Why is 11beta-hydroxysteroid dehydrogenase type 1 facing the endoplasmic reticulum lumen? Physiological relevance of the membrane topology of 11beta-HSD1

11Beta-hydroxysteroid dehydrogenase type 1 (11beta-HSD1) is essential for the local activation of glucocorticoid receptors (GR). Unlike unliganded cytoplasmic GR, 11beta-HSD1 is an endoplasmic reticulum (ER)-membrane protein with lumenal orientation. Cortisone might gain direct access to 11beta-HSD1 by free diffusion across membranes, indirectly via intracellular binding proteins or, alternatively, by insertion into membranes. Membranous cortisol, formed by 11beta-HSD1 at the ER-lumenal side, might then activate cytoplasmic GR or bind to ER-lumenal secretory proteins. Compartmentalization of 11beta-HSD1 is important for its regulation by hexose-6-phosphate dehydrogenase (H6PDH), which regenerates cofactor NADPH in the ER lumen and stimulates oxoreductase activity. ER-lumenal orientation of 11beta-HSD1 is also essential for the metabolism of the alternative substrate 7-ketocholesterol (7KC), a major cholesterol oxidation product found in atherosclerotic plaques and taken up from processed cholesterol-rich food. An 11beta-HSD1 mutant adopting cytoplasmic orientation efficiently catalyzed the oxoreduction of cortisone but not 7KC, indicating access to cortisone from both sides of the ER-membrane but to 7KC only from the lumenal side. These aspects may be relevant for understanding the physiological role of 11beta-HSD1 and for developing therapeutic interventions to control glucocorticoid reactivation.

Extensions to Gene Set Enrichment

Motivation: Gene Set Enrichment Analysis (GSEA) has been developed recently to capture moderate but coordinated changes in the expression of sets of functionally related genes. We propose number of extensions to GSEA, which uses different statistics to describe the association between genes and phenotype of interest. We make use of dimension reduction procedures, such as principle component analysis to identify gene sets containing coordinated genes. We also address the problem of overlapping among gene sets in this paper. Results: We applied our methods to the data come from a clinical trial in acute lymphoblastic leukemia (ALL) [1]. We identified interesting gene sets using different statistics. We find that gender may have effects on the gene expression in addition to the phenotype effects. Investigating overlap among interesting gene sets indicate that overlapping could alter the interpretation of the significant results.

GENE SET ENRICHMENT ANALYSIS MADE SIMPLE

Among the many applications of microarray technology, one of the most popular is the identification of genes that are differentially expressed in two conditions. A common statistical approach is to quantify the interest of each gene with a p-value, adjust these p-values for multiple comparisons, chose an appropriate cut-off, and create a list of candidate genes. This approach has been criticized for ignoring biological knowledge regarding how genes work together. Recently a series of methods, that do incorporate biological knowledge, have been proposed. However, many of these methods seem overly complicated. Furthermore, the most popular method, Gene Set Enrichment Analysis (GSEA), is based on a statistical test known for its lack of sensitivity. In this paper we compare the performance of a simple alternative to GSEA.We find that this simple solution clearly outperforms GSEA.We demonstrate this with eight different microarray datasets.

[Evaluation of the "Schema-focused Emotive Behavioural Therapy" (SET) for Patients with Personality Disorders: Results of a Randomised Controlled Trial.]

The "Schema-focussed Emotive Behavioral Therapy" (SET) was developed by our research group as a new group therapy approach for patients with personality disorders from all clusters (A to C; DSM-IV). It was evaluated in a randomised controlled study (n = 93). Data were collected before and after treatment as well as one year after study entry. A completer analysis was conducted with matched subgroups (n = 60). After therapy, SET patients improved in the outcome domains interactional behavior, strain, and symptomatic complaints (IIP-D, GAF, VEV-VW, BSI-P). Furthermore, they showed a significant lower dropout rate. At the follow-up assessment, Cluster C patients of the experimental group deteriorated with regard to symptomatic complaints (BSI-P). In contrast, cluster B patients improved more over time compared to control subjects. SET seems to be an adequate and effective group therapy with effects that seem to be stable over time, especially for patients with Cluster B diagnosis.

Correspondence establishment in statistical modeling of shapes with arbitrary topology

Correspondence establishment is a key step in statistical shape model building. There are several automated methods for solving this problem in 3D, but they usually can only handle objects with simple topology, like that of a sphere or a disc. We propose an extension to correspondence establishment over a population based on the optimization of the minimal description length function, allowing considering objects with arbitrary topology. Instead of using a fixed structure of kernel placement on a sphere for the systematic manipulation of point landmark positions, we rely on an adaptive, hierarchical organization of surface patches. This hierarchy can be built on surfaces of arbitrary topology and the resulting patches are used as a basis for a consistent, multi-scale modification of the surfaces' parameterization, based on point distribution models. The feasibility of the approach is demonstrated on synthetic models with different topologies.