The aim of present study was to investigate the effect of Pregabalin on hormonal profile of pituitary and ovarian hormones in female albino rats. Three groups of healthy adult female albino rats having fifteen rats in each group were selected for present study. The rats of groups G2 and G3 were administered with Pregabalin with two doses 150 mg and 300mg/kg b.wt/day respectively by orally route daily for 1month, 2 months, and 3 months. Animals of group G1 (Control) were given saline alone. After the experimental periods, the rats were sacrificed, and the study of hormonal profile was carried out by collecting blood samples from the heart puncture method, centrifuged sera and analyzing concentrations of estrogen, progesterone and gonadotropins for hormonal profile via RIA method. The results were shown significant decrease in the body weight among various groups. Also ovarian weight and ovarian diameter in the experimental groups G2 and G3 were decreased significantly (p≤ 0.05). Significant decrease in the levels of FSH, LH and PRL hormones were observed in the low dose and high dose. In contrast to the levels of progesterone, estradiol, and testosterone hormones were showed a significant increase in all experimental groups compared with the control group. Final remarks of our investigation are that, the oral administration 150 mg and 300mg/kg b.wt/day of Pregabalin can produce adverse effects on hormonal profile
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In this research, the kinetic studies of four isoenzymes of Asprtate aminotransferase, which partially purified from the urine of chronic renal failure patients were carried out .The four isoenzymes were obeyed Michaelis-Menton's equation and the optimum concentration of their substrate (Aspartic acid) was (166.5x10-3) mole/liter,and their Km values were determined. Four isoenzymesI,II,III,IV have shown an optimum pH at 7.4.The four isoenzymes obeyed Arrhenius equation up to 37º C and their Ea and Q10 constants were determined .
The use of real-time machine learning to optimize passport control procedures at airports can greatly improve both the efficiency and security of the processes. To automate and optimize these procedures, AI algorithms such as character recognition, facial recognition, predictive algorithms and automatic data processing can be implemented. The proposed method is to use the R-CNN object detection model to detect passport objects in real-time images collected by passport control cameras. This paper describes the step-by-step process of the proposed approach, which includes pre-processing, training and testing the R-CNN model, integrating it into the passport control system, and evaluating its accuracy and speed for efficient passenger flow
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KE Sharquie, HR Al-Hamamy, AA Noaimi, KA Ali, Journal of Cosmetics, Dermatological Sciences and Applications, 2015 - Cited by 3
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Release of industrial effluents comprising dyes in water bodies is one of the foremost causes of water pollution. Therefore, the proper and proficient treatment of these dyes contaminated left-over material before their release is crucial. Herein, an eco-friendly biological macromolecule Gum-Acacia (GA) integrated Fe3O4 nanoparticles composite hydrogel was manufactured via co-precipitation technique for effective adsorption of Congo red (CR) dye existing in water bodies. The as-prepared magnetic GA/Fe3O4 composite hydrogel was characterized by FTIR, XRD, EDX, VSM, SEM, and BET techniques. These studies discovered the fruitful fabrication of biodegradable magnetic GA/Fe3O4 composite hydrogel possessing porous structure with large surface are
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