Calculation of electronic properties of amorphous alloys

We describe the application of the locally-self-consistent-multiple-scattering (LSMS)[1] method to amorphous alloys. The LSMS algorithm is optimized for the Intel XP/S-150, a multiple-instruction-multiple-data parallel computer with 1024 nodes and 2 compute processors per node. The electron density at each site is determined by solving the multiple scattering equation for atoms within a specified distance of the atom under consideration. Because this method is carried out in real space it is ideal for treating amorphous alloys. We have adapted the code to the calculation of the electronic properties of amorphous alloys. In these calculations we determine the potentials in the atomic sphere approximation self consistently at each site, unlike previous calculations[2] where we determined the potentials self consistently at an average site. With these self-consistent potentials, we then calculate electronic properties of various amorphous alloy systems. We present calculated total electronic densities of states for amorphous Ni$_{80}$P$_{20}$ and Ni$_{40}$Pd$_{40}$P$_{20}$ with 300 atoms in a supercell.Comment: 10 pages, plain tex, 2 figures. Paper accepted for publication in Proceedings of LAM-9 and Journal of non-Crystalline Solids. Please request preprints from J.C. Swihart ([email protected]

Large-scale phenotyping of patients with long COVID post-hospitalization reveals mechanistic subtypes of disease

One in ten severe acute respiratory syndrome coronavirus 2 infections result in prolonged symptoms termed long coronavirus disease (COVID), yet disease phenotypes and mechanisms are poorly understood1. Here we profiled 368 plasma proteins in 657 participants ≥3 months following hospitalization. Of these, 426 had at least one long COVID symptom and 233 had fully recovered. Elevated markers of myeloid inflammation and complement activation were associated with long COVID. IL-1R2, MATN2 and COLEC12 were associated with cardiorespiratory symptoms, fatigue and anxiety/depression; MATN2, CSF3 and C1QA were elevated in gastrointestinal symptoms and C1QA was elevated in cognitive impairment. Additional markers of alterations in nerve tissue repair (SPON-1 and NFASC) were elevated in those with cognitive impairment and SCG3, suggestive of brain–gut axis disturbance, was elevated in gastrointestinal symptoms. Severe acute respiratory syndrome coronavirus 2-specific immunoglobulin G (IgG) was persistently elevated in some individuals with long COVID, but virus was not detected in sputum. Analysis of inflammatory markers in nasal fluids showed no association with symptoms. Our study aimed to understand inflammatory processes that underlie long COVID and was not designed for biomarker discovery. Our findings suggest that specific inflammatory pathways related to tissue damage are implicated in subtypes of long COVID, which might be targeted in future therapeutic trials

SARS-CoV-2-specific nasal IgA wanes 9 months after hospitalisation with COVID-19 and is not induced by subsequent vaccination

BACKGROUND: Most studies of immunity to SARS-CoV-2 focus on circulating antibody, giving limited insights into mucosal defences that prevent viral replication and onward transmission. We studied nasal and plasma antibody responses one year after hospitalisation for COVID-19, including a period when SARS-CoV-2 vaccination was introduced. METHODS: In this follow up study, plasma and nasosorption samples were prospectively collected from 446 adults hospitalised for COVID-19 between February 2020 and March 2021 via the ISARIC4C and PHOSP-COVID consortia. IgA and IgG responses to NP and S of ancestral SARS-CoV-2, Delta and Omicron (BA.1) variants were measured by electrochemiluminescence and compared with plasma neutralisation data. FINDINGS: Strong and consistent nasal anti-NP and anti-S IgA responses were demonstrated, which remained elevated for nine months (p < 0.0001). Nasal and plasma anti-S IgG remained elevated for at least 12 months (p < 0.0001) with plasma neutralising titres that were raised against all variants compared to controls (p < 0.0001). Of 323 with complete data, 307 were vaccinated between 6 and 12 months; coinciding with rises in nasal and plasma IgA and IgG anti-S titres for all SARS-CoV-2 variants, although the change in nasal IgA was minimal (1.46-fold change after 10 months, p = 0.011) and the median remained below the positive threshold determined by pre-pandemic controls. Samples 12 months after admission showed no association between nasal IgA and plasma IgG anti-S responses (R = 0.05, p = 0.18), indicating that nasal IgA responses are distinct from those in plasma and minimally boosted by vaccination. INTERPRETATION: The decline in nasal IgA responses 9 months after infection and minimal impact of subsequent vaccination may explain the lack of long-lasting nasal defence against reinfection and the limited effects of vaccination on transmission. These findings highlight the need to develop vaccines that enhance nasal immunity. FUNDING: This study has been supported by ISARIC4C and PHOSP-COVID consortia. ISARIC4C is supported by grants from the National Institute for Health and Care Research and the Medical Research Council. Liverpool Experimental Cancer Medicine Centre provided infrastructure support for this research. The PHOSP-COVD study is jointly funded by UK Research and Innovation and National Institute of Health and Care Research. The funders were not involved in the study design, interpretation of data or the writing of this manuscript

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2,3,4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

Target plane imaging system for the Nova laser

The Nova laser, in operation since December 1984, is capable of irradiating targets with light at 1.05 ..mu..m, 0.53 ..mu..m, and 0.35 ..mu..m. Correct alignment of these harmonic beams uses a system called a target plane imager (TPI). It is a large microscope (four meters long, weighing one thousand kilograms) that relays images from the target chamber center to a video optics module located on the outside of the chamber. Several modes of operation are possible including: near-field viewing and far-field viewing at three magnifications and three wavelengths. In addition, the entire instrument can be scanned in X,Y,Z to examine various planes near chamber center. Performance of this system and its computer controls will be described

Multi-teraflops spin dynamics studies of the magnetic structure of FeMn/Co interfaces

The authors have used the power of massively parallel computers to perform first principles spin dynamics (SD) simulations of the magnetic structure of Iron-Manganese/Cobalt (FeMn/Co) interfaces. These large scale quantum mechanical simulations, involving 2016-atom super-cell models, reveal details of the orientational configuration of the magnetic moments at the interface that are unobtainable by any other means. Exchange bias, which involves the use of an antiferromagnetic (AFM) layer such as FeMn to pin the orientation of the magnetic moment of a proximate ferromagnetic (FM) layer such as Co, is of fundamental importance in magnetic multilayer storage and read head devices. Here the equation of motion of first principles SD is used to perform relaxations of model magnetic structures to the true ground (equilibrium) state. Our code is intrinsically parallel and has achieved a maximum execution rate of 2.46 Teraflops on the IBM SP at the National Energy Research Scientific Computing Center (NERSC)

Predictors of serum polychlorinated biphenyl concentrations in Anniston residents

The Anniston Community Health Survey was a community-based cross-sectional study of Anniston, Alabama, residents who live in close proximity to a former PCB production facility to identify factors associated with serum PCB levels. The survey comprises 765 Anniston residents who completed a questionnaire interview and provided a blood sample for analysis in 2005-2007. Several reports based on data from the Anniston survey have been previously published, including associations between PCB exposure and diabetes and blood pressure. In this study we examine demographic, behavioral, dietary, and occupational characteristics of Anniston survey participants as predictors of serum PCB concentrations. Of the 765 participants, 54% were White and 45% were African-American; the sample was predominantly female (70%), with a mean age of 55. years. Serum PCB concentrations varied widely between participants (range for sum of 35 PCBs: 0.11-170.4. ng/g wet weight). Linear regression models with stepwise selection were employed to examine factors associated with serum PCBs. Statistically significant positive associations were observed between serum PCB concentrations and age, race, residential variables, current smoking, and local fish consumption, as was a negative association with education level. Age and race were the most influential predictors of serum PCB levels. A small age by sex interaction was noted, indicating that the increase in PCB levels with age was steeper for women than for men. Significant interaction terms indicated that the associations between PCB levels and having ever eaten locally raised livestock and local clay were much stronger among African-Americans than among White participants. In summary, demographic variables and past consumption of locally produced foods were found to be the most important predictors of PCB concentrations in residents living in the vicinity of a former PCB manufacturing facility