The study included selection six species of the fungi related to Pleurotus genus were evaluated for their ability to production of Pleurotin, one of them, Pleurotus ostreatus (P.11) was isolated and identified in the present study. Pleurotin was extracted with screening by Thin Layer Chromatography (TLC) and quantification High Performance Liquid Chromatography (HPLC). Cytotoxicity of Pleurotin extracted from P. ostreatus (P.11) grown in different sugar sources (galactose, mannitol, sucrose, dextrose and lactose) liquid media was test against three selected cancer cell lines, CaSki, MCF-7 and A549 addition to Human Non Cancer Fibroblast Cell Line (MRC-5). Pleurotin of P. ostreatus (P.11) grown in galactose induced the significant highest growth inhibition against all three cancer cell lines MCF-7 CaSki, and A549 at 72 h treatment period with IC50 29.84 ± 2.37, 30.25 ± 2.40 and 37.60 ± 2.65 μg/ml respectively when the P≤0.01, while it showed no adverse effect on the non-cancer human fibroblast cell line MRC-5 with IC50 >200 μg/ml. Cytotoxicity of Pleurotin was compared with cytotoxicity of the positive controls (chemotherapeutic drugs) including Doxorubicin against CaSki and A549 cell lines and Cisplatin against MCF-7 and MRC-5 cell lines, although IC50 of pleurotin was higher (30.25 ± 2.40 and 37.60 ± 2.65 μg/ml) than Doxorubicin (0.18 ± 0.00 and 1.10 ± 0.02 μg/ml) of CaSki and A549 cell lines, respectively, and also IC50 of Pleurotin was higher (29.84 ± 1.73 and >200 μg/ml) than Cisplatin (8.20 ± 0.25 and 8.88 ± 0.13 μg/ml) of MCF-7 and MRC-5 cell lines, respectively, pleurotin was natural product from an edible fungus while Doxorubicin and Cisplatin were chemical drugs.
This study aimed to identify the employment of the social networking platform «Twitter» in the 2016 presidential campaign led by the Republican candidate, Donald Trump; and analyse his tweets through his personal account on «Twitter» for the period from: 10/ 8/2016 to: 11/ 8/2016 which represents the last month of the election campaign.
The study belongs to the type of descriptive studies using the analytical method through an analysis index that includes sub-categories and other secondary categories. The research has adopted the ordinary unit of information material (tweet) as an analysis unit for this purpose.
... Show MoreThe present study is concerned with studying the effect of aquatic plant Hydrella vorticellata with the concentration of 10 and 20 gm/2 K gm soil on percentage and growth rate of germinating seeds of Hordeum vulgare and Vicia faba. More overs, the quantitative amount of NPK in both tested plants and Hydrella vorticellata, are estimated as an organic fertilizer. It has also been find the total number of root cells, the number of dividing cells, and stages of mitosis. The study reveales, that there are no significant differences between the concentration of hydrella used in germination percentage, growth rate, wet and dry weight. While there are differences in the plants containing NPK. The number of cells dividing stages and number of divid
... Show MoreA new Species of the Cerambycinae belonging to the genus Hesperophanes was found new to the fauna of Iraq and Science. H. testaceus was studied in details and the male genitalia were illustrated. Type's paratypes and the locality of this newly described Species were mentioned.
Abstract A descriptive study using evaluation technique was carried at the health organizations concerning STIs/HIV/AIDS, mainly the AIDS Researches and Studies Center in Baghdad and many of the AIDS sections in the Health Directorates in the Governorates throughout the period of May 15th , 2003 through September 30th, 2003( to describe the surveillance system for the period 1993 through 2002). The study aimed to describe the STIs/HIV/AIDS surveillance system in Iraq. System evaluation questionnaire was adopted from WHO and developed for the purpose of this study. Content validity of questionnaire was establis
To determine the important pathogenic role of celiac disease in triggering several autoimmune disease, thirty patients with Multiple Sclerosis of ages (22-55) years have been investigated and compared with 25 healthy individuals. All the studied groups were carried out to measure anti-tissue transglutaminase antibodies IgA IgG by ELISA test, anti-reticulin antibodies IgA and IgG, and anti-endomysial antibodies IgA and IgG by IFAT. There was a significant elevation in the concentration of anti-tissue transglutaminase antibodies IgA and IgG compared to control groups (P≤0.05), there was 4(13.33%) positive results for anti-reticulin antibodies IgA and IgG , 3(10%) positive results for anti-endomysial antibodies IgA and IgG . There were 4 pos
... Show MoreTo determine the important pathogenic role of celiac disease in triggering several autoimmune disease, thirty patients with Multiple Sclerosis of ages (22-55) years have been investigated and compared with 25 healthy individuals. All the studied groups were carried out to measure anti-tissue transglutaminase antibodies IgA IgG by ELISA test, anti-reticulin antibodies IgA and IgG, and anti-endomysial antibodies IgA and IgG by IFAT. There was a significant elevation in the concentration of anti-tissue transglutaminase antibodies IgA and IgG compared to control groups (P≤0.05), there was 4(13.33%) positive results for anti-reticulin antibodies IgA and IgG , 3(10%) positive results for anti-endomysial antibodies IgA and IgG . There were 4 pos
... Show Moreالغرض من هذا العمل هو دراسة الفضاء الإسقاطي ثلاثي الأبعاد PG (3، P) حيث p = 4 باستخدام المعادلات الجبرية وجدنا النقاط والخطوط والمستويات وفي هذا الفضاء نبني (k، ℓ) -span وهي مجموعة من خطوط k لا يتقاطع اثنان منها. نثبت أن الحد الأقصى للكمال (k، ℓ) -span في PG (3،4) هو (17، ℓ) -span ، وهو ما يساوي جميع نقاط المساحة التي تسمى السبريد.
A three-stage learning algorithm for deep multilayer perceptron (DMLP) with effective weight initialisation based on sparse auto-encoder is proposed in this paper, which aims to overcome difficulties in training deep neural networks with limited training data in high-dimensional feature space. At the first stage, unsupervised learning is adopted using sparse auto-encoder to obtain the initial weights of the feature extraction layers of the DMLP. At the second stage, error back-propagation is used to train the DMLP by fixing the weights obtained at the first stage for its feature extraction layers. At the third stage, all the weights of the DMLP obtained at the second stage are refined by error back-propagation. Network structures an
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