Metabolic effect of telmisartan and losartan in hypertensive patients with metabolic syndrome

Background

Metabolic syndrome is a cluster of common cardiovascular risk factors that includes hypertension and insulin resistance. Hypertension and diabetes mellitus are frequent comorbidities and, like metabolic syndrome, increase the risk of cardiovascular events. Telmisartan, an antihypertensive agent with evidence of partial peroxisome proliferator-activated receptor activity-gamma (PPARγ) activity, may improve insulin sensitivity and lipid profile in patients with metabolic syndrome.

Methods

In a double-blind, parallel-group, randomized study, patients with World Health Organization criteria for metabolic syndrome received once-daily doses of telmisartan (80 mg, n = 20) or losartan (50 mg, n = 20) for 3 months. At baseline and end of treatment, fasting and postprandial plasma glucose, insulin sensitivity, glycosylated haemoglobin (HBA_1c) and 24-hour mean systolic and diastolic blood pressures were determined.

Results

Telmisartan, but not losartan, significantly (p < 0.05) reduced free plasma glucose, free plasma insulin, homeostasis model assessment of insulin resistance and HbA_ic. Following treatment, plasma glucose and insulin were reduced during the oral glucose tolerance test by telmisartan, but not by losartan. Telmisartan also significantly reduced 24-hour mean systolic blood pressure (p < 0.05) and diastolic blood pressure (p < 0.05) compared with losartan.

Conclusion

As well as providing superior 24-hour blood pressure control, telmisartan, unlike losartan, displayed insulin-sensitizing activity, which may be explained by its partial PPARγ activity.     

Canonical Wnt signaling: high-throughput RNAi widens the path

The canonical Wnt signaling pathway is highly conserved in evolution, widely used throughout animal development, and frequently hyperactive in cancer. Although Wnt signaling has been the subject of extensive genetic analysis in the past, some 200 genes have now been identified as candidate modulators of this pathway by a recent study using high-throughput RNAi screening.     

Integrating gene expression and GO classification for PCA by preclustering

Background  

Gene expression data can be analyzed by summarizing groups of individual gene expression profiles based on GO annotation information. The mean expression profile per group can then be used to identify interesting GO categories in relation to the experimental settings. However, the expression profiles present in GO classes are often heterogeneous, i.e., there are several different expression profiles within one class. As a result, important experimental findings can be obscured because the summarizing profile does not seem to be of interest. We propose to tackle this problem by finding homogeneous subclasses within GO categories: preclustering.     

Mapping of citrullinated fibrinogen B-cell epitopes in rheumatoid arthritis by imaging surface plasmon resonance

Introduction  

Rheumatoid arthritis (RA) frequently involves the loss of tolerance to citrullinated antigens, which may play a role in pathogenicity. Citrullinated fibrinogen is commonly found in inflamed synovial tissue and is a frequent target of autoantibodies in RA patients. To obtain insight into the B-cell response to citrullinated fibrinogen in RA, its autoepitopes were systematically mapped using a new methodology.     

Quantification of global transcription patterns in prokaryotes using spotted microarrays

We describe an analysis, applicable to any spotted microarray dataset produced using genomic DNA as a reference, that quantifies prokaryotic levels of mRNA on a genome-wide scale. Applying this to Mycobacterium tuberculosis, we validate the technique, show a correlation between level of expression and biological importance, define the complement of invariant genes and analyze absolute levels of expression by functional class to develop ways of understanding an organism's biology without comparison to another growth condition.