268 research outputs found
Associations between fruit and vegetable intake, leisure-time physical activity, sitting time and self-rated health among older adults : cross-sectional data from the WELL study
BackgroundLifestyle behaviours, such as healthy diet, physical activity and sedentary behaviour, are key elements of healthy ageing and important modifiable risk factors in the prevention of chronic diseases. Little is known about the relationship between these behaviours in older adults. The purpose of this study was to explore the relationship between fruit and vegetable (F&V) intake, leisure-time physical activity (LTPA) and sitting time (ST), and their association with self-rated health in older adults.MethodsThis cross-sectional study comprised 3,644 older adults (48% men) aged 55-65 years, who participated in the Wellbeing, Eating and Exercise for a Long Life ("WELL") study. Respondents completed a postal survey about their health and their eating and physical activity behaviours in 2010 (38% response rate). Spearman\u27s coefficient (rho) was used to evaluate the relationship between F&V intake, LTPA and ST. Their individual and shared associations with self-rated health were examined using ordinal logistic regression models, stratified by sex and adjusted for confounders (BMI, smoking, long-term illness and socio-demographic characteristics).ResultsThe correlations between F&V intake, LTPA and ST were low. F&V intake and LTPA were positively associated with self-rated health. Each additional serving of F&V or MET-hour of LTPA were associated with approximately 10% higher likelihood of reporting health as good or better among women and men. The association between ST and self-rated health was not significant in the multivariate analysis. A significant interaction was found (ST*F&V intake). The effect of F&V intake on self-rated health increased with increasing ST in women, whereas the effect decreased with increasing ST in men.ConclusionThis study contributes to the scarce literature related to lifestyle behaviours and their association with health indicators among older adults. The findings suggest that a modest increase in F&V intake, or LTPA could have a marked effect on the health of older adults. Further research is needed to fully understand the correlates and determinants of lifestyle behaviours, particularly sitting time, in this age group
A dietary carbohydrate–gut Parasutterella–human fatty acid biosynthesis metabolic axis in obesity and type 2 diabetes
Recent rodent microbiome experiments suggest that besides Akkermansia, Parasutterella sp. are important in type 2 diabetes and obesity development. In the present translational human study, we aimed to characterize Parasutterella in our European cross-sectional FoCus cohort (n = 1,544) followed by validation of the major results in an independent Canadian cohort (n = 438). In addition, we examined Parasutterella abundance in response to a weight loss intervention (n = 55). Parasutterella was positively associated with BMI and type 2 diabetes independently of the reduced microbiome α/β diversity and low-grade inflammation commonly found in obesity. Nutritional analysis revealed a positive association with the dietary intake of carbohydrates but not with fat or protein consumption. Out of 126 serum metabolites differentially detectable by untargeted HPLC-based MS-metabolomics, L-cysteine showed the strongest reduction in subjects with high Parasutterella abundance. This is of interest, since Parasutterella is a known high L-cysteine consumer and L-cysteine is known to improve blood glucose levels in rodents. Furthermore, metabolic network enrichment analysis identified an association of high Parasutterella abundance with the activation of the human fatty acid biosynthesis pathway suggesting a mechanism for body weight gain. This is supported by a significant reduction of the Parasutterella abundance during our weight loss intervention. Together, these data indicate a role for Parasutterella in human type 2 diabetes and obesity, whereby the link to L-cysteine might be relevant in type 2 diabetes development and the link to the fatty acid biosynthesis pathway for body weight gain in response to a carbohydrate-rich diet in obesity development
Host-microbe-drug-nutrient screen identifies bacterial effectors of metformin therapy
Metformin is the first-line therapy for treating type-2 diabetes and a promising anti-aging drug. We set out to address the fundamental question of how gut microbes and nutrition, key regulators of host physiology, impact the effects of metformin. Combining two tractable genetic models, the bacterium E. coli and the nematode C. elegans, we developed a high-throughput four-way screen to define the underlying host-microbe-drug-nutrient interactions. We show that microbes integrate cues from metformin and the diet through the phosphotransferase signalling pathway that converges on the transcriptional regulator Crp. A detailed experimental characterization of metformin effects downstream of Crp in combination with metabolic modelling of the microbiota in metformin-treated type-2 diabetic patients predicts the production of microbial agmatine, a regulator of metformin effects on host lipid metabolism and lifespan. Our high-throughput screening platform paves the way for identifying exploitable drug-nutrient-microbiome interactions to improve host health and longevity through targeted microbiome therapie
Crystalline Arrays of Pairs of Molecular Rotors: Correlated Motion, Rotational Barriers, and Space-Inversion Symmetry Breaking Due to Conformational Mutations
The rod-like molecule bis 4-(4-pyridyl)ethynyl)bicyclo[2.2.2]oct-1-yl)buta-1,3-diyne, 1, contains two 1,4-bis(ethynyl)bicyclo[2.2.2]octane (ethynyl) chiral rotators linked by a diyne fragment and self assembles in a one-dimensional, monoclinic C2/c centrosymmetric structure where two equilibrium positions with large occupancy imbalance (88% versus 12%) are identified on a single rotor site Combining variable temperature (70-300 K) proton spin-lattice relaxation, H-1 T-1(-1), at two different H-1 Larmor frequencies (55 and 210 MHz) and DFT calculations of rotational barriers, we were able to assign two types of Brownian rotators with different activation energies, 1.85 and 6.1 kcal mol(-1), to the two H-1 spin-lattice relaxation processes on the single rotor site. On the basis of DFT calculations, the low-energy process has been assigned to adjacent rotors in a well-correlated synchronous motion, whereas the high-energy process is the manifestation of an abrupt change in their kinematics once two blades of adjacent rotors are seen to rub together. Although crystals of 1 should be second harmonic inactive, a large second-order optical response is recorded when the electric field oscillates in a direction parallel to the unique rotor axle director. We conclude that conformational mutations by torsional interconversion of the three blades of the BCO units break space-inversion symmetry in sequences of mutamers in dynamic equilibrium in the crystal in domains at a rnesoscopic scale comparable with the wavelength of light used A control experiment was performed with a crystalline film of a similar tetrayne molecule, 1,4-bis(3-((trimethylsilyl)ethynyl)bicyclo-[1.1.1]pent-1-yObuta-1,3-diyne, whose bic-ydopentane units can rotate but are achiral and produce no second-order optical response
Identification of metabolic engineering targets through analysis of optimal and sub-optimal routes
Identification of optimal genetic manipulation strategies for redirecting substrate uptake towards a desired product is a challenging task owing to the complexity of metabolic networks, esp. in terms of large number of routes leading to the desired product. Algorithms that can exploit the whole range of optimal and suboptimal routes for product formation while respecting the biological objective of the cell are therefore much needed. Towards addressing this need, we here introduce the notion of structural flux, which is derived from the enumeration of all pathways in the metabolic network in question and accounts for the contribution towards a given biological objective function. We show that the theoretically estimated structural fluxes are good predictors of experimentally measured intra-cellular fluxes in two model organisms, namely, Escherichia coli and Saccharomyces cerevisiae. For a small number of fluxes for which the predictions were poor, the corresponding enzyme-coding transcripts were also found to be distinctly regulated, showing the ability of structural fluxes in capturing the underlying regulatory principles. Exploiting the observed correspondence between in vivo fluxes and structural fluxes, we propose an in silico metabolic engineering approach, iStruF, which enables the identification of gene deletion strategies that couple the cellular biological objective with the product flux while considering optimal as well as sub-optimal routes and their efficiency.This work was supported by the Portuguese Science Foundation [grant numbers MIT-Pt/BS-BB/0082/2008, SFRH/BPD/44180/2008 to ZS] (http://www.fct.pt/). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript
Expression of estrogen receptor beta in the breast carcinoma of BRCA1 mutation carriers
<p>Abstract</p> <p>Background</p> <p>Breast cancers (BC) in women carrying mutations in BRCA1 gene are more frequently estrogen receptor negative than the nonhereditary BC. Nevertheless, tamoxifen has been found to have a protective effect in preventing contralateral tumors in BRCA1 mutation carriers. The identification of the second human estrogen receptor, ERβ, raised a question of its role in hereditary breast cancer. The aim of this study was to assess the frequency of ERα, ERβ, PgR (progesterone receptor) and HER-2 expression in breast cancer patients with mutated <it>BRCA1 </it>gene and in the control group.</p> <p>Methods</p> <p>The study group consisted of 48 women with <it>BRCA1 </it>gene mutations confirmed by multiplex PCR assay. The patients were tested for three most common mutations of BRCA1 affecting the Polish population (5382insC, C61G, 4153delA). Immunostaining for ERα, ERβ and PgR (progesterone receptor) was performed using monoclonal antibodies against ERα, PgR (DakoCytomation), and polyclonal antibody against ERβ (Chemicon). The EnVision detection system was applied. The study population comprised a control group of 120 BC operated successively during the years 1998–99.</p> <p>Results</p> <p>The results of our investigation showed that <it>BRCA1 </it>mutation carriers were more likely to have ERα-negative breast cancer than those in the control group. Only 14.5% of <it>BRCA1</it>-related cancers were ERα-positive compared with 57.5% in the control group (<it>P </it>< 0.0001). On the contrary, the expression of ERβ protein was observed in 42% of <it>BRCA1</it>-related tumors and in 55% of the control group. An interesting finding was that most hereditary cancers (75% of the whole group) were triple-negative: ERα(-)/PgR(-)/HER-2(-) but almost half of this group (44.4%) showed the expression of ERβ.</p> <p>Conclusion</p> <p>In the case of <it>BRCA1</it>-associated tumors the expression of ERβ was significantly higher than the expression of ERα. This may explain the effectiveness of tamoxifen in preventing contralateral breast cancer development in <it>BRCA1 </it>mutation carriers.</p
Chlamydiosis in British Garden Birds (2005–2011): Retrospective Diagnosis and Chlamydia psittaci Genotype Determination
Aging Skin: Nourishing from the Inside Out, Effects of Good Versus Poor Nitrogen Intake on Skin Health and Healing
Skin is the outermost defense organ which protects us from the environment, constituting around 8 % of an adult’s body weight. Healthy skin contains one-eighth of the body’s total proteins. The balance of turnover and synthesis of skin proteins is primarily dependent on the availability of sufficient nitrogen-containing substrates, namely, amino acids, essential for protein metabolism in any other tissue and body organs. The turnover of skin proteins has been shown to be rapid, and the mobilization of amino acids at the expense of skin proteins is relevant in experimental models of protein malnutrition. As a result, alterations in nutritional status should be suspected, diagnosed, and eventually treated for any skin lesions. Protein malnutrition has a dramatic prevalence in patients aged >70 or more, independent of the reason for hospitalization. The quality of nutrition and content of essential amino acids are strictly connected to skin health and integrity of its protein components. Collagen fiber deposition is highly and rapidly influenced by alterations in the essential to nonessential amino acid ratios. The most relevant nutritional factor of skin health is the prevalence of essential amino acids
Meneco, a Topology-Based Gap-Filling Tool Applicable to Degraded Genome-Wide Metabolic Networks
International audienceIncreasing amounts of sequence data are becoming available for a wide range of non-model organisms. Investigating and modelling the metabolic behaviour of those organisms is highly relevant to understand their biology and ecology. As sequences are often incomplete and poorly annotated, draft networks of their metabolism largely suffer from incompleteness. Appropriate gap-filling methods to identify and add missing reactions are therefore required to address this issue. However, current tools rely on phenotypic or taxonomic information, or are very sensitive to the stoichiometric balance of metabolic reactions, especially concerning the co-factors. This type of information is often not available or at least prone to errors for newly-explored organisms. Here we introduce Meneco, a tool dedicated to the topological gap-filling of genome-scale draft metabolic networks. Meneco reformulates gap-filling as a qualitative combinatorial optimization problem, omitting constraints raised by the stoichiometry of a metabolic network considered in other methods, and solves this problem using Answer Set Programming. Run on several artificial test sets gathering 10,800 degraded Escherichia coli networks Meneco was able to efficiently identify essential reactions missing in networks at high degradation rates, outperforming the stoichiometry-based tools in scalability. To demonstrate the utility of Meneco we applied it to two case studies. Its application to recent metabolic networks reconstructed for the brown algal model Ectocarpus siliculosus and an associated bacterium Candidatus Phaeomarinobacter ectocarpi revealed several candidate metabolic pathways for algal-bacterial interactions. Then Meneco was used to reconstruct, from transcriptomic and metabolomic data, the first metabolic network for the microalga Euglena mutabilis. These two case studies show that Meneco is a versatile tool to complete draft genome-scale metabolic networks produced from heterogeneous data, and to suggest relevant reactions that explain the metabolic capacity of a biological system
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