Assessment of Optimal Selected Prognostic Factors

The identification and assessment of prognostic factors is one of the major tasks in clinical research. The assessment of one single prognostic factor can be done by recently established methods for using optimal cutpoints. Here, we suggest a method to consider an optimal selected prognostic factor from a set of prognostic factors of interest. This can be viewed as a variable selection method and is the underlying decision problem at each node of various tree building algorithms. We propose to use maximally selected statistics where the selection is defined over the set of prognostic factors and over all cutpoints in each prognostic factor. We demonstrate that it is feasible to compute the approximate null distribution. We illustrate the new variable selection test with data of the German Breast Cancer Study Group and of a small study on patients with diffuse large B‐cell lymphoma. Using the null distribution for a p‐value adjusted regression trees algorithm, we adjust for the number of variables analysed at each node as well. (© 2004 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

Variables Affecting the Foam Separation of Escherichia coli

The removal of washed and standardized Escherichia coli from distilled-water suspension by foam separation with nitrogen gas and 30 μg/ml of ethylhexadecyldimethylammonium bromide surfactant was increased by increasing the gas rate from 4.3 to 9.3 liters per min and by lowering the port level at which foam was removed from 60.4 to 20.4 cm, but with concomitant increases in foam volumes. The concentrations of cells and of surfactant in the residual suspensions were related to foam volumes; a given number of cells adsorbed a constant amount of surfactant. The addition of from 10 to 500 μg/ml of inorganic salts decreased the total cell removal, with magnesium sulfate producing an anomalously large effect. The addition of surfactant in several doses (compared with a single dose) together with an increase in foaming time from 10 to 24 min produced residual suspensions with lower cell concentrations, and, when salts were present in the initial suspensions, produced lower foam volumes and more concentrated foams.     

Equivalence of regression curves sharing common parameters

In clinical trials, the comparison of two different populations is a common problem. Nonlinear (parametric) regression models are commonly used to describe the relationship between covariates, such as concentration or dose, and a response variable in the two groups. In some situations, it is reasonable to assume some model parameters to be the same, for instance, the placebo effect or the maximum treatment effect. In this paper, we develop a (parametric) bootstrap test to establish the similarity of two regression curves sharing some common parameters. We show by theoretical arguments and by means of a simulation study that the new test controls its significance level and achieves a reasonable power. Moreover, it is demonstrated that under the assumption of common parameters, a considerably more powerful test can be constructed compared with the test that does not use this assumption. Finally, we illustrate the potential applications of the new methodology by a clinical trial example.     

Efficient two-sample designs for microarray experiments with biological replications

In the last years, biostatistical research has begun to apply linear models and design theory to develop efficient experimental designs and analysis tools for gene expression microarray data. With two-colour microarrays, direct comparisons of RNA-targets are possible and lead to incomplete block designs. In this setting, efficient designs for simple and factorial microarray experiments have mainly been proposed for technical replicates. But for biological replicates, which are crucial to obtain inference that can be generalised to a biological population, this question has only been discussed recently and is not fully solved yet. In this paper, we propose efficient designs for independent two-sample experiments using two-colour microarrays enabling biologists to measure their biological random samples in an efficient manner to draw generalisable conclusions. We give advice for experimental situations with differing group sizes and show the impact of different designs on the variance and degrees of freedom of the test statistics. The designs proposed in this paper can be evaluated using SAS PROC MIXED or S+/R lme.     

Guidelines for consistent reporting of exchanges/to nature within life cycle inventories (LCI)

Data availability and data quality are still critical factors for successful LCA work. The SETAC-Europe LCA Working Group ‘Data Availability and Data Quality’ has therefore focused on ongoing developments toward a common data exchange format, public databases and accepted quality measures to find science-based solutions than can be widely accepted. A necessary prerequisite for the free flow and exchange of life cycle inventory (LCI) data and the comparability of LCIs is the consistent definition, nomenclature, and use of inventory parameters. This is the main subject of the subgroup ‘Recommended List of Exchanges’ that presents its results and findings here:

Inflammatory cytokine regulation of TRAIL-mediated apoptosis in thyroid epithelial cells

Death receptor-mediated apoptosis has been implicated in target organ destruction in chronic autoimmune thyroiditis. Depending on the circumstances, inflammatory cytokines such as IL-1, TNF and IFNgamma have been shown to contribute to either the induction, progression or inhibition of this disease. Here we demonstrate that the death ligand TRAIL can induce apoptosis in primary, normal, thyroid epithelial cells under physiologically relevant conditions, specifically, treatment with the combination of inflammatory cytokines IL-1beta and TNFalpha. In contrast, IFNgamma is capable of blocking TRAIL-induced apoptosis in these cells. This regulation of TRAIL-mediated apoptosis by inflammatory cytokines appears to be due to alterations of cell surface expression of TRAIL receptor DR5 and not DR4. We also show the in vivo presence of TRAIL and TRAIL receptors DR5 and DcR1 in both normal and inflamed thyroids. Our data suggests TRAIL-mediated apoptosis may contribute to target organ destruction in chronic autoimmune thyroiditis.     

Evaluation of phenolic compounds in Brazilian propolis from different geographic regions

Chemometrics has been shown quite efficient to uncover relationships between chemical composition of a sample and its geographical origin. Forty propolis samples originated from the the South and South East of Brazil were analyzed by HPLC and 18 compounds of interest were studied which included: caffeic, p-coumaric and ferulic acids, and some of their derivatives, pinobanksin, a derivative of kaempferol and five phenolic compounds (assigned as 3-prenyl4-hydroxycinnamic acid (PHCA); 2,2-dimethyl-6-carboxyethnyl-2H-1-benzopyran (DCBE); 3,5-diprenyl-4-hydroxycinnamic acid (DHCA); compound E (still unknown) and 6-propenoic-2,2-dimethyl-8-prenyl-2H-1-benzopyran acid (DPB). Principal Component Analysis (PCA) indicated three different groups of propolis samples, having the same typical chromatogram, evaluated by HPLC. Samples from the South East group were rich in derivatives of kaempferol. Samples from the South group I had a high content of DPB compound, but a low concentration of kaempferol derivatives and of DCBEN compound. Samples from the South group II were characterized by a high concentration of DCBEN, DHCA, p-coumaric and DPB compounds. Therefore, the identification of new compounds in Brazilian propolis can give, useful information about the plant sources of a given geographic region.