Is dietary zinc protective for type 2 diabetes? Results from the Australian longitudinal study on women's health

Background: Animal studies have shown that zinc intake has protective effects against type 2 diabetes, but few studies have been conducted to examine this relationship in humans. The aim of this study is to investigate if dietary zinc is associated with risk of type 2 diabetes in a longitudinal study of mid-age Australian women. Methods: Data were collected from a cohort of women aged 45-50 years at baseline, participating in the Australian Longitudinal Study on Women's Health. A validated food frequency questionnaire was used to assess dietary intake and other nutrients. Predictors of 6-year incidence of type 2 diabetes were examined using multivariable logistic regression. Results: From 8921 participants, 333 incident cases of type 2 diabetes were identified over 6 years of follow-up. After adjustment for dietary and non-dietary factors, the highest quintile dietary zinc intake had almost half the odds of developing type 2 diabetes (OR = 0.50, 95% C.I. 0.32-0.77) compared with the lowest quintile. Similar findings were observed for the zinc/iron ratio; the highest quintile had half the odds of developing type 2 diabetes (OR = 0.50, 95% C.I 0.30-0.83) after multivariable adjustment of covariates. Conclusions: Higher total dietary zinc intake and high zinc/iron ratio are associated with lower risk of type 2 diabetes in women. This finding is a positive step towards further research to determine if zinc supplementation may reduce the risk of developing type 2 diabetes. © 2013 Vashum et al.; licensee BioMed Central Ltd

The Effect of Arsenic Mitigation Interventions on Disease Burden in Bangladesh

Many interventions have been advocated to mitigate the impact of arsenic contamination of drinking water in Bangladesh. However, there are few data on the true magnitude of arsenic-related disease in Bangladesh nationally. There has also been little consideration given to possible adverse effects of such interventions, in particular, diarrheal disease. The purpose of this study was to estimate and compare the likely impacts of arsenic mitigation interventions on both arsenic-related disease and water-borne infectious disease. We found that arsenic-related disease currently results in 9,136 deaths per year and 174,174 disability-adjusted life years (DALYs; undiscounted) lost per year in those exposed to arsenic concentrations > 50 μg/L. This constitutes 0.3% of the total disease burden in Bangladesh in terms of undiscounted DALYs. We found intervention to be of overall benefit in reducing disease burden in most scenarios examined, but the concomitant increase in water-related infectious disease significantly reduced the potential benefits gained from intervention. A minimum reduction in arsenic-related DALYs of 77% was necessary before intervention achieved any reduction in net disease burden. This is assuming that interventions were provided to those exposed to > 50 μg/L and would concomitantly result in a 20% increase in water-related infectious disease in those without access to adequate sanitation. Intervention appears to be justified for those populations exposed to high levels of arsenic, but it must be based on exposure levels and on the effectiveness of interventions not only in reducing arsenic but in minimizing risk of water-related infections

Topological confinement in an antisymmetric potential in bilayer graphene in the presence of a magnetic field

We investigate the effect of an external magnetic field on the carrier states that are localized at a potential kink and a kink-antikink in bilayer graphene. These chiral states are localized at the interface between two potential regions with opposite signs

Lung function in adults following in utero and childhood exposure to arsenic in drinking water: preliminary findings

PurposeEvidence suggests that arsenic in drinking water causes non-malignant lung disease, but nearly all data concern exposed adults. The desert city of Antofagasta (population 257,976) in northern Chile had high concentrations of arsenic in drinking water (>800 μg/l) from 1958 until 1970, when a new treatment plant was installed. This scenario, with its large population, distinct period of high exposure, and accurate data on past exposure, is virtually unprecedented in environmental epidemiology. We conducted a pilot study on early-life arsenic exposure and long-term lung function. We present these preliminary findings because of the magnitude of the effects observed.MethodsWe recruited a convenience sample consisting primarily of nursing school employees in Antofagasta and Arica, a city with low drinking water arsenic. Lung function and respiratory symptoms in 32 adults exposed to >800 μg/l arsenic before age 10 were compared to 65 adults without high early-life exposure.ResultsEarly-life arsenic exposure was associated with 11.5% lower forced expiratory volume in 1 s (FEV(1)) (P = 0.04), 12.2% lower forced vital capacity (FVC) (P = 0.04), and increased breathlessness (prevalence odds ratio = 5.94, 95% confidence interval 1.36-26.0). Exposure-response relationships between early-life arsenic concentration and adult FEV(1) and FVC were also identified (P trend = 0.03).ConclusionsEarly-life exposure to arsenic in drinking water may have irreversible respiratory effects of a magnitude similar to smoking throughout adulthood. Given the small study size and non-random recruitment methods, further research is needed to confirm these findings

Properties of Graphene: A Theoretical Perspective

In this review, we provide an in-depth description of the physics of monolayer and bilayer graphene from a theorist's perspective. We discuss the physical properties of graphene in an external magnetic field, reflecting the chiral nature of the quasiparticles near the Dirac point with a Landau level at zero energy. We address the unique integer quantum Hall effects, the role of electron correlations, and the recent observation of the fractional quantum Hall effect in the monolayer graphene. The quantum Hall effect in bilayer graphene is fundamentally different from that of a monolayer, reflecting the unique band structure of this system. The theory of transport in the absence of an external magnetic field is discussed in detail, along with the role of disorder studied in various theoretical models. We highlight the differences and similarities between monolayer and bilayer graphene, and focus on thermodynamic properties such as the compressibility, the plasmon spectra, the weak localization correction, quantum Hall effect, and optical properties. Confinement of electrons in graphene is nontrivial due to Klein tunneling. We review various theoretical and experimental studies of quantum confined structures made from graphene. The band structure of graphene nanoribbons and the role of the sublattice symmetry, edge geometry and the size of the nanoribbon on the electronic and magnetic properties are very active areas of research, and a detailed review of these topics is presented. Also, the effects of substrate interactions, adsorbed atoms, lattice defects and doping on the band structure of finite-sized graphene systems are discussed. We also include a brief description of graphane -- gapped material obtained from graphene by attaching hydrogen atoms to each carbon atom in the lattice.Comment: 189 pages. submitted in Advances in Physic

A process evaluation of a "physical activity pathway" in the primary care setting

<p>Abstract</p> <p>Background</p> <p>Let's Get Moving (LGM) is a systematic approach to integrating physical activity promotion into the primary care setting. LGM combines a number of recommended strategies to support behavior change including brief interventions, goal-setting, written resources, and follow-up support. This study involved a process evaluation of implementing LGM in UK general practice.</p> <p>Methods</p> <p>The LGM intervention was implemented in six general practices in London. Practices recruited patients either 'opportunistically' in routine consultations or by letter of invitation sent to patients on the hypertension disease register. A key component of the intervention was the delivery of a brief counselling session aimed at facilitating physical activity behaviour change. Data collection methods included electronic patient records, a practice survey and focus groups and interviews with practitioners.</p> <p>Results</p> <p>A total of 526 patients were considered for LGM, 378 via the 'opportunistic' recruitment method and 148 using the disease register approach. Patient interest in the brief counselling session was high although the actual delivery style and content varied between practitioners. Patients were directed towards a variety of physical activity opportunities including local leisure services and walking schemes.</p> <p>Conclusion</p> <p>The learning from this pilot should inform a revised update of the LGM protocols before the planned dissemination of the intervention which is outlined in the Governments 'Be Active, Be Healthy' physical activity strategy. A robust assessment of effectiveness involving an experimental design and behaviour change measures is also warranted prior to wider dissemination.</p

Category label and response location shifts in category learning

The category shift literature suggests that rule-based classification, an important form of explicit learning, is mediated by two separate learned associations: a stimulus-to-label association that associates stimuli and category labels, and a label-to-response association that associates category labels and responses. Three experiments investigate whether information–integration classification, an important form of implicit learning, is also mediated by two separate learned associations. Participants were trained on a rule-based or an information–integration categorization task and then the association between stimulus and category label, or between category label and response location was altered. For rule-based categories, and in line with previous research, breaking the association between stimulus and category label caused more interference than breaking the association between category label and response location. However, no differences in recovery rate emerged. For information–integration categories, breaking the association between stimulus and category label caused more interference and led to greater recovery than breaking the association between category label and response location. These results provide evidence that information–integration category learning is mediated by separate stimulus-to-label and label-to-response associations. Implications for the neurobiological basis of these two learned associations are discussed

Prediction of catalytic residues using Support Vector Machine with selected protein sequence and structural properties

BACKGROUND: The number of protein sequences deriving from genome sequencing projects is outpacing our knowledge about the function of these proteins. With the gap between experimentally characterized and uncharacterized proteins continuing to widen, it is necessary to develop new computational methods and tools for functional prediction. Knowledge of catalytic sites provides a valuable insight into protein function. Although many computational methods have been developed to predict catalytic residues and active sites, their accuracy remains low, with a significant number of false positives. In this paper, we present a novel method for the prediction of catalytic sites, using a carefully selected, supervised machine learning algorithm coupled with an optimal discriminative set of protein sequence conservation and structural properties. RESULTS: To determine the best machine learning algorithm, 26 classifiers in the WEKA software package were compared using a benchmarking dataset of 79 enzymes with 254 catalytic residues in a 10-fold cross-validation analysis. Each residue of the dataset was represented by a set of 24 residue properties previously shown to be of functional relevance, as well as a label {+1/-1} to indicate catalytic/non-catalytic residue. The best-performing algorithm was the Sequential Minimal Optimization (SMO) algorithm, which is a Support Vector Machine (SVM). The Wrapper Subset Selection algorithm further selected seven of the 24 attributes as an optimal subset of residue properties, with sequence conservation, catalytic propensities of amino acids, and relative position on protein surface being the most important features. CONCLUSION: The SMO algorithm with 7 selected attributes correctly predicted 228 of the 254 catalytic residues, with an overall predictive accuracy of more than 86%. Missing only 10.2% of the catalytic residues, the method captures the fundamental features of catalytic residues and can be used as a "catalytic residue filter" to facilitate experimental identification of catalytic residues for proteins with known structure but unknown function

Push-out bond strength of fiber posts to root dentin using glass ionomer and resin modified glass ionomer cements

OBJECTIVE: The purpose of this study was to assess the push-out bond strength of glass fiber posts to root dentin after cementation with glass ionomer (GICs) and resinmodified glass ionomer cements (RMGICs). MATERIAL AND METHODS: Fifty human maxillary canines were transversally sectioned at 15 mm from the apex. Canals were prepared with a step back technique until the application of a #55 K-file and filled. Post spaces were prepared and specimens were divided into five groups according to the cement used for post cementation: Luting & Lining Cement; Fuji II LC Improved; RelyX Luting; Ketac Cem; and Ionoseal. After cementation of the glass fiber posts, all roots were stored at 100% humidity until testing. For push-out test, 1-mm thick slices were produced. The push-out test was performed in a universal testing machine at a crosshead speed of 0.5 mm/minute and the values (MPa) were analyzed by Kolmogorov-Smirnov and Levene's tests and by two-way ANOVA and Tukey's post hoc test at a significance level of 5%. RESULTS: Fiber posts cemented using Luting & Lining Cement, Fuji II LC Improved, and Ketac Cem presented the highest bond strength to root dentin, followed by RelyX Luting. Ionoseal presented the lowest bond strength values (P>0.05). The post level did not influence the bond strength of fiber posts to root dentin (P=0.148). The major cause of failure was cohesive at the cement for all GICs and RMGICs. CONCLUSIONS: Except for Ionoseal, all cements provided satisfactory bond strength values