70 research outputs found

    Reading the book: from "chemical anomalies" to "standard composition" of globular clusters

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    It is now commonly accepted that globular clusters (GCs) have undergone a complex formation and that they host at least two stellar generations. This is a recent paradigm and is founded on both photometric and spectroscopic evidence. We concentrate on results based on high-resolution spectroscopy and on how we moved from single to multiple stellar populations concept for GCs. We underline that the peculiar chemical composition of GC stars is fundamental in establishing the multiple populations scenario and briefly outline what can be learned from observations. Finally, recent observational results on large samples of stars in different evolutionary phases are discussed.Comment: 5 pages, 1 figure. To appear in the proceedings of "Reading the book of globular clusters with the lens of stellar evolution", in the Memorie della Societa Astronomica Italian

    Chemical characterization of the globular cluster NGC 5634 associated to the Sagittarius dwarf spheroidal galaxy

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    As part of our on-going project on the homogeneous chemical characterization of multiple stellar populations in globular clusters (GCs), we studied NGC 5634, associated to the Sagittarius dwarf spheroidal galaxy, using high-resolution spectroscopy of red giant stars collected with FLAMES@VLT. We present here the radial velocity distribution of the 45 observed stars, 43 of which are member, the detailed chemical abundance of 22 species for the seven stars observed with UVES-FLAMES, and the abundance of six elements for stars observed with GIRAFFE. On our homogeneous UVES metallicity scale we derived a low metallicity [Fe/H]=-1.867 +/-0.019 +/-0.065 dex (+/-statistical +/-systematic error) with sigma=0.050 dex (7 stars). We found the normal anti-correlations between light elements (Na and O, Mg and Al), signature of multiple populations typical of massive and old GCs. We confirm the associations of NGC 5634 to the Sgr dSph, from which the cluster was lost a few Gyr ago, on the basis of its velocity and position and the abundance ratios of alpha and neutron capture elements.Comment: 16 pages, 10 figures, 11 tables; accepted for publication on Astronomy and Astrophysic

    LDL-C Concentrations and the 12-SNP LDL-C Score for Polygenic Hypercholesterolaemia in Self-Reported South Asian, Black and Caribbean Participants of the UK Biobank

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    Background: Monogenic familial hypercholesterolaemia (FH) is an autosomal dominant disorder characterised by elevated low-density lipoprotein cholesterol (LDL-C) concentrations due to monogenic mutations in LDLR, APOB, PCSK9, and APOE. Some mutation-negative patients have a polygenic cause for elevated LDL-C due to a burden of common LDL-C-raising alleles, as demonstrated in people of White British (WB) ancestry using a 12-single nucleotide polymorphism (SNP) score. This score has yet to be evaluated in people of South Asian (SA), and Black and Caribbean (BC) ethnicities. Objectives: 1) Compare the LDL-C and 12-SNP score distributions across the three major ethnic groups in the United Kingdom: WB, SA, and BC individuals; 2) compare the association of the 12-SNP score with LDL-C in these groups; 3) evaluate ethnicity-specific and WB 12-SNP score decile cut-off values, applied to SA and BC ethnicities, in predicting LDL-C concentrations and hypercholesterolaemia (LDL-C>4.9 mmol/L). Methods: The United Kingdom Biobank cohort was used to analyse the LDL-C (adjusted for statin use) and 12-SNP score distributions in self-reported WB (n = 353,166), SA (n = 7,016), and BC (n = 7,082) participants. To evaluate WB and ethnicity-specific 12-SNP score deciles, the total dataset was split 50:50 into a training and testing dataset. Regression analyses (logistic and linear) were used to analyse hypercholesterolaemia (LDL-C>4.9 mmol/L) and LDL-C. Findings: The mean (±SD) measured LDL-C differed significantly between the ethnic groups and was highest in WB [3.73 (±0.85) mmol/L], followed by SA [3.57 (±0.86) mmol/L, p < 2.2 × 10−16], and BC [3.42 (±0.90) mmol/L] participants (p < 2.2 × 10−16). There were significant differences in the mean (±SD) 12-SNP score between WB [0.90 (±0.23)] and BC [0.72 (±0.25), p < 2.2 × 10−16], and WB and SA participants [0.86 (±0.19), p < 2.2 × 10−16]. In all three ethnic groups the 12-SNP score was associated with measured LDL-C [R2 (95% CI): WB = 0.067 (0.065–0.069), BC = 0.080 (0.063–0.097), SA = 0.027 (0.016–0.038)]. The odds ratio and the area under the curve for hypercholesterolaemia were not statistically different when applying ethnicity-specific or WB deciles in all ethnic groups. Interpretation: We provide information on the differences in LDL-C and the 12-SNP score distributions in self-reported WB, SA, and BC individuals of the United Kingdom Biobank. We report the association between the 12-SNP score and LDL-C in these ethnic groups. We evaluate the performance of ethnicity-specific and WB 12-SNP score deciles in predicting LDL-C and hypercholesterolaemia

    Potassium in globular cluster stars: comparing normal clusters to the peculiar cluster NGC 2419

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    Two independent studies recently uncovered two distinct populations among giants in the distant, massive globular cluster (GC) NGC 2419. One of these populations has normal magnesium (Mg) and potassium (K) abundances for halo stars: enhanced Mg and roughly solar K. The other population has extremely depleted Mg and very enhanced K. To better anchor the peculiar NGC 2419 chemical composition, we have investigated the behavior of K in a few red giant branch stars in NGC 6752, NGC 6121, NGC 1904, and omega Cen. To verify that the high K abundances are intrinsic and not due to some atmospheric features in giants, we also derived K abundances in less evolved turn-off and subgiant stars of clusters 47 Tuc, NGC 6752, NGC 6397, and NGC 7099. We normalized the K abundance as a function of the cluster metallicity using 21 field stars analyzed in a homogeneous manner. For all GCs of our sample, the stars lie in the K-Mg abundance plane on the same locus occupied by the Mg-normal population in NGC 2419 and by field stars. This holds both for giants and less evolved stars. At present, NGC 2419 seems unique among GCs.Comment: 5 pages, 8 figures, 3 tables, uses emulateapj, accepted for publication on the Astrophysical Journa

    Monomer–dimer dynamics and distribution of GPI-anchored uPAR are determined by cell surface protein assemblies

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    To search for functional links between glycosylphosphatidylinositol (GPI) protein monomer–oligomer exchange and membrane dynamics and confinement, we studied urokinase plasminogen activator (uPA) receptor (uPAR), a GPI receptor involved in the regulation of cell adhesion, migration, and proliferation. Using a functionally active fluorescent protein–uPAR in live cells, we analyzed the effect that extracellular matrix proteins and uPAR ligands have on uPAR dynamics and dimerization at the cell membrane. Vitronectin directs the recruitment of dimers and slows down the diffusion of the receptors at the basal membrane. The commitment to uPA–plasminogen activator inhibitor type 1–mediated endocytosis and recycling modifies uPAR diffusion and induces an exchange between uPAR monomers and dimers. This exchange is fully reversible. The data demonstrate that cell surface protein assemblies are important in regulating the dynamics and localization of uPAR at the cell membrane and the exchange of monomers and dimers. These results also provide a strong rationale for dynamic studies of GPI-anchored molecules in live cells at steady state and in the absence of cross-linker/clustering agents

    Modelling a two-stage adult population screen for autosomal dominant familial hypercholesterolaemia: cross-sectional analysis within the UK Biobank

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    Background: Most people with autosomal dominant familial hypercholesterolaemia (FH) remain undetected, which represents a missed opportunity for coronary heart disease prevention. Objective: To evaluate the performance of two-stage adult population screening for FH. Design: Using data from UK Biobank, we estimated the screening performance of different low-density lipoprotein cholesterol (LDL-C) cut-offs (stage 1) to select adults for DNA sequencing (stage 2) to identify individuals with FH-causing variants inLDLR, APOB, PCSK9andAPOE. We estimated the number of additional FH cases detected by cascade testing of first-degree relatives of index cases and compared the overall approach with screening in childhood. Setting: UK Biobank. Participants: 140 439 unrelated participants of European ancestry from UK Biobank with information on circulating LDL-C concentration and exome sequence. Main outcome measures: For different LDL-C cut-offs, we estimated the detection and false-positive rate, the proportion of individuals who would be referred for DNA sequencing (stage 1 screen positive rate), and the number of FH cases identified by population screening followed by cascade testing. Results: We identified 488 individuals with an FH-causing variant and 139 951 without (prevalence 1 in 288). An LDL-C cut-off of &gt;4.8 mmol/L had a stage 1 detection rate (sensitivity) of 40% (95% CI 36 to 44%) for a false-positive rate of 10% (95% CI 10 to 11%). Detection rate increased at lower LDL-C cut-offs but at the expense of higher false-positive and screen positive rates, and vice versa. Two-stage screening of 100 000 adults using an LDL-C cut-off of 4.8 mmol/L would generate 10 398 stage 1 screen positives for sequencing, detect 138 FH cases and miss 209. Up to 207 additional cases could be detected throughtwo-generationcascade testing of first-degree relatives. By comparison, based on previously published data, childhood screening followed by cascade testing was estimated to detect nearly three times as many affected individuals for around half the sequencing burden. Conclusions: Two-stage adult population screening for FH could help achieve the 25% FH case detection target set in the National Health Service Long Term Plan, but less efficiently than childhood screening and with a greater sequencing requirement

    Forecasting neutrino masses from galaxy clustering in the Dark Energy Survey combined with the Planck Measurements

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    We study the prospects for detecting neutrino masses from the galaxy angular power spectrum in photometric redshift shells of the Dark Energy Survey (DES) over a volume of 20 (Gpc/h)^3 combined with the Cosmic Microwave Background (CMB) angular fluctuations expected to be measured from the Planck satellite. We find that for a Lambda-CDM concordance model with 7 free parameters in addition to a fiducial neutrino mass of M_nu = 0.24 eV, we recover from DES &Planck the correct value with uncertainty of +- 0.12 eV (95 % CL), assuming perfect knowledge of the galaxy biasing. If the fiducial total mass is close to zero, then the upper limit is 0.11 eV (95 % CL). This upper limit from DES &Planck is over 3 times tighter than using Planck alone, as DES breaks the parameter degeneracies in a CMB-only analysis. The analysis utlilizes spherical harmonics up to 300, averaged in bin of 10 to mimic the DES sky coverage. The results are similar if we supplement DES bands (grizY) with the VISTA Hemisphere Survey (VHS) near infrared band (JHK). The result is robust to uncertainties in non-linear fluctuations and redshift distortions. However, the result is sensitive to the assumed galaxy biasing schemes and it requires accurate prior knowledge of the biasing. To summarize, if the total neutrino mass in nature greater than 0.1eV, we should be able to detect it with DES &Planck, a result with great importance to fundamental Physics.Comment: Submitted to MNRAS, 9 pages, 10 figure

    Performance of polygenic risk scores in screening, prediction, and risk stratification: secondary analysis of data in the Polygenic Score Catalog

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    OBJECTIVE: To clarify the performance of polygenic risk scores in population screening, individual risk prediction, and population risk stratification. DESIGN: Secondary analysis of data in the Polygenic Score Catalog. SETTING: Polygenic Score Catalog, April 2022. Secondary analysis of 3915 performance metric estimates for 926 polygenic risk scores for 310 diseases to generate estimates of performance in population screening, individual risk, and population risk stratification. PARTICIPANTS: Individuals contributing to the published studies in the Polygenic Score Catalog. MAIN OUTCOME MEASURES: Detection rate for a 5% false positive rate (DR5) and the population odds of becoming affected given a positive result; individual odds of becoming affected for a person with a particular polygenic score; and odds of becoming affected for groups of individuals in different portions of a polygenic risk score distribution. Coronary artery disease and breast cancer were used as illustrative examples. RESULTS: For performance in population screening, median DR5 for all polygenic risk scores and all diseases studied was 11% (interquartile range 8-18%). Median DR5 was 12% (9-19%) for polygenic risk scores for coronary artery disease and 10% (9-12%) for breast cancer. The population odds of becoming affected given a positive results were 1:8 for coronary artery disease and 1:21 for breast cancer, with background 10 year odds of 1:19 and 1:41, respectively, which are typical for these diseases at age 50. For individual risk prediction, the corresponding 10 year odds of becoming affected for individuals aged 50 with a polygenic risk score at the 2.5th, 25th, 75th, and 97.5th centiles were 1:54, 1:29, 1:15, and 1:8 for coronary artery disease and 1:91, 1:56, 1:34, and 1:21 for breast cancer. In terms of population risk stratification, at age 50, the risk of coronary artery disease was divided into five groups, with 10 year odds of 1:41 and 1:11 for the lowest and highest quintile groups, respectively. The 10 year odds was 1:7 for the upper 2.5% of the polygenic risk score distribution for coronary artery disease, a group that contributed 7% of cases. The corresponding estimates for breast cancer were 1:72 and 1:26 for the lowest and highest quintile groups, and 1:19 for the upper 2.5% of the distribution, which contributed 6% of cases. CONCLUSION: Polygenic risk scores performed poorly in population screening, individual risk prediction, and population risk stratification. Strong claims about the effect of polygenic risk scores on healthcare seem to be disproportionate to their performance
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