Search

The frequencies of erythrocytic nuclear abnormalities (ENA), micronuclei (MN), vacuolated nuclei (VN) including cytoplasmic vacuoles (CV) were monitored in the peripheral blood of cultured shade fish Argyrosomus regius (Asso, 1801). Sampling was performed through three seasons: at the end of the winter (March), spring (May) and summer (July) at one location from southern Adriatic Sea (Croatia). ENA comprised blebbed, lobed and notched nuclei, which were the most frequent features, while the MN, VN and CV appeared sporadically. The highest level of ENA and MN were detected in July, and VN in March, respectively. The rarest appearance of these parameteres were recorded in May. Inversely, cytoplasmic vacuoles were the most frequent in May and the least in July. The Spearman rank order correlation test revealed a significant positive correlation between the frequencies of ENA and MN (P < 0.05, r = 0.44), ENA and VN (P < 0.05, r = 0.56). Also, the frequency of MN significantly positively correlated with water temperature (P < 0.05, r = 0.42) and negatively with level of oxygen (P < 0.05, r = - 0.42). Cytoplasmic vacuoles did not correlate with any measured parameters. Our results demonstrate that these parameters displayed a distinct seasonal variation.

Plasma biochemical profile was examined in cage cultured shade fish Argirosomus regius in order to evaluate physiological profile and provide detailed picture of its seasonal changes. Biochemical procedures were employed to study trygliceride (TRIG), cholesterol (CHOL), total protein (TP), glucose (GLU), urea (BUN), inorganic phosphate (PHOS), calcium (Ca), creatine kinase (CK), lactate dehydrogenase (LDH), ammonia (NH3), magnesium (Mg), aspartate aminotransferase (AST), amylase (AMYL), alkaline phosphatase (ALKP), creatinine (CREA), gamma glutamyltransferase (GGT) and total bilirubin (TBIL). The results were evaluated through different statistical analyses. Conventional statistical methods do not provide solutions that meet the goals of the research, so machine learning methodology was used to construct and evaluate classifiers as well as to assess parameter (plasma metabolites and enzymes) importances with respect to the target variable (season). It is evident that about half of the parameters (UREA, ALKP, NH3, CHOL, Ca, PHOS, GLU and CREA) have significant importance (i.e. exhibit significant differences between seasons) for seasonal discrimination models. It is also important to stress that using only a subset of most important parameters is generally enough to obtain high accuracy classifiers, which suggests rather high correlation between these parameters on a seasonal scale.