This study explores the reactions and related species of NOx pollutants in methane flames in order to understand their production and consumption during the combustion process. To do this, several analytical simulations were run to explore the behavior of nitrogen species in the pre-flame, post- flame, and reaction layer regions. The results were then analyzed in order to identify all "steady-state" species in the flame as well as the determine all the unnecessary reactions and species that are not required to meet a defined accuracy. The reductions were then applied and proven to be viable.

Biochemical reactions make up most of the activity in a cell. There is inherent stochasticity in the kinetic behavior of biochemical reactions which in turn governs the fate of various cellular processes. In this work, the precision of a method for dimensionality reduction for stochastic modeling of biochemical reactions is evaluated. Further, a method of stochastic simulation of reaction kinetics is implemented in case of a specific biochemical network involved in maintenance of long-term potentiation (LTP), the basic substrate for learning and memory formation. The dimensionality reduction method diverges significantly from a full stochastic model in prediction the variance of the fluctuations. The application of the stochastic simulation method to LTP modeling was used to find qualitative dependence of stochastic fluctuations on reaction volume and model parameters. / text

Nitric Oxide (NO) has been known for long to regulate vessel tone. However, the close proximity of the site of NO production to “sinks” of NO such as hemoglobin (Hb) in blood suggest that blood will scavenge most of the NO produced. Therefore, it is unclear how NO is able to play its physiological roles. The current study deals with means by which this could be understood. Towards studying the role of nitrosothiols and nitrite in preserving NO availability, a study of the kinetics of glutathione (GSH) nitrosation by NO donors in aerated buffered solutions was undertaken first. Results suggest an increase in the rate of the corresponding nitrosothiol (GSNO) formation with an increase in GSH with a half-maximum constant EC50 that depends on NO concentration, thus indicating a significant contribution of ∙NO2 mediated nitrosation in the production of GSNO. Next, the ability of nitrite to be reduced to NO in the smooth muscle cells was evaluated. The NO formed was inhibited by sGC inhibitors and accelerated by activators and was independent of O2 concentration. Nitrite transport mechanisms and effects of exogenous nitrate on transport and reduction of nitrite were examined. The results showed that sGC can mediate nitrite reduction to NO and nitrite is transported across the smooth muscle cell membrane via anion channels, both of which can be attenuated by nitrate. Finally, a 2 – D axisymmetric diffusion model was constructed to test the accumulation of NO in the smooth muscle layer from reduction of nitrite. It was observed that at the end of the simulation period with physiological concentrations of nitrite in the smooth muscle cells (SMC), a low sustained NO generated from nitrite reduction could maintain significant sGC activity and might affect vessel tone. The major nitrosating mechanism in the circulation at reduced O2 levels was found to be anaerobic and a Cu+ dependent GSNO reduction activity was found to deliver minor amounts of NO from physiological GSNO levels in the tissue.