Escherichia coli of sequence type 3835 carrying blaNDM-1, blaCTX-M-15, blaCMY-42 and blaSHV-12

New Delhi metallo-β-lactamase (NDM) represents a serious challenge for treatment and public health. A carbapenem-resistant Escherichia coli clinical strain WCHEC13-8 was subjected to antimicrobial susceptibility tests, whole genome sequencing and conjugation experiments. It was resistant to imipenem (MIC, >256 μg/ml) and meropenem (MIC, 128 μg/ml) and belonged to ST3835. blaNDM-1 was the only carbapenemase gene detected. Strain WCHEC13-8 also had a plasmid-borne AmpC gene (blaCMY-42) and two extended-spectrum β-lactamase genes (blaCTX-M-15 and blaSHV-12). blaNDM-1 and blaSHV-12 were carried by a 54-kb IncX3 self-transmissible plasmid, which is identical to plasmid pNDM-HF727 from Enterobacter cloacae. blaCMY-42 was carried by a 64-kb IncI1 plasmid and blaCTX-M-15 was located on a 141-kb plasmid with multiple F replicons (replicon type: F36:A4:B1). blaCMY-42 was in a complicated context and the mobilisation of blaCMY-42 was due to the transposition of IS Ecp1 by misidentifying its right-end boundary. Genetic context of blaNDM-1 in strain WCHEC13-8 was closely related to those on IncX3 plasmids in various Enterobacteriaceae species in China. In conclusion, a multidrug-resistant ST3835 E. coli clinical strain carrying blaNDM-1, blaCTX-M-15, blaCMY-42 and blaSHV-12 was identified. IncX3 plasmids may be making a significant contribution to the dissemination of blaNDM among Enterobacteriaceae in China

Insights from ARPES for an undoped, four-layered, two-gap high-T_c superconductor

An undoped cuprate with apical fluorine and inner (i) and outer (o) CuO2-layers is a 60 K superconductor whose Fermi surface (FS) has large n- and p-doped sheets with the SC gap on the n-sheet twice that on the p -sheet (Y. Chen et al.). The Fermi surface is not reproduced by the LDA, but the screening must be substantially reduced due to electronic correlations, and oxygen in the o-layers must be allowed to dimple outwards. This charges the i-layers by 0.01|e|, causes an 0.4 eV Madelung-potential difference between the i and o -layers, quenches the i-o hopping, and localizes the n-sheets onto the i-layers, thus protecting their d-wave pairs from being broken by scattering on impurities in the BaF layers. The correlation-reduced screening strengthens the coupling to z-axis phonons.Comment: 4 pages, 3 figure

A system for learning statistical motion patterns

Analysis of motion patterns is an effective approach for anomaly detection and behavior prediction. Current approaches for the analysis of motion patterns depend on known scenes, where objects move in predefined ways. It is highly desirable to automatically construct object motion patterns which reflect the knowledge of the scene. In this paper, we present a system for automatically learning motion patterns for anomaly detection and behavior prediction based on a proposed algorithm for robustly tracking multiple objects. In the tracking algorithm, foreground pixels are clustered using a fast accurate fuzzy k-means algorithm. Growing and prediction of the cluster centroids of foreground pixels ensure that each cluster centroid is associated with a moving object in the scene. In the algorithm for learning motion patterns, trajectories are clustered hierarchically using spatial and temporal information and then each motion pattern is represented with a chain of Gaussian distributions. Based on the learned statistical motion patterns, statistical methods are used to detect anomalies and predict behaviors. Our system is tested using image sequences acquired, respectively, from a crowded real traffic scene and a model traffic scene. Experimental results show the robustness of the tracking algorithm, the efficiency of the algorithm for learning motion patterns, and the encouraging performance of algorithms for anomaly detection and behavior prediction