Startling Sweet Temptations: Hedonic Chocolate Deprivation Modulates Experience,Eating Behavior,and Eyeblink Startle

Many individuals restrict their food intake to prevent weight gain. This restriction has both homeostatic and hedonic effects but their relative contribution is currently unclear. To isolate hedonic effects of food restriction, we exposed regular chocolate eaters to one week of chocolate deprivation but otherwise regular eating. Before and after this hedonic deprivation, participants viewed images of chocolate and images of high-calorie but non-chocolate containing foods, while experiential, behavioral and eyeblink startle responses were measured. Compared to satiety, hedonic deprivation triggered increased chocolate wanting, liking, and chocolate consumption but also feelings of frustration and startle potentiation during the intertrial intervals. Deprivation was further characterized by startle inhibition during both chocolate and food images relative to the intertrial intervals. Individuals who responded with frustration to the manipulation and those who scored high on a questionnaire of impulsivity showed more relative startle inhibition. The results reveal the profound effects of hedonic deprivation on experiential, behavioral and attentional/appetitive response systems and underscore the role of individual differences and state variables for startle modulation. Implications for dieting research and practice as well as for eating and weight disorders are discussed.     

Optimizing purebred selection for crossbred performance using QTL with different degrees of dominance

A method was developed to optimize simultaneous selection for a quantitative trait with a known QTL within a male and a female line to maximize crossbred performance from a two-way cross. Strategies to maximize cumulative discounted response in crossbred performance over ten generations were derived by optimizing weights in an index of a QTL and phenotype. Strategies were compared to selection on purebred phenotype. Extra responses were limited for QTL with additive and partial dominance effects, but substantial for QTL with over-dominance, for which optimal QTL selection resulted in differential selection in male and female lines to increase the frequency of heterozygotes and polygenic responses. For over-dominant QTL, maximization of crossbred performance one generation at a time resulted in similar responses as optimization across all generations and simultaneous optimal selection in a male and female line resulted in greater response than optimal selection within a single line without crossbreeding. Results show that strategic use of information on over-dominant QTL can enhance crossbred performance without crossbred testing.     

Modulation of social interactions by immune stimulation in honey bee, <Emphasis Type="Italic">Apis mellifera</Emphasis>, workers

Background  

Immune response pathways have been relatively well-conserved across animal species, with similar systems in both mammals and invertebrates. Interestingly, honey bees have substantially reduced numbers of genes associated with immune function compared with solitary insect species. However, social species such as honey bees provide an excellent environment for pathogen or parasite transmission with controlled environmental conditions in the hive, high population densities, and frequent interactions. This suggests that honey bees may have developed complementary mechanisms, such as behavioral modifications, to deal with disease.     

Flying lemurs – The 'flying tree shrews'? Molecular cytogenetic evidence for a Scandentia-Dermoptera sister clade

Background  

Flying lemurs or Colugos (order Dermoptera) represent an ancient mammalian lineage that contains only two extant species. Although molecular evidence strongly supports that the orders Dermoptera, Scandentia, Lagomorpha, Rodentia and Primates form a superordinal clade called Supraprimates (or Euarchontoglires), the phylogenetic placement of Dermoptera within Supraprimates remains ambiguous.     

A study on the minimum number of loci required for genetic evaluation using a finite locus model

For a finite locus model, Markov chain Monte Carlo (MCMC) methods can be used to estimate the conditional mean of genotypic values given phenotypes, which is also known as the best predictor (BP). When computationally feasible, this type of genetic prediction provides an elegant solution to the problem of genetic evaluation under non-additive inheritance, especially for crossbred data. Successful application of MCMC methods for genetic evaluation using finite locus models depends, among other factors, on the number of loci assumed in the model. The effect of the assumed number of loci on evaluations obtained by BP was investigated using data simulated with about 100 loci. For several small pedigrees, genetic evaluations obtained by best linear prediction (BLP) were compared to genetic evaluations obtained by BP. For BLP evaluation, used here as the standard of comparison, only the first and second moments of the joint distribution of the genotypic and phenotypic values must be known. These moments were calculated from the gene frequencies and genotypic effects used in the simulation model. BP evaluation requires the complete distribution to be known. For each model used for BP evaluation, the gene frequencies and genotypic effects, which completely specify the required distribution, were derived such that the genotypic mean, the additive variance, and the dominance variance were the same as in the simulation model. For lowly heritable traits, evaluations obtained by BP under models with up to three loci closely matched the evaluations obtained by BLP for both purebred and crossbred data. For highly heritable traits, models with up to six loci were needed to match the evaluations obtained by BLP.     

Influence of miRNA-106b and miRNA-135a on butyrate-regulated expression of p21 and Cyclin D2 in human colon adenoma cells

Epigenetic and posttranslational modifications of the expression of cell cycle-relevant genes or proteins like p21, e.g., by miRNAs are crucial mechanisms in the development or prevention of colon cancer. The present study investigated the influence of butyrate and trichostatin A (TSA) as histone deacetylase inhibitors on the expression of colon cancer-relevant miRNA (miR-135a, miR-135b, miR-24, miR-106b, miR-let-7a) in LT97 colon adenoma cells as a model of an early stage of colon carcinogenesis. The impact of distinct miRNAs (miR-106b, miR-135a) on butyrate-mediated regulation of p21 and Cyclin D2 gene and protein expression as well as the effect on LT97 cell proliferation (non-transfected, miR-106b and miR-135a mimic transfected) was analyzed. Butyrate and partial TSA reduced the expression of miR-135a, miR-135b, miR-24 and miR-let-7a (~0.5-fold, 24 h) and miR-24, miR-106b and miR-let-7a (~0.5–0.7-fold, 48 h) in LT97 cells. Levels of p21 mRNA and protein were significantly increased by butyrate and TSA (~threefold and 4.5-fold, respectively, 24 h) in non-transfected but not in miR-106b transfected LT97 cells. Levels of Cyclin D2 mRNA were significantly reduced by butyrate and TSA (~0.3-fold, 24 h) in non-transfected and miR-135a-transfected LT97 cells, whereas protein levels were predominantly not influenced. MiR-106b and miR-135a significantly reduced butyrate-/TSA-mediated inhibition of LT97 cell proliferation (72 h). These results indicate that butyrate is able to modify colon cancer-relevant miRNAs like miR-106b and miR-135a which are involved in the regulation of cell cycle-relevant genes like p21 and might influence inhibition of adenoma cell proliferation.

Electronic supplementary material

The online version of this article (doi:10.1007/s12263-015-0500-4) contains supplementary material, which is available to authorized users.