A Cellular, Language Directed Computer Architecture

If a VLSI computer architecture is to influence the field of computing in some major way, it must have attractive properties in all important aspects affecting the design, production, and the use of the resulting computers. A computer architecture that is believed to have such properties is briefly discussed

NdYAG laser treatment of a glomus tympanicum tumour

Glomus tympanicum tumours are highly vascular tumours of the middle ear. Their removal by conventional surgical methods requires an extensive procedure in many cases, often with ossicular disarticulation to allow adequate exposure prior to the 'chaotic' and haemorrhagic event of tumour removal. This paper reports on the use of an NdYAG laser in a case of a large glomus tympanicum tumour. The laser facilitated a transcanal approach, avoided ossicular disarticulation and allowed accurate and almost bloodless ablation of the entire tumour.The NdYAG laser appears to be a very useful treatment modality in the management of these highly vascular tumours. Care should be taken to avoid accidental energy transmission to the cochlea

Identification and Characterisation of the RalA-ERp57 Interaction: Evidence for GDI Activity of ERp57

RalA is a membrane-associated small GTPase that regulates vesicle trafficking. Here we identify a specific interaction between RalA and ERp57, an oxidoreductase and signalling protein. ERp57 bound specifically to the GDP-bound form of RalA, but not the GTP-bound form, and inhibited the dissociation of GDP from RalA in vitro. These activities were inhibited by reducing agents, but no disulphide bonds were detected between RalA and ERp57. Mutation of all four of ERp57's active site cysteine residues blocked sensitivity to reducing agents, suggesting that redox-dependent conformational changes in ERp57 affect binding to RalA. Mutations in the switch II region of the GTPase domain of RalA specifically reduced or abolished binding to ERp57, but did not block GTP-specific binding to known RalA effectors, the exocyst and RalBP1. Oxidative treatment of A431 cells with H2O2 inhibited cellular RalA activity, and the effect was exacerbated by expression of recombinant ERp57. The oxidative treatment significantly increased the amount of RalA localised to the cytosol. These findings suggest that ERp57 regulates RalA signalling by acting as a redox-sensitive guanine-nucleotide dissociation inhibitor (RalGDI). © 2012 Brymora et al

Distinguishing functional polymorphism from random variation in the sequences of >10,000 HLA-A, -B and -C alleles

HLA class I glycoproteins contain the functional sites that bind peptide antigens and engage lymphocyte receptors. Recently, clinical application of sequence-based HLA typing has uncovered an unprecedented number of novel HLA class I alleles. Here we define the nature and extent of the variation in 3,489 HLA-A, 4,356 HLA-B and 3,111 HLA-C alleles. This analysis required development of suites of methods, having general applicability, for comparing and analyzing large numbers of homologous sequences. At least three amino-acid substitutions are present at every position in the polymorphic α1 and α2 domains of HLA-A, -B and -C. A minority of positions have an incidence >1% for the 'second' most frequent nucleotide, comprising 70 positions in HLA-A, 85 in HLA-B and 54 in HLA-C. The majority of these positions have three or four alternative nucleotides. These positions were subject to positive selection and correspond to binding sites for peptides and receptors. Most alleles of HLA class I (>80%) are very rare, often identified in one person or family, and they differ by point mutation from older, more common alleles. These alleles with single nucleotide polymorphisms reflect the germ-line mutation rate. Their frequency predicts the human population harbors 8-9 million HLA class I variants. The common alleles of human populations comprise 42 core alleles, which represent all selected polymorphism, and recombinants that have assorted this polymorphism

Effects of ecstasy/polydrug use on memory for associative information

Rationale. Associative learning underpins behaviours that are fundamental to the everyday functioning of the individual. Evidence pointing to learning deficits in recreational drug users merits further examination. Objectives. A word pair learning task was administered to examine associative learning processes in ecstasy/polydrug users. Methods. After assignment to either single or divided attention conditions, 44 ecstasy/polydrug users, and 48 nonusers were presented with 80 word pairs at encoding. Following this, four types of stimuli were presented at the recognition phase; the words as originally paired (old pairs), previously presented words in different pairings (conjunction pairs), old words paired with new words, and pairs of new words (not presented previously). The task was to identify which of the stimuli were intact old pairs. Results. Ecstasy/ploydrug users produced significantly more false positive responses overall compared to nonusers. Increased long-term frequency of ecstasy use was positively associated with the propensity to produce false positive responses. It was also associated with a more liberal signal detection theory (SDT) decision criterion value. Measures of long term and recent cannabis use were also associated with these same word pair learning outcome measures. Conjunction word pairs, irrespective of drug use, generated the highest level of false positive responses and significantly more false positive responses were made in the DA condition compared to the SA condition. Conclusions. Overall, the results suggest that long-term ecstasy exposure may induce a deficit in associative learning and this may be in part a consequence of users adopting a more liberal decision criterion value. Key Words: Ecstasy, Drug Use, Cognition, Memory, Associative Learning, Word Pair

Bounded Influence Regression in the Presence of Heteroskedasticity of Unknown Form

In a regression model with conditional heteroskedasticity of unknown form, we propose a general class of M-estimators scaled by nonparametric estimates of the conditional standard deviations of the dependent variable. We give regularity conditions under which these estimators are asymptotically equivalent to M-estimators scaled by the true conditional standard deviations. The practical performance of these estimators is investigated through a Monte Carlo experiment

Winter wheat roots grow twice as deep as spring wheat roots, is this important for N uptake and N leaching losses?

Cropping systems comprising winter catch crops followed by spring wheat could reduce N leaching risks compared to traditional winter wheat systems in humid climates. We studied the soil mineral N (Ninorg) and root growth of winter- and spring wheat to 2.5 m depth during three years. Root depth of winter wheat (2.2 m) was twice that of spring wheat, and this was related to much lower amounts of Ninorg in the 1 to 2.5 m layer after winter wheat (81 kg Ninorg ha-1 less). When growing winter catch crops before spring wheat, N content in the 1 to 2.5 m layer after spring wheat was not different from that after winter wheat. The results suggest that by virtue of its deep rooting, winter wheat may not lead to high levels of leaching as it is often assumed in humid climates. Deep soil and root measurements (below 1 m) in this experiment were essential to answer the questions we posed

An intuitive Python interface for Bioconductor libraries demonstrates the utility of language translators

<p>Abstract</p> <p>Background</p> <p>Computer languages can be domain-related, and in the case of multidisciplinary projects, knowledge of several languages will be needed in order to quickly implements ideas. Moreover, each computer language has relative strong points, making some languages better suited than others for a given task to be implemented. The Bioconductor project, based on the R language, has become a reference for the numerical processing and statistical analysis of data coming from high-throughput biological assays, providing a rich selection of methods and algorithms to the research community. At the same time, Python has matured as a rich and reliable language for the agile development of prototypes or final implementations, as well as for handling large data sets.</p> <p>Results</p> <p>The data structures and functions from Bioconductor can be exposed to Python as a regular library. This allows a fully transparent and native use of Bioconductor from Python, without one having to know the R language and with only a small community of <it>translators</it> required to know both. To demonstrate this, we have implemented such Python representations for key infrastructure packages in Bioconductor, letting a Python programmer handle annotation data, microarray data, and next-generation sequencing data.</p> <p>Conclusions</p> <p>Bioconductor is now not solely reserved to R users. Building a Python application using Bioconductor functionality can be done just like if Bioconductor was a Python package. Moreover, similar principles can be applied to other languages and libraries. Our Python package is available at: <url>http://pypi.python.org/pypi/rpy2-bioconductor-extensions/</url></p