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ABSTRACT:Cattle represent an important source of animal-derived foodproducts; nonetheless, our knowledge about the expression of drug-metabolizing enzymes (DMEs) in present and other foodproducing animals still remains superficial, despite the obvious toxicological consequences. Breed represents an internal factor that modulates DME expression and catalytic activity. In the present work, the effect of breed upon relevant phase I and phase II DMEs was investigated at the pretranscriptional and post-translational levels in male Charolais (CH), Piedmontese (PM) and Blonde d'Aquitaine (BA) cattle. Because specific substrates for cattle have not yet been identified, the breed effect upon specific cytochrome P450 (P450), UDP-glucuronosyltransferase (UGT), or glutathione S-transferase (GST) DMEs, in terms of catalytic activity, was determined by using human marker substrates. Among P450s, benzphetamine N-demethylase, 16␤-, 6␤-, and 2␤-testosterone hydroxylase, aniline and p-nitrophenol hydroxylase, and ␣-naphthol and p-nitrophenol UGT activities were significantly higher in CH; in contrast, lower levels of CYP1A1-, CYP1A2-, CYP2B6-, CYP2C9-, CYP2C18-, CYP3A4-, and UGT1A1-like mRNAs were noticed, with CH < PM < BA as a trend. CYP2B and CYP3A mRNA results were confirmed with immunoblotting, too. As regards conjugative DMEs, UGT1A6-like mRNA levels were consistent with respective catalytic activities. Both 1-chloro-2,4-dinitrobenzene and 3,4-dichloronitrobenzene GST activities were higher in BA, and these results agreed with GSTA1-, GSTM1-, and GSTP1-like mRNA amounts. Correlation analysis between catalytic activities and mRNAs showed either significant or uneven results, depending on the substrate. These findings confirm previous data obtained in laboratory species; however, further studies are required to ascribe this behavior to pretranscriptional or post-translational phenomena.Historically, studies concerning drug-metabolizing enzyme (DME) expression and regulation in veterinary food-producing species (e.g., cattle, swine, poultry) have always been considered of lesser interest, if compared with those done in man and laboratory animals. This is rather peculiar. Basically, the DMEs comparative knowledge is useful either to extrapolate pharmacotoxicological data from one species to another or to extend veterinary drug licenses of use from major to minor or exotic species. On the other hand, farm animals are often exposed to pesticides, pollutants, or drugs (sometimes used illicitly to increase growth performances), which are potentially harmful for the animal itself and also for humans, if the consumption of animal edible tissues containing relevant amounts of residues occurs. Consequently, drug metabolism studies, performed in these animals, are of value for the evaluation of the consumer's risk (Sivapathasundaram et al., 2001, This study was supported by the Università degli Studi di Padova (Grants 60A08-8213/05, Studi sull'espressione degli enzimi farmaco-metabolizzanti nel fegato di bovini appartenenti a razze dive...

oxalic acid / varroosis / honeybee / honey / residues Tests on the use of oxalic acid for controlling varroosis (Takeuchi et al, 1983; Zjuman, 1987;Radetzki et al, 1994;Nanetti et al, 1995;Imdorf et al, 1997) Bee mortality was determined using 'underbasket traps' applied to each hive (Accorti, 1994).The mean efficacy of the three treatments with oxalic acid was 95% (± 7.39%) (

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Cytochrome P450 3A is the most important CYP subfamily in humans, and CYP3A4/CYP3A5 genetic variants contribute to inter-individual variability in drug metabolism. However, no information is available for bovine CYP3A (bCYP3A). Here we described bCYP3A missense single nucleotide variants (SNVs) and evaluated their functional effects. CYP3A28, CYP3A38 and CYP3A48 missense SNVs were identified in 300 bulls of Piedmontese breed through targeted sequencing. Wild-type and mutant bCYP3A cDNAs were cloned and expressed in V79 cells. CYP3A-dependent oxidative metabolism of testosterone (TST) and nifedipine (NIF) was assessed by LC-MS/MS. Finally, SNVs functional impact on TST hydroxylation was measured ex vivo in liver microsomes from individually genotyped animals. Thirteen missense SNVs were identified and validated. Five variants showed differences in CYP3A catalytic activity: three CYP3A28 SNVs reduced TST 6β-hydroxylation; one CYP3A38 variant increased TST 16β-hydroxylation, while a CYP3A48 SNV showed enhanced NIF oxidation. Individuals homozygous for rs384467435 SNV showed a reduced TST 6β-hydroxylation. Molecular modelling showed that most of SNVs were distal to CYP3A active site, suggesting indirect effects on the catalytic activity. Collectively, these findings demonstrate the importance of pharmacogenetics studies in veterinary species and suggest bCYP3A genotype variation might affect the fate of xenobiotics in food-producing species such as cattle.

In this work the feasibility of near infrared spectroscopy was evaluated combined with chemometric approaches, as a tool for the botanical origin prediction of 119 honey samples. Four varieties related to polyfloral, acacia, chestnut, and linden were first characterized by their physical-chemical parameters and then analyzed in triplicate using a near infrared spectrophotometer equipped with an optical path gold reflector. Three different classifiers were built on distinct multivariate and machine learning approaches for honey botanical classification. A partial least squares discriminant analysis was used as a first approach to build a predictive model for honey classification. Spectra pretreatments named autoscale, standard normal variate, detrending, first derivative, and smoothing were applied for the reduction of scattering related to the presence of particle size, like glucose crystals. The values of the descriptive statistics of the partial least squares discriminant analysis model allowed a sufficient floral group prediction for the acacia and polyfloral honeys but not in the cases of chestnut and linden. The second classifier, based on a support vector machine, allowed a better classification of acacia and polyfloral and also achieved the classification of chestnut. The linden samples instead remained unclassified. A further investigation, aimed to improve the botanical discrimination, exploited a feature selection algorithm named Boruta, which assigned a pool of 39 informative averaged near infrared spectral variables on which a canonical discriminant analysis was assessed. The canonical discriminant analysis accounted a better separation of samples according to the botanical origin than the partial least squares discriminant analysis. The approach used has permitted to achieve a complete authentication of the acacia honeys but not a precise segregation of polyfloral ones. The comparison between the variables important in projection and the Boruta pool showed that the informative wavelengths are partially shared especially in the middle and far band of the near infrared spectral range.

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