Mimicking of glutathione peroxidase deficiency by exposition of JAR cells to increased level of synthetic hydroperoxide

A short chain synthetic analogue of lipid hydroperoxides was used to overload glutathione peroxidase (GPx) in human choriocarcinoma cell line JAR cells. Cells exposed to 100 µM tBuOOH displayed a 40% reduction in ATP level and significantly increased in membrane permeability, visualised by the lactate dehydrogenase (LDH) release into the extracellular medium. The intracellular level of oxygen free radicals measured as an oxidation of the dichlorodihydro-fluorescein diacetate (H2DCF-DA) significantly increased after 2 hours of cell exposition to 100 µM tBuOOH. Concomitantly MDA, 4-HNE level increased to 2 nmol/mg of cell protein after 2 hours. Mitochondria stained with MitoTracker Red CMXRos displayed a filamentous appearance in control cells but changed into granular less energised organelles after exposition to tBuOOH. Collectively, the above results indicate the importance of the contribution of oxidative stress in the development of pre-eclampsia

On Perturbation Measure of Sets : Properties

In this paper we describe a new measure of remoteness between sets described by nominal values. The introduced measures of perturbation of one set by another are considered instead of commonly used distance between two sets. The operations of the set theory are operated and the considered measures describe changes of the perturbed second set by adding the first one or vice versa. The values of the measure of sets’ perturbation are range between 0 and 1, and in general, are not symmetric – it means that the perturbation of one set by another is not the same as the perturbation of the second set by the first one

A hybrid approach to dimension reduction in classification

In this paper we introduce a hybrid approach to data series classification. The approach is based on the concept of aggregated upper and lower envelopes, and the principal components here called 'essential attributes', generated by multilayer neural networks. The essential attributes are represented by outputs of hidden layer neurons. Next, the real valued essential attributes are nominalized and symbolic data series representation is obtained. The symbolic representation is used to generate decision rules in the IF. . . THEN. . . form for data series classification. The approach reduces the dimension of data series. The efficiency of the approach was verified by considering numerical examples