This work was influenced the separation and preconcentration steps were carried out to determination of metformin (MET) in pharmaceutical preparations and human serum samples. Complex formation method and cloud-point extraction (CPE) coupling with UV-Visible spectrophotometry were used to investigated of study target.The results has showed the best optical characteristic for calibration curve and statistical data which were obtained under optimum conditions. The first method is based on the reaction of MET with nickel (II) in alkaline medium an absorption maximum ?)max) at 434nm. ''Beer's low'' is obeyed in the concentration range (10-100µg.ml-1) with molar absorptivity of 3.9x103 L.mol-1.cm-1.The limit of detection and quantitation values were 2.37 and7.11 µg.ml-1 respectively. The second method based on extraction of traces amounts of MET using the cloud-point extraction (CPE). This method implicated for using of a nonionic surfactant (Triton x-114) as an extraction medium which was entrap the hydrophobic complex formed between MET and nickel(ii) in basic medium as reaction system for designing the CPE procedure. The optimum conditions were similar the first method expect the amount of surfactant which was 0.5 ml. The concentrations range of calibration curve from 3.5to100 µg.ml-1 and molar absorptivity of 1.2x104 L.mol-1.cm-1. In this method was access to less of concentrations in Limit of detection and quantitation which were 0.74and 2.22 µg.ml-1 respectively. The precise (RSD %) and accuracy (recovery %) of both methods were ranged between 0.24-0.47, 97.86-98.68 respectively. The data of two methods were appeared high acceptable with standered of British Pharmacopoeia through using statistic methods (f-test and t-test), that they may be used in analysis of MET.
After baking the flour, azodicarbonamide, an approved food additive, can be converted into carcinogenic semicarbazide hydrochloride (SEM) and biurea in flour products. Thus, determine SEM in commercial bread products is become mandatory and need to be performed. Therefore, two accurate, precision, simple and economics colorimetric methods have been developed for the visual detection and quantitative determination of SEM in commercial flour products. The 1st method is based on the formation of a blue-coloured product with λmax at 690 nm as a result of a reaction between the SEM and potassium ferrocyanide in an acidic medium (pH 6.0). In the 2nd method, a brownish-green colored product is formed due to the reaction between the SEM and phosph
... Show MoreObjective: To identify of the effect of the different concentrations of the special liquid (for mixing the investment, Gilvest)
and mixed with water/powder ratio on setting time of phosphate–bonded investment.
Method and materials: The present study is (60) specimens made from phosphate bonded investment divided into (4)
groups (control and experimental groups), (15) specimens for each group. The Gillmore needle device is used to setting
time of phosphate bonded investment mixed with different concentration of Gilvest and water.
Results: Showed that there is a high significant difference (P<0.01) between each groups in the ANOVA test and a
significant difference (P<0.05) between the group (A) and control group i
The current study included the separation of three alkaloid compounds from Anastatica Hierochuntica and studied the effect of the these compounds on cancerous cells , specifically liver cancer it was found that compound number one is the most influential or inhibiting at 50 percent followed by compound number three when using concentration of 400 μg/mL.
The experiment was conducted in the fields belonging to the Department of Horticulture, College of Agricultural Engineering Sciences, University of Baghdad, at Al-Jadriya Complex / Station A, for the autumn season of 2022-2023. The aim was to study the effect of water fish irrigation and water lens plant extract foliar application on the growth and productivity of beetroot. The experiment included two factors: the first factor was water fish irrigation with five concentrations (A) Control treatment (irrigation with river water and recommended fertilization), (B) Water fish irrigation at 25% concentration, (C) water Fish irrigation at 50% concentration, (D) Water Fish irrigation at 75%
Disease diagnosis with computer-aided methods has been extensively studied and applied in diagnosing and monitoring of several chronic diseases. Early detection and risk assessment of breast diseases based on clinical data is helpful for doctors to make early diagnosis and monitor the disease progression. The purpose of this study is to exploit the Convolutional Neural Network (CNN) in discriminating breast MRI scans into pathological and healthy. In this study, a fully automated and efficient deep features extraction algorithm that exploits the spatial information obtained from both T2W-TSE and STIR MRI sequences to discriminate between pathological and healthy breast MRI scans. The breast MRI scans are preprocessed prior to the feature
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