Proposal of \u3cem\u3eVibrionimonas magnilacihabitans\u3c/em\u3e gen. nov., sp. nov., a Curved Gram Negative Bacterium Isolated From Lake Michigan Water

A mesophilic bacterium appearing as curved rod-shaped cells was isolated from Lake Michigan water. It exhibited highest similarities with Sediminibacterium ginsengisoli DCY13T (94.4 %); Sediminibacterium salmoneum NJ-44T (93.6 %) and Hydrotalea flava CCUG 51397 T (93.1 %) while similarities with other recognized species were sym-homospermidine was the primary polyamine. The major cellular fatty acids were iso-C15 : 1G, iso-C15 : 0, iso-C16 : 0 3-OH and iso-C17 : 0 3-OH, with moderate amounts of iso-C16 : 0. The presence of glycolipids differentiated the novel strains from related genera. The DNA mol% G+C content of the type strain MU-2T was 45.2. Results for other phenotypic and molecular analyses indicated that strain MU-2T is a representative of a novel genus and species for which the name Vibrionimonas magnilacihabitans is proposed. The type strain is MU-2T ( = NRRL B-59231 = DSM 22423)

Diagnosis of exercise-induced left bundle branch block at rest by scintigraphic phase analysis

Accurate diagnosis of diseases of the ventricular conducting system is essential for their appropriate therapy. some conduction abnormalities, such as exercise-induced left bundle branch block (EX-LBBB), are not apparent on resting electrocardiograms. Phase analysis of rest and exercise radionuclide ventriculograms (RVG's) was used to compare four EX-LBBB patients with six normal controls. All patients had normal resting electrocardiograms, ejection fractions, and visually normal wall motion. First harmonic phase images were generated reflecting the timing of ventricular contraction. Dynamic phase displays were reviewed and graded in a blinded fashion by three independent experienced observers. Phase angle histograms of the right and left ventricle were determined for both resting and exercise images. The mean phase angle and standard deviation were also calculated for each ventricle. Visual grading of the resting phase images failed to show a significant difference between normal patients and patients with EX-LBBB. Quantitative analysis, however, revealed a significant difference in mean phase angle differences (LV-RV) in resting studies: 0.8° (±1.9° SEM) in normals versus 9.3° (±2.3° SEM) in EX-LBBB patients ( P <0.03). Exercise accentuated the phase angle differences: 1.8° in normals vs. 31.2° in EX-LBBB patients ( P <0.001). Quantitative phase analysis of resting RVG's permits the diagnosis of cardiac conduction disease that is not apparent on the resting EKG and may result in better monitoring and treatment.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/46821/1/259_2004_Article_BF00261005.pd

Overview of BioCreative II gene mention recognition.

Nineteen teams presented results for the Gene Mention Task at the BioCreative II Workshop. In this task participants designed systems to identify substrings in sentences corresponding to gene name mentions. A variety of different methods were used and the results varied with a highest achieved F1 score of 0.8721. Here we present brief descriptions of all the methods used and a statistical analysis of the results. We also demonstrate that, by combining the results from all submissions, an F score of 0.9066 is feasible, and furthermore that the best result makes use of the lowest scoring submissions

Sand and gravel resources of Butler County, Ohio

Relief shown by contour lines and spot heights.Includes text, 3 tables, location map, and water-well logs

Sand and gravel resources of Clark County, Ohio

Includes tables, water-well logs and location map

Synergistic Use of Compound Properties and Docking Scores in Neural Network Modeling of CYP2D6 Binding: Predicting Affinity and Conformational Sampling

Cytochrome P450 2D6 (CYP2D6) is used to develop an approach for predicting affinity and relevant binding conformation(s) for highly flexible binding sites. The approach combines the use of docking scores and compound properties as attributes in building a neural network (NN) model. It begins by identifying segments of CYP2D6 that are important for binding specificity, based on structural variability among diverse CYP enzymes. A family of distinct, low-energy conformations of CYP2D6 are generated using simulated annealing (SA) and a collection of 82 compounds with known CYP2D6 affinities are docked. Interestingly, docking poses are observed on the backside of the heme as well as in the known actiVe site. Docking scores for the actiVe site binders, along with compound-specific attributes, are used to train a neural network model to properly bin compounds as strong binders, moderate binders, or nonbinders. Attribute selection is used to preselect the most important scores and compound-specific attributes for the model. A prediction accuracy of 85 ( 6 % is achieved. Dominant attributes include docking scores for three of the 20 conformations in the ensemble as well as the compound’s formal charge, number of aromatic rings, and AlogP. Although compound properties were highly predictive attributes (12 % improvement over baseline) in the NN-based prediction of CYP2D6 binders, their combined use with docking score attributes is synergistic (net increase of 23 % above baseline). Beyond prediction of affinity, attribute selection provides a way to identify the most relevant protein conformation(s), in terms of binding competence. In the case of CYP2D6, three out of the ensemble of 20 SA-generated structures are found to be the most predictive for binding