Experience with index selection in icelandic sheep

International audienc

Multiscale Kinetic Monte-Carlo for Simulating Epitaxial Growth

We present a fast Monte-Carlo algorithm for simulating epitaxial surface growth, based on the continuous-time Monte-Carlo algorithm of Bortz, Kalos and Lebowitz. When simulating realistic growth regimes, much computational time is consumed by the relatively fast dynamics of the adatoms. Continuum and continuum-discrete hybrid methods have been developed to approach this issue; however in many situations, the density of adatoms is too low to efficiently and accurately simulate as a continuum. To solve the problem of fast adatom dynamics, we allow adatoms to take larger steps, effectively reducing the number of transitions required. We achieve nearly a factor of ten speed up, for growth at moderate temperatures and large D/F.Comment: 7 pages, 6 figures; revised text, accepted by PR

A trans-homologue interaction between reciprocally imprinted miR-127 and Rtl1 regulates placenta development.

The paternally expressed imprinted retrotransposon-like 1 (Rtl1) is a retrotransposon-derived gene that has evolved a function in eutherian placentation. Seven miRNAs, including miR-127, are processed from a maternally expressed antisense Rtl1 transcript (Rtl1as) and regulate Rtl1 levels through RNAi-mediated post-transcriptional degradation. To determine the relative functional role of Rtl1as miRNAs in Rtl1 dosage, we generated a mouse specifically deleted for miR-127. The miR-127 knockout mice exhibit placentomegaly with specific defects within the labyrinthine zone involved in maternal-fetal nutrient transfer. Although fetal weight is unaltered, specific Rtl1 transcripts and protein levels are increased in both the fetus and placenta. Phenotypic analysis of single (ΔmiR-127/Rtl1 or miR-127/ΔRtl1) and double (ΔmiR-127/ΔRtl1) heterozygous miR-127- and Rtl1-deficient mice indicate that Rtl1 is the main target gene of miR-127 in placental development. Our results demonstrate that miR-127 is an essential regulator of Rtl1, mediated by a trans-homologue interaction between reciprocally imprinted genes on the maternally and paternally inherited chromosomes.This work was supported by the Biotechnology and Biological Sciences Research Council (BBSRC) and Medical Research Council (MRC) and EU FP7 Marie Curie Action 290123 (INGENIUM). This work was partly funded by a National Health and Medical Research Council (NHMRC) CJ Martin Biomedical Fellowship to A.N.S.P.This is the accepted manuscript. The final version is available at http://dev.biologists.org/content/early/2015/07/01/dev.121996.abstract

Systematic Parameterization, Storage, and Representation of Volumetric DICOM Data

Tomographic medical imaging systems produce hundreds to thousands of slices, enabling three-dimensional (3D) analysis. Radiologists process these images through various tools and techniques in order to generate 3D renderings for various applications, such as surgical planning, medical education, and volumetric measurements. To save and store these visualizations, current systems use snapshots or video exporting, which prevents further optimizations and requires the storage of significant additional data. The Grayscale Softcopy Presentation State extension of the Digital Imaging and Communications in Medicine (DICOM) standard resolves this issue for two-dimensional (2D) data by introducing an extensive set of parameters, namely 2D Presentation States (2DPR), that describe how an image should be displayed. 2DPR allows storing these parameters instead of storing parameter applied images, which cause unnecessary duplication of the image data. Since there is currently no corresponding extension for 3D data, in this study, a DICOM-compliant object called 3D presentation states (3DPR) is proposed for the parameterization and storage of 3D medical volumes. To accomplish this, the 3D medical visualization process is divided into four tasks, namely pre-processing, segmentation, post-processing, and rendering. The important parameters of each task are determined. Special focus is given to the compression of segmented data, parameterization of the rendering process, and DICOM-compliant implementation of the 3DPR object. The use of 3DPR was tested in a radiology department on three clinical cases, which require multiple segmentations and visualizations during the workflow of radiologists. The results show that 3DPR can effectively simplify the workload of physicians by directly regenerating 3D renderings without repeating intermediate tasks, increase efficiency by preserving all user interactions, and provide efficient storage as well as transfer of visualized data. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s40846-015-0097-5) contains supplementary material, which is available to authorized users

New approaches for the assessment of vessel sizes in quantitative (cardio-)vascular X-ray analysis

This paper presents new approaches for the assessment of the arterial and reference diameters in (cardio-)vascular X-ray images, designed to overcome the problems experienced in conventional quantitative coronary and vascular angiography approaches. In single or “straight” vessel segments, the arterial and reference diameter directions were made independent of each other in order to be able to measure the minimal lumen diameter (MLD) more accurately, especially in curved vessel segments. For ostial segments, an extension of this approach was used, to allow measurement of ostial lesions in sidebranches more proximal than using conventional methods. Furthermore, two new bifurcation approaches were developed. The validation study shows that the straight segment approach results in significant smaller MLDs (on average 0.032 mm) and the ostial approach achieves on average an increase in %DS of 3.8% and an increase in lesion length of 0.59 mm due to loosening the directional constraint. The validation of our new bifurcation approaches in phantom data as well as clinical data shows only small differences between pre- and post-intervention measurements of the reference diameters outside the bifurcation core (errors smaller than 0.06 mm) and the bifurcation core area (errors smaller than 1.4% for phantom data). In summary, these new approaches have led to further improvements in the quantitative analyses of (cardio-)vascular X-ray angiographies

Missense Mutation in Exon 2 of SLC36A1 Responsible for Champagne Dilution in Horses

Champagne coat color in horses is controlled by a single, autosomal-dominant gene (CH). The phenotype produced by this gene is valued by many horse breeders, but can be difficult to distinguish from the effect produced by the Cream coat color dilution gene (CR). Three sires and their families segregating for CH were tested by genome scanning with microsatellite markers. The CH gene was mapped within a 6 cM region on horse chromosome 14 (LOD = 11.74 for θ = 0.00). Four candidate genes were identified within the region, namely SPARC [Secreted protein, acidic, cysteine-rich (osteonectin)], SLC36A1 (Solute Carrier 36 family A1), SLC36A2 (Solute Carrier 36 family A2), and SLC36A3 (Solute Carrier 36 family A3). SLC36A3 was not expressed in skin tissue and therefore not considered further. The other three genes were sequenced in homozygotes for CH and homozygotes for the absence of the dilution allele (ch). SLC36A1 had a nucleotide substitution in exon 2 for horses with the champagne phenotype, which resulted in a transition from a threonine amino acid to an arginine amino acid (T63R). The association of the single nucleotide polymorphism (SNP) with the champagne dilution phenotype was complete, as determined by the presence of the nucleotide variant among all 85 horses with the champagne dilution phenotype and its absence among all 97 horses without the champagne phenotype. This is the first description of a phenotype associated with the SLC36A1 gene

Stochastic simulation and analysis of biomolecular reaction networks

<p>Abstract</p> <p>Background</p> <p>In recent years, several stochastic simulation algorithms have been developed to generate Monte Carlo trajectories that describe the time evolution of the behavior of biomolecular reaction networks. However, the effects of various stochastic simulation and data analysis conditions on the observed dynamics of complex biomolecular reaction networks have not recieved much attention. In order to investigate these issues, we employed a a software package developed in out group, called Biomolecular Network Simulator (BNS), to simulate and analyze the behavior of such systems. The behavior of a hypothetical two gene <it>in vitro </it>transcription-translation reaction network is investigated using the Gillespie exact stochastic algorithm to illustrate some of the factors that influence the analysis and interpretation of these data.</p> <p>Results</p> <p>Specific issues affecting the analysis and interpretation of simulation data are investigated, including: (1) the effect of time interval on data presentation and time-weighted averaging of molecule numbers, (2) effect of time averaging interval on reaction rate analysis, (3) effect of number of simulations on precision of model predictions, and (4) implications of stochastic simulations on optimization procedures.</p> <p>Conclusion</p> <p>The two main factors affecting the analysis of stochastic simulations are: (1) the selection of time intervals to compute or average state variables and (2) the number of simulations generated to evaluate the system behavior.</p