134 research outputs found

    Photometric IGM tomography with Subaru/HSC: the large-scale structure of Lyα emitters and IGM transmission in the COSMOS field at z ∼ 5

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    We present a novel technique called “photometric IGM tomography” to map the intergalactic medium (IGM) at z ≃ 4.9 in the COSMOS field. It utilizes deep narrow-band (NB) imaging to photometrically detect faint Lyα forest transmission in background galaxies across the Subaru/Hyper-Suprime Cam (HSC)’s 1.8sq.deg field of view and locate Lyα emitters (LAEs) in the same cosmic volume. Using ultra-deep HSC images and Bayesian spectral energy distribution fitting, we measure the Lyα forest transmission at z ≃ 4.9 along a large number (140) of background galaxies selected from the DEIMOS10k spectroscopic catalogue at 4.98 < z < 5.89 and the SILVERRUSH LAEs at z ≃ 5.7. We photometrically measure the mean Lyα forest transmission and achieve a result consistent with previous measurements based on quasar spectra. We also measure the angular LAE-Lyα forest cross-correlation and Lyα forest auto-correlation functions and place an observational constraint on the large-scale fluctuations of the IGM around LAEs at z ≃ 4.9. Finally, we present the reconstructed 2D tomographic map of the IGM, co-spatial with the large-scale structure of LAEs, at a transverse resolution of 11h−1cMpc across 140h−1cMpc in the COSMOS field at z ≃ 4.9. We discuss the observational requirements and the potential applications of this new technique for understanding the sources of reionization, quasar radiative history, and galaxy-IGM correlations across z ∼ 3 − 6. Our results represent the first proof-of-concept of photometric IGM tomography, offering a new route to examining early galaxy evolution in the context of the large-scale cosmic web from the epoch of reionization to cosmic noon

    Nonequilibrium clumped isotope signals in microbial methane

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    Methane is a key component in the global carbon cycle with a wide range of anthropogenic and natural sources. Although isotopic compositions of methane have traditionally aided source identification, the abundance of its multiply-substituted “clumped” isotopologues, e.g., 13CH3D, has recently emerged as a proxy for determining methane-formation temperatures; however, the impact of biological processes on methane’s clumped isotopologue signature is poorly constrained. We show that methanogenesis proceeding at relatively high rates in cattle, surface environments, and laboratory cultures exerts kinetic control on 13CH3D abundances and results in anomalously elevated formation temperature estimates. We demonstrate quantitatively that H2 availability accounts for this effect. Clumped methane thermometry can therefore provide constraints on the generation of methane in diverse settings, including continental serpentinization sites and ancient, deep groundwaters.National Science Foundation (U.S.) (EAR-1250394)National Science Foundation (U.S.) (EAR-1322805)Deep Carbon Observatory (Program)Natural Sciences and Engineering Research Council of CanadaDeutsche Forschungsgemeinschaft (Gottfried Wilhelm Leibniz Program)United States. Dept. of Defense (National Defense Science and Engineering Graduate Fellowship)Neil & Anna Rasmussen FoundationGrayce B. Kerr Fund, Inc. (Fellowship)MIT Energy Initiative (Shell-MITEI Graduate Fellowship)Shell International Exploration and Production B.V. (N. Braunsdorf and D. Smit of Shell PTI/EG grant

    Actin Nemaline Myopathy Mouse Reproduces Disease, Suggests Other Actin Disease Phenotypes and Provides Cautionary Note on Muscle Transgene Expression

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    Mutations in the skeletal muscle α-actin gene (ACTA1) cause congenital myopathies including nemaline myopathy, actin aggregate myopathy and rod-core disease. The majority of patients with ACTA1 mutations have severe hypotonia and do not survive beyond the age of one. A transgenic mouse model was generated expressing an autosomal dominant mutant (D286G) of ACTA1 (identified in a severe nemaline myopathy patient) fused with EGFP. Nemaline bodies were observed in multiple skeletal muscles, with serial sections showing these correlated to aggregates of the mutant skeletal muscle α-actin-EGFP. Isolated extensor digitorum longus and soleus muscles were significantly weaker than wild-type (WT) muscle at 4 weeks of age, coinciding with the peak in structural lesions. These 4 week-old mice were ∼30% less active on voluntary running wheels than WT mice. The α-actin-EGFP protein clearly demonstrated that the transgene was expressed equally in all myosin heavy chain (MHC) fibre types during the early postnatal period, but subsequently became largely confined to MHCIIB fibres. Ringbinden fibres, internal nuclei and myofibrillar myopathy pathologies, not typical features in nemaline myopathy or patients with ACTA1 mutations, were frequently observed. Ringbinden were found in fast fibre predominant muscles of adult mice and were exclusively MHCIIB-positive fibres. Thus, this mouse model presents a reliable model for the investigation of the pathobiology of nemaline body formation and muscle weakness and for evaluation of potential therapeutic interventions. The occurrence of core-like regions, internal nuclei and ringbinden will allow analysis of the mechanisms underlying these lesions. The occurrence of ringbinden and features of myofibrillar myopathy in this mouse model of ACTA1 disease suggests that patients with these pathologies and no genetic explanation should be screened for ACTA1 mutations

    The Role of Galaxies and AGN in Reionising the IGM - I: Keck Spectroscopy of 5 < z < 7 Galaxies in the QSO Field J1148+5251

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    We introduce a new method for determining the influence of galaxies and active galactic nuclei (AGN) on the physical state of the intergalactic medium (IGM) at high redshift and illustrate its potential via a first application to the field of the z=6.42z=6.42 QSO J1148+5251. By correlating the spatial positions of spectroscopically-confirmed Lyman break galaxies (LBGs) with fluctuations in the Lyman alpha forest seen in the high signal-to-noise spectrum of a background QSO, we provide a statistical measure of the typical escape fraction of Lyman continuum photons close to the end of cosmic reionisation. Here we use Keck DEIMOS spectroscopy to locate 7 colour-selected LBGs in the redshift range 5.3z6.45.3\lesssim z\lesssim 6.4 and confirm a faint z=5.701z=5.701 AGN. We then examine the spatial correlation between this sample and Lyα\alpha/Lyβ\beta transmission fluctuations in a Keck ESI spectrum of the QSO. Interpreting the statistical HI proximity effect as arising from faint galaxies clustered around the detected LBGs, we translate the observed mean Lyα\alpha transmitted flux around an average detected LBG into a constraint on the mean escape fraction fesc0.08\langle f_{\rm esc}\rangle\geq0.08 at z6z\simeq6. We also report evidence of the individual transverse HI proximity effect of a z=6.177z=6.177 luminous LBG via a Lyβ\beta transmission spike and two broad Lyα\alpha transmission spikes around the z=5.701z=5.701 AGN. We discuss the possible origin of such associations which suggest that while faint galaxies are primarily driving reionisation, luminous galaxies and AGN may provide important contributions to the UV background or thermal fluctuations of the IGM at z6z\simeq6. Although a limited sample, our results demonstrate the potential of making progress using this method in resolving one of the most challenging aspects of the contribution of galaxies and AGN to cosmic reionisation.Comment: 21 pages, 16 figures, the version accepted in MNRA

    Gap-filling eddy covariance methane fluxes : Comparison of machine learning model predictions and uncertainties at FLUXNET-CH4 wetlands

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    Time series of wetland methane fluxes measured by eddy covariance require gap-filling to estimate daily, seasonal, and annual emissions. Gap-filling methane fluxes is challenging because of high variability and complex responses to multiple drivers. To date, there is no widely established gap-filling standard for wetland methane fluxes, with regards both to the best model algorithms and predictors. This study synthesizes results of different gap-filling methods systematically applied at 17 wetland sites spanning boreal to tropical regions and including all major wetland classes and two rice paddies. Procedures are proposed for: 1) creating realistic artificial gap scenarios, 2) training and evaluating gap-filling models without overstating performance, and 3) predicting halfhourly methane fluxes and annual emissions with realistic uncertainty estimates. Performance is compared between a conventional method (marginal distribution sampling) and four machine learning algorithms. The conventional method achieved similar median performance as the machine learning models but was worse than the best machine learning models and relatively insensitive to predictor choices. Of the machine learning models, decision tree algorithms performed the best in cross-validation experiments, even with a baseline predictor set, and artificial neural networks showed comparable performance when using all predictors. Soil temperature was frequently the most important predictor whilst water table depth was important at sites with substantial water table fluctuations, highlighting the value of data on wetland soil conditions. Raw gap-filling uncertainties from the machine learning models were underestimated and we propose a method to calibrate uncertainties to observations. The python code for model development, evaluation, and uncertainty estimation is publicly available. This study outlines a modular and robust machine learning workflow and makes recommendations for, and evaluates an improved baseline of, methane gap-filling models that can be implemented in multi-site syntheses or standardized products from regional and global flux networks (e.g., FLUXNET).Peer reviewe

    Rising rural body-mass index is the main driver of the global obesity epidemic in adults

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    Body-mass index (BMI) has increased steadily in most countries in parallel with a rise in the proportion of the population who live in cities(.)(1,2) This has led to a widely reported view that urbanization is one of the most important drivers of the global rise in obesity(3-6). Here we use 2,009 population-based studies, with measurements of height and weight in more than 112 million adults, to report national, regional and global trends in mean BMI segregated by place of residence (a rural or urban area) from 1985 to 2017. We show that, contrary to the dominant paradigm, more than 55% of the global rise in mean BMI from 1985 to 2017-and more than 80% in some low- and middle-income regions-was due to increases in BMI in rural areas. This large contribution stems from the fact that, with the exception of women in sub-Saharan Africa, BMI is increasing at the same rate or faster in rural areas than in cities in low- and middle-income regions. These trends have in turn resulted in a closing-and in some countries reversal-of the gap in BMI between urban and rural areas in low- and middle-income countries, especially for women. In high-income and industrialized countries, we noted a persistently higher rural BMI, especially for women. There is an urgent need for an integrated approach to rural nutrition that enhances financial and physical access to healthy foods, to avoid replacing the rural undernutrition disadvantage in poor countries with a more general malnutrition disadvantage that entails excessive consumption of low-quality calories.Peer reviewe

    Height and body-mass index trajectories of school-aged children and adolescents from 1985 to 2019 in 200 countries and territories: a pooled analysis of 2181 population-based studies with 65 million participants

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    Summary Background Comparable global data on health and nutrition of school-aged children and adolescents are scarce. We aimed to estimate age trajectories and time trends in mean height and mean body-mass index (BMI), which measures weight gain beyond what is expected from height gain, for school-aged children and adolescents. Methods For this pooled analysis, we used a database of cardiometabolic risk factors collated by the Non-Communicable Disease Risk Factor Collaboration. We applied a Bayesian hierarchical model to estimate trends from 1985 to 2019 in mean height and mean BMI in 1-year age groups for ages 5–19 years. The model allowed for non-linear changes over time in mean height and mean BMI and for non-linear changes with age of children and adolescents, including periods of rapid growth during adolescence. Findings We pooled data from 2181 population-based studies, with measurements of height and weight in 65 million participants in 200 countries and territories. In 2019, we estimated a difference of 20 cm or higher in mean height of 19-year-old adolescents between countries with the tallest populations (the Netherlands, Montenegro, Estonia, and Bosnia and Herzegovina for boys; and the Netherlands, Montenegro, Denmark, and Iceland for girls) and those with the shortest populations (Timor-Leste, Laos, Solomon Islands, and Papua New Guinea for boys; and Guatemala, Bangladesh, Nepal, and Timor-Leste for girls). In the same year, the difference between the highest mean BMI (in Pacific island countries, Kuwait, Bahrain, The Bahamas, Chile, the USA, and New Zealand for both boys and girls and in South Africa for girls) and lowest mean BMI (in India, Bangladesh, Timor-Leste, Ethiopia, and Chad for boys and girls; and in Japan and Romania for girls) was approximately 9–10 kg/m2. In some countries, children aged 5 years started with healthier height or BMI than the global median and, in some cases, as healthy as the best performing countries, but they became progressively less healthy compared with their comparators as they grew older by not growing as tall (eg, boys in Austria and Barbados, and girls in Belgium and Puerto Rico) or gaining too much weight for their height (eg, girls and boys in Kuwait, Bahrain, Fiji, Jamaica, and Mexico; and girls in South Africa and New Zealand). In other countries, growing children overtook the height of their comparators (eg, Latvia, Czech Republic, Morocco, and Iran) or curbed their weight gain (eg, Italy, France, and Croatia) in late childhood and adolescence. When changes in both height and BMI were considered, girls in South Korea, Vietnam, Saudi Arabia, Turkey, and some central Asian countries (eg, Armenia and Azerbaijan), and boys in central and western Europe (eg, Portugal, Denmark, Poland, and Montenegro) had the healthiest changes in anthropometric status over the past 3·5 decades because, compared with children and adolescents in other countries, they had a much larger gain in height than they did in BMI. The unhealthiest changes—gaining too little height, too much weight for their height compared with children in other countries, or both—occurred in many countries in sub-Saharan Africa, New Zealand, and the USA for boys and girls; in Malaysia and some Pacific island nations for boys; and in Mexico for girls. Interpretation The height and BMI trajectories over age and time of school-aged children and adolescents are highly variable across countries, which indicates heterogeneous nutritional quality and lifelong health advantages and risks
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