports that the locus on chromosome 11 is a strong risk locus for ADHD + DBDs across European and Chinese ancestries (rs7118422, P = 3.15×10-10, OR = 1.17). We find a higher SNP heritability for ADHD + DBDs (h2SNP = 0.34) when compared to ADHD without DBDs (h2SNP = 0.20), high genetic correlations between ADHD + DBDs and aggressive (rg = 0.81) and anti-social behaviors (rg = 0.82), and an increased burden (polygenic score) of variants associated with ADHD and aggression in ADHD + DBDs compared to ADHD without DBDs. Our results suggest an increased load of common risk variants in ADHD + DBDs compared to ADHD without DBDs, which in part can be explained by variants associated with aggressive behavior