Laboratory measurements of forward and backward scattering of laser beams in water droplet clouds

Many aspects of the forward and backward scattering in dense water droplet clouds were studied using a laboratory scattering facility. This system is configured in a lidar geometry to facilitate comparison of the laboratory results to current lidar oriented theory and measurements. The backscatter measurements are supported with simultaneous measurements of the optical density, mass concentration, and droplet size distribution of the clouds. Measurements of the extinction and backscatter coefficients at several important laser wavelength have provided data on the relationship between these quantities for laboratory clouds at .633, 1.06, and 10.6 microns. The polarization characteristics of the backscatter of 1.06 microns were studied using several different types of clouds. More recently, the laboratory facility was modified to allow range-resolved backscatter measurements at 1.06 microns. Clouds made up of 3 layers, each with its own density, can be constructed. This allows the study of the effect of cloud inhomogeneity on the forward and backscatter

SAM68 is required for regulation of Pumilio by the NORAD long noncoding RNA

The number of known long noncoding RNA (lncRNA) functions is rapidly growing, but how those functions are encoded in their sequence and structure remains poorly understood. NORAD (noncoding RNA activated by DNA damage) is a recently characterized, abundant, and highly conserved lncRNA that is required for proper mitotic divisions in human cells. NORAD acts in the cytoplasm and antagonizes repressors from the Pumilio family that bind at least 17 sites spread through 12 repetitive units in NORAD sequence. Here we study conserved sequences in NORAD repeats, identify additional interacting partners, and characterize the interaction between NORAD and the RNA-binding protein SAM68 (KHDRBS1), which is required for NORAD function in antagonizing Pumilio. These interactions provide a paradigm for how repeated elements in a lncRNA facilitate function.</jats:p

Macrostate Data Clustering

We develop an effective nonhierarchical data clustering method using an analogy to the dynamic coarse graining of a stochastic system. Analyzing the eigensystem of an interitem transition matrix identifies fuzzy clusters corresponding to the metastable macroscopic states (macrostates) of a diffusive system. A "minimum uncertainty criterion" determines the linear transformation from eigenvectors to cluster-defining window functions. Eigenspectrum gap and cluster certainty conditions identify the proper number of clusters. The physically motivated fuzzy representation and associated uncertainty analysis distinguishes macrostate clustering from spectral partitioning methods. Macrostate data clustering solves a variety of test cases that challenge other methods.Comment: keywords: cluster analysis, clustering, pattern recognition, spectral graph theory, dynamic eigenvectors, machine learning, macrostates, classificatio

Alternative 3' UTRs direct localization of functionally diverse protein isoforms in neuronal compartments

The proper subcellular localization of RNAs and local translational regulation is crucial in highly compartmentalized cells, such as neurons. RNA localization is mediated by specific cis-regulatory elements usually found in mRNA 3'UTRs. Therefore, processes that generate alternative 3'UTRs-alternative splicing and polyadenylation-have the potential to diversify mRNA localization patterns in neurons. Here, we performed mapping of alternative 3'UTRs in neurites and soma isolated from mESC-derived neurons. Our analysis identified 593 genes with differentially localized 3'UTR isoforms. In particular, we have shown that two isoforms of Cdc42 gene with distinct functions in neuronal polarity are differentially localized between neurites and soma of mESC-derived and mouse primary cortical neurons, at both mRNA and protein level. Using reporter assays and 3'UTR swapping experiments, we have identified the role of alternative 3'UTRs and mRNA transport in differential localization of alternative CDC42 protein isoforms. Moreover, we used SILAC to identify isoform-specific Cdc42 3'UTR-bound proteome with potential role in Cdc42 localization and translation. Our analysis points to usage of alternative 3'UTR isoforms as a novel mechanism to provide for differential localization of functionally diverse alternative protein isoforms

From E-MAPs to module maps: dissecting quantitative genetic interactions using physical interactions

Recent technological breakthroughs allow the quantification of hundreds of thousands of genetic interactions (GIs) in Saccharomyces cerevisiae. The interpretation of these data is often difficult, but it can be improved by the joint analysis of GIs along with complementary data types. Here, we describe a novel methodology that integrates genetic and physical interaction data. We use our method to identify a collection of functional modules related to chromosomal biology and to investigate the relations among them. We show how the resulting map of modules provides clues for the elucidation of function both at the level of individual genes and at the level of functional modules

Equation of State Scalings in Kull

In this short report, we consider two types of equation of state (EOS) scalings, which will be referred to as type I (or density scaling) and type II (or Thomas-Fermi scaling). EOS scalings are used to correct for the fact that EOS tables are constructed with a fixed isotopic composition. Even if the isotopics in a computational zone are evolving through chemical or nuclear reactions, the EOS lookups for pressure and energy (and their derivatives with respect to density and temperature) aren't normally cognizant of this fact. The EOS scalings are an attempt to fix this shortcoming. They typically modify the incoming density and/or temperature based on ratios of isotopic quantities (like &lt;A&gt;{sub table}/&lt;A&gt;{sub zone}, &lt;Z&gt;{sub table}/&lt;Z&gt;{sub zone}), and then modify the table lookup values. In this way, the EOS can dynamically respond to the changing isotopics

Ab-initio density functional study of O on the Ag(001) surface

The adsorption of oxygen on the Ag(001) is investigated by means of density functional techniques. Starting from a characterization of the clean silver surfaces oxygen adsorption in several modifications (molecularly, on-surface, sub-surface, Ag$_2$O) for varying coverage was studied. Besides structural parameters and adsorption energies also work-function changes, vibrational frequencies and core level energies were calculated for a better characterization of the adsorption structures and an easier comparison to the rich experimental data.Comment: 26 pages, 8 figures, Surf. Sci. accepte

Intertemporal excess burden, bequest motives, and the budget deficit

The author aims to empirically determine the significant factors that affect the levels of budget deficits of central governments across time and across countries. He empirically tests two prominent theories of budget deficits-the Barro (1979) tax-smoothing approach, and the still-untested theory of negative bequest motives advocated by Cukierman and Meltzer (1989). The author uses econometric techniques including fixed-effects (both country and time) panel regressions spanning 87 countries over the period 1975 to 1992, and the Griliches treatment of missing data. The author finds relatively stronger statistical support for the tax-smoothing approach among developing countries but not in industrial countries. The existence of empirical evidence supporting the theory of negative bequest motives is indeterminate. The author also conducted post-regression analyses to assess the proportion of observed differences in budget deficits the factors were actually able to explain. These reveal that both theories are generally weak in accounting for inter-temporal changes in budget deficit shares for both industrial and developing countries. The theories performed significantly better in accounting for cross-section differences. The author has many contributions to the literature. First, he analyzes the question of what determines the size of central government budget deficits using cross-country time series data leading into the 1990s. Second, he provides empirical tests of the still-untested Cukierman-Meltzer (1989) negative bequest motive theory of budget deficits. By using the panel data, the author attempts to determine the factors that influence not only the inter-temporal differences in budget deficits but also those factors that lead to cross-country differences. Last but not least, he provides some preliminary evidence that poverty reduction is necessary for long-term government budget deficit reduction.Public Sector Economics&Finance,Environmental Economics&Policies,Economic Theory&Research,Banks&Banking Reform,Municipal Financial Management,Public Sector Economics&Finance,Economic Theory&Research,Economic Stabilization,Banks&Banking Reform,National Governance

Dietary elimination of children with food protein induced gastrointestinal allergy – micronutrient adequacy with and without a hypoallergenic formula?

Background: The cornerstone for management of Food protein-induced gastrointestinal allergy (FPGIA) is dietary exclusion; however the micronutrient intake of this population has been poorly studied. We set out to determine the dietary intake of children on an elimination diet for this food allergy and hypothesised that the type of elimination diet and the presence of a hypoallergenic formula (HF) significantly impacts on micronutrient intake. Method: A prospective observational study was conducted on children diagnosed with FPIGA on an exclusion diet who completed a 3 day semi-quantitative food diary 4 weeks after commencing the diet. Nutritional intake where HF was used was compared to those without HF, with or without a vitamin and mineral supplement (VMS). Results: One-hundred-and-five food diaries were included in the data analysis: 70 boys (66.7%) with median age of 21.8 months [IQR: 10 - 67.7]. Fifty-three children (50.5%) consumed a HF and the volume of consumption was correlated to micronutrient intake. Significantly (p <0.05) more children reached their micronutrient requirements if a HF was consumed. In those without a HF, some continued not to achieve requirements in particular for vitamin D and zinc, in spite of VMS. Conclusion: This study points towards the important micronutrient contribution of a HF in children with FPIGA. Children, who are not on a HF and without a VMS, are at increased risk of low intakes in particular vitamin D and zinc. Further studies need to be performed, to assess whether dietary intake translates into actual biological deficiencies

Increased entropy of signal transduction in the cancer metastasis phenotype

Studies into the statistical properties of biological networks have led to important biological insights, such as the presence of hubs and hierarchical modularity. There is also a growing interest in studying the statistical properties of networks in the context of cancer genomics. However, relatively little is known as to what network features differ between the cancer and normal cell physiologies, or between different cancer cell phenotypes. Based on the observation that frequent genomic alterations underlie a more aggressive cancer phenotype, we asked if such an effect could be detectable as an increase in the randomness of local gene expression patterns. Using a breast cancer gene expression data set and a model network of protein interactions we derive constrained weighted networks defined by a stochastic information flux matrix reflecting expression correlations between interacting proteins. Based on this stochastic matrix we propose and compute an entropy measure that quantifies the degree of randomness in the local pattern of information flux around single genes. By comparing the local entropies in the non-metastatic versus metastatic breast cancer networks, we here show that breast cancers that metastasize are characterised by a small yet significant increase in the degree of randomness of local expression patterns. We validate this result in three additional breast cancer expression data sets and demonstrate that local entropy better characterises the metastatic phenotype than other non-entropy based measures. We show that increases in entropy can be used to identify genes and signalling pathways implicated in breast cancer metastasis. Further exploration of such integrated cancer expression and protein interaction networks will therefore be a fruitful endeavour.Comment: 5 figures, 2 Supplementary Figures and Table