A simulation approach for power calculation in large cohort studies based on multistate models

Realistic power calculations for large cohort studies and nested case control studies are essential for successfully answering important and complex research questions in epidemiology and clinical medicine. For this, we provide a methodical framework for general realistic power calculations via simulations that we put into practice by means of an R‐based template. We consider staggered recruitment and individual hazard rates, competing risks, interaction effects, and the misclassification of covariates. The study cohort is assembled with respect to given age‐, gender‐, and community distributions. Nested case‐control analyses with a varying number of controls enable comparisons of power with a full cohort analysis. Time‐to‐event generation under competing risks, including delayed study‐entry times, is realized on the basis of a six‐state Markov model. Incidence rates, prevalence of risk factors and prefixed hazard ratios allow for the assignment of age‐dependent transition rates given in the form of Cox models. These provide the basis for a central simulation‐algorithm, which is used for the generation of sample paths of the underlying time‐inhomogeneous Markov processes. With the inclusion of frailty terms into the Cox models the Markov property is specifically biased. An “individual Markov process given frailty” creates some unobserved heterogeneity between individuals. Different left‐truncation‐ and right‐censoring patterns call for the use of Cox models for data analysis. p‐values are recorded over repeated simulation runs to allow for the desired power calculations. For illustration, we consider scenarios with a “testing” character as well as realistic scenarios. This enables the validation of a correct implementation of theoretical concepts and concrete sample size recommendations against an actual epidemiological background, here given with possible substudy designs within the German National Cohort.     

State-of-the art data normalization methods improve NMR-based metabolomic analysis

Extracting biomedical information from large metabolomic datasets by multivariate data analysis is of considerable complexity. Common challenges include among others screening for differentially produced metabolites, estimation of fold changes, and sample classification. Prior to these analysis steps, it is important to minimize contributions from unwanted biases and experimental variance. This is the goal of data preprocessing. In this work, different data normalization methods were compared systematically employing two different datasets generated by means of nuclear magnetic resonance (NMR) spectroscopy. To this end, two different types of normalization methods were used, one aiming to remove unwanted sample-to-sample variation while the other adjusts the variance of the different metabolites by variable scaling and variance stabilization methods. The impact of all methods tested on sample classification was evaluated on urinary NMR fingerprints obtained from healthy volunteers and patients suffering from autosomal polycystic kidney disease (ADPKD). Performance in terms of screening for differentially produced metabolites was investigated on a dataset following a Latin-square design, where varied amounts of 8 different metabolites were spiked into a human urine matrix while keeping the total spike-in amount constant. In addition, specific tests were conducted to systematically investigate the influence of the different preprocessing methods on the structure of the analyzed data. In conclusion, preprocessing methods originally developed for DNA microarray analysis, in particular, Quantile and Cubic-Spline Normalization, performed best in reducing bias, accurately detecting fold changes, and classifying samples.

     

Chemo-enzymatic synthesis of the Galili epitope Gal(alpha)(1-->3)Galbeta(1-->4)GlcNAc on a homogeneously soluble PEG polymer by a multi-enzyme system.

The alpha-Gal trisaccharide Gal(alpha)(1-->3)Galbeta(1-->4)GlcNAc 11 was synthesized on a homogeneously soluble polymeric support (polyethylene glycol, PEG) by use of a multi-enzyme system consisting of beta-1,4-galactosyltransferase (EC 2.4.1.38), alpha-1,3-galactosyltransferase (EC 2.4.1.151), sucrose synthase (EC 2.4.1.13) and UDP-glucose-4-epimerase (EC 5.1.3.2). In addition workup was simplified by use of dia-ultrafiltration. Thus the advantages of classic chemistry/enzymology and solid-phase synthesis could be united in one. Subsequent hydrogenolytic cleavage afforded the free alpha-Gal trisaccharide.     

Time course of pump inhibition by ouabain in amphibian epithelia

Inhibition by ouabain of rheogenic Na⁺ transport across the basolateral membranes of frog skin is found to be manifest within 3–4 min. This rate of pump inhibition is not different from the rate of diffusion through extracellular tissue layers between the serosal bath and the actual site of action, i.e., the epithelial cell layers. It is concluded that the well-known slow time course of decrease in transepithelial current flow is due ionic redistribution and conductance changes of the epithelial membranes secondary to pump inhibition.     

Histochemistry of mucosubstances in Brunner's-gland cells and duodenal goblet cells of two New World monkey species (Saimiri sciureus and Saguinus fuscicollis)

Duodenal goblet cells and Brunner's-gland cells obtained from two species of New World monkeys (Saimiri sciureus and Saguinus fuscicollis) were studied using conventional histochemical methods and by applying a panel of 17 labelled lectins. The secretions of both goblet and Brunner's-gland cells were found to contain neutral mucosubstances, while those of goblet cells also exhibit acid and sulphated carbohydrate components. Lectin binding studies allowed a more detailed analysis of the mucus glycoproteins. Marked differences between the two examined species were not detected. N-Acetyl-galactosamine, galactose, fucose and N-Acetyl-glucosamine were found to be the predominant sugar residues in Brunner's-glands glycoproteins, with mannose and glucose being only minor components.     

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)     

Interaction of androgens and estrogens in the control of reproduction

Castrated male quail were injected with the synthetic oestrogen, diethylstylbestrol (DES) or the synthetic androgen, methyltrienolone (R 1881) or both compounds simultaneously. Both R 1881 and DES activated male sexual behaviour, inhibited LH and FSH secretion and increased hypothalamic aromatase activity. Additive effects between R 1881 and DES were observed for the induction of brain aromatase and for the inhibition of FSH secretion. As a consequence, mechanisms mediated by androgen and estrogen receptors must be involved in the control of these reproductive characteristics.     

Resolution of d,l-menthol by interesterification with triacetin using the free and immobilized lipase of Candida cylindracea

Summary Interesterification in isooctane with triacetin as an acyl donor was found to be a new and effective method of racemic resolution of d,l-menthol, when using the free and immobilized lipase of Candida cylindracea. No water was produced by this highly stereoselective type of reaction in contrast to ester synthesis with acetic acid as an acyl donor. Even with diacetin no possible back reaction occurred and the enzyme was easily separated from the reaction solution as opposed to ester hydrolysis in aqueous systems. Inhibition of interesterification was caused by increasing concentrations of the acyl donor triacetin by more than 10 mmol·l^-1 on the one hand, and especially by diacetin on the other hand. The reaction product menthyl acetate had no influence. By adding water the interesterification activity of the lipase was reduced significantly. An alteration of the acyl donor triacetin to longerchained triglycerides caused changes in higher specific activities but poor enantioselectivities of the products, as in the case of ester synthesis starting from longer-chained organic acids.Dedicated to Prof. Dr. Fritz Wagner on the occasion of his 60th birthday