Fumonisin B1 (FB1) is a mycotoxin produced in some grains (mainly corn) by Fusarium species. Due to a structural similarity between FB1 and sphinganine, sphingolipids metabolism is inhibited. Such inhibition plays a critical role in cell to cell singling and structure of lipoprotein; therefore FB1 has been suggested to have a relationship with human and animal cancer. This research is planned to study the effect of FB1 on male mice at two doses (20 and 30 µg/ ml) on the expression of TGF-β1 and p16 in liver cells. Three groups of Swiss albino male mice; each group was orally administrated with FB1 toxin as the following: normal saline (control group); 20 and 30 µg/ ml. All groups were sacrificed after two weeks of oral management. Liver samples were collected and prepared for immunohistochemistry technique (IHC) using anti-TGF-β1 and anti-p16 antibodies. The results showed that exposure to FB1 caused significant elevation of TGF-β1 in both doses (76.74 ± 2.387% and 80.62 ± 7.277%, respectively) in comparison with the control group (46.79 ± 2.404%). The level of p16 protein was decreased at 20 µg/ml (76.63 ± 2.349%) and then increased at 30 µg/ml (81.25 ± 6.263%) but the expression was lower than that of control (90.00 ± 0.805%). In conclusion, FB1 has a significant effect on TGF-β1 and p16 protein expression at both doses (20 and 30 µg/ml), and therefore, its role in cancer development is suggested.
The aim of the research is to identify the impact of the dimensions of the European Excellence Model in evaluating the performance of the bank of the research sample, as well as to interpret which dimensions are more important to the banks of the research sample. Based on the dimensions of this model, the United Bank for Investment and Finance has chosen a research community, and has met with officials of the United Bank for Investment and Finance at various administrative levels to measure the practices of excellence management in the European model, and the analytical approach has been the case study and the construction of the checklist as a tool to collect information. The research has reached the most important results There is a discr
... Show MoreAs the prices of the fuel and power had fluctuated many times in the last decade and new policies appeared and signed by most of the world countries to eliminate global warming and environmental impact on the earth surface and humanity exciting, an urgent need appeared to develop the renewable energy harnessing technologies on the short-term and long-term and one of these promising technologies are the vertical axis wind turbines, and mostly the combined types. The purpose of the present work is to combine a cavity type Savonius with straight bladed Darrieus to eliminate the poor self-starting ability for Darrieus type and low performance for Savonius type and for this purpose, a three-bladed Darrieus type with symmetric
... Show MoreThis study proposed using color components as artificial intelligence (AI) input to predict milk moisture and fat contents. In this sense, an adaptive neuro‐fuzzy inference system (ANFIS) was applied to milk processed by moderate electrical field‐based non‐thermal (NP) and conventional pasteurization (CP). The differences between predicted and experimental data were not significant (
Conventional identification of three coccoid green algae isolates was attempted to characterize the studied algae morphologically under compound microscope, which demonstrated confusional phenomenal convergence; all were classified microscopically as the green alga Chlorella vulgaris Beijerinck, 1890.
Phylogenetic studies were conducted to settle the argument about the phenotype by studying the genotype. Genotype the promising field in advance classification by using 18S rRNA and compared to GenBank database using to search the related sequences. The determined sequences showed high a similarity to the strains registered in GenBank.
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... Show MoreOptical burst switching (OBS) network is a new generation optical communication technology. In an OBS network, an edge node first sends a control packet, called burst header packet (BHP) which reserves the necessary resources for the upcoming data burst (DB). Once the reservation is complete, the DB starts travelling to its destination through the reserved path. A notable attack on OBS network is BHP flooding attack where an edge node sends BHPs to reserve resources, but never actually sends the associated DB. As a result the reserved resources are wasted and when this happen in sufficiently large scale, a denial of service (DoS) may take place. In this study, we propose a semi-supervised machine learning approach using k-means algorithm
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