Chokeberry juice affects membrane lipid status and cellular antioxidant enzymes in healthy women with aerobic training activity

The present study examined the effects of aerobic training alone or combined with chokeberry juice on membrane lipid status and activities of antioxidant enzymes in non-athlete women. Participants were randomly assigned into the training group performing aerobic training three times per week; the chokeberry-training group followed the same training regime and additionally consumed 100 ml of chokeberry juice per day and the control group neither trained nor consumed the juice. Blood samples were collected at baseline and the end of the eight-week-long intervention. Membrane fatty acids’ composition was analyzed by gas-liquid chromatography, while the activities of antioxidant enzymes were measured by spectrophotometry. As a result, the n-3 fatty acids’ content was significantly higher in the chokeberry-training (median (interquartile range) of 5.96 (1.65) %) compared with the control group (5.12 (0.87) %), while saturated fatty acids’ content was lower in the chokeberry-training (40.14±1.19 %) than in the training group (42.59±2.29 %). We detected significantly higher activity of superoxide dismutase in the training (2224 (2170) U/gHb) compared with the chokeberry-training (1252 (734) U/gHb) and control group (1397 (475) U/gHb). Our study indicates that supplementation with chokeberry juice may induce favorable changes in cell fatty acid composition and antioxidant response in women performing aerobic training

O suicídio deles e o nosso

O suicídio deles e o noss

Cidade do Caos

Cidade do Cao

Overcoming System Complexity using Models and Knowledge Structures. Editorial Introduction to Issue 36 of CSIMQ

Models allow us to simplify reality and give advantages to both decomposition and abstraction. Models can have various forms from textual, tabular, mathematical, and graphical to a combination of these formats. Formal models can be processed, or even executed, by machines. An engineering model must satisfy such characteristics as abstraction, understandability, accuracy, predictiveness, and inexpensiveness. Models explicitly represent knowledge of the modeled domain in a form suitable for reasoning about them and learning. Knowledge may be descriptive, structural, procedural, meta-, or heuristic. Focus on one type of knowledge during the analysis may ignore the other one. Moreover, analysis and reasoning also rely on data representation forms which may lose accuracy due to simplification and different assumptions. Therefore, completeness, correctness, and adequacy of knowledge as well as particularities of the representing structure may affect the results of knowledge processing and decision making. Therefore, the capability of models (and other structures) to represent knowledge completely, adequately, and accurately is still a matter of various research activities. This issue of CSIMQ is devoted to this matter