Changes in cholesterol homeostasis modify the response of F1B hamsters to dietary very long chain n-3 and n-6 polyunsaturated fatty acids

<p>Abstract</p> <p>Background</p> <p>The plasma lipoprotein response of F1B Golden-Syrian hamsters fed diets high in very long chain (VLC) n-3 polyunsaturated fatty acids (PUFA) is paradoxical to that observed in humans. This anomaly is attributed, in part, to low lipoprotein lipase activity and is dependent on cholesterol status. To further elucidate the mechanism(s) for these responses, hamsters were fed diets containing supplemental fish oil (VLC n-3 PUFA) or safflower oil (n-6 PUFA) (both 10% [w/w]) and either cholesterol-supplemented (0.1% cholesterol [w/w]) or cholesterol-depleted (0.01% cholesterol [w/w] and 10 days prior to killing fed 0.15% lovastatin+2% cholestyramine [w/w]).</p> <p>Results</p> <p>Cholesterol-supplemented hamsters fed fish oil, relative to safflower oil, had higher non-high density lipoprotein (HDL) cholesterol and triglyceride concentrations (P < 0.001) which were associated with lower hepatic low density lipoprotein (LDL) receptor, sterol regulatory element binding protein (SREBP)-1c and acyl-CoA: cholesterol acyl transferase-2 (ACAT) mRNA and protein (p < 0.05), and higher hepatic apolipoprotein (apo) B-100 and apo E protein levels. In contrast, cholesterol-depleted hamsters fed fish oil, relative to safflower oil, had lower non-HDL cholesterol and triglyceride concentrations (P < 0.001) which were associated with lower hepatic SREBP-1c (p < 0.05) but not apo B-100, apo E or ACAT-2 mRNA or protein levels. Independent of cholesterol status, fish oil fed hamsters had lower HDL cholesterol concentrations (p < 0.001), which were associated with lower hepatic apoA-I protein levels (p < 0.05).</p> <p>Conclusion</p> <p>These data suggest disturbing cholesterol homeostasis in F1B hamsters alters their response to dietary fatty acids, which is reflected in altered plasma lipoprotein patterns and regulation of genes associated with their metabolism.</p

Means and covariance functions for geostatistical compositional data: an axiomatic approach

This work focuses on the characterization of the central tendency of a sample of compositional data. It provides new results about theoretical properties of means and covariance functions for compositional data, with an axiomatic perspective. Original results that shed new light on the geostatistical modeling of compositional data are presented. As a first result, it is shown that the weighted arithmetic mean is the only central tendency characteristic satisfying a small set of axioms, namely continuity, reflexivity and marginal stability. Moreover, this set of axioms also implies that the weights must be identical for all parts of the composition. This result has deep consequences on the spatial multivariate covariance modeling of compositional data. In a geostatistical setting, it is shown as a second result that the proportional model of covariance functions (i.e., the product of a covariance matrix and a single correlation function) is the only model that provides identical kriging weights for all components of the compositional data. As a consequence of these two results, the proportional model of covariance function is the only covariance model compatible with reflexivity and marginal stability

Associations of HDL metrics with coronary artery calcium score and density among women traversing menopause

The cardioprotective association of high-density lipoprotein cholesterol (HDL-C) may vary by menopause stage or estradiol level. We tested whether associations of comprehensive HDL metrics (HDL subclasses, phospholipid and triglyceride content, and HDL cholesterol efflux capacity [HDL-CEC]) with coronary artery calcium (CAC) score and density vary by menopause stage or estradiol level in women transitioning through menopause. Participants (N = 294; mean age [SD]: 51.3 [2.9]) had data on HDL metrics and CAC measures at one or two time points during the menopause transition. Generalized estimating equations were used for analyses. Effect modifications by menopause stage or estradiol level were tested in multivariable models. In adjusted models, menopause stage modified the associations of specific HDL metrics with CAC measures. Higher small HDL particles (HDL-P) concentrations (p-interaction = 0.008) and smaller HDL size (p-interaction = 0.02) were associated with greater odds of CAC presence in late perimenopause than in pre/early perimenopause stage. Women in the highest estradiol tertile, but not the lower tertiles, showed a protective association of small HDL-P with CAC presence (p-interaction = 0.007). Lower large HDL-P concentrations (p-interaction = 0.03) and smaller HDL size (p-interaction = 0.03) were associated with lower CAC density in late perimenopause than in postmenopause stage. Associations of HDL phospholipid and triglyceride content and HDL-CEC with CAC measures did not vary by menopause stage or estradiol level. We concluded that HDL subclasses may impact the likelihood of CAC presence and the stability of coronary plaque differently over the menopause transition. Endogenous estradiol levels may contribute to this observation

The state of the Martian climate

60°N was +2.0°C, relative to the 1981–2010 average value (Fig. 5.1). This marks a new high for the record. The average annual surface air temperature (SAT) anomaly for 2016 for land stations north of starting in 1900, and is a significant increase over the previous highest value of +1.2°C, which was observed in 2007, 2011, and 2015. Average global annual temperatures also showed record values in 2015 and 2016. Currently, the Arctic is warming at more than twice the rate of lower latitudes

Creating spatially continuous maps of past land cover from point estimates: A new statistical approach applied to pollen data

International audienceReliable estimates of past land cover are critical for assessing potential effects of anthropogenic land-cover changes on past earth surface-climate feedbacks and landscape complexity. Fossil pollen records from lakes and bogs have provided important information on past natural and human-induced vegetation cover. However, those records provide only point estimates of past land cover, and not the spatially continuous maps at regional and sub-continental scales needed for climate modelling. We propose a set of statistical models that create spatially continuous maps of past land cover by combining two data sets: 1) pollen-based point estimates of past land cover (from the REVEALS model) and 2) spatially continuous estimates of past land cover, obtained by combining simulated potential vegetation (from LPJ-GUESS) with an anthropogenic land-cover change scenario (KK10). The proposed models rely on statistical methodology for compositional data and use Gaussian Markov Random Fields to model spatial dependencies in the data. Land-cover reconstructions are presented for three time windows in Europe: 0.05, 0.2, and 6 ka years before present (BP). The models are evaluated through cross-validation, deviance information criteria and by comparing the reconstruction of the 0.05 ka time window to the present-day land-cover data compiled by the European Forest Institute (EFI). For 0.05 ka, the proposed models provide reconstructions that are closer to the EFI data than either the REVEALS-or LPJ-GUESS/KK10-based estimates; thus the statistical combination of the two estimates improves the reconstruction. The reconstruction by the proposed models for 0.2 ka is also good. For 6 ka, however, the large differences between the REVEALS-and LPJ-GUESS/KK10-based estimates reduce the reliability of the proposed models. Possible reasons for the increased differences between REVEALS and LPJ-GUESS/KK10 for older time periods and further improvement of the proposed models are discussed