Identifying Mechanisms by Which Escherichia coli O157:H7 Subverts Interferon-γ Mediated Signal Transducer and Activator of Transcription-1 Activation

Enterohemorrhagic Escherichia coli serotype O157:H7 is a food borne enteric bacterial pathogen that causes significant morbidity and mortality in both developing and industrialized nations. E. coli O157:H7 infection of host epithelial cells inhibits the interferon gamma pro-inflammatory signaling pathway, which is important for host defense against microbial pathogens, through the inhibition of Stat-1 tyrosine phosphorylation. The aim of this study was to determine which bacterial factors are involved in the inhibition of Stat-1 tyrosine phosphorylation. Human epithelial cells were challenged with either live bacteria or bacterial-derived culture supernatants, stimulated with interferon-gamma, and epithelial cell protein extracts were then analyzed by immunoblotting. The results show that Stat-1 tyrosine phosphorylation was inhibited by E. coli O157:H7 secreted proteins. Using sequential anion exchange and size exclusion chromatography, YodA was identified, but not confirmed to mediate subversion of the Stat-1 signaling pathway using isogenic mutants. We conclude that E. coli O157:H7 subverts Stat-1 tyrosine phosphorylation in response to interferon-gamma through a still as yet unidentified secreted bacterial protein

Evaluation of methods for detection of fluorescence labeled subcellular objects in microscope images

<p>Abstract</p> <p>Background</p> <p>Several algorithms have been proposed for detecting fluorescently labeled subcellular objects in microscope images. Many of these algorithms have been designed for specific tasks and validated with limited image data. But despite the potential of using extensive comparisons between algorithms to provide useful information to guide method selection and thus more accurate results, relatively few studies have been performed.</p> <p>Results</p> <p>To better understand algorithm performance under different conditions, we have carried out a comparative study including eleven spot detection or segmentation algorithms from various application fields. We used microscope images from well plate experiments with a human osteosarcoma cell line and frames from image stacks of yeast cells in different focal planes. These experimentally derived images permit a comparison of method performance in realistic situations where the number of objects varies within image set. We also used simulated microscope images in order to compare the methods and validate them against a ground truth reference result. Our study finds major differences in the performance of different algorithms, in terms of both object counts and segmentation accuracies.</p> <p>Conclusions</p> <p>These results suggest that the selection of detection algorithms for image based screens should be done carefully and take into account different conditions, such as the possibility of acquiring empty images or images with very few spots. Our inclusion of methods that have not been used before in this context broadens the set of available detection methods and compares them against the current state-of-the-art methods for subcellular particle detection.</p

Nontypable Haemophilus influenzae Displays a Prevalent Surface Structure Molecular Pattern in Clinical Isolates

Non-typable Haemophilus influenzae (NTHi) is a Gram negative pathogen that causes acute respiratory infections and is associated with the progression of chronic respiratory diseases. Previous studies have established the existence of a remarkable genetic variability among NTHi strains. In this study we show that, in spite of a high level of genetic heterogeneity, NTHi clinical isolates display a prevalent molecular feature, which could confer fitness during infectious processes. A total of 111 non-isogenic NTHi strains from an identical number of patients, isolated in two distinct geographical locations in the same period of time, were used to analyse nine genes encoding bacterial surface molecules, and revealed the existence of one highly prevalent molecular pattern (lgtF+, lic2A+, lic1D+, lic3A+, lic3B+, siaA−, lic2C+, ompP5+, oapA+) displayed by 94.6% of isolates. Such a genetic profile was associated with a higher bacterial resistance to serum mediated killing and enhanced adherence to human respiratory epithelial cells

Analyzing factors that influence the folk use and phytonomy of 18 medicinal plants in Navarra

BACKGROUND: This article analyzes whether the distribution or area of use of 18 medicinal plants is influenced by ecological and cultural factors which might account for their traditional use and/or phytonymy in Navarra. This discussion may be helpful for comparative studies, touching as it does on other ethnopharmacological issues: a) which cultural and ecological factors affect the selection of medicinal plants; b) substitutions of medicinal plants in popular medicine; c) the relation between local nomenclature and uses. To analyze these questions, this paper presents an example of a species used for digestive disorders (tea and camomile: Jasonia glutinosa, J. tuberosa, Sideritis hyssopifolia, Bidens aurea, Chamaemelum nobile, Santolina chamaecyparissus...), high blood pressure (Rhamnus alaternus, Olea europaea...) or skin diseases (Hylotelephium maximum, H. telephium, Anagallis arvensis, A. foemina). METHODS: Fieldwork began on January 2004 and continued until December 2006. During that time we interviewed 505 informants in 218 locations in Navarra. Information was collected using semi-structured ethnobotanical interviews, and we subsequently made maps using Arc-View 8.0 program to determine the area of use of each taxon. Each map was then compared with the bioclimatic and linguistic map of Navarra, using the soil and ethnographic data for the region, and with other ethnobotanical and ethnopharmacological studies carried out in Europe. RESULTS: The results clearly show that ecological and cultural factors influence the selection of medicinal plants in this region. Climate and substrate are the most important ecological factors that influence the distribution and abundance of plants, which are the biological factors that affect medicinal plant selection. CONCLUSION: The study of edaphological and climatological factors, on the one hand, and culture, on the other, can help us to understand why a plant is replaced by another one for the same purposes, either in the same or in a different area. In many cases, the cultural factor means that the use of a species is more widespread than its ecological distribution. This may also explain the presence of synonyms and polysemies which are useful for discussing ethnopharmacological data