ABSTRACT
Biochemical markers against hydrogen peroxide-induced oxidative stress were developed in marine cyanobacteria under standard laboratory conditions. To find out the ability to cope with different concentrations of hydrogen peroxide, two species of marine cyanobacteria including unicellular and filamentous forms were exposed for shorter duration. Synechococcus aeruginosus and Phormidium valderianum tolerated hydrogen peroxide by showing the highest growth of Superoxide dismutase in Synechococcus aeruginosus and Phormidium valderianum, catalase in Synechococcus aeruginosus, peroxidase in Synechococcus aeruginosus and Phormidium valderianum, Glutathione S-transferase in Synechococcus aeruginosus and Phormidium valderianum which were identified as biochemical markers of oxidative stress against H2O2 in marine cyanobacteria. Synechococcus aeruginosus showed new isoforms for Superoxide dismutase, catalase, peroxidase, Glutathione peroxidase, and Glutathione S-transferase and Phormidium valderianum for Superoxide dismutase, peroxidase, and Glutathione S-transferase. Synechococcus aeruginosus is suggested as the indicator species for biochemical markers against hydrogen peroxide in marine cyanobacteria. Peroxidase is suggested as biochemical enzyme marker. The present investigated on these new isoenzymes were identified as biochemical markers for oxidative stress.
Subject(s)
Cyanobacteria , Cyanothece , Hydrogen Peroxide , Catalase/metabolism , Hydrogen Peroxide/pharmacology , Phormidium/metabolism , Cyanobacteria/metabolism , Peroxidases/metabolism , Antioxidants/metabolism , Glutathione Peroxidase , Oxidative Stress , Superoxide Dismutase/metabolism , Glutathione Transferase , BiomarkersABSTRACT
This article identifies a new upper bound norm for the intervalized interconnection matrices pertaining to delayed dynamical neural networks under the parameter uncertainties. By formulating the appropriate Lyapunov functional and slope-bounded activation functions, the derived new upper bound norms provide new sufficient conditions corresponding to the equilibrium point of the globally asymptotic robust stability with respect to the delayed neural networks. The new upper bound norm also yields the optimized minimum results as compared with some existing methods. Numerical examples are given to demonstrate the effectiveness of the proposed results obtained through the new upper bound norm method.
