Psychosocial Predictors of Metabolic Syndrome among Latino Groups in the Multi-Ethnic Study of Atherosclerosis (MESA).

ObjectiveWe sought to determine the contribution of psychological variables to risk for metabolic syndrome (MetS) among Latinos enrolled in the Multi-Ethnic Study of Atherosclerosis (MESA), and to investigate whether social support moderates these associations, and whether inflammatory markers mediate the association between psychological variables and MetS.Research design and methodsCross-sectional analyses at study baseline were conducted with a national Latino cohort (n = 1,388) that included Mexican Americans, Dominican Americans, Puerto Rican Americans and Central/South Americans. Hierarchical logistic regression analyses were conducted to test the effects of psychosocial variables (chronic stress, depressive symptoms, and social support) on MetS. In addition, separate subgroup-specific models, controlling for nationality, age, gender, socioeconomic position, language spoken at home, exercise, smoking and drinking status, and testing for the effects of chronic stress, depressive symptoms and inflammation (IL-6, CRP, fibrinogen) in predicting risk for MetS were conducted.ResultsIn the overall sample, high chronic stress independently predicted risk for MetS, however this association was found to be significant only in Mexican Americans and Puerto Rican Americans. Social support did not moderate the associations between chronic stress and MetS for any group. Chronic stress was not associated with inflammatory markers in either the overall sample or in each group.ConclusionsOur results suggest a differential contribution of chronic stress to the prevalence of MetS by national groups

Droplets I: Pressure-Dominated Sub-0.1 pc Coherent Structures in L1688 and B18

We present the observation and analysis of newly discovered coherent structures in the L1688 region of Ophiuchus and the B18 region of Taurus. Using data from the Green Bank Ammonia Survey (GAS), we identify regions of high density and near-constant, almost-thermal, velocity dispersion. Eighteen coherent structures are revealed, twelve in L1688 and six in B18, each of which shows a sharp "transition to coherence" in velocity dispersion around its periphery. The identification of these structures provides a chance to study the coherent structures in molecular clouds statistically. The identified coherent structures have a typical radius of 0.04 pc and a typical mass of 0.4 Msun, generally smaller than previously known coherent cores identified by Goodman et al. (1998), Caselli et al. (2002), and Pineda et al. (2010). We call these structures "droplets." We find that unlike previously known coherent cores, these structures are not virially bound by self-gravity and are instead predominantly confined by ambient pressure. The droplets have density profiles shallower than a critical Bonnor-Ebert sphere, and they have a velocity (VLSR) distribution consistent with the dense gas motions traced by NH3 emission. These results point to a potential formation mechanism through pressure compression and turbulent processes in the dense gas. We present a comparison with a magnetohydrodynamic simulation of a star-forming region, and we speculate on the relationship of droplets with larger, gravitationally bound coherent cores, as well as on the role that droplets and other coherent structures play in the star formation process.Comment: Accepted by ApJ in April, 201

Mass Assembly of Stellar Systems and Their Evolution with the SMA (MASSES)-Full Data Release

We present and release the full dataset for the Mass Assembly of Stellar Systems and their Evolution with the SMA (MASSES) survey. This survey used the Submillimeter Array (SMA) to image the 74 known protostars within the Perseus molecular cloud. The SMA was used in two array configurations to capture outflows for scales $>$30$^{\prime\prime}$ ($>$9000 au) and to probe scales down to $\sim$1$^{\prime\prime}$ ($\sim$300 au). The protostars were observed with the 1.3 mm and 850 $\mu$m receivers simultaneously to detect continuum at both wavelengths and molecular line emission from CO(2-1), $^{13}$CO(2-1), C$^{18}$O(2-1), N$_2$D$^+$(3-2), CO(3-2), HCO$^+$(4-3), and H$^{13}$CO$^+$(4-3). Some of the observations also used the SMA's recently upgraded correlator, SWARM, whose broader bandwidth allowed for several more spectral lines to be observed (e.g., SO, H$_2$CO, DCO$^+$, DCN, CS, CN). Of the main continuum and spectral tracers observed, 84% of the images and cubes had emission detected. The median C$^{18}$O(2-1) linewidth is $\sim$1.0 km s$^{-1}$, which is slightly higher than those measured with single-dish telescopes at scales of 3000-20000 au. Of the 74 targets, six are suggested to be first hydrostatic core candidates, and we suggest that L1451-mm is the best candidate. We question a previous continuum detection toward L1448 IRS2E. In the SVS13 system, SVS13A certainly appears to be the most evolved source, while SVS13C appears to be hotter and more evolved than SVS13B. The MASSES survey is the largest publicly available interferometric continuum and spectral line protostellar survey to date, and is largely unbiased as it only targets protostars in Perseus. All visibility ($uv$) data and imaged data are publicly available at https://dataverse.harvard.edu/dataverse/full_MASSES/.Comment: Accepted to ApJ

Ecosystem Overfishing in the Ocean

Fisheries catches represent a net export of mass and energy that can no longer be used by trophic levels higher than those fished. Thus, exploitation implies a depletion of secondary production of higher trophic levels (here the production of mass and energy by herbivores and carnivores in the ecosystem) due to the removal of prey. The depletion of secondary production due to the export of biomass and energy through catches was recently formulated as a proxy for evaluating the ecosystem impacts of fishing–i.e., the level of ecosystem overfishing. Here we evaluate the historical and current risk of ecosystem overfishing at a global scale by quantifying the depletion of secondary production using the best available fisheries and ecological data (i.e., catch and primary production). Our results highlight an increasing trend in the number of unsustainable fisheries (i.e., an increase in the risk of ecosystem overfishing) from the 1950s to the 2000s, and illustrate the worldwide geographic expansion of overfishing. These results enable to assess when and where fishing became unsustainable at the ecosystem level. At present, total catch per capita from Large Marine Ecosystems is at least twice the value estimated to ensure fishing at moderate sustainable levels

Eccentric resistance training and beta-hydroxy-beta-methylbutyrate free acid affects muscle PGC-1 alpha expression and serum irisin, nesfatin-1 and resistin in rats

The hypothalamus controls metabolism and feeding behaviour via several signals with other tissues. Exercise and supplements can change hypothalamic signalling pathways, so the present study investigated the influence of eccentric resistance training and β-hydroxy-β-methylbutyrate free acid supplementation on PGC-1α expression, serum irisin, nesfatin-1 and resistin concentrations. Thirty-two male rats (8 weeks old, 200±17 g body mass) were randomly allocated to control, β-hydroxy-β-methylbutyrate free acid supplementation (HMB), eccentric resistance training (ERT), and β-hydroxy-β-methylbutyrate free acid supplementation plus eccentric resistance training (HMB+ERT) groups. Training groups undertook eccentric resistance training (6 weeks, 3 times a week) and supplement groups consumed β-hydroxy-β-methylbutyrate free acid (HMB-FA) orally (76 mg kg-1 day-1). Twenty-four hours after the last training session, serum and triceps brachii muscle samples were collected and sent to the laboratory for analysis. Two-way ANOVA and Pearson correlation were employed (significance level: P<0.05). The results showed that eccentric resistance training increases skeletal muscle PGC-1α gene expression, as well as serum levels of irisin and nesfatin-1 (P=0.001). Eccentric resistance training decreased the serum concentration of resistin (P=0.001). HMB-FA supplementation increased skeletal muscle PGC-1α gene expression (P=0.002), as well as the serum concentration of irisin and nesfatin-1 (P=0.001), but decreased the serum concentration of resistin (P=0.001). Significant correlations were observed between PGC-1α gene expression and serum concentrations of irisin, nesfatin-1 and resistin. HMB-FA supplementation with eccentric resistance training may induce crosstalk between peptide release from other tissues and increases maximal muscle strength. The combination of the two interventions had a more substantial effect than each in isolation

The Fourteenth Data Release of the Sloan Digital Sky Survey: First Spectroscopic Data from the extended Baryon Oscillation Spectroscopic Survey and from the second phase of the Apache Point Observatory Galactic Evolution Experiment

The fourth generation of the Sloan Digital Sky Survey (SDSS-IV) has been in operation since July 2014. This paper describes the second data release from this phase, and the fourteenth from SDSS overall (making this, Data Release Fourteen or DR14). This release makes public data taken by SDSS-IV in its first two years of operation (July 2014-2016). Like all previous SDSS releases, DR14 is cumulative, including the most recent reductions and calibrations of all data taken by SDSS since the first phase began operations in 2000. New in DR14 is the first public release of data from the extended Baryon Oscillation Spectroscopic Survey (eBOSS); the first data from the second phase of the Apache Point Observatory (APO) Galactic Evolution Experiment (APOGEE-2), including stellar parameter estimates from an innovative data driven machine learning algorithm known as "The Cannon"; and almost twice as many data cubes from the Mapping Nearby Galaxies at APO (MaNGA) survey as were in the previous release (N = 2812 in total). This paper describes the location and format of the publicly available data from SDSS-IV surveys. We provide references to the important technical papers describing how these data have been taken (both targeting and observation details) and processed for scientific use. The SDSS website (www.sdss.org) has been updated for this release, and provides links to data downloads, as well as tutorials and examples of data use. SDSS-IV is planning to continue to collect astronomical data until 2020, and will be followed by SDSS-V.Comment: SDSS-IV collaboration alphabetical author data release paper. DR14 happened on 31st July 2017. 19 pages, 5 figures. Accepted by ApJS on 28th Nov 2017 (this is the "post-print" and "post-proofs" version; minor corrections only from v1, and most of errors found in proofs corrected

Mature Andean forests as globally important carbon sinks and future carbon refuges

It is largely unknown how South America’s Andean forests affect the global carbon cycle, and thus regulate climate change. Here, we measure aboveground carbon dynamics over the past two decades in 119 monitoring plots spanning a range of >3000 m elevation across the subtropical and tropical Andes. Our results show that Andean forests act as strong sinks for aboveground carbon (0.67 ± 0.08 Mg C ha−1 y−1) and have a high potential to serve as future carbon refuges. Aboveground carbon dynamics of Andean forests are driven by abiotic and biotic factors, such as climate and size-dependent mortality of trees. The increasing aboveground carbon stocks offset the estimated C emissions due to deforestation between 2003 and 2014, resulting in a net total uptake of 0.027 Pg C y−1. Reducing deforestation will increase Andean aboveground carbon stocks, facilitate upward species migrations, and allow for recovery of biomass losses due to climate change.Fil: Duque, Alvaro. Universidad Nacional de Colombia; ColombiaFil: Peña, Miguel A.. Universidad Nacional de Colombia; ColombiaFil: Cuesta, Francisco. Universidad de Las Américas; EcuadorFil: González Caro, Sebastián. Universidad Nacional de Colombia; ColombiaFil: Kennedy, Peter. University of Minnesota; Estados UnidosFil: Phillips, Oliver L.. University of Leeds; Reino UnidoFil: Calderón Loor, Marco. Universidad de Las Américas; EcuadorFil: Blundo, Cecilia Mabel. Universidad Nacional de Tucumán. Instituto de Ecología Regional. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto de Ecología Regional; ArgentinaFil: Carilla, Julieta. Universidad Nacional de Tucumán. Instituto de Ecología Regional. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto de Ecología Regional; ArgentinaFil: Cayola, Leslie. Missouri Botanical Garden; Estados UnidosFil: Farfán Ríos, William. Washington University in St. Louis; Estados UnidosFil: Fuentes, Alfredo. Missouri Botanical Garden; Estados UnidosFil: Grau, Hector Ricardo. Universidad Nacional de Tucumán. Instituto de Ecología Regional. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto de Ecología Regional; ArgentinaFil: Homeier, Jürgen. Universität Göttingen; AlemaniaFil: Loza-Rivera, María I.. Missouri Botanical Garden; Estados UnidosFil: Malhi, Yadvinder. University of Oxford; Reino UnidoFil: Malizia, Agustina. Universidad Nacional de Tucumán. Instituto de Ecología Regional. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto de Ecología Regional; ArgentinaFil: Malizia, Lucio Ricardo. Universidad Nacional de Jujuy; ArgentinaFil: Martínez Villa, Johanna A.. Université du Québec a Montreal; CanadáFil: Myers, Jonathan A.. Washington University in St. Louis; Estados UnidosFil: Osinaga Acosta, Oriana. Universidad Nacional de Tucumán. Instituto de Ecología Regional. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto de Ecología Regional; ArgentinaFil: Peralvo, Manuel. No especifíca;Fil: Pinto, Esteban. No especifíca;Fil: Saatchi, Sassan. Jet Propulsion Laboratory; Estados UnidosFil: Silman, Miles. Center For Energy, Environment And Sustainability; Estados UnidosFil: Tello, J. Sebastián. Missouri Botanical Garden; Estados UnidosFil: Terán Valdez, Andrea. No especifíca;Fil: Feeley, Kenneth J.. University of Miami; Estados Unido

Mature Andean forests as globally important carbon sinks and future carbon refuges

It is largely unknown how South America’s Andean forests affect the global carbon cycle, and thus regulate climate change. Here, we measure aboveground carbon dynamics over the past two decades in 119 monitoring plots spanning a range of >3000 m elevation across the subtropical and tropical Andes. Our results show that Andean forests act as strong sinks for aboveground carbon (0.67 ± 0.08 Mg C ha−1 y−1) and have a high potential to serve as future carbon refuges. Aboveground carbon dynamics of Andean forests are driven by abiotic and biotic factors, such as climate and size-dependent mortality of trees. The increasing aboveground carbon stocks offset the estimated C emissions due to deforestation between 2003 and 2014, resulting in a net total uptake of 0.027 Pg C y−1. Reducing deforestation will increase Andean aboveground carbon stocks, facilitate upward species migrations, and allow for recovery of biomass losses due to climate change.Fil: Duque, Alvaro. Universidad Nacional de Colombia; ColombiaFil: Peña, Miguel A.. Universidad Nacional de Colombia; ColombiaFil: Cuesta, Francisco. Universidad de Las Américas; EcuadorFil: González Caro, Sebastián. Universidad Nacional de Colombia; ColombiaFil: Kennedy, Peter. University of Minnesota; Estados UnidosFil: Phillips, Oliver L.. University of Leeds; Reino UnidoFil: Calderón Loor, Marco. Universidad de Las Américas; EcuadorFil: Blundo, Cecilia Mabel. Universidad Nacional de Tucumán. Instituto de Ecología Regional. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto de Ecología Regional; ArgentinaFil: Carilla, Julieta. Universidad Nacional de Tucumán. Instituto de Ecología Regional. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto de Ecología Regional; ArgentinaFil: Cayola, Leslie. Missouri Botanical Garden; Estados UnidosFil: Farfán Ríos, William. Washington University in St. Louis; Estados UnidosFil: Fuentes, Alfredo. Missouri Botanical Garden; Estados UnidosFil: Grau, Hector Ricardo. Universidad Nacional de Tucumán. Instituto de Ecología Regional. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto de Ecología Regional; ArgentinaFil: Homeier, Jürgen. Universität Göttingen; AlemaniaFil: Loza-Rivera, María I.. Missouri Botanical Garden; Estados UnidosFil: Malhi, Yadvinder. University of Oxford; Reino UnidoFil: Malizia, Agustina. Universidad Nacional de Tucumán. Instituto de Ecología Regional. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto de Ecología Regional; ArgentinaFil: Malizia, Lucio Ricardo. Universidad Nacional de Jujuy; ArgentinaFil: Martínez Villa, Johanna A.. Université du Québec a Montreal; CanadáFil: Myers, Jonathan A.. Washington University in St. Louis; Estados UnidosFil: Osinaga Acosta, Oriana. Universidad Nacional de Tucumán. Instituto de Ecología Regional. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto de Ecología Regional; ArgentinaFil: Peralvo, Manuel. No especifíca;Fil: Pinto, Esteban. No especifíca;Fil: Saatchi, Sassan. Jet Propulsion Laboratory; Estados UnidosFil: Silman, Miles. Center For Energy, Environment And Sustainability; Estados UnidosFil: Tello, J. Sebastián. Missouri Botanical Garden; Estados UnidosFil: Terán Valdez, Andrea. No especifíca;Fil: Feeley, Kenneth J.. University of Miami; Estados Unido

Synthetic Biology Open Language (SBOL) Version 1.1.0

In this BioBricks Foundation Request for Comments (BBF RFC), we specify the Synthetic Biology Open Language (SBOL) Version 1.1.0 to enable the electronic exchange of information describing DNA components used in synthetic biology. We define: 1. the vocabulary, a set of preferred terms and 2. the core data model, a common computational representation