349 research outputs found

    Solar radiation induced damage to optical properties of ZnO-type pigments Technical summary report, Jun. 27, 1966 - Mar. 27, 1967

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    Degradation model of solar radiation damage to optical properties of zinc oxide pigments used for spacecraft thermal control coating

    Structural and electronic properties of Pb1-xCdxTe and Pb1-xMnxTe ternary alloys

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    A systematic theoretical study of two PbTe-based ternary alloys, Pb1-xCdxTe and Pb1-xMnxTe, is reported. First, using ab initio methods we study the stability of the crystal structure of CdTe - PbTe solid solutions, to predict the composition for which rock-salt structure of PbTe changes into zinc-blende structure of CdTe. The dependence of the lattice parameter on Cd (Mn) content x in the mixed crystals is studied by the same methods. The obtained decrease of the lattice constant with x agrees with what is observed in both alloys. The band structures of PbTe-based ternary compounds are calculated within a tight-binding approach. To describe correctly the constituent materials new tight-binding parameterizations for PbTe and MnTe bulk crystals as well as a tight-binding description of rock-salt CdTe are proposed. For both studied ternary alloys, the calculated band gap in the L point increases with x, in qualitative agreement with photoluminescence measurements in the infrared. The results show also that in p-type Pb1-xCdxTe and Pb1-xMnxTe mixed crystals an enhancement of thermoelectrical power can be expected.Comment: 10 pages, 13 figures, submitted to Physical Review

    Glauber Dynamics for the mean-field Potts Model

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    We study Glauber dynamics for the mean-field (Curie-Weiss) Potts model with q3q\geq 3 states and show that it undergoes a critical slowdown at an inverse-temperature βs(q)\beta_s(q) strictly lower than the critical βc(q)\beta_c(q) for uniqueness of the thermodynamic limit. The dynamical critical βs(q)\beta_s(q) is the spinodal point marking the onset of metastability. We prove that when β<βs(q)\beta<\beta_s(q) the mixing time is asymptotically C(β,q)nlognC(\beta, q) n \log n and the dynamics exhibits the cutoff phenomena, a sharp transition in mixing, with a window of order nn. At β=βs(q)\beta=\beta_s(q) the dynamics no longer exhibits cutoff and its mixing obeys a power-law of order n4/3n^{4/3}. For β>βs(q)\beta>\beta_s(q) the mixing time is exponentially large in nn. Furthermore, as ββs\beta \uparrow \beta_s with nn, the mixing time interpolates smoothly from subcritical to critical behavior, with the latter reached at a scaling window of O(n2/3)O(n^{-2/3}) around βs\beta_s. These results form the first complete analysis of mixing around the critical dynamical temperature --- including the critical power law --- for a model with a first order phase transition.Comment: 45 pages, 5 figure

    Qualitative theory testing as mixed-method research

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    While the concept of mixed-methods research is more usually associated with combining quantitative and qualitative approaches, this paper outlines a study that mixed methods by undertaking qualitative theory testing and derivation when examining the relationship between health promotion theory and hospital nursing practice. Thus, it is concerned with relating the metatheoretical aspects of the debate and not with the pragmatic aspects of the research and concomitant methods. A deductive–inductive–deductive design, based on the theory–research–theory strategy of Meleis (1985), tested, revised and developed for nursing established health promotion theory using theory-testing criteria. To complement the methodological mix, the study also used the theory (i.e. a health-promotion taxonomy) as a framework to contextualise the findings rather than generate theory in the way associated with interpretative inquiry. While inconsistent with the traditional view linking theory testing with quantitative, objective epistemology, the process enabled a theoretically robust health-promotion taxonomy to be synthesised and advanced for use in nursing in relation to a paradigm of social thought

    Phenotypic screen for oxygen consumption rate identifies an anti-cancer naphthoquinone that induces mitochondrial oxidative stress.

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    A hallmark of cancer cells is their ability to reprogram nutrient metabolism. Thus, disruption to this phenotype is a potential avenue for anti-cancer therapy. Herein we used a phenotypic chemical library screening approach to identify molecules that disrupted nutrient metabolism (by increasing cellular oxygen consumption rate) and were toxic to cancer cells. From this screen we discovered a 1,4-Naphthoquinone (referred to as BH10) that is toxic to a broad range of cancer cell types. BH10 has improved cancer-selective toxicity compared to doxorubicin, 17-AAG, vitamin K3, and other known anti-cancer quinones. BH10 increases glucose oxidation via both mitochondrial and pentose phosphate pathways, decreases glycolysis, lowers GSH:GSSG and NAPDH/NAPD+ ratios exclusively in cancer cells, and induces necrosis. BH10 targets mitochondrial redox defence as evidenced by increased mitochondrial peroxiredoxin 3 oxidation and decreased mitochondrial aconitase activity, without changes in markers of cytosolic or nuclear damage. Over-expression of mitochondria-targeted catalase protects cells from BH10-mediated toxicity, while the thioredoxin reductase inhibitor auranofin synergistically enhances BH10-induced peroxiredoxin 3 oxidation and cytotoxicity. Overall, BH10 represents a 1,4-Naphthoquinone with an improved cancer-selective cytotoxicity profile via its mitochondrial specificity

    Fine-mapping of the HNF1B multicancer locus identifies candidate variants that mediate endometrial cancer risk.

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    Common variants in the hepatocyte nuclear factor 1 homeobox B (HNF1B) gene are associated with the risk of Type II diabetes and multiple cancers. Evidence to date indicates that cancer risk may be mediated via genetic or epigenetic effects on HNF1B gene expression. We previously found single-nucleotide polymorphisms (SNPs) at the HNF1B locus to be associated with endometrial cancer, and now report extensive fine-mapping and in silico and laboratory analyses of this locus. Analysis of 1184 genotyped and imputed SNPs in 6608 Caucasian cases and 37 925 controls, and 895 Asian cases and 1968 controls, revealed the best signal of association for SNP rs11263763 (P = 8.4 × 10(-14), odds ratio = 0.86, 95% confidence interval = 0.82-0.89), located within HNF1B intron 1. Haplotype analysis and conditional analyses provide no evidence of further independent endometrial cancer risk variants at this locus. SNP rs11263763 genotype was associated with HNF1B mRNA expression but not with HNF1B methylation in endometrial tumor samples from The Cancer Genome Atlas. Genetic analyses prioritized rs11263763 and four other SNPs in high-to-moderate linkage disequilibrium as the most likely causal SNPs. Three of these SNPs map to the extended HNF1B promoter based on chromatin marks extending from the minimal promoter region. Reporter assays demonstrated that this extended region reduces activity in combination with the minimal HNF1B promoter, and that the minor alleles of rs11263763 or rs8064454 are associated with decreased HNF1B promoter activity. Our findings provide evidence for a single signal associated with endometrial cancer risk at the HNF1B locus, and that risk is likely mediated via altered HNF1B gene expression

    EC-BLAST: a tool to automatically search and compare enzyme reactions.

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    We present EC-BLAST (http://www.ebi.ac.uk/thornton-srv/software/rbl/), an algorithm and Web tool for quantitative similarity searches between enzyme reactions at three levels: bond change, reaction center and reaction structure similarity. It uses bond changes and reaction patterns for all known biochemical reactions derived from atom-atom mapping across each reaction. EC-BLAST has the potential to improve enzyme classification, identify previously uncharacterized or new biochemical transformations, improve the assignment of enzyme function to sequences, and assist in enzyme engineering

    Properties and identification of antibiotic drug targets

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    <p>Abstract</p> <p>Background</p> <p>We analysed 48 non-redundant antibiotic target proteins from all bacteria, 22 antibiotic target proteins from <it>E. coli </it>only and 4243 non-drug targets from <it>E. coli </it>to identify differences in their properties and to predict new potential drug targets.</p> <p>Results</p> <p>When compared to non-targets, bacterial antibiotic targets tend to be long, have high β-sheet and low α-helix contents, are polar, are found in the cytoplasm rather than in membranes, and are usually enzymes, with ligases particularly favoured. Sequence features were used to build a support vector machine model for <it>E. coli </it>proteins, allowing the assignment of any sequence to the drug target or non-target classes, with an accuracy in the training set of 94%. We identified 319 proteins (7%) in the non-target set that have target-like properties, many of which have unknown function. 63 of these proteins have significant and undesirable similarity to a human protein, leaving 256 target like proteins that are not present in humans.</p> <p>Conclusions</p> <p>We suggest that antibiotic discovery programs would be more likely to succeed if new targets are chosen from this set of target like proteins or their homologues. In particular, 64 are essential genes where the cell is not able to recover from a random insertion disruption.</p
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