976 research outputs found

    Properties of the QCD thermal transition with Nf=2+1 flavors of Wilson quark

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    We study properties of the thermal transition in QCD, using anisotropic, fixed-scale lattice simulations with Nf=2+1 flavors of Wilson fermion. Observables are compared for two values of the pion mass, focusing on chiral properties. Results are presented for the Polyakov loop, various susceptibilities, the chiral condensate and its susceptibility, and the onset of parity doubling in the light and strange baryonic sector

    A paradox of syntactic priming: why response tendencies show priming for passives, and response latencies show priming for actives

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    Speakers tend to repeat syntactic structures across sentences, a phenomenon called syntactic priming. Although it has been suggested that repeating syntactic structures should result in speeded responses, previous research has focused on effects in response tendencies. We investigated syntactic priming effects simultaneously in response tendencies and response latencies for active and passive transitive sentences in a picture description task. In Experiment 1, there were priming effects in response tendencies for passives and in response latencies for actives. However, when participants' pre-existing preference for actives was altered in Experiment 2, syntactic priming occurred for both actives and passives in response tendencies as well as in response latencies. This is the first investigation of the effects of structure frequency on both response tendencies and latencies in syntactic priming. We discuss the implications of these data for current theories of syntactic processing

    Identification of disease-causing genes using microarray data mining and gene ontology

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    Background: One of the best and most accurate methods for identifying disease-causing genes is monitoring gene expression values in different samples using microarray technology. One of the shortcomings of microarray data is that they provide a small quantity of samples with respect to the number of genes. This problem reduces the classification accuracy of the methods, so gene selection is essential to improve the predictive accuracy and to identify potential marker genes for a disease. Among numerous existing methods for gene selection, support vector machine-based recursive feature elimination (SVMRFE) has become one of the leading methods, but its performance can be reduced because of the small sample size, noisy data and the fact that the method does not remove redundant genes. Methods: We propose a novel framework for gene selection which uses the advantageous features of conventional methods and addresses their weaknesses. In fact, we have combined the Fisher method and SVMRFE to utilize the advantages of a filtering method as well as an embedded method. Furthermore, we have added a redundancy reduction stage to address the weakness of the Fisher method and SVMRFE. In addition to gene expression values, the proposed method uses Gene Ontology which is a reliable source of information on genes. The use of Gene Ontology can compensate, in part, for the limitations of microarrays, such as having a small number of samples and erroneous measurement results. Results: The proposed method has been applied to colon, Diffuse Large B-Cell Lymphoma (DLBCL) and prostate cancer datasets. The empirical results show that our method has improved classification performance in terms of accuracy, sensitivity and specificity. In addition, the study of the molecular function of selected genes strengthened the hypothesis that these genes are involved in the process of cancer growth. Conclusions: The proposed method addresses the weakness of conventional methods by adding a redundancy reduction stage and utilizing Gene Ontology information. It predicts marker genes for colon, DLBCL and prostate cancer with a high accuracy. The predictions made in this study can serve as a list of candidates for subsequent wet-lab verification and might help in the search for a cure for cancers

    Positive words carry less information than negative words

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    We show that the frequency of word use is not only determined by the word length \cite{Zipf1935} and the average information content \cite{Piantadosi2011}, but also by its emotional content. We have analyzed three established lexica of affective word usage in English, German, and Spanish, to verify that these lexica have a neutral, unbiased, emotional content. Taking into account the frequency of word usage, we find that words with a positive emotional content are more frequently used. This lends support to Pollyanna hypothesis \cite{Boucher1969} that there should be a positive bias in human expression. We also find that negative words contain more information than positive words, as the informativeness of a word increases uniformly with its valence decrease. Our findings support earlier conjectures about (i) the relation between word frequency and information content, and (ii) the impact of positive emotions on communication and social links.Comment: 16 pages, 3 figures, 3 table

    G-protein inwardly rectifying potassium channel 1 (GIRK 1) gene expression correlates with tumor progression in non-small cell lung cancer

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    BACKGROUND: G-protein inwardly rectifying potassium channel 1 (GIRK1) is thought to play a role in cell proliferation in cancer, and GIRK1 gene expression level may define a more aggressive phenotype. We detected GIRK1 expression in tissue specimens from patients with non-small cell lung cancers (NSCLCs) and assessed their clinical characteristics. METHODS: Using reverse transcription-polymerase chain reaction (RT-PCR) analyses, we quantified the expression of GIRK1 in 72 patients with NSCLCs to investigate the relationship between GIRK1 expression and clinicopathologic factors and prognosis. RESULTS: In 72 NSCLC patients, 50 (69%) samples were evaluated as having high GIRK1 gene expression, and 22 (31%) were evaluated as having low GIRK1 gene expression. GIRK1 gene expression was significantly associated with lymph node metastasis, stage (p = 0.0194 for lymph node metastasis; p = 0.0207 for stage). The overall and stage I survival rates for patients with high GIRK1 gene expressed tumors was significantly worse than for those individuals whose tumors had low GIRK1 expression (p = 0.0004 for the overall group; p = 0.0376 for stage I). CONCLUSIONS: These data indicate that GIRK1 may contribute to tumor progression and GIRK1 gene expression can serve as a useful prognostic marker in the overall and stage I NSCLCs

    Radio Emission from Ultra-Cool Dwarfs

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    The 2001 discovery of radio emission from ultra-cool dwarfs (UCDs), the very low-mass stars and brown dwarfs with spectral types of ~M7 and later, revealed that these objects can generate and dissipate powerful magnetic fields. Radio observations provide unparalleled insight into UCD magnetism: detections extend to brown dwarfs with temperatures <1000 K, where no other observational probes are effective. The data reveal that UCDs can generate strong (kG) fields, sometimes with a stable dipolar structure; that they can produce and retain nonthermal plasmas with electron acceleration extending to MeV energies; and that they can drive auroral current systems resulting in significant atmospheric energy deposition and powerful, coherent radio bursts. Still to be understood are the underlying dynamo processes, the precise means by which particles are accelerated around these objects, the observed diversity of magnetic phenomenologies, and how all of these factors change as the mass of the central object approaches that of Jupiter. The answers to these questions are doubly important because UCDs are both potential exoplanet hosts, as in the TRAPPIST-1 system, and analogues of extrasolar giant planets themselves.Comment: 19 pages; submitted chapter to the Handbook of Exoplanets, eds. Hans J. Deeg and Juan Antonio Belmonte (Springer-Verlag

    A modified empirical criterion for strength of transversely anisotropic rocks with metamorphic origin

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    A modified empirical criterion is proposed to determine the strength of transversely anisotropic rocks. In this regard, mechanical properties of intact anisotropic slate obtained from three different districts of Iran were taken into consideration. Afterward, triaxial rock strength criterion introduced by Rafiai was modified for transversely anisotropic rocks. The criterion was modified by adding a new parameter α for taking the influence of strength anisotropy into consideration. The results obtained have shown that the parameter α can be considered as the strength reduction parameter due to rock anisotropy. The modified criterion was compared to the modified Hoek–Brown (Saroglou and Tsiambaos) and Ramamurthy criteria for different anisotropic rocks. It was concluded that the criterion proposed in this paper is a more accurate and precise criterion in predicting the strength of anisotropic rocks

    The capabilities and limitations of conductance-based compartmental neuron models with reduced branched or unbranched morphologies and active dendrites

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    Conductance-based neuron models are frequently employed to study the dynamics of biological neural networks. For speed and ease of use, these models are often reduced in morphological complexity. Simplified dendritic branching structures may process inputs differently than full branching structures, however, and could thereby fail to reproduce important aspects of biological neural processing. It is not yet well understood which processing capabilities require detailed branching structures. Therefore, we analyzed the processing capabilities of full or partially branched reduced models. These models were created by collapsing the dendritic tree of a full morphological model of a globus pallidus (GP) neuron while preserving its total surface area and electrotonic length, as well as its passive and active parameters. Dendritic trees were either collapsed into single cables (unbranched models) or the full complement of branch points was preserved (branched models). Both reduction strategies allowed us to compare dynamics between all models using the same channel density settings. Full model responses to somatic inputs were generally preserved by both types of reduced model while dendritic input responses could be more closely preserved by branched than unbranched reduced models. However, features strongly influenced by local dendritic input resistance, such as active dendritic sodium spike generation and propagation, could not be accurately reproduced by any reduced model. Based on our analyses, we suggest that there are intrinsic differences in processing capabilities between unbranched and branched models. We also indicate suitable applications for different levels of reduction, including fast searches of full model parameter space

    Analytic philosophy for biomedical research: the imperative of applying yesterday's timeless messages to today's impasses

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    The mantra that "the best way to predict the future is to invent it" (attributed to the computer scientist Alan Kay) exemplifies some of the expectations from the technical and innovative sides of biomedical research at present. However, for technical advancements to make real impacts both on patient health and genuine scientific understanding, quite a number of lingering challenges facing the entire spectrum from protein biology all the way to randomized controlled trials should start to be overcome. The proposal in this chapter is that philosophy is essential in this process. By reviewing select examples from the history of science and philosophy, disciplines which were indistinguishable until the mid-nineteenth century, I argue that progress toward the many impasses in biomedicine can be achieved by emphasizing theoretical work (in the true sense of the word 'theory') as a vital foundation for experimental biology. Furthermore, a philosophical biology program that could provide a framework for theoretical investigations is outlined

    Destabilization of the Dystrophin-Glycoprotein Complex without Functional Deficits in α-Dystrobrevin Null Muscle

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    α-Dystrobrevin is a component of the dystrophin-glycoprotein complex (DGC) and is thought to have both structural and signaling roles in skeletal muscle. Mice deficient for α-dystrobrevin (adbn−/−) exhibit extensive myofiber degeneration and neuromuscular junction abnormalities. However, the biochemical stability of the DGC and the functional performance of adbn−/− muscle have not been characterized. Here we show that the biochemical association between dystrophin and β-dystroglycan is compromised in adbn−/− skeletal muscle, suggesting that α-dystrobrevin plays a structural role in stabilizing the DGC. However, despite muscle cell death and DGC destabilization, costamere organization and physiological performance is normal in adbn−/− skeletal muscle. Our results demonstrate that myofiber degeneration alone does not cause functional deficits and suggests that more complex pathological factors contribute to the development of muscle weakness in muscular dystrophy
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