Pseudomonas aeruginosa, a ubiquitous environmental organism, is a difficult-to-treat opportunistic pathogen due to its broad-spectrum antibiotic resistance and its ability to form biofilms. In this study, we investigate the link between resistance to a clinically important antibiotic, imipenem, and biofilm formation. First, we observed that the laboratory strain P. aeruginosa PAO1 carrying a mutation in the oprD gene, which confers resistance to imipenem, showed a modest reduction in biofilm formation.We also observed an inverse relationship between imipenem resistance and biofilm formation for imipenem-resistant strains selected in vitro, as well as for clinical isolates.We identified two clinical isolates of P. aeruginosa from the sputum of cystic fibrosis patients that formed robust biofilms, but were sensitive to imipenem (MIC≤2 μg/ml). To test the hypothesis that there is a general link between imipenem resistance and biofilm formation, we performed transposon mutagenesis of these two clinical strains to identify mutants defective in biofilm formation, and then tested these mutants for imipenem resistance. Analysis of the transposon mutants revealed a role for previously described biofilm factors in these clinical isolates of P. aeruginosa, including mutations in the pilY1, pilX, pilW, algC, and pslI genes, but none of the biofilmdeficient mutants became imipenem resistant (MIC≥8 μg/ml), arguing against a general link between biofilm formation and resistance to imipenem. Thus, assessing biofilm formation capabilities of environmental isolates is unlikely to serve as a good predictor of imipenem resistance. We also discuss our findings in light of the limited literature addressing planktonic antibiotic resistance factors that impact biofilm formation.
Deep learning has recently received a lot of attention as a feasible solution to a variety of artificial intelligence difficulties. Convolutional neural networks (CNNs) outperform other deep learning architectures in the application of object identification and recognition when compared to other machine learning methods. Speech recognition, pattern analysis, and image identification, all benefit from deep neural networks. When performing image operations on noisy images, such as fog removal or low light enhancement, image processing methods such as filtering or image enhancement are required. The study shows the effect of using Multi-scale deep learning Context Aggregation Network CAN on Bilateral Filtering Approximation (BFA) for d
... Show MoreIn this work, silicon nitride (Si3N4) thin films were deposited on metallic substrates (aluminium and titanium sheets) by the DC reactive sputtering technique using two different silicon targets (n-type and p-type Si wafers) as well as two Ar:N2 gas mixing ratios (50:50 and 70:30). The electrical conductivity of the metallic (aluminium and titanium) substrates was measured before and after the deposition of silicon nitride thin films on both surfaces of the substrates. The results obtained from this work showed that the deposited films, in general, reduced the electrical conductivity of the substrates, and the thin films prepared from n-type silicon targets using a 50:50 mixing ratio and deposited on both
... Show MoreInundation floodingmap aimedto find outearly warningsto avoidenvironmental damageandhumanin terms of theheight ofthe wave ofwater, speed time arrival, effects of inundation sideanddepth of the water/ distanceand reduce the impact of the flood wave after obtaining the process of collapse of the dam in the lower part of the river to the dam area. The study has been using a numerical model one-dimensional depends on the development of equations (Saint-Venant) so that parts of the river, any river channel main banks of the right and left treated as separate parts, that’s the difference in the characteristics of the hydraulic and engineering, along the line of the flow will take into account in each section of the sections and flow in the riv
... Show MoreWater flooding is one of the most important methods used in enhanced production; it was a pioneer method in use, but the development of technology within the oil industry, takes this subject toward another form in the oil production and application in oil fields with all types of oils and oil reservoirs. Now days most of the injection wells directed from the vertical to re-entry of full horizontal wells in order to get full of horizontal wells advantages.
This paper describes the potential benefits for using of re-entry horizontal injection wells as well as combination of re –entry horizontal injection and production wells. Al Qurainat productive sector was selected for study, which is one of the four main productive sectors of Sout
The microstructures of rapidly solidified laser clad layers of laser cladding of Inconel 617 with different nickel-aluminum premixed clad powders are discussed. The effect of different cladding speeds on the microstructures of rapidly solidified laser clad layers is discussed too. The detailed microstructural results showed that different growth mechanisms are produced during rapid solidification. These are planar, cellular, cellular/dendritic and dendritic.
An experimental study was conducted with low cost natural waste adsorbent materials, barley husks and eggshells, for the removal of Levofloxacine (LEVX) antibacterial from synthetic waste water. Batch sorption tests were conducted to study their isothermal adsorption capacity and compared with conventional activated carbon which were, activated carbon > barley husks > eggshells with removal efficiencies 74, 71 and 42 % with adsorbents doses of 5, 5 and 50 g/L of activated carbon, barley husks, and eggshells respectively. The equilibrium sorption isotherms had been analyzed by Langmuir, Freundlich, and Sips models, and their parameters were evaluated. The experimental data were correlated well with the Langmuir model which gives the
... Show MoreMammography is at present one of the available method for early detection of masses or abnormalities which is related to breast cancer. The most common abnormalities that may indicate breast cancer are masses and calcifications. The challenge lies in early and accurate detection to overcome the development of breast cancer that affects more and more women throughout the world. Breast cancer is diagnosed at advanced stages with the help of the digital mammogram images. Masses appear in a mammogram as fine, granular clusters, which are often difficult to identify in a raw mammogram. The incidence of breast cancer in women has increased significantly in recent years.
This paper proposes a computer aided diagnostic system for the extracti