Prospects for asteroseismology

The observational basis for asteroseismology is being dramatically strengthened, through more than two years of data from the CoRoT satellite, the flood of data coming from the Kepler mission and, in the slightly longer term, from dedicated ground-based facilities. Our ability to utilize these data depends on further development of techniques for basic data analysis, as well as on an improved understanding of the relation between the observed frequencies and the underlying properties of the stars. Also, stellar modelling must be further developed, to match the increasing diagnostic potential of the data. Here we discuss some aspects of data interpretation and modelling, focussing on the important case of stars with solar-like oscillations.Comment: Proc. HELAS Workshop on 'Synergies between solar and stellar modelling', eds M. Marconi, D. Cardini & M. P. Di Mauro, Astrophys. Space Sci., in the press Revision: correcting abscissa labels on Figs 1 and

Modeling the Subsurface Structure of Sunspots

While sunspots are easily observed at the solar surface, determining their subsurface structure is not trivial. There are two main hypotheses for the subsurface structure of sunspots: the monolithic model and the cluster model. Local helioseismology is the only means by which we can investigate subphotospheric structure. However, as current linear inversion techniques do not yet allow helioseismology to probe the internal structure with sufficient confidence to distinguish between the monolith and cluster models, the development of physically realistic sunspot models are a priority for helioseismologists. This is because they are not only important indicators of the variety of physical effects that may influence helioseismic inferences in active regions, but they also enable detailed assessments of the validity of helioseismic interpretations through numerical forward modeling. In this paper, we provide a critical review of the existing sunspot models and an overview of numerical methods employed to model wave propagation through model sunspots. We then carry out an helioseismic analysis of the sunspot in Active Region 9787 and address the serious inconsistencies uncovered by \citeauthor{gizonetal2009}~(\citeyear{gizonetal2009,gizonetal2009a}). We find that this sunspot is most probably associated with a shallow, positive wave-speed perturbation (unlike the traditional two-layer model) and that travel-time measurements are consistent with a horizontal outflow in the surrounding moat.Comment: 73 pages, 19 figures, accepted by Solar Physic

Estimating overdiagnosis in giant cell arteritis diagnostic pathways using genetic data: genetic association study

Objectives GCA can be confirmed by temporal artery biopsy (TAB) but false negatives can occur. GCA may be overdiagnosed in TAB-negative cases, or if neither TAB nor imaging is done. We used HLA genetic association of TAB-positive GCA as an ‘unbiased umpire’ test to estimate historic overdiagnosis of GCA. Methods Patients diagnosed with GCA between 1990 and 2014 were genotyped. During this era, vascular imaging alone was rarely used to diagnose GCA. HLA region variants were jointly imputed from genome-wide genotypic data of cases and controls. Per-allele frequencies across all HLA variants with P < 1.0 × 10−5 were compared with population control data to estimate overdiagnosis rates in cases without a positive TAB. Results Genetic data from 663 GCA patients were compared with data from 2619 population controls. TAB-negative GCA (n = 147) and GCA without TAB result (n = 160) had variant frequencies intermediate between TAB-positive GCA (n = 356) and population controls. For example, the allele frequency of HLA-DRB1*04 was 32% for TAB-positive GCA, 29% for GCA without TAB result, 27% for TAB-negative GCA and 20% in population controls. Making several strong assumptions, we estimated that around two-thirds of TAB-negative cases and one-third of cases without TAB result may have been overdiagnosed. From these data, TAB sensitivity is estimated as 88%. Conclusions Conservatively assuming 95% specificity, TAB has a negative likelihood ratio of around 0.12. Our method for utilizing standard genotyping data as an ‘unbiased umpire’ might be used as a way of comparing the accuracy of different diagnostic pathways