269 resultados para 105-646
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Diseases that affect the regulation of bone turnover can lead to skeletal fragility and increased fracture risk. Members of the TGF-superfamily have been shown to be involved in the regulation of bone mass. Activin A, a TGF-� signaling ligand, is present at high levels in bone and may play a role in the regulation of bone metabolism. Here we demonstrate that pharmacological blockade of ligand signaling through the high affinity receptor for activin, type II activin receptor (ActRIIA), by administration of the soluble extracellular domain of ActRIIA fused to a murine IgG2a-Fc, increases bone formation, bone mass, and bone strength in normal mice and in ovariectomized mice with established bone loss. These observations support the development of this pharmacological strategy for the treatment of diseases with skeletal fragility.
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Plant small RNAs are a class of 19- to 25-nucleotide (nt) RNA molecules that are essential for genome stability, development and differentiation, disease, cellular communication, signaling, and adaptive responses to biotic and abiotic stress. Small RNAs comprise two major RNA classes, short interfering RNAs (siRNAs) and microRNAs (miRNAs). Efficient and reliable detection and quantification of small RNA expression has become an essential step in understanding their roles in specific cells and tissues. Here we provide protocols for the detection of miRNAs by stem-loop RT-PCR. This method enables fast and reliable miRNA expression profiling from as little as 20 pg of total RNA extracted from plant tissue and is suitable for high-throughput miRNA expression analysis. In addition, this method can be used to detect other classes of small RNAs, provided the sequence is known and their GC contents are similar to those specific for miRNAs.
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Review of His Stupid Boyhood by Peter Goldsworthy (Hamish Hamilton, 2013).
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Objective This study compared correlates of physical activity (PA) among African-American and white girls of different weight groups to guide future interventions. Research Methods and Procedures Participants were 1015 girls (mean age, 14.6 years; 45% African-American) from 12 high schools in South Carolina who served as control subjects for a school-based intervention. Post-intervention measures obtained at the end of ninth grade were used. PA was measured using the Three-Day PA Recall, and a questionnaire measured social-cognitive and environmental variables thought to mediate PA. Height and weight were measured, and BMI was calculated. Girls were stratified by race and categorized into three groups, based on BMI percentiles for girls from CDC growth charts: normal (BMI < 85th percentile), at risk (BMI, 85th to 94th percentile), and overweight (BMI ≥ 95th percentile). Girls were further divided into active and low-active groups, based on a vigorous PA standard (average of one or more 30-minute blocks per day per 3-day period). Mixed-model ANOVA was used to compare factors among groups, treating school as a random effect Results None of the social-cognitive or environmental variables differed by weight status for African-American or white girls. Perceived behavioral control and sports team participation were significantly higher in girls who were more active, regardless of weight or race group. In general, social-cognitive variables seem to be more related to activity in white girls, whereas environmental factors seem more related to activity in African-American girls. Discussion PA interventions should be tailored to the unique needs of girls based on PA levels and race, rather than on weight status alone.
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Australian surveys have found that only 43% of women meet the current recommendation for regular moderate physical activity, and that women who are mothers of young children are even less likely to be adequately active for health benefit. These women spend a significant proportion of their day in occupational, household and care-giving activities, which may not be ‘captured’ in conventional physical activity surveys. The purpose of this study was to compare physical activity in young mothers and age-matched controls using three different measures of physical activity. 35 women (16 mothers of young children, M) and 19 age-matched comparison women (NM) completed a survey which asked about walking to and from places, and about moderate and vigorous activity in leisure time and at work (paid and unpaid). They also kept a detailed diary of all their activities for two week-days and two week-end days, and wore a pedometer (Yamax digiwalker) on these days. Each activity in the diary was assigned an energy expenditure (EE) score based on it's intensity (Compendium of Physical Activity) and time spent in that activity. There were no differences between M and NM for pedometer steps (M: 9270 sd 2947; NM: 9768 sd 3051) or for daily energy expenditure (EE) calculated from the diaries (M: 2029 sd 189; NM: 2015 sd 169 METS.mins) or survey (M: 2079 sd 448; NM: 1495 sd 325). There was a significant correlation between pedometer steps and daily METs.mins estimated from the diaries (r = 0.35, p = 0.04); however no relationship was observed between pedometer steps and EE from the survey (r = .09, p = .56). Further analysis of the individual survey items found pedometer steps to be related to EE from walking to and from places (r = .34) and leisure time (r = .31), but not work related activity (r = -.08). There were no significant relationships between EE computed from the diaries and any of the survey questions. The three activity measures indicate that the physical activity levels of the young mothers in our sample were comparable to age-matched non-mothers. The results of the correlation analyses highlight the difficulty of assessing low-intensity work-related physical activity via self-report. Supported by Australian Commonwealth Department of Health and Aged Care.
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As a sequel to a paper that dealt with the analysis of two-way quantitative data in large germplasm collections, this paper presents analytical methods appropriate for two-way data matrices consisting of mixed data types, namely, ordered multicategory and quantitative data types. While various pattern analysis techniques have been identified as suitable for analysis of the mixed data types which occur in germplasm collections, the clustering and ordination methods used often can not deal explicitly with the computational consequences of large data sets (i.e. greater than 5000 accessions) with incomplete information. However, it is shown that the ordination technique of principal component analysis and the mixture maximum likelihood method of clustering can be employed to achieve such analyses. Germplasm evaluation data for 11436 accessions of groundnut (Arachis hypogaea L.) from the International Research Institute of the Semi-Arid Tropics, Andhra Pradesh, India were examined. Data for nine quantitative descriptors measured in the post-rainy season and five ordered multicategory descriptors were used. Pattern analysis results generally indicated that the accessions could be distinguished into four regions along the continuum of growth habit (or plant erectness). Interpretation of accession membership in these regions was found to be consistent with taxonomic information, such as subspecies. Each growth habit region contained accessions from three of the most common groundnut botanical varieties. This implies that within each of the habit types there is the full range of expression for the other descriptors used in the analysis. Using these types of insights, the patterns of variability in germplasm collections can provide scientists with valuable information for their plant improvement programs.
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The Arabidopsis (Arabidopsis thaliana) orthologs of Brca2, a protein whose mutations are involved in breast cancer in humans, were previously shown to be essential at meiosis. In an attempt to better understand the Brca2-interacting properties, we examined four partners of the two isoforms of Brca2 identified in Arabidopsis (AtRad51, AtDmc1, and two AtDss1 isoforms). The two Brca2 and the two Dss1 isoforms are named AtBrca2(IV), AtBrca2(V), AtDss1(I), and AtDss1(V) after their chromosomal localization. We first show that both AtBrca2 proteins can interact with either AtRad51 or AtDmc1 in vitro, and that the N-terminal region of AtBrca2 is responsible for these interactions. More specifically, the BRC motifs (so called because iterated in the Brca2 protein) in Brca2 are involved in these interactions: BRC motif number 2 (BRC2) alone can interact with AtDmc1, whereas BRC motif number 4 (BRC4) recognizes AtRad51. The human Rad51 and Dmc1 proteins themselves can interact with either the complete (HsRad51) or a shorter version of AtBrca2 (HsRad51 or HsDmc1) that comprises all four BRC motifs. We also identified two Arabidopsis isoforms of Dss1, another known partner of Brca2 in other organisms. Although all four Brca2 and Dss1 proteins are much conserved, AtBrca2(IV) interacts with only one of these AtDss1 proteins, whereas AtBrca2(V) interacts with both of them. Finally, we show for the first time that an AtBrca2 protein could bind two different partners at the same time: AtRad51 and AtDss1(I), or AtDmc1 and AtDss1(I).
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With nine examples, we seek to illustrate the utility of the Renormalization Group approach as a unification of other asymptotic and perturbation methods.
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In this paper we examine the combined azimuthal and axial shear of a compressible isotropic elastic circular cylindrical tube of finite extent, otherwise referred to as helical shear (which is an isochoric deformation). The equilibrium equations are formulated in terms of the principal stretches, and explicit necessary and sufficient conditions on the strain-energy function for the material to support this deformation are obtained and compared with those obtained previously for this problem. Several classes of strain-energy functions are derived and in some general cases complete solutions of the equilibrium equations are obtained. Existing results are recovered as special cases and some new results for the strain-energy functions derived are determined and discussed.
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Ferromagnetism in graphene is fascinating, but it is still a big challenge for practical applications due to the weak magnetization. In order to enhance the magnetization, here, we design plasma-enabled graphene nanopetals with ultra-long defective edges of up to 105 m/g, ultra-dense lattice vacancies, and hydrogen chemisorptions. The designed graphene nanopetals display robust ferromagnetism with large saturation magnetization of up to 2 emu/g at 5 K and 1.2 emu/g at room temperatures. This work identifies the plasma-enabled graphene nanopetals as a promising candidate for graphene-based magnetic devices.
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Textured silicon surfaces are widely used in manufacturing of solar cells due to increasing the light absorption probability and also the antireflection properties. However, these Si surfaces have a high density of surface defects that need to be passivated. In this study, the effect of the microscopic surface texture on the plasma surface passivation of solar cells is investigated. The movement of 105 H+ ions in the texture-modified plasma sheath is studied by Monte Carlo numerical simulation. The hydrogen ions are driven by the combined electric field of the plasma sheath and the textured surface. The ion dynamics is simulated, and the relative ion distribution over the textured substrate is presented. This distribution can be used to interpret the quality of the Si dangling bonds saturation and consequently, the direct plasma surface passivation.
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Plasma-based techniques offer many unique possibilities for the synthesis of various nanostructures both on the surface and in the plasma bulk. In contrast to the conventional chemical vapor deposition and some other techniques, plasma-based processes ensure high level of controllability, good quality of the produced nanomaterials, and reduced environmental risk. In this work, the authors briefly review the unique features of the plasma-enhanced chemical vapor deposition approaches, namely, the techniques based on inductively coupled, microwave, and arc discharges. Specifically, the authors consider the plasmas with the ion/electron density ranging from 10^10 to 10^14 cm−3, electron energy in the discharge up to ∼10 eV, and the operating pressure ranging from 1 to 10^4 Pa (up to 105 Pa for the atmospheric-pressure arc discharges). The operating frequencies of the discharges considered range from 460 kHz for the inductively coupled plasmas, and up to 2.45 GHz for the microwave plasmas. The features of the direct-current arc discharges are also examined. The authors also discuss the principles of operation of these systems, as well as the effects of the key plasma parameters on the conditions of nucleation and growth of the carbon nanostructures, mainly carbon nanotubes and graphene. Advantages and disadvantages of these plasma systems are considered. Future trends in the development of these plasma-based systems are also discussed.
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Carbon nanotips have been synthesized from a thin carbon film deposited on silicon by bias-enhanced hot filament chemical vapor deposition under different process parameters. The results of scanning electron microscopy indicate that high-quality carbon nanotips can only be obtained under conditions when the ion flux is effectively drawn from the plasma sustained in a CH4 + NH3 + H2 gas mixture. It is shown that the morphology of the carbon nanotips can be controlled by varying the process parameters such as the applied bias, gas pressure, and the NH3 / H2 mass flow ratios. The nanotip formation process is examined through a model that accounts for surface diffusion, in addition to sputtering and deposition processes included in the existing models. This model makes it possible to explain the major difference in the morphologies of the carbon nanotips formed without and with the aid of the plasma as well as to interpret the changes of their aspect ratio caused by the variation in the ion/gas fluxes. Viable ways to optimize the plasma-based process parameters to synthesize high-quality carbon nanotips are suggested. The results are relevant to the development of advanced plasma-/ion-assisted methods of nanoscale synthesis and processing.
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This paper reports on ab initio numerical simulations of the effect of Co and Cu dopings on the electronic structure and optical properties of ZnO, pursued to develop diluted magnetic semiconductors vitally needed for spintronic applications. The simulations are based upon the Perdew-Burke-Enzerh generalized gradient approximation on the density functional theory. It is revealed that the electrons with energies close to the Fermi level effectively transfer only between Cu and Co ions which substitute Zn atoms, and are located in the neighbor sites connected by an O ion. The simulation results are consistent with the experimental observations that addition of Cu helps achieve stable ferromagnetism of Co-doped ZnO. It is shown that simultaneous insertion of Co and Cu atoms leads to smaller energy band gap, redshift of the optical absorption edge, as well as significant changes in the reflectivity, dielectric function, refractive index, and electron energy loss function of ZnO as compared to the doping with either Co or Cu atoms. These highly unusual optical properties are explained in terms of the computed electronic structure and are promising for the development of the next-generation room-temperature ferromagnetic semiconductors for future spintronic devices on the existing semiconductor micromanufacturing platform.