627 research outputs found

    Proof of Stanley's conjecture about irreducible character values of the symmetric group

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    R. Stanley has found a nice combinatorial formula for characters of irreducible representations of the symmetric group of rectangular shape. Then, he has given a conjectural generalisation for any shape. Here, we will prove this formula using shifted Schur functions and Jucys-Murphy elements.Comment: 9 page

    Non-linear complex principal component analysis of nearshore bathymetry

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    International audienceComplex principal component analysis (CPCA) is a useful linear method for dimensionality reduction of data sets characterized by propagating patterns, where the CPCA modes are linear functions of the complex principal component (CPC), consisting of an amplitude and a phase. The use of non-linear methods, such as the neural-network based circular non-linear principal component analysis (NLPCA.cir) and the recently developed non-linear complex principal component analysis (NLCPCA), may provide a more accurate description of data in case the lower-dimensional structure is non-linear. NLPCA.cir extracts non-linear phase information without amplitude variability, while NLCPCA is capable of extracting both. NLCPCA can thus be viewed as a non-linear generalization of CPCA. In this article, NLCPCA is applied to bathymetry data from the sandy barred beaches at Egmond aan Zee (Netherlands), the Hasaki coast (Japan) and Duck (North Carolina, USA) to examine how effective this new method is in comparison to CPCA and NLPCA.cir in representing propagating phenomena. At Duck, the underlying low-dimensional data structure is found to have linear phase and amplitude variability only and, accordingly, CPCA performs as well as NLCPCA. At Egmond, the reduced data structure contains non-linear spatial patterns (asymmetric bar/trough shapes) without much temporal amplitude variability and, consequently, is about equally well modelled by NLCPCA and NLPCA.cir. Finally, at Hasaki, the data structure displays not only non-linear spatial variability but also considerably temporal amplitude variability, and NLCPCA outperforms both CPCA and NLPCA.cir. Because it is difficult to know the structure of data in advance as to which one of the three models should be used, the generalized NLCPCA model can be used in each situation

    Quantitative trait loci associated with traits determining grain and stover yield in pearl millet under terminal drought stress conditions.

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    Drought stress during the reproductive stage is one of the most important environmental factors reducing the grain yield and yield stability of pearl millet. A QTL mapping approach has been used in this study to understand the genetic and physiological basis of drought tolerance in pearl millet and to provide a more-targeted approach to improving the drought tolerance and yield of this crop in water-limited environments. The aim was to identify specific genomic regions associated with the enhanced tolerance of pearl millet to drought stress during the flowering and grain-filling stages. Test-crosses of a set of mapping-population progenies, derived from a cross of two inbred pollinators that differed in their response to drought, were evaluated in a range of managed terminal drought-stress environments. A number of genomic regions were associated with drought tolerance in terms of both grain yield and its components. For example, a QTL associated with grain yield per se and for the drought tolerance of grain yield mapped on linkage group 2 and explained up to 23% of the phenotypic variation. Some of these QTLs were common across stress environments whereas others were specific to only a particular stress environment. All the QTLs that contributed to increased drought tolerance did so either through better than average maintenance (compared to non-stress environments) of harvest index, or harvest index and biomass productivity. It is concluded that there is considerable potential for marker-assisted backcross transfer of selected QTLs to the elite parent of the mapping population and for their general use in the improvement of pearl millet productivity in water-limited environments

    Differentially expressed genes in platinum-resistant high-grade serous ovarian cancer

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    Objectives: The purpose of this study was to identify genes and pathways differentially expressed in platinum resistant high grade serous ovarian cancer (HGSOC) when compared to sensitive HGSOC. Methods: A total of 37 patients with HGSOC tissue samples underwent RNA sequencing performed by TEMPUS (N=37, 21 platinum sensitive, 16 resistant; 85% Stage III-IV; 58% received neoadjuvant chemotherapy). RNA gene expression data and significantly impacted pathways were analyzed using Advaita Bio\u27s iPathwayGuide. Differentially expressed (DE) genes were identified using FDR of 0.05 and fold-change of 1.5. Genes from several impacted canonical metabolic pathways were validated by PCR against external data sets in a separate ovarian cancer sample group (n=15), platinum resistant ovarian cancer mouse tumor model, and wild-type sensitive and platinum resistant ovarian cancer cell lines. Relative gene expression was calculated using the comparative Ct method, also referred to as the “2 DDCT”, using L27 as internal control gene. Results: We identified 177 differentially expressed (DE) genes out of a total of 16,607 genes (1.1%) with measured expression. 15 pathways were found to be significantly impacted. Of the 15 canonical pathways, all were up regulated in the resistant HGSOC and the majority of the most significantly altered (5/10) were related to metabolism (Retinol metabolism (p-value = 0.002); Tyrosine Metabolism (p-value = 0.005); Tryptophan Metabolism (p-value = 0.009); and Phenylalanine Metabolism (p-value = 0.012); CYP Drug Metabolism (p-value = 0.022)). A total of 3 separate genes from the CYP family and two from the Dopa Decarboxylase family of genes were validated against an external data set of human ovarian tissue samples, cell lines, mouse ovarian tumor model, and found to have similarly increased gene expression in the genes tested in the platinum resistant groups. Compilation of KEGG analysis and the common network genes revealed pathways associated with amino acid metabolism to be most significantly altered. Conclusions: We describe the identification of a unique transcriptomic profile associated with platinum resistance. Interestingly, the main pathways identified are related to metabolism, suggesting that the survival to chemotherapy demands a major metabolic adaptation. These findings also represent a first step towards the identification of biomarkers for the detection of chemo-resistant disease and metabolism-based drug targets specific for chemo-resistant tumors. Further validation of this model is required in order to determine its clinical value

    Smooth Muscle Stiffness Sensitivity is Driven by Soluble and Insoluble ECM Chemistry

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    Smooth muscle cell (SMC) invasion into plaques and subsequent proliferation is a major factor in the progression of atherosclerosis. During disease progression, SMCs experience major changes in their microenvironment, such as what integrin-binding sites are exposed, the portfolio of soluble factors available, and the elasticity and modulus of the surrounding vessel wall. We have developed a hydrogel biomaterial platform to examine the combined effect of these changes on SMC phenotype. We were particularly interested in how the chemical microenvironment affected the ability of SMCs to sense and respond to modulus. To our surprise, we observed that integrin binding and soluble factors are major drivers of several critical SMC behaviors, such as motility, proliferation, invasion, and differentiation marker expres- sion, and these factors modulated the effect of stiffness on proliferation and migration. Overall, modulus only modestly affected behaviors other than proliferation, relative to integrin binding and soluble factors. Surprisingly, patho- logical behaviors (proliferation, motility) are not inversely related to SMC marker expression, in direct conïŹ‚ict with previous studies on substrates coupled with single extracel- lular matrix (ECM) proteins. A high-throughput bead-based ELISA approach and inhibitor studies revealed that differ- entiation marker expression is mediated chieïŹ‚y via focal adhesion kinase (FAK) signaling, and we propose that integrin binding and FAK drive the transition from a migratory to a proliferative phenotype. We emphasize the importance of increasing the complexity of in vitro testing platforms to capture these subtleties in cell phenotypes and signaling, in order to better recapitulate important features of in vivo disease and elucidate potential context-dependent therapeutic targets

    The maintenance gap: a new theoretical perspective on the evolution of aging

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    One of the prevailing theories of aging, the disposable soma theory, views aging as the result of the accumulation of damage through imperfect maintenance. Aging, then, is explained from an evolutionary perspective by asserting that this lack of maintenance exists because the required resources are better invested in reproduction. However, the amount of maintenance necessary to prevent aging, ‘maintenance requirement’ has so far been largely neglected and has certainly not been considered from an evolutionary perspective. To our knowledge we are the first to do so, and arrive at the conclusion that all maintenance requirement needs an evolutionary explanation. Increases in maintenance requirement can only be selected for if these are linked with either higher fecundity or better capabilities to cope with environmental challenges to the integrity of the organism. Several observations are suggestive of the latter kind of trade-off, the existence of which leads to the inevitable conclusion that the level of maintenance requirement is in principle unbound. Even the allocation of all available resources to maintenance could be unable to stop aging in some organisms. This has major implications for our understanding of the aging process on both the evolutionary and the mechanistic level. It means that the expected effect of measures to reallocate resources to maintenance from reproduction may be small in some species. We need to have an idea of how much maintenance is necessary in the first place. Our explorations of how natural selection is expected to act on the maintenance requirement provides the first step in understanding this
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