185 research outputs found

    Identification of Retinoic Acid in a High Content Screen for Agents that Overcome the Anti-Myogenic Effect of TGF-Beta-1

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    Transforming growth factor beta 1 (TGF-β1) is an inhibitor of muscle cell differentiation that is associated with fibrosis, poor regeneration and poor function in some diseases of muscle. When neutralizing antibodies to TGF-β1 or the angiotensin II inhibitor losartan were used to reduce TGF-β1 signaling, muscle morphology and function were restored in mouse models of Marfan Syndrome and muscular dystrophy. The goal of our studies was to identify additional agents that overcome the anti-myogenic effect of TGF-β1.A high-content cell-based assay was developed in a 96-well plate format that detects the expression of myosin heavy chain (MHC) in C2C12 cells. The assay was used to quantify the dose-dependent responses of C2C12 cell differentiation to TGF-β1 and to the TGF-β1 Type 1 receptor kinase inhibitor, SB431542. Thirteen agents previously described as promoting C2C12 differentiation in the absence of TGF-β1 were screened in the presence of TGF-β1. Only all-trans retinoic acid and 9-cis retinoic acid allowed a maximal level of C2C12 cell differentiation in the presence of TGF-β1; the angiotensin-converting enzyme inhibitor captopril and 10 nM estrogen provided partial rescue. Vitamin D was a potent inhibitor of retinoic acid-induced myogenesis in the presence of TGF-β1. TGF-β1 inhibits myoblast differentiation through activation of Smad3; however, retinoic acid did not inhibit TGF-β1-induced activation of a Smad3-dependent reporter gene in C2C12 cells.Retinoic acid alleviated the anti-myogenic effect of TGF-β1 by a Smad3-independent mechanism. With regard to the goal of improving muscle regeneration and function in individuals with muscle disease, the identification of retinoic acid is intriguing in that some retinoids are already approved for human therapy. However, retinoids also have well-described adverse effects. The quantitative, high-content assay will be useful to screen for less-toxic retinoids or combinations of agents that promote myoblast differentiation in the presence of TGF-β1

    Metabolic Profiling of a Mapping Population Exposes New Insights in the Regulation of Seed Metabolism and Seed, Fruit, and Plant Relations

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    To investigate the regulation of seed metabolism and to estimate the degree of metabolic natural variability, metabolite profiling and network analysis were applied to a collection of 76 different homozygous tomato introgression lines (ILs) grown in the field in two consecutive harvest seasons. Factorial ANOVA confirmed the presence of 30 metabolite quantitative trait loci (mQTL). Amino acid contents displayed a high degree of variability across the population, with similar patterns across the two seasons, while sugars exhibited significant seasonal fluctuations. Upon integration of data for tomato pericarp metabolite profiling, factorial ANOVA identified the main factor for metabolic polymorphism to be the genotypic background rather than the environment or the tissue. Analysis of the coefficient of variance indicated greater phenotypic plasticity in the ILs than in the M82 tomato cultivar. Broad-sense estimate of heritability suggested that the mode of inheritance of metabolite traits in the seed differed from that in the fruit. Correlation-based metabolic network analysis comparing metabolite data for the seed with that for the pericarp showed that the seed network displayed tighter interdependence of metabolic processes than the fruit. Amino acids in the seed metabolic network were shown to play a central hub-like role in the topology of the network, maintaining high interactions with other metabolite categories, i.e., sugars and organic acids. Network analysis identified six exceptionally highly co-regulated amino acids, Gly, Ser, Thr, Ile, Val, and Pro. The strong interdependence of this group was confirmed by the mQTL mapping. Taken together these results (i) reflect the extensive redundancy of the regulation underlying seed metabolism, (ii) demonstrate the tight co-ordination of seed metabolism with respect to fruit metabolism, and (iii) emphasize the centrality of the amino acid module in the seed metabolic network. Finally, the study highlights the added value of integrating metabolic network analysis with mQTL mapping

    Measurement and interpretation of same-sign W boson pair production in association with two jets in pp collisions at s = 13 TeV with the ATLAS detector

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    This paper presents the measurement of fducial and diferential cross sections for both the inclusive and electroweak production of a same-sign W-boson pair in association with two jets (W±W±jj) using 139 fb−1 of proton-proton collision data recorded at a centre-of-mass energy of √s = 13 TeV by the ATLAS detector at the Large Hadron Collider. The analysis is performed by selecting two same-charge leptons, electron or muon, and at least two jets with large invariant mass and a large rapidity diference. The measured fducial cross sections for electroweak and inclusive W±W±jj production are 2.92 ± 0.22 (stat.) ± 0.19 (syst.)fb and 3.38±0.22 (stat.)±0.19 (syst.)fb, respectively, in agreement with Standard Model predictions. The measurements are used to constrain anomalous quartic gauge couplings by extracting 95% confdence level intervals on dimension-8 operators. A search for doubly charged Higgs bosons H±± that are produced in vector-boson fusion processes and decay into a same-sign W boson pair is performed. The largest deviation from the Standard Model occurs for an H±± mass near 450 GeV, with a global signifcance of 2.5 standard deviations

    Combination of searches for heavy spin-1 resonances using 139 fb−1 of proton-proton collision data at s = 13 TeV with the ATLAS detector

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    A combination of searches for new heavy spin-1 resonances decaying into different pairings of W, Z, or Higgs bosons, as well as directly into leptons or quarks, is presented. The data sample used corresponds to 139 fb−1 of proton-proton collisions at = 13 TeV collected during 2015–2018 with the ATLAS detector at the CERN Large Hadron Collider. Analyses selecting quark pairs (qq, bb, , and tb) or third-generation leptons (τν and ττ) are included in this kind of combination for the first time. A simplified model predicting a spin-1 heavy vector-boson triplet is used. Cross-section limits are set at the 95% confidence level and are compared with predictions for the benchmark model. These limits are also expressed in terms of constraints on couplings of the heavy vector-boson triplet to quarks, leptons, and the Higgs boson. The complementarity of the various analyses increases the sensitivity to new physics, and the resulting constraints are stronger than those from any individual analysis considered. The data exclude a heavy vector-boson triplet with mass below 5.8 TeV in a weakly coupled scenario, below 4.4 TeV in a strongly coupled scenario, and up to 1.5 TeV in the case of production via vector-boson fusion
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