Effect of Dietary Fats on Oxidative-Antioxidative Status of Blood in Rats

This study was performed to examine the effect of different fat sources, lard, sunflower oil (SO), and fish oil (FO) in high-fat and low-fat diet on reactive oxygen species generation by blood phagocytes, glutathione redox status in erythrocytes, and total plasma antioxidant ability in rats. Whole blood chemiluminescence (CL) did not differ between three low-fat fed groups. However, baseline and phorbol myristate acetate (PMA)-stimulated CL in blood of high-lard fed rats were lower than in low-lard and high-SO fed animals. Phagocyte-stimulated oxidative burst was higher in rats fed high-SO diet than in those fed low-SO and high-FO diets. The highest level of oxidize glutathione (GSSH), the lowest reduce glutathione (GSH)/GSSG ratio in erythrocytes, and the highest plasma activity to reduce ferric ions were observed in rats fed both diets contaning linoleic acid-rich sunflower oil compared to animals fed the corresponding energy from other fats. 1,1-diphenyl-2-picrylhydrazyl radical scavenging activity of plasma was lower in high-lard and high-FO fed rats compared to the corresponding low-fat diets, and the lowest in low-FO fed rats among low-fat fed animals. We presume from our results that linoleic acid may have dual effect, prooxidative in blood cells but maintaining total antioxidant plasma ability

Approximate mean value analysis based on Markov chain aggregation by composition

AbstractMarkovian performance models are impractical for large systems because their state space grows very rapidly with the system size. This paper derives an approximate Mean Value Analysis (AMVA) solution for Markov models that represent a composition of subsystems. The goal is robust scalable analytical approximation. The approach taken here is to create approximate aggregated Markov chain submodels, each representing a view of the Markov chain for the entire system from the perspective of a selected set D of tagged components, and to derive mean value equations from them. The analytic solutions of submodels are then combined using system-level relationships, which must be identified for each system; this is not automatic but is usually straightforward. The first point of novelty is the method used to create the aggregate submodels for different sets D, building up each submodel by composition of the components in D rather than by aggregating the entire state space. Another point of novelty is the use of partitioned Markov models to obtain analytic solutions

Performance modelling of queues with rendezvous service

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