Advanced Computational Research in Materials Processing for Design and Manufacturing

Advanced mathematical techniques and computer simulation play a major role in providing enhanced understanding of conventional and advanced materials processing operations. Development and application of mathematical models and computer simulation techniques can provide a quantitative understanding of materials processes and will minimize the need for expensive and time consuming trial- and error-based product development. As computer simulations and materials databases grow in complexity, high performance computing and simulation are expected to play a key role in supporting the improvements required in advanced material syntheses and processing by lessening the dependence on expensive prototyping and re-tooling. Many of these numerical models are highly compute-intensive. It is not unusual for an analysis to require several hours of computational time on current supercomputers despite the simplicity of the models being studied. For example, to accurately simulate the heat transfer in a 1-m{sup 3} block using a simple computational method requires 10`2 arithmetic operations per second of simulated time. For a computer to do the simulation in real time would require a sustained computation rate 1000 times faster than that achievable by current supercomputers. Massively parallel computer systems, which combine several thousand processors able to operate concurrently on a problem are expected to provide orders of magnitude increase in performance. This paper briefly describes advanced computational research in materials processing at ORNL. Continued development of computational techniques and algorithms utilizing the massively parallel computers will allow the simulation of conventional and advanced materials processes in sufficient generality

Columnar and Equiaxed Solidification of Al-7 wt.% Si Alloys in Reduced Gravity in the Framework of the CETSOL Project

International audienceDuring casting, often a dendritic microstructure is formed, resulting in a columnar or an equiaxed grain structure, or leading to a transition from columnar to equiaxed growth (CET). The detailed knowledge of the critical parameters for the CET is important because the microstructure affects materials properties. To provide unique data for testing of fundamental theories of grain and microstructure formation, solidification experiments in microgravity environment were performed within the European Space Agency Microgravity Application Promotion (ESA MAP) project Columnar-to-Equiaxed Transition in SOLidification Processing (CETSOL). Reduced gravity allows for purely diffusive solidification conditions, i.e., suppressing melt flow and sedimentation and floatation effects. On-board the International Space Station, Al-7 wt.% Si alloys with and without grain refiners were solidified in different temperature gradients and with different cooling conditions. Detailed analysis of the microstructure and the grain structure showed purely columnar growth for nonrefined alloys. The CET was detected only for refined alloys, either as a sharp CET in the case of a sudden increase in the solidification velocity or as a progressive CET in the case of a continuous decrease of the temperature gradient. The present experimental data were used for numerical modeling of the CET with three different approaches: (1) a front tracking model using an equiaxed growth model, (2) a three-dimensional (3D) cellular automaton–finite element model, and (3) a 3D dendrite needle network method. Each model allows for predicting the columnar dendrite tip undercooling and the growth rate with respect to time. Furthermore, the positions of CET and the spatial extent of the CET, being sharp or progressive, are in reasonably good quantitative agreement with experimental measurements

eIF5A Promotes Translation Elongation, Polysome Disassembly and Stress Granule Assembly

Stress granules (SGs) are cytoplasmic foci at which untranslated mRNAs accumulate in cells exposed to environmental stress. We have identified ornithine decarboxylase (ODC), an enzyme required for polyamine synthesis, and eIF5A, a polyamine (hypusine)-modified translation factor, as proteins required for arsenite-induced SG assembly. Knockdown of deoxyhypusine synthase (DHS) or treatment with a deoxyhypusine synthase inhibitor (GC7) prevents hypusine modification of eIF5A as well as arsenite-induced polysome disassembly and stress granule assembly. Time-course analysis reveals that this is due to a slowing of stress-induced ribosome run-off in cells lacking hypusine-eIF5A. Whereas eIF5A only marginally affects protein synthesis under normal conditions, it is required for the rapid onset of stress-induced translational repression. Our results reveal that hypusine-eIF5A-facilitated translation elongation promotes arsenite-induced polysome disassembly and stress granule assembly in cells subjected to adverse environmental conditions

Generation of ribosome imprinted polymers for sensitive detection of translational responses

Whilst the profiling of the transcriptome and proteome even of single-cells becomes feasible, the analysis of the translatome, which refers to all messenger RNAs (mRNAs) engaged with ribosomes for protein synthesis, is still an elaborate procedure requiring millions of cells. Herein, we report the generation and use of “smart materials”, namely molecularly imprinted polymers (MIPs) to facilitate the isolation of ribosomes and translated mRNAs from merely 1,000 cells. In particular, we show that a hydrogel-based ribosome imprinted polymer could recover ribosomes and associated mRNAs from human, simian and mice cellular extracts, but did not selectively enrich yeast ribosomes, thereby demonstrating selectivity. Furthermore, ribosome imprinted polymers enabled the sensitive measurement of an mRNA translational regulatory event, requiring 1,000-fold less cells than current methodologies. These results provide first evidence for the suitability of MIPs to selectively recover ribonucleoprotein complexes such as ribosomes, founding a novel means for sensitive detection of gene regulation

A reference panel of 64,976 haplotypes for genotype imputation.

We describe a reference panel of 64,976 human haplotypes at 39,235,157 SNPs constructed using whole-genome sequence data from 20 studies of predominantly European ancestry. Using this resource leads to accurate genotype imputation at minor allele frequencies as low as 0.1% and a large increase in the number of SNPs tested in association studies, and it can help to discover and refine causal loci. We describe remote server resources that allow researchers to carry out imputation and phasing consistently and efficiently

A Large-Scale Multi-ancestry Genome-wide Study Accounting for Smoking Behavior Identifies Multiple Significant Loci for Blood Pressure

Genome-wide association analysis advanced understanding of blood pressure (BP), a major risk factor for vascular conditions such as coronary heart disease and stroke. Accounting for smoking behavior may help identify BP loci and extend our knowledge of its genetic architecture. We performed genome-wide association meta-analyses of systolic and diastolic BP incorporating gene-smoking interactions in 610,091 individuals. Stage 1 analysis examined similar to 18.8 million SNPs and small insertion/deletion variants in 129,913 individuals from four ancestries (European, African, Asian, and Hispanic) with follow-up analysis of promising variants in 480,178 additional individuals from five ancestries. We identified 15 loci that were genome-wide significant (p <5 x 10(-8)) in stage 1 and formally replicated in stage 2. A combined stage 1 and 2 meta-analysis identified 66 additional genome-wide significant loci (13, 35, and 18 loci in European, African, and trans-ancestry, respectively). A total of 56 known BP loci were also identified by our results (p <5 x 10(-8)). Of the newly identified loci, ten showed significant interaction with smoking status, but none of them were replicated in stage 2. Several loci were identified in African ancestry, highlighting the importance of genetic studies in diverse populations. The identified loci show strong evidence for regulatory features and support shared pathophysiology with cardiometabolic and addiction traits. They also highlight a role in BP regulation for biological candidates such as modulators of vascular structure and function (CDKN1B, BCAR1-CFDP1, PXDN, EEA1), ciliopathies (SDCCAG8, RPGRIP1L), telomere maintenance (TNKS, PINX1, AKTIP), and central dopaminergic signaling MSRA, EBF2).Peer reviewe

Genome-wide analysis identifies 12 loci influencing human reproductive behavior.

The genetic architecture of human reproductive behavior-age at first birth (AFB) and number of children ever born (NEB)-has a strong relationship with fitness, human development, infertility and risk of neuropsychiatric disorders. However, very few genetic loci have been identified, and the underlying mechanisms of AFB and NEB are poorly understood. We report a large genome-wide association study of both sexes including 251,151 individuals for AFB and 343,072 individuals for NEB. We identified 12 independent loci that are significantly associated with AFB and/or NEB in a SNP-based genome-wide association study and 4 additional loci associated in a gene-based effort. These loci harbor genes that are likely to have a role, either directly or by affecting non-local gene expression, in human reproduction and infertility, thereby increasing understanding of these complex traits

Формирование эмоциональной культуры как компонента инновационной культуры студентов

Homozygosity has long been associated with rare, often devastating, Mendelian disorders1 and Darwin was one of the first to recognise that inbreeding reduces evolutionary fitness2. However, the effect of the more distant parental relatedness common in modern human populations is less well understood. Genomic data now allow us to investigate the effects of homozygosity on traits of public health importance by observing contiguous homozygous segments (runs of homozygosity, ROH), which are inferred to be homozygous along their complete length. Given the low levels of genome-wide homozygosity prevalent in most human populations, information is required on very large numbers of people to provide sufficient power3,4. Here we use ROH to study 16 health-related quantitative traits in 354,224 individuals from 102 cohorts and find statistically significant associations between summed runs of homozygosity (SROH) and four complex traits: height, forced expiratory lung volume in 1 second (FEV1), general cognitive ability (g) and educational attainment (nominal p<1 × 10−300, 2.1 × 10−6, 2.5 × 10−10, 1.8 × 10−10). In each case increased homozygosity was associated with decreased trait value, equivalent to the offspring of first cousins being 1.2 cm shorter and having 10 months less education. Similar effect sizes were found across four continental groups and populations with different degrees of genome-wide homozygosity, providing convincing evidence for the first time that homozygosity, rather than confounding, directly contributes to phenotypic variance. Contrary to earlier reports in substantially smaller samples5,6, no evidence was seen of an influence of genome-wide homozygosity on blood pressure and low density lipoprotein (LDL) cholesterol, or ten other cardio-metabolic traits. Since directional dominance is predicted for traits under directional evolutionary selection7, this study provides evidence that increased stature and cognitive function have been positively selected in human evolution, whereas many important risk factors for late-onset complex diseases may not have been