Proteus mirabilis is considered as a third common cause of catheter-associated urinary tract infection, with urease production, the potency of catheter blockage due to the formation of biofilm formation is significantly enhanced. Biofilms are major virulence factors expressed by pathogenic bacteria to resist antibiotics; in this concern the need for providing new alternatives for antibiotics is getting urgent need, This study aimed to explore whether green synthesized zinc oxide nanoparticles (ZnO NPs) can function as an anti-biofilm agent produced by P.mirabilis. Bacterial cells were capable of catalyzing the biosynthesis process by producing reductive enzymes. The nanoparticles were synthesized from cell free extract of P.mirabilis. Characterization of biosynthesized zinc nanoparticles was carried out to determine the chemical and physical properties of the product using AFM, TEM, FESEM, XRD and UV visible spectrometry. The hexagonal structure was confirmed by XRD, Particle size was marked at 84.45 nm by TEM, FESEM was used to confirm the surface morphology. AFM analysis was used to reveal the roughness and distribution of nanoparticles. UV–visible spectra of the synthesized nanoparticles recorded maximum peak at 287 nm. Zinc nanoparticles showed remarkable biofilm inhibitory effect on clinical isolates of multidrug resistant Proteus mirabilis. Strong biofilm producer strains show weak biofilm production After incubation for 24 and 48 hours at 37Co with 32 μg/ml sub -MIC concentration of ZnO nanoparticles. Down regulation changes in LuxS expression using Real time PCR technology were detected after treatment with zink nanoparticles of these isolates compared to untreated isolates. From all findings conducted by this study, zinc oxide nanoparticles can function as anti-bacterial agent in concentration dependent manner.
By definition, the detection of protein complexes that form protein-protein interaction networks (PPINs) is an NP-hard problem. Evolutionary algorithms (EAs), as global search methods, are proven in the literature to be more successful than greedy methods in detecting protein complexes. However, the design of most of these EA-based approaches relies on the topological information of the proteins in the PPIN. Biological information, as a key resource for molecular profiles, on the other hand, acquired a little interest in the design of the components in these EA-based methods. The main aim of this paper is to redesign two operators in the EA based on the functional domain rather than the graph topological domain. The perturb
... Show MoreAim of the study: Using surface roughness and tensile bond strength tests, the objective of this investigation was to ascertain the impact of laser surface modification on the binding strength of injectable thermoplastic acrylic denture base material to acrylic-based soft-liner material. Materials and methods: Acrylic base soft liner material was bonded to injectable thermoplastic acrylic resin (Deflex). Forty specimens were created (20 disc, 20 dumbbells) 10 of each specimen type as control specimens, and 10 were treated with nano pulse Nd: YAG laser. The data were analyzed using the Kruskal-Wallis test and unpaired t-test (a=.05) and the roughness test was performed utilizing a double column universal test machine. Results: Compar
... Show MoreIn this paper, the dynamic behaviour of the stage-structure prey-predator fractional-order derivative system is considered and discussed. In this model, the Crowley–Martin functional response describes the interaction between mature preys with a predator. e existence, uniqueness, non-negativity, and the boundedness of solutions are proved. All possible equilibrium points of this system are investigated. e sucient conditions of local stability of equilibrium points for the considered system are determined. Finally, numerical simulation results are carried out to conrm the theoretical results.
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 MoreThe optimum conditions for the production of neutral protease from local strain Aspergillus niger var carbonarius by solid – state fermentation system (Wheat bran) moisted with 0.2 M phosphate buffer (PH7.0) . the hydration ratio was 1:5 (V:W) . the concentration of inoculum was 1×106 spores per 10 gram of solid materials , initial P H 6.5 and 96 hours of incubation period at 30? C .the enzyme activity was 1300 unit / ml and specific activity was 1550 unit / mg protein .
This study thoroughly investigates the potential of niobium oxide (Nb2O5) thin films as UV-A photodetectors. The films were precisely fabricated using dc reactive magnetron sputtering on Si(100) and quartz substrates, maintaining a consistent power output of 50W while varying substrate temperatures. The dominant presence of hexagonal crystal structure Nb2O5 in the films was confirmed. An increased particle diameter at 150°C substrate temperature and a reduced Nb content at higher substrate temperatures were revealed. A distinct band gap with high UV sensitivity at 350 nm was determined. Remarkably, films sputtered using 50W displayed the highest photosensitivity at 514.89%. These outstanding optoelectronic properties highlight Nb2O5 thin f
... Show MoreObjective: This study aims to assess the efficacy of CT-guided true-cut biopsy as a less invasive and cost-effective diagnostic technique for peripherally placed lung lesions.
A direct, sensitive and efficient spectrophotometric method for the determination of nitrofurantoin
drug (NIT) in pure as well as in dosage form (capsules) was described. The suggested method was
based on reduction NIT drug using Zn/HCl and then coupling with 3-methyl-2-benzothiazolinone
hydrazone hydrochloride (MBTH) in the presence of ammonium ceric sulfate. Spectrophotometric
measurement was established by recording the absorbance of the green colored product at 610 nm.
Using the optimized reaction conditions, beer’s law was obeyed in the range of 0.5-30 μg/mL, with
good correlation coefficient of 0.9998 and limits of detection and quantitation of 0.163 and 0.544
μg/mL, respectively. The accuracy and