To better characterize the inflammatory response Rapamycin Sirolimus in microglia we additionally examined the activation of the upstream I B kinase experimentally. The time course of IKK activity was measured for the first 30 min following 10 ng ml TNFa treatment in three identical experiments. IKK is rapidly activated, reaching peak levels near 5 min. By 10 min IKK activity sharply drops to below half maximal levels and gradually declines to near basal levels over the next 20 min. This transient profile resembles IKK activation characteristic of the response in most other cell types to high TNFa doses, in which IKK activity peaks between 5 15 min and drops below 25% of its Inhibitors,Modulators,Libraries maximal value by 30 min. However, the rapid decline from maximum activity at 5 min to 33% activity by 10 min is particu larly prominent in microglia.

Intermediate steps in the IKK induced I Ba degradation pathway reconcile the mathematical model Inhibitors,Modulators,Libraries with NF B activation in microglia Next we sought to quantitatively describe microglial NF B activation using a mathematical model. While a num ber of mathematical models for NF B have been pub lished in recent years, our preference was to begin with a simple description that still captures the essential components of the network. For this pur pose we selected a deterministic, ordinary differential AV-951 equation model structure recently published by Ashall et al, which was based primarily on an earlier model by Lipniacki et al. This model includes the core architecture of the canonical signaling pathway and was able to predict many key features of NF B activa tion in different cell types under a variety of conditions.

We first attempted to identify parameters for the exist ing model structure to fit the experimental NF B and T IKK activation profiles of microglia. An optimization based parameter estimation algorithm was run using many randomly selected parameter values from the para meter space as initial guesses. However, no parameter Inhibitors,Modulators,Libraries sets were found that matched microglial IKK and NF B activity. In particular, the model was unable to qualita tively reproduce the rapid induction and attenuation of IKK activity observed in microglia for any of the para meter sets tested, and NF B activation was predicted to occur more rapidly than the 5 min delay observed in Figure 2A. The discrepancies between the model and data prompted us to investigate the time interval imme diately following TNFa stimulus.

Sensitivity analyses were performed on the model to quantify the relative contributions of each of the system parameters to the concentration of free NF B Inhibitors,Modulators,Libraries during the first 10 min given the large mismatches between the model and data in this interval. Only seven of the origi nal 26 system parameters have appreciable effects on NF B activity during this time based on VX-770 their time averaged sensitivity scores.