A 96-well plate fluorescence assay for assessment of cellular permeability and active efflux in Salmonella enterica serovar Typhimurium and Escherichia coli

Multiply antibiotic-resistant (MAR) mutants of Escherichia coli and Salmonella enterica are characterized by reduced susceptibility to several unrelated antibiotics, biocides and other xenobiotics. Porin loss and/or active efflux have been identified as a key mechanisms of MAR. A single rapid test was developed for MAR. The intracellular accumulation of the fluorescent probe Hoechst (H) 33342 (bisbenzimide) by MAR mutants and those with defined disruptions in efflux pump and porin genes was determined in 96-well plate format. The accumulation of H33342 was significantly (P < 0.0001) reduced in MAR mutants of S. enterica serovar Typhimurium (n = 4) and E. coli (n = 3) by 41 +/- 8% and 17.3 +/- 7.2%, respectively, compared with their parental strains, which was reversed by the transmembrane proton gradient-collapsing agent carbonyl cyanide-m-chlorophenyl hydrazone (CCCP) and the efflux pump inhibitor phenylalanine-arginine-beta-naphthylamide (PA beta N). The accumulation of H33342 was significantly reduced in mutants of Salmonella Typhimurium with defined disruptions in genes encoding the porins OmpC, OmpF, OmpX and OmpW, but increased in those with disruptions in efflux pump components TolC, AcrB and AcrF. Reduced accumulation of H33342 in three other MAR mutants of Salmonella Typhimurium correlated with the expression of porin and efflux pump proteins. The intracellular accumulation of H33342 provided a sensitive and specific test for MAR that is cheap and relatively rapid. Differential sensitivity to CCCP and PA beta N provided a further means to phenotypically identify MAR mutants and the role of active efflux in each strain.

Advances in sequential data assimilation and numerical weather forecasting: an Ensemble Transform Kalman-Bucy Filter, a study on clustering in deterministic Ensemble Square Root Filters, and a test of a new time stepping scheme in an atmospheric model

This dissertation deals with aspects of sequential data assimilation (in particular ensemble Kalman filtering) and numerical weather forecasting. In the first part, the recently formulated Ensemble Kalman-Bucy (EnKBF) filter is revisited. It is shown that the previously used numerical integration scheme fails when the magnitude of the background error covariance grows beyond that of the observational error covariance in the forecast window. Therefore, we present a suitable integration scheme that handles the stiffening of the differential equations involved and doesn’t represent further computational expense. Moreover, a transform-based alternative to the EnKBF is developed: under this scheme, the operations are performed in the ensemble space instead of in the state space. Advantages of this formulation are explained. For the first time, the EnKBF is implemented in an atmospheric model. The second part of this work deals with ensemble clustering, a phenomenon that arises when performing data assimilation using of deterministic ensemble square root filters in highly nonlinear forecast models. Namely, an M-member ensemble detaches into an outlier and a cluster of M-1 members. Previous works may suggest that this issue represents a failure of EnSRFs; this work dispels that notion. It is shown that ensemble clustering can be reverted also due to nonlinear processes, in particular the alternation between nonlinear expansion and compression of the ensemble for different regions of the attractor. Some EnSRFs that use random rotations have been developed to overcome this issue; these formulations are analyzed and their advantages and disadvantages with respect to common EnSRFs are discussed. The third and last part contains the implementation of the Robert-Asselin-Williams (RAW) filter in an atmospheric model. The RAW filter is an improvement to the widely popular Robert-Asselin filter that successfully suppresses spurious computational waves while avoiding any distortion in the mean value of the function. Using statistical significance tests both at the local and field level, it is shown that the climatology of the SPEEDY model is not modified by the changed time stepping scheme; hence, no retuning of the parameterizations is required. It is found the accuracy of the medium-term forecasts is increased by using the RAW filter.

Passive and active hybrid approach to buildings design in Saudi Arabia

The building sector is one of the highest consumers of energy in the world. This has led to high dependency on using fossil fuel to supply energy without due consideration to its environmental impact. Saudi Arabia has been through rapid development accompanied by population growth, which in turn has increased the demand for construction. However, this fast development has been met without considering sustainable building design. General design practices rely on using international design approaches and features without considering the local climate and aspects of traditional passive design. This is by constructing buildings with a large amount of glass fully exposed to solar radiation. The aim of this paper is to investigate the development of sustainability in passive design and vernacular architecture. Furthermore, it compares them with current building in Saudi Arabia in terms of making the most of the climate. Moreover, it will explore the most sustainable renewable energy that can be used to reduce the environmental impact on modern building in Saudi Arabia. This will be carried out using case studies demonstrating the performance of vernacular design in Saudi Arabia and thus its benefits in terms of environmental, economic and social sustainability. It argues that the adoption of a hybrid approach can improve the energy efficiency as well as reduce the carbon footprint of buildings. This is by combining passive design, learning from the vernacular architecture and implementing innovative sustainable technologies.

Identification of critical residues in the active site of porcine membrane-bound aminopeptidase P

The membrane-bound form of mammalian aminopeptidase P (AP-P; EC 3.4. 11.9) is a mono-zinc-containing enzyme that lacks any of the typical metal binding motifs found in other zinc metalloproteases. To identify residues involved in metal binding and catalysis, sequence and structural information was used to align the sequence of porcine membrane-bound AP-P with other members of the peptidase clan MG, including Escherichia coli AP-P and methionyl aminopeptidases. Residues predicted to be critical for activity were mutated and the resultant proteins were expressed in COS-1 cells. Immunoelectrophoretic blot analysis was used to compare the levels of expression of the mutant proteins, and their ability to hydrolyze bradykinin and Gly-Pro-hydroxyPro was assessed. Asp449, Asp460, His523, Glu554, and Glu568 are predicted to serve as metal ion ligands in the active site, and mutagenesis of these residues resulted in fully glycosylated proteins that were catalytically inactive. Mutation of His429 and His532 also resulted in catalytically inactive proteins, and these residues, by analogy with E. coli AP-P, are likely to play a role in shuttling protons during catalysis. These studies indicate that mammalian membrane-bound AP-P has an active-site configuration similar to that of other members of the peptidase clan MG, which is compatible with either a dual metal ion model or a single metal ion in the active site. The latter model is consistent, however, with the known metal stoichiometry of both the membrane-bound and cytosolic forms of AP-P and with a recently proposed model for methionyl aminopeptidase.

Redox-active, dinuclear sandwich compounds [Cp*Fe(μ-L)FeCp*] (L = naphthalene and anthracene)

Although there has been much interest in the chemistry of bimetallic transition metal complexes, compounds with naphthalene or anthracene as bridging ligands are still rare. In this article, we describe the synthesis of the homodinuclear iron complexes [Cp*Fe(μ-η4:η4-L)FeCp*] (1: L = C10H8, 2: L = C14H10; Cp* = η5-C5Me5). The complexes were characterized by 1H and 13C{1H} NMR, UV/Vis, and 57Fe Mössbauer spectroscopy, and their molecular structures were determined by X-ray crystallography. Both complexes are diamagnetic as a result of the strong magnetic coupling of the 17e FeI centers mediated by the polyarene bridge. An analysisof the redox behavior of 1 and 2 by cyclic voltammetry andUV/Vis spectroelectrochemistry shows that the complexes can be oxidized reversibly in two well-separated one-electron steps to the monocation [Cp*Fe(μ-L)FeCp*]+ and the dication [Cp*Fe(μ-L)FeCp*]2+. The reduction to the monoanion [Cp*Fe(μ-L)FeCp*]– was also observed.

Altitude acts as an environmental filter on phylogenetic composition, traits and diversity in bee communities.

Knowledge about the phylogeny and ecology of communities along environmental gradients helps to disentangle the role of competition-driven processes and environmental filtering for community assembly. In this study, we evaluated patterns in species richness, phylogenetic structure and life-history traits of bee communities along altitudinal gradients in the Alps, Germany. We found a linear decline in species richness and abundance but increasing phylogenetic clustering in communities with increasing altitude. The proportion of social- and ground-nesting species, as well as mean body size and altitudinal range of bee communities, increased with increasing altitude, whereas the mean geographical distribution decreased. Our results suggest that community assembly at high altitudes is dominated by environmental filtering effects, whereas the relative importance of competition increases at low altitudes. We conclude that inherent phylogenetic and ecological species attributes at high altitudes pose a threat for less competitive alpine specialists with ongoing climate change.

A low-order model investigation of the analysis of gravity waves in the ensemble Kalman filter.

The behavior of the ensemble Kalman filter (EnKF) is examined in the context of a model that exhibits a nonlinear chaotic (slow) vortical mode coupled to a linear (fast) gravity wave of a given amplitude and frequency. It is shown that accurate recovery of both modes is enhanced when covariances between fast and slow normal-mode variables (which reflect the slaving relations inherent in balanced dynamics) are modeled correctly. More ensemble members are needed to recover the fast, linear gravity wave than the slow, vortical motion. Although the EnKF tends to diverge in the analysis of the gravity wave, the filter divergence is stable and does not lead to a great loss of accuracy. Consequently, provided the ensemble is large enough and observations are made that reflect both time scales, the EnKF is able to recover both time scales more accurately than optimal interpolation (OI), which uses a static error covariance matrix. For OI it is also found to be problematic to observe the state at a frequency that is a subharmonic of the gravity wave frequency, a problem that is in part overcome by the EnKF.However, error in themodeled gravity wave parameters can be detrimental to the performance of the EnKF and remove its implied advantages, suggesting that a modified algorithm or a method for accounting for model error is needed.

Electro-active nanofibres electrospun from blends of poly-vinyl cinnamate and a cholesteric liquid crystalline silicone polymer

Electrospinning was used to generate polymer nanofibres from blends of poly-vinyl cinnamate (PVCN) and a cholesteric silicone polymer. Only blends that contained at least 40 % of PVCN produced fibres. Both differential scanning calorimetry and electron dispersion spectroscopy data indicate that the samples are miscible over a wide temperature interval. The variation of fibre diameter with concentration is nonlinear with a well-defined minimum corresponding to an 80 % PVCN blend. The fibres are birefringent with Kerr constants similar to that of cholesteric liquid crystals. Although not significant, the Kerr constant increases with increasing silicone polymer concentration.

A Gaussian-mixture ensemble transform filter

We generalize the popular ensemble Kalman filter to an ensemble transform filter, in which the prior distribution can take the form of a Gaussian mixture or a Gaussian kernel density estimator. The design of the filter is based on a continuous formulation of the Bayesian filter analysis step. We call the new filter algorithm the ensemble Gaussian-mixture filter (EGMF). The EGMF is implemented for three simple test problems (Brownian dynamics in one dimension, Langevin dynamics in two dimensions and the three-dimensional Lorenz-63 model). It is demonstrated that the EGMF is capable of tracking systems with non-Gaussian uni- and multimodal ensemble distributions. Copyright © 2011 Royal Meteorological Society