The Pristine survey II: a sample of bright stars observed with FEROS

Extremely metal-poor (EMP) stars are old objects formed in the first Gyr of the Universe. They are rare and, to select them, the most successful strategy has been to build on large and low-resolution spectroscopic surveys. The combination of narrow- and broad band photometry provides a powerful and cheaper alternative to select metal-poor stars. The on-going Pristine Survey is adopting this strategy, conducting photometry with the CFHT MegaCam wide field imager and a narrow-band filter centred at 395.2 nm on the CaII-H and -K lines. In this paper we present the results of the spectroscopic follow-up conducted on a sample of 26 stars at the bright end of the magnitude range of the Survey (g<=15), using FEROS at the MPG/ESO 2.2 m telescope. From our chemical investigation on the sample, we conclude that this magnitude range is too bright to use the SDSS gri bands, which are typically saturated. Instead the Pristine photometry can be usefully combined with the APASS gri photometry to provide reliable metallicity estimates.Comment: AN accepte

Incidence of variations in human cadaveric renal vessels

Background: Awareness of discrepancies of renal vasculature is crucial for some medical procedures. The present study investigated origin and course of aberrant and accessory renal vessels and any associated variations. Materials and methods: Renal blood vessels of 63 cadavers were examined. Number of renal veins and arteries, arrangement, location where the vasculature attached to the kidneys, and presence of variations were recorded. Incidence of renal vasculature variations was determined, and associations were tested with age at death, sex, and cause of death and whether variations were more common on a specific side. Results: Variations were found in 7 (11%; 95% confidence interval [CI] 5–22%) cadavers. For renal veins, double, triple, and quadruple veins unilaterally (5; 8%) and veins that drained the superior pole (1; 2%) or inferior pole only (5; 8%) were found. For renal arteries, double and triple arteries unilaterally (3; 5%) and arteries attached to the superior pole only (1; 2%) or inferior pole only (2; 3%) were found. Other variations (polycystic kidney, variations in the common iliac or gonadal veins) were observed. Only renal failure as a cause of death was different between those with or without variations (4/7 [57%] vs. 1/56 [2%]; p &lt; 0.001). Conclusions: The present study found many variations in renal vasculature. Awareness of such variations may be useful for physicians concerned with this region

Therapeutic role of bone marrow mesenchymal stem cells in diabetic neuronal alternations of rat hippocampus

Background: As the hippocampus is the main brain region for many forms of learning and memory functions and is acutely sensitive to blood glucose changes, diabetes mellitus, which is a serious metabolic disease, is often accompanied by learning and memory deficits. Through scientific literatures, mesenchymal stem cells (MSCs) promote functional recovery in rats with traumatic brain injury, so the present work was conducted to study MSCs as a possible treatment for the diabetic neuronal degeneration and functional impairment of rat hippocampus. Materials and methods: It was carried out using male albino rats: non-diabetic control groups (4, 8, 12 weeks) (n = 15), diabetic groups by i.v. injection of streptozotocin for (4, 8, 12 weeks) (n = 15) and MSCs treatment to diabetic groups for (8, 12 weeks) (n = 10). Hippocampal learning and memory functions were assessed by the Morris Water Maze test and its results were statistically analysed. The rat hippocampal regions (CA1 and CA3) were subjected to histological, ultrastructural examination and morphometrical analyse of pyramidal neurons. Results: Neurons of the diabetic groups showed disturbed function and architecture; shrunken hyperchromatic nuclei and vacuolated eosinophilic cytoplasm (apoptotic changes) also MSCs treatment improved hippocampal learning and memory functions plus its architectural changes; increasing populations and normal regular distribution. Conclusions: It can be concluded that diabetic hippocampal neuronal alternations and functional impairment can be ameliorated by MSCs treatment

Titanium abundances in late-type stars I. 1D non-LTE modelling in benchmark dwarfs and giants

The titanium abundances of late-type stars are important tracers of Galactic formation history. However, abundances inferred from Ti I and Ti II lines can be in stark disagreement in very metal-poor giants. Departures from local thermodynamic equilibrium (LTE) have a large impact on the minority neutral species and thus influences the ionisation imbalance, but satisfactory non-LTE modelling for both dwarfs and giants has not been achieved in previous literature. The reliability of titanium abundances is reassessed in benchmark dwarfs and giants using a new non-LTE model and one-dimensional (1D) model atmospheres. A comprehensive model atom was compiled with a more extended level structure and newly published data for inelastic collisions between Ti I and neutral hydrogen. In 1D LTE, the Ti I and Ti II lines agree to within $0.06$ dex for the Sun, Arcturus, and the very metal-poor stars HD84937 and HD140283. For the very metal-poor giant HD122563, the Ti I lines give an abundance that is $0.47$ dex lower than that from Ti II. The 1D non-LTE corrections can reach $+0.4$ dex for individual Ti I lines and $+0.1$ dex for individual Ti II lines, and reduce the overall ionisation imbalance to $-0.17$ dex for HD122563. However, it also increases the imbalance for the very metal-poor dwarf and sub-giant to around $0.2$ dex. Using 1D non-LTE reduces the ionisation imbalance in very metal-poor giants but breaks the balance of other very metal-poor stars, consistent with the conclusions in earlier literature. To make further progress, consistent 3D non-LTE models are needed.Comment: 9 pages plus appendix, 6 figures; accepted for publication in Astronomy & Astrophysic

Hypervelocity star candidates in Gaia DR1/TGAS

Galaxie

Beyond Gaia DR3: tracing the [{\alpha}/M]-[M/H] bimodality from the inner to the outer Milky Way disc with Gaia RVS and Convolutional Neural-Networks

Gaia DR3 has provided the community with about one million RVS spectra covering the CaII triplet region. In the next Gaia data releases, we anticipate the number of RVS spectra to successively increase from several 10 million spectra to eventually more than 200M spectra. Thus, stellar spectra are produced on an "industrial scale" with numbers well above those for current and anticipated ground based surveys. However, many of these spectra have low S/N (from 15 to 25 per pixel), such that they pose problems for classical spectral analysis pipelines and therefore alternative ways to tap into these large datasets need to be devised. We aim to leverage the versatility/capabilities of machine learning techniques for supercharged stellar parametrization, by combining Gaia RVS spectra with the full set of Gaia products and high-resolution, high-quality spectroscopic reference data sets. We develop a hybrid Convolutional Neural-Network (CNN) which combines the Gaia DR3 RVS spectra, photometry (G, Bp, Rp), parallaxes, and XP coefficients to derive atmospheric parameters (Teff, log(g), and overall [M/H]) and chemical abundances ([Fe/H] and [$\alpha$/M]). We trained the CNN with a high-quality training sample based on APOGEE DR17 labels. With this CNN, we derived homogeneous atmospheric parameters and abundances for 841300 stars, that remarkably compared to external data-sets. The CNN is robust against noise in the RVS data, and very precise labels are derived down to S/N=15. We managed to characterize the [$\alpha$/M]-[M/H] bimodality from the inner regions to the outer parts of the Milky Way, which has never been done using RVS spectra or similar datasets. This work is the first to combine machine-learning with such diverse datasets (spectroscopy, astrometry, and photometry), and paves the way for the large scale machine-learning analysis of Gaia-RVS spectra from future data releases.Comment: 24 pages, 24 figures, submitted to A&

Using the multi-object adaptive optics demonstrator RAVEN to observe metal-poor stars in and towards the Galactic Centre

The chemical abundances for five metal-poor stars in and towards the Galactic bulge have been determined from the H-band infrared spectroscopy taken with the RAVEN multi-object adaptive optics science demonstrator and the Infrared Camera and Spectrograph at the Subaru 8.2-m telescope. Three of these stars are in the Galactic bulge and have metallicities between −2.1 < [Fe/H] < −1.5, and high [α/Fe] ∼ +0.3, typical of Galactic disc and bulge stars in this metallicity range; [Al/Fe] and [N/Fe] are also high, whereas [C/Fe] < +0.3. An examination of their orbits suggests that two of these stars may be confined to the Galactic bulge and one is a halo trespasser, though proper motion values used to calculate orbits are quite uncertain. An additional two stars in the globular cluster M22 show [Fe/H] values consistent to within 1σ, although one of these two stars has [Fe/H] = −2.01 ± 0.09, which is on the low end for this cluster. The [α/Fe] and [Ni/Fe] values differ by 2σ, with the most metal-poor star showing significantly higher values for these elements. M22 is known to show element abundance variations, consistent with a multipopulation scenario though our results cannot discriminate this clearly given our abundance uncertainties. This is the first science demonstration of multi-object adaptive optics with high-resolution infrared spectroscopy, and we also discuss the feasibility of this technique for use in the upcoming era of 30-m class telescope facilities