A novel autotransporter of uropathogenic Proteus mirabilis is both a cytotoxin and an agglutinin

One of the six predicted Proteus mirabilis autotransporters (ATs), ORF c2341, is predicted to contain a serine protease motif and was earlier identified as an immunogenic outer membrane protein in P. mirabilis . The 3.2 kb gene encodes a 117 kDa protein with a 58-amino-acid-long signal peptide, a 75-kDa-long N-terminal passenger domain and a 30-kDa-long C-terminal translocator. Affinity-purified 110 kDa AT exhibited chymotrypsin-like activity and hydrolysed N -Suc–Ala–Ala–Pro–Phe– p Na and N -Suc–Ala–Ala–Pro–Leu– p Na with a K M of 22 μM and 31 μM, respectively, under optimal pH of 8.5–9.0 in a Ca 2+ -dependent manner. Activity was inhibited by subtilase-specific inhibitors leupeptin and chymostatin. Both the cell-associated and purified form elicited cytopathic effects on cultured kidney and bladder epithelial cells. Substrate hydrolysis as well as cytotoxicity was associated with the passenger domain and was compromised upon mutation of any of the catalytic residues (Ser366, His147 and Asp533). At alkaline pH and optimal cell density, the AT also promoted autoaggregation of P. mirabilis and this function was independent of its protease activity. Cytotoxicity, autoaggregation and virulence were significantly reduced in an isogenic pta mutant of P. mirabilis . Proteus toxic agglutinin (Pta) represents a novel autotransported cytotoxin with no bacterial homologues that works optimally in the alkalinized urinary tract, a characteristic of urease-mediated urea hydrolysis during P. mirabilis infection.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/73221/1/j.1365-2958.2008.06199.x.pd

Spectral high resolution feature selection for retrieval of combustion temperature profiles

Proceeding of: 7th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2006 (Burgos, Spain, September 20-23, 2006)The use of high spectral resolution measurements to obtain a retrieval of certain physical properties related with the radiative transfer of energy leads a priori to a better accuracy. But this improvement in accuracy is not easy to achieve due to the great amount of data which makes difficult any treatment over it and it's redundancies. To solve this problem, a pick selection based on principal component analysis has been adopted in order to make the mandatory feature selection over the different channels. In this paper, the capability to retrieve the temperature profile in a combustion environment using neural networks jointly with this spectral high resolution feature selection method is studied.Publicad

Improved model identification for non-linear systems using a random subsampling and multifold modelling (RSMM) approach

In non-linear system identification, the available observed data are conventionally partitioned into two parts: the training data that are used for model identification and the test data that are used for model performance testing. This sort of 'hold-out' or 'split-sample' data partitioning method is convenient and the associated model identification procedure is in general easy to implement. The resultant model obtained from such a once-partitioned single training dataset, however, may occasionally lack robustness and generalisation to represent future unseen data, because the performance of the identified model may be highly dependent on how the data partition is made. To overcome the drawback of the hold-out data partitioning method, this study presents a new random subsampling and multifold modelling (RSMM) approach to produce less biased or preferably unbiased models. The basic idea and the associated procedure are as follows. First, generate K training datasets (and also K validation datasets), using a K-fold random subsampling method. Secondly, detect significant model terms and identify a common model structure that fits all the K datasets using a new proposed common model selection approach, called the multiple orthogonal search algorithm. Finally, estimate and refine the model parameters for the identified common-structured model using a multifold parameter estimation method. The proposed method can produce robust models with better generalisation performance

Active Galactic Nuclei at the Crossroads of Astrophysics

Over the last five decades, AGN studies have produced a number of spectacular examples of synergies and multifaceted approaches in astrophysics. The field of AGN research now spans the entire spectral range and covers more than twelve orders of magnitude in the spatial and temporal domains. The next generation of astrophysical facilities will open up new possibilities for AGN studies, especially in the areas of high-resolution and high-fidelity imaging and spectroscopy of nuclear regions in the X-ray, optical, and radio bands. These studies will address in detail a number of critical issues in AGN research such as processes in the immediate vicinity of supermassive black holes, physical conditions of broad-line and narrow-line regions, formation and evolution of accretion disks and relativistic outflows, and the connection between nuclear activity and galaxy evolution.Comment: 16 pages, 5 figures; review contribution; "Exploring the Cosmic Frontier: Astrophysical Instruments for the 21st Century", ESO Astrophysical Symposia Serie

Genetic variants in CPA6 and PRPF31 are associated with variation in response to metformin in individuals with type 2 diabetes

Metformin is the first-line treatment for type 2 diabetes (T2D). Although widely prescribed, the glucose-lowering mechanism for metformin is incompletely understood. Here, we used a genome-wide association approach in a diverse group of individuals with T2D from the Action to Control Cardiovascular Risk in Diabetes (ACCORD) clinical trial to identify common and rare variants associated with HbA 1c response to metformin treatment and followed up these findings in four replication cohorts. Common variants in PRPF31 and CPA6 were associated with worse and better metformin response, respectively (P < 5 3 10 26 ), and meta-analysis in independent cohorts displayed similar associations with metformin response (P = 1.2 3 10 2 8 and P = 0.005, respectively). Previous studies have shown that PRPF31(+/2) knockout mice have increased total body fat (P = 1.78 3 10 26 ) and increased fasted circulating glucose (P = 5.73 3 10 26 ). Furthermore, rare variants in STAT3 associated with worse metformin response (q <0.1). STAT3 is a ubiquitously expressed pleiotropic transcriptional activator that participates in the regulation of metabolism and feeding behavior. Here, we provide novel evidence for associations of common and rare variants in PRPF31, CPA6, and STAT3 with metformin response that may provide insight into mechanisms important for metformin efficacy in T2D

Homogenization via formal multiscale asymptotics and volume averaging: How do the two techniques compare?

A wide variety of techniques have been developed to homogenize transport equations in multiscale and multiphase systems. This has yielded a rich and diverse field, but has also resulted in the emergence of isolated scientific communities and disconnected bodies of literature. Here, our goal is to bridge the gap between formal multiscale asymptotics and the volume averaging theory. We illustrate the methodologies via a simple example application describing a parabolic transport problem and, in so doing, compare their respective advantages/disadvantages from a practical point of view. This paper is also intended as a pedagogical guide and may be viewed as a tutorial for graduate students as we provide historical context, detail subtle points with great care, and reference many fundamental works