154 research outputs found

    A Low Cost Synthesis and Characterization of CuO Nanoparticles for Photovoltaic Applications

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    A simple low cost chemical route has been used to synthesize cupric oxide nanoparticles. The synthesized CuO nanoparticles were characterized using XRD, TEM and UV-absorption. X-ray diffraction analysis showed the synthesized nanoparticles to be a pure cupric oxide. EDAX analysis showed the presence of copper and Oxygen in the as prepared CuO nano particles, with the AAS indicating that Cu2+ represented 53.5% of the sample. The particle size and particle size distribution of the cupric oxide nanoparticles were obtained by transmission electron microscopy (TEM) whereas the crystallite size and crystallite size distribution were obtained by X-ray diffraction. The particle size was found to be between 20 nm and 60 nm. The particle size distribution obtained from cumulative percentage frequency plots features a log-normal function. Absorbance measurements and analysis showed that the material has an absorbance peak at 314 nm and energy bandgap of 1.48 eV, making it a good candidate for photovoltaic applications

    Integration of genetics into a systems model of electrocardiographic traits using humanCVD BeadChip

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    <p>Background—Electrocardiographic traits are important, substantially heritable determinants of risk of arrhythmias and sudden cardiac death.</p> <p>Methods and Results—In this study, 3 population-based cohorts (n=10 526) genotyped with the Illumina HumanCVD Beadchip and 4 quantitative electrocardiographic traits (PR interval, QRS axis, QRS duration, and QTc interval) were evaluated for single-nucleotide polymorphism associations. Six gene regions contained single nucleotide polymorphisms associated with these traits at P<10−6, including SCN5A (PR interval and QRS duration), CAV1-CAV2 locus (PR interval), CDKN1A (QRS duration), NOS1AP, KCNH2, and KCNQ1 (QTc interval). Expression quantitative trait loci analyses of top associated single-nucleotide polymorphisms were undertaken in human heart and aortic tissues. NOS1AP, SCN5A, IGFBP3, CYP2C9, and CAV1 showed evidence of differential allelic expression. We modeled the effects of ion channel activity on electrocardiographic parameters, estimating the change in gene expression that would account for our observed associations, thus relating epidemiological observations and expression quantitative trait loci data to a systems model of the ECG.</p> <p>Conclusions—These association results replicate and refine the mapping of previous genome-wide association study findings for electrocardiographic traits, while the expression analysis and modeling approaches offer supporting evidence for a functional role of some of these loci in cardiac excitation/conduction.</p&gt

    Social deprivation and exposure to health promotion. A study of the distribution of health promotion resources to schools in England

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    This article has been made available through the Brunel Open Access Publishing Fund and is available from the specified link - Copyright @ 2010 Chivu and ReidpathBACKGROUND: Area deprivation is a known determinant of health. It is also known that area deprivation is associated with lower impact health promotion. It is less well known, however, whether deprived areas are less responsive to health promotion, or whether they are less exposed. Using data from a national, school-based campaign to promote vaccination against the human papilloma virus (HPV), the relationship between area deprivation and exposure was examined. METHODS: Taking advantage of a health promotion campaign to provide information to schools about HPV vaccination, a cross sectional study was conducted to examine the relationship between area level, social deprivation, and take-up of (i.e., exposure to) available health promotion material. The sample was 4,750 schools across England, including government maintained and independent schools. The relationship between area deprivation and exposure was examined using bi- and multivariate logistic regression. RESULTS: It was found that schools in the least deprived quintile had 1.32 times the odds of requesting health promotion materials than schools in the most deprived areas (p = .01). This effect was independent of the school size, the type of school, and the geographic region. Conclusion The relationship between area deprivation and the impact of health promotion may be due, at least in part, to differential levels of exposure. The study was limited in scope, pointing to the need for more research, but also points to potentially important policy implications

    Predicting heterosis for egg production traits in crossbred offspring of individual White Leghorn sires using genome-wide SNP data

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    International audienceAbstractBackgroundThe development of a reliable method to predict heterosis would greatly improve the efficiency of commercial crossbreeding schemes. Extending heterosis prediction from the line level to the individual sire level would take advantage of variation between sires from the same pure line, and further increase the use of heterosis in crossbreeding schemes. We aimed at deriving the theoretical expectation for heterosis due to dominance in the crossbred offspring of individual sires, and investigating how much extra variance in heterosis can be explained by predicting heterosis at the individual sire level rather than at the line level. We used 53 421 SNP (single nucleotide polymorphism) genotypes of 3427 White Leghorn sires, allele frequencies of six White Leghorn dam-lines and cage-based records on egg number and egg weight of ~210 000 crossbred hens.ResultsWe derived the expected heterosis for the offspring of individual sires as the between- and within-line genome-wide heterozygosity excess in the offspring of a sire relative to the mean heterozygosity of the pure lines. Next, we predicted heterosis by regressing offspring performance on the heterozygosity excess. Predicted heterosis ranged from 7.6 to 16.7 for egg number, and from 1.1 to 2.3 grams for egg weight. Between-line differences accounted for 99.0% of the total variance in predicted heterosis, while within-line differences among sires accounted for 0.7%.ConclusionsWe show that it is possible to predict heterosis at the sire level, thus to distinguish between sires within the same pure line with offspring that show different levels of heterosis. However, based on our data, variation in genome-wide predicted heterosis between sires from the same pure line was small; most differences were observed between lines. We hypothesise that this method may work better if predictions are based on SNPs with identified dominance effects

    Investigating associations between the built environment and physical activity among older people in 20 UK towns.

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    BACKGROUND: Policy initiatives such as WHO Age Friendly Cities recognise the importance of the urban environment for improving health of older people, who have both low physical activity (PA) levels and greater dependence on local neighbourhoods. Previous research in this age group is limited and rarely uses objective measures of either PA or the environment. METHODS: We investigated the association between objectively measured PA (Actigraph GT3x accelerometers) and multiple dimensions of the built environment, using a cross-sectional multilevel linear regression analysis. Exposures were captured by a novel foot-based audit tool that recorded fine-detail neighbourhood features relevant to PA in older adults, and routine data. RESULTS: 795 men and 638 women aged 69-92 years from two national cohorts, covering 20 British towns, were included in the analysis. Median time in moderate to vigorous PA (MVPA) was 27.9 (lower quartile: 13.8, upper quartile: 50.4) minutes per day. There was little evidence of associations between any of the physical environmental domains (eg, road and path quality defined by latent class analysis; number of bus stops; area aesthetics; density of shops and services; amount of green space) and MVPA. However, analysis of area-level income deprivation suggests that the social environment may be associated with PA in this age group. CONCLUSIONS: Although small effect sizes cannot be discounted, this study suggests that older individuals are less affected by their local physical environment and more by social environmental factors, reflecting both the functional heterogeneity of this age group and the varying nature of their activity spaces

    Machine learning approaches classify clinical malaria outcomes based on haematological parameters

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    Background Malaria is still a major global health burden, with more than 3.2 billion people in 91 countries remaining at risk of the disease. Accurately distinguishing malaria from other diseases, especially uncomplicated malaria (UM) from non-malarial infections (nMI), remains a challenge. Furthermore, the success of rapid diagnostic tests (RDTs) is threatened by Pfhrp2/3 deletions and decreased sensitivity at low parasitaemia. Analysis of haematological indices can be used to support the identification of possible malaria cases for further diagnosis, especially in travellers returning from endemic areas. As a new application for precision medicine, we aimed to evaluate machine learning (ML) approaches that can accurately classify nMI, UM, and severe malaria (SM) using haematological parameters. Methods We obtained haematological data from 2,207 participants collected in Ghana: nMI (n = 978), SM (n = 526), and UM (n = 703). Six different ML approaches were tested, to select the best approach. An artificial neural network (ANN) with three hidden layers was used for multi-classification of UM, SM, and uMI. Binary classifiers were developed to further identify the parameters that can distinguish UM or SM from nMI. Local interpretable model-agnostic explanations (LIME) were used to explain the binary classifiers. Results The multi-classification model had greater than 85% training and testing accuracy to distinguish clinical malaria from nMI. To distinguish UM from nMI, our approach identified platelet counts, red blood cell (RBC) counts, lymphocyte counts, and percentages as the top classifiers of UM with 0.801 test accuracy (AUC = 0.866 and F1 score = 0.747). To distinguish SM from nMI, the classifier had a test accuracy of 0.96 (AUC = 0.983 and F1 score = 0.944) with mean platelet volume and mean cell volume being the unique classifiers of SM. Random forest was used to confirm the classifications, and it showed that platelet and RBC counts were the major classifiers of UM, regardless of possible confounders such as patient age and sampling location. Conclusion The study provides proof of concept methods that classify UM and SM from nMI, showing that the ML approach is a feasible tool for clinical decision support. In the future, ML approaches could be incorporated into clinical decision-support algorithms for the diagnosis of acute febrile illness and monitoring response to acute SM treatment particularly in endemic settings

    Investigation of Genetic Resistance to Newcastle Disease in Local Chickens in Tanzania using Natural Challenge by Field Velogenic NDV Strains

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    Genetic resistance to Newcastle disease among three ecotypes of Tanzanian local chickens, Ching’wekwe, Kuchi and Morogoro MEDIUM was investigated by natural challenge with endemic velogenic strains of Newcastle disease virus (vNDV). The study was designed to determine variations in susceptibility and response to NDV among the three ecotypes. Naturally NDV-infected seeders were introduced into flocks of susceptible chickens under a controlled environment. For each bird, body weights were measured at 0, 7, 9, 11, 13, 15, 17, and 25 days post-exposure. Flock mortality was assessed every 8 hours for the first three days and then every 12 hours thereafter until 29 days post-exposure. Date and time of death was recorded, and post-mortem examinations performed for each dead chicken. Lesions on the trachea, proventriculus, intestines, and caecal tonsils were scored for severity ranging from 0 to 3. Linear models were used for survival days, post-exposure growth rate and average lesion score. Preliminary results indicate that post-exposure weight reduction in Ching’wekwe was significantly less than in Morogoro Medium and Kuchi. No significant differences were observed in the lesion scores and survival times among the three ecotypes after exposure. More data is being collected for more comprehensive analysis

    Phenotypic and genotypic diversity of selected Free Range Local Chickens in Tanzania

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    Free range local chickens are an important source of protein as meat and eggs in Tanzania. Few studies have been done to improve their productivity. To this end, this paper focuses on characterizing three common Tanzanian local chicken ecotypes. Morphologic and genetic diversity studies show that the Kuchi have relatively higher body dimension measures than Ching’wekwe and Morogoro medium and that the Ching’wekwe ecotype is genetically more related to Morogoro medium than to the Kuchi ecotype. These differences indicate variation in traits that call for further research and opportunities to improve productivity of free range local chickens

    Plasma urate concentration and risk of coronary heart disease: a Mendelian randomisation analysis.

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    BACKGROUND: Increased circulating plasma urate concentration is associated with an increased risk of coronary heart disease, but the extent of any causative effect of urate on risk of coronary heart disease is still unclear. In this study, we aimed to clarify any causal role of urate on coronary heart disease risk using Mendelian randomisation analysis. METHODS: We first did a fixed-effects meta-analysis of the observational association of plasma urate and risk of coronary heart disease. We then used a conventional Mendelian randomisation approach to investigate the causal relevance using a genetic instrument based on 31 urate-associated single nucleotide polymorphisms (SNPs). To account for potential pleiotropic associations of certain SNPs with risk factors other than urate, we additionally did both a multivariable Mendelian randomisation analysis, in which the genetic associations of SNPs with systolic and diastolic blood pressure, HDL cholesterol, and triglycerides were included as covariates, and an Egger Mendelian randomisation (MR-Egger) analysis to estimate a causal effect accounting for unmeasured pleiotropy. FINDINGS: In the meta-analysis of 17 prospective observational studies (166 486 individuals; 9784 coronary heart disease events) a 1 SD higher urate concentration was associated with an odds ratio (OR) for coronary heart disease of 1·07 (95% CI 1·04-1·10). The corresponding OR estimates from the conventional, multivariable adjusted, and Egger Mendelian randomisation analysis (58 studies; 198 598 individuals; 65 877 events) were 1·18 (95% CI 1·08-1·29), 1·10 (1·00-1·22), and 1·05 (0·92-1·20), respectively, per 1 SD increment in plasma urate. INTERPRETATION: Conventional and multivariate Mendelian randomisation analysis implicates a causal role for urate in the development of coronary heart disease, but these estimates might be inflated by hidden pleiotropy. Egger Mendelian randomisation analysis, which accounts for pleiotropy but has less statistical power, suggests there might be no causal effect. These results might help investigators to determine the priority of trials of urate lowering for the prevention of coronary heart disease compared with other potential interventions. FUNDING: UK National Institute for Health Research, British Heart Foundation, and UK Medical Research Council
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