Diabetes mellitus, or simply diabetes, is a group of metabolic diseases in which a person has high blood sugar, either because the pancreas does not produce enough insulin, or because cells do not respond to the insulin that is produced. This high blood sugar produces the classical symptoms of polyuria (frequent urination), polydipsia (increased thirst), and polyphagia (increased hunger). The aim of the study is to measure several biochemical parameters in T2DM patients and the effect of these parameters in development the disease. Laboratory investigations including Ceruloplasmin , fasting blood glucose (FBG) , malondialdehyde (MDA), serum protein, uric acid, and protein electrophoresis have been measured in patients with type

Background: Isoxazoles are an important class of five-membered unsaturated heterocyclic compounds. They show several applications in diverse areas such as pharmaceuticals, agrochemistry and industry. Isoxazoles are also found in natural sources showing insecticidal, plant growth regulation and pigment functions. Current study was conducted for synthesis of twenty five new Isoxazole derivatives and to evaluate the in vitro antibacterial activities of these derivatives. Methods: Benzaldoxime and their substituted [I] ae were prepared via addition-elimination reactions between aromatic aldehyde and hydroxylamine hydrochloride. In a second step, para-or meta-substituted benzaldoximes [I] ae were reacted with N-chlorosucceinimide in DMF to yield

Laryngoscopy and tracheal intubation are considered the most invasive stimuli in anesthesia. They provoked cardiovascular responses that include hypertension, tachycardia and dysrhythmias. Various pharmacological approaches have been used to blunt or attenuate such pressor responses. The present study was designed to evaluate the effect of medazolom, lignocaine and propranolol as a valuable adjuvant to fentanyl in attenuating hemodynamic responses to endotracheal intubation in normotensive patients. Thirty two patient with physical status I or II according to the score of American Society of Anesthesiologist (ASA), scheduled for elective surgery under standard general anesthesia, were randomly allocated into four groups (8 patients in ea

This paper includes an experimental study of hydrogen mass flow rate and inlet hydrogen pressure effect on the fuel cell performance. Depending on the experimental results, a model of fuel cell based on artificial neural networks is proposed. A back propagation learning rule with the log-sigmoid activation function is adopted to construct neural networks model. Experimental data resulting from 36 fuel cell tests are used as a learning data. The hydrogen mass flow rate, applied load and inlet hydrogen pressure are inputs to fuel cell model, while the current and voltage are outputs. Proposed model could successfully predict the fuel cell performance in good agreement with actual data. This work is extended to developed fuel cell feedback