Coupling reaction of 4-amino antipyrene with 2,6-dimethyl phenol gave bidentate azo ligand. The prepared ligand was identified by Microelemental Analysis, 1HNMR, FT-IR and UV-Vis spectroscopic techniques. Treatment of the prepared ligand with the following metal ions (CoII, NiII, CuII, ZnII, CdII, and HgII) in aqueous ethanol with a 1:2 M:L ratio and at optimum pH, yielded a series of neutral complexes of the general formula [M(L)2Cl2]. The prepared complexes were characterized using flame atomic absorption, (C.H.N) Analysis, FT-IR and UVVis spectroscopic methods as well as magnetic susceptibility and conductivity measurements. Chloride ion content was also evaluated by (Mohr method). The nature of the complexes formed were studied following the mole ratio and continuous variation methods, Beer's law obeyed over a concentration range (1×10-4 - 3× 10-4 M). High molar absorbtivity of the complex solutions were observed. The stability constant of the complexes have also been studied.
Pregnancy- including hypertension(PIH), also known as preeclampsia, is one of the major causes of maternal and fetal death. This study was carried out on 30 pregnant women with preeclampsia and 30 healthy pregnant women as control ranging in age mean ±SD (28.84±3.55) years , BMI (76.80±9.78) Kg/m2 and gestation age(30.82±0.75)week. The aim of this research was studied the plasma Metanephrine level and other biochemical parameters such as Hemoglobin(Hb), serum Protein, S. Albumin, Globulin, Albumin/Globulin ratio (Alb/Glu. ratio), S.Glutamate Pyruvate aminotransferase (GPT), S.Glutamate Oxaloacetate aminotransferase(GOT). The obtained results have been compared with 30 healthy pregnant women as control group. The result showed
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The expression of MUC5AC has been associated with the loss of the differentiation, TNM system, and nodal metastasis, in many cancers including gastric carcinoma (GC).Objective: To evaluate whether the MUC5AC could be used as a predictor in patients with GC and to assess the correlation between the expression of MUC5AC& the clinicpathological parameters as age, sex, histopathological subtypes, grade and stage of the tumor. This is a retrospective study conducted on 60 randomly selected patients (30 normal vs 30 GC), at the Pathology Department of the Gastroenterology and Hepatology Teaching Hospital&some private laboratories. They were collected and diagnosed during the period 2014-2018. Histological sections were stained with H&E and IHC st
... Show MoreHuman health was and still the most important problem and objective of all most researches. Finding out what causes in the decadence of healthiness of Iraqi population is our tendency in the present work, Uranium causing cancer that is affected by a correlation between age and gender of bladder cancer patients is studied in the present work. Mean of Uranium concentration (Uc) decreased with increasing age for all age group without dependency on gender. While, there is a wide dispersion in Mean Uc excretion between males and females, due to the effect of correlated gender with age, where female Mean Uc is maximum at age 50-69 year (2.355 µg/L), and it's higher than male Mean Uc (2.022 µg/L) in this age stage because of menopause, a
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The objective of this study is to determine levels of some pro-inflammatory cytokines (IL-12 and SIL-2R) in pregnant women with polycystic ovary syndrome (PCOS) and also to determine incidence of spontaneous abortion during first trimester in pregnant women with PCOS compared with non-PCOS pregnant women. This Study was performed on (93) women, consisted of: 1- (63) pregnant women during the first trimester, which included:A- (33)PCOS pregnant women and subdivided into the following groups: (20) successful pregnant PCOS, (7) blighted Ovum PCOS and (6) missed abortion PCOS. B- (30) non-PCOS pregnant women, which included: (27) successful pregnant control and (3) non-PCOS pregnant women were withdrawn from this study because of their abortion
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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
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