Genome-Wide Identification of Small RNAs in the Opportunistic Pathogen Enterococcus faecalis V583

Small RNA molecules (sRNAs) are key mediators of virulence and stress inducible gene expressions in some pathogens. In this work we identify sRNAs in the Gram positive opportunistic pathogen Enterococcus faecalis. We characterized 11 sRNAs by tiling microarray analysis, 5′ and 3′ RACE-PCR, and Northern blot analysis. Six sRNAs were specifically expressed at exponential phase, two sRNAs were observed at stationary phase, and three were detected during both phases. Searches of putative functions revealed that three of them (EFA0080_EFA0081 and EFB0062_EFB0063 on pTF1 and pTF2 plasmids, respectively, and EF0408_EF04092 located on the chromosome) are similar to antisense RNA involved in plasmid addiction modules. Moreover, EF1097_EF1098 shares strong homologies with tmRNA (bi-functional RNA acting as both a tRNA and an mRNA) and EF2205_EF2206 appears homologous to 4.5S RNA member of the Signal Recognition Particle (SRP) ribonucleoprotein complex. In addition, proteomic analysis of the ΔEF3314_EF3315 sRNA mutant suggests that it may be involved in the turnover of some abundant proteins. The expression patterns of these transcripts were evaluated by tiling array hybridizations performed with samples from cells grown under eleven different conditions some of which may be encountered during infection. Finally, distribution of these sRNAs among genome sequences of 54 E. faecalis strains was assessed. This is the first experimental genome-wide identification of sRNAs in E. faecalis and provides impetus to the understanding of gene regulation in this important human pathogen

Restoration of 3D medical images with total variation scheme on wavelet domains

The multiplicity of sensors used in medical imaging leads to different noises. Non informative noise can damage the image interpretation process and the performance of automatic analysis. The method proposed in this paper allows compensating highly noisy image data from non informative noise without sophisticated modeling of the noise statistics. This generic approach uses jointly a wavelet decomposition scheme [3] and a non-isotropic Total Variation filtering [9] of the transform coefficients. This framework benefits from both the hierarchical capabilities of the wavelet transform and the well-posed regularization scheme of the Total Variation. This algorithm has been tested and validated on test-bed data, as well as different clinical MR and 3D ultrasound images, enhancing the capabilities of the proposed method to cope with different noise models

Bias Image Correction Via Stationarity Maximization

International audienceAutomated acquisitions in microscopy may come along with strong illumination artifacts due to poor physical imaging conditions. Such artifacts obviously have direct consequences on the efficiency of an image analysis algorithm and on the quantitative measures. In this paper, we propose a method to correct illumination artifacts on biological images. This correction is based on orthogonal polynomial modeling, combined with stationary maximization criteria. To validate the proposed method we show that we improve particle detection algorithm

A New Color Representation for Intensity Independent Pixel Classification in Confocal Microscopy Images

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Areas of muscle tissue alteration can differ from activated regions during electrically-induced isometric contractions

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Areas of muscle tissue alteration can differ from activated regions during electrically-induced isometric contractions

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Suivi dynamique 3D des organes pelviens - résultats préliminaires

International audienceDans le contexte de l’étude des troubles de la statique pelvienne, nous proposons un processus d’observation temporelle de la vessie en 3D. Grâce à des acquisitions IRM multiplanaires associées à une stratégie de reconstruction adaptée, les déformations subies par la vessie ont pu être suivies lors d’exercices de charges en analysant plusieurs volumes par seconde. A notre connaissance, c’est la première fois qu’une telle observation est effectuée. De plus, nous proposons des indices d’estimation de déformation susceptibles d’être utiles à la caractérisation des pathologies et au diagnostic clinique

3D Dynamic MRI for Pelvis Observation - a First Step

International audienceIn the context of pelvic floor diseases understanding we advocate a process to observe the bladder over time in 3D. Thanks to multiplanar MRI acquisitions and adequate volume constructions, several volumes per seconds can show a bladder undergoing deformations under strain conditions. To our knowledge it is the first time such observation is performed. In addition we propose some deformation estimation clues that may be useful to pathology characterization and clinical diagnosis