521 research outputs found

    Binary coalescence from case A evolution -- mergers and blue stragglers

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    We constructed some main-sequence mergers from case A binary evolution and studied their characteristics via Eggleton's stellar evolution code. Both total mass and orbital angular momentum are conservative in our binary evolutions. Some mergers might be on the left of the ZAMS as defined by normal surface composition on a CMD because of enhanced surface helium content. The study also shows that central hydrogen content of the mergers is independent of mass. As a consequence, we fit the formula of magnitude and B-V of the mergers when they return back to thermal equilibrium with maximum error 0.29 and 0.037, respectively. Employing the consequences above, we performed Monte Carlo simulations to examine our models in NGC 2682 and NGC 2660. In NGC 2682, binary mergers from our models cover the region with high luminosity, but its importance is much less than that of AML. Our results are well-matched to the observations of NGC2660 if there is about 0.5Mo of mass loss in the merger process.Comment: 14 pages, 12 figures. accepted by MNRA

    Impact of granulation effects on the use of Balmer lines as temperature indicators

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    Balmer lines serve as important indicators of stellar effective temperatures in late-type stellar spectra. One of their modelling uncertainties is the influence of convective flows on their shape. We aim to characterize the influence of convection on the wings of Balmer lines. We perform a differential comparison of synthetic Balmer line profiles obtained from 3D hydrodynamical model atmospheres and 1D hydrostatic standard ones. The model parameters are appropriate for F,G,K dwarf and subgiant stars of metallicity ranging from solar to 1/1000 solar. The shape of the Balmer lines predicted by 3D models can never be exactly reproduced by a 1D model, irrespective of its effective temperature. We introduce the concept of a 3D temperature correction, as the effective temperature difference between a 3D model and a 1D model which provides the closest match to the 3D profile. The temperature correction is different for the different members of the Balmer series and depends on the adopted mixing-length parameter in the 1D model. Among the investigated models, the 3D correction ranges from -300K to +300K. Horizontal temperature fluctuations tend to reduce the 3D correction. Accurate effective temperatures cannot be derived from the wings of Balmer lines, unless the effects of convection are properly accounted for. The 3D models offer a physically well justified way of doing so. The use of 1D models treating convection with the mixing-length theory do not appear to be suitable for this purpose. In particular, there are indications that it is not possible to determine a single value of the mixing-length parameter which will optimally reproduce the Balmer lines for any choice of atmospheric parameters.Comment: 6 pages, 3 figures, accepted for publication in A&

    Designing a research infrastructure on dietary intake and its determinants

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    Research on dietary intake and its determinants is crucial for an adequate response to the current epidemic of diet-related non-communicable chronic diseases. In order to respond to this challenge, the RICHFIELDS project was tasked with designing a research infrastructure (RI) that connects data on dietary intake of consumers in Europe, and its determinants, collected using apps and wearable sensors, from behavioural laboratories and experimental facilities and from other RIs. The main output of the project, an RI design, describes interfaces (portals) to collect data, a meta-database and a data-model to enable data linkage and sharing. The RICHFIELDS project comprises three phases, each consisting of three work packages, and an overarching methodological support work package. Phase 1 focused on data generated by consumers (e.g. collected by apps and sensors) relating to the purchase, preparation and consumption of food. Phase 2 focused on data generated by organisations such as businesses (e.g. retail data), government (e.g. procurement data) and experimental research facilities (e.g. virtual supermarkets). Phases 1 and 2 provided Phase 3 with insights on data types and design requirements, including the business models, data integration and management systems and governance and ethics. The final design will be used in the coming years to build an RI for the scientific research community, policy makers and businesses in Europe. The RI will boost interdisciplinary multi-stakeholder research through harmonisation and integration of data on food behaviour.</p

    Detailed analysis of Balmer lines in cool dwarf stars

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    An analysis of H alpha and H beta spectra in a sample of 30 cool dwarf and subgiant stars is presented using MARCS model atmospheres based on the most recent calculations of the line opacities. A detailed quantitative comparison of the solar flux spectra with model spectra shows that Balmer line profile shapes, and therefore the temperature structure in the line formation region, are best represented under the mixing length theory by any combination of a low mixing-length parameter alpha and a low convective structure parameter y. A slightly lower effective temperature is obtained for the sun than the accepted value, which we attribute to errors in models and line opacities. The programme stars span temperatures from 4800 to 7100 K and include a small number of population II stars. Effective temperatures have been derived using a quantitative fitting method with a detailed error analysis. Our temperatures find good agreement with those from the Infrared Flux Method (IRFM) near solar metallicity but show differences at low metallicity where the two available IRFM determinations themselves are in disagreement. Comparison with recent temperature determinations using Balmer lines by Fuhrmann (1998, 2000), who employed a different description of the wing absorption due to self-broadening, does not show the large differences predicted by Barklem et al. (2000). In fact, perhaps fortuitously, reasonable agreement is found near solar metallicity, while we find significantly cooler temperatures for low metallicity stars of around solar temperature.Comment: 17 pages, 9 figures, to appear in A&

    Bias in protein and potassium intake collected with 24-h recalls (EPIC-Soft) is rather comparable across European populations

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    Purpose: We investigated whether group-level bias of a 24-h recall estimate of protein and potassium intake, as compared to biomarkers, varied across European centers and whether this was influenced by characteristics of individuals or centers. Methods: The combined data from EFCOVAL and EPIC studies included 14 centers from 9 countries (n = 1,841). Dietary data were collected using a computerized 24-h recall (EPIC-Soft). Nitrogen and potassium in 24-h urine collections were used as reference method. Multilevel linear regression analysis was performed, including individual-level (e.g., BMI) and center-level (e.g., food pattern index) variables. Results: For protein intake, no between-center variation in bias was observed in men while it was 5.7% in women. For potassium intake, the between-center variation in bias was 8.9% in men and null in women. BMI was an important factor influencing the biases across centers (p <0.01 in all analyses). In addition, mode of administration (p = 0.06 in women) and day of the week (p = 0.03 in men and p = 0.06 in women) may have influenced the bias in protein intake across centers. After inclusion of these individual variables, between-center variation in bias in protein intake disappeared for women, whereas for potassium, it increased slightly in men (to 9.5%). Center-level variables did not influence the results. Conclusion: The results suggest that group-level bias in protein and potassium (for women) collected with 24-h recalls does not vary across centers and to a certain extent varies for potassium in men. BMI and study design aspects, rather than center-level characteristics, affected the biases across center

    A gene expression profile for detection of sufficient tumour cells in breast tumour tissue: microarray diagnosis eligibility

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    <p>Abstract</p> <p>Background</p> <p>Microarray diagnostics of tumour samples is based on measurement of prognostic and/or predictive gene expression profiles. Typically, diagnostic profiles have been developed using bulk tumour samples with a sufficient amount of tumour cells (usually >50%). Consequentially, a diagnostic results depends on the minimal percentage of tumour cells within a sample. Currently, tumour cell percentage is assessed by conventional histopathological review. However, even for experienced pathologists, such scoring remains subjective and time consuming and can lead to ambiguous results.</p> <p>Methods</p> <p>In this study we investigated whether we could use transcriptional activity of a specific set of genes instead of histopathological review to identify samples with sufficient tumour cell content. Genome-wide gene expression measurements were used to develop a transcriptional gene profile that could accurately assess a sample's tumour cell percentage.</p> <p>Results</p> <p>Supervised analysis across 165 breast tumour samples resulted in the identification of a set of 13 genes which expression correlated with presence of tumour cells. The developed gene profile showed a high performance (AUC 0.92) for identification of samples that are suitable for microarray diagnostics. Validation on 238 additional breast tumour samples indicated a robust performance for correct classification with an overall accuracy of 91 percent and a kappa score of 0.63 (95%CI 0.47–0.73).</p> <p>Conclusion</p> <p>The developed 13-gene profile provides an objective tool for assessment whether a breast cancer sample contains sufficient tumour cells for microarray diagnostics. It will improve the efficiency and throughput for diagnostic gene expression profiling as it no longer requires histopathological analysis for initial tumour percentage scoring. Such profile will also be very use useful for assessment of tumour cell percentage in biopsies where conventional histopathology is difficult, such as fine needle aspirates.</p

    Nutri-RecQuest: a web-based search engine on current micronutrient recommendations

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    Background: The EURRECA (EURopean micronutrient RECommendations Aligned) Network of Excellence collated current micronutrient recommendations. A user-friendly tool, Nutri-RecQuest, was developed to allow access to the collated data and to create a database source for use in other nutritional software tools. Methods: Recommendations, that is, intakes of micronutrients sufficient to meet the requirements of the majority of healthy individuals of that population, from 37 European countries/organizations and eight key non-European countries/regions comprising 29 micronutrients were entered into a database. General information on the source of the recommendations, as well scientific background information, was added. Results: A user-friendly web-based interface was developed to provide efficient search, comparison, display, print and export functions. Conclusion: Easy access to existing recommendations through the web-based tool may be valuable for bodies responsible for setting recommendations, as well as for users of recommendations including scientists, policy makers, health professionals and industry. Adding related dietary reference values such as average nutrient requirements and upper limits may extend the utility of the tool. European Journal of Clinical Nutrition (2010) 64, S43-S47; doi:10.1038/ejcn.2010.6

    Genomic approaches in the management and treatment of breast cancer

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    Breast cancer is the most common malignancy afflicting women from Western cultures. It has been estimated that approximately 211 000 women will be diagnosed with breast cancer in 2003 in the United States alone, and each year over 40 000 women will die of this disease. Developments in breast cancer molecular and cellular biology research have brought us closer to understanding the genetic basis of this disease. Unfortunately, this information has not yet been incorporated into the routine diagnosis and treatment of breast cancer in the clinic. Recent advancements in microarray technology hold the promise of further increasing our understanding of the complexity and heterogeneity of this disease, and providing new avenues for the prognostication and prediction of breast cancer outcomes. The most recent application of microarray genomic technologies to studying breast cancer will be the focus of this review
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