109 resultados para 560.9
Resumo:
We show that the X-ray line flux of the Mn Kα line at 5.9 keV from the decay of 55Fe is a promising diagnostic to distinguish between Type Ia supernova (SN Ia) explosion models. Using radiation transport calculations, we compute the line flux for two three-dimensional explosion models: a near-Chandrasekhar mass delayed detonation and a violent merger of two (1.1 and 0.9 M⊙) white dwarfs. Both models are based on solar metallicity zero-age main-sequence progenitors. Due to explosive nuclear burning at higher density, the delayed-detonation model synthesizes ˜3.5 times more radioactive 55Fe than the merger model. As a result, we find that the peak Mn Kα line flux of the delayed-detonation model exceeds that of the merger model by a factor of ˜4.5. Since in both models the 5.9-keV X-ray flux peaks five to six years after the explosion, a single measurement of the X-ray line emission at this time can place a constraint on the explosion physics that is complementary to those derived from earlier phase optical spectra or light curves. We perform detector simulations of current and future X-ray telescopes to investigate the possibilities of detecting the X-ray line at 5.9 keV. Of the currently existing telescopes, XMM-Newton/pn is the best instrument for close (≲1-2 Mpc), non-background limited SNe Ia because of its large effective area. Due to its low instrumental background, Chandra/ACIS is currently the best choice for SNe Ia at distances above ˜2 Mpc. For the delayed-detonation scenario, a line detection is feasible with Chandra up to ˜3 Mpc for an exposure time of 106 s. We find that it should be possible with currently existing X-ray instruments (with exposure times ≲5 × 105 s) to detect both of our models at sufficiently high S/N to distinguish between them for hypothetical events within the Local Group. The prospects for detection will be better with future missions. For example, the proposed Athena/X-IFU instrument could detect our delayed-detonation model out to a distance of ˜5 Mpc. This would make it possible to study future events occurring during its operational life at distances comparable to those of the recent supernovae SN 2011fe (˜6.4 Mpc) and SN 2014J (˜3.5 Mpc).
Resumo:
Context. The ESA Rosetta spacecraft, currently orbiting around comet 67P/Churyumov-Gerasimenko, has already provided in situ measurements of the dust grain properties from several instruments,particularly OSIRIS and GIADA. We propose adding value to those measurements by combining them with ground-based observations of the dust tail to monitor the overall, time-dependent dust-production rate and size distribution.
Aims. To constrain the dust grain properties, we take Rosetta OSIRIS and GIADA results into account, and combine OSIRIS data during the approach phase (from late April to early June 2014) with a large data set of ground-based images that were acquired with the ESO Very Large Telescope (VLT) from February to November 2014.
Methods. A Monte Carlo dust tail code, which has already been used to characterise the dust environments of several comets and active asteroids, has been applied to retrieve the dust parameters. Key properties of the grains (density, velocity, and size distribution) were obtained from Rosetta observations: these parameters were used as input of the code to considerably reduce the number of free parameters. In this way, the overall dust mass-loss rate and its dependence on the heliocentric distance could be obtained accurately.
Results. The dust parameters derived from the inner coma measurements by OSIRIS and GIADA and from distant imaging using VLT data are consistent, except for the power index of the size-distribution function, which is α = −3, instead of α = −2, for grains smaller than 1 mm. This is possibly linked to the presence of fluffy aggregates in the coma. The onset of cometary activity occurs at approximately 4.3 AU, with a dust production rate of 0.5 kg/s, increasing up to 15 kg/s at 2.9 AU. This implies a dust-to-gas mass ratio varying between 3.8 and 6.5 for the best-fit model when combined with water-production rates from the MIRO experiment.
Resumo:
BACKGROUND: Glucagon-like peptide-1 (GLP-1) therapies are routinely used for glycaemic control in diabetes and their emerging cardiovascular actions have been a major recent research focus. In addition to GLP-1 receptor activation, the metabolically-inactive breakdown product, GLP-1(9-36)amide, also appears to exert notable cardiovascular effects, including protection against acute cardiac ischaemia. Here, we specifically studied the influence of GLP-1(9-36)amide on chronic post-myocardial infarction (MI) remodelling, which is a major driver of heart failure progression.
METHODS: Adult female C57BL/6 J mice were subjected to permanent coronary artery ligation or sham surgery prior to continuous infusion with GLP-1(9-36)amide or vehicle control for 4 weeks.
RESULTS: Infarct size was similar between groups with no effect of GLP-1(9-36)amide on MI-induced cardiac hypertrophy, although modest reduction of in vitro phenylephrine-induced H9c2 cardiomyoblast hypertrophy was observed. Whilst echocardiographic systolic dysfunction post-MI remained unchanged, diastolic dysfunction (decreased mitral valve E/A ratio, increased E wave deceleration rate) was improved by GLP-1(9-36)amide treatment. This was associated with modulation of genes related to extracellular matrix turnover (MMP-2, MMP-9, TIMP-2), although interstitial fibrosis and pro-fibrotic gene expression were unaltered by GLP-1(9-36)amide. Cardiac macrophage infiltration was also reduced by GLP-1(9-36)amide together with pro-inflammatory cytokine expression (IL-1β, IL-6, MCP-1), whilst in vitro studies using RAW264.7 macrophages revealed global potentiation of basal pro-inflammatory and tissue protective cytokines (e.g. IL-1β, TNF-α, IL-10, Fizz1) in the presence of GLP-1(9-36)amide versus exendin-4.
CONCLUSIONS: These data suggest that GLP-1(9-36)amide confers selective protection against post-MI remodelling via preferential preservation of diastolic function, most likely due to modulation of infiltrating macrophages, indicating that this often overlooked GLP-1 breakdown product may exert significant actions in this setting which should be considered in the context of GLP-1 therapy in patients with cardiovascular disease.
Resumo:
OBJECTIVE: To develop a model of the psychological factors which predict people's intention to adopt personalised nutrition. Potential determinants of adoption included perceived risk and benefit, perceived self-efficacy, internal locus of control and health commitment.
METHODS: A questionnaire, developed from exploratory study data and the existing theoretical literature, and including validated psychological scales was administered to N=9381 participants from 9 European countries (Germany, Greece, Ireland, Poland, Portugal, Spain, the Netherlands, the UK, and Norway).
RESULTS: Structural equation modelling indicated that the greater participants' perceived benefits to be associated with personalised nutrition, the more positive their attitudes were towards personalised nutrition, and the greater their intention to adopt it. Higher levels of nutrition self-efficacy were related to more positive attitudes towards, and a greater expressed intention to adopt, personalised nutrition. Other constructs positively impacting attitudes towards personalised nutrition included more positive perceptions of the efficacy of regulatory control to protect consumers (e.g. in relation to personal data protection), higher self-reported internal health locus of control, and health commitment. Although higher perceived risk had a negative relationship with attitude and an inverse relationship with perceived benefit, its effects on attitude and intention to adopt personalised nutrition was less influential than perceived benefit. The model was stable across the different European countries, suggesting that psychological factors determining adoption of personalised nutrition have generic applicability across different European countries.
CONCLUSION: The results suggest that transparent provision of information about potential benefits, and protection of consumers' personal data is important for adoption, delivery of public health benefits, and commercialisation of personalised nutrition.