1000 resultados para phenotipic data
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This paper proposes full-Bayes priors for time-varying parameter vector autoregressions (TVP-VARs) which are more robust and objective than existing choices proposed in the literature. We formulate the priors in a way that they allow for straightforward posterior computation, they require minimal input by the user, and they result in shrinkage posterior representations, thus, making them appropriate for models of large dimensions. A comprehensive forecasting exercise involving TVP-VARs of different dimensions establishes the usefulness of the proposed approach.
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Time-lapse crosshole ground-penetrating radar (GPR) data, collected while infiltration occurs, can provide valuable information regarding the hydraulic properties of the unsaturated zone. In particular, the stochastic inversion of such data provides estimates of parameter uncertainties, which are necessary for hydrological prediction and decision making. Here, we investigate the effect of different infiltration conditions on the stochastic inversion of time-lapse, zero-offset-profile, GPR data. Inversions are performed using a Bayesian Markov-chain-Monte-Carlo methodology. Our results clearly indicate that considering data collected during a forced infiltration test helps to better refine soil hydraulic properties compared to data collected under natural infiltration conditions
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This paper develops a methodology to estimate the entire population distributions from bin-aggregated sample data. We do this through the estimation of the parameters of mixtures of distributions that allow for maximal parametric flexibility. The statistical approach we develop enables comparisons of the full distributions of height data from potential army conscripts across France's 88 departments for most of the nineteenth century. These comparisons are made by testing for differences-of-means stochastic dominance. Corrections for possible measurement errors are also devised by taking advantage of the richness of the data sets. Our methodology is of interest to researchers working on historical as well as contemporary bin-aggregated or histogram-type data, something that is still widely done since much of the information that is publicly available is in that form, often due to restrictions due to political sensitivity and/or confidentiality concerns.
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BACKGROUND: Certolizumab pegol (Cimzia, CZP) was approved for the treatment of Crohn's disease (CD) patients in 2007 in Switzerland as the first country worldwide. This prospective phase IV study aimed to evaluate the efficacy and safety of CZP over 26 weeks in a multicenter cohort of practice-based patients. METHODS: Evaluation questionnaires at baseline, week 6, and week 26 were completed by gastroenterologists in hospitals and private practices. Adverse events were evaluated according to World Health Organization (WHO) guidelines. RESULTS: Sixty patients (38F/22M) were included; 53% had complicated disease (stricturing or penetrating), 45% had undergone prior CD-related surgery. All patients had prior exposure to systemic steroids, 96% to immunomodulators, 73% to infliximab, and 43% to adalimumab. A significant decrease of the Harvey-Bradshaw Index (HBI) was observed under CZP therapy (12.2 ± 4.9 at week 0 versus 6.3 ± 4.7 at week 6 and 6.7 ± 5.3 at week 26, both P < 0.001). Response and remission rates were 70% and 40% (week 6) and 67% and 36%, respectively (week 26). The complete perianal fistula closure rate was 36% at week 6 and 55% at week 26. The frequency of adverse drug reactions attributed to CZP was 5%. CZP was continued in 88% of patients beyond week 6 and in 67% beyond week 26. CONCLUSIONS: In a population of CD patients with predominantly complicated disease behavior, CZP proved to be effective in induction and maintenance of response and remission. This series provides the first evidence of CZP's effectiveness in perianal fistulizing CD in clinical practice.
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The use of Geographic Information Systems has revolutionalized the handling and the visualization of geo-referenced data and has underlined the critic role of spatial analysis. The usual tools for such a purpose are geostatistics which are widely used in Earth science. Geostatistics are based upon several hypothesis which are not always verified in practice. On the other hand, Artificial Neural Network (ANN) a priori can be used without special assumptions and are known to be flexible. This paper proposes to discuss the application of ANN in the case of the interpolation of a geo-referenced variable.
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The effects of azadirachtin A, a tetranortriterpenoid from the neem tree Azadirachta indica J., on both development and interaction between Trypanosoma cruzi, the causative agent of Chagas' disease, and its vector Rhodnius prolixus were studied. Given through a blood meal, a dose-rsponse relationship of azadirachtin was established using antifeedant effect and ecdysis inhibition as effective parameters. A singlo dose of azadirachtin A was able to block the onset of mitosis in the epidermis and ecdysteroid titers in the hemnolymph, determined by radioimmuneassay, were too low for an induction of ecadysis. The survival of T. cruzi was also studied in R. prolixus treated with the drug. If the trypomastigotes were fed in presence of azadirachtin A the number of parasites drastically decreased. If the drug was applied after infection of the bug with T. cruzi, the parasite was still abolished from the gut. If the insect was pretreated with azadirachtin A before infection the same observation was obtained. A single dose of azadirachtin A was enough for a permanent resistance of the insect host against its reinfection with T. cruzi and for blocking the ecdysis for a long time. The effects of azadirachtin A on the hormonal balance of the host and growth inhibition of the parasite will be discussed on the basis of the present results.
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Proallatotoxins, and particularly preconcenes, are exceptionally promising models for studying Rhodnius prolixus physiology and for comparison with other natural compounds with anti-hormonal activities. Effects of preconcenes on feeding, development and reproduction of R. prolixus are being detailed. The precocenes reveal significant effects on feeding, moulting cycle (inducing precocious metamorphosis and ecdysial stasis), and reproduction of these insect. The mechanism of action of proallatotoxins was discussed based on the corpus allatum cytotoxic effect and on the ecdysteroid biosynthesis in prothoracic glands and ovaries. Further studies of these compounds on R. prolixus are need and will hopefully reveal other unesplored points regarding the action of the proallatotoxins on insects.
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BACKGROUND AND AIMS: In critically ill patients, fractional hepatic de novo lipogenesis increases in proportion to carbohydrate administration during isoenergetic nutrition. In this study, we sought to determine whether this increase may be the consequence of continuous enteral nutrition and bed rest. We, therefore, measured fractional hepatic de novo lipogenesis in a group of 12 healthy subjects during near-continuous oral feeding (hourly isoenergetic meals with a liquid formula containing 55% carbohydrate). In eight subjects, near-continuous enteral nutrition and bed rest were applied over a 10 h period. In the other four subjects, it was extended to 34 h. Fractional hepatic de novo lipogenesis was measured by infusing(13) C-labeled acetate and monitoring VLDL-(13)C palmitate enrichment with mass isotopomer distribution analysis. Fractional hepatic de novo lipogenesis was 3.2% (range 1.5-7.5%) in the eight subjects after 10 h of near continuous nutrition and 1.6% (range 1.3-2.0%) in the four subjects after 34 h of near-continuous nutrition and bed rest. This indicates that continuous nutrition and physical inactivity do not increase hepatic de novo lipogenesis. Fractional hepatic de novo lipogenesis previously reported in critically ill patients under similar nutritional conditions (9.3%) (range 5.3-15.8%) was markedly higher than in healthy subjects (P<0.001). These data from healthy subjects indicate that fractional hepatic de novo lipogenesis is increased in critically ill patients.
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Texte intégral: http://www.springerlink.com/content/3q68180337551r47/fulltext.pdf
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The comparison of consecutively manufactured tools and firearms has provided much, but not all, of the basis for the profession of firearm and toolmark examination. The authors accept the fundamental soundness of this approach but appeal to the experimental community to close two minor gaps in the experimental procedure. We suggest that "blinding" and attention to appropriateness of other experimental conditions that would consolidate the foundations of our profession. We do not suggest that previous work is unsound.
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In this paper we analyze the persistence of aggregate real exchange rates (RERs) for a group of EU-15 countries by using sectoral data. The tight relation between aggregate and sectoral persistence recently investigated by Mayoral (2008) allows us to decompose aggregate RER persistence into the persistence of its different subcomponents. We show that the distribution of sectoral persistence is highly heterogeneous and very skewed to the right, and that a limited number of sectors are responsible for the high levels of persistence observed at the aggregate level. We use quantile regression to investigate whether the traditional theories proposed to account for the slow reversion to parity (lack of arbitrage due to nontradibilities or imperfect competition and price stickiness) are able to explain the behavior of the upper quantiles of sectoral persistence. We conclude that pricing to market in the intermediate goods sector together with price stickiness have more explanatory power than variables related to the tradability of the goods or their inputs.
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Consider a model with parameter phi, and an auxiliary model with parameter theta. Let phi be a randomly sampled from a given density over the known parameter space. Monte Carlo methods can be used to draw simulated data and compute the corresponding estimate of theta, say theta_tilde. A large set of tuples (phi, theta_tilde) can be generated in this manner. Nonparametric methods may be use to fit the function E(phi|theta_tilde=a), using these tuples. It is proposed to estimate phi using the fitted E(phi|theta_tilde=theta_hat), where theta_hat is the auxiliary estimate, using the real sample data. This is a consistent and asymptotically normally distributed estimator, under certain assumptions. Monte Carlo results for dynamic panel data and vector autoregressions show that this estimator can have very attractive small sample properties. Confidence intervals can be constructed using the quantiles of the phi for which theta_tilde is close to theta_hat. Such confidence intervals are found to have very accurate coverage.
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Excessive exposure to solar ultraviolet (UV) is the main cause of skin cancer. Specific prevention should be further developed to target overexposed or highly vulnerable populations. A better characterisation of anatomical UV exposure patterns is however needed for specific prevention. To develop a regression model for predicting the UV exposure ratio (ER, ratio between the anatomical dose and the corresponding ground level dose) for each body site without requiring individual measurements. A 3D numeric model (SimUVEx) was used to compute ER for various body sites and postures. A multiple fractional polynomial regression analysis was performed to identify predictors of ER. The regression model used simulation data and its performance was tested on an independent data set. Two input variables were sufficient to explain ER: the cosine of the maximal daily solar zenith angle and the fraction of the sky visible from the body site. The regression model was in good agreement with the simulated data ER (R(2)=0.988). Relative errors up to +20% and -10% were found in daily doses predictions, whereas an average relative error of only 2.4% (-0.03% to 5.4%) was found in yearly dose predictions. The regression model predicts accurately ER and UV doses on the basis of readily available data such as global UV erythemal irradiance measured at ground surface stations or inferred from satellite information. It renders the development of exposure data on a wide temporal and geographical scale possible and opens broad perspectives for epidemiological studies and skin cancer prevention.