Forest ecosystems store approximately 45% of the carbon found in terrestrial ecosystems, but they are sensitive to climate-induced dieback. Forest die-off constitutes a large uncertainty in ...projections of climate impacts on terrestrial ecosystems, climate–ecosystem interactions, and carbon-cycle feedbacks. Current understanding of the physiological mechanisms mediating climate-induced forest mortality limits the ability to model or project these threshold events. We report here a direct and in situ study of the mechanisms underlying recent widespread and climate-induced trembling aspen (Populus tremuloides) forest mortality in western North America. We find substantial evidence of hydraulic failure of roots and branches linked to landscape patterns of canopy and root mortality in this species. On the contrary, we find no evidence that drought stress led to depletion of carbohydrate reserves. Our results illuminate proximate mechanisms underpinning recent aspen forest mortality and provide guidance for understanding and projecting forest die-offs under climate change.
Using the Murchison Widefield Array (MWA), the low-frequency Square Kilometre Array precursor located in Western Australia, we have completed the GaLactic and Extragalactic All-sky MWA (GLEAM) ...survey, and present the resulting extragalactic catalogue, utilizing the first year of observations. The catalogue covers 24 831 square degrees, over declinations south of +30... and Galactic latitudes outside 10... of the Galactic plane, excluding some areas such as the Magellanic Clouds. It contains 307 455 radio sources with 20 separate flux density measurements across 72-231 MHz, selected from a time- and frequency-integrated image centred at 200 MHz, with a resolution of ...2 arcmin. Over the catalogued region, we estimate that the catalogue is 90 per cent complete at 170 mJy, and 50 per cent complete at 55 mJy, and large areas are complete at even lower flux density levels. Its reliability is 99.97 per cent above the detection threshold of 5..., which itself is typically 50 mJy. These observations constitute the widest fractional bandwidth and largest sky area survey at radio frequencies to date, and calibrate the low-frequency flux density scale of the southern sky to better than 10 per cent. This paper presents details of the flagging, imaging, mosaicking and source extraction/characterization, as well as estimates of the completeness and reliability. All source measurements and images are available online. This is the first in a series of publications describing the GLEAM survey results. (ProQuest: ... denotes formulae/symbols omitted.)
VIRAC: the VVV Infrared Astrometric Catalogue Smith, L. C; Lucas, P. W; Kurtev, R ...
Monthly Notices of the Royal Astronomical Society,
02/2018, Letnik:
474, Številka:
2
Journal Article
Recenzirano
Odprti dostop
Abstract
We present VIRAC version 1, a near-infrared proper motion and parallax catalogue of the VISTA Variables in the Via Lactea (VVV) survey for 312 587 642 unique sources averaged across all ...overlapping pawprint and tile images covering 560 deg2 of the bulge of the Milky Way and southern disc. The catalogue includes 119 million high-quality proper motion measurements, of which 47 million have statistical uncertainties below 1 mas yr−1. In the 11 < Ks < 14 magnitude range, the high-quality motions have a median uncertainty of 0.67 mas yr−1. The catalogue also includes 6935 sources with quality-controlled 5σ parallaxes with a median uncertainty of 1.1 mas. The parallaxes show reasonable agreement with the Tycho-Gaia Astrometric Solution, though caution is advised for data with modest significance. The SQL data base housing the data is made available via the web. We give example applications for studies of Galactic structure, nearby objects (low-mass stars and brown dwarfs, subdwarfs, white dwarfs) and kinematic distance measurements of young stellar objects. Nearby objects discovered include LTT 7251 B, an L7 benchmark companion to a G dwarf with over 20 published elemental abundances, a bright L subdwarf, VVV 1256−6202, with extremely blue colours and nine new members of the 25 pc sample. We also demonstrate why this catalogue remains useful in the era of Gaia. Future versions will be based on profile fitting photometry, use the Gaia absolute reference frame and incorporate the longer time baseline of the VVV extended survey.
The diagnosis of autism spectrum disorder (ASD) at the earliest age possible is important for initiating optimally effective intervention. In the United States the average age of diagnosis is 4 ...years. Identifying metabolic biomarker signatures of ASD from blood samples offers an opportunity for development of diagnostic tests for detection of ASD at an early age.
To discover metabolic features present in plasma samples that can discriminate children with ASD from typically developing (TD) children. The ultimate goal is to identify and develop blood-based ASD biomarkers that can be validated in larger clinical trials and deployed to guide individualized therapy and treatment.
Blood plasma was obtained from children aged 4 to 6, 52 with ASD and 30 age-matched TD children. Samples were analyzed using 5 mass spectrometry-based methods designed to orthogonally measure a broad range of metabolites. Univariate, multivariate and machine learning methods were used to develop models to rank the importance of features that could distinguish ASD from TD.
A set of 179 statistically significant features resulting from univariate analysis were used for multivariate modeling. Subsets of these features properly classified the ASD and TD samples in the 61-sample training set with average accuracies of 84% and 86%, and with a maximum accuracy of 81% in an independent 21-sample validation set.
This analysis of blood plasma metabolites resulted in the discovery of biomarkers that may be valuable in the diagnosis of young children with ASD. The results will form the basis for additional discovery and validation research for 1) determining biomarkers to develop diagnostic tests to detect ASD earlier and improve patient outcomes, 2) gaining new insight into the biochemical mechanisms of various subtypes of ASD 3) identifying biomolecular targets for new modes of therapy, and 4) providing the basis for individualized treatment recommendations.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
We investigate the inner regions of the Milky Way using data from APOGEE and
Gaia
EDR3. Our inner Galactic sample has more than 26 500 stars within |
X
Gal
|< 5 kpc, |
Y
Gal
|< 3.5 kpc, |
Z
Gal
|< 1 ...kpc, and we also carry out the analysis for a foreground-cleaned subsample of 8000 stars that is more representative of the bulge–bar populations. These samples allow us to build chemo-dynamical maps of the stellar populations with vastly improved detail. The inner Galaxy shows an apparent chemical bimodality in key abundance ratios
α
/Fe, C/N, and Mn/O, which probe different enrichment timescales, suggesting a star formation gap (quenching) between the high- and low-
α
populations. Using a joint analysis of the distributions of kinematics, metallicities, mean orbital radius, and chemical abundances, we can characterize the different populations coexisting in the innermost regions of the Galaxy for the first time. The chemo-kinematic data dissected on an eccentricity–|
Z
|
max
plane reveal the chemical and kinematic signatures of the bar, the thin inner disc, and an inner thick disc, and a broad metallicity population with large velocity dispersion indicative of a pressure-supported component. The interplay between these different populations is mapped onto the different metallicity distributions seen in the eccentricity–|
Z
|
max
diagram consistently with the mean orbital radius and
V
ϕ
distributions. A clear metallicity gradient as a function of |
Z
|
max
is also found, which is consistent with the spatial overlapping of different populations. Additionally, we find and chemically and kinematically characterize a group of counter-rotating stars that could be the result of a gas-rich merger event or just the result of clumpy star formation during the earliest phases of the early disc that migrated into the bulge. Finally, based on 6D information, we assign stars a probability value of being on a bar orbit and find that most of the stars with large bar orbit probabilities come from the innermost 3 kpc, with a broad dispersion of metallicity. Even stars with a high probability of belonging to the bar show chemical bimodality in the
α
/Fe versus Fe/H diagram. This suggests bar trapping to be an efficient mechanism, explaining why stars on bar orbits do not show a significant, distinct chemical abundance ratio signature.
Abstract
Formed in late 1999, the Rat Genome Database (RGD, https://rgd.mcw.edu) will be 20 in 2020, the Year of the Rat. Because the laboratory rat, Rattus norvegicus, has been used as a model for ...complex human diseases such as cardiovascular disease, diabetes, cancer, neurological disorders and arthritis, among others, for >150 years, RGD has always been disease-focused and committed to providing data and tools for researchers doing comparative genomics and translational studies. At its inception, before the sequencing of the rat genome, RGD started with only a few data types localized on genetic and radiation hybrid (RH) maps and offered only a few tools for querying and consolidating that data. Since that time, RGD has expanded to include a wealth of structured and standardized genetic, genomic, phenotypic, and disease-related data for eight species, and a suite of innovative tools for querying, analyzing and visualizing this data. This article provides an overview of recent substantial additions and improvements to RGD’s data and tools that can assist researchers in finding and utilizing the data they need, whether their goal is to develop new precision models of disease or to more fully explore emerging details within a system or across multiple systems.
Dealing with confounds is an essential step in large cohort studies to address problems such as unexplained variance and spurious correlations. UK Biobank is a powerful resource for studying ...associations between imaging and non-imaging measures such as lifestyle factors and health outcomes, in part because of the large subject numbers. However, the resulting high statistical power also raises the sensitivity to confound effects, which therefore have to be carefully considered. In this work we describe a set of possible confounds (including non-linear effects and interactions that researchers may wish to consider for their studies using such data). We include descriptions of how we can estimate the confounds, and study the extent to which each of these confounds affects the data, and the spurious correlations that may arise if they are not controlled. Finally, we discuss several issues that future studies should consider when dealing with confounds.
APOGEE-2 is a high-resolution, near-infrared spectroscopic survey observing ∼3 × 105 stars across the entire sky. It is the successor to APOGEE and is part of the Sloan Digital Sky Survey IV ...(SDSS-IV). APOGEE-2 is expanding on APOGEE's goals of addressing critical questions of stellar astrophysics, stellar populations, and Galactic chemodynamical evolution using (1) an enhanced set of target types and (2) a second spectrograph at Las Campanas Observatory in Chile. APOGEE-2 is targeting red giant branch and red clump stars, RR Lyrae, low-mass dwarf stars, young stellar objects, and numerous other Milky Way and Local Group sources across the entire sky from both hemispheres. In this paper, we describe the APOGEE-2 observational design, target selection catalogs and algorithms, and the targeting-related documentation included in the SDSS data releases.
UK Biobank is a large-scale prospective epidemiological study with all data accessible to researchers worldwide. It is currently in the process of bringing back 100,000 of the original participants ...for brain, heart and body MRI, carotid ultrasound and low-dose bone/fat x-ray. The brain imaging component covers 6 modalities (T1, T2 FLAIR, susceptibility weighted MRI, Resting fMRI, Task fMRI and Diffusion MRI). Raw and processed data from the first 10,000 imaged subjects has recently been released for general research access. To help convert this data into useful summary information we have developed an automated processing and QC (Quality Control) pipeline that is available for use by other researchers. In this paper we describe the pipeline in detail, following a brief overview of UK Biobank brain imaging and the acquisition protocol. We also describe several quantitative investigations carried out as part of the development of both the imaging protocol and the processing pipeline.
Invasive methods requiring general anaesthesia are needed to sample the lung microbiota in young children who do not expectorate. This poses substantial challenges to longitudinal study of paediatric ...airway microbiota. Non-invasive upper airway sampling is an alternative method for monitoring airway microbiota; however, there are limited data describing the relationship of such results with lung microbiota in young children. In this study, we compared the upper and lower airway microbiota in young children to determine whether non-invasive upper airway sampling procedures provide a reliable measure of either lung microbiota or clinically defined differences.
The microbiota in oropharyngeal (OP) swabs, nasopharyngeal (NP) swabs and bronchoalveolar lavage (BAL) from 78 children (median age 2.2 years) with and without lung disease were characterised using 16S rRNA gene sequencing. Permutational multivariate analysis of variance (PERMANOVA) detected significant differences between the microbiota in BAL and those in both OP swabs (p = 0.0001, Pseudo-F = 12.2, df = 1) and NP swabs (p = 0.0001; Pseudo-F = 21.9, df = 1) with the NP and BAL microbiota more different than the OP and BAL, as indicated by a higher Pseudo-F value. The microbiota in combined OP and NP data (upper airways) provided a more comprehensive representation of BAL microbiota, but significant differences between the upper airway and BAL microbiota remained, albeit with a considerably smaller Pseudo-F (PERMANOVA p = 0.0001; Pseudo-F = 4.9, df = 1). Despite this overall difference, paired BAL and upper airway (OP and NP) microbiota were >50 % similar among 69 % of children. Furthermore, canonical analysis of principal coordinates (CAP analysis) detected significant differences between the microbiota from clinically defined groups when analysing either BAL (eigenvalues >0.8; misclassification rate 26.5 %) or the combined OP and NP data (eigenvalues >0.8; misclassification rate 12.2 %).
Upper airway sampling provided an imperfect, but reliable, representation of the BAL microbiota for most children in this study. We recommend inclusion of both OP and NP specimens when non-invasive upper airway sampling is needed to assess airway microbiota in young children who do not expectorate. The results of the CAP analysis suggest lower and upper airway microbiota profiles may differentiate children with chronic suppurative lung disease from those with persistent bacterial bronchitis; however, further research is needed to confirm this observation.
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