Light Rare Earth Element Depletion During Deepwater Horizon Blowout Methanotrophy

Rare earth elements have generally not been thought to have a biological role. However, recent work has demonstrated that the light REEs (LREEs: La, Ce, Pr, and Nd) are essential for at least some methanotrophs, being co-factors in the XoxF type of methanol dehydrogenase (MDH). We show here that dissolved LREEs were significantly removed in a submerged plume of methane-rich water during the Deepwater Horizon (DWH) well blowout. Furthermore, incubation experiments conducted with naturally methane-enriched waters from hydrocarbon seeps in the vicinity of the DWH wellhead also showed LREE removal concurrent with methane consumption. Metagenomic sequencing of incubation samples revealed that LREE-containing MDHs were present. Our field and laboratory observations provide further insight into the biochemical pathways of methanotrophy during the DWH blowout. Additionally, our results are the first observations of direct biological alteration of REE distributions in oceanic systems. In view of the ubiquity of LREE-containing MDHs in oceanic systems, our results suggest that biological uptake of LREEs is an overlooked aspect of the oceanic geochemistry of this group of elements previously thought to be biologically inactive and an unresolved factor in the flux of methane, a potent greenhouse gas, from the ocean

Light Rare Earth Element Depletion During Deepwater Horizon Blowout Methanotrophy

Rare earth elements have generally not been thought to have a biological role. However, recent work has demonstrated that the light REEs (LREEs: La, Ce, Pr, and Nd) are essential for at least some methanotrophs, being co-factors in the XoxF type of methanol dehydrogenase (MDH). We show here that dissolved LREEs were significantly removed in a submerged plume of methane-rich water during the Deepwater Horizon (DWH) well blowout. Furthermore, incubation experiments conducted with naturally methane-enriched waters from hydrocarbon seeps in the vicinity of the DWH wellhead also showed LREE removal concurrent with methane consumption. Metagenomic sequencing of incubation samples revealed that LREE-containing MDHs were present. Our field and laboratory observations provide further insight into the biochemical pathways of methanotrophy during the DWH blowout. Additionally, our results are the first observations of direct biological alteration of REE distributions in oceanic systems. In view of the ubiquity of LREE-containing MDHs in oceanic systems, our results suggest that biological uptake of LREEs is an overlooked aspect of the oceanic geochemistry of this group of elements previously thought to be biologically inactive and an unresolved factor in the flux of methane, a potent greenhouse gas, from the ocean

Investigations of Aerobic Methane Oxidation in Two Marine Seep Environments: Part 1—Chemical Kinetics

Microbial aerobic oxidation is known to be a significant sink of marine methane (CH4), contributing to the relatively minor atmospheric release of this greenhouse gas over vast stretches of the ocean. However, the chemical kinetics of aerobic CH4 oxidation are not well established, making it difficult to predict and assess the extent that CH4 is oxidized in seawater following seafloor release. Here we investigate the kinetics of aerobic CH4 oxidation using mesocosm incubations of fresh seawater samples collected from seep fields in Hudson Canyon, U.S. Atlantic Margin and MC118, Gulf of Mexico to gain a fundamental chemical understanding of this CH4 sink. The goals of this investigation were to determine the response or lag time following CH4 release until more rapid oxidation begins, the reaction order, and the stoichiometry of reactants utilized (i.e., CH4, oxygen, nitrate, phosphate, trace metals) during CH4 oxidation. The results for both Hudson Canyon and MC118 environments show that CH4 oxidation rates sharply increased within less than one month following the CH4 inoculation of seawater. However, the exact temporal characteristics of this more rapid CH4 oxidation varied based on location, possibly dependent on the local circulation and biogeochemical conditions at the point of seawater collection. The data further suggest that methane oxidation behaves as a first‐order kinetic process and that the reaction rate constant remains constant once rapid CH4 oxidation begins

Investigations of Aerobic Methane Oxidation in Two Marine Seep Environments: Part 2—Isotopic Kinetics

During aerobic oxidation of methane (CH4) in seawater, a process which mitigates atmospheric emissions, the 12C‐isotopologue reacts with a slightly greater rate constant than the 13C‐isotopologue, leaving the residual CH4 isotopically fractionated. Prior studies have attempted to exploit this systematic isotopic fractionation from methane oxidation to quantify the extent that a CH4 pool has been oxidized in seawater. However, cultivation‐based studies have suggested that isotopic fractionation fundamentally changes as a microbial population blooms in response to an influx of reactive substrates. Using a systematic mesocosm incubation study with recently collected seawater, here we investigate the fundamental isotopic kinetics of aerobic CH4 oxidation during a microbial bloom. As detailed in a companion paper, seawater samples were collected from seep fields in Hudson Canyon, U.S. Atlantic Margin, and atop Woolsey Mound (also known as Sleeping Dragon) which is part of lease block MC118 in the northern Gulf of Mexico, and used in these investigations. The results from both Hudson Canyon and MC118 show that in these natural environments isotopic fraction for CH4 oxidation follows a first‐order kinetic process. The results also show that the isotopic fractionation factor remains constant during this methanotrophic bloom once rapid CH4 oxidation begins and that the magnitude of the fractionation factor appears correlated with the first‐order reaction rate constant. These findings greatly simplify the use of natural stable isotope changes in CH4 to assess the extent that CH4 is oxidized in seawater following seafloor release

Severity of Depressive Symptoms and Accuracy of Dietary Reporting among Obese Women with Major Depressive Disorder Seeking Weight Loss Treatment

An elevation in symptoms of depression has previously been associated with greater accuracy of reported dietary intake, however this association has not been investigated among individuals with a diagnosis of major depressive disorder. The purpose of this study was to investigate reporting accuracy of dietary intake among a group of women with major depressive disorder in order to determine if reporting accuracy is similarly associated with depressive symptoms among depressed women. Reporting accuracy of dietary intake was calculated based on three 24-hour phone-delivered dietary recalls from the baseline phase of a randomized trial of weight loss treatment for 161 obese women with major depressive disorder. Regression models indicated that higher severity of depressive symptoms was associated with greater reporting accuracy, even when controlling for other factors traditionally associated with reporting accuracy (coefficient  =  0.01 95% CI = 0.01 – 0.02). Seventeen percent of the sample was classified as low energy reporters. Reporting accuracy of dietary intake increases along with depressive symptoms, even among individuals with major depressive disorder. These results suggest that any study investigating associations between diet quality and depression should also include an index of reporting accuracy of dietary intake as accuracy varies with the severity of depressive symptoms

Towards OPM-MEG in a virtual reality environment

Virtual reality (VR) provides an immersive environment in which a participant can experience a feeling of presence in a virtual world. Such environments generate strong emotional and physical responses and have been used for wide-ranging applications. The ability to collect functional neuroimaging data whilst a participant is immersed in VR would represent a step change for experimental paradigms; unfortunately, traditional brain imaging requires participants to remain still, limiting the scope of naturalistic interaction within VR. Recently however, a new type of magnetoencephalography (MEG) device has been developed, that employs scalp-mounted optically-pumped magnetometers (OPMs) to measure brain electrophysiology. Lightweight OPMs, coupled with precise control of the background magnetic field, enables participant movement during data acquisition. Here, we exploit this technology to acquire MEG data whilst a participant uses a virtual reality head-mounted display (VRHMD). We show that, despite increased magnetic interference from the VRHMD, we were able to measure modulation of alpha-band oscillations, and the visual evoked field. Moreover, in a VR experiment in which a participant had to move their head to look around a virtual wall and view a visual stimulus, we showed that the measured MEG signals map spatially in accordance with the known organisation of primary visual cortex. This technique could transform the type of neuroscientific experiment that can be undertaken using functional neuroimaging

The Baryon Oscillation Spectroscopic Survey of SDSS-III

The Baryon Oscillation Spectroscopic Survey (BOSS) is designed to measure the scale of baryon acoustic oscillations (BAO) in the clustering of matter over a larger volume than the combined efforts of all previous spectroscopic surveys of large scale structure. BOSS uses 1.5 million luminous galaxies as faint as i=19.9 over 10,000 square degrees to measure BAO to redshifts z<0.7. Observations of neutral hydrogen in the Lyman alpha forest in more than 150,000 quasar spectra (g<22) will constrain BAO over the redshift range 2.15<z<3.5. Early results from BOSS include the first detection of the large-scale three-dimensional clustering of the Lyman alpha forest and a strong detection from the Data Release 9 data set of the BAO in the clustering of massive galaxies at an effective redshift z = 0.57. We project that BOSS will yield measurements of the angular diameter distance D_A to an accuracy of 1.0% at redshifts z=0.3 and z=0.57 and measurements of H(z) to 1.8% and 1.7% at the same redshifts. Forecasts for Lyman alpha forest constraints predict a measurement of an overall dilation factor that scales the highly degenerate D_A(z) and H^{-1}(z) parameters to an accuracy of 1.9% at z~2.5 when the survey is complete. Here, we provide an overview of the selection of spectroscopic targets, planning of observations, and analysis of data and data quality of BOSS.Comment: 49 pages, 16 figures, accepted by A

Host galaxy identification for supernova surveys

Host galaxy identification is a crucial step for modern supernova (SN) surveys such as the Dark Energy Survey (DES) and the Large Synoptic Survey Telescope (LSST), which will discover SNe by the thousands. Spectroscopic resources are limited, so in the absence of real-time SN spectra these surveys must rely on host galaxy spectra to obtain accurate redshifts for the Hubble diagram and to improve photometric classification of SNe. In addition, SN luminosities are known to correlate with host-galaxy properties. Therefore, reliable identification of host galaxies is essential for cosmology and SN science. We simulate SN events and their locations within their host galaxies to develop and test methods for matching SNe to their hosts. We use both real and simulated galaxy catalog data from the Advanced Camera for Surveys General Catalog and MICECATv2.0, respectively. We also incorporate "hostless" SNe residing in undetected faint hosts into our analysis, with an assumed hostless rate of 5%. Our fully automated algorithm is run on catalog data and matches SNe to their hosts with 91% accuracy. We find that including a machine learning component, run after the initial matching algorithm, improves the accuracy (purity) of the matching to 97% with a 2% cost in efficiency (true positive rate). Although the exact results are dependent on the details of the survey and the galaxy catalogs used, the method of identifying host galaxies we outline here can be applied to any transient survey