Minia University

About: Minia University is a education organization based out in Minya, Egypt. It is known for research contribution in the topics: Population & Medicine. The organization has 4967 authors who have published 8986 publications receiving 108384 citations.

Distribution of constitutive (COX-1) and inducible (COX-2) cyclooxygenase in postviral human liver cirrhosis: a possible role for COX-2 in the pathogenesis of liver cirrhosis

Abstract: Aims: Prostaglandins produced by the action of cyclooxygenases (COX) are important mediators of systemic vasodilatation and inflammation in liver cirrhosis. The aim of this study was to investigate the distribution of COX-1 and COX–2 in postviral cirrhosis. Methods: The immunohistochemical expression of the constitutive (COX-1) and the inducible (COX-2) isoenzymes was investigated in 15 patients with cirrhosis after hepatitis B and C infection; three normal control livers were also analysed. Results: COX-2 was absent from normal liver but was highly expressed in cirrhosis, mainly in the inflammatory, sinusoidal, vascular endothelial, and biliary epithelial cells. Low amounts of COX-1 were expressed in both normal and cirrhotic livers, exclusively in sinusoidal and vascular endothelial cells, with no differences seen between normal and cirrhotic livers. Conclusions: COX-2 is overexpressed in liver cirrhosis, and possibly contributes to prostaglandin overproduction, which may be a major component of the inflammation and hyperdynamic circulation associated with cirrhosis. Because COX-2 is thought to contribute to tumour development, high COX-2 production could be a contributor to hepatocellular carcinoma development in cirrhosis. The finding of COX-2 and not COX-1 upregulation in cirrhosis could provide a possible new role for selective COX-2 inhibitors in reducing inflammation and minimising the occurrence of hepatocellular carcinoma in patients with cirrhosis.

Hybrid slime mould algorithm with adaptive guided differential evolution algorithm for combinatorial and global optimization problems

Abstract: The Slime Mould Algorithm (SMA) is a recent metaheuristic inspired by the oscillation of slime mould. Similar to other original metaheuristic algorithms (MAs), SMA may suffer from drawbacks, such as being trapped in minimum local regions and improper balance between exploitation and exploration phases. To overcome these weaknesses, this paper proposes a hybrid algorithm: SMA combined to Adaptive Guided Differential Evolution Algorithm (AGDE) (SMA-AGDE). The AGDE mutation method is employed to enhance the swarm agents’ local search, increase the population’s diversity, and help avoid premature convergence. The SMA-AGDE’s performance is evaluated on the CEC’17 test suite, three engineering design problems – tension/compression spring, pressure vessel, and rolling element bearing – and two combinatorial optimization problems – bin packing and quadratic assignment. The SMA-AGDE is compared with three categories of optimization methods: (1) The well-studied MAs, i.e., Biogeography-Based Optimizer (BBO), Gravitational Search Algorithm (GSA), and Teaching Learning-Based Optimization (TLBO), (2) Recently developed MAs, i.e., Harris Hawks Optimization (HHO), Manta Ray Foraging optimization (MRFO), and the original SMA, and (3) High-performance MAs, i.e., Evolution Strategy with Covariance Matrix Adaptation (CMA-ES), and AGDE. The overall simulation results reveal that the SMA-AGDE ranked first among the compared algorithms, and so, over different function landscapes. Thus, the proposed SMA-AGDE is a promising optimization tool for global and combinatorial optimization problems and engineering design problems.