Системный анализ процесса затвердевания литых заготовок разной массы и назначения

Выявлены особенности пространственно-временной эволюции температурных полей в процессе затвердевания разных заготовок (слитков и отливок) для повышения их качества.Виявлено особливості просторово-часової еволюції температурних полів в процесі тверднення різних заготовок (зливків та виливків) для підвищення їх якості.It is revealed the peculiarities of distance-time evolution of the temperature fields in solidification process different billets (ingots and casts) for raise them quality

Tephrochronology

Tephrochronology is the use of primary, characterized tephras or cryptotephras as chronostratigraphic marker beds to connect and synchronize geological, paleoenvironmental, or archaeological sequences or events, or soils/paleosols, and, uniquely, to transfer relative or numerical ages or dates to them using stratigraphic and age information together with mineralogical and geochemical compositional data, especially from individual glass-shard analyses, obtained for the tephra/cryptotephra deposits. To function as an age-equivalent correlation and chronostratigraphic dating tool, tephrochronology may be undertaken in three steps: (i) mapping and describing tephras and determining their stratigraphic relationships, (ii) characterizing tephras or cryptotephras in the laboratory, and (iii) dating them using a wide range of geochronological methods. Tephrochronology is also an important tool in volcanology, informing studies on volcanic petrology, volcano eruption histories and hazards, and volcano-climate forcing. Although limitations and challenges remain, multidisciplinary applications of tephrochronology continue to grow markedly

Nicotine exposure and transgenerational impact: a prospective study on small regulatory microRNAs

Early developmental stages are highly sensitive to stress and it has been reported that pre-conditioning with tobacco smoking during adolescence predisposes those youngsters to become smokers as adults. However, the molecular mechanisms of nicotine-induced transgenerational consequences are unknown. In this study, we genome-widely investigated the impact of nicotine exposure on small regulatory microRNAs (miRNAs) and its implication on health disorders at a transgenerational aspect. Our results demonstrate that nicotine exposure, even at the low dose, affected the global expression profiles of miRNAs not only in the treated worms (F0 parent generation) but also in two subsequent generations (F1 and F2, children and grandchildren). Some miRNAs were commonly affected by nicotine across two or more generations while others were specific to one. The general miRNA patterns followed a “two-hit� model as a function of nicotine exposure and abstinence. Target prediction and pathway enrichment analyses showed daf-4, daf-1, fos-1, cmk-1, and unc-30 to be potential effectors of nicotine addiction. These genes are involved in physiological states and phenotypes that paralleled previously published nicotine induced behavior. Our study offered new insights and further awareness on the transgenerational effects of nicotine exposed during the vulnerable post-embryonic stages, and identified new biomarkers for nicotine addiction.ECU Open Access Publishing Support Fun

Linking Proteomic and Transcriptional Data through the Interactome and Epigenome Reveals a Map of Oncogene-induced Signaling

Cellular signal transduction generally involves cascades of post-translational protein modifications that rapidly catalyze changes in protein-DNA interactions and gene expression. High-throughput measurements are improving our ability to study each of these stages individually, but do not capture the connections between them. Here we present an approach for building a network of physical links among these data that can be used to prioritize targets for pharmacological intervention. Our method recovers the critical missing links between proteomic and transcriptional data by relating changes in chromatin accessibility to changes in expression and then uses these links to connect proteomic and transcriptome data. We applied our approach to integrate epigenomic, phosphoproteomic and transcriptome changes induced by the variant III mutation of the epidermal growth factor receptor (EGFRvIII) in a cell line model of glioblastoma multiforme (GBM). To test the relevance of the network, we used small molecules to target highly connected nodes implicated by the network model that were not detected by the experimental data in isolation and we found that a large fraction of these agents alter cell viability. Among these are two compounds, ICG-001, targeting CREB binding protein (CREBBP), and PKF118–310, targeting β-catenin (CTNNB1), which have not been tested previously for effectiveness against GBM. At the level of transcriptional regulation, we used chromatin immunoprecipitation sequencing (ChIP-Seq) to experimentally determine the genome-wide binding locations of p300, a transcriptional co-regulator highly connected in the network. Analysis of p300 target genes suggested its role in tumorigenesis. We propose that this general method, in which experimental measurements are used as constraints for building regulatory networks from the interactome while taking into account noise and missing data, should be applicable to a wide range of high-throughput datasets.National Science Foundation (U.S.) (DB1-0821391)National Institutes of Health (U.S.) (Grant U54-CA112967)National Institutes of Health (U.S.) (Grant R01-GM089903)National Institutes of Health (U.S.) (P30-ES002109

Absorbing and transferring risk: assessing the impact of a statewide high-risk-pregnancy telemedical program on VLBW maternal transports

BACKGROUND: Prior research has shown that resources have an impact on birth outcomes. In this paper we ask how combinations of telemedical and hospital-level resources impact transports of mothers expecting very low birth weight (VLBW) babies in Arkansas. METHODS: Using de-identified birth certificate data from the Arkansas Department of Health, data were gathered on transports of women carrying VLBW babies for two six-month periods: a period just before the start of ANGELS (12/02-05/03), a telemedical outreach program for high-risk pregnancies, and a period after the program had been running for six months (12/03-05/04). For each maternal transport, the following information was recorded: maternal race-ethnicity, maternal age, and the birth weight of the infant. Logistic regression was used to assess the relationship between the predictors (telemedicine, hospital level, maternal characteristics) and the probability of a transport. RESULTS: Having a telemedical site available increases the probability of a mother carrying a VLBW baby being transported to a level III facility either before or during birth. Having at least a level II nursery also increases the chance of a maternal transport. Where both level II nurseries and telemedical access are available, the odds of VLBW maternal transports are only modestly increased in comparison to the case where neither is present. At the individual level, Hispanic mothers were less likely to be transported than other mothers, and teenaged mothers were more likely to be transported than those 18 and over. A mother's being Black or being over 35 did not have an impact on the odds of being transported to a level III facility. CONCLUSION: Combinations of resources have an impact on physician decisions regarding VLBW transports and are interpretable in terms of the capacity to diagnose and absorb risk. We suggest a collegial review of transport patterns and birth outcomes from areas with different levels of resources as a vehicle for moving the entire system of care forward over time. With such an evidence-based review in place, the collegial relations among level III specialists and obstetricians from around the state can, over time, develop workable protocols for when and how level III facilities should be involved

Surfing a genetic association interaction network to identify modulators of antibody response to smallpox vaccine

The variation in antibody response to vaccination likely involves small contributions of numerous genetic variants, such as single-nucleotide polymorphisms (SNPs), which interact in gene networks and pathways. To accumulate the bits of genetic information relevant to the phenotype that are distributed throughout the interaction network, we develop a network eigenvector centrality algorithm (SNPrank) that is sensitive to the weak main effects, gene–gene interactions and small higher-order interactions through hub effects. Analogous to Google PageRank, we interpret the algorithm as the simulation of a random SNP surfer (RSS) that accumulates bits of information in the network through a dynamic probabilistic Markov chain. The transition matrix for the RSS is based on a data-driven genetic association interaction network (GAIN), the nodes of which are SNPs weighted by the main-effect strength and edges weighted by the gene–gene interaction strength. We apply SNPrank to a GAIN analysis of a candidate-gene association study on human immune response to smallpox vaccine. SNPrank implicates a SNP in the retinoid X receptor α (RXRA) gene through a network interaction effect on antibody response. This vitamin A- and D-signaling mediator has been previously implicated in human immune responses, although it would be neglected in a standard analysis because its significance is unremarkable outside the context of its network centrality. This work suggests SNPrank to be a powerful method for identifying network effects in genetic association data and reveals a potential vitamin regulation network association with antibody response

Transcriptomics and adaptive genomics of the asymptomatic bacteriuria Escherichia coli strain 83972

Escherichia coli strains are the major cause of urinary tract infections in humans. Such strains can be divided into virulent, UPEC strains causing symptomatic infections, and asymptomatic, commensal-like strains causing asymptomatic bacteriuria, ABU. The best-characterized ABU strain is strain 83972. Global gene expression profiling of strain 83972 has been carried out under seven different sets of environmental conditions ranging from laboratory minimal medium to human bladders. The data reveal highly specific gene expression responses to different conditions. A number of potential fitness factors for the human urinary tract could be identified. Also, presence/absence data of the gene expression was used as an adaptive genomics tool to model the gene pool of 83972 using primarily UPEC strain CFT073 as a scaffold. In our analysis, 96% of the transcripts filtered present in strain 83972 can be found in CFT073, and genes on six of the seven pathogenicity islands were expressed in 83972. Despite the very different patient symptom profiles, the two strains seem to be very similar. Genes expressed in CFT073 but not in 83972 were identified and can be considered as virulence factor candidates. Strain 83972 is a deconstructed pathogen rather than a commensal strain that has acquired fitness properties

Systematic identification of conserved motif modules in the human genome

<p>Abstract</p> <p>Background</p> <p>The identification of motif modules, groups of multiple motifs frequently occurring in DNA sequences, is one of the most important tasks necessary for annotating the human genome. Current approaches to identifying motif modules are often restricted to searches within promoter regions or rely on multiple genome alignments. However, the promoter regions only account for a limited number of locations where transcription factor binding sites can occur, and multiple genome alignments often cannot align binding sites with their true counterparts because of the short and degenerative nature of these transcription factor binding sites.</p> <p>Results</p> <p>To identify motif modules systematically, we developed a computational method for the entire non-coding regions around human genes that does not rely upon the use of multiple genome alignments. First, we selected orthologous DNA blocks approximately 1-kilobase in length based on discontiguous sequence similarity. Next, we scanned the conserved segments in these blocks using known motifs in the TRANSFAC database. Finally, a frequent pattern mining technique was applied to identify motif modules within these blocks. In total, with a false discovery rate cutoff of 0.05, we predicted 3,161,839 motif modules, 90.8% of which are supported by various forms of functional evidence. Compared with experimental data from 14 ChIP-seq experiments, on average, our methods predicted 69.6% of the ChIP-seq peaks with TFBSs of multiple TFs. Our findings also show that many motif modules have distance preference and order preference among the motifs, which further supports the functionality of these predictions.</p> <p>Conclusions</p> <p>Our work provides a large-scale prediction of motif modules in mammals, which will facilitate the understanding of gene regulation in a systematic way.</p