Photoemission electron microscopy of localized surface plasmons in silver nanostructures at telecommunication wavelengths

We image the field enhancement at Ag nanostructures using femtosecond laser pulses with a center wavelength of 1.55 micrometer. Imaging is based on non-linear photoemission observed in a photoemission electron microscope (PEEM). The images are directly compared to ultra violet PEEM and scanning electron microscopy (SEM) imaging of the same structures. Further, we have carried out atomic scale scanning tunneling microscopy (STM) on the same type of Ag nanostructures and on the Au substrate. Measuring the photoelectron spectrum from individual Ag particles shows a larger contribution from higher order photoemission process above the work function threshold than would be predicted by a fully perturbative model, consistent with recent results using shorter wavelengths. Investigating a wide selection of both Ag nanoparticles and nanowires, field enhancement is observed from 30% of the Ag nanoparticles and from none of the nanowires. No laser-induced damage is observed of the nanostructures neither during the PEEM experiments nor in subsequent SEM analysis. By direct comparison of SEM and PEEM images of the same nanostructures, we can conclude that the field enhancement is independent of the average nanostructure size and shape. Instead, we propose that the variations in observed field enhancement could originate from the wedge interface between the substrate and particles electrically connected to the substrate

Inference of α\alpha-particle density profiles from ITER collective Thomson scattering

The primary purpose of the collective Thomson scattering (CTS) diagnostic at ITER is to measure the properties of fast-ion populations, in particular those of fusion-born $\alpha$-particles. Based on the present design of the diagnostic, we compute and fit synthetic CTS spectra for the ITER baseline plasma scenario, including the effects of noise, refraction, multiple fast-ion populations, and uncertainties on nuisance parameters. As part of this, we developed a model for CTS that incorporates spatial effects of frequency-dependent refraction. While such effects will distort the measured ITER CTS spectra, we demonstrate that the true $\alpha$-particle densities can nevertheless be recovered to within ~10% from noisy synthetic spectra, using existing fitting methods that do not take these spatial effects into account. Under realistic operating conditions, we thus find the predicted performance of the ITER CTS system to be consistent with the ITER measurement requirements of a 20% accuracy on inferred $\alpha$-particle density profiles at 100 ms time resolution.Comment: 17 pages, 11 figures. Accepted for publication in Nucl. Fusio

Carrier-envelope phase dependent high-order harmonic generation with a high-repetition rate OPCPA-system

We study high-order harmonic generation with a high-repetition rate (200 kHz), few-cycle, driving laser, based on optical parametric chirped pulse amplification. The system delivers carrier-envelope phase stable, 8 fs, 10 μJ pulses at a central wavelength of 890 nm. High-order harmonics, generated in a high-pressure Ar gas jet, exhibit a strong CEP-dependence over a large spectral range owing to excellent stability of the driving laser pulses. This range can be divided into three spectral regions with distinct CEP influence. The observed spectral interference structures are explained by an analytical model based upon multiple pulse interferences.Marie Curie Research Training Network ATTOFELEuropean Research CouncilKnut and Alice Wallenberg foundationSwedish Foundation for Strategic ResearchSwedish Research Counci

Predicting the impact of Lynch syndrome-causing missense mutations from structural calculations

Accurate methods to assess the pathogenicity of mutations are needed to fully leverage the possibilities of genome sequencing in diagnosis. Current data-driven and bioinformatics approaches are, however, limited by the large number of new variations found in each newly sequenced genome, and often do not provide direct mechanistic insight. Here we demonstrate, for the first time, that saturation mutagenesis, biophysical modeling and co-variation analysis, performed in silico, can predict the abundance, metabolic stability, and function of proteins inside living cells. As a model system, we selected the human mismatch repair protein, MSH2, where missense variants are known to cause the hereditary cancer predisposition disease, known as Lynch syndrome. We show that the majority of disease-causing MSH2 mutations give rise to folding defects and proteasome-dependent degradation rather than inherent loss of function, and accordingly our in silico modeling data accurately identifies disease-causing mutations and outperforms the traditionally used genetic disease predictors. Thus, in conclusion, in silico biophysical modeling should be considered for making genotype-phenotype predictions and for diagnosis of Lynch syndrome, and perhaps other hereditary diseases

Dissecting the Shared Genetic Architecture of Suicide Attempt, Psychiatric Disorders, and Known Risk Factors

Background Suicide is a leading cause of death worldwide, and nonfatal suicide attempts, which occur far more frequently, are a major source of disability and social and economic burden. Both have substantial genetic etiology, which is partially shared and partially distinct from that of related psychiatric disorders. Methods We conducted a genome-wide association study (GWAS) of 29,782 suicide attempt (SA) cases and 519,961 controls in the International Suicide Genetics Consortium (ISGC). The GWAS of SA was conditioned on psychiatric disorders using GWAS summary statistics via multitrait-based conditional and joint analysis, to remove genetic effects on SA mediated by psychiatric disorders. We investigated the shared and divergent genetic architectures of SA, psychiatric disorders, and other known risk factors. Results Two loci reached genome-wide significance for SA: the major histocompatibility complex and an intergenic locus on chromosome 7, the latter of which remained associated with SA after conditioning on psychiatric disorders and replicated in an independent cohort from the Million Veteran Program. This locus has been implicated in risk-taking behavior, smoking, and insomnia. SA showed strong genetic correlation with psychiatric disorders, particularly major depression, and also with smoking, pain, risk-taking behavior, sleep disturbances, lower educational attainment, reproductive traits, lower socioeconomic status, and poorer general health. After conditioning on psychiatric disorders, the genetic correlations between SA and psychiatric disorders decreased, whereas those with nonpsychiatric traits remained largely unchanged. Conclusions Our results identify a risk locus that contributes more strongly to SA than other phenotypes and suggest a shared underlying biology between SA and known risk factors that is not mediated by psychiatric disorders.Peer reviewe