205 resultados para Wide-angle seismic modeling


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Recent studies have pointed out a similarity between tectonics and slope tectonic-induced structures. Numerous studies have demonstrated that structures and fabrics previously interpreted as of purely geodynamical origin are instead the result of large slope deformation, and this led in the past to erroneous interpretations. Nevertheless, their limit seems not clearly defined, but it is somehow transitional. Some studies point out continuity between failures developing at surface with upper crust movements. In this contribution, the main studies which examine the link between rock structures and slope movements are reviewed. The aspects regarding model and scale of observation are discussed together with the role of pre-existing weaknesses in the rock mass. As slope failures can develop through progressive failure, structures and their changes in time and space can be recognized. Furthermore, recognition of the origin of these structures can help in avoiding misinterpretations of regional geology. This also suggests the importance of integrating different slope movement classifications based on distribution and pattern of deformation and the application of structural geology techniques. A structural geology approach in the landslide community is a tool that can greatly support the hazard quantification and related risks, because most of the physical parameters, which are used for landslide modeling, are derived from geotechnical tests or the emerging geophysical approaches.

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Natural selection is typically exerted at some specific life stages. If natural selection takes place before a trait can be measured, using conventional models can cause wrong inference about population parameters. When the missing data process relates to the trait of interest, a valid inference requires explicit modeling of the missing process. We propose a joint modeling approach, a shared parameter model, to account for nonrandom missing data. It consists of an animal model for the phenotypic data and a logistic model for the missing process, linked by the additive genetic effects. A Bayesian approach is taken and inference is made using integrated nested Laplace approximations. From a simulation study we find that wrongly assuming that missing data are missing at random can result in severely biased estimates of additive genetic variance. Using real data from a wild population of Swiss barn owls Tyto alba, our model indicates that the missing individuals would display large black spots; and we conclude that genes affecting this trait are already under selection before it is expressed. Our model is a tool to correctly estimate the magnitude of both natural selection and additive genetic variance.

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The geological evolution of the northern Peru convergent margin can be traced using samples collected during deep-sea dives of the submersible Nautile. In the Paita area (5 degrees-6 degrees S), the sedimentary sequence was intensively sampled along the main scarp of the middle slope area. It consists of Upper Miocene (7-9 Ma) to Pleistocene siltstone, sandstone and rare dolostone. The age distribution of these samples is the basis for a new geologic interpretation of the multichannel seismic line CDP3. Siliceous microfossils (both diatoms and radiolarians) show influence of both cold and temperate waters (local species mixed with upwelling ones). Diatom assemblages studied from the NP1-13 and NP1-15 dives bear a strong resemblance to assemblages from the Pisco Formation of southern Peru. Micropaleontological data from siliceous microfossils, provide evidence for two main unconformities, one is at the base of the Quaternary sequence and the other corresponds to a hiatus of 1 Myr, separating the Upper Miocene (7-8 Ma) sediments from uppermost Miocene (5-6 Ma) sediments. During the past 400 kyr, a wide rollover fold developed in the middle slope area associated with a major seaward dipping detachment fault. A catastrophic debris avalanche occurred as the result of an oversteepening of the landward flank of the rollover fold. The gravity failure of the slope, recognized by SeaBEAM and hydrosweep mapping, displaced enough material to produce a destructive tsunami which occurred 13.8 +/- 2.7 kyr ago.

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Genotyping and molecular characterization of drug resistance mechanisms in Mycobacterium leprae enables disease transmission and drug resistance trends to be monitored. In the present study, we performed genome-wide analysis of Airaku-3, a multidrug-resistant strain with an unknown mechanism of resistance to rifampicin. We identified 12 unique non-synonymous single-nucleotide polymorphisms (SNPs) including two in the transporter-encoding ctpC and ctpI genes. In addition, two SNPs were found that improve the resolution of SNP-based genotyping, particularly for Venezuelan and South East Asian strains of M. leprae.

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A solution of (18)F was standardised with a 4pibeta-4pigamma coincidence counting system in which the beta detector is a one-inch diameter cylindrical UPS89 plastic scintillator, positioned at the bottom of a well-type 5''x5'' NaI(Tl) gamma-ray detector. Almost full detection efficiency-which was varied downwards electronically-was achieved in the beta-channel. Aliquots of this (18)F solution were also measured using 4pigamma NaI(Tl) integral counting and Monte Carlo calculated efficiencies as well as the CIEMAT-NIST method. Secondary measurements of the same solution were also performed with an IG11 ionisation chamber whose equivalent activity is traceable to the Système International de Référence through the contribution IRA-METAS made to it in 2001; IRA's degree of equivalence was found to be close to the key comparison reference value (KCRV). The (18)F activity predicted by this coincidence system agrees closely with the ionisation chamber measurement and is compatible within one standard deviation of the other primary measurements. This work demonstrates that our new coincidence system can standardise short-lived radionuclides used in nuclear medicine.

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The adipocyte-derived protein adiponectin is highly heritable and inversely associated with risk of type 2 diabetes mellitus (T2D) and coronary heart disease (CHD). We meta-analyzed 3 genome-wide association studies for circulating adiponectin levels (n = 8,531) and sought validation of the lead single nucleotide polymorphisms (SNPs) in 5 additional cohorts (n = 6,202). Five SNPs were genome-wide significant in their relationship with adiponectin (P< or =5x10(-8)). We then tested whether these 5 SNPs were associated with risk of T2D and CHD using a Bonferroni-corrected threshold of P< or =0.011 to declare statistical significance for these disease associations. SNPs at the adiponectin-encoding ADIPOQ locus demonstrated the strongest associations with adiponectin levels (P-combined = 9.2x10(-19) for lead SNP, rs266717, n = 14,733). A novel variant in the ARL15 (ADP-ribosylation factor-like 15) gene was associated with lower circulating levels of adiponectin (rs4311394-G, P-combined = 2.9x10(-8), n = 14,733). This same risk allele at ARL15 was also associated with a higher risk of CHD (odds ratio [OR] = 1.12, P = 8.5x10(-6), n = 22,421) more nominally, an increased risk of T2D (OR = 1.11, P = 3.2x10(-3), n = 10,128), and several metabolic traits. Expression studies in humans indicated that ARL15 is well-expressed in skeletal muscle. These findings identify a novel protein, ARL15, which influences circulating adiponectin levels and may impact upon CHD risk.

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Objective: The purpose of this study was to find loci for major depression via linkage analysis of a large sibling pair sample. Method: The authors conducted a genome-wide linkage analysis of 839 families consisting of 971 affected sibling pairs with severe recurrent major depression, comprising waves I and II of the Depression Network Study cohort. In addition to examining affected status, linkage analyses in the full data set were performed using diagnoses restricted by impairment severity, and association mapping of hits in a large case-control data set was attempted. Results: The authors identified genome-wide significant linkage to chromosome 3p25-26 when the diagnoses were restricted by severity, which was a maximum LOD score of 4.0 centered at the linkage marker D3S1515. The linkage signal identified was genome-wide significant after correction for the multiple phenotypes tested, although subsequent association mapping of the region in a genome-wide association study of a U.K. depression sample did not provide significant results. Conclusions: The authors report a genome-wide significant locus for depression that implicates genes that are highly plausible for involvement in the etiology of recurrent depression. Despite the fact that association mapping in the region was negative, the linkage finding was replicated by another group who found genome-wide-significant linkage for depression in the same region. This suggests that 3p25-26 is a new locus for severe recurrent depression. This represents the first report of a genome-wide significant locus for depression that also has an independent genome-wide significant replication.

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In the context of the investigation of the use of automated fingerprint identification systems (AFIS) for the evaluation of fingerprint evidence, the current study presents investigations into the variability of scores from an AFIS system when fingermarks from a known donor are compared to fingerprints that are not from the same source. The ultimate goal is to propose a model, based on likelihood ratios, which allows the evaluation of mark-to-print comparisons. In particular, this model, through its use of AFIS technology, benefits from the possibility of using a large amount of data, as well as from an already built-in proximity measure, the AFIS score. More precisely, the numerator of the LR is obtained from scores issued from comparisons between impressions from the same source and showing the same minutia configuration. The denominator of the LR is obtained by extracting scores from comparisons of the questioned mark with a database of non-matching sources. This paper focuses solely on the assignment of the denominator of the LR. We refer to it by the generic term of between-finger variability. The issues addressed in this paper in relation to between-finger variability are the required sample size, the influence of the finger number and general pattern, as well as that of the number of minutiae included and their configuration on a given finger. Results show that reliable estimation of between-finger variability is feasible with 10,000 scores. These scores should come from the appropriate finger number/general pattern combination as defined by the mark. Furthermore, strategies of obtaining between-finger variability when these elements cannot be conclusively seen on the mark (and its position with respect to other marks for finger number) have been presented. These results immediately allow case-by-case estimation of the between-finger variability in an operational setting.

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Adiponectin has a variety of metabolic effects on obesity, insulin sensitivity, and atherosclerosis. To identify genes influencing variation in plasma adiponectin levels, we performed genome-wide linkage and association scans of adiponectin in two cohorts of subjects recruited in the Genetic Epidemiology of Metabolic Syndrome Study. The genome-wide linkage scan was conducted in families of Turkish and southern European (TSE, n = 789) and Northern and Western European (NWE, N = 2,280) origin. A whole genome association (WGA) analysis (500K Affymetrix platform) was carried out in a set of unrelated NWE subjects consisting of approximately 1,000 subjects with dyslipidemia and 1,000 overweight subjects with normal lipids. Peak evidence for linkage occurred at chromosome 8p23 in NWE subjects (lod = 3.10) and at chromosome 3q28 near ADIPOQ, the adiponectin structural gene, in TSE subjects (lod = 1.70). In the WGA analysis, the single-nucleotide polymorphisms (SNPs) most strongly associated with adiponectin were rs3774261 and rs6773957 (P < 10(-7)). These two SNPs were in high linkage disequilibrium (r(2) = 0.98) and located within ADIPOQ. Interestingly, our fourth strongest region of association (P < 2 x 10(-5)) was to an SNP within CDH13, whose protein product is a newly identified receptor for high-molecular-weight species of adiponectin. Through WGA analysis, we confirmed previous studies showing SNPs within ADIPOQ to be strongly associated with variation in adiponectin levels and further observed these to have the strongest effects on adiponectin levels throughout the genome. We additionally identified a second gene (CDH13) possibly influencing variation in adiponectin levels. The impact of these SNPs on health and disease has yet to be determined.

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In mammals, the circadian clock allows them to anticipate and adapt physiology around the 24 hours. Conversely, metabolism and food consumption regulate the internal clock, pointing the existence of an intricate relationship between nutrient state and circadian homeostasis that is far from being understood. The Sterol Regulatory Element Binding Protein 1 (SREBP1) is a key regulator of lipid homeostasis. Hepatic SREBP1 function is influenced by the nutrient-response cycle, but also by the circadian machinery. To systematically understand how the interplay of circadian clock and nutrient-driven rhythm regulates SREBP1 activity, we evaluated the genome-wide binding of SREBP1 to its targets throughout the day in C57BL/6 mice. The recruitment of SREBP1 to the DNA showed a highly circadian behaviour, with a maximum during the fed status. However, the temporal expression of SREBP1 targets was not always synchronized with its binding pattern. In particular, different expression phases were observed for SREBP1 target genes depending on their function, suggesting the involvement of other transcription factors in their regulation. Binding sites for Hepatocyte Nuclear Factor 4 (HNF4) were specifically enriched in the close proximity of SREBP1 peaks of genes, whose expression was shifted by about 8 hours with respect to SREBP1 binding. Thus, the cross-talk between hepatic HNF4 and SREBP1 may underlie the expression timing of this subgroup of SREBP1 targets. Interestingly, the proper temporal expression profile of these genes was dramatically changed in Bmal1-/- mice upon time-restricted feeding, for which a rhythmic, but slightly delayed, binding of SREBP1 was maintained. Collectively, our results show that besides the nutrient-driven regulation of SREBP1 nuclear translocation, a second layer of modulation of SREBP1 transcriptional activity, strongly dependent from the circadian clock, exists. This system allows us to fine tune the expression timing of SREBP1 target genes, thus helping to temporally separate the different physiological processes in which these genes are involved.

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MOTIVATION: Understanding gene regulation in biological processes and modeling the robustness of underlying regulatory networks is an important problem that is currently being addressed by computational systems biologists. Lately, there has been a renewed interest in Boolean modeling techniques for gene regulatory networks (GRNs). However, due to their deterministic nature, it is often difficult to identify whether these modeling approaches are robust to the addition of stochastic noise that is widespread in gene regulatory processes. Stochasticity in Boolean models of GRNs has been addressed relatively sparingly in the past, mainly by flipping the expression of genes between different expression levels with a predefined probability. This stochasticity in nodes (SIN) model leads to over representation of noise in GRNs and hence non-correspondence with biological observations. RESULTS: In this article, we introduce the stochasticity in functions (SIF) model for simulating stochasticity in Boolean models of GRNs. By providing biological motivation behind the use of the SIF model and applying it to the T-helper and T-cell activation networks, we show that the SIF model provides more biologically robust results than the existing SIN model of stochasticity in GRNs. AVAILABILITY: Algorithms are made available under our Boolean modeling toolbox, GenYsis. The software binaries can be downloaded from http://si2.epfl.ch/ approximately garg/genysis.html.

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Metabolic problems lead to numerous failures during clinical trials, and much effort is now devoted to developing in silico models predicting metabolic stability and metabolites. Such models are well known for cytochromes P450 and some transferases, whereas less has been done to predict the activity of human hydrolases. The present study was undertaken to develop a computational approach able to predict the hydrolysis of novel esters by human carboxylesterase hCES2. The study involved first a homology modeling of the hCES2 protein based on the model of hCES1 since the two proteins share a high degree of homology (congruent with 73%). A set of 40 known substrates of hCES2 was taken from the literature; the ligands were docked in both their neutral and ionized forms using GriDock, a parallel tool based on the AutoDock4.0 engine which can perform efficient and easy virtual screening analyses of large molecular databases exploiting multi-core architectures. Useful statistical models (e.g., r (2) = 0.91 for substrates in their unprotonated state) were calculated by correlating experimental pK(m) values with distance between the carbon atom of the substrate's ester group and the hydroxy function of Ser228. Additional parameters in the equations accounted for hydrophobic and electrostatic interactions between substrates and contributing residues. The negatively charged residues in the hCES2 cavity explained the preference of the enzyme for neutral substrates and, more generally, suggested that ligands which interact too strongly by ionic bonds (e.g., ACE inhibitors) cannot be good CES2 substrates because they are trapped in the cavity in unproductive modes and behave as inhibitors. The effects of protonation on substrate recognition and the contrasting behavior of substrates and products were finally investigated by MD simulations of some CES2 complexes.

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There is great interindividual variability in HIV-1 viral setpoint after seroconversion, some of which is known to be due to genetic differences among infected individuals. Here, our focus is on determining, genome-wide, the contribution of variable gene expression to viral control, and to relate it to genomic DNA polymorphism. RNA was extracted from purified CD4+ T-cells from 137 HIV-1 seroconverters, 16 elite controllers, and 3 healthy blood donors. Expression levels of more than 48,000 mRNA transcripts were assessed by the Human-6 v3 Expression BeadChips (Illumina). Genome-wide SNP data was generated from genomic DNA using the HumanHap550 Genotyping BeadChip (Illumina). We observed two distinct profiles with 260 genes differentially expressed depending on HIV-1 viral load. There was significant upregulation of expression of interferon stimulated genes with increasing viral load, including genes of the intrinsic antiretroviral defense. Upon successful antiretroviral treatment, the transcriptome profile of previously viremic individuals reverted to a pattern comparable to that of elite controllers and of uninfected individuals. Genome-wide evaluation of cis-acting SNPs identified genetic variants modulating expression of 190 genes. Those were compared to the genes whose expression was found associated with viral load: expression of one interferon stimulated gene, OAS1, was found to be regulated by a SNP (rs3177979, p = 4.9E-12); however, we could not detect an independent association of the SNP with viral setpoint. Thus, this study represents an attempt to integrate genome-wide SNP signals with genome-wide expression profiles in the search for biological correlates of HIV-1 control. It underscores the paradox of the association between increasing levels of viral load and greater expression of antiviral defense pathways. It also shows that elite controllers do not have a fully distinctive mRNA expression pattern in CD4+ T cells. Overall, changes in global RNA expression reflect responses to viral replication rather than a mechanism that might explain viral control.

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Natural genetic variation can have a pronounced influence on human taste perception, which in turn may influence food preference and dietary choice. Genome-wide association studies represent a powerful tool to understand this influence. To help optimize the design of future genome-wide-association studies on human taste perception we have used the well-known TAS2R38-PROP association as a tool to determine the relative power and efficiency of different phenotyping and data-analysis strategies. The results show that the choice of both data collection and data processing schemes can have a very substantial impact on the power to detect genotypic variation that affects chemosensory perception. Based on these results we provide practical guidelines for the design of future GWAS studies on chemosensory phenotypes. Moreover, in addition to the TAS2R38 gene past studies have implicated a number of other genetic loci to affect taste sensitivity to PROP and the related bitter compound PTC. None of these other locations showed genome-wide significant associations in our study. To facilitate further, target-gene driven, studies on PROP taste perception we provide the genome-wide list of p-values for all SNPs genotyped in the current study.