Characterisation of the MacA/MacB/TolC tripartite pump that confers resistance to macrolides in E. coli

Gram-negative bacteria possess tripartite pumps, composed of a membrane fusion protein (MFP), an inner membrane protein (IMP) and an outer membrane protein (OMP), to transport drugs across the inner and outer membranes. The plasmid encoding MacA, MacB and TolC confers resistance to the macrolide erythromycin in the host E. coli cell Kam3, indicating the three proteins are assembled and actively functional. MFPs are believed to have an important role in the stabilizing the pump complex; intriguingly, we found that the MFP MacA not only interacts directly with the IMP MacB and the OMP TolC, but regulates the function of MacB, apparently increasing its affinity for both ATP and erythromycin. As MacB hydrolyzes ATP there is a burst in phosphate production that is symptomatic of the reaction being rate- limited by product release; but the burst disappeared in the presence of MacA. Since MacA caused only a marginal increase in the k(_cat), but a significant decrease in the Km, for the steady-state ATPase activity, this suggests that the disappearance of the phosphate burst is due to a decrease in the rate of hydrolysis, rather than an increase in the rate of product release. This kinetic behaviour indicates that MacA promotes and stabilizes the ATP-binding form of the transporter. MacA regulates the activity of MacB via its ẞ-strand domain since S. aureus MacA, which lacks the coiled coil structure that is present in E. coli MacA and believed to be involved in the interaction with TolC, was able to abolish the Pi burst catalysed by MacB, in direct analogy with the effect of E. coli MacA on MacB. Analytical ultracentrifugation, mass spectrometry and atomic force microscopy indicated that MacB forms dimers, in analogy to ABC- transporters that require a pair of NBDs to bind ATP. Our data suggests a direct role for MacA in facilitating the delivery of drugs by MacB to TolC: by enhancing the binding of drugs to MacB and stabilizing the reorientation of MacB to the outward- facing conformation

Particle bonding mechanism in CGDS-a three-dimensional approach

Abstract: Cold gas dynamics spray (CGDS) is a surface coating process using highly accelerated particles to form the surface coating by high speed impact of the particles. In the CGDS process, metal particles of generally 1-50 μm diameter is carried by a gas stream in high pressure (typically 20-30 atm) through a DE Laval type nozzle to achieve supersonic flying so as to impact on the substrate. Typically, the impact velocity ranges between 300 and 1200 m/s in the CGDS process. When the particle gains its critical velocity, the minimum in-flight speed at which it can deposit, adiabatic shear instabilities will occur. Herein, to ascertain the critical velocities of different particle sizes on the bonding efficiency in CGDS process, three-dimensional numerical simulations of single particle deposition process were performed. In the CGDS process, one of the most important parameters which determine the bonding strength with the substrate is particle impact temperature. Bonding will occur when the particle’s impacting velocity surpass the critical velocity, at which the interface can achieve 60 % of melting temperature of particle material (Ref 1). Therefore, critical velocity should be a main parameter on the coating quality. The particle critical velocity is determined not only by its size, but also by its material properties. This study numerically investigate the critical velocity for the particle deposition process in CGDS. In the present numerical analysis, copper (Cu) was chosen as particle material and aluminum (Al) as substrate material for this study. The impacting velocities were selected between 300 m/s and 800 m/s increasing in steps of 100 m/s. The simulation result reveals temporal and spatial interfacial temperature distribution and deformation between particle(s) and substrate. Finally, comparison is carried out between the computed results and experimental data

Spatial and temporal EEG dynamics of dual-task driving performance

<p>Abstract</p> <p>Background</p> <p>Driver distraction is a significant cause of traffic accidents. The aim of this study is to investigate Electroencephalography (EEG) dynamics in relation to distraction during driving. To study human cognition under a specific driving task, simulated real driving using virtual reality (VR)-based simulation and designed dual-task events are built, which include unexpected car deviations and mathematics questions.</p> <p>Methods</p> <p>We designed five cases with different stimulus onset asynchrony (SOA) to investigate the distraction effects between the deviations and equations. The EEG channel signals are first converted into separated brain sources by independent component analysis (ICA). Then, event-related spectral perturbation (ERSP) changes of the EEG power spectrum are used to evaluate brain dynamics in time-frequency domains.</p> <p>Results</p> <p>Power increases in the theta and beta bands are observed in relation with distraction effects in the frontal cortex. In the motor area, alpha and beta power suppressions are also observed. All of the above results are consistently observed across 15 subjects. Additionally, further analysis demonstrates that response time and multiple cortical EEG power both changed significantly with different SOA.</p> <p>Conclusions</p> <p>This study suggests that theta power increases in the frontal area is related to driver distraction and represents the strength of distraction in real-life situations.</p

Face recognition using nonparametric-weighted Fisherfaces

This study presents an appearance-based face recognition scheme called the nonparametric-weighted Fisherfaces (NW-Fisherfaces). Pixels in a facial image are considered as coordinates in a high-dimensional space and are transformed into a face subspace for analysis by using nonparametric-weighted feature extraction (NWFE). According to previous studies of hyperspectral image classification, NWFE is a powerful tool for extracting hyperspectral image features. The Fisherfaces method maximizes the ratio of between-class scatter to that of within-class scatter. In this study, the proposed NW-Fisherfaces weighted the between-class scatter to emphasize the boundary structure of the transformed face subspace and, therefore, enhances the separability for different persons' face. The proposed NW-Fisherfaces was compared with Orthogonal Laplacianfaces, Eigenfaces, Fisherfaces, direct linear discriminant analysis, and null space linear discriminant analysis methods for tests on five facial databases. Experimental results showed that the proposed approach outperforms other feature extraction methods for most databases. © 2012 Li et al