326 research outputs found

    Limited utility of qPCR-based detection of tumor-specific circulating mRNAs in whole blood from clear cell renal cell carcinoma patients

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    BACKGROUND: RNA sequencing data is providing abundant information about the levels of dysregulation of genes in various tumors. These data, as well as data based on older microarray technologies have enabled the identification of many genes which are upregulated in clear cell renal cell carcinoma (ccRCC) compared to matched normal tissue. Here we use RNA sequencing data in order to construct a panel of highly overexpressed genes in ccRCC so as to evaluate their RNA levels in whole blood and determine any diagnostic potential of these levels for renal cell carcinoma patients. METHODS: A bioinformatics analysis with Python was performed using TCGA, GEO and other databases to identify genes which are upregulated in ccRCC while being absent in the blood of healthy individuals. Quantitative Real Time PCR (RT-qPCR) was subsequently used to measure the levels of candidate genes in whole blood (PAX gene) of 16 ccRCC patients versus 11 healthy individuals. PCR results were processed in qBase and GraphPadPrism and statistics was done with Mann-Whitney U test. RESULTS: While most analyzed genes were either undetectable or did not show any dysregulated expression, two genes, CDK18 and CCND1, were paradoxically downregulated in the blood of ccRCC patients compared to healthy controls. Furthermore, LOX showed a tendency towards upregulation in metastatic ccRCC samples compared to non-metastatic. CONCLUSIONS: This analysis illustrates the difficulty of detecting tumor regulated genes in blood and the possible influence of interference from expression in blood cells even for genes conditionally absent in normal blood. Testing in plasma samples indicated that tumor specific mRNAs were not detectable. While CDK18, CCND1 and LOX mRNAs might carry biomarker potential, this would require validation in an independent, larger patient cohort

    Constraining Single-Field Inflation with MegaMapper

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    We forecast the constraints on single-field inflation from the bispectrum of future high-redshift surveys such as MegaMapper. Considering non-local primordial non-Gaussianity (NLPNG), we find that current methods will yield constraints of order σ(fNLeq)23\sigma(f_{\rm NL}^{\rm eq})\approx 23, σ(fNLorth)12\sigma(f_{\rm NL}^{\rm orth})\approx 12 in a joint power-spectrum and bispectrum analysis, varying both nuisance parameters and cosmology, including a conservative range of scales. Fixing cosmological parameters and quadratic bias parameter relations, the limits tighten significantly to σ(fNLeq)17\sigma(f_{\rm NL}^{\rm eq})\approx 17, σ(fNLorth)8\sigma(f_{\rm NL}^{\rm orth})\approx 8. These compare favorably with the forecasted bounds from CMB-S4: σ(fNLeq)21\sigma(f_{\rm NL}^{\rm eq})\approx 21, σ(fNLorth)9\sigma(f_{\rm NL}^{\rm orth})\approx 9, with a combined constraint of σ(fNLeq)14\sigma(f_{\rm NL}^{\rm eq})\approx 14, σ(fNLorth)7\sigma(f_{\rm NL}^{\rm orth})\approx 7; this weakens only slightly if one instead combines with data from the Simons Observatory. We additionally perform a range of Fisher analyses for the error, forecasting the dependence on nuisance parameter marginalization, scale cuts, and survey strategy. Lack of knowledge of bias and counterterm parameters is found to significantly limit the information content; this could be ameliorated by tight simulation-based priors on the nuisance parameters. The error-bars decrease significantly as the number of observed galaxies and survey depth is increased: as expected, deep dense surveys are the most constraining, though it will be difficult to reach σ(fNL)1\sigma(f_{\rm NL})\approx 1 with current methods. The NLPNG constraints will tighten further with improved theoretical models (incorporating higher-loop corrections), as well as the inclusion of additional higher-order statistics.Comment: 6 pages, 3 figures, submitted to Phys. Lett.

    Modifying the photodetachment near a metal surface by a weak electric field

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    We show the photodetachment cross sections of H near a metal surface can be modified using a weak static electric field. The modification is possible because the oscillatory part of the cross section near a metal surface is directly connected with the transit-time and the action of the detached-electron closed-orbit which can be changed systematically by varying the static electric field strength. Photodetachment cross sections for various photon energies and electric field values are calculated and displayed.Comment: 16 pages, 7 figure

    Classical Coulomb three-body problem in collinear eZe configuration

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    Classical dynamics of two-electron atom and ions H^{-}, He, Li+^{+}, Be2+^{2+},... in collinear eZe configuration is investigated. It is revealed that the mass ratio ξ\xi between necleus and electron plays an important role for dynamical behaviour of these systems. With the aid of analytical tool and numeircal computation, it is shown that thanks to large mass ratio ξ\xi, classical dynamics of these systems is fully chaotic, probably hyperbolic. Experimental manifestation of this finding is also proposed.Comment: Largely rewritten. 21 pages. All figures are available in http://ace.phys.h.kyoto-u.ac.jp/~sano/3-body/index.htm

    Fewer Mocks and Less Noise: Reducing the Dimensionality of Cosmological Observables with Subspace Projections

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    Creating accurate and low-noise covariance matrices represents a formidable challenge in modern-day cosmology. We present a formalism to compress arbitrary observables into a small number of bins by projection into a model-specific subspace that minimizes the prior-averaged log-likelihood error. The lower dimensionality leads to a dramatic reduction in covariance matrix noise, significantly reducing the number of mocks that need to be computed. Given a theory model, a set of priors, and a simple model of the covariance, our method works by using singular value decompositions to construct a basis for the observable that is close to Euclidean; by restricting to the first few basis vectors, we can capture almost all the constraining power in a lower-dimensional subspace. Unlike conventional approaches, the method can be tailored for specific analyses and captures non-linearities that are not present in the Fisher matrix, ensuring that the full likelihood can be reproduced. The procedure is validated with full-shape analyses of power spectra from BOSS DR12 mock catalogs, showing that the 96-bin power spectra can be replaced by 12 subspace coefficients without biasing the output cosmology; this allows for accurate parameter inference using only 100\sim 100 mocks. Such decompositions facilitate accurate testing of power spectrum covariances; for the largest BOSS data chunk, we find that: (a) analytic covariances provide accurate models (with or without trispectrum terms); and (b) using the sample covariance from the MultiDark-Patchy mocks incurs a 0.5σ\sim 0.5\sigma shift in Ωm\Omega_m, unless the subspace projection is applied. The method is easily extended to higher order statistics; the 2000\sim 2000-bin bispectrum can be compressed into only 10\sim 10 coefficients, allowing for accurate analyses using few mocks and without having to increase the bin sizes.Comment: 22 pages, 6 figures. Accepted by Phys. Rev.

    Risk assessment of non-native fishes in the Balkans Region using FISK, the invasiveness screening tool for non-native freshwater fishes

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    A high level of freshwater fish endemism in the Balkans Region emphasizes the need for non-native species risk assessments to inform management and control measures, with pre-screening tools, such as the Fish Invasiveness Screening Kit (FISK) providing a useful first step. Applied to 43 non-native and translocated freshwater fishes in four Balkan countries, FISK reliably discriminated between invasive and non-invasive species, with a calibration threshold value of 9.5 distinguishing between species of medium and high risk sensu lato of becoming invasive. Twelve of the 43 species were assessed by scientists from two or more Balkan countries, and the remaining 31 species by a single assessor. Using the 9.5 threshold, three species were classed as low risk, 10 as medium risk, and 30 as high risk, with the latter category comprised of 26 moderately high risk, three high risk, and one very high risk species. Confidence levels in the assessments were relatively constant for all species, indicating concordance amongst assessors

    Renormalization group scale-setting from the action - a road to modified gravity theories

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    The renormalization group (RG) corrected gravitational action in Einstein-Hilbert and other truncations is considered. The running scale of the renormalization group is treated as a scalar field at the level of the action and determined in a scale-setting procedure recently introduced by Koch and Ramirez for the Einstein-Hilbert truncation. The scale-setting procedure is elaborated for other truncations of the gravitational action and applied to several phenomenologically interesting cases. It is shown how the logarithmic dependence of the Newton's coupling on the RG scale leads to exponentially suppressed effective cosmological constant and how the scale-setting in particular RG corrected gravitational theories yields the effective f(R)f(R) modified gravity theories with negative powers of the Ricci scalar RR. The scale-setting at the level of the action at the non-gaussian fixed point in Einstein-Hilbert and more general truncations is shown to lead to universal effective action quadratic in Ricci tensor.Comment: v1: 15 pages; v2: shortened to 10 pages, main results unchanged, published in Class. Quant. Gra

    STRING v11: protein-protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets

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    Proteins and their functional interactions form the backbone of the cellular machinery. Their connectivity network needs to be considered for the full understanding of biological phenomena, but the available information on protein-protein associations is incomplete and exhibits varying levels of annotation granularity and reliability. The STRING database aims to collect, score and integrate all publicly available sources of protein-protein interaction information, and to complement these with computational predictions. Its goal is to achieve a comprehensive and objective global network, including direct (physical) as well as indirect (functional) interactions. The latest version of STRING (11.0) more than doubles the number of organisms it covers, to 5090. The most important new feature is an option to upload entire, genome-wide datasets as input, allowing users to visualize subsets as interaction networks and to perform gene-set enrichment analysis on the entire input. For the enrichment analysis, STRING implements well-known classification systems such as Gene Ontology and KEGG, but also offers additional, new classification systems based on high-throughput text-mining as well as on a hierarchical clustering of the association network itself. The STRING resource is available online at https://string-db.org/
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