3,132 research outputs found

    Qualitative and quantitative analysis of mixtures of compounds containing both hydrogen and deuterium

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    Method allows qualitative and quantitative analysis of mixtures of partially deuterated compounds. Nuclear magnetic resonance spectroscopy determines location and amount of deuterium in organic compounds but not fully deuterated compounds. Mass spectroscopy can detect fully deuterated species but not the location

    Why and How Imprinted Genes Drive Fetal Programming

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    Imprinted genes mediate fetal and childhood growth and development, and early growth patterns drive fetal programming effects. However, predictions and evidence from the kinship theory of imprinting have yet to be directly integrated with data on fetal programming and risks of metabolic disease. I first define paternal-gene and maternal-gene optima with regard to early human growth and development. Next, I review salient evidence with regard to imprinted gene effects on birth weight, body composition, trajectories of feeding and growth, and timing of developmental stages, to evaluate why and how imprinted gene expression influences risks of metabolic disease in later life. I find that metabolic disease risks derive primarily from maternal gene biases that lead to reduced placental efficacy, low birth weight, low relative muscle mass, high relative white fat, increased abdominal adiposity, reduced pancreatic β-cell mass that promotes insulin resistance, reduced appetite and infant sucking efficacy, catch-up fat deposition from family foods after weaning, and early puberty. Paternal gene biases, by contrast, may contribute to metabolic disease via lower rates of brown fat thermiogenesis, and through favoring more rapid postnatal catch-up growth after intrauterine growth restriction from environmental causes. These disease risks can be alleviated through dietary and pharmacological alterations that selectively target imprinted gene expression and relevant metabolic pathways. The kinship theory of imprinting, and mother-offspring conflict more generally, provide a clear predictive framework for guiding future research on fetal programming and metabolic disease

    Real-time detection of tsunami ionospheric disturbances with a stand-alone GNSS receiver. A preliminary feasibility demonstration

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    It is well known that tsunamis can produce gravity waves that propagate up to the ionosphere generating disturbed electron densities in the E and F regions. These ionospheric disturbances can be studied in detail using ionospheric total electron content (TEC) measurements collected by continuously operating ground-based receivers from the Global Navigation Satellite Systems (GNSS). Here, we present results using a new approach, named VARION (Variometric Approach for Real-Time Ionosphere Observation), and estimate slant TEC (sTEC) variations in a real-time scenario. Using the VARION algorithm we compute TEC variations at 56 GPS receivers in Hawaii as induced by the 2012 Haida Gwaii tsunami event. We observe TEC perturbations with amplitudes of up to 0.25 TEC units and traveling ionospheric perturbations (TIDs) moving away from the earthquake epicenter at an approximate speed of 316 m/s. We perform a wavelet analysis to analyze localized variations of power in the TEC time series and we find perturbation periods consistent with a tsunami typical deep ocean period. Finally, we present comparisons with the real-time tsunami MOST (Method of Splitting Tsunami) model produced by the NOAA Center for Tsunami Research and we observe variations in TEC that correlate in time and space with the tsunami waves

    Estimating magnetic fields of homes near transmission lines in the California Power Line Study.

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    The California Power Line Study is a case-control study investigating the relation between residences near transmission lines and risk of childhood leukemia. It includes 5788 childhood leukemia cases and 5788 matched primary controls born between 1986 and 2007. We describe the methodology for estimating magnetic fields at study residences as well as for characterizing sources of uncertainty in these estimates. Birth residences of study subjects were geocoded and their distances to transmission lines were ascertained. 302 residences were deemed sufficiently close to transmission lines to have non-zero magnetic fields attributable to the lines. These residences were visited and detailed data, describing the physical configuration and dimensions of the lines contributing to the magnetic field at the residence, were collected. Phasing, loading, and directional load flow data for years of birth and diagnosis for each subject as well as for the day of site visit were obtained from utilities when available; when yearly average load for a particular year was not available, extrapolated values based on expert knowledge and prediction models were obtained. These data were used to estimate the magnetic fields at the center, closest and farthest point of each residence. We found good correlation between calculated fields and spot measurements of fields taken on site during visits. Our modeling strategies yielded similar calculated field estimates, and they were in high agreement with utility extrapolations. Phasing was known for over 90% of the lines. Important sources of uncertainty included a lack of information on the precise location of residences located within apartment buildings or other complexes. Our findings suggest that we were able to achieve high specificity in exposure assessment, which is essential for examining the association between distance to or magnetic fields from power lines and childhood leukemia risk
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