972 resultados para pseudo-random number generator


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Nanoparticles <100 nanometres are being introduced into industrial processes, but they are suspected to cause similar negative health effects to ambient particles. Poor knowledge about the scale of introduction has not allowed global risk analysis until now. In 2006 a targeted telephone survey among Swiss companies (1) showed the usage of nanoparticles in a few selected companies but did not provide data to extrapolate to the full Swiss workforce. The purpose of the study presented here was to provide a quantitative estimate of the potential occupational exposure to nanoparticles in Swiss industry. Method: A layered representative questionnaire survey among 1626 Swiss companies of the production sector was conducted in 2007. The survey was a written questionnaire, collecting data about the used nanoparticles, the number of potentially exposed persons in the companies and their protection strategy. Results: The response rate of the study was 58.3%. The number of companies estimated to be using nanoparticles in Switzerland was 586 (95% Confidence Interval 145 to 1027). It is estimated that 1309 workers (95% CI 1073 to 1545) do their job in the same room as a nanoparticle application. Personal protection was shown to be the predominant protection means. Such information is valuable for risk evaluation. The low number of companies dealing with nanoparticles in Switzerland suggests that policy makers as well as health, safety and environmental officers within companies can focus their efforts on a relatively small number of companies or workers. The collected data about types of particles and applications may be used for research on prevention strategies and adapted protection means. However, to reflect the most recent trends, the information presented here has to be continuously updated, and a large-scale inventory of the usage should be considered.

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Urease is an important virulence factor for Helicobacter pylori and is critical for bacterial colonization of the human gastric mucosa. Specific inhibition of urease activity has been proposed as a possible strategy to fight this bacteria which infects billions of individual throughout the world and can lead to severe pathological conditions in a limited number of cases. We have selected peptides which specifically bind and inhibit H. pylori urease from libraries of random peptides displayed on filamentous phage in the context of pIII coat protein. Screening of a highly diverse 25-mer combinatorial library and two newly constructed random 6-mer peptide libraries on solid phase H. pylori urease holoenzyme allowed the identification of two peptides, 24-mer TFLPQPRCSALLRYLSEDGVIVPS and 6-mer YDFYWW that can bind and inhibit the activity of urease purified from H. pylori. These two peptides were chemically synthesized and their inhibition constants (Ki) were found to be 47 microM for the 24-mer and 30 microM for the 6-mer peptide. Both peptides specifically inhibited the activity of H. pylori urease but not that of Bacillus pasteurii.

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We present models predicting the potential distribution of a threatened ant species, Formica exsecta Nyl., in the Swiss National Park ( SNP). Data to fit the models have been collected according to a random-stratified design with an equal number of replicates per stratum. The basic aim of such a sampling strategy is to allow the formal testing of biological hypotheses about those factors most likely to account for the distribution of the modeled species. The stratifying factors used in this study were: vegetation, slope angle and slope aspect, the latter two being used as surrogates of solar radiation, considered one of the basic requirements of F. exsecta. Results show that, although the basic stratifying predictors account for more than 50% of the deviance, the incorporation of additional non-spatially explicit predictors into the model, as measured in the field, allows for an increased model performance (up to nearly 75%). However, this was not corroborated by permutation tests. Implementation on a national scale was made for one model only, due to the difficulty of obtaining similar predictors on this scale. The resulting map on the national scale suggests that the species might once have had a broader distribution in Switzerland. Reasons for its particular abundance within the SNP might possibly be related to habitat fragmentation and vegetation transformation outside the SNP boundaries.

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Background: Prognostic and predictive markers are of great importance for future study designs and essential for the interpretation of clinical trials incorporating an EGFR-inhibitor. The current study prospectively assessed and validated KRAS, BRAF and PIK3CA mutations in rectal cancer patients screened for the trial SAKK41/07 of concomitant preoperative radio-chemotherapy with or without panitumumab.Methods: Macrodissection was performed on pretreatment formalin fixed paraffin embedded biopsy tissue sections to arrive at a minimum of 50% of tumor cells. DNA was extracted with the Maxwell 16 FFPE Tissue LEV DNA purification kit. After PCR amplification, mutations were identified by pyrosequencing. We prospectively analysed pretreatment biopsy material from 149 rectal cancer pts biopsies for KRAS (exon 2 codon 12 [2-12] and 13 [2-13], exon 3 codon 59 [3-59]) and 61 [3-61], exon 4 codon 117 [4-117] and 146 [4-146]). Sixty-eight pts (KRASwt exon 2, 3 only) were further analysed for BRAF (exon 15 codon 600) and PIK3CA (exon 9 codon 542, 545 and 546, exon 20 codon 1043 [20-1043] and 1047 [20-1047]) mutations, and EGFR copy number by qPCR. For the calculation of the EGFR copy number, we used KRAS copy number as internal reference standard. The calculation was done on the basis of the two standard curves relative quantification method.Results: In 149 screened pts with rectal cancer, the prevalence of KRAS mutations was 36%. Among the 68 pts enrolled in SAKK 41/07 based on initially presumed KRASwt status (exon 2/codons 12+13), 18 pts (26%) had a total of 23 mutations in the RAS/PIK3CA-pathways upon validation analysis. Twelve pts had a KRAS mutation, 7 pts had a PIK3CA mutation, 3 pts had a NRAS mutation, 1 patient a BRAF mutation. Surprisingly, five of these pts had double- mutations, including 4 pts with KRAS plus PIK3CA mutations, and 1 pt with NRAS plus PIK3CA mutations. The median normalized EGFR copy number was 1. Neither mutations of KRAS, BRAF, and PIK3CA, nor EGFR copy number were statistically associated with the primary study endpoint pCR (pathological complete regression).Conclusions: The prevalence of KRAS mutations in rectal and in colon cancer appears to be similar. BRAF mutations are rare; PIK3CA mutations are more common (10%). EGFR copy number is not increased in rectal cancer. A considerable number or KRAS exon 2 wt tumors harbored KRAS exon 3+4 mutations. Further study is needed to determine if KRAS testing should include exons 2-4.

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Size and copy number of organelles are influenced by an equilibrium of membrane fusion and fission. We studied this equilibrium on vacuoles-the lysosomes of yeast. Vacuole fusion can readily be reconstituted and quantified in vitro, but it had not been possible to study fission of the organelle in a similar way. Here we present a cell-free system that reconstitutes fragmentation of purified yeast vacuoles (lysosomes) into smaller vesicles. Fragmentation in vitro reproduces physiological aspects. It requires the dynamin-like GTPase Vps1p, V-ATPase pump activity, cytosolic proteins, and ATP and GTP hydrolysis. We used the in vitro system to show that the vacuole-associated TOR complex 1 (TORC1) stimulates vacuole fragmentation but not the opposing reaction of vacuole fusion. Under nutrient restriction, TORC1 is inactivated, and the continuing fusion activity then dominates the fusion/fission equilibrium, decreasing the copy number and increasing the volume of the vacuolar compartment. This result can explain why nutrient restriction not only induces autophagy and a massive buildup of vacuolar/lysosomal hydrolases, but also leads to a concomitant increase in volume of the vacuolar compartment by coalescence of the organelles into a single large compartment.

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Cancer genomes frequently contain somatic copy number alterations (SCNA) that can significantly perturb the expression level of affected genes and thus disrupt pathways controlling normal growth. In melanoma, many studies have focussed on the copy number and gene expression levels of the BRAF, PTEN and MITF genes, but little has been done to identify new genes using these parameters at the genome-wide scale. Using karyotyping, SNP and CGH arrays, and RNA-seq, we have identified SCNA affecting gene expression ('SCNA-genes') in seven human metastatic melanoma cell lines. We showed that the combination of these techniques is useful to identify candidate genes potentially involved in tumorigenesis. Since few of these alterations were recurrent across our samples, we used a protein network-guided approach to determine whether any pathways were enriched in SCNA-genes in one or more samples. From this unbiased genome-wide analysis, we identified 28 significantly enriched pathway modules. Comparison with two large, independent melanoma SCNA datasets showed less than 10% overlap at the individual gene level, but network-guided analysis revealed 66% shared pathways, including all but three of the pathways identified in our data. Frequently altered pathways included WNT, cadherin signalling, angiogenesis and melanogenesis. Additionally, our results emphasize the potential of the EPHA3 and FRS2 gene products, involved in angiogenesis and migration, as possible therapeutic targets in melanoma. Our study demonstrates the utility of network-guided approaches, for both large and small datasets, to identify pathways recurrently perturbed in cancer.

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Background: With increasing computer power, simulating the dynamics of complex systems in chemistry and biology is becoming increasingly routine. The modelling of individual reactions in (bio)chemical systems involves a large number of random events that can be simulated by the stochastic simulation algorithm (SSA). The key quantity is the step size, or waiting time, τ, whose value inversely depends on the size of the propensities of the different channel reactions and which needs to be re-evaluated after every firing event. Such a discrete event simulation may be extremely expensive, in particular for stiff systems where τ can be very short due to the fast kinetics of some of the channel reactions. Several alternative methods have been put forward to increase the integration step size. The so-called τ-leap approach takes a larger step size by allowing all the reactions to fire, from a Poisson or Binomial distribution, within that step. Although the expected value for the different species in the reactive system is maintained with respect to more precise methods, the variance at steady state can suffer from large errors as τ grows. Results: In this paper we extend Poisson τ-leap methods to a general class of Runge-Kutta (RK) τ-leap methods. We show that with the proper selection of the coefficients, the variance of the extended τ-leap can be well-behaved, leading to significantly larger step sizes.Conclusions: The benefit of adapting the extended method to the use of RK frameworks is clear in terms of speed of calculation, as the number of evaluations of the Poisson distribution is still one set per time step, as in the original τ-leap method. The approach paves the way to explore new multiscale methods to simulate (bio)chemical systems.

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One of the first useful products from the human genome will be a set of predicted genes. Besides its intrinsic scientific interest, the accuracy and completeness of this data set is of considerable importance for human health and medicine. Though progress has been made on computational gene identification in terms of both methods and accuracy evaluation measures, most of the sequence sets in which the programs are tested are short genomic sequences, and there is concern that these accuracy measures may not extrapolate well to larger, more challenging data sets. Given the absence of experimentally verified large genomic data sets, we constructed a semiartificial test set comprising a number of short single-gene genomic sequences with randomly generated intergenic regions. This test set, which should still present an easier problem than real human genomic sequence, mimics the approximately 200kb long BACs being sequenced. In our experiments with these longer genomic sequences, the accuracy of GENSCAN, one of the most accurate ab initio gene prediction programs, dropped significantly, although its sensitivity remained high. Conversely, the accuracy of similarity-based programs, such as GENEWISE, PROCRUSTES, and BLASTX was not affected significantly by the presence of random intergenic sequence, but depended on the strength of the similarity to the protein homolog. As expected, the accuracy dropped if the models were built using more distant homologs, and we were able to quantitatively estimate this decline. However, the specificities of these techniques are still rather good even when the similarity is weak, which is a desirable characteristic for driving expensive follow-up experiments. Our experiments suggest that though gene prediction will improve with every new protein that is discovered and through improvements in the current set of tools, we still have a long way to go before we can decipher the precise exonic structure of every gene in the human genome using purely computational methodology.

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This report presents systematic empirical annotation of transcript products from 399 annotated protein-coding loci across the 1% of the human genome targeted by the Encyclopedia of DNA elements (ENCODE) pilot project using a combination of 5' rapid amplification of cDNA ends (RACE) and high-density resolution tiling arrays. We identified previously unannotated and often tissue- or cell-line-specific transcribed fragments (RACEfrags), both 5' distal to the annotated 5' terminus and internal to the annotated gene bounds for the vast majority (81.5%) of the tested genes. Half of the distal RACEfrags span large segments of genomic sequences away from the main portion of the coding transcript and often overlap with the upstream-annotated gene(s). Notably, at least 20% of the resultant novel transcripts have changes in their open reading frames (ORFs), most of them fusing ORFs of adjacent transcripts. A significant fraction of distal RACEfrags show expression levels comparable to those of known exons of the same locus, suggesting that they are not part of very minority splice forms. These results have significant implications concerning (1) our current understanding of the architecture of protein-coding genes; (2) our views on locations of regulatory regions in the genome; and (3) the interpretation of sequence polymorphisms mapping to regions hitherto considered to be "noncoding," ultimately relating to the identification of disease-related sequence alterations.

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The construction of metagenomic libraries has permitted the study of microorganisms resistant to isolation and the analysis of 16S rDNA sequences has been used for over two decades to examine bacterial biodiversity. Here, we show that the analysis of random sequence reads (RSRs) instead of 16S is a suitable shortcut to estimate the biodiversity of a bacterial community from metagenomic libraries. We generated 10,010 RSRs from a metagenomic library of microorganisms found in human faecal samples. Then searched them using the program BLASTN against a prokaryotic sequence database to assign a taxon to each RSR. The results were compared with those obtained by screening and analysing the clones containing 16S rDNA sequences in the whole library. We found that the biodiversity observed by RSR analysis is consistent with that obtained by 16S rDNA. We also show that RSRs are suitable to compare the biodiversity between different metagenomic libraries. RSRs can thus provide a good estimate of the biodiversity of a metagenomic library and, as an alternative to 16S, this approach is both faster and cheaper.

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Executive order signed by Governor Thomas Vilsck

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Excecutive order signed by Governor Thomas Vilsck

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Executive order signed by Governor Thomas Vilsck

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Executive order signed by Governor Thomas Vilsck