Actions of metformin and statins on lipid and glucose metabolism and possible benefit of combination therapy

Patients with diabetes type 2 have an increased risk for cardiovascular disease and commonly use combination therapy consisting of the anti-diabetic drug metformin and a cholesterol-lowering statin. However, both drugs act on glucose and lipid metabolism which could lead to adverse effects when used in combination as compared to monotherapy. In this review, the proposed molecular mechanisms of action of statin and metformin therapy in patients with diabetes and dyslipidemia are critically assessed, and a hypothesis for mechanisms underlying interactions between these drugs in combination therapy is developed

Restoration of SMN in Schwann cells reverses myelination defects and improves neuromuscular function in spinal muscular atrophy

Spinal muscular atrophy (SMA) is a neuromuscular disease caused by low levels of SMN protein, primarily affecting lower motor neurons. Recent evidence from SMA and related conditions suggests that glial cells can influence disease severity. Here, we investigated the role of glial cells in the peripheral nervous system by creating SMA mice selectively overexpressing SMN in myelinating Schwann cells (Smn(−/−);SMN2(tg/0);SMN1(SC)). Restoration of SMN protein levels restricted solely to Schwann cells reversed myelination defects, significantly improved neuromuscular function and ameliorated neuromuscular junction pathology in SMA mice. However, restoration of SMN in Schwann cells had no impact on motor neuron soma loss from the spinal cord or ongoing systemic and peripheral pathology. This study provides evidence for a defined, intrinsic contribution of glial cells to SMA disease pathogenesis and suggests that therapies designed to include Schwann cells in their target tissues are likely to be required in order to rescue myelination defects and associated disease symptoms

A Reappraisal of the Mechanism by Which Plant Sterols Promote Neutral Sterol Loss in Mice

Dietary plant sterols (PS) reduce serum total and LDL-cholesterol in hyperlipidemic animal models and in humans. This hypocholesterolemic effect is generally ascribed to inhibition of cholesterol absorption. However, whether this effect fully explains the reported strong induction of neutral sterol excretion upon plant sterol feeding is not known. Recent data demonstrate that the intestine directly mediates plasma cholesterol excretion into feces, i.e., without involvement of the hepato-biliary route

Intervention in the Foreign Exchange Market: Rationale, Effectiveness, Costs and Benefits

This paper reviews the underlying rationale for intervention in the foreign exchange market and argues that intervention can at times be justified due to the market producing the “wrong rate”, to mitigate the effects of exchange rate overshooting and also to slow down the process of economic adjustment. However, in order to be effective foreign exchange market intervention needs to be of the non-sterilized variety, that is, affect the domestic money supply and short term interest rate. Unfortunately, as the case of the Peoples Bank of China and the recent case of the Swiss National Bank’s attempts to stem the appreciation of their currencies, the side effects have shown the rapid expansion of their money supplies and low interest rates have had imposed significant costs on their economies. The result is that the Cemtral Bank has to continually monitor the costs and benefits of their foreign exchange interventions and be prepared consider a return to floating when the costs become too high

Gidsen in de stadse jungle, biologentweeling wekt verwondering voor stadsecologie

Conservation Biolog

Plasma oxyphytosterols most likely originate from hepatic oxidation and subsequent spill-over in the circulation

We evaluated oxyphytosterol (OPS) concentrations in plasma and various tissues of two genetically modified mouse models with either increased cholesterol (apoE KO mice) or increased cholesterol and plant sterol (PS) concentrations (apoExABCG8 dKO mice). Sixteen female apoE KO and 16 dKO mice followed the same standard, low OPS-chow diet. Animals were euthanized at 36 weeks to measure PS and OPS concentrations in plasma, brain, liver and aortic tissue. Cholesterol and oxysteml (OS) concentrations were analyzed as reference for sterol oxidation in general. Plasma campesterol (24.1 +/- 4.3 vs. 11.8 +/- 3.0 mg/dL) and sitosterol (67.4 +/- 12.7 vs. 4.9 +/- 1.1 mg/dL) concentrations were severely elevated in the dKO compared to the apoE KO mice (p < 0.001). Also, in aortic and brain tissue, PS levels were significantly elevated in dKO. However, plasma, aortic and brain OPS concentrations were comparable or even lower in the dKO mice. In contrast, in liver tissue, both PS and OPS concentrations were severely elevated in the dKO compared to apoE KO mice (sum OPS: 7.4 +/- 1.6 vs. 4.1 +/- 0.8 ng/mg, p < 0.001). OS concentrations followed cholesterol concentrations in plasma and all tissues suggesting ubiquitous oxidation. Despite severely elevated PS concentrations, OPS concentrations were only elevated in liver tissue, suggesting that OPS are primarily formed in the liver and plasma concentrations originate from hepatic spill-over into the circulation

The effect of organelle discovery upon sub-cellular protein localisation.

Prediction of protein sub-cellular localisation by employing quantitative mass spectrometry experiments is an expanding field. Several methods have led to the assignment of proteins to specific subcellular localisations by partial separation of organelles across a fractionation scheme coupled with computational analysis. Methods developed to analyse organelle data have largely employed supervised machine learning algorithms to map unannotated abundance profiles to known protein–organelle associations. Such approaches are likely to make association errors if organelle-related groupings present in experimental output are not included in data used to create a protein–organelle classifier. Currently, there is no automated way to detect organelle-specific clusters within such datasets. In order to address the above issues we adapted a phenotype discovery algorithm, originally created to filter image-based output for RNAi screens, to identify putative subcellular groupings in organelle proteomics experiments. We were able to mine datasets to a deeper level and extract interesting phenotype clusters for more comprehensive evaluation in an unbiased fashion upon application of this approach. Organelle-related protein clusters were identified beyond those sufficiently annotated for use as training data. Furthermore, we propose avenues for the incorporation of observations made into general practice for the classification of protein–organelle membership from quantitative MS experiments. Biological significance Protein sub-cellular localisation plays an important role in molecular interactions, signalling and transport mechanisms. The prediction of protein localisation by quantitative mass-spectrometry (MS) proteomics is a growing field and an important endeavour in improving protein annotation. Several such approaches use gradient-based separation of cellular organelle content to measure relative protein abundance across distinct gradient fractions. The distribution profiles are commonly mapped in silico to known protein–organelle associations via supervised machine learning algorithms, to create classifiers that associate unannotated proteins to specific organelles. These strategies are prone to error, however, if organelle-related groupings present in experimental output are not represented, for example owing to the lack of existing annotation, when creating the protein–organelle mapping. Here, the application of a phenotype discovery approach to LOPIT gradient-based MS data identifies candidate organelle phenotypes for further evaluation in an unbiased fashion. Software implementation and usage guidelines are provided for application to wider protein–organelle association experiments. In the wider context, semi-supervised organelle discovery is discussed as a paradigm with which to generate new protein annotations from MS-based organelle proteomics experiments. This article is part of a Special Issue entitled: New Horizons and Applications for Proteomics [EuPA 2012]

Identification of Discriminating Metabolic Pathways and Metabolites in Human PBMCs Stimulated by Various Pathogenic Agents

Immunity and cellular metabolism are tightly interconnected but it is not clear whether different pathogens elicit specific metabolic responses. To address this issue, we studied differential metabolic regulation in peripheral blood mononuclear cells (PBMCs) of healthy volunteers challenged by Candida albicans, Borrelia burgdorferi, lipopolysaccharide, and Mycobacterium tuberculosis in vitro. By integrating gene expression data of stimulated PBMCs of healthy individuals with the KEGG pathways, we identified both common and pathogen-specific regulated pathways depending on the time of incubation. At 4 h of incubation, pathogenic agents inhibited expression of genes involved in both the glycolysis and oxidative phosphorylation pathways. In contrast, at 24 h of incubation, particularly glycolysis was enhanced while genes involved in oxidative phosphorylation remained unaltered in the PBMCs. In general, differential gene expression was less pronounced at 4 h compared to 24 h of incubation. KEGG pathway analysis allowed differentiation between effects induced by Candida and bacterial stimuli. Application of genome-scale metabolic model further generated a Candida-specific set of 103 reporter metabolites (e.g., desmosterol) that might serve as biomarkers discriminating Candida stimulated PBMCs from bacteria-stimuated PBMCs. Our analysis also identified a set of 49 metabolites that allowed discrimination between the effects of Borrelia burgdorferi, lipopolysaccharide and Mycobacterium tuberculosis. We conclude that analysis of pathogen-induced effects on PBMCs by a combination of KEGG pathways and genome-scale metabolic model provides deep insight in the metabolic changes coupled to host defense

Mapping cells and sub-cellular organelles on 2-D gels: ‘new tricks for an old horse’

AbstractNowadays, investigators in all fields are faced with the identification of unknown, up- or down-regulated, modified proteins that they are trying to identify. Two-dimensional (2-D) gel electrophoresis, with its ability to resolve several thousand proteins, is an extremely powerful technique. The current resolution and reproducibility of 2-D gel technology and the establishment of computer assisted 2-D gel protein databases have paved new ways for the identification of proteins