Multidimensional local false discovery rate for microarray studies

MOTIVATION: The false discovery rate (fdr) is a key tool for statistical assessment of differential expression (DE) in microarray studies. Overall control of the fdr alone, however, is not sufficient to address the problem of genes with small variance, which generally suffer from a disproportionally high rate of false positives. It is desirable to have an fdr-controlling procedure that automatically accounts for gene variability. METHODS: We generalize the local fdr as a function of multiple statistics, combining a common test statistic for assessing DE with its standard error information. We use a non-parametric mixture model for DE and non-DE genes to describe the observed multi-dimensional statistics, and estimate the distribution for non-DE genes via the permutation method. We demonstrate this fdr2d approach for simulated and real microarray data. RESULTS: The fdr2d allows objective assessment of DE as a function of gene variability. We also show that the fdr2d performs better than commonly used modified test statistics. AVAILABILITY: An R-package OCplus containing functions for computing fdr2d() and other operating characteristics of microarray data is available at http://www.meb.ki.se/~yudpaw.     

Finding regions of significance in SELDI measurements for identifying protein biomarkers

MOTIVATION: There is a well-recognized potential of protein expression profiling using the surface-enhanced laser desorption and ionization technology for discovering biomarkers that can be applied in clinical diagnosis, prognosis and therapy prediction. The pre-processing of the raw data, however, is still problematic. METHODS: We focus on the peak detection step, where the standard method is marked by poor specificity. Currently, scientists need to inspect individual spectra visually and laboriously in order to verify that spectral peaks identified by the standard method are real. Motivated by this multi-spectral process, we investigate an analytical approach-called RS for 'regions of significance'-that reduces the data to a single spectrum of F-statistics capturing significant variability between spectra. To account for multiple testing, we use a false discovery rate criterion for identifying potentially interesting proteins. RESULTS: We show that RS has better operating characteristics than several existing methods and demonstrate routine applications on a number of large datasets.     

Modulation of human time processing by subthalamic deep brain stimulation

Timing in the range of seconds referred to as interval timing is crucial for cognitive operations and conscious time processing. According to recent models of interval timing basal ganglia (BG) oscillatory loops are involved in time interval recognition. Parkinsońs disease (PD) is a typical disease of the basal ganglia that shows distortions in interval timing. Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is a powerful treatment of PD which modulates motor and cognitive functions depending on stimulation frequency by affecting subcortical-cortical oscillatory loops. Thus, for the understanding of BG-involvement in interval timing it is of interest whether STN-DBS can modulate timing in a frequency dependent manner by interference with oscillatory time recognition processes. We examined production and reproduction of 5 and 15 second intervals and millisecond timing in a double blind, randomised, within-subject repeated-measures design of 12 PD-patients applying no, 10-Hz- and ≥ 130-Hz-STN-DBS compared to healthy controls. We found under(re-)production of the 15-second interval and a significant enhancement of this under(re-)production by 10-Hz-stimulation compared to no stimulation, ≥ 130-Hz-STN-DBS and controls. Milliseconds timing was not affected. We provide first evidence for a frequency-specific modulatory effect of STN-DBS on interval timing. Our results corroborate the involvement of BG in general and of the STN in particular in the cognitive representation of time intervals in the range of multiple seconds.     

5-Methoxyleoligin,a Lignan from Edelweiss,Stimulates CYP26B1-Dependent Angiogenesis In Vitro and Induces Arteriogenesis in Infarcted Rat Hearts In Vivo

Background

Insufficient angiogenesis and arteriogenesis in cardiac tissue after myocardial infarction (MI) is a significant factor hampering the functional recovery of the heart. To overcome this problem we screened for compounds capable of stimulating angiogenesis, and herein investigate the most active molecule, 5-Methoxyleoligin (5ML), in detail.

Methods and Results

5ML potently stimulated endothelial tube formation, angiogenic sprouting, and angiogenesis in a chicken chorioallantoic membrane assay. Further, microarray- and knock down- based analyses revealed that 5ML induces angiogenesis by upregulation of CYP26B1. In an in vivo rat MI model 5ML potently increased the number of arterioles in the peri-infarction and infarction area, reduced myocardial muscle loss, and led to a significant increase in LV function (plus 21% 28 days after MI).

Conclusion

The present study shows that 5ML induces CYP26B1-dependent angiogenesis in vitro, and arteriogenesis in vivo. Whether or not CYP26B1 is relevant for in vivo arteriogenesis is not clear at the moment. Importantly, 5ML-induced arteriogenesis in vivo makes the compound even more interesting for a post MI therapy. 5ML may constitute the first low molecular weight compound leading to an improvement of myocardial function after MI.     

Algorithm of OMA for large-scale orthology inference

Background  

OMA is a project that aims to identify orthologs within publicly available, complete genomes. With 657 genomes analyzed to date, OMA is one of the largest projects of its kind.