Ariel - Volume 10 Number 3

Executive Editors Madalyn Schaefgen David Reich Business Manager David Reich News Editors Medical College Edward Zurad CAHS John Guardiani World Mark Zwanger Features Editors Meg Trexler Jim O\u27Brien Editorials Editor Jeffrey Banyas Photography and Sports Editor Stuart Singer Commons Editor Brenda Peterso

Superconductivity in graphite intercalation compounds

The field of superconductivity in the class of materials known as graphite intercalation compounds has a history dating back to the 1960s. This paper recontextualizes the field in light of the discovery of superconductivity in CaC6 and YbC6 in 2005. In what follows, we outline the crystal structure and electronic structure of these and related compounds. We go on to experiments addressing the superconducting energy gap, lattice dynamics, pressure dependence, and how this relates to theoretical studies. The bulk of the evidence strongly supports a BCS superconducting state. However, important questions remain regarding which electronic states and phonon modes are most important for superconductivity and whether current theoretical techniques can fully describe the dependence of the superconducting transition temperature on pressure and chemical composition

Meta-analysis of shared genetic architecture across ten pediatric autoimmune diseases

Genome-wide association studies (GWASs) have identified hundreds of susceptibility genes, including shared associations across clinically distinct autoimmune diseases. We performed an inverse χ(2) meta-analysis across ten pediatric-age-of-onset autoimmune diseases (pAIDs) in a case-control study including more than 6,035 cases and 10,718 shared population-based controls. We identified 27 genome-wide significant loci associated with one or more pAIDs, mapping to in silico-replicated autoimmune-associated genes (including IL2RA) and new candidate loci with established immunoregulatory functions such as ADGRL2, TENM3, ANKRD30A, ADCY7 and CD40LG. The pAID-associated single-nucleotide polymorphisms (SNPs) were functionally enriched for deoxyribonuclease (DNase)-hypersensitivity sites, expression quantitative trait loci (eQTLs), microRNA (miRNA)-binding sites and coding variants. We also identified biologically correlated, pAID-associated candidate gene sets on the basis of immune cell expression profiling and found evidence of genetic sharing. Network and protein-interaction analyses demonstrated converging roles for the signaling pathways of type 1, 2 and 17 helper T cells (TH1, TH2 and TH17), JAK-STAT, interferon and interleukin in multiple autoimmune diseases

A Large-Scale Genetic Analysis Reveals a Strong Contribution of the HLA Class II Region to Giant Cell Arteritis Susceptibility

We conducted a large-scale genetic analysis on giant cell arteritis (GCA), a polygenic immune-mediated vasculitis. A case-control cohort, comprising 1,651 case subjects with GCA and 15,306 unrelated control subjects from six different countries of European ancestry, was genotyped by the Immunochip array. We also imputed HLA data with a previously validated imputation method to perform a more comprehensive analysis of this genomic region. The strongest association signals were observed in the HLA region, with rs477515 representing the highest peak (p = 4.05 × 10−40, OR = 1.73). A multivariate model including class II amino acids of HLA-DRβ1 and HLA-DQα1 and one class I amino acid of HLA-B explained most of the HLA association with GCA, consistent with previously reported associations of classical HLA alleles like HLA-DRB1∗04. An omnibus test on polymorphic amino acid positions highlighted DRβ1 13 (p = 4.08 × 10−43) and HLA-DQα1 47 (p = 4.02 × 10−46), 56, and 76 (both p = 1.84 × 10−45) as relevant positions for disease susceptibility. Outside the HLA region, the most significant loci included PTPN22 (rs2476601, p = 1.73 × 10−6, OR = 1.38), LRRC32 (rs10160518, p = 4.39 × 10−6, OR = 1.20), and REL (rs115674477, p = 1.10 × 10−5, OR = 1.63). Our study provides evidence of a strong contribution of HLA class I and II molecules to susceptibility to GCA. In the non-HLA region, we confirmed a key role for the functional PTPN22 rs2476601 variant and proposed other putative risk loci for GCA involved in Th1, Th17, and Treg cell function

Reversible Loss of Bernal Stacking during the Deformation of Few-Layer Graphene in Nanocomposites

The deformation of nanocomposites containing graphene flakes with different numbers of layers has been investigated with the use of Raman spectroscopy. It has been found that there is a shift of the 2D band to lower wavenumber and that the rate of band shift per unit strain tends to decrease as the number of graphene layers increases. It has been demonstrated that band broadening takes place during tensile deformation for mono- and bi-layer graphene but that band narrowing occurs when the number of graphene layers is more than two. It is also found that the characteristic asymmetric shape of the 2D Raman band for the graphene with three or more layers changes to a symmetrical shape above about 0.4% strain and that it reverts to an asymmetric shape on unloading. This change in Raman band shape and width has been interpreted as being due to a reversible loss of Bernal stacking in the few-layer graphene during deformation. It has been shown that the elastic strain energy released from the unloading of the inner graphene layers in the few-layer material (0.2 meV/atom) is similar to the accepted value of the stacking fault energies of graphite and few layer graphene. It is further shown that this loss of Bernal stacking can be accommodated by the formation of arrays of partial dislocations and stacking faults on the basal plane. The effect of the reversible loss of Bernal stacking upon the electronic structure of few-layer graphene and possibility of using it to modify the electronic structure of few-layer graphene is discussed

Recommendations towards standards for quantitative MRI (qMRI) and outstanding needs

Level of evidence5 Technical Efficacy: Stage 5 J. Magn. Reson. Imaging 2019

Recommendations towards standards for quantitative MRI (qMRI) and outstanding needs

Level of Evidence: 5. Technical Efficacy: Stage 5. J. Magn. Reson. Imaging 2019

Recommendations towards standards for quantitative MRI (qMRI) and outstanding needs

Level of Evidence: 5. Technical Efficacy: Stage 5. J. Magn. Reson. Imaging 2019