Lipid oxidation kinetics of ozone-processed shrimp during iced storage using peroxide value measurements

In this research, in situ generated ozone exposure/wash cycles of 1, 3, and 5 min applied to shrimp samples either before (BIS) or during iced storage (DIS) has been used to study the lipid oxidation kinetics using the peroxide values (PV). The induction period (IP) as well as PV at end of the IP (PVIP) have been obtained. The rate constants (k) as well as half-lives (t1/2) of hydroperoxides formation for different oxidation stages were calculated. The results showed that both IP and PVIP were lower with BIS (IP between 4.35±0.09 and 5.08±0.23 days; PVIP between 2.92±0.06 and 3.40±0.18 mEq kg−1) compared with DIS (IP between 5.92±0.12 and 6.14±0.09 days; PVIP between 4.49±0.17 and 4.56±0.10 mEq kg−1). The k value for DIS seemed to be the greater compared to BIS. In addition, whilst decreases and increases in t1/2 were found at propagation, respectively, for BIS and DIS, decreases and increases were only found at the induction of oxidation stage(s) for BIS. Further, the PV of ozone-processed samples would fit first order lipid oxidation kinetics independent of duration of ozone exposures. For the first time, PV measurements and fundamental kinetic principles have been used to describe how increasing ozone exposures positively affects the different oxidation stages responsible for the formation of hydroperoxides in ozone-processed shrimp.

Kinetic modelling of in vitro data of PI3K, mTOR1, PTEN enzymes and on-target inhibitors Rapamycin, BEZ235, and LY294002

The phosphatidylinositide 3-kinases (PI3K) and mammalian target of rapamycin-1 (mTOR1) are two key targets for anti-cancer therapy. Predicting the response of the PI3K/AKT/mTOR1 signalling pathway to targeted therapy is made difficult because of network complexities. Systems biology models can help explore those complexities but the value of such models is dependent on accurate parameterisation. Motivated by a need to increase accuracy in kinetic parameter estimation, and therefore the predictive power of the model, we present a framework to integrate kinetic data from enzyme assays into a unified enzyme kinetic model. We present exemplar kinetic models of PI3K and mTOR1, calibrated on in vitro enzyme data and founded on Michaelis-Menten (MM) approximation. We describe the effects of an allosteric mTOR1 inhibitor (Rapamycin) and ATP-competitive inhibitors (BEZ2235 and LY294002) that show dual inhibition of mTOR1 and PI3K. We also model the kinetics of phosphatase and tensin homolog (PTEN), which modulates sensitivity of the PI3K/AKT/mTOR1 pathway to these drugs. Model validation with independent data sets allows investigation of enzyme function and drug dose dependencies in a wide range of experimental conditions. Modelling of the mTOR1 kinetics showed that Rapamycin has an IC50 independent of ATP concentration and that it is a selective inhibitor of mTOR1 substrates S6K1 and 4EBP1: it retains 40% of mTOR1 activity relative to 4EBP1 phosphorylation and inhibits completely S6K1 activity. For the dual ATP-competitive inhibitors of mTOR1 and PI3K, LY294002 and BEZ235, we derived the dependence of the IC50 on ATP concentration that allows prediction of the IC50 at different ATP concentrations in enzyme and cellular assays. Comparison of the drug effectiveness in enzyme and cellular assays showed that some features of these drugs arise from signalling modulation beyond the on-target action and MM approximation and require a systems-level consideration of the whole PI3K/PTEN/AKT/mTOR1 network in order to understand mechanisms of drug sensitivity and resistance in different cancer cell lines. We suggest that using these models in systems biology investigation of the PI3K/AKT/mTOR1 signalling in cancer cells can bridge the gap between direct drug target action and the therapeutic response to these drugs and their combinations.