Effect of acarbose on postmeal mononuclear blood cell response in patients with early type 2 diabetes: the AI(I)DA study

So far little is known about how the antidiabetic drugs acting at the level of gastrointestinal mucosa may affect immune and cellular response to food intake. The following study investigated the association between acarbose treatment and postprandial metabolism, immune- and inflammatory activity in patients with early type 2 diabetes: The Acarbose action on low grade Inflammation and Immune response in type 2 Diabetes on Atherosclerosis risk (AIIDA) study. Middle-aged patients (n=87) with early type 2 diabetes (2 h-plasma-glucose >or=11.1 mmol/l and/or HbA1c >or=6.5%) and sub-clinical inflammation (leucocytes >or=6.2 GPt/l and/or hsCRP >or=1.0 mg/l) underwent a mixed meal load (527 kcal). Metabolic parameters and markers of subclinical inflammation were measured at fasting (0'), 2 h-postprandial (2-hpp) and 4-hpp before and after 20 weeks of treatment with acarbose or placebo. Leukocytes and lymphocytes excursion after 20 weeks of treatment was significantly reduced with acarbose 4 h after testmeal [GPt/l] (7.5 vs. 7; p<0.05; and 2.29 vs. 2.14; p<0.05, respectively). Acarbose had only marginal effects on pp glucose, FFA, triglycerides, and insulin excursion. Biomarkers of inflammation (hsCRP, MBL, and PAI1) were not affected by acarbose. Multivariate analysis reveals only baseline leukocytes and of acarbose as independent determinant of 4-h leucocytes excursion. Postprandial metabolic and inflammatory parameters were strongly interrelated. These results suggest pleiotropic effects of acarbose, which may contribute to its vasoprotective potentials.

Comparison of unsupervised and supervised gene selection methods

Modern machine learning methods based on matrix decomposition techniques like Independent Component Analysis (ICA) provide new and efficient analysis tools which are currently explored to analyze gene expression profiles. These exploratory feature extraction techniques yield informative expression modes (ICA) which are considered indicative of underlying regulatory processes. Their most strongly expressed genes represent marker genes for classification of the tissue samples under investigation. Comparison with supervised gene selection methods based on statistical scores or support vector machines corroborate these findings. The method is applied to macrophages loaded/de-loaded with chemically modified low density lipids.

Analyzing time-dependent microarray data using independent component analysis derived expression modes from human macrophages infected with F. tularensis holartica

The analysis of large-scale gene expression profiles is still a demanding and extensive task. Modern machine learning and data mining techniques developed in linear algebra, like Independent Component Analysis (ICA), become increasingly popular as appropriate tools for analyzing microarray data. We applied ICA to analyze kinetic gene expression profiles of human monocyte derived macrophages (MDM) from three different donors infected with Francisella tularensis holartica and compared them to more classical methods like hierarchical clustering. Results were compared using a pathway analysis tool, based on the Gene Ontology and the MeSH database. We could show that both methods lead to time-dependent gene regulatory patterns which fit well to known TNFalpha induced immune responses. In comparison, the nonexclusive attribute of ICA results in a more detailed view and a higher resolution in time dependent behavior of the immune response genes. Additionally, we identified NFkappaB as one of the main regulatory genes during response to F. tularensis infection.

Thermal stability of a Co/Cu giant magnetoresistance (GMR) multilayer system

Critical limitations exist regarding the thermal stability of multilayer giant magnetoresistance (GMR) sensors due to significant contribution of layer interfaces and grain boundaries to their performance. This paper addresses the stability of, and thermal reaction in Co/Cu magnetoresistive systems. Thin film multilayers were deposited by ion beam sputtering on top of preformed tungsten tips. The multilayers were then analyzed by a wide-angle tomographic atom probe (WATAP) in the as-prepared state and after heat treatments in the temperature range from 150 to 550 degrees C. As revealed by the WATAP analysis, Co breakthroughs along grain boundaries in the Cu spacers appear at 450 degrees C. This morphological change leads to a deterioration of the GMR effect due to the magnetostatic ferromagnetic coupling between Co layers. Furthermore, a strong effect of Cu layers faceting is observed after annealing in the same temperature range, which may lead to the deterioration of the layered structure on high-angle grain boundaries.

Magnon kinetics and Bose-Einstein condensation studied in phase space

Using a novel technique providing simultaneous resolution with respect to the wave vector and frequency of magnons, we observed the formation of a Bose-Einstein condensate documented by the narrowing of the magnon distribution in phase space. Based on the measured width of the distribution we determined the effective correlation length of the condensate, which appears to be anisotropic, reflecting the anisotropy of the magnon dispersion spectrum.

Flow cytometric analysis of reticulated platelets

Flow Cytometric Analysis of Reticulated Platelets (G. Matic, G. Rothe, and G. Schmitz, University of Regensburg, Regensburg, Germany). In the last several years, flow cytometry has emerged as one of the tools of choice in evaluation of platelets. In particular, the distinction between reticulated platelets and mature platelets based on RNA fluorescence has proved to be a vital tool in the clinical hematology laboratory. Further, as is now well understood, it is important to evaluate platelets in whole blood rather than in isolated populations. Platelet quantification in a dual-color whole-blood method is of interest for the characterization of thrombocytopoiesis in (immune)-thrombocytopenia or in the regenerating bone marrow.

Knowledge-based gene expression classification via matrix factorization

Motivation: Modern machine learning methods based on matrix decomposition techniques, like independent component analysis (ICA) or non-negative matrix factorization (NMF), provide new and efficient analysis tools which are currently explored to analyze gene expression profiles. These exploratory feature extraction techniques yield expression modes (ICA) or metagenes (NMF). These extracted features are considered indicative of underlying regulatory processes. They can as well be applied to the classification of gene expression datasets by grouping samples into different categories for diagnostic purposes or group genes into functional categories for further investigation of related metabolic pathways and regulatory networks.

Results: In this study we focus on unsupervised matrix factorization techniques and apply ICA and sparse NMF to microarray datasets. The latter monitor the gene expression levels of human peripheral blood cells during differentiation from monocytes to macrophages. We show that these tools are able to identify relevant signatures in the deduced component matrices and extract informative sets of marker genes from these gene expression profiles. The methods rely on the joint discriminative power of a set of marker genes rather than on single marker genes. With these sets of marker genes, corroborated by leave-one-out or random forest cross-validation, the datasets could easily be classified into related diagnostic categories. The latter correspond to either monocytes versus macrophages or healthy vs Niemann Pick C disease patients.

Supplementary information:Supplementary data are available at Bioinformatics online.

Contact:elmar.lang@biologie.uni-regensburg.de

Routes to identify marker genes for microarray classification

Support vector machines are applied to extract marker genes from various microarray data sets: Breast Cancer, Leukemia and Monocyte - Macrophage Differentiation to ease classification of related pathologies or characterize related gene regulation pathways.

How to extract marker genes from microarray data sets

In this study we focus on classification tasks and apply matrix factorization techniques like principal component analysis (PCA), independent component analysis (ICA) and non-negative matrix factorization (NMF) to a microarray data set. The latter monitors the gene expression levels (GEL) of mononcytes and macrophages during and after differentiation. We show that these tools are able to identify relevant signatures in the deduced matrices and extract marker genes from these gene expression profiles (GEPs) without the need for extensive data bank search for appropriate functional annotations. With these marker genes corresponding test data sets can then easily be classified into related diagnostic categories.

Human aldehyde oxidase 1 interacts with ATP-binding cassette transporter-1 and modulates its activity in hepatocytes

AOX1, a member of the cytosolic molybdenum hydroxylase family, has been identified by us earlier as an ABCA1-interacting protein. AOX1 is well-described as xenobiotic metabolizing enzyme, which upon oxidation of acetaldehyde and retinaldehyde to acetic acid and retinoic acid generates reactive oxygen species. Here we show that knock-down of AOX1 in HepG2 by small interfering RNA significantly reduced ABCA1-dependent lipid efflux and enhanced phagocytic uptake of microspheres similar to ABCA1 deficiency, without affecting ABCA1 mRNA and protein levels. ABCA1 and AOX1 are coexpressed in human hepatocytes, kidney proximal tubular epithelial cells, Leydig, and adrenocortical cells. Expression of ABCA1 and AOX1 was investigated by immunohistochemistry in liver tissue arrays. A strong AOX1 expression was found in normal liver, and in cirrhosis. In contrast, hepatocellular carcinomas showed either a complete loss or reduced expression of AOX1. Significant correlations were found between reduced AOX1 expression and tumor stage, or metastatic or regional lymph node states. Deregulation was also observed for ABCA1 expression but to a lesser extent. Our findings show that the interaction of ABCA1 with AOX1 modulates ABCA1-linked cellular functions such as lipid efflux and phagocytosis in hepatocytes, and the reduced expression of AOX1 in malignant transformed hepatocytes supports the differentiation dependent upregulation of AOX1.

Low-density lipoproteins induce the renin-angiotensin system and their receptors in human endothelial cells

Increased levels of low-density lipoproteins are well-established risk factors of endothelial dysfunction and the metabolic syndrome. In this study, we evaluated the effect of native low-density lipoprotein (nLDL) and oxidized LDL (oxLDL) on the expression of genes of the renin-angiotensin system (angiotensin-converting enzyme, ACE; angiotensin II type 1 receptor, AT(1)) and their receptors (low-density lipoprotein receptor: LDLR; lectin-like oxLDL receptor: LOX-1; toll-like receptor 4: TLR4) in primary cultures of human umbilical vein endothelial cells. ACE and AT(1) expressions were significantly increased after stimulation with nLDL and oxLDL. OxLDL receptor LOX-1 showed a maximum induction after 7 hours. Increased LOX-1 protein expression in response to oxLDL could be blocked by a LOX-1-specific antibody. TLR4 expression was increased by nLDL and oxLDL as well. We conclude that LDL and oxLDL can activate the renin-angiotensin system and their receptors LDLR, LOX-1, and TLR4 in human endothelial cells. These data suggest a novel link between hypercholesterolemia and hypertension in patients with the metabolic syndrome.

Laser-assisted atom probe tomography of oxide materials

Atom probe tomography provides a chemical analysis of nanostructured materials with outstanding resolution. However, due to the process of field evaporation triggered by nanosecond high voltage pulses, the method is usually limited to conductive materials. As part of recent efforts to overcome this limitation, it is demonstrated that the analysis of thick NiO and WO3 oxide layers is possible by laser pulses of 500 ps duration. A careful analysis of the mass spectra demonstrates that the expected stoichiometries are well reproduced by the measurement. The reconstruction of lattice planes proves that surface diffusion is negligible also in the case of thermal pulses.