L-arabinose isomerase from Escherichia coli O157:H7 Was immobilized with activated Bentonite from local markets of Baghdad, Iraq by 10% 3-APTES and treated with 10% aqueous glutaraldehyde, the results refer that the yield of immobilization was 89%, and pH profile of free and immobilized L-arabinose isomerase was 7 and 7.5 and it is stable at 6-8 for 60 min respectively, while, the optimum temperature was 30 and 35°C and it was stable at 35 and 40°C for 60 min but it loses more than 60 and 30% from its original activity at 50°C for free and immobilized L-arabinose isomerase respectively. Immobilized enzyme retained its full activity for 32 day, but it retained 73.58% of its original activity after storage for 60 d

Introduction: Breast cancer is a significant global health concern, affecting millions of women worldwide. While advancements in diagnosis and treatment have improved survival rates, the impact of this disease extends beyond physical health. It also significantly influences a woman's lifestyle and overall well-being. Objectives: The current study intends to analyze the lifestyle of breast cancer patients who are receiving therapy or are being followed up at the Oncology Teaching Hospital in Medical City, Baghdad, Iraq. Method: The present study uses a descriptive design with an application of an evaluation approach. A convenience sample of 100 women with breast cancer was selected from the Teaching Oncology Hospital at the Medical C

   Industrial Investment according to Clean Productive methods is an important element in the process of rational use of Economic Resources, and the Iraqi industrial sector relied on traditional production methods; the productive activities in this sector did not take into consideration the environmental dimension, which leads to achieving the optimal use of economic resources, so it was necessary to have new investment trends heading with Clean Production. Therefore, the research is based on the hypothesis that "Clean Production contributes to improving the environment and rational use of Natural Resources." Based on the descriptive - inductive analysis methodology that study of Iraqi industries with Clean Production,

This research aims to estimate production functions through which production relations, possibilities for production elements substitution, measurement of its substitution elasticity, and efficiency and distribution coefficients can be analyzed. This would be done through estimation of constant elasticity of substitution production function for agricultural companies in Iraq depending on data from Iraqi Stock Exchange reports of 2005-2016. The researcher had used panel data model and estimated its three models: the Pooled Regression Model (PRM), the Fixed Effect Model (FEM) and the Random Effect Model (REM). A comparison was made for theses three models using F, LM, Husman tests. Tests show that Fixed Effect Model (FEM) is the best

In the present study, nanoporous material type MCM-41 was prepared by the sol-gel technique and was used as a carrier for prednisolone (PRD) drug delivery. The structural properties of mesoporous were fully characterized by X-ray diffraction (XRD), N₂ adsorption /desorption and Fourier-transform infrared (FTIR). The mass transfer in term of adsorption process (loading) and desorption process (releasing) properties were investigated. The maximum drug loading efficiency was equal to 38% and 47.5% at different concentrations. The PRD released was prudently studied in water media of pH 6.8 simulated body fluid (SBF) in according to "United State Pharmacopeia (USP38)". The results proved that the release of prednisolone from MCM-41

Problem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a

: Clobetasol propionate (CP) is a potent corticosteroid used for skin conditions but often causes side effects due its systemic absorption. To improve its solubility and reduce it side effects (like skin irritation, skin atrophy, hypopigmentation and steroidal acne), Microsponge (Msg) has been employed as a unique three-dimensional particle that can encapsulate hydrophilic and lipophilic drugs. This study aims to develop and evaluate CP Msg-loaded hydrogels. Two Clobetasol-loaded ethylcellulose-based Msg formulas were prepared using the quasi-emulsion solvent diffusion method, then they were incorporated into Carbopol hydrogel. Two ratios of Carbopol 940 (1% and 1.5% w/w) were used. The prepared hydrogel were assessed for appearance, pH, dr

Fusidic acid (FA) is a well-known pharmaceutical antibiotic used to treat dermal infections. This experiment aimed for developing a standardized HPLC protocol to determine the accurate concentration of fusidic acid in both non-ionic and cationic nano-emulsion based gels. For this purpose, a simple, precise, accurate approach was developed. A column with reversed-phase C18 (250 mm x 4.6 mm ID x 5 m) was utilized for the separation process. The main constituents of the HPLC mobile phase were composed of water: acetonitrile (1: 4); adjusted at pH 3.3. The flow rate was 1.0 mL/minute. The optimized wavelength was selected at 235 nm. This approach achieved strong linearity for alcoholic solutions of FA when loaded at a serial concentrati