The new liganed Schiff base named [(E)-3-hydroxy-4-((3,4,5- trimethoxybenzylidene)amino) naphthalene-1- sulfonic acid] was synthesized from 3,4,5-trimethoxybenzyldehyde and 1-amino-2-aphthol-4- sulfonic acid in equal molar ratio. A series of new metal complexes' of the common molecular formulation [M(L)2(H2O)2].H2O are synthesized and characterized by IR, UV–Vis spectra, mass spectra, atomic absorption, elemental analyses, chloride content, magnetic susceptibility and conductivity measurements as well as thermo gravimetric analysis (TGA, DSC). Consistent with results of the magnetic and spectral studies, the advised geometrical structures for all of the prepared complexes have been octahedral formula

           In this research, the preparation of a chemically activated carbon from date stones by using electric and microwave assisted K₂CO₃ activation was studied. The effect of radiation power, radiation time, and impregnation ratio on the yield and Iodine number on the activated carbons was investigated. The activated carbon characterizations were examined by its surface area, pore structure analysis, bulk density, moisture content, ash content, iodine number, FTIR, and scanning electron microscopy (SEM). The adsorption capacity was also studied by adsorption of fluoroquinolones antibiotics, CIP, NOR, and LEVO, by the prepared activated carbon.

Objective: The aim of this study was to develop a bioadhesive gel of gatifloxacin for the treatment of periodontal diseases.Methods: Periodontal gels of gatifloxacin were prepared using different hydrophilic polymers such as carbopol 940 (CP 940), carboxymethyl cellulose (CMC) and hydroxypropylmethyl cellulose (HPMC) in varied concentrations, either alone or as a combination. The prepared gels were evaluated for their physical appearance, pH, drug content, viscosity, bioadhesiveness and in vitro drug release profile. The influence of the type and the concentration of polymer on the drug release as well as on viscosity and mucoadhesiveness of prepared gels were investigated.Results: The prepared gels showed acceptable physical proper

This study aims to formulate azithromycin oleogel to locally treat skin infections such as acne vulgaris and skin wound infection. Providing a form of azithromycin that can be administered topically is highly desired to prevent unwanted systemic complications including diarrhea, nausea, and abdominal pain. Additionally, it will avoid first pass metabolism, improves patient acceptance, provides an alternative in nauseated patients, decreases the dose by direct contact with the pathological site, and provides a noninvasive and convenient mode of administration. Furthermore, for treating wound infections, the gel will act as a scaffold biomaterial for wound closure besides its antibacterial effect. Herein, we propose the use of grapeseed oil-b

Endoglucanase produced from Aspergillus flavus was purified by several steps including precipitation with 25 % ammonium sulphate followed by Ion –exchange chromatography, the obtained specific activity was 377.35 U/ mg protein, with a yield of 51.32 % .This step was followed by gel filtration chromatography (Sepharose -6B), when a value of specific activity was 400 U/ mg protein, with a yield of 48 %. Certain properties of this purified enzyme were investigated, the optimum pH of activity was 7 and the pH of its stability was 4.5, while the temperature stability was 40 °C for 60 min. The enzyme retained 100% of its original activity after incubation at 40 °C for 60 min; the optimum temperature for enzyme activity was 40 °C.

Abstract

The present investigation aimed to formulate a liquid self-microemulsifying drug delivery system (SMEDDS) of tacrolimus to enhance its oral bioavailability by improving its dispersibility and dissolution rate. Four liquid SMEDDS were prepared using maisine CC as oil phase, labrasol ALF as surfactant and transcutol HP as co-surfactant based on the solubility studies of tacrolimus in these components. The phase behavior of the components and the area of microemulsion were evaluated using pseudoternary phase diagrams. The formulations were also assessed for thermodynamic stability, robustness to dilution, self-emulsification time, drug content, globule size and polydispersity index. The prepared SMEDDS formulations exhibi

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

Background: Hyperthyroidism refers to overactive of thyroid gland leading to excessive synthesis of thyroid hormones and accelerated metabolism in the peripheral tissue. Objective: The aim of this study is to evaluate a new member of the IL-1 super family of cytokines interleukin-33(IL-33) levels in serum .in order to evaluate its utility as clinical bio marker of autoimmune disease (i.e. hyperthyroidism) Methods: The present study was conducted on 30 patients from the Iraqi female patients with hyperthyroidism attending Baghdad teaching hospital, in addition to 30 healthy controls. All subjects were (35-65) years old. Parameters measured in the sera of patients and healthy groups, were interleukin -33 (IL-33), Thyroxin (T4), Thyroxin (T3)

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

This paper deals  with constructing mixed probability distribution  from exponential with scale parameter (β) and also Gamma distribution with (2,β), and the mixed proportions are (  .first of all, the probability density function (p.d.f) and also cumulative distribution function (c.d.f) and also the reliability function are obtained. The parameters of mixed distribution, ( ,β)  are estimated by three different methods, which are  maximum likelihood, and  Moments method,as well proposed method (Differential Least Square Method)(DLSM).The comparison is done using simulation procedure, and all the results are explained in tables.