929 resultados para basis of the solution space of a homogeneous sparse linear system
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Macrophages and B cells are activated by unmethylated CpG-containing sequences in bacterial DNA. The lack of activity of self DNA has generally been attributed to CpG suppression and methylation, although the role of methylation is in doubt. The frequency of CpG in the mouse genome is 12.5% of Escherichia coli, with unmethylated CpG occurring at similar to3% the frequency of E. coli. This suppression of CpG alone is insufficient to explain the inactivity of self DNA; vertebrate DNA was inactive at 100 mug/ml, 3000 times the concentration at which E. coli DNA activity was observed. We sought to resolve why self DNA does not activate macrophages. Known active CpG motifs occurred in the mouse genome at 18% of random occurrence, similar to general CpG suppression. To examine the contribution of methylation, genomic DNAs were PCR amplified. Removal of methylation from the mouse genome revealed activity that was 23-fold lower than E. coli DNA, although there is only a 7-fold lower frequency of known active CpG motifs in the mouse genome. This discrepancy may be explained by G-rich sequences such as GGAGGGG, which potently inhibited activation and are found in greater frequency in the mouse than the E. coli genome. In summary, general CpG suppression, CpG methylation, inhibitory motifs, and saturable DNA uptake combined to explain the inactivity of self DNA. The immunostimulatory activity of DNA is determined by the frequency of unmethylated stimulatory sequences within an individual DNA strand and the ratio of stimulatory to inhibitory sequences.
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We introduce a novel way of measuring the entropy of a set of values undergoing changes. Such a measure becomes useful when analyzing the temporal development of an algorithm designed to numerically update a collection of values such as artificial neural network weights undergoing adjustments during learning. We measure the entropy as a function of the phase-space of the values, i.e. their magnitude and velocity of change, using a method based on the abstract measure of entropy introduced by the philosopher Rudolf Carnap. By constructing a time-dynamic two-dimensional Voronoi diagram using Voronoi cell generators with coordinates of value- and value-velocity (change of magnitude), the entropy becomes a function of the cell areas. We term this measure teleonomic entropy since it can be used to describe changes in any end-directed (teleonomic) system. The usefulness of the method is illustrated when comparing the different approaches of two search algorithms, a learning artificial neural network and a population of discovering agents. (C) 2004 Elsevier Inc. All rights reserved.
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Sulfite-oxidizing molybdoenzymes convert the highly reactive and therefore toxic sulfite to sulfate and have been identified in insects, animals, plants, and bacteria. Although the well studied enzymes from higher animals serve to detoxify sulfite that arises from the catabolism of sulfur-containing amino acids, the bacterial enzymes have a central role in converting sulfite formed during dissimilatory oxidation of reduced sulfur compounds. Here we describe the structure of the Starkeya novella sulfite dehydrogenase, a heterodimeric complex of the catalytic molybdopterin subunit and a c-type cytochrome subunit, that reveals the molecular mechanism of intramolecular electron transfer in sulfite-oxidizing enzymes. The close approach of the two redox centers in the protein complex (Mo-Fe distance 16.6 angstrom) allows for rapid electron transfer via tunnelling or aided by the protein environment. The high resolution structure of the complex has allowed the identification of potential through-bond pathways for electron transfer including a direct link via Arg-55A and/or an aromatic-mediated pathway. A potential site of electron transfer to an external acceptor cytochrome c was also identified on the SorB subunit on the opposite side to the interaction with the catalytic SorA subunit.
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The United States National Aeronautics and Space Administration (NASA) publishes data (2003) which includes the name, gender, town of birth, education and some interests of almost every astronaut who has been launched into space by the dominant space explorer, the United States. This list identifies astronauts form the United States, the former USSR and its subsequently independent states, Europe, Australia and Asian participants. Our analysis of this data, we suggest, revealed the most likely characteristics of the members of the first communities in space. This led us to think about these communities as "audiences," just as earthbound communities have been grouped into audience, or "market," segments by media companies.
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The prevalence of tumours of the germ line is increasing in the male population. This complex disease has a complex aetiology. We examine the contribution of genetic mutations to the development of germ line tumours in this review. In particular, we concentrate on fly and mouse experimental systems in order to demonstrate that mutations in some conserved genes cause pathologies typical of certain human germ cell tumours, whereas other mutations elicit phenotypes that are unique to the experimental model. Despite these experimental systems being imperfect, we show that they are useful models of human testicular germ cell tumourigenesis.
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First, this study examined genetic and environmental sources of variation in performance on a standardised test of academic achievement, the Queensland Core Skills Test (QCST) (Queensland Studies Authority, 2003a). Second, it assessed the genetic correlation among the QCST score and Verbal and Performance IQ measures using the Multidimensional Aptitude Battery (MAB), [Jackson, D. N. (1984) Multidimensional Aptitude Battery manual. Port Huron, MI:Research Psychologist Press, Inc.]. Participants were 256 monozygotic twin pairs and 326 dizygotic twin pairs aged from 15 to 18 years (mean 17 years +/- 0.4 [SD]) when achievement tested, and from 15 to 22 years (mean 16 years +/- 0.4 [SD]) when IQ tested. Univariate analysis indicated a heritability for the QCST of 0.72. Adjustment to this estimate due to truncate selection (downward adjustment) and positive phenotypic assortative mating (upward adjustment) suggested a heritability of 0.76 The phenotypic (0.81) and genetic (0.91) correlations between the QCST and Verbal IQ (VIQ) were significantly stronger than the phenotypic (0.57) and genetic (0.64) correlations between the QCST and Performance IQ (PIQ). The findings suggest that individual variation in QCST performance is largely due to genetic factors and that common environmental effects may be substantially accounted for by phenotypic assortative mating. Covariance between academic achievement on the QCST and psychometric IQ (particularly VIQ) is to a large extent due to common genetic influences.
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Aims This paper presents the recommendations, developed from a 3-year consultation process, for a program of research to underpin the development of diagnostic concepts and criteria in the Substance Use Disorders section of the Diagnostic and Statistical Manual of Mental Disorders (DSM) and potentially the relevant section of the next revision of the International Classification of Diseases (ICD). Methods A preliminary list of research topics was developed at the DSM-V Launch Conference in 2004. This led to the presentation of articles on these topics at a specific Substance Use Disorders Conference in February 2005, at the end of which a preliminary list of research questions was developed. This was further refined through an iterative process involving conference participants over the following year. Results Research questions have been placed into four categories: (1) questions that could be addressed immediately through secondary analyses of existing data sets; (2) items likely to require position papers to propose criteria or more focused questions with a view to subsequent analyses of existing data sets; (3) issues that could be proposed for literature reviews, but with a lower probability that these might progress to a data analytic phase; and (4) suggestions or comments that might not require immediate action, but that could be considered by the DSM-V and ICD 11 revision committees as part of their deliberations. Conclusions A broadly based research agenda for the development of diagnostic concepts and criteria for substance use disorders is presented.
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Determining the dimensionality of G provides an important perspective on the genetic basis of a multivariate suite of traits. Since the introduction of Fisher's geometric model, the number of genetically independent traits underlying a set of functionally related phenotypic traits has been recognized as an important factor influencing the response to selection. Here, we show how the effective dimensionality of G can be established, using a method for the determination of the dimensionality of the effect space from a multivariate general linear model introduced by AMEMIYA (1985). We compare this approach with two other available methods, factor-analytic modeling and bootstrapping, using a half-sib experiment that estimated G for eight cuticular hydrocarbons of Drosophila serrata. In our example, eight pheromone traits were shown to be adequately represented by only two underlying genetic dimensions by Amemiya's approach and factor-analytic modeling of the covariance structure at the sire level. In, contrast, bootstrapping identified four dimensions with significant genetic variance. A simulation study indicated that while the performance of Amemiya's method was more sensitive to power constraints, it performed as well or better than factor-analytic modeling in correctly identifying the original genetic dimensions at moderate to high levels of heritability. The bootstrap approach consistently overestimated the number of dimensions in all cases and performed less well than Amemiya's method at subspace recovery.
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The genetic analysis of mate choice is fraught with difficulties. Males produce complex signals and displays that can consist of a combination of acoustic, visual, chemical and behavioural phenotypes. Furthermore, female preferences for these male traits are notoriously difficult to quantify. During mate choice, genes not only affect the phenotypes of the individual they are in, but can influence the expression of traits in other individuals. How can genetic analyses be conducted to encompass this complexity? Tighter integration of classical quantitative genetic approaches with modern genomic technologies promises to advance our understanding of the complex genetic basis of mate choice.
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Predator-induced morphological plasticity is a model system for investigating phenotypic plasticity in an ecological context. We investigated the genetic basis of the predator-induced plasticity in Rana lessonae by determining the pattern of genetic covariation of three morphological traits that were found to be induced in a predatory environment. Body size decreased and tail dimensions increased when reared in the presence of preying dragonfly larvae. Genetic variance in body size increased by almost an order of magnitude in the predator environment, and the first genetic principal component was found to be highly significantly different between the two environments. The across environment genetic correlation for body size was significantly below 1 indicating that different genes contributed to this trait in the two environments. Body size may therefore be able to respond to selection independently in the two environments to some extent.
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Circadian clocks maintain robust and accurate timing over a broad range of physiological temperatures, a characteristic termed temperature compensation. In Arabidopsis thaliana, ambient temperature affects the rhythmic accumulation of transcripts encoding the clock components TIMING OF CAB EXPRESSION1 (TOC1), GIGANTEA (GI), and the partially redundant genes CIRCADIAN CLOCK ASSOCIATED1 (CCA1) and LATE ELONGATED HYPOCOTYL (LHY). The amplitude and peak levels increase for TOC1 and GI RNA rhythms as the temperature increases (from 17 to 27 degrees C), whereas they decrease for LHY. However, as temperatures decrease ( from 17 to 12 degrees C), CCA1 and LHY RNA rhythms increase in amplitude and peak expression level. At 27 degrees C, a dynamic balance between GI and LHY allows temperature compensation in wild-type plants, but circadian function is impaired in Ihy and gi mutant plants. However, at 12 degrees C, CCA1 has more effect on the buffering mechanism than LHY, as the cca1 and gi mutations impair circadian rhythms more than Ihy at the lower temperature. At 17 degrees C, GI is apparently dispensable for free-running circadian rhythms, although partial GI function can affect circadian period. Numerical simulations using the interlocking-loop model show that balancing LHY/CCA1 function against GI and other evening-expressed genes can largely account for temperature compensation in wild-type plants and the temperature-specific phenotypes of gi mutants.
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We propose a novel interpretation and usage of Neural Network (NN) in modeling physiological signals, which are allowed to be nonlinear and/or nonstationary. The method consists of training a NN for the k-step prediction of a physiological signal, and then examining the connection-weight-space (CWS) of the NN to extract information about the signal generator mechanism. We de. ne a novel feature, Normalized Vector Separation (gamma(ij)), to measure the separation of two arbitrary states i and j in the CWS and use it to track the state changes of the generating system. The performance of the method is examined via synthetic signals and clinical EEG. Synthetic data indicates that gamma(ij) can track the system down to a SNR of 3.5 dB. Clinical data obtained from three patients undergoing carotid endarterectomy of the brain showed that EEG could be modeled (within a root-means-squared-error of 0.01) by the proposed method, and the blood perfusion state of the brain could be monitored via gamma(ij), with small NNs having no more than 21 connection weight altogether.
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Purpose: Tissue Doppler strain rate imaging (SRI) have been validated and applied in various clinical settings, but the clinical use of this modality is still limited due to time-consuming postprocessing, unfavorable signal to noise ratio and major angle dependency of image acquisition. 2D Strain (2DS) measures strain parameters through automated tissue tracking (Lagrangian strain) rather than tissue velocity regression. We sought to compare the accuracy of this technique with SRI and evaluate whether it overcomes the above limitations. Methods: We assessed 26 patients (13 female, age 60±5yrs) at low risk of CAD and with normal DSE at both baseline and peak stress. End systolic strain (ESS), peak systolic strain rate (SR), and timing parameters were measured by two independent observers using SRI and 2D Strain. Myocardial segments were excluded from the analyses if the insonation angle exceeded 30 degrees or if the segments were not visualized; 417 segments were evaluated. Results: Normal ranges for TVI and CEB approaches were comparable for SR (-0.99 ± 0.39 vs -0.88 ± 0.36, p=NS), ESS (-15.1 ± 6.5 vs -14.9 ± 6.3, p=NS), time to end of systole (174 ± 47 vs 174 ± 53, p=NS) and time to peak SR (TTP; 340 ± 34 vs 375 ± 57). The best correlations between the techniques were for time to end systole (rest r=0.6, p