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Pikeperch (Sander lucioperca), European catfish (Silurus glanis), common carp (Cyprinus carpio), and gobies (Neogobius gymnotrachelus, Neogobius melanostomus) were collected from the Danube River (Belgrade section), and samples of liver, muscle, or whole-body composites (in the case of gobies) were analyzed for As, Cu, Fe, Hg, Mn, and Zn with inductively coupled plasma optical spectrometry to find out if there was a correlation between accumulation of these elements in predatory and prey species, as well as in pairs of species with overlapping diets. Concentrations of all analyzed elements were either higher (Cu, Fe, Mn, Zn) in liver than in muscle, or equal (As, Hg), except for Hg in carp, which was higher in muscle. Mercury concentration in liver and muscle of predators (catfish, pikeperch) was significantly (<10(-4)) higher than in prey fishes (carp and gobies). The results indicate that Hg concentration was biomagnified through the food chain. Concentrations of As, Fe, and Hg in carp liver and gobies whole-body composite were similar, but carp had significantly (<10(-4)) higher values of Zn and Cu in liver. The regression analysis and trendline equations indicate that the concentrations of all tested elements, except for As in liver, and Mn and Fe in muscle, were similar in predatory fish (pikeperch and catfish), on one hand, and in prey fish (carp and gobies), on the other hand. Distinctly high Zn concentration in carp is very common in this species due to its physiology. Concentrations of Hg and Zn were higher than the maximum acceptable concentration due to the high pollution level in this section of the Danube River, accordingly posing a risk for the human consumption of these fish species.

The complexity, entropy and other non-linear measures of the electroencephalogram (EEG), such as Higuchi fractal dimension (FD), have been recently proposed as the measures of anesthesia depth and sedation. We hypothesized that during unconciousness in rats induced by the general anesthetics with opposite mechanism of action, behaviorally and poligraphically controlled as appropriately achieved stable anesthesia, we can detect distinct inter-structure brain dynamic using mean FDs. We used the surrogate data test for nonlinearity in order to establish the existence of nonlinear dynamics, and to justify the use of FD as a nonlinear measure in the time series analysis. The surrogate data of predefined probability distribution and autocorrelation properties have been generated using the algorithm of statically transformed autoregressive process (STAP). FD then is applied to quantify EEG signal complexity at the cortical, hippocampal and pontine level during stable general anesthesia (ketamine/xylazine or nembutal anesthesia). Our study showed for the first time that global neuronal inhibition caused by different mechanisms of anesthetic action induced distinct brain inter-structure complexity gradient in Sprague Dawley rats. EEG signal complexities were higher at cortical and hippocampal level in ketamine/xylazine vs. nembutal anesthesia, with the dominance of hippocampal complexity. In nembutal anesthesia the complexity dominance moved to pontine level, and ponto-hippocampo-cortical decreasing complexity gradient was established. This study has proved the Higuchi fractal dimension as a valuable tool for measuring the anesthesia induced inter-structure EEG complexity.

With application of the Higuchi algorithm, fractal dimension (FD) values of the electrocortical activity of the rat parietal cerebral and paravermal cerebellar cortex were calculated, before and after unilateral discrete injury of the left parietal cortex. Immediately following the first acute injury, in a group of six rats, a reversible increase in mean FD was found at the left (ipsilateral side to the injury) cerebral cortex, from 1.38 to 1.59, and at the left cerebellar cortex from 1.51 to 1.73. In addition, an indication of plastic changes after repeated (third) injury was found as an irreversible increase in mean FD: 1.54 on the left and 1.48 on the right side of parietal cortex.

We propose a new method for calculating fractal dimension (DF) of a signal y(t), based on coefficients m (n) y , mean absolute values of its nth order derivatives (consecutive finite differences for sampled signals). We found that logarithms of m (n) y , n = 2, 3, . . . , n max , exhibited linear dependence on n:with stable slopes and Y -intercepts proportional to signal DF values. Using a family of Weierstrass functions, we established a link between Y -intercepts and signal fractal dimension:and calculated parameters A(n max ) and B(n max ) for n max = 3, . . . , 7. Compared to Higuchi's algorithm, advantages of this method include greater speed and eliminating the need to choose value for k max , since the smallest error was obtained with n max = 3. 283 Fractals 2005.13:283-292. Downloaded from www.worldscientific.com by EMORY UNIVERSITY on 07/30/15. For personal use only.