TNF-α-induced osteoclastogenesis is central to post-menopausal and inflammatory bone loss, however, the effect of phytoestrogens on TNF-α-induced bone resorption has not been studied. The phytoestrogens genistein, daidzein, and coumestrol directly suppressed TNF-α-induced osteoclastogenesis and bone resorption. TRAP positive osteoclast formation and resorption area were significantly reduced by genistein (10(-7) M), daidzein (10(-5) M), and coumestrol (10(-7) M), which was prevented by the estrogen antagonist ICI 182,780. TRAP expression in mature TNF-α-induced osteoclasts was also significantly reduced by these phytoestrogen concentrations. In addition, in the presence of ICI 182,780 genistein and coumestrol (10(-5) -10(-6) M) augmente

An aromatic ester containing two azo groups namely p-nitro phenyl azo-β-naphthyl-(4'-azobenzoic acid)-4-benzoate was synthesized by esterfiaction of 4,4'-azo dibenzoic acid with p-nitro phenyl azo-β-naphthol. Synthesized ester was characterized by CHN-Elemental analysis, FTIR, 1H NMR and 13C NMR. A modified PVA polymer was obtained by grafting 10 g of PVA-polymer via partial esterification with (2, 3, 4 g) p-nitro phenyl azo-1-naphthyl-4-azobenzoic acid)-4-azo benzoate. Grafting PVA-polymer behaviours was studied, by physical measurements (solubility, swelling), thermal properties (DSC) and tensile.

The synthesized ligand [4-chloro-5-(N-(5,5-dimethyl-3-oxocyclohex-1-en-1-yl)sulfamoyl)-2-((furan-2-ylmethyl)amino)benzoic acid] (H2L1) was identified utilizing Fourier transform infrared spectroscopy (FT-IR), 1 H, 13 C – NMR, (C.H.N), Mass spectra, UVVis methods based on spectroscopy. To detect mixed ligand complexes, analytical and spectroscopic approaches such as micro-analysis, conductance, UV-Visible, magnetic susceptibility, and FT-IR spectra were utilized. Its mixed ligand complexes [M(L1)(Q)Cl2] [ where M= Co(II), Ni(II) , and Cd(II)] and complexes [Pd(L1)(Q)] and [Pt(L1)(Q)Cl2]; [H2L1] =β-enaminone ligand =L1 and Q= 8-Hydroxyquinoline = L2]. The results showed that the complexes were synthesised utilizing the molar ratio M: L1

Out of 150 clinical samples, 50 isolates of Klebsiella pneumoniae were identified according to morphological and biochemical properties. These isolates were collected from different clinical samples, including 15 (30%) urine, 12 (24%) blood, 9 (18%) sputum, 9 (18%) wound, and 5 (10%) burn. The minimum inhibitory concentrations (MICs) assay revealed that 25 (50%) of isolates were resistant to gentamicin (≥16µg/ml), 22 (44%) of isolates were resistant to amikacin (≥64 µg/ml), 21 (42%) of isolates were resistant to ertapenem (≥8 µg/ml), 18 (36%) of isolates were resistant to imipenem (4- ≥16µg/ml), 43 (86%) of isolates were resistant to ceftriaxone (4- ≥64 µg/ml), 42 (84%) of isolates were resistant to ceftazidime (1

Recently, numerous the generalizations of Hurwitz-Lerch zeta functions are investigated and introduced. In this paper, by using the extended generalized Hurwitz-Lerch zeta function, a new Salagean’s differential operator is studied. Based on this new operator, a new geometric class and yielded coefficient bounds, growth and distortion result, radii of convexity, star-likeness, close-to-convexity, as well as extreme points are discussed.

The analysis of survival and reliability considered of topics and methods of vital statistics at the present time because of their importance in the various demographical, medical, industrial and engineering fields. This research focused generate random data for samples from the probability distribution Generalized Gamma: GG, known as: "Inverse Transformation" Method: ITM, which includes the distribution cycle integration function incomplete Gamma integration making it more difficult classical estimation so will be the need to illustration to the method of numerical approximation and then appreciation of the function of survival function. It was estimated survival function by simulation the way "Monte Carlo". The Entropy method used for the

This paper deals with, Bayesian estimation of the parameters of Gamma distribution under Generalized Weighted loss function, based on Gamma and Exponential priors for the shape and scale parameters, respectively. Moment, Maximum likelihood estimators and Lindley’s approximation have been used effectively in Bayesian estimation. Based on Monte Carlo simulation method, those estimators are compared in terms of the mean squared errors (MSE’s).

This paper aims at introducing a new generalized differential operator and new subclass of analytic functions to obtain some interesting properties like coefficient estimates and fractional derivatives.

     In this paper, suggested formula as well a conventional method for estimating the twoparameters (shape and scale) of the Generalized Rayleigh Distribution was proposed. For different sample sizes (small, medium, and large) and assumed several contrasts for the two parameters a percentile estimator was been used. Mean Square Error was implemented as an indicator of performance and comparisons of the performance have been carried out through data analysis and computer simulation between the suggested formulas versus the studied formula according to the applied indicator. It was observed from the results that the suggested method which was performed for the first time (as far as we know), had highly advantage than t