24 resultados para High-level languages


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Streptococcus agalactiae (group B Streptococcus, GBS) is a leading cause of sepsis in neonates. The rate of invasive GBS disease in non-pregnant adults also continues to climb. Aminoglycosides alone have little or no effect on GBS, but synergistic killing with penicillin has been shown in vitro. High-level gentamicin resistance (HLGR) in GBS isolates, however, leads to loss of a synergistic effect. We therefore performed a multicentre study to determine the frequency of HLGR GBS isolates and to elucidate the molecular mechanisms leading to gentamicin resistance. From eight centres in four countries, 1128 invasive and colonizing GBS isolates were pooled and investigated for the presence of HLGR. We identified two strains that displayed HLGR (BSU1203 and BSU452), both of which carried the aacA-aphD gene, typically conferring HLGR. Though, only one strain (BSU1203) also carried the previously described chromosomal gentamicin resistance transposon, designated Tn3706. In the other strain (BSU452), plasmid purification and subsequent DNA sequencing resulted in the detection of plasmid pIP501 carrying a remnant of a Tn3 family transposon. Its ability to confer HLGR was proven by transfer into an Enterococcus faecalis isolate. Conversely, loss of HLGR was documented after curing both GBS BSU452 and the transformed E. faecalis strain from the plasmid. This is the first report showing a plasmid mediated HLGR in GBS. Thus, in our clinical GBS isolates HLGR is mediated both chromosomally and extrachromosomally.

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The role of low-level stimulus-driven control in the guidance of overt visual attention has been difficult to establish because low- and high-level visual content are spatially correlated within natural visual stimuli. Here we show that impairment of parietal cortical areas, either permanently by a lesion or reversibly by repetitive transcranial magnetic stimulation (rTMS), leads to fixation of locations with higher values of low-level features as compared to control subjects or in a no-rTMS condition. Moreover, this unmasking of stimulus-driven control crucially depends on the intrahemispheric balance between top-down and bottom-up cortical areas. This result suggests that although in normal behavior high-level features might exert a strong influence, low-level features do contribute to guide visual selection during the exploration of complex natural stimuli.

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As object-oriented languages are extended with novel modularization mechanisms, better underlying models are required to implement these high-level features. This paper describes CELL, a language model that builds on delegation-based chains of object fragments. Composition of groups of cells is used: 1) to represent objects, 2) to realize various forms of method lookup, and 3) to keep track of method references. A running prototype of CELL is provided and used to realize the basic kernel of a Smalltalk system. The paper shows, using several examples, how higher-level features such as traits can be supported by the lower-level model.

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Concurrency control is mostly based on locks and is therefore notoriously difficult to use. Even though some programming languages provide high-level constructs, these add complexity and potentially hard-to-detect bugs to the application. Transactional memory is an attractive mechanism that does not have the drawbacks of locks, however the underlying implementation is often difficult to integrate into an existing language. In this paper we show how we have introduced transactional semantics into Smalltalk by using the reflective facilities of the language. Our approach is based on method annotations, incremental parse tree transformations and an optimistic commit protocol. The implementation does not depend on modifications to the virtual machine and therefore can be changed at the language level. We report on a practical case study, benchmarks and further and on-going work.

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RATIONALE In biomedical journals authors sometimes use the standard error of the mean (SEM) for data description, which has been called inappropriate or incorrect. OBJECTIVE To assess the frequency of incorrect use of SEM in articles in three selected cardiovascular journals. METHODS AND RESULTS All original journal articles published in 2012 in Cardiovascular Research, Circulation: Heart Failure and Circulation Research were assessed by two assessors for inappropriate use of SEM when providing descriptive information of empirical data. We also assessed whether the authors state in the methods section that the SEM will be used for data description. Of 441 articles included in this survey, 64% (282 articles) contained at least one instance of incorrect use of the SEM, with two journals having a prevalence above 70% and "Circulation: Heart Failure" having the lowest value (27%). In 81% of articles with incorrect use of SEM, the authors had explicitly stated that they use the SEM for data description and in 89% SEM bars were also used instead of 95% confidence intervals. Basic science studies had a 7.4-fold higher level of inappropriate SEM use (74%) than clinical studies (10%). LIMITATIONS The selection of the three cardiovascular journals was based on a subjective initial impression of observing inappropriate SEM use. The observed results are not representative for all cardiovascular journals. CONCLUSION In three selected cardiovascular journals we found a high level of inappropriate SEM use and explicit methods statements to use it for data description, especially in basic science studies. To improve on this situation, these and other journals should provide clear instructions to authors on how to report descriptive information of empirical data.

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BACKGROUND A cost-effective strategy to increase the density of available markers within a population is to sequence a small proportion of the population and impute whole-genome sequence data for the remaining population. Increased densities of typed markers are advantageous for genome-wide association studies (GWAS) and genomic predictions. METHODS We obtained genotypes for 54 602 SNPs (single nucleotide polymorphisms) in 1077 Franches-Montagnes (FM) horses and Illumina paired-end whole-genome sequencing data for 30 FM horses and 14 Warmblood horses. After variant calling, the sequence-derived SNP genotypes (~13 million SNPs) were used for genotype imputation with the software programs Beagle, Impute2 and FImpute. RESULTS The mean imputation accuracy of FM horses using Impute2 was 92.0%. Imputation accuracy using Beagle and FImpute was 74.3% and 77.2%, respectively. In addition, for Impute2 we determined the imputation accuracy of all individual horses in the validation population, which ranged from 85.7% to 99.8%. The subsequent inclusion of Warmblood sequence data further increased the correlation between true and imputed genotypes for most horses, especially for horses with a high level of admixture. The final imputation accuracy of the horses ranged from 91.2% to 99.5%. CONCLUSIONS Using Impute2, the imputation accuracy was higher than 91% for all horses in the validation population, which indicates that direct imputation of 50k SNP-chip data to sequence level genotypes is feasible in the FM population. The individual imputation accuracy depended mainly on the applied software and the level of admixture.