The influence of hypomagnesemia on erythrocyte antioxidant enzyme defence system in mice

The effect of magnesium deficiency on antioxidant defence system was studied in RBC of mice suffering from hypomagnesemia. The animals were kept for 8, 15 and 22 days on magnesium-deficient diet with consequent reduction of magnesium level in plasma by 38% at the first 8 days and by 64% after 22 days of experiment. The activities of the most important antioxidant enzymes, catalase, glutathione peroxidase, superoxide dismutase, glutathione reductase, glutahione S-transferase were assayed in hemolysates. The level of reduced glutathione in erythrocytes was measured as well. Apart from catalase, the activities of antioxidant enzymes were decreasing. The activity of superoxide dismutase decreased gradually during the experiment and on the 15th and 22nd day of experiment was significantly (P<0,05) lowered by 30 and 32% respectively. The catalase activity was increased on each point of the experiment with the peak value up to 149% on 15th day, and by 32% on 22nd day. Glutathione peroxidase activity was insignificantly reduced. The reduction of Glutatione reductase and Glutathione S-transferase activities by 24 and 21%, respectively, were observed after 8 days of the experiment with a further downward tendency. The reduced glutathione was significantly depleted after 8 days by 33% and was kept on that level in the course of the study. These findings support previous reports on the hypomagnesemia – induced alteration in endogenous enzyme antioxidant defences and glutathione redox cycle of mice.     

Solving the N-Queens problem with a binary Hopfield-type network

The application of a discrete Hopfield-type neural network to solving the NP-Hard optimization problem — the N-Queens Problem (NQP) — is presented. The applied network is binary, and at every moment each neuron potential is equal to either 0 or 1. The network can be implemented in the asynchronous mode as well as in the synchronous one with n parallel running processors. In both cases the convergence rate is up to 100%, and the experimental estimate of the average computational complexity is polynomial. Based on the computer simulation results and the theoretical analysis, the proper network parameters are established. The behaviour of the network is explained.