646 research outputs found

    The anti-sigma factor RsrA responds to oxidative stress by reburying its hydrophobic core

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    Redox-regulated effector systems that counteract oxidative stress are essential for all forms of life. Here we uncover a new paradigm for sensing oxidative stress centred on the hydrophobic core of a sensor protein. RsrA is an archetypal zinc-binding anti-sigma factor that responds to disulfide stress in the cytoplasm of Actinobacteria. We show that RsrA utilizes its hydrophobic core to bind the sigma factor σ R preventing its association with RNA polymerase, and that zinc plays a central role in maintaining this high-affinity complex. Oxidation of RsrA is limited by the rate of zinc release, which weakens the RsrA-σ R complex by accelerating its dissociation. The subsequent trigger disulfide, formed between specific combinations of RsrA's three zinc-binding cysteines, precipitates structural collapse to a compact state where all σ R-binding residues are sequestered back into its hydrophobic core, releasing σ R to activate transcription of anti-oxidant genes

    Stable Field Emitters for a Miniature X-ray Tube Using Carbon Nanotube Drop Drying on a Flat Metal Tip

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    Stable carbon nanotube (CNT) field emitters for a vacuum-sealed miniature X-ray tube have been fabricated. The field emitters with a uniform CNT coating are prepared by a simple drop drying of a CNT mixture solution that is composed of chemically modified multi-walled CNTs, silver nanoparticles, and isopropyl alcohol on flat tungsten tips. A highly thermal- and electrical-conductive silver layer strongly attaches CNTs to the tungsten tips. Consequently, the field emitters exhibit good electron emission stability: continuous electron emission of around 100 μA at 2.3 V/μm has stably lasted over 40 h even at non-high vacuum ambient (~10−3 Pa)

    Regulation of the let-7a-3 Promoter by NF-ÎşB

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    Changes in microRNA expression have been linked to a wide array of pathological states. However, little is known about the regulation of microRNA expression. The let-7 microRNA is a tumor suppressor that inhibits cellular proliferation and promotes differentiation, and is frequently lost in tumors. We investigated the transcriptional regulation of two let-7 family members, let-7a-3 and let-7b, which form a microRNA cluster and are located 864 bp apart on chromosome 22q13.31. Previous reports present conflicting data on the role of the NF-κB transcription factor in regulating let-7. We cloned three fragments upstream of the let-7a-3/let-7b miRNA genomic region into a plasmid containing a luciferase reporter gene. Ectopic expression of subunits of NF-κB (p50 or p65/RelA) significantly increased luciferase activity in HeLa, 293, 293T and 3T3 cells, indicating that the let-7a-3/let-7b promoter is highly responsive to NF-κB. Mutation of a putative NF-κB binding site at bp −833 reduced basal promoter activity and decreased promoter activity in the presence of p50 or p65 overexpression. Mutation of a second putative binding site, at bp −947 also decreased promoter activity basally and in response to p65 induction, indicating that both sites contribute to NF-κB responsiveness. While the levels of the endogenous primary let-7a and let-7b transcript were induced in response to NF-κB overexpression in 293T cells, the levels of fully processed, mature let-7a and let-7b miRNAs did not increase. Instead, levels of Lin-28B, a protein that blocks let-7 maturation, were induced by NF-κB. Increased Lin-28B levels could contribute to the lack of an increase in mature let-7a and let-7b. Our results suggest that the final biological outcome of NF-κB activation on let-7 expression may vary depending upon the cellular context. We discuss our results in the context of NF-κB activity in repressing self-renewal and promoting differentiation

    Comparison of bio-inspired algorithms applied to the coordination of mobile robots considering the energy consumption

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    Many applications, related to autonomous mobile robots, require to explore in an unknown environment searching for static targets, without any a priori information about the environment topology and target locations. Targets in such rescue missions can be fire, mines, human victims, or dangerous material that the robots have to handle. In these scenarios, some cooperation among the robots is required for accomplishing the mission. This paper focuses on the application of different bio-inspired metaheuristics for the coordination of a swarm of mobile robots that have to explore an unknown area in order to rescue and handle cooperatively some distributed targets. This problem is formulated by first defining an optimization model and then considering two sub-problems: exploration and recruiting. Firstly, the environment is incrementally explored by robots using a modified version of ant colony optimization. Then, when a robot detects a target, a recruiting mechanism is carried out to recruit a certain number of robots to deal with the found target together. For this latter purpose, we have proposed and compared three approaches based on three different bio-inspired algorithms (Firefly Algorithm, Particle Swarm Optimization, and Artificial Bee Algorithm). A computational study and extensive simulations have been carried out to assess the behavior of the proposed approaches and to analyze their performance in terms of total energy consumed by the robots to complete the mission. Simulation results indicate that the firefly-based strategy usually provides superior performance and can reduce the wastage of energy, especially in complex scenarios

    Performance of CMS muon reconstruction in pp collision events at sqrt(s) = 7 TeV

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    The performance of muon reconstruction, identification, and triggering in CMS has been studied using 40 inverse picobarns of data collected in pp collisions at sqrt(s) = 7 TeV at the LHC in 2010. A few benchmark sets of selection criteria covering a wide range of physics analysis needs have been examined. For all considered selections, the efficiency to reconstruct and identify a muon with a transverse momentum pT larger than a few GeV is above 95% over the whole region of pseudorapidity covered by the CMS muon system, abs(eta) < 2.4, while the probability to misidentify a hadron as a muon is well below 1%. The efficiency to trigger on single muons with pT above a few GeV is higher than 90% over the full eta range, and typically substantially better. The overall momentum scale is measured to a precision of 0.2% with muons from Z decays. The transverse momentum resolution varies from 1% to 6% depending on pseudorapidity for muons with pT below 100 GeV and, using cosmic rays, it is shown to be better than 10% in the central region up to pT = 1 TeV. Observed distributions of all quantities are well reproduced by the Monte Carlo simulation.Comment: Replaced with published version. Added journal reference and DO

    Performance of CMS muon reconstruction in pp collision events at sqrt(s) = 7 TeV

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    The performance of muon reconstruction, identification, and triggering in CMS has been studied using 40 inverse picobarns of data collected in pp collisions at sqrt(s) = 7 TeV at the LHC in 2010. A few benchmark sets of selection criteria covering a wide range of physics analysis needs have been examined. For all considered selections, the efficiency to reconstruct and identify a muon with a transverse momentum pT larger than a few GeV is above 95% over the whole region of pseudorapidity covered by the CMS muon system, abs(eta) < 2.4, while the probability to misidentify a hadron as a muon is well below 1%. The efficiency to trigger on single muons with pT above a few GeV is higher than 90% over the full eta range, and typically substantially better. The overall momentum scale is measured to a precision of 0.2% with muons from Z decays. The transverse momentum resolution varies from 1% to 6% depending on pseudorapidity for muons with pT below 100 GeV and, using cosmic rays, it is shown to be better than 10% in the central region up to pT = 1 TeV. Observed distributions of all quantities are well reproduced by the Monte Carlo simulation.Comment: Replaced with published version. Added journal reference and DO

    Meta-analysis on the effect of the N363S polymorphism of the glucocorticoid receptor gene (GRL) on human obesity

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    BACKGROUND: Since both excess glucocorticoid secretion and central obesity are clinical features of some obese patients, it is worthwhile to study a possible association of glucocorticoid receptor gene (GRL) variants with obesity. Previous studies have linked the N363S variant of the GRL gene to increased glucocorticoid effects such as higher body fat, a lower lean-body mass and a larger insulin response to dexamethasone. However, contradictory findings have been also reported about the association between this variant and obesity phenotypes. Individual studies may lack statistical power which may result in disparate results. This limitation can be overcome using meta-analytic techniques. METHODS: We conducted a meta-analysis to assess the association between the N363S polymorphism of the GRL gene and obesity risk. In addition to published research, we included also our own unpublished data -three novel case-control studies- in the meta-analysis The new case-control studies were conducted in German and Spanish children, adolescents and adults (total number of subjects: 1,117). Genotype was assessed by PCR-RFLP (Tsp509I). The final formal meta-analysis included a total number of 5,909 individuals. RESULTS: The meta-analysis revealed a higher body mass index (BMI) with an overall estimation of +0.18 kg/m(2 )(95% CI: +0.004 to +0.35) for homo-/heterozygous carriers of the 363S allele of the GRL gene in comparison to non-carriers. Moreover, differences in pooled BMI were statistically significant and positive when considering one-group studies from the literature in which participants had a BMI below 27 kg/m(2 )(+ 0.41 kg/m(2 )[95% CI +0.17 to +0.66]), but the differences in BMI were negative when only our novel data from younger (aged under 45) and normal weight subjects were pooled together (-0.50 kg/m(2 )[95% CI -0.84 to -0.17]). The overall risk for obesity for homo-/heterozygous carriers of the 363S allele was not statistically significant in the meta-analysis (pooled OR = 1.02; 95% CI: 0.56–1.87). CONCLUSION: Although certain genotypic effects could be population-specific, we conclude that there is no compelling evidence that the N363S polymorphism of the GRL gene is associated with either average BMI or obesity risk
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