993 resultados para SUBSET
Resumo:
Before the advent of genome-wide association studies (GWASs), hundreds of candidate genes for obesity-susceptibility had been identified through a variety of approaches. We examined whether those obesity candidate genes are enriched for associations with body mass index (BMI) compared with non-candidate genes by using data from a large-scale GWAS. A thorough literature search identified 547 candidate genes for obesity-susceptibility based on evidence from animal studies, Mendelian syndromes, linkage studies, genetic association studies and expression studies. Genomic regions were defined to include the genes ±10 kb of flanking sequence around candidate and non-candidate genes. We used summary statistics publicly available from the discovery stage of the genome-wide meta-analysis for BMI performed by the genetic investigation of anthropometric traits consortium in 123 564 individuals. Hypergeometric, rank tail-strength and gene-set enrichment analysis tests were used to test for the enrichment of association in candidate compared with non-candidate genes. The hypergeometric test of enrichment was not significant at the 5% P-value quantile (P = 0.35), but was nominally significant at the 25% quantile (P = 0.015). The rank tail-strength and gene-set enrichment tests were nominally significant for the full set of genes and borderline significant for the subset without SNPs at P < 10(-7). Taken together, the observed evidence for enrichment suggests that the candidate gene approach retains some value. However, the degree of enrichment is small despite the extensive number of candidate genes and the large sample size. Studies that focus on candidate genes have only slightly increased chances of detecting associations, and are likely to miss many true effects in non-candidate genes, at least for obesity-related traits.
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A stand-alone sea ice model is tuned and validated using satellite-derived, basinwide observations of sea ice thickness, extent, and velocity from the years 1993 to 2001. This is the first time that basin-scale measurements of sea ice thickness have been used for this purpose. The model is based on the CICE sea ice model code developed at the Los Alamos National Laboratory, with some minor modifications, and forcing consists of 40-yr ECMWF Re-Analysis (ERA-40) and Polar Exchange at the Sea Surface (POLES) data. Three parameters are varied in the tuning process: Ca, the air–ice drag coefficient; P*, the ice strength parameter; and α, the broadband albedo of cold bare ice, with the aim being to determine the subset of this three-dimensional parameter space that gives the best simultaneous agreement with observations with this forcing set. It is found that observations of sea ice extent and velocity alone are not sufficient to unambiguously tune the model, and that sea ice thickness measurements are necessary to locate a unique subset of parameter space in which simultaneous agreement is achieved with all three observational datasets.
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Some climatological information from 14 atmospheric general circulation models is presented and compared in order to assess the ability of a broad group of models to simulate current climate. The quantities considered are cross sections of temperature, zonal wind, and meridional stream function together with latitudinal distributions of mean sea level pressure and precipitation rate. The nature of the deficiencies in the simulated climates that are common to all models and those which differ among models is investigated; the general improvement in the ability of models to simulate certain aspects of the climate is shown; consideration is given to the effect of increasing resolution on simulated climate; and approaches to understanding and reducing model deficiencies are discussed. The information presented here is a subset of a more voluminous compilation which is available in report form (Boer et al., 1991). This report contains essentially the same text, but results from all 14 models are presented together with additional results in the form of geographical distributions of surface variables and certain difference statistics.
Resumo:
The potential impact of climate change on areas of strategic importance for water resources remains a concern. Here, river flow projections for the River Medway, above Teston in southeast England are presented, which is just such an area of strategic importance. The river flow projections use climate inputs from the Hadley Centre Regional Climate Model (HadRM3) for the time period 1960–2080 (a subset of the early release UKCP09 projections). River flow predictions are calculated using CATCHMOD, the main river flow prediction tool of the Environment Agency (EA) of England and Wales. In order to use this tool in the best way for climate change predictions, model setup and performance are analysed using sensitivity and uncertainty analysis. The model's representation of hydrological processes is discussed and the direct percolation and first linear storage constant parameters are found to strongly affect model results in a complex way, with the former more important for low flows and the latter for high flows. The uncertainty in predictions resulting from the hydrological model parameters is demonstrated and the projections of river flow under future climate are analysed. A clear climate change impact signal is evident in the results with a persistent lowering of mean daily river flows for all months and for all projection time slices. Results indicate that a projection of lower flows under future climate is valid even taking into account the uncertainties considered in this modelling chain exercise. The model parameter uncertainty becomes more significant under future climate as the river flows become lower. This has significant implications for those making policy decisions based on such modelling results. Copyright © 2010 John Wiley & Sons, Ltd.
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Proteolytic enzymes comprise approximately 2 percent of the human genome [1]. Given their abundance, it is not surprising that proteases have diverse biological functions, ranging from the degradation of proteins in lysosomes to the control of physiological processes such as the coagulation cascade. However, a subset of serine proteases (possessing serine residues within their catalytic sites), which may be soluble in the extracellular fluid or tethered to the plasma membrane, are signaling molecules that can specifically regulate cells by cleaving protease-activated receptors (PARs), a family of four G-protein-coupled receptors (GPCRs). These serine proteases include members of the coagulation cascade (e.g., thrombin, factor VIIa, and factor Xa), proteases from inflammatory cells (e.g., mast cell tryptase, neutrophil cathepsin G), and proteases from epithelial tissues and neurons (e.g., trypsins). They are often generated or released during injury and inflammation, and they cleave PARs on multiple cell types, including platelets, endothelial and epithelial cells, myocytes, fibroblasts, and cells of the nervous system. Activated PARs regulate many essential physiological processes, such as hemostasis, inflammation, pain, and healing. These proteases and their receptors have been implicated in human disease and are potentially important targets for therapy. Proteases and PARs participate in regulating most organ systems and are the subject of several comprehensive reviews [2, 3]. Within the central and peripheral nervous systems, proteases and PARs can control neuronal and astrocyte survival, proliferation and morphology, release of neurotransmitters, and the function and activity of ion channels, topics that have also been comprehensively reviewed [4, 5]. This chapter specifically concerns the ability of PARs to regulate TRPV channels of sensory neurons and thereby affect neurogenic inflammation and pain transmission [6, 7].
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In this article, we investigate how the choice of the attenuation factor in an extended version of Katz centrality influences the centrality of the nodes in evolving communication networks. For given snapshots of a network, observed over a period of time, recently developed communicability indices aim to identify the best broadcasters and listeners (receivers) in the network. Here we explore the attenuation factor constraint, in relation to the spectral radius (the largest eigenvalue) of the network at any point in time and its computation in the case of large networks. We compare three different communicability measures: standard, exponential, and relaxed (where the spectral radius bound on the attenuation factor is relaxed and the adjacency matrix is normalised, in order to maintain the convergence of the measure). Furthermore, using a vitality-based measure of both standard and relaxed communicability indices, we look at the ways of establishing the most important individuals for broadcasting and receiving of messages related to community bridging roles. We compare those measures with the scores produced by an iterative version of the PageRank algorithm and illustrate our findings with two examples of real-life evolving networks: the MIT reality mining data set, consisting of daily communications between 106 individuals over the period of one year, a UK Twitter mentions network, constructed from the direct \emph{tweets} between 12.4k individuals during one week, and a subset the Enron email data set.
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Apolipoprotein E (APOE) genotype is believed to play an important role in cardiovascular risk. APOE4 carriers have been associated with higher blood lipid levels and a more pro-inflammatory state compared with APOE3/E3 individuals. Although dietary fat composition has been considered to modulate the inflammatory state in humans, very little is known about how APOE genotype can impact on this response. In a follow-up to the main SATgene study, we aimed to explore the effects of APOE genotype, as well as, dietary fat manipulation on ex vivo cytokine production. Blood samples were collected from a subset of SATgene participants (n = 52/88), prospectively recruited according to APOE genotype (n = 26 E3/E3 and n = 26 E3/E4) after low-fat (LF), high saturated fat (HSF) and HSF with 3.45 g docosahexaenoic acid (DHA) dietary periods (each diet eight weeks in duration assigned in the same order) for the measurement of ex vivo cytokine production using whole blood culture (WBC). Concentrations of IL-1beta, IL-6, IL-8, IL-10 and TNF-alpha were measured in WBC supernatant samples after stimulation for 24 h with either 0.05 or 1 lg/ml of bacterial lipopolysaccharide (LPS). Cytokine levels were not influenced by genotype, whereas, dietary fat manipulation had a significant impact on TNF-a and IL-10 production; TNF-a concentration was higher after consumption of the HSF diet compared with baseline and the LF diet (P < 0.05), whereas, IL-10 concentration was higher after the LF diet compared with baseline (P < 0.05). In conclusion, our study has revealed the amount and type of dietary fat can significantly modulate the production of TNF-a and IL-10 by ex vivo LPS-stimulated WBC samples obtained from normolipidaemic subjects.
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Doctor-patient jokes are universally popular because of the information asymmetries within the diagnostic relationship. We contend that entrepreneurial diagnosis is present in markets where consumers are unable to diagnose their own problems and, instead, may rely on the entrepreneur to diagnose them. Entrepreneurial diagnosis is a cognitive skill possessed by the entrepreneur. It is an identifiable subset of entrepreneurial judgment and can be modeled – which we attempt to do. In order to overcome the information asymmetries and exploit opportunities, we suggest that entrepreneurs must invest in market making innovations (as distinct from product innovations) such as trustworthy reputations. The diagnostic entrepreneur described in this paper represents a creative response to difficult diagnostic problems and helps to explain the success of many firms whose products are not particularly innovative but which are perceived as offering high standards of service. These firms are trusted not only for their truthfulness about the quality of their product, but for their honesty, confidentiality and understanding in helping customers identify the most appropriate product to their needs.
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Retrieving a subset of items can cause the forgetting of other items, a phenomenon referred to as retrieval-induced forgetting. According to some theorists, retrieval-induced forgetting is the consequence of an inhibitory mechanism that acts to reduce the accessibility of non-target items that interfere with the retrieval of target items. Other theorists argue that inhibition is unnecessary to account for retrieval-induced forgetting, contending instead that the phenomenon can be best explained by non-inhibitory mechanisms, such as strength-based competition or blocking. The current paper provides the first major meta-analysis of retrieval-induced forgetting, conducted with the primary purpose of quantitatively evaluating the multitude of findings that have been used to contrast these two theoretical viewpoints. The results largely supported inhibition accounts, but also provided some challenging evidence, with the nature of the results often varying as a function of how retrieval-induced forgetting was assessed. Implications for further research and theory development are discussed.
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Recent studies showed that features extracted from brain MRIs can well discriminate Alzheimer’s disease from Mild Cognitive Impairment. This study provides an algorithm that sequentially applies advanced feature selection methods for findings the best subset of features in terms of binary classification accuracy. The classifiers that provided the highest accuracies, have been then used for solving a multi-class problem by the one-versus-one strategy. Although several approaches based on Regions of Interest (ROIs) extraction exist, the prediction power of features has not yet investigated by comparing filter and wrapper techniques. The findings of this work suggest that (i) the IntraCranial Volume (ICV) normalization can lead to overfitting and worst the accuracy prediction of test set and (ii) the combined use of a Random Forest-based filter with a Support Vector Machines-based wrapper, improves accuracy of binary classification.
Resumo:
Comparison of single-forcing varieties of 20th century historical experiments in a subset of models from the Fifth Coupled Model Intercomparison Project (CMIP5) reveals that South Asian summer monsoon rainfall increases towards the present day in Greenhouse Gas (GHG)-only experiments with respect to pre-industrial levels, while it decreases in anthropogenic aerosol-only experiments. Comparison of these single-forcing experiments with the all-forcings historical experiment suggests aerosol emissions have dominated South Asian monsoon rainfall trends in recent decades, especially during the 1950s to 1970s. The variations in South Asian monsoon rainfall in these experiments follows approximately the time evolution of inter-hemispheric temperature gradient over the same period, suggesting a contribution from the large-scale background state relating to the asymmetric distribution of aerosol emissions about the equator. By examining the 24 available all-forcings historical experiments, we show that models including aerosol indirect effects dominate the negative rainfall trend. Indeed, models including only the direct radiative effect of aerosol show an increase in monsoon rainfall, consistent with the dominance of increasing greenhouse gas emissions and planetary warming on monsoon rainfall in those models. For South Asia, reduced rainfall in the models with indirect effects is related to decreased evaporation at the land surface rather than from anomalies in horizontal moisture flux, suggesting the impact of indirect effects on local aerosol emissions. This is confirmed by examination of aerosol loading and cloud droplet number trends over the South Asia region. Thus, while remote aerosols and their asymmetric distribution about the equator play a role in setting the inter-hemispheric temperature distribution on which the South Asian monsoon, as one of the global monsoons, operates, the addition of indirect aerosol effects acting on very local aerosol emissions also plays a role in declining monsoon rainfall. The disparity between the response of monsoon rainfall to increasing aerosol emissions in models containing direct aerosol effects only and those also containing indirect effects needs to be urgently investigated since the suggested future decline in Asian anthropogenic aerosol emissions inherent to the representative concentration pathways (RCPs) used for future climate projection may turn out to be optimistic. In addition, both groups of models show declining rainfall over China, also relating to local aerosol mechanisms. We hypothesize that aerosol emissions over China are large enough, in the CMIP5 models, to cause declining monsoon rainfall even in the absence of indirect aerosol effects. The same is not true for India.
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We consider a generic basic semi-algebraic subset S of the space of generalized functions, that is a set given by (not necessarily countably many) polynomial constraints. We derive necessary and sufficient conditions for an infinite sequence of generalized functions to be realizable on S, namely to be the moment sequence of a finite measure concentrated on S. Our approach combines the classical results about the moment problem on nuclear spaces with the techniques recently developed to treat the moment problem on basic semi-algebraic sets of Rd. In this way, we determine realizability conditions that can be more easily verified than the well-known Haviland type conditions. Our result completely characterizes the support of the realizing measure in terms of its moments. As concrete examples of semi-algebraic sets of generalized functions, we consider the set of all Radon measures and the set of all the measures having bounded Radon–Nikodym density w.r.t. the Lebesgue measure.
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A realistic representation of the North Atlantic tropical cyclone tracks is crucial as it allows, for example, explaining potential changes in US landfalling systems. Here we present a tentative study, which examines the ability of recent climate models to represent North Atlantic tropical cyclone tracks. Tracks from two types of climate models are evaluated: explicit tracks are obtained from tropical cyclones simulated in regional or global climate models with moderate to high horizontal resolution (1° to 0.25°), and downscaled tracks are obtained using a downscaling technique with large-scale environmental fields from a subset of these models. For both configurations, tracks are objectively separated into four groups using a cluster technique, leading to a zonal and a meridional separation of the tracks. The meridional separation largely captures the separation between deep tropical and sub-tropical, hybrid or baroclinic cyclones, while the zonal separation segregates Gulf of Mexico and Cape Verde storms. The properties of the tracks’ seasonality, intensity and power dissipation index in each cluster are documented for both configurations. Our results show that except for the seasonality, the downscaled tracks better capture the observed characteristics of the clusters. We also use three different idealized scenarios to examine the possible future changes of tropical cyclone tracks under 1) warming sea surface temperature, 2) increasing carbon dioxide, and 3) a combination of the two. The response to each scenario is highly variable depending on the simulation considered. Finally, we examine the role of each cluster in these future changes and find no preponderant contribution of any single cluster over the others.
Resumo:
Superposed epoch studies have been carried out in order to determine the ionospheric response at mid-latitudes to southward turnings of the interplanetary magnetic field (IMF). This is compared with the geomagnetic response, as seen in the indices K p, AE and Dst. The solar wind, IMF and geomagnetic data used were hourly averages from the years 1967–1989 and thus cover a full 22-year cycle in the solar magnetic field. These data were divided into subsets, determined by the magnitudes of the southward turnings and the concomitant increase in solar wind pressure. The superposed epoch studies were carried out using the time of the southward turning as time zero. The response of the mid-latitude ionosphere is studied by looking at the F-layer critical frequencies, f o F2, from hourly soundings by the Slough ionosonde and their deviation from the monthly median values, δf o F2. For the southward turnings with a change in B z of δB z > 11.5 nT accompanied by a solar wind dynamic pressure P exceeding 5 nPa, the F region critical frequency, f o F2, shows a marked decrease, reaching a minimum value about 20 h after the southward turning. This recovers to pre-event values over the subsequent 24 h, on average. The Dst index shows the classic storm-time decrease to about −60 nT. Four days later, the index has still to fully recover and is at about −25 nT. Both the K p and AE indices show rises before the southward turnings, when the IMF is strongly northward but the solar wind dynamic pressure is enhanced. The average AE index does register a clear isolated pulse (averaging 650 nT for 2 h, compared with a background peak level of near 450 nT at these times) showing enhanced energy deposition at high latitudes in substorms but, like K p, remains somewhat enhanced for several days, even after the average IMF has returned to zero after 1 day. This AE background decays away over several days as the Dst index recovers, indicating that there is some contamination of the currents observed at the AE stations by the continuing enhanced equatorial ring current. For data averaged over all seasons, the critical frequencies are depressed at Slough by 1.3 MHz, which is close to the lower decile of the overall distribution of δf o Fl values. Taking 30-day periods around summer and winter solstice, the largest depression is 1.6 and 1.2 MHz, respectively. This seasonal dependence is confirmed by a similar study for a Southern Hemisphere station, Argentine Island, giving peak depressions of 1.8 MHz and 0.5 MHz for summer and winter. For the subset of turnings where δB z > 11.5 nT and P ≤ 5 nPa, the response of the geomagnetic indices is similar but smaller, while the change in δf o F2 has all but disappeared. This confirms that the energy deposited at high latitudes, which leads to the geomagnetic and ionospheric disturbances following a southward turning of the IMF, increases with the energy density (dynamic pressure) of the solar wind flow. The magnitude of all responses are shown to depend on δB z . At Slough, the peak depression always occurs when Slough rotates into the noon sector. The largest ionospheric response is for southward turnings seen between 15–21 UT.
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Resistance of bacteria to phages may be gained by alteration of surface proteins to which phages bind, a mechanism that is likely to be costly as these molecules typically have critical functions such as movement or nutrient uptake. To address this potential trade-off, we combine a systematic study of natural bacteria and phage populations with an experimental evolution approach. We compare motility, growth rate and susceptibility to local phages for 80 bacteria isolated from horse chestnut leaves and, contrary to expectation, find no negative association between resistance to phages and bacterial motility or growth rate. However, because correlational patterns (and their absence) are open to numerous interpretations, we test for any causal association between resistance to phages and bacterial motility using experimental evolution of a subset of bacteria in both the presence and absence of naturally associated phages. Again, we find no clear link between the acquisition of resistance and bacterial motility, suggesting that for these natural bacterial populations, phage-mediated selection is unlikely to shape bacterial motility, a key fitness trait for many bacteria in the phyllosphere. The agreement between the observed natural pattern and the experimental evolution results presented here demonstrates the power of this combined approach for testing evolutionary trade-offs.