A Bayesian shared component model for genetic association studies

We present a novel approach to address genome association studies between single nucleotide polymorphisms (SNPs) and disease. We propose a Bayesian shared component model to tease out the genotype information that is common to cases and controls from the one that is specific to cases only. This allows to detect the SNPs that show the strongest association with the disease. The model can be applied to case-control studies with more than one disease. In fact, we illustrate the use of this model with a dataset of 23,418 SNPs from a case-control study by The Welcome Trust Case Control Consortium (2007) with 2,000 patients with diabetes type 1, 2,000 with diabetes type 2 and a control group with 3,000 individuals. We carry out a simulation study to assess the sensitivity and specificity of our model to detect SNPs with excess risk. Our results show that the method we propose here can be a very useful tool for this type of studies. The model has been implemented in the bayesGen library of the R statistical package

VLTI/AMBER spectro-interferometry of the late-type supergiants V766 Cen (=HR 5171 A), sigma Oph, BM Sco, and HD 206859

We add four warmer late-type supergiants to our previous spectro-interferometric studies of red giants and supergiants. V766 Cen (=HR 5171 A) is found to be a high-luminosity log(L/L_sun)=5.8+-0.4 source of Teff 4290+-760 K and radius 1490+-540 Rsun located close to both the Hayashi and Eddington limits; this source is consistent with a 40 Msun evolutionary track without rotation and current mass 27-36 Msun. It exhibits NaI in emission arising from a shell of radius 1.5 Rphot and a photocenter displacement of about 0.1 Rphot. V766 Cen shows strong extended molecular (CO) layers and a dusty circumstellar background component. This suggest an optically thick pseudo-photosphere at about 1.5 Rphot at the onset of the wind. V766 Cen is a red supergiant located close to the Hayashi limit instead of a yellow hypergiant already evolving back toward warmer Teff as previously discussed. The stars sigma Oph, BM Sco, and HD 206859 are found to have lower luminosities of about log(L/Lsun)=3.4-3.5 and Teff of 3900-5300 K, corresponding to 5-9 Msun tracks. They do not show extended molecular layers as observed for higher luminosity red supergiants of our sample. BM Sco shows an unusually strong contribution by an over-resolved circumstellar dust component. These stars are more likely high-mass red giants instead of red supergiants. This leaves us with an unsampled locus in the HR diagram corresponding to luminosities log(L/Lsun)~3.8-4.8 or masses 10-13 Msun, possibly corresponding to the mass region where stars explode as type II-P supernovae during the RSG stage. Our previously found relation of increasing strength of extended molecular layers with increasing luminosities is now confirmed to extend to double our previous luminosities and up to the Eddington limit. This might further point to steadily increasing radiative winds with increasing luminosity. [Abridged]Comment: 16 pages, 14 figures, accepted for publication in Astronomy and Astrophysics (A&A

What causes the large extensions of red-supergiant atmospheres? Comparisons of interferometric observations with 1-D hydrostatic, 3-D convection, and 1-D pulsating model atmospheres

We present the atmospheric structure and the fundamental parameters of three red supergiants, increasing the sample of RSGs observed by near-infrared spectro-interferometry. Additionally, we test possible mechanisms that may explain the large observed atmospheric extensions of RSGs. We carried out spectro-interferometric observations of 3 RSGs in the near-infrared K-band with the VLTI/AMBER instrument at medium spectral resolution. To comprehend the extended atmospheres, we compared our observational results to predictions by available hydrostatic PHOENIX, available 3-D convection, and new 1-D self-excited pulsation models of RSGs. Our near-infrared flux spectra are well reproduced by the PHOENIX model atmospheres. The continuum visibility values are consistent with a limb-darkened disk as predicted by the PHOENIX models, allowing us to determine the angular diameter and the fundamental parameters of our sources. Nonetheless, in the case of V602 Car and HD 95686, the PHOENIX model visibilities do not predict the large observed extensions of molecular layers, most remarkably in the CO bands. Likewise, the 3-D convection models and the 1-D pulsation models with typical parameters of RSGs lead to compact atmospheric structures as well, which are similar to the structure of the hydrostatic PHOENIX models. They can also not explain the observed decreases in the visibilities and thus the large atmospheric molecular extensions. The full sample of our RSGs indicates increasing observed atmospheric extensions with increasing luminosity and decreasing surface gravity, and no correlation with effective temperature or variability amplitude, which supports a scenario of radiative acceleration on Doppler-shifted molecular lines.Comment: Accepted for publication in A&

Estimation of treatment policy estimands for continuous outcomes using off treatment sequential multiple imputation

The estimands framework outlined in ICH E9 (R1) describes the components needed to precisely define the effects to be estimated in clinical trials, which includes how post-baseline "intercurrent" events (IEs) are to be handled. In late-stage clinical trials, it is common to handle intercurrent events like "treatment discontinuation" using the treatment policy strategy and target the treatment effect on all outcomes regardless of treatment discontinuation. For continuous repeated measures, this type of effect is often estimated using all observed data before and after discontinuation using either a mixed model for repeated measures (MMRM) or multiple imputation (MI) to handle any missing data. In basic form, both of these estimation methods ignore treatment discontinuation in the analysis and therefore may be biased if there are differences in patient outcomes after treatment discontinuation compared to patients still assigned to treatment, and missing data being more common for patients who have discontinued treatment. We therefore propose and evaluate a set of MI models that can accommodate differences between outcomes before and after treatment discontinuation. The models are evaluated in the context of planning a phase 3 trial for a respiratory disease. We show that analyses ignoring treatment discontinuation can introduce substantial bias and can sometimes underestimate variability. We also show that some of the MI models proposed can successfully correct the bias but inevitably lead to increases in variance. We conclude that some of the proposed MI models are preferable to the traditional analysis ignoring treatment discontinuation, but the precise choice of MI model will likely depend on the trial design, disease of interest and amount of observed and missing data following treatment discontinuation

Fabrication and Characterisation of an Adaptable Plasmonic Nanorod Array for Solar Energy Conversion

The surface plasmonic modes of a side-by-side aligned gold nanorod array supported on a gold substrate has been characterised by electron energy loss spectroscopy (EELS). Plasmonic coupling within the array splits the nanorods' longitudinal mode into a bright mode (symmetrically aligned dipoles) and a dark mode (anti-symmetrically aligned dipoles). We support this observation by means of finite element modelling (FEM)

Feasibility and utility of mapping disease risk at the neighbourhood level within a Canadian public health unit: an ecological study

<p>Abstract</p> <p>Background</p> <p>We conducted spatial analyses to determine the geographic variation of cancer at the neighbourhood level (dissemination areas or DAs) within the area of a single Ontario public health unit, Wellington-Dufferin-Guelph, covering a population of 238,326 inhabitants. Cancer incidence data between 1999 and 2003 were obtained from the Ontario Cancer Registry and were geocoded down to the level of DA using the enhanced Postal Code Conversion File. The 2001 Census of Canada provided information on the size and age-sex structure of the population at the DA level, in addition to information about selected census covariates, such as average neighbourhood income.</p> <p>Results</p> <p>Age standardized incidence ratios for cancer and the prevalence of census covariates were calculated for each of 331 dissemination areas in Wellington-Dufferin-Guelph. The standardized incidence ratios (SIR) for cancer varied dramatically across the dissemination areas. However, application of the Moran's I statistic, a popular index of spatial autocorrelation, suggested significant spatial patterns for only two cancers, lung and prostate, both in males (p < 0.001 and p = 0.002, respectively). Employing Bayesian hierarchical models, areas in the urban core of the City of Guelph had significantly higher SIRs for male lung cancer than the remainder of Wellington-Dufferin-Guelph; and, neighbourhoods in the urban and surrounding rural areas of Orangeville exhibited significantly higher SIRs for prostate cancer. After adjustment for age and spatial dependence, average household income attenuated much of the spatial pattern of lung cancer, but not of prostate cancer.</p> <p>Conclusion</p> <p>This paper demonstrates the feasibility and utility of a systematic approach to identifying neighbourhoods, within the area served by a public health unit, that have significantly higher risks of cancer. This exploratory, ecologic study suggests several hypotheses for these spatial patterns that warrant further investigations. To the best of our knowledge, this is the first Canadian study published in the peer-reviewed literature estimating the risk of relatively rare public health outcomes at a very small areal level, namely dissemination areas.</p

Adaptive Control Optimization of Cutting Parameters for High Quality Machining Operations Based on Neural Networks and Search Algorithms

This book chapter presents an Adaptive Control with Optimization (ACO) system for optimising a multi-objective function based on material removal rate, quality loss function related to surface roughness, and cutting-tool life subjected to surface roughness specifications constraint