76 research outputs found

    Association between physical activity and metabolic syndrome: a cross sectional survey in adolescents in Ho Chi Minh City, Vietnam

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    <p>Abstract</p> <p>Background</p> <p>The emerging epidemic of overweight/obesity in adolescents in Ho Chi Minh City, Vietnam underlines the importance of studying the metabolic syndrome in Vietnamese adolescents who are becoming progressively more inactive. No study in Vietnam has examined the association of metabolic syndrome with moderate to vigorous physical activity (PA) levels among adolescents. We aimed to examine this association in a sample of urban adolescents from Ho Chi Minh City.</p> <p>Methods</p> <p>A cross-sectional assessment was conducted in 2007 on a representative sample of 693 high-school students from urban districts in Ho Chi Minh City. Metabolic syndrome was defined according to the International Diabetes Federation criteria and physical activity was measured with Actigraph accelerometers. The association between physical activity and metabolic syndrome was assessed by using multiple logistic regression models.</p> <p>Results</p> <p>Overall 4.6% of the adolescents and 11.8% of the overweight/obese adolescents had metabolic syndrome. Elevated BP was the most common individual component of the metabolic syndrome (21.5%), followed by hypertriglyceridemia (11.1%). After adjusting for other study factors, the odds of metabolic syndrome among youth in the lowest physical activity group (<43 minutes of physical activity/day) were five times higher than those in the highest physical activity group (>103 minutes/day) (AOR = 5.3, 95% CI: 1.5, 19.1). Metabolic syndrome was also positively associated with socioeconomic status (AOR = 9.4, 95% CI: 2.1, 42.4).</p> <p>Conclusions</p> <p>A more physically active lifestyle appears to be associated with a lower odds of metabolic syndrome in Vietnamese adolescents. Socio-economic status should be taken into account when planning interventions to prevent adolescent metabolic syndrome.</p

    Climate Change and the Geographic Distribution of Infectious Diseases

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    Our ability to predict the effects of climate change on the spread of infectious diseases is in its infancy. Numerous, and in some cases conflicting, predictions have been developed, principally based on models of biological processes or mapping of current and historical disease statistics. Current debates on whether climate change, relative to socioeconomic determinants, will be a major influence on human disease distributions are useful to help identify research needs but are probably artificially polarized. We have at least identified many of the critical geophysical constraints, transport opportunities, biotic requirements for some disease systems, and some of the socioeconomic factors that govern the process of migration and establishment of parasites and pathogens. Furthermore, we are beginning to develop a mechanistic understanding of many of these variables at specific sites. Better predictive understanding will emerge in the coming years from analyses regarding how these variables interact with each other

    Lactic Acidosis Triggers Starvation Response with Paradoxical Induction of TXNIP through MondoA

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    Although lactic acidosis is a prominent feature of solid tumors, we still have limited understanding of the mechanisms by which lactic acidosis influences metabolic phenotypes of cancer cells. We compared global transcriptional responses of breast cancer cells in response to three distinct tumor microenvironmental stresses: lactic acidosis, glucose deprivation, and hypoxia. We found that lactic acidosis and glucose deprivation trigger highly similar transcriptional responses, each inducing features of starvation response. In contrast to their comparable effects on gene expression, lactic acidosis and glucose deprivation have opposing effects on glucose uptake. This divergence of metabolic responses in the context of highly similar transcriptional responses allows the identification of a small subset of genes that are regulated in opposite directions by these two conditions. Among these selected genes, TXNIP and its paralogue ARRDC4 are both induced under lactic acidosis and repressed with glucose deprivation. This induction of TXNIP under lactic acidosis is caused by the activation of the glucose-sensing helix-loop-helix transcriptional complex MondoA:Mlx, which is usually triggered upon glucose exposure. Therefore, the upregulation of TXNIP significantly contributes to inhibition of tumor glycolytic phenotypes under lactic acidosis. Expression levels of TXNIP and ARRDC4 in human cancers are also highly correlated with predicted lactic acidosis pathway activities and associated with favorable clinical outcomes. Lactic acidosis triggers features of starvation response while activating the glucose-sensing MondoA-TXNIP pathways and contributing to the “anti-Warburg” metabolic effects and anti-tumor properties of cancer cells. These results stem from integrative analysis of transcriptome and metabolic response data under various tumor microenvironmental stresses and open new paths to explore how these stresses influence phenotypic and metabolic adaptations in human cancers

    Optimal foraging and community structure: implications for a guild of generalist grassland herbivores

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    A particular linear programming model is constructed to predict the diets of each of 14 species of generalist herbivores at the National Bison Range, Montana. The herbivores have body masses ranging over seven orders of magnitude and belonging to two major taxa: insects and mammals. The linear programming model has three feeding constraints: digestive capacity, feeding time and energy requirements. A foraging strategy that maximizes daily energy intake agrees very well with the observed diets. Body size appears to be an underlying determinant of the foraging parameters leading to diet selection. Species that possess digestive capacity and feeding time constraints which approach each other in magnitude have the most generalized diets. The degree that the linear programming models change their diet predictions with a given percent change in parameter values (sensitivity) may reflect the observed ability of the species to vary their diets. In particular, the species which show the most diet variability are those whose diets tend to be balanced between monocots and dicots. The community-ecological parameters of herbivore body-size ranges and species number can possibly be related to foraging behavior.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/47765/1/442_2004_Article_BF00377109.pd

    Neuroinflammation, Neuroautoimmunity, and the Co-Morbidities of Complex Regional Pain Syndrome

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