Quorum sensing (QS) is a perfectly orchestrated molecular communication system. It is a boon for Klebsiella pneumoniae, and bane for the host. This system is believed to make K. pneumoniae a leading cause of multidrug-resistant (MDR) nosocomial infections. This study aimed to investigate the antibacterial and anti-biofilm potential of medicinal plant extracts through interfering with QS of K. pneumoniae. The effect of different concentrations of ethanolic extracts of cinnamon and clove on K. pneumoniae was determined by analyzing the growth curve, survival assay (MTT), Qualitative and quantitative biofilm formation, antibiotic resistance, along with studying gene expression of the genes encoding the above traits, using quantitative real time polymerase chain reaction (qRT-PCR). The low concentrations of the plant extracts did not affect neither on the bacterial growth, nor on the viability of K. pneumoniae, supported with growth curves. Additionally, the biofilm production was inhibited even by lower plant concentrations, and both cinnamon and clove extracts were able to render the MDR bacteria to be more susceptible to antibiotics. At the molecular levels, the bacterium treated with either clove or cinnamon or in combination showed under expression of the biofilm formation regulation gene (bssS), the carbapenem resistance gene (bla), as well as the QS target gene (LuxS). Both clove and cinnamon ethanolic extracts exerted potent impacts on reducing pathogenic traits regulated by QS in K. pneumoniae. Finally, the study recommends further exploration of clove and cinnamon extracts separately or in combination to develop alternative therapies against MDR K. pneumoniae infections.
A new efficient Two Derivative Runge-Kutta method (TDRK) of order five is developed for the numerical solution of the special first order ordinary differential equations (ODEs). The new method is derived using the property of First Same As Last (FSAL). We analyzed the stability of our method. The numerical results are presented to illustrate the efficiency of the new method in comparison with some well-known RK methods.
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Background: Moral distress, as one of the most important issues in the nursing profession, can negatively affect the healthcare system. Purpose: To examine the effect of moral distress on professional quality work life. Method: A descriptive cross-sectional study a non-probability sampling method used and total sample collected was (126) of ICU nurses. Results: Moral distress, BO, STS, and, CS among ICUs nurses were moderate. Conclusion: Nurses in ICUs suffered from moderate MD which that effected their BO and STS, and the result can be negative effects on quality of care. Although MD did not affect nurses' CS, it is still an important issue that nurses may face in ICUs
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In this paper the effect of engagement length, number of teeth, amount of applied load, wave propagation time, number of cycles, and initial crack length on the principal stress distribution, velocity of crack propagation, and cyclic crack growth rate in a spline coupling subjected to cyclic torsional impact have been investigated analytically and experimentally. It was found that the stresses induced due to cyclic impact loading are higher than the stresses induced due to impact loading with high percentage depends on the number of cycles and total loading time. Also increasing the engagement length and the number of teeth reduces the principal stresses (40%) and
(25%) respectively for increasing the engagement length from (0.15 to 0
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Transmission lines are generally subjected to faults, so it is advantageous to determine these faults as quickly as possible. This study uses an Artificial Neural Network technique to locate a fault as soon as it happens on the Doukan-Erbil of 132kv double Transmission lines network. CYME 7.1-Programming/Simulink utilized simulation to model the suggested network. A multilayer perceptron feed-forward artificial neural network with a back propagation learning algorithm is used for the intelligence locator's training, testing, assessment, and validation. Voltages and currents were applied as inputs during the neural network's training. The pre-fault and post-fault values determined the scaled values. The neural network's p
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An integrated GIS-VBA (Geographical Information System – Visual Basic for Application), model is developed for selecting an optimum water harvesting dam location among an available locations in a watershed. The proposed model allows quick and precise estimation of an adopted weighted objective function for each selected location. In addition to that for each location, a different dam height is used as a nominee for optimum selection. The VBA model includes an optimization model with a weighted objective function that includes beneficiary items (positive) , such as the available storage , the dam height allowed by the site as an indicator for the potential of hydroelectric power generation , the rainfall rate as a source of water . In a
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