EPA, DHA, and Lipoic Acid Differentially Modulate the n-3 Fatty Acid Biosynthetic Pathway in Atlantic Salmon Hepatocytes

The aim of the present study was to investigate how EPA, DHA, and lipoic acid (LA) influence the different metabolic steps in the n-3 fatty acid (FA) biosynthetic pathway in hepatocytes from Atlantic salmon fed four dietary levels (0, 0.5, 1.0 and 2.0%) of EPA, DHA or a 1:1 mixture of these FA. The hepatocytes were incubated with [1-14C] 18:3n-3 in the presence or absence of LA (0.2 mM). Increased endogenous levels of EPA and/or DHA and LA exposure both led to similar responses in cells with reduced desaturation and elongation of [1-14C] 18:3n-3 to 18:4n-3, 20:4n-3, and EPA, in agreement with reduced expression of the Δ6 desaturase gene involved in the first step of conversion. DHA production, on the other hand, was maintained even in groups with high endogenous levels of DHA, possibly due to a more complex regulation of this last step in the n-3 metabolic pathway. Inhibition of the Δ6 desaturase pathway led to increased direct elongation to 20:3n-3 by both DHA and LA. Possibly the route by 20:3n-3 and then Δ8 desaturation to 20:4n-3, bypassing the first Δ6 desaturase step, can partly explain the maintained or even increased levels of DHA production. LA increased DHA production in the phospholipid fraction of hepatocytes isolated from fish fed 0 and 0.5% EPA and/or DHA, indicating that LA has the potential to further increase the production of this health-beneficial FA in fish fed diets with low levels of EPA and/or DHA.submittedVersio

Monitoring obesity prevalence in the United States through bookmarking activities in online food portals.

Studying the impact of food consumption on people's health is a serious matter for its implications on public policy, but it has traditionally been a slow process since it requires information gathered through expensive collection processes such as surveys, census and systematic reviews of research articles. We argue that this process could be supported and hastened using data collected via online social networks. In this work we investigate the relationships between the online traces left behind by users of a large US online food community and the prevalence of obesity in 47 states and 311 counties in the US. Using data associated with the recipes bookmarked over an 9-year period by 144,839 users of the Allrecipes.com food website residing throughout the US, several hierarchical regression models are created to (i) shed light on these relations and (ii) establish their magnitude. The results of our analysis provide strong evidence that bookmarking activities on recipes in online food communities can provide a signal allowing food and health related issues, such as obesity to be better understood and monitored. We discover that higher fat and sugar content in bookmarked recipes is associated with higher rates of obesity. The dataset is complicated, but strong temporal and geographical trends are identifiable. We show the importance of accounting for these trends in the modeling process