Effects of crude oil and oil fractions on the liver P450-dependent monooxygenase activities and antioxidant defence system of different freshwater fish species.

The effects of crude oil (Szeged-Algyo, Hungary) and oil fractions (F1: rich in aromatics; F2 fraction: free from aromatics) were investigated on liver CYP1A isoenzymes and antioxidant defence system following their i.p. injection into different freshwater fish species: carp (Cyprinus carpio L.), silver carp (Hyphothalmichtys molitrix V.), and European eel (Anquilla anquilla). A dose of 2 mL kg -1 crude oil enhanced EROD activity 8-fold in carp and only 5-fold in eel after 3 days. Oil fraction F1 caused only a 2-fold induction in EROD activity only in carp, while F2 fraction caused significant inhibition in all three investigated fish species. The antioxidant parameters [lipid peroxidation (LP), catalase (CAT), superoxide dismutase (SOD), glutathione peroxidase (GPx), glutathione (GSH)] were measured following the treatment. A decrease of 50% in CAT activity was observed after oil treatment. The GSH level enhanced, resulting the protective effects against LP. The same dose of crude oil but a longer duration time resulted in lower CYP1A induction in carp and antioxidant parameters had returned close to control. In all treatments the EROD isoenzymes proved to be more sensitive and the effects of oil treatment showed species to be different. Carp proved to be more sensitive than eel or silver carp.

In vivo and in vitro effects of deltamethrin on cytochrome P450 monooxygenase activity in carp (Cyprinus carpio L) liver.

The in vivo and in vitro effects of the insecticide deltamethrin (DM) on hepatic cytochrome P450 (Cyt P450) monooxygenase were examined in adult carp. The in vivo experiments were carried out with 0.2 microgram/l DM at 20 degrees C. The changes in the hepatic microsomal Cyt P450 content and the Cyt P450-dependent monooxygenase activities were studied in DM-treated fish. Although there were no changes in the Cyt P450 content during the exposure time, after treatment for 24 h all the investigated isoenzyme activities (para-nitrophenetole-O-deethylase, p-NPOD; aminopyrene-N-demethylase, APND; ethylmorphine-N-demethylase, EMND; 7-ethoxycoumarin-O-deethylase, ECOD; and ethoxyresorufin-O-deethylase, EROD) were significantly inhibited. After 72 h, all the activities were still lower than in the control animals. In vitro incubation of liver microsomes with DM led to a concentration-dependent decrease in total microsomal Cyt P450 content. A complete loss of Cyt P450 occurred after a 5-min incubation with 60 microM DM. The maximum in the difference spectra of microsomes was shifted to higher wavelength, showing the strong interaction of DM with Cyt P450. EROD and ECOD activities were inhibited by DM. The in vitro kinetic results on ECOD revealed that the inhibition was of non-competitive type, with K1 = 9.8 +/- 2.3 microM. This study indicates important biochemical effects of DM in fish liver, and suggests that exposure to DM may cause loss of the Cyt P450-dependent metabolism in fish.

Recognizing people seen in events via dynamic "mug shots".

This study examined effects of an event and dynamic mug shots on facial recognition. Witnesses saw either a film of a liquor store holdup staged by six perpetrators, slides of the same targets, or freeze-framed views from the filmed event. Slides of different facial views of targets among 12 foils, or dynamic 180 degrees mug shots of the same men, or multiple static views were administered 24 hr later in yes-no recognition tests. Recognition (d') was poorer for the same men seen in the event than in slides, but better for dynamic than for static mug shots. Nondynamic event characteristics were responsible for poor recognition of people seen in events, whereas dynamic aspects of facial transformations, not multiple views, seemed responsible for the superiority of dynamic mug shots. The implications of these results for issues of ecological validity of traditional face recognition methodology and for static feature models vs. dynamic transformation models of face recognition are discussed.