1,588 research outputs found

    Effects of sex chromosome dosage on corpus callosum morphology in supernumerary sex chromosome aneuploidies.

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    BackgroundSupernumerary sex chromosome aneuploidies (sSCA) are characterized by the presence of one or more additional sex chromosomes in an individual's karyotype; they affect around 1 in 400 individuals. Although there is high variability, each sSCA subtype has a characteristic set of cognitive and physical phenotypes. Here, we investigated the differences in the morphometry of the human corpus callosum (CC) between sex-matched controls 46,XY (N =99), 46,XX (N =93), and six unique sSCA karyotypes: 47,XYY (N =29), 47,XXY (N =58), 48,XXYY (N =20), 47,XXX (N =30), 48,XXXY (N =5), and 49,XXXXY (N =6).MethodsWe investigated CC morphometry using local and global area, local curvature of the CC boundary, and between-landmark distance analysis (BLDA). We hypothesized that CC morphometry would vary differentially along a proposed spectrum of Y:X chromosome ratio with supernumerary Y karyotypes having the largest CC areas and supernumerary X karyotypes having significantly smaller CC areas. To investigate this, we defined an sSCA spectrum based on a descending Y:X karyotype ratio: 47,XYY, 46,XY, 48,XXYY, 47,XXY, 48,XXXY, 49,XXXXY, 46,XX, 47,XXX. We similarly explored the effects of both X and Y chromosome numbers within sex. Results of shape-based metrics were analyzed using permutation tests consisting of 5,000 iterations.ResultsSeveral subregional areas, local curvature, and BLDs differed between groups. Moderate associations were found between area and curvature in relation to the spectrum and X and Y chromosome counts. BLD was strongly associated with X chromosome count in both male and female groups.ConclusionsOur results suggest that X- and Y-linked genes have differential effects on CC morphometry. To our knowledge, this is the first study to compare CC morphometry across these extremely rare groups

    Customers as decision-makers: strategic environmental assessment in the private sector

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    Despite its diversification and global spread, strategic environmental assessment (SEA) remains limited mainly to activities characterised by well-defined planning processes, typically within the public sector. This article explores the possible application of SEA within certain private-sector contexts where higher-level strategy-making itself is inherently weaker and development is often piecemeal and reactive. The possible adaptation of SEA to the preparation of a strategic document by a particular industrial concern in the UK is examined: this draws attention to the multi-actor nature of development processes within the industry. This leads to the suggestion that SEA in this setting should be thought of as a form of environmental advocacy oriented towards industrial customers, who are understood as sharing a decision-making role in infrastructure development.</p

    Applying New Research Methods to Inform Mountain Lion Harvest Management in Western Montana

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    The lack of reliable methods to accurately estimate mountain lion abundance has made lion (Puma concolor) management one of the most contentious wildlife issues in western Montana over the last 20 years. Lion harvest prescriptions and hunting season structure varied widely during that period because social factors drove management decisions in the absence of objective population data. During winter 2012-2013, we used a DNA-based spatial capture-recapture (SCR) approach to estimate mountain lion abundance in hunting districts 250 and 270 in the southern Bitterroot Watershed of western Montana. Mountain lion hair, scat, and muscle samples were collected for genetic analysis to identify individuals. We developed extensions to standard SCR models to accommodate simultaneous sampling and harvest events and incorporate existing information regarding mountain lion habitat quality. We estimated the abundance of 85 (95% CI = 54, 141) independent mountain lions in hunting district 250 and 82 (95% CI = 51, 137) in hunting district 270. These results are 2 - 3 times higher than previously reported mountain lion abundance in this area and correspond to density estimates of 4.6 and 5.4 lions per 100 km2. Because current harvest regulations in western Montana were developed under the assumption of lower population abundance, lion management objectives are unlikely to be met unless harvest prescriptions are adjusted to account for this new understanding of lion population status. More broadly, the analytic improvements in SCR methods will enhance the ability of wildlife managers to reliably and economically estimate abundance of harvested species

    Discovery and Early Evolution of ASASSN-19bt, the First TDE Detected by TESS

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    We present the discovery and early evolution of ASASSN-19bt, a tidal disruption event (TDE) discovered by the All-Sky Automated Survey for Supernovae (ASAS-SN) at a distance of d115d\simeq115 Mpc and the first TDE to be detected by TESS. As the TDE is located in the TESS Continuous Viewing Zone, our dataset includes 30-minute cadence observations starting on 2018 July 25, and we precisely measure that the TDE begins to brighten 8.3\sim8.3 days before its discovery. Our dataset also includes 18 epochs of Swift UVOT and XRT observations, 2 epochs of XMM-Newton observations, 13 spectroscopic observations, and ground data from the Las Cumbres Observatory telescope network, spanning from 32 days before peak through 37 days after peak. ASASSN-19bt thus has the most detailed pre-peak dataset for any TDE. The TESS light curve indicates that the transient began to brighten on 2019 January 21.6 and that for the first 15 days its rise was consistent with a flux t2\propto t^2 power-law model. The optical/UV emission is well-fit by a blackbody SED, and ASASSN-19bt exhibits an early spike in its luminosity and temperature roughly 32 rest-frame days before peak and spanning up to 14 days that has not been seen in other TDEs, possibly because UV observations were not triggered early enough to detect it. It peaked on 2019 March 04.9 at a luminosity of L1.3×1044L\simeq1.3\times10^{44} ergs s1^{-1} and radiated E3.2×1050E\simeq3.2\times10^{50} ergs during the 41-day rise to peak. X-ray observations after peak indicate a softening of the hard X-ray emission prior to peak, reminiscent of the hard/soft states in X-ray binaries.Comment: 23 pages, 14 figures, 5 tables. A machine-readable table containing the host-subtracted photometry presented in this manuscript is included as an ancillary fil

    Inference and Evolutionary Analysis of Genome-Scale Regulatory Networks in Large Phylogenies

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    Changes in transcriptional regulatory networks can significantly contribute to species evolution and adaptation. However, identification of genome-scale regulatory networks is an open challenge, especially in non-model organisms. Here, we introduce multi-species regulatory network learning (MRTLE), a computational approach that uses phylogenetic structure, sequence-specific motifs, and transcriptomic data, to infer the regulatory networks in different species. Using simulated data from known networks and transcriptomic data from six divergent yeasts, we demonstrate that MRTLE predicts networks with greater accuracy than existing methods because it incorporates phylogenetic information. We used MRTLE to infer the structure of the transcriptional networks that control the osmotic stress responses of divergent, non-model yeast species and then validated our predictions experimentally. Interrogating these networks reveals that gene duplication promotes network divergence across evolution. Taken together, our approach facilitates study of regulatory network evolutionary dynamics across multiple poorly studied species. Keywords: regulatory networks; network inference; evolution of gene regulatory networks; evolution of stress response; yeast; probabilistic graphical model; phylogeny; comparative functional genomicsNational Science Foundation (U.S.) (Grant DBI-1350677)National Institutes of Health (U.S.) (Grant R01CA119176-01)National Institutes of Health (U.S.) (Grant DP1OD003958-01

    Effects of local meteorology and aerosols on ozone and nitrogen dioxide retrievals from OMI and pandora spectrometers in Maryland, USA during DISCOVER-AQ 2011

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    An analysis is presented for both ground- and satellite-based retrievals of total column ozone and nitrogen dioxide levels from the Washington, D.C., and Baltimore, Maryland, metropolitan area during the NASA-sponsored July 2011 campaign of Deriving Information on Surface COnditions from Column and VERtically Resolved Observations Relevant to Air Quality (DISCOVER-AQ). Satellite retrievals of total column ozone and nitrogen dioxide from the Ozone Monitoring Instrument (OMI) on the Aura satellite are used, while Pandora spectrometers provide total column ozone and nitrogen dioxide amounts from the ground. We found that OMI and Pandora agree well (residuals within ±25 % for nitrogen dioxide, and ±4.5 % for ozone) for a majority of coincident observations during July 2011. Comparisons with surface nitrogen dioxide from a Teledyne API 200 EU NOx Analyzer showed nitrogen dioxide diurnal variability that was consistent with measurements by Pandora. However, the wide OMI field of view, clouds, and aerosols affected retrievals on certain days, resulting in differences between Pandora and OMI of up to ±65 % for total column nitrogen dioxide, and ±23 % for total column ozone. As expected, significant cloud cover (cloud fraction \u3e0.2) was the most important parameter affecting comparisons of ozone retrievals; however, small, passing cumulus clouds that do not coincide with a high (\u3e0.2) cloud fraction, or low aerosol layers which cause significant backscatter near the ground affected the comparisons of total column nitrogen dioxide retrievals. Our results will impact post-processing satellite retrieval algorithms and quality control procedures
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