Genome-wide analysis in German shepherd dogs reveals association of a locus on CFA 27 with atopic dermatitis

Humans and dogs are both affected by the allergic skin disease atopic dermatitis (AD), caused by an interaction between genetic and environmental factors. The German shepherd dog (GSD) is a high-risk breed for canine AD (CAD). In this study, we used a Swedish cohort of GSDs as a model for human AD. Serum IgA levels are known to be lower in GSDs compared to other breeds. We detected significantly lower IgA levels in the CAD cases compared to controls (p = 1.1 × 10(-5)) in our study population. We also detected a separation within the GSD cohort, where dogs could be grouped into two different subpopulations. Disease prevalence differed significantly between the subpopulations contributing to population stratification (λ = 1.3), which was successfully corrected for using a mixed model approach. A genome-wide association analysis of CAD was performed (n cases = 91, n controls = 88). IgA levels were included in the model, due to the high correlation between CAD and low IgA levels. In addition, we detected a correlation between IgA levels and the age at the time of sampling (corr = 0.42, p = 3.0 × 10(-9)), thus age was included in the model. A genome-wide significant association was detected on chromosome 27 (praw = 3.1 × 10(-7), pgenome = 0.03). The total associated region was defined as a ~1.5-Mb-long haplotype including eight genes. Through targeted re-sequencing and additional genotyping of a subset of identified SNPs, we defined 11 smaller haplotype blocks within the associated region. Two blocks showed the strongest association to CAD. The ~209-kb region, defined by the two blocks, harbors only the PKP2 gene, encoding Plakophilin 2 expressed in the desmosomes and important for skin structure. Our results may yield further insight into the genetics behind both canine and human AD.

BENCHMARKING AND IMPLEMENTATION OF A NEW INDEPENDENT MONTE CARLO DOSE CALCULATION QUALITY ASSURANCE AUDIT TOOL FOR CLINICAL TRIALS

Introduction Commercial treatment planning systems employ a variety of dose calculation algorithms to plan and predict the dose distributions a patient receives during external beam radiation therapy. Traditionally, the Radiological Physics Center has relied on measurements to assure that institutions participating in the National Cancer Institute sponsored clinical trials administer radiation in doses that are clinically comparable to those of other participating institutions. To complement the effort of the RPC, an independent dose calculation tool needs to be developed that will enable a generic method to determine patient dose distributions in three dimensions and to perform retrospective analysis of radiation delivered to patients who enrolled in past clinical trials. Methods A multi-source model representing output for Varian 6 MV and 10 MV photon beams was developed and evaluated. The Monte Carlo algorithm, know as the Dose Planning Method (DPM), was used to perform the dose calculations. The dose calculations were compared to measurements made in a water phantom and in anthropomorphic phantoms. Intensity modulated radiation therapy and stereotactic body radiation therapy techniques were used with the anthropomorphic phantoms. Finally, past patient treatment plans were selected and recalculated using DPM and contrasted against a commercial dose calculation algorithm. Results The multi-source model was validated for the Varian 6 MV and 10 MV photon beams. The benchmark evaluations demonstrated the ability of the model to accurately calculate dose for the Varian 6 MV and the Varian 10 MV source models. The patient calculations proved that the model was reproducible in determining dose under similar conditions described by the benchmark tests. Conclusions The dose calculation tool that relied on a multi-source model approach and used the DPM code to calculate dose was developed, validated, and benchmarked for the Varian 6 MV and 10 MV photon beams. Several patient dose distributions were contrasted against a commercial algorithm to provide a proof of principal to use as an application in monitoring clinical trial activity.

Effect of an intervertebral disk spacer on stiffness after monocortical screw/polymethylmethacrylate fixation in simulated and cadaveric canine cervical vertebral columns.

OBJECTIVE To determine the biomechanical effect of an intervertebral spacer on construct stiffness in a PVC model and cadaveric canine cervical vertebral columns stabilized with monocortical screws/polymethylmethacrylate (PMMA). STUDY DESIGN Biomechanical study. SAMPLE POPULATION PVC pipe; cadaveric canine vertebral columns. METHODS PVC model-PVC pipe was used to create a gap model mimicking vertebral endplate orientation and disk space width of large-breed canine cervical vertebrae; 6 models had a 4-mm gap with no spacer (PVC group 1); 6 had a PVC pipe ring spacer filling the gap (PCV group 2). Animals-large breed cadaveric canine cervical vertebral columns (C2-C7) from skeletally mature dogs without (cadaveric group 1, n = 6, historical data) and with an intervertebral disk spacer (cadaveric group 2, n = 6) were used. All PVC models and cadaver specimens were instrumented with monocortical titanium screws/PMMA. Stiffness of the 2 PVC groups was compared in extension, flexion, and lateral bending using non-destructive 4-point bend testing. Stiffness testing in all 3 directions was performed of the unaltered C4-C5 vertebral motion unit in cadaveric spines and repeated after placement of an intervertebral cortical allograft ring and instrumentation. Data were compared using a linear mixed model approach that also incorporated data from previously tested spines with the same screw/PMMA construct but without disk spacer (cadaveric group 1). RESULTS Addition of a spacer increased construct stiffness in both the PVC model (P < .001) and cadaveric vertebral columns (P < .001) compared to fixation without a spacer. CONCLUSIONS Addition of an intervertebral spacer significantly increased construct stiffness of monocortical screw/PMMA fixation.

Genomics of Rapid Incipient Speciation in Sympatric Threespine Stickleback

Ecological speciation is the process by which reproductively isolated populations emerge as a consequence of divergent natural or ecologically-mediated sexual selection. Most genomic studies of ecological speciation have investigated allopatric populations, making it difficult to infer reproductive isolation. The few studies on sympatric ecotypes have focused on advanced stages of the speciation process after thousands of generations of divergence. As a consequence, we still do not know what genomic signatures of the early onset of ecological speciation look like. Here, we examined genomic differentiation among migratory lake and resident stream ecotypes of threespine stickleback reproducing in sympatry in one stream, and in parapatry in another stream. Importantly, these ecotypes started diverging less than 150 years ago. We obtained 34,756 SNPs with restriction-site associated DNA sequencing and identified genomic islands of differentiation using a Hidden Markov Model approach. Consistent with incipient ecological speciation, we found significant genomic differentiation between ecotypes both in sympatry and parapatry. Of 19 islands of differentiation resisting gene flow in sympatry, all were also differentiated in parapatry and were thus likely driven by divergent selection among habitats. These islands clustered in quantitative trait loci controlling divergent traits among the ecotypes, many of them concentrated in one region with low to intermediate recombination. Our findings suggest that adaptive genomic differentiation at many genetic loci can arise and persist in sympatry at the very early stage of ecotype divergence, and that the genomic architecture of adaptation may facilitate this.

Application of stellar photometry to the analysis of microarray images

Improvements in the analysis of microarray images are critical for accurately quantifying gene expression levels. The acquisition of accurate spot intensities directly influences the results and interpretation of statistical analyses. This dissertation discusses the implementation of a novel approach to the analysis of cDNA microarray images. We use a stellar photometric model, the Moffat function, to quantify microarray spots from nylon microarray images. The inherent flexibility of the Moffat shape model makes it ideal for quantifying microarray spots. We apply our novel approach to a Wilms' tumor microarray study and compare our results with a fixed-circle segmentation approach for spot quantification. Our results suggest that different spot feature extraction methods can have an impact on the ability of statistical methods to identify differentially expressed genes. We also used the Moffat function to simulate a series of microarray images under various experimental conditions. These simulations were used to validate the performance of various statistical methods for identifying differentially expressed genes. Our simulation results indicate that tests taking into account the dependency between mean spot intensity and variance estimation, such as the smoothened t-test, can better identify differentially expressed genes, especially when the number of replicates and mean fold change are low. The analysis of the simulations also showed that overall, a rank sum test (Mann-Whitney) performed well at identifying differentially expressed genes. Previous work has suggested the strengths of nonparametric approaches for identifying differentially expressed genes. We also show that multivariate approaches, such as hierarchical and k-means cluster analysis along with principal components analysis, are only effective at classifying samples when replicate numbers and mean fold change are high. Finally, we show how our stellar shape model approach can be extended to the analysis of 2D-gel images by adapting the Moffat function to take into account the elliptical nature of spots in such images. Our results indicate that stellar shape models offer a previously unexplored approach for the quantification of 2D-gel spots. ^

Radiogenic isotope trace composition of the Labrador Sea

Geological reconstructions and general circulation models suggest that the onset of both Northern Hemisphere glaciation, 2.7 Myr ago, and convection of Labrador Sea Water (LSW) were caused by the closure of the Panama Gateway ~4.5 Myr ago. Time series data that have been obtained from studies of ferromanganese crusts from the northwestern Atlantic suggest that radiogenic isotopes of intermediate ocean residence time (Pb and Nd) can serve as suitable tracers to reconstruct these events. However, it has been unclear until now as to whether the changes that have been observed in isotope composition at this time are the result of increased thermohaline circulation or due to the effects of increased glacial weathering. In this paper we adopt a box model approach to demonstrate that the shifts in radiogenic isotope compositions are unlikely to be due to changes in convection in LSW but can be explained in terms of increases of erosion levels due to the glaciation of Greenland and Canada. Furthermore, we provide experimental evidence for the incongruent release of a labile fraction of strongly radiogenic Pb and nonradiogenic Nd from continental detritus eroding into the Labrador Sea. This can be attributed to the glacial weathering of old continents and accounts for the paradox that one of the areas of the world most deficient in radiogenic Pb should provide such a rich supply of radiogenic Pb to the oceans. An important general conclusion is that the compositions of radiogenic isotopes in seawater are not always a reflection of their continental sources. Perhaps more importantly, the transition from chemical weathering to mechanical erosion is likely to result in significant variations in radiogenic tracers in seawater.

(Table 1) Estimated e-Nd(0) input calculated using the relative fraction of ODP Hole 105-647A amphibole grains originated from different provinces of the North America

Many marine radiogenic isotope records show both spatial and temporal variations, reflecting both the degree of mixing of distinct sources in the oceans and changes in the distribution of chemical weathering on the continents. However, changes in weathering and transport processes may themselves affect the composition of radiogenic isotopes released into seawater. The provenance of physically weathered material in the Labrador Sea, constrained through the use of Ar-Ar ages of individual detrital minerals, has been used to estimate the relative contributions of chemically weathered terranes releasing radiogenic isotopes into the Labrador Sea. A simple box-model approach for balancing observed Nd-isotope variations has been used to constrain the relative importance of localised input in the Labrador Sea, and the subsequent mixing of Labrador Sea Water into North Atlantic Deep-Water. The long-term pattern of erosion and deep-water formation around the North Atlantic seems to have been a relatively stable feature since 1.5 Ma, although there has been a dramatic shift in the nature of physical and chemical weathering affecting the release of Hf and Pb isotopes. The modelled Nd isotopes imply a relative decrease in water mass advection into the Labrador Sea between 2.4 and 1.5 Ma, accompanied by a decrease in the rate of overturning, possibly caused by an increased freshwater input into the Labrador Sea.

Consequences of different meteorological scenarios in the environmental impact assessment of tritium in air

The environmental impact of systems managing large (kg) tritium amount represents a public scrutiny issue for the next coming fusion facilities as ITER and DEMO. Furthermore, potentially new dose limits imposed by international regulations (ICRP) shall impact next coming devices designs and the overall costs of fusion technology deployment. Refined environmental tritium dose impact assessment schemes are then overwhelming. Detailed assessments can be procured from the knowledge of the real boundary conditions of the primary tritium discharge phase into atmosphere (low levels) and into soils. Lagrangian dispersion models using real-time meteorological and topographic data provide a strong refinement. Advance simulation tools are being developed in this sense. The tool integrates a numerical model output records from European Centre for Medium range Weather Forecast (ECMWF) with a lagrangian atmospheric dispersion model (FLEXPART). The composite model ECMWF/FLEXTRA results can be coupled with tritium dose secondary phase pathway assessment tools. Nominal tritium discharge operational reference and selected incidental ITER-like plant systems tritium form source terms have been assumed. The realtime daily data and mesh-refined records together with lagrangian dispersion model approach provide accurate results for doses to population by inhalation or ingestion in the secondary phase

Language identification based on a discriminative text categorization technique

In this paper, we describe new results and improvements to a lan-guage identification (LID) system based on PPRLM previously introduced in [1] and [2]. In this case, we use as parallel phone recognizers the ones provided by the Brno University of Technology for Czech, Hungarian, and Russian lan-guages, and instead of using traditional n-gram language models we use a lan-guage model that is created using a ranking with the most frequent and discrim-inative n-grams. In this language model approach, the distance between the ranking for the input sentence and the ranking for each language is computed, based on the difference in relative positions for each n-gram. This approach is able to model reliably longer span information than in traditional language models obtaining more reliable estimations. We also describe the modifications that we have being introducing along the time to the original ranking technique, e.g., different discriminative formulas to establish the ranking, variations of the template size, the suppression of repeated consecutive phones, and a new clus-tering technique for the ranking scores. Results show that this technique pro-vides a 12.9% relative improvement over PPRLM. Finally, we also describe re-sults where the traditional PPRLM and our ranking technique are combined.

Experimental and numerical analysis of concrete Slabs subjected to Blast

This paper summarizes the research activities focused on the behaviour of concrete and concrete structures subjected to blast loading carried out by the Department of Materials Science of the Technical University of Madrid (PUM). These activities comprise the design and construction of a test bench that allows for testing up to four planar concrete specimens with one single explosion, the study of the performance of different protection concepts for concrete structures and, finally, the development of a numerical model for the simulation of concrete structural elements subjected to blast. Up to date 6 different types of concrete have been studied, from plain normal strength concrete, to high strength concrete, including also fibre reinforced concretes with different types of fibres. The numerical model is based on the Cohesive Crack Model approach, and has been developed for the LSDYNA finite element code through a user programmed subroutine. Despite its simplicity, the model is able to predict the failure patterns of the concrete slabs tested with a high level of accuracy

Multiscale modeling of the plastic behaviour in single crystal tungsten: from atomistic to crystal plasticity simulations

En una planta de fusión, los materiales en contacto con el plasma así como los materiales de primera pared experimentan condiciones particularmente hostiles al estar expuestos a altos flujos de partículas, neutrones y grandes cargas térmicas. Como consecuencia de estas diferentes y complejas condiciones de trabajo, el estudio, desarrollo y diseño de estos materiales es uno de los más importantes retos que ha surgido en los últimos años para la comunidad científica en el campo de los materiales y la energía. Debido a su baja tasa de erosión, alta resistencia al sputtering, alta conductividad térmica, muy alto punto de fusión y baja retención de tritio, el tungsteno (wolframio) es un importante candidato como material de primera pared y como posible material estructural avanzado en fusión por confinamiento magnético e inercial. Sin embargo, el tiempo de vida del tungsteno viene controlado por diversos factores como son su respuesta termo-mecánica en la superficie, la posibilidad de fusión y el fallo por acumulación de helio. Es por ello que el tiempo de vida limitado por la respuesta mecánica del tungsteno (W), y en particular su fragilidad, sean dos importantes aspectos que tienes que ser investigados. El comportamiento plástico en materiales refractarios con estructura cristalina cúbica centrada en las caras (bcc) como el tungsteno está gobernado por las dislocaciones de tipo tornillo a escala atómica y por conjuntos e interacciones de dislocaciones a escalas más grandes. El modelado de este complejo comportamiento requiere la aplicación de métodos capaces de resolver de forma rigurosa cada una de las escalas. El trabajo que se presenta en esta tesis propone un modelado multiescala que es capaz de dar respuestas ingenieriles a las solicitudes técnicas del tungsteno, y que a su vez está apoyado por la rigurosa física subyacente a extensas simulaciones atomísticas. En primer lugar, las propiedades estáticas y dinámicas de las dislocaciones de tipo tornillo en cinco potenciales interatómicos de tungsteno son comparadas, determinando cuáles de ellos garantizan una mayor fidelidad física y eficiencia computacional. Las grandes tasas de deformación asociadas a las técnicas de dinámica molecular hacen que las funciones de movilidad de las dislocaciones obtenidas no puedan ser utilizadas en los siguientes pasos del modelado multiescala. En este trabajo, proponemos dos métodos alternativos para obtener las funciones de movilidad de las dislocaciones: un modelo Monte Cario cinético y expresiones analíticas. El conjunto de parámetros necesarios para formular el modelo de Monte Cario cinético y la ley de movilidad analítica son calculados atomísticamente. Estos parámetros incluyen, pero no se limitan a: la determinación de las entalpias y energías de formación de las parejas de escalones que forman las dislocaciones, la parametrización de los efectos de no Schmid característicos en materiales bcc,etc. Conociendo la ley de movilidad de las dislocaciones en función del esfuerzo aplicado y la temperatura, se introduce esta relación como ecuación de flujo dentro de un modelo de plasticidad cristalina. La predicción del modelo sobre la dependencia del límite de fluencia con la temperatura es validada experimentalmente con ensayos uniaxiales en tungsteno monocristalino. A continuación, se calcula el límite de fluencia al aplicar ensayos uniaxiales de tensión para un conjunto de orientaciones cristalográticas dentro del triángulo estándar variando la tasa de deformación y la temperatura de los ensayos. Finalmente, y con el objetivo de ser capaces de predecir una respuesta más dúctil del tungsteno para una variedad de estados de carga, se realizan ensayos biaxiales de tensión sobre algunas de las orientaciones cristalográficas ya estudiadas en función de la temperatura.-------------------------------------------------------------------------ABSTRACT ----------------------------------------------------------Tungsten and tungsten alloys are being considered as leading candidates for structural and functional materials in future fusion energy devices. The most attractive properties of tungsten for the design of magnetic and inertial fusion energy reactors are its high melting point, high thermal conductivity, low sputtering yield and low longterm disposal radioactive footprint. However, tungsten also presents a very low fracture toughness, mostly associated with inter-granular failure and bulk plasticity, that limits its applications. As a result of these various and complex conditions of work, the study, development and design of these materials is one of the most important challenges that have emerged in recent years to the scientific community in the field of materials for energy applications. The plastic behavior of body-centered cubic (bcc) refractory metals like tungsten is governed by the kink-pair mediated thermally activated motion of h¿ (\1 11)i screw dislocations on the atomistic scale and by ensembles and interactions of dislocations at larger scales. Modeling this complex behavior requires the application of methods capable of resolving rigorously each relevant scale. The work presented in this thesis proposes a multiscale model approach that gives engineering-level responses to the technical specifications required for the use of tungsten in fusion energy reactors, and it is also supported by the rigorous underlying physics of extensive atomistic simulations. First, the static and dynamic properties of screw dislocations in five interatomic potentials for tungsten are compared, determining which of these ensure greater physical fidelity and computational efficiency. The large strain rates associated with molecular dynamics techniques make the dislocation mobility functions obtained not suitable to be used in the next steps of the multiscale model. Therefore, it is necessary to employ mobility laws obtained from a different method. In this work, we suggest two alternative methods to get the dislocation mobility functions: a kinetic Monte Carlo model and analytical expressions. The set of parameters needed to formulate the kinetic Monte Carlo model and the analytical mobility law are calculated atomistically. These parameters include, but are not limited to: enthalpy and energy barriers of kink-pairs as a function of the stress, width of the kink-pairs, non-Schmid effects ( both twinning-antitwinning asymmetry and non-glide stresses), etc. The function relating dislocation velocity with applied stress and temperature is used as the main source of constitutive information into a dislocation-based crystal plasticity framework. We validate the dependence of the yield strength with the temperature predicted by the model against existing experimental data of tensile tests in singlecrystal tungsten, with excellent agreement between the simulations and the measured data. We then extend the model to a number of crystallographic orientations uniformly distributed in the standard triangle and study the effects of temperature and strain rate. Finally, we perform biaxial tensile tests and provide the yield surface as a function of the temperature for some of the crystallographic orientations explored in the uniaxial tensile tests.

Modelling inpatient length of stay by a hierarchical mixture regression via the EM algorithm

The modelling of inpatient length of stay (LOS) has important implications in health care studies. Finite mixture distributions are usually used to model the heterogeneous LOS distribution, due to a certain proportion of patients sustaining-a longer stay. However, the morbidity data are collected from hospitals, observations clustered within the same hospital are often correlated. The generalized linear mixed model approach is adopted to accommodate the inherent correlation via unobservable random effects. An EM algorithm is developed to obtain residual maximum quasi-likelihood estimation. The proposed hierarchical mixture regression approach enables the identification and assessment of factors influencing the long-stay proportion and the LOS for the long-stay patient subgroup. A neonatal LOS data set is used for illustration, (C) 2003 Elsevier Science Ltd. All rights reserved.

Mixture modelling for cluster analysis

Cluster analysis via a finite mixture model approach is considered. With this approach to clustering, the data can be partitioned into a specified number of clusters g by first fitting a mixture model with g components. An outright clustering of the data is then obtained by assigning an observation to the component to which it has the highest estimated posterior probability of belonging; that is, the ith cluster consists of those observations assigned to the ith component (i = 1,..., g). The focus is on the use of mixtures of normal components for the cluster analysis of data that can be regarded as being continuous. But attention is also given to the case of mixed data, where the observations consist of both continuous and discrete variables.

Historical and contemporary mating patterns in remnant populations of the forest tree Fraxinus excelsior L.

Genetic variation at microsatellite markers was used to quantify genetic structure and mating behavior in a severely fragmented population of the wind-pollinated, wind-dispersed temperate tree Fraxinus excelsior in a deforested catchment in Scotland. Remnants maintain high levels of genetic diversity, comparable with those reported for continuous populations in southeastern Europe, and show low interpopulation differentiation (Theta = 0.080), indicating that historical gene exchange has not been limited (Nm = 3.48). We estimated from seeds collected from all trees producing fruits in three of five remnants that F. excelsior is predominantly outcrossing (t(m). = 0.971 +/- 0.028). Use of a neighborhood model approach to describe the relative contribution of local and long-distance pollen dispersal indicates that pollen gene flow into each of the three remnants is extensive (46-95%) and pollen dispersal has two components. The first is very localized and restricted to tens of meters around the mother trees. The second is a long-distance component with dispersal occurring over several kilometers. Effective dispersal distances, accounting for the distance and directionality to mother trees of sampled pollen donors, average 328 m and are greater than values reported for a continuous population. These results suggest that the opening of the landscape facilitates airborne pollen movement and may alleviate the expected detrimental genetic effects of fragmentation.