Leptin is a four-helix bundle: secondary structure by NMR

AbstractLeptin is a signaling protein that in its mutant forms has been associated with obesity and Type II diabetes. The lack of sequence similarity has precluded analogies based on structural resemblance to known systems. Backbone NMR signals for mouse leptin (13C/15N -labeled) have been assigned and its secondary structure reveals it to be a four-helix bundle cytokine. Helix lengths and disulfide pattern are in agreement with leptin as a member of the short-helix cytokine family. A three-dimensional model was built verifying the mechanical consistency of the identified elements with a short-helix cytokine core

Genomic Dissection of Bipolar Disorder and Schizophrenia, Including 28 Subphenotypes

publisher: Elsevier articletitle: Genomic Dissection of Bipolar Disorder and Schizophrenia, Including 28 Subphenotypes journaltitle: Cell articlelink: https://doi.org/10.1016/j.cell.2018.05.046 content_type: article copyright: © 2018 Elsevier Inc

An Overview of High Energy Short Pulse Technology for Advanced Radiography of Laser Fusion Experiments

The technical challenges and motivations for high-energy, short-pulse generation with NIF-class, Nd:glass laser systems are reviewed. High energy short pulse generation (multi-kilojoule, picosecond pulses) will be possible via the adaptation of chirped pulse amplification laser techniques on the NIF. Development of meter-scale, high efficiency, high-damage-threshold final optics is a key technical challenge. In addition, deployment of HEPW pulses on NIF is constrained by existing laser infrastructure and requires new, compact compressor designs and short-pulse, fiber-based, seed-laser systems. The key motivations for high energy petawatt pulses on NIF is briefly outlined and includes high-energy, x-ray radiography, proton beam radiography, proton isochoric heating and tests of the fast ignitor concept for inertial confinement fusion

Genetic relationship between five psychiatric disorders estimated from genome-wide SNPs

<p>Most psychiatric disorders are moderately to highly heritable. The degree to which genetic variation is unique to individual disorders or shared across disorders is unclear. To examine shared genetic etiology, we use genome-wide genotype data from the Psychiatric Genomics Consortium (PGC) for cases and controls in schizophrenia, bipolar disorder, major depressive disorder, autism spectrum disorders (ASD) and attention-deficit/hyperactivity disorder (ADHD). We apply univariate and bivariate methods for the estimation of genetic variation within and covariation between disorders. SNPs explained 17-29% of the variance in liability. The genetic correlation calculated using common SNPs was high between schizophrenia and bipolar disorder (0.68 +/- 0.04 s.e.), moderate between schizophrenia and major depressive disorder (0.43 +/- 0.06 s.e.), bipolar disorder and major depressive disorder (0.47 +/- 0.06 s.e.), and ADHD and major depressive disorder (0.32 +/- 0.07 s.e.), low between schizophrenia and ASD (0.16 +/- 0.06 s.e.) and non-significant for other pairs of disorders as well as between psychiatric disorders and the negative control of Crohn's disease. This empirical evidence of shared genetic etiology for psychiatric disorders can inform nosology and encourages the investigation of common pathophysiologies for related disorders.</p>

Genetic relationship between five psychiatric disorders estimated from genome-wide SNPs

Most psychiatric disorders are moderately to highly heritable. The degree to which genetic variation is unique to individual disorders or shared across disorders is unclear. To examine shared genetic etiology, we use genome-wide genotype data from the Psychiatric Genomics Consortium (PGC) for cases and controls in schizophrenia, bipolar disorder, major depressive disorder, autism spectrum disorders (ASD) and attention-deficit/hyperactivity disorder (ADHD). We apply univariate and bivariate methods for the estimation of genetic variation within and covariation between disorders. SNPs explained 17-29% of the variance in liability. The genetic correlation calculated using common SNPs was high between schizophrenia and bipolar disorder (0.68 ± 0.04 s.c.), moderate between schizophrenia and major depressive disorder (0.43 ± 0.06 s.e.), bipolar disorder and major depressive disorder (0.47 ± 0.06 s.e.), and ADHD and major depressive disorder (0.32 ± 0.07 s.e.), low between schizophrenia and ASD (0.16 ± 0.06 s.e.) and non-significant for other pairs of disorders as well as between psychiatric disorders and the negative control of Crohn's disease. This empirical evidence of shared genetic etiology for psychiatric disorders can inform nosology and encourages the investigation of common pathophysiologies for related disorders