250 research outputs found
The effectiveness of nutrition education and labeling in Dutch supermarkets
No full textThe effectiveness of nutrition education and labeling in Dutch supermarkets. Steenhuis I, van Assema P, van Breukelen G, Glanz K. Department of Psychology, Open University, PO Box 2960, 6401 DL Heerlen, The Netherlands. PURPOSE: Nutrition education and labeling may help consumers to eat less fat. The purpose of this study is to assess the effect of nutrition education with and without shelf labeling on reduced fat intake in Dutch supermarkets. METHODS: The design consisted of a randomized, pretest-posttest, experimental control group design. In total, 2203 clients of 13 supermarkets were included in the sample. Total fat intake of clients and behavioral determinants of eating less fat were measured by a questionnaire. A mixed-effect regression model was used for the analysis. RESULTS: No significant effects were found for the educational intervention, alone or with the labeling, on total fat intake and the psychosocial determinants of eating less fat. CONCLUSION: Nutrition education and labeling of low-fat food products in supermarkets did not prove to be effective strategies. The fact that the supermarket is a highly competitive environment may have accounted for this lack of effect
High confidence and sensitivity four-dimensional fractionation for human plasma proteome analysis.
No full textReducing the complexity of plasma proteome through complex multidimensional fractionation protocols is critical for the detection of low abundance proteins that have the potential to be the most specific disease biomarkers. Therefore, we examined a four dimension profiling method, which includes low abundance protein enrichment, tryptic digestion and peptide fractionation by IEF, SCX and RP-LC. The application of peptide pI filtering as an additional criterion for the validation of the identifications allows to minimize the false discovery rate and to optimize the best settings of the protein identification database search engine. This sequential approach allows for the identification of low abundance proteins, such as angiogenin (10(-9) g/L), pigment epithelium growth factor (10(-8) g/L), hepatocyte growth factor activator (10(-7) g/L) and thrombospondin-1 (10(-6) g/L), having concentrations similar to those of many other growth factors and cytokines involved in disease pathophysiolog
Integrating Enzyme-Based Kinetics in Reactive Transport Models to Simulate Spatiotemporal Dynamics of Biomarkers during Chlorinated Ethene Degradation
No full textBiomarkers such as functional gene mRNA (transcripts) and proteins (enzymes) provide direct proof of metabolic regulation during the reductive dechlorination (RD) of chlorinated ethenes (CEs). Yet, current models to simulate their spatiotemporal variability are not flexible enough to mimic the homologous behavior of RDase functional genes. To this end, we developed new enzyme-based kinetics to model the concentrations of CEs together with the transcript and enzyme levels during RD. First, the model was calibrated to existing microcosm data on RD of cis-DCE. The model mirrored the tceA and vcrA gene expression and the production of their enzymes in Dehalococcoides spp. Considering tceA and vcrA as homologous instead of nonhomologous improved fitting of the mRNA time series. Second, CEs and biomarker patterns were explored as a proof of concept under groundwater flow conditions, considering degraders occurring in immobile and mobile states. Under both microcosm and flow conditions, biomarker-rate relationships were nonlinear hysteretic because tceA and vcrA acted as homologous genes. The mobile biomarkers additionally undergo advective-dispersive transport, which increases the nonlinearity and makes the observed patterns even more challenging to interpret. The model offers a thorough mechanistic description of RD while also allowing simulation of spatiotemporal dynamic patterns of various key biomarkers in aquifers
Phosphate Removal from Wastewater by Mineral Wool Filters
No full textAccording to the United Nations, eutrophication is the most prevalent water quality problem. Developing countries especially are struggling to manage the increasing volume of untreated wastewater. A preliminary study of a Dutch-Indian partnership, developing universal watermanagement (LOTUSHR), has shown some indication of ortho-phosphate removal by mineral wool. The objective of this research is to understand the ortho-phosphate removal mechanism of mineral wool used for wastewater treatment. It was hypothesized that mineral wool dissociates ions due to biologically mediated pH changes, which subsequently interact with ortho-phosphate, forming minerals and removing ortho-phosphate from wastewater. First of all, the chemical composition of mineral wool was determined. Secondly, the dissolution of mineral wool was quantified by batch experiments at different pH and phosphate concentrations. Furthermore, geochemical modeling with PHREEQC was used to analyze the thermodynamic potential of wastewaters to precipitation, not containing mineral wool. Additionally, the phosphate removal rates of a flow-through experiment, using mimicked Indian Drain Water and mineral wool, was compared with PHREEQC simulations. Results showed that based on chemical analysis mineral wool contains: 188.0 g/kg silicon, 187.6 g/kg calcium, 79.3 g/kg aluminum, 43.1 g/kg iron, among other elements. The mineral wool showed no significant dissolution of ions under different pH and phosphate concentrations. Therefore, the hypothesis was rejected, as the mineral wool did not release ions when stressed with different pH. Consequently, biological conversion will not facilitate ion release from the mineral wool either. The mineral wool did show a self-buffering effect, due to its alkaline properties. Furthermore, with use of PHREEQC, amorphous tricalcium phosphate was characterized as the major mineral phase. In conclusion, the hypothesis formulated was rejected. This research performed did not lead to the identification of the removal mechanism responsible for the ortho-phosphate removal from wastewater by mineral wool filters.LOTUS-HRCivil Engineering | Environmental Engineerin
The luminosity function of Lyα emitters at 2.3 < z < 4.6 from integral-field spectroscopy
No full textWe have used Visible MultiObject Spectrograph Integral-Field Unit observations centred on a radio galaxy at z= 2.9 to search for Lyα emitters within a comoving volume of ∼104 Mpc3 . We find 14 Lyα emitters with flux >1.4 × 10−20 W m−2 , yielding a comoving space density of 0.0018+0.0006−0.0005 Mpc−3 . We fit a Schechter luminosity function that agrees well with previous studies both at similar redshift (z∼ 3.4) and higher redshift (z∼ 5.7) . We therefore find no evidence for evolution in the properties of Lyα emitters between 3 < z < 6 , although our sample is small. By summing the star-formation rates of the individual Lyα emitters we find a total cosmic star-formation rate density of ρSFR= 6.7 ± 0.5 × 10−3 M⊙ yr−1 Mpc−3 . Integrating over the luminosity function for the combined Lyα surveys at z∼ 3.4 and accounting for the difference in obscuration between the Lyα line and the ultraviolet-continuum yields an estimate of ρSFR∼ 2.2 × 10−2 M⊙ yr−1 Mpc−3 , in line with previous multi-colour and narrow-band surveys of high-redshift star-forming galaxies. The detection of high-redshift emission-line galaxies in our volumetric search shows that the unique capabilities of wide-field integral-field spectroscopy are well suited to searching for high-redshift galaxies in a relatively unbiased manner
Statistical Validation of Surrogate Markers in Clinical Trials
No full textThe increasing cost of drug development has raised the demand on the use of biomarkers as surrogate endpoints for the evaluation of new drugs in clinical trials. However, failed past attempts to use surrogate endpoints made it clear that, before deciding on the use of a candidate surrogate endpoint, it is of the utmost importance to investigate its validity. Such validation process has proven challenging for conceptual and practical reasons. In the present chapter, some of the statistical methods introduced for the evaluation of surrogate markers will be discussed. Emphasis will be made on the so-called meta-analytic approach and its information-theoretic version, where information from several units is combined to carry out the validation exercise. The methods will be illustrated using a case study in ophthalmology
Some problems encountered in surgical treatment of reticuloperitonitis traumatica in bovines.
No full textBastawi (lia shed Helmy).Diss. Utrecht
Spectroscopic follow-up of a cluster candidate at z = 1.45
Full text linkWe have obtained deep optical spectroscopic data of the highest-redshift cluster candidate (z ~ 1.4, CVB13) selected by Van Breukelen et al. (2006) in a photometric optical/infrared catalogue of the Subaru XMM-Newton Deep Field. The data, which comprise 104 targeted galaxies, were taken with the DEep Imaging Multi-Object Spectrograph (DEIMOS) on the Keck 2 telescope and yielded 31 secure redshifts in the range 1.25 10^14 M_sun and it may therefore be termed a cluster. There is an X-ray source at the cluster position which is marginally spatially resolved but whose X-ray spectrum is too hard to be thermal cluster emission. Its origin could be the summed X-ray emission from active galaxies in, and projected onto, the cluster. Serendipitously we have discovered a cluster at z = 1.28 with a mass of > 10^14 M_sun at the same position on the sky, comprising six spectroscopically confirmed cluster galaxies and at least one additional radio source. The selection of CVB13 for the cluster catalogue was evidently aided by the superposition of other, presumably lower-mass, structures, whereas the single cluster at z = 1.28 contained too few galaxies to be isolated by the same algorithm. Given the complicated nature of such structures, caution must be employed when measuring the mass function of putative high-redshift clusters with photometric techniques alone
Sample size calculation for treatment effects in randomized trials with fixed cluster sizes and heterogeneous intraclass correlations and variances
Full text linkWhen comparing two different kinds of group therapy or two individual treatments where patients within each arm are nested within care providers, clustering of observations may occur in both arms. The arms may differ in terms of (a) the intraclass correlation, (b) the outcome variance, (c) the cluster size, and (d) the number of clusters, and there may be some ideal group size or ideal caseload in case of care providers, fixing the cluster size. For this case, optimal cluster numbers are derived for a linear mixed model analysis of the treatment effect under cost constraints as well as under power constraints. To account for uncertain prior knowledge on relevant model parameters, also maximin sample sizes are given. Formulas for sample size calculation are derived, based on the standard normal as the asymptotic distribution of the test statistic. For small sample sizes, an extensive numerical evaluation shows that in a two-tailed test employing restricted maximum likelihood estimation, a safe correction for both 80% and 90% power, is to add three clusters to each arm for a 5% type I error rate and four clusters to each arm for a 1% type I error rate
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