940 resultados para Unconditional and Conditional Grants,


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This work was supported by grants from Spanish Ministry of Science andInnovation (MICINN) BIO2011-22568 & BIO2008-205.

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Cells are subjected to dramatic changes of gene expression upon environmental changes. Stresscauses a general down-regulation of gene expression together with the induction of a set of stress-responsivegenes. The p38-related stress-activated protein kinase Hog1 is an important regulator of transcription uponosmostress in yeast. Genome-wide localization studies of RNA polymerase II (RNA Pol II) and Hog1 showed that stress induced major changes in RNA Pol II localization, with a shift toward stress-responsive genes relative to housekeeping genes. RNA Pol II relocalization required Hog1, which was also localized to stress-responsive loci. In addition to RNA Pol II-bound genes, Hog1 also localized to RNA polymerase III-bound genes, pointing to a wider role for Hog1 in transcriptional control than initially expected. Interestingly, an increasing association of Hog1 with stressresponsive genes was strongly correlated with chromatin remodeling and increased gene expression. Remarkably, MNase-Seq analysis showed that although chromatin structure was not significantly altered at a genome-wide level in response to stress, there was pronounced chromatin remodeling for those genes that displayed Hog1 association. Hog1 serves to bypass the general down-regulation of gene expression that occurs in response to osmostress, and does so both by targeting RNA Pol II machinery and by inducing chromatin remodeling at stressresponsive loci.

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Many governments in developing countries implement programs that aim to address nutrionalfailures in early childhood, yet evidence on the effectiveness of these interventions is scant. Thispaper evaluates the impact of a conditional food supplementation program on child mortality inEcuador. The Programa de Alimentaci?n y Nutrici?n Nacional (PANN) 2000 was implementedby regular staff at local public health posts and consisted of offering a free micronutrient-fortifiedfood, Mi Papilla, for children aged 6 to 24 months in exchange for routine health check-ups forthe children. Our regression discontinuity design exploits the fact that at its inception, the PANN2000 was running for about 8 months only in the poorest communities (parroquias) of certainprovinces. Our main result is that the presence of the program reduced child mortality in cohortswith 8 months of differential exposure from a level of about 2.5 percent by 1 to 1.5 percentagepoints.

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AbstractBACKGROUND: Scientists have been trying to understand the molecular mechanisms of diseases to design preventive and therapeutic strategies for a long time. For some diseases, it has become evident that it is not enough to obtain a catalogue of the disease-related genes but to uncover how disruptions of molecular networks in the cell give rise to disease phenotypes. Moreover, with the unprecedented wealth of information available, even obtaining such catalogue is extremely difficult.PRINCIPAL FINDINGS: We developed a comprehensive gene-disease association database by integrating associations from several sources that cover different biomedical aspects of diseases. In particular, we focus on the current knowledge of human genetic diseases including mendelian, complex and environmental diseases. To assess the concept of modularity of human diseases, we performed a systematic study of the emergent properties of human gene-disease networks by means of network topology and functional annotation analysis. The results indicate a highly shared genetic origin of human diseases and show that for most diseases, including mendelian, complex and environmental diseases, functional modules exist. Moreover, a core set of biological pathways is found to be associated with most human diseases. We obtained similar results when studying clusters of diseases, suggesting that related diseases might arise due to dysfunction of common biological processes in the cell.CONCLUSIONS: For the first time, we include mendelian, complex and environmental diseases in an integrated gene-disease association database and show that the concept of modularity applies for all of them. We furthermore provide a functional analysis of disease-related modules providing important new biological insights, which might not be discovered when considering each of the gene-disease association repositories independently. Hence, we present a suitable framework for the study of how genetic and environmental factors, such as drugs, contribute to diseases.AVAILABILITY: The gene-disease networks used in this study and part of the analysis are available at http://ibi.imim.es/DisGeNET/DisGeNETweb.html#Download

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We introduce a width parameter that bounds the complexity of classical planning problems and domains, along with a simple but effective blind-search procedure that runs in time that is exponential in the problem width. We show that many benchmark domains have a bounded and small width provided thatgoals are restricted to single atoms, and hence that such problems are provably solvable in low polynomial time. We then focus on the practical value of these ideas over the existing benchmarks which feature conjunctive goals. We show that the blind-search procedure can be used for both serializing the goal into subgoals and for solving the resulting problems, resulting in a ‘blind’ planner that competes well with a best-first search planner guided by state-of-the-art heuristics. In addition, ideas like helpful actions and landmarks can be integrated as well, producing a planner with state-of-the-art performance.

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The mechanisms that guide progenitor cell fate and differentiation in the vertebrate central nervous system (CNS) are poorly understood. Gain-of-function experiments suggest that Notch signaling is involved in the early stages of mammalian neurogenesis. On the basis of the expression of Notch1 by putative progenitor cells of the vertebrate CNS, we have addressed directly the role of Notch1 in the development of the mammalian brain. Using conditional gene ablation, we show that loss of Notch1 results in premature onset of neurogenesis by neuroepithelial cells of the midbrain-hindbrain region of the neural tube. Notch1-deficient cells do not complete differentiation but are eliminated by apoptosis, resulting in a reduced number of neurons in the adult cerebellum. We have also analyzed the effects of Notch1 ablation on gliogenesis in vivo. Our results show that Notch1 is required for both neuron and glia formation and modulates the onset of neurogenesis within the cerebellar neuroepithelium.

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Geophysical techniques can help to bridge the inherent gap with regard to spatial resolution and the range of coverage that plagues classical hydrological methods. This has lead to the emergence of the new and rapidly growing field of hydrogeophysics. Given the differing sensitivities of various geophysical techniques to hydrologically relevant parameters and their inherent trade-off between resolution and range the fundamental usefulness of multi-method hydrogeophysical surveys for reducing uncertainties in data analysis and interpretation is widely accepted. A major challenge arising from such endeavors is the quantitative integration of the resulting vast and diverse database in order to obtain a unified model of the probed subsurface region that is internally consistent with all available data. To address this problem, we have developed a strategy towards hydrogeophysical data integration based on Monte-Carlo-type conditional stochastic simulation that we consider to be particularly suitable for local-scale studies characterized by high-resolution and high-quality datasets. Monte-Carlo-based optimization techniques are flexible and versatile, allow for accounting for a wide variety of data and constraints of differing resolution and hardness and thus have the potential of providing, in a geostatistical sense, highly detailed and realistic models of the pertinent target parameter distributions. Compared to more conventional approaches of this kind, our approach provides significant advancements in the way that the larger-scale deterministic information resolved by the hydrogeophysical data can be accounted for, which represents an inherently problematic, and as of yet unresolved, aspect of Monte-Carlo-type conditional simulation techniques. We present the results of applying our algorithm to the integration of porosity log and tomographic crosshole georadar data to generate stochastic realizations of the local-scale porosity structure. Our procedure is first tested on pertinent synthetic data and then applied to corresponding field data collected at the Boise Hydrogeophysical Research Site near Boise, Idaho, USA.

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Well-established associations between reproductive characteristics and epithelial ovarian cancer (EOC) support an involvement of sex steroid hormones in the etiology of EOC. Limited previous studies have evaluated circulating androgens and the risk of EOC, and estrogens and progesterone have been investigated in only one of the previous studies. Furthermore, there is little data on potential heterogeneity in the association between circulating hormones and EOC by histological subgroup. Therefore, we conducted a nested case-control study within the Finnish Maternity Cohort and the Northern Sweden Maternity Cohort to investigate the associations between circulating pre-diagnostic sex steroid concentrations and the histological subtypes of EOC. We identified 1052 EOC cases among cohort members diagnosed after recruitment (1975-2008) and before March 2011. Up to three controls were individually matched to each case (n=2694). Testosterone, androstenedione, 17-hydroxyprogesterone (17-OHP), progesterone, estradiol (E2), and sex hormone-binding globulin levels were measured in serum samples collected during the last pregnancy before EOC diagnosis. We used conditional logistic regression to estimate odds ratios (ORs) and 95% CIs. Associations between hormones and EOC differed with respect to tumor histology and invasiveness. Sex steroid concentrations were not associated with invasive serous tumors; however, doubling of testosterone and 17-OHP concentration was associated with approximately 40% increased risk of borderline serous tumors. A doubling of androgen concentrations was associated with a 50% increased risk of mucinous tumors. The risk of endometrioid tumors increased with higher E2 concentrations (OR: 1.89 (1.20-2.98)). This large prospective study in pregnant women supports a role of sex steroid hormones in the etiology of EOC arising in the ovaries.

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Audit report on the Community Development Block Grants program for the City of Bedford, Iowa for the year ended June 30, 2014

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Although sources in general nonlinear mixturm arc not separable iising only statistical independence, a special and realistic case of nonlinear mixtnres, the post nonlinear (PNL) mixture is separable choosing a suited separating system. Then, a natural approach is based on the estimation of tho separating Bystem parameters by minimizing an indcpendence criterion, like estimated mwce mutual information. This class of methods requires higher (than 2) order statistics, and cannot separate Gaarsian sources. However, use of [weak) prior, like source temporal correlation or nonstationarity, leads to other source separation Jgw rithms, which are able to separate Gaussian sourra, and can even, for a few of them, works with second-order statistics. Recently, modeling time correlated s011rces by Markov models, we propose vcry efficient algorithms hmed on minimization of the conditional mutual information. Currently, using the prior of temporally correlated sources, we investigate the fesihility of inverting PNL mixtures with non-bijectiw non-liacarities, like quadratic functions. In this paper, we review the main ICA and BSS results for riunlinear mixtures, present PNL models and algorithms, and finish with advanced resutts using temporally correlated snu~sm

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OBJECTIVES: To determine whether older paternal age increases the risk of fathering a pregnancy with Patau (trisomy 13), Edwards (trisomy 18), Klinefelter (XXY) or XYY syndrome. DESIGN: Case-control: cases with each of these syndromes were matched to four controls with Down syndrome from within the same congenital anomaly register and with maternal age within 6 months. SETTING: Data from 22 EUROCAT congenital anomaly registers in 12 European countries. PARTICIPANTS: Diagnoses with observed or (for terminations) predicted year of birth from 1980 to 2005, comprising live births, fetal deaths with gestational age ≥ 20 weeks and terminations after prenatal diagnosis of the anomaly. Data include 374 cases of Patau syndrome, 929 of Edwards syndrome, 295 of Klinefelter syndrome, 28 of XYY syndrome and 5627 controls with Down syndrome. MAIN OUTCOME MEASURES: Odds ratio (OR) associated with a 10-year increase in paternal age for each anomaly was estimated using conditional logistic regression. Results were adjusted to take account of the estimated association of paternal age with Down syndrome (1.11; 95% CI 1.01 to 1.23). RESULTS: The OR for Patau syndrome was 1.10 (95% CI 0.83 to 1.45); for Edwards syndrome, 1.15 (0.96 to 1.38); for Klinefelter syndrome, 1.35 (1.02 to 1.79); and for XYY syndrome, 1.99 (0.75 to 5.26). CONCLUSIONS: There was a statistically significant increase in the odds of Klinefelter syndrome with increasing paternal age. The larger positive associations of Klinefelter and XYY syndromes with paternal age compared with Patau and Edwards syndromes are consistent with the greater percentage of these sex chromosome anomalies being of paternal origin.

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Simulated-annealing-based conditional simulations provide a flexible means of quantitatively integrating diverse types of subsurface data. Although such techniques are being increasingly used in hydrocarbon reservoir characterization studies, their potential in environmental, engineering and hydrological investigations is still largely unexploited. Here, we introduce a novel simulated annealing (SA) algorithm geared towards the integration of high-resolution geophysical and hydrological data which, compared to more conventional approaches, provides significant advancements in the way that large-scale structural information in the geophysical data is accounted for. Model perturbations in the annealing procedure are made by drawing from a probability distribution for the target parameter conditioned to the geophysical data. This is the only place where geophysical information is utilized in our algorithm, which is in marked contrast to other approaches where model perturbations are made through the swapping of values in the simulation grid and agreement with soft data is enforced through a correlation coefficient constraint. Another major feature of our algorithm is the way in which available geostatistical information is utilized. Instead of constraining realizations to match a parametric target covariance model over a wide range of spatial lags, we constrain the realizations only at smaller lags where the available geophysical data cannot provide enough information. Thus we allow the larger-scale subsurface features resolved by the geophysical data to have much more due control on the output realizations. Further, since the only component of the SA objective function required in our approach is a covariance constraint at small lags, our method has improved convergence and computational efficiency over more traditional methods. Here, we present the results of applying our algorithm to the integration of porosity log and tomographic crosshole georadar data to generate stochastic realizations of the local-scale porosity structure. Our procedure is first tested on a synthetic data set, and then applied to data collected at the Boise Hydrogeophysical Research Site.

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Even though laboratory evolution experiments have demonstrated genetic variation for learning ability, we know little about the underlying genetic architecture and genetic relationships with other ecologically relevant traits. With a full diallel cross among twelve inbred lines of Drosophila melanogaster originating from a natural population (0.75 < F < 0.93), we investigated the genetic architecture of olfactory learning ability and compared it to that for another behavioral trait (unconditional preference for odors), as well as three traits quantifying the ability to deal with environmental challenges: egg-to-adult survival and developmental rate on a low-quality food, and resistance to a bacterial pathogen. Substantial additive genetic variation was detected for each trait, highlighting their potential to evolve. Genetic effects contributed more than nongenetic parental effects to variation in traits measured at the adult stage: learning, odorant perception, and resistance to infection. In contrast, the two traits quantifying larval tolerance to low-quality food were more strongly affected by parental effects. We found no evidence for genetic correlations between traits, suggesting that these traits could evolve at least to some degree independently of one another. Finally, inbreeding adversely affected all traits.

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Many loan repayment and incentive programs are available to encourage college students and graduates to enter into and continue to work in designated high-need careers. More and more Iowans are reaping the rewards of these federal, state and private programs that help reduce student loan debt while allowing them to pursue their career goals. Some programs make payments directly to the recipient’s student loan servicer to reduce the balance owed (loan repayment), while others may provide the option of an income stipend or bonus for eligible recipients who meet specified employment and other criteria. This guide provides information on many of the federal and state loan repayment and incentive programs currently available.

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We consider the problem of estimating the mean hospital cost of stays of a class of patients (e.g., a diagnosis-related group) as a function of patient characteristics. The statistical analysis is complicated by the asymmetry of the cost distribution, the possibility of censoring on the cost variable, and the occurrence of outliers. These problems have often been treated separately in the literature, and a method offering a joint solution to all of them is still missing. Indirect procedures have been proposed, combining an estimate of the duration distribution with an estimate of the conditional cost for a given duration. We propose a parametric version of this approach, allowing for asymmetry and censoring in the cost distribution and providing a mean cost estimator that is robust in the presence of extreme values. In addition, the new method takes covariate information into account.