Spawning stock identification of Atlantic cod (Gadus morhua) in US waters using Pan I and microsatellite genetic markers

Most Atlantic cod (Gadus morhua) stocks within U.S. waters are currently in decline as a result of overexploitation and fishing pressure from commercial fisheries. A better understanding of the genetic structure of cod populations is essential to identify stocks for successful fisheries management. In this study, the genetic structure of cod from major temporally and geographically distinct spawning grounds in U.S. waters was investigated. Adult and juvenile cod were sampled from aggregations within the Gulf of Maine, Georges Bank, and southern New England waters in cooperation with commercial fishermen and state fishery biologists. Caudal fin clips were collected and analyzed using 11 microsatellite markers and the Pan I locus. Two spawning complexes of cod were identified. The northern spring complex was comprised of cod from coastal Gulf of Maine regions during the spring and summer seasons. The southern complex was comprised of cod collected during the winter months in the Gulf of Maine, on Stellwagen Bank in early spring, and at all southern locations. Georges Bank spawners were identified as a possible intermediate population between the complexes; they exhibited significant divergence from southern New England spawning aggregations, but not from cod within the Gulf of Maine. Differentiation among these populations was stable over a two year study period and was consistent with previous results for Atlantic cod reported by Lage et al. 2004 and Wirgin et al. 2007. Juveniles collected from within the Gulf of Maine could be assigned as mixtures to parental spawning complexes. Divergence among adult and juvenile cod was primarily dependent on differentiation at the Gmo132 and Pan I markers, which are suspected to be under natural selection pressures. Local adaptation to environmental factors such as water temperature and salinity may therefore be the driving force of population differentiation. Natal homing and water currents that limit larval dispersal may also influence the stock structure, but cod migrations and dispersions among spawning aggregations likely limit reproductive isolation and neutral genetic drift of populations within US waters

Evolutionary Analysis of Mitogenomes from Parasitic and Free-Living Flatworms

Copyright: © 2015 Solà et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. The attached file is the published version of the article

Revisiting the Red Giant Branch Hosts KOI-3886 and ι Draconis.:Detailed Asteroseismic Modeling and Consolidated Stellar Parameters

Asteroseismology is playing an increasingly important role in the characterization of red giant host stars and their planetary systems. Here, we conduct detailed asteroseismic modeling of the evolved red giant branch (RGB) hosts KOI-3886 and ι Draconis, making use of end-of-mission Kepler (KOI-3886) and multisector TESS (ι Draconis) time-series photometry. We also model the benchmark star KIC 8410637, a member of an eclipsing binary, thus providing a direct test to the seismic determination. We test the impact of adopting different sets of observed modes as seismic constraints. Inclusion of .,"= 1 and 2 modes improves the precision of the stellar parameters, albeit marginally, compared to adopting radial modes alone, with 1.9%-3.0% (radius), 5%-9% (mass), and 19%-25% (age) reached when using all p-dominated modes as constraints. Given the very small spacing of adjacent dipole mixed modes in evolved RGB stars, the sparse set of observed g-dominated modes is not able to provide extra constraints, further leading to highly multimodal posteriors. Access to multiyear time-series photometry does not improve matters, with detailed modeling of evolved RGB stars based on (lower-resolution) TESS data sets attaining a precision commensurate with that based on end-of-mission Kepler data. Furthermore, we test the impact of varying the atmospheric boundary condition in our stellar models. We find the mass and radius estimates to be insensitive to the description of the near-surface layers, at the expense of substantially changing both the near-surface structure of the best-fitting models and the values of associated parameters like the initial helium abundance, Y i . Attempts to measure Y i from seismic modeling of red giants may thus be systematically dependent on the choice of atmospheric physics

The NANOGrav Nine-year Data Set:Mass and Geometric Measurements of Binary Millisecond Pulsars

We analyze 24 binary radio pulsars in the North American Nanohertz Observatory for Gravitational Waves (NANOGrav) nine-year data set. We make 14 significant measurements of the Shapiro delay, including new detections in four pulsar-binary systems (PSRs J0613−0200, J2017+0603, J2302+4442, and J2317+1439), and derive estimates of the binary-component masses and orbital inclination for these MSP-binary systems. We find a wide range of binary pulsar masses, with values as low as ${m}_{{\rm{p}}}={1.18}_{-0.09}^{+0.10}\,{M}_{\odot }$ for PSR J1918−0642 and as high as ${m}_{{\rm{p}}}={1.928}_{-0.017}^{+0.017}\,{M}_{\odot }$ for PSR J1614−2230 (both 68.3% credibility). We make an improved measurement of the Shapiro timing delay in the PSR J1918−0642 and J2043+1711 systems, measuring the pulsar mass in the latter system to be ${m}_{{\rm{p}}}={1.41}_{-0.18}^{+0.21}\,{M}_{\odot }$ (68.3% credibility) for the first time. We measure secular variations of one or more orbital elements in many systems, and use these measurements to further constrain our estimates of the pulsar and companion masses whenever possible. In particular, we used the observed Shapiro delay and periastron advance due to relativistic gravity in the PSR J1903+0327 system to derive a pulsar mass of ${m}_{{\rm{p}}}={1.65}_{-0.02}^{+0.02}\,{M}_{\odot }$ (68.3% credibility). We discuss the implications that our mass measurements have on the overall neutron-star mass distribution, and on the "mass/orbital-period" correlation due to extended mass transfer

Asteroseismology and Spectropolarimetry of the Exoplanet Host Star λ Serpentis

The bright star lambda Ser hosts a hot Neptune with a minimum mass of 13.6 M & OPLUS; and a 15.5 day orbit. It also appears to be a solar analog, with a mean rotation period of 25.8 days and surface differential rotation very similar to the Sun. We aim to characterize the fundamental properties of this system and constrain the evolutionary pathway that led to its present configuration. We detect solar-like oscillations in time series photometry from the Transiting Exoplanet Survey Satellite, and we derive precise asteroseismic properties from detailed modeling. We obtain new spectropolarimetric data, and we use them to reconstruct the large-scale magnetic field morphology. We reanalyze the complete time series of chromospheric activity measurements from the Mount Wilson Observatory, and we present new X-ray and ultraviolet observations from the Chandra and Hubble space telescopes. Finally, we use the updated observational constraints to assess the rotational history of the star and estimate the wind braking torque. We conclude that the remaining uncertainty on the stellar age currently prevents an unambiguous interpretation of the properties of lambda Ser, and that the rate of angular momentum loss appears to be higher than for other stars with a similar Rossby number. Future asteroseismic observations may help to improve the precision of the stellar age

A pervasive role for biomass burning in tropical high ozone/low water structures.

Air parcels with mixing ratios of high O3 and low H2O (HOLW) are common features in the tropical western Pacific (TWP) mid-troposphere (300-700 hPa). Here, using data collected during aircraft sampling of the TWP in winter 2014, we find strong, positive correlations of O3 with multiple biomass burning tracers in these HOLW structures. Ozone levels in these structures are about a factor of three larger than background. Models, satellite data and aircraft observations are used to show fires in tropical Africa and Southeast Asia are the dominant source of high O3 and that low H2O results from large-scale descent within the tropical troposphere. Previous explanations that attribute HOLW structures to transport from the stratosphere or mid-latitude troposphere are inconsistent with our observations. This study suggest a larger role for biomass burning in the radiative forcing of climate in the remote TWP than is commonly appreciated.We thank L. Pan for coordinating the CONTRAST flights and her constructive criticism of an early version of the manuscript; S. Schauffler, V. Donets and R. Lueb for collecting and analysing AWAS samples; T. Robinson and O. Shieh for providing meteorology forecasts in the field; and the pilots and crews of the CAST BAe-146 and CONTRAST Gulfstream V aircrafts for their dedication and professionalism. CAST was funded by the Natural Environment Research Council; CONTRAST was funded by the National Science Foundation. Research at the Jet Propulsion Laboratory, California Institute of Technology, is performed under contract with the National Aeronautics and Space Administration (NASA). A number of the US-based investigators also benefitted from the support of NASA as well as the National Oceanic and Atmospheric Administration. The views, opinions, and findings contained in this report are those of the author(s) and should not be construed as an official National Oceanic and Atmospheric Administration or US Government position, policy or decision. We would like to acknowledge high-performance computing support from Yellowstone (ark:/85065/d7wd3xhc) provided by NCAR's Computational and Information Systems Laboratory. NCAR is sponsored by the National Science Foundation.This is the final version of the article. It first appeared from Nature Publishing Group via http://dx.doi.org/10.1038/ncomms1026

A Glycemia Risk Index (GRI) of Hypoglycemia and Hyperglycemia for Continuous Glucose Monitoring Validated by Clinician Ratings

BackgroundA composite metric for the quality of glycemia from continuous glucose monitor (CGM) tracings could be useful for assisting with basic clinical interpretation of CGM data.MethodsWe assembled a data set of 14-day CGM tracings from 225 insulin-treated adults with diabetes. Using a balanced incomplete block design, 330 clinicians who were highly experienced with CGM analysis and interpretation ranked the CGM tracings from best to worst quality of glycemia. We used principal component analysis and multiple regressions to develop a model to predict the clinician ranking based on seven standard metrics in an Ambulatory Glucose Profile: very low-glucose and low-glucose hypoglycemia; very high-glucose and high-glucose hyperglycemia; time in range; mean glucose; and coefficient of variation.ResultsThe analysis showed that clinician rankings depend on two components, one related to hypoglycemia that gives more weight to very low-glucose than to low-glucose and the other related to hyperglycemia that likewise gives greater weight to very high-glucose than to high-glucose. These two components should be calculated and displayed separately, but they can also be combined into a single Glycemia Risk Index (GRI) that corresponds closely to the clinician rankings of the overall quality of glycemia (r = 0.95). The GRI can be displayed graphically on a GRI Grid with the hypoglycemia component on the horizontal axis and the hyperglycemia component on the vertical axis. Diagonal lines divide the graph into five zones (quintiles) corresponding to the best (0th to 20th percentile) to worst (81st to 100th percentile) overall quality of glycemia. The GRI Grid enables users to track sequential changes within an individual over time and compare groups of individuals.ConclusionThe GRI is a single-number summary of the quality of glycemia. Its hypoglycemia and hyperglycemia components provide actionable scores and a graphical display (the GRI Grid) that can be used by clinicians and researchers to determine the glycemic effects of prescribed and investigational treatments

AI is a viable alternative to high throughput screening: a 318-target study

: High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNet® convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, high-quality X-ray crystal structures, or manual cherry-picking of compounds. We show that the molecules selected by the AtomNet® model are novel drug-like scaffolds rather than minor modifications to known bioactive compounds. Our empirical results suggest that computational methods can substantially replace HTS as the first step of small-molecule drug discovery