Nutrient-content and health claims labeling on Oregon restaurant menus

The recency of the Food and Drug Administration menu-labeling regulations and the lack of research available on restaurateur response initiated this study. Advocates claim the new regulations will protect consumers and foster the selection of nutritious choices, however, critics believe the regulations will result in restaurateurs removing all nutrition information from their menus. This research describes Oregon restaurateurs perceptions of the new FDA regulations, current and past experience with nutrition labeling and the impact of the new FDA regulations on their nutrition labeling practices. Study methodology involved a focus group of local restaurateurs and a statewide survey of randomly selected Oregon restaurateurs. A total of 160 questionnaires were returned, representing a 50% response rate. Data analysis included descriptive statistics and associations between variables through use of chi-square analysis. Forty five percent of respondents currently use nutrition labeling, 12% of respondents have past experience with nutrition labeling and 43% of respondents have never used nutrition labeling. The majority of respondents (55%) were interested in learning more about making nutrition claims on their menus. Benefits associated with nutrition labeling included reaching a wider variety of customers, increasing sales, fulfilling customers wishes and satisfying personal beliefs in healthy dining. Lack of customer interest and the new FDA regulations were the most frequently cited factors involved in the decision not to use nutrition labeling. Only 8% of respondents believed the new FDA regulations had affected their operations, however, over one quarter, 27%, of respondents were not even aware of the new FDA regulations. Overall understanding of the new regulations was extremely poor. Professional organizations such as the National Restaurant Association (NRA) are the preferred resource for advice on nutrition labeling of menu items. However, many opportunities exist for dietitians in the area of nutrition and health claims labeling on restaurant menus but before progress can be made, we must aggressively market our services to restaurateurs

Neurofibromin is a novel regulator of Ras-induced reactive oxygen species production in mice and humans

Neurofibromatosis type 1 (NF1) predisposes individuals to early and debilitating cardiovascular disease. Loss of function mutations in the NF1 tumor suppressor gene, which encodes the protein neurofibromin, leads to accelerated p21(Ras) activity and phosphorylation of multiple downstream kinases, including Erk and Akt. Nf1 heterozygous (Nf1(+/-)) mice develop a robust neointima that mimics human disease. Monocytes/macrophages play a central role in NF1 arterial stenosis as Nf1 mutations in myeloid cells alone are sufficient to reproduce the enhanced neointima observed in Nf1(+/-) mice. Though the molecular mechanisms underlying NF1 arterial stenosis remain elusive, macrophages are important producers of reactive oxygen species (ROS) and Ras activity directly regulates ROS production. Here, we use compound mutant and lineage-restricted mice to demonstrate that Nf1(+/-) macrophages produce excessive ROS, which enhance Nf1(+/-) smooth muscle cell proliferation in vitro and in vivo. Further, use of a specific NADPH oxidase-2 inhibitor to limit ROS production prevents neointima formation in Nf1(+/-) mice. Finally, mononuclear cells from asymptomatic NF1 patients have increased oxidative DNA damage, an indicator of chronic exposure to oxidative stress. These data provide genetic and pharmacologic evidence that excessive exposure to oxidant species underlie NF1 arterial stenosis and provide a platform for designing novels therapies and interventions

A global model of the response of tropical and sub-tropical forest biodiversity to anthropogenic pressures

Habitat loss and degradation, driven largely by agricultural expansion and intensification, present the greatest immediate threat to biodiversity. Tropical forests harbour among the highest levels of terrestrial species diversity and are likely to experience rapid land-use change in the coming decades. Synthetic analyses of observed responses of species are useful for quantifying how land use affects biodiversity and for predicting outcomes under land-use scenarios. Previous applications of this approach have typically focused on individual taxonomic groups, analysing the average response of the whole community to changes in land use. Here, we incorporate quantitative remotely sensed data about habitats in, to our knowledge, the first worldwide synthetic analysis of how individual species in four major taxonomic groups—invertebrates, ‘herptiles’ (reptiles and amphibians), mammals and birds—respond to multiple human pressures in tropical and sub-tropical forests. We show significant independent impacts of land use, human vegetation offtake, forest cover and human population density on both occurrence and abundance of species, highlighting the value of analysing multiple explanatory variables simultaneously. Responses differ among the four groups considered, and—within birds and mammals—between habitat specialists and habitat generalists and between narrow-ranged and wide-ranged species

The genomes of two key bumblebee species with primitive eusocial organization

Background: The shift from solitary to social behavior is one of the major evolutionary transitions. Primitively eusocial bumblebees are uniquely placed to illuminate the evolution of highly eusocial insect societies. Bumblebees are also invaluable natural and agricultural pollinators, and there is widespread concern over recent population declines in some species. High-quality genomic data will inform key aspects of bumblebee biology, including susceptibility to implicated population viability threats. Results: We report the high quality draft genome sequences of Bombus terrestris and Bombus impatiens, two ecologically dominant bumblebees and widely utilized study species. Comparing these new genomes to those of the highly eusocial honeybee Apis mellifera and other Hymenoptera, we identify deeply conserved similarities, as well as novelties key to the biology of these organisms. Some honeybee genome features thought to underpin advanced eusociality are also present in bumblebees, indicating an earlier evolution in the bee lineage. Xenobiotic detoxification and immune genes are similarly depauperate in bumblebees and honeybees, and multiple categories of genes linked to social organization, including development and behavior, show high conservation. Key differences identified include a bias in bumblebee chemoreception towards gustation from olfaction, and striking differences in microRNAs, potentially responsible for gene regulation underlying social and other traits. Conclusions: These two bumblebee genomes provide a foundation for post-genomic research on these key pollinators and insect societies. Overall, gene repertoires suggest that the route to advanced eusociality in bees was mediated by many small changes in many genes and processes, and not by notable expansion or depauperation

Structure-Based Predictive Models for Allosteric Hot Spots

In allostery, a binding event at one site in a protein modulates the behavior of a distant site. Identifying residues that relay the signal between sites remains a challenge. We have developed predictive models using support-vector machines, a widely used machine-learning method. The training data set consisted of residues classified as either hotspots or non-hotspots based on experimental characterization of point mutations from a diverse set of allosteric proteins. Each residue had an associated set of calculated features. Two sets of features were used, one consisting of dynamical, structural, network, and informatic measures, and another of structural measures defined by Daily and Gray [1]. The resulting models performed well on an independent data set consisting of hotspots and non-hotspots from five allosteric proteins. For the independent data set, our top 10 models using Feature Set 1 recalled 68–81% of known hotspots, and among total hotspot predictions, 58–67% were actual hotspots. Hence, these models have precision P = 58–67% and recall R = 68–81%. The corresponding models for Feature Set 2 had P = 55–59% and R = 81–92%. We combined the features from each set that produced models with optimal predictive performance. The top 10 models using this hybrid feature set had R = 73–81% and P = 64–71%, the best overall performance of any of the sets of models. Our methods identified hotspots in structural regions of known allosteric significance. Moreover, our predicted hotspots form a network of contiguous residues in the interior of the structures, in agreement with previous work. In conclusion, we have developed models that discriminate between known allosteric hotspots and non-hotspots with high accuracy and sensitivity. Moreover, the pattern of predicted hotspots corresponds to known functional motifs implicated in allostery, and is consistent with previous work describing sparse networks of allosterically important residues

Mutations in the Mitochondrial Methionyl-tRNA Synthetase Cause a Neurodegenerative Phenotype in Flies and a Recessive Ataxia (ARSAL) in Humans

The study of Drosophila neurodegenerative mutants combined with genetic and biochemical analyses lead to the identification of multiple complex mutations in 60 patients with a novel form of ataxia/leukoencephalopathy

The astrobiology primer: An outline of general knowledge - Version 1, 2006

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