Infection of the gastric mucosa with Helicobacter pylori is strongly associated with chronic gastritis, peptic ulcer and gastric cancer. Helicobacter pylori virulence factors include a variety of proteins that are involved in its pathogenesis, such as VacA and CagA. Another group of virulence factors is clearly important for colonization of H.pylori in the gastric mucosa. These include urease, motility factors (flagellin), and Superoxide dismutase (SOD). Because of this organism's microaerophilic nature and the increased levels of reactive oxygen in the infected host, we expect that other factors involved in the response to oxidative stress are likely to be required for virulence. Superoxide dismutase is a near

1-[4-(2-Hydroxy-4, 6-dimethyl-phenylazo)-phenol]-ethanone (HL1) and 2-(4-methoxy-phenylazo)-3, 5- dimethyl-phenol (HL2) were produced by combination the diazonium salts of amines with 3, 5- dimethylphenol. The geometry of azo compounds was resolved on the basis of (C.H.N) analyses, 1H and 13CNMR, FT-IR and UV-Vis spectroscopic mechanisms. Complexes of La (III) and Rh (III) have been performed and depicted. The formation of complexes has been identified by using elemental analysis, FTIR and UV-Vis spectroscopic process as well, conductivity molar quantifications. Nature of complexes produced have been studied obeyed mole ratio and continuous alteration ways, Beer's law followed through a concentration scope (1×10-4 - 3×10-4 M). High molar

This paper describes the problem of online autonomous mobile robot path planning, which is consisted of finding optimal paths or trajectories for an autonomous mobile robot from a starting point to a destination across a flat map of a terrain, represented by a 2-D workspace. An enhanced algorithm for solving the problem of path planning using Bacterial Foraging Optimization algorithm is presented. This nature-inspired metaheuristic algorithm, which imitates the foraging behavior of E-coli bacteria, was used to find the optimal path from a starting point to a target point. The proposed algorithm was demonstrated by simulations in both static and dynamic different environments. A comparative study was evaluated between the developed algori

The increasing anti-bacterial drug resistance is one of the biggest challenges facing doctors around the globe, so finding alternative treatments is one of the ideal options to overcome this problem. The cruciferous family is one of the wealthiest plants worldwide because it contains the most important secondary metabolites, glucosinolates, known for their anti-microbial properties. The present study aimed to evaluate the anti-bacterial effect of glucosinolates (Sinigrin) against eight bacterial isolates (Staphylococcus aureus, Enterococcus faecalis, Escherichia coli, Klebsiella pneumoniae, Pseudomonas aeruginosa, Actinomyces, Proteus mirabilis and Streptococcus pneumoniae). The current study investigated six concentrations of pure

A new modified differential evolution algorithm DE-BEA, is proposed to improve the reliability of the standard DE/current-to-rand/1/bin by implementing a new mutation scheme inspired by the bacterial evolutionary algorithm (BEA). The crossover and the selection schemes of the DE method are also modified to fit the new DE-BEA mechanism. The new scheme diversifies the population by applying to all the individuals a segment based scheme that generates multiple copies (clones) from each individual one-by-one and applies the BEA segment-wise mechanism. These new steps are embedded in the DE/current-to-rand/bin scheme. The performance of the new algorithm has been compared with several DE variants over eighteen benchmark functions including sever

Four local hemolysin producer bacterial isolates were selected, tow of them gram negative bacteria (Escherichia coli ,Pseudomonas aeruginosa ) and the other two were gram positive bacteria (Staphylococcus aureus , Bacillus cereus ). Minimum inhibitory concentration of the aqueous and alcoholic extracts of Punica granatum L. pericarp were determined towards the four bacterial isolates ,results obtaind showed that MICs of the aqueous extract were 200 mg/ml for E .coli and P. aeruginosa isolates while were 5 mg/ml and 2 mg/ml for B. cereus, S. aureus , respectively The MICs for the ethanolic extract were 50 mg/ml , 20 mg/ml ,1 mg/ml ,0.5 mg/ml for E. coli ,P. aeruginosa ,B. cereus ,S. aureus , respectively. The effect of Sub-MICs o