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Correlations between urinary excretion of DGA and exposure indices (styrene in air and MA + PGA in urine).
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Styrene, oxidized by liver microsomal enzymes, can determine a liver enzyme induction. Urinary excretion of D-glucaric acid (DGA), which is believed to estimate this effect, was measured in 27 workers exposed to styrene in a fiberglass plant and in 27 control subjects in order to make a comparison with environmental and biological exposure indices....
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... mol Cr. There was a statistically significant increase in the DGA urinary excretion of exposed workers with respect to controls. Nevertheless, it should be stressed that no significant correlation was found between individual exposure to styrene evaluated by the environmental concentration or by urinary metabolites and urinary excretion of DGA (Fig. 2). Table 2 shows that styrene exposure is the variable with the greatest influence on urinary excretion of DGA (29.8%), followed by age (6.8%). No other variable significantly affects DGA ...
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(1) Background: The products of guanine oxidation in DNA and RNA excreted in urine are 8-oxo-7,8-dihydroguanine (8-oxoGua), 8-oxo-7,8-dihydroguanosine (8-oxoGuo), and 8-oxo-7,8-dihydro-2’-deoxyguanosine (8-oxodGuo). Despite intra and inter-individual variability, it is possible to identify situations that significantly increase the levels of these...
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The essential oil from Rosmarinus officinalis presents antifungal activity and is used in industry as a natural preserving agent. However, essential oils are unstable compounds. So, the encapsulation of essential oils is a technique used to protect it, minimizing degradation and reducing undesired interaction with the other formulation components. Thus, this work focuses on the synthesis of terpolymeric capsules containing essential oil from Rosmarinus officinalis, aiming to use it as an antifungal component in cosmetics. The capsules were obtained via terpolymerization of methyl methacrylate, styrene and methacrylic acid in a dispersed phase polymerization process. The properties of the polymers and the fungicide activity were evaluated. The studied essential oil presented a Minimum Inhibitory Concentration (MIC) ranging from 2.25 to 4.5 mg mL-1 and a Minimum Fungicidal Concentration (MFC) from 4.5 to 9.0 mg mL-1 for strains of Candida albicans, Candida glabrata and Candida parapsilosis, and after the encapsulation process, the antifungal activity of the oil was maintained. Additionally, cytotoxicity assays against fibroblast cell lines and human keratinocytes showed that the polymeric nanocapsules containing Rosmarinus officinalis essential oil can be regarded as a very promising material intended for cosmetics and drug delivery applications.
Occupational exposure to styrene was studied in 34 workers employed in the production of fiberglass-reinforced plastic sheets and compared to 29 unexposed healthy controls. We evaluated genotoxic effects induced by occupational styrene exposure in lymphocytes by alkaline version of the comet assay to detect single-strand breaks (SSBs), DNA oxidation products (formamido pyrimidine glycosilase (Fpg)- and endonuclease (Endo III)-sensitive sites) and DNA repair kinetics studies, as well as the neutral version of comet assay for DNA double-strand breaks (DSBs). An innovative aspect of this study was the use of immuno-comet assay, a new technique that recognizes DSBs with specific antibody by DAPI/FITC method. The battery of parameters included markers of external and internal exposure. Exposed workers showed significant high levels of SSBs (p<0.0001) and DSBs (p<0.0001) in neutral- and immuno-comet assay. A drastic decrease in DNA repair activity as compared to controls was observed (180 min vs. 35 min). Styrene workplace concentration significantly correlated with alkaline comet parameters (TM, p=0.013; TI, p=0.008), in negative with TL (p=0.022), and with DNA-base oxidation (TM Endo III, p=0.048 and TI Endo III, p=0.028). There was a significant negative correlation between urinary metabolites (MA+PGA) and TM Endo III (p=0.032) and TI Endo III (p=0.017).
Designing biologically active chemicals and managing their risks requires a holistic perspective on the chemical-biological interactions that form the basis of selective toxicity. The balance of therapeutic and adverse outcomes for new drugs and pesticides is managed by shaping the probabilities for transport, metabolism, and molecular initiating events. For chemicals activated as well as detoxified by metabolism, selective toxicity may be considered in terms of relative probabilities, which shift dramatically across species as well as within a population, depending on many factors. The complexity in toxicology that results from metabolism has been troublesome in QSAR research because the parent structure is less relevant to predicting ultimate effects and finding reference species/conditions for metabolic rates seems hopeless. Even the complexity of comparative xenobiotic metabolism itself seems paradoxical in light of the evidence of highly conserved catabolic processes across species. Clearly, predicting the role of metabolism in selective toxicity and adverse health outcomes requires a probabilistic framework for deterministic models as well as the many factors shaping the metabolic probability distributions under specific conditions. This paper presents a tissue metabolism simulator (TIMES), which uses a heuristic algorithm to generate plausible metabolic maps from a comprehensive library of biotransformations and abiotic reactions and estimates for system-specific transformation probabilities. The transformation probabilities can be calibrated to specific reference conditions using transformation rate information from systematic testing. In the absence of rate data, a combinatorial algorithm is used to translate known metabolic maps taken from reference systems into best-fit transformation probabilities. Finally, toxicity test data itself can be used to shape the transformation probabilities for toxicity pathways in which the metabolic activation is the rate-limiting process leading to a toxic effect. The conceptual approach for metabolic simulation will be presented along with practical uses in forecasting plausible activated metabolites.
Traditional attempts to model genotoxicity data have been limited to congeneric data sets, primarily because the mechanism of action was ignored, and frequently, the chemicals required metabolism to the active species. In this exercise, the COmmon REactivity PAtterns (COREPA) approach was used to delineate the structural requirements for eliciting mutagenicity in terms of ranges of descriptors associated with three-dimensional molecular structures. The database used to build the mutagenicity model includes 1196 structurally diverse chemicals tested in the Ames assay by the National Toxicology Program. This manuscript describes the development of the TA100 model that predicts the results of mutagenicity testing using only the Ames TA100 strain. The TA100 model was developed using 148 chemicals that tested positive in TA100 strain without rat liver enzymes (S-9) and 188 chemicals that tested positive in TA100 strain with rat liver enzymes. A decision tree was developed by first comparing the reactivity profile of chemicals that were positive in TA100 without rat liver enzymes to the reactivity profile of the remaining 1048 chemicals. This approach correctly identified 82% of the primary acting mutagens and 94% of the nonmutagens in the training set. The 188 chemicals in the training set that are positive only in the presence of metabolic activation would pass through the decision tree as negative. The next step was to identify the chemicals that are positive only in the presence of metabolic activation. To accomplish this, a series of hierarchically ordered metabolic transformations were used to develop an S-9 metabolism simulator that was applied to each of the 1048 chemicals. The potential metabolites were then screened through the decision tree to identify reactive mutagens. This model correctly identified 77% of the metabolically activated chemicals in a training set. A computer system that applies the COREPA models and predicts mutagenicity of chemicals, including their metabolic activation, was developed. Each prediction is accompanied by a probabilistic estimate of the chemical being in the structural domain covered by the training set.
The aim of this study was to review modifications of the endogenous pathways (e.g. enzyme elevations, normal body constituent depletion or higher formation/excretion of endogenous metabolites) which could be ascribed to enzyme induction by antiepileptic drugs (AEDs). Information on older (e.g. phenobarbital, phenytoin and carbamazepine) and newer drugs (where information is available) is discussed together with clinical implications. The enzymes involved in the endogenous pathways and induced by the AEDs will not be limited to the hepatic microsomal enzymes; extrahepatic enzymes and/or enzymes present in other subcellular fractions will also be discussed, if pertinent. The induction of endogenous pathways by AEDs has been taken into account in the past, but much less emphasis has been given compared with the extensive literature on induction by AEDs of the metabolism of concomitantly administered drugs, either of the same or of different classes. Not all of the endogenous pathways examined and induced by AEDs appear to result in serious clinical consequences (e.g. induction of hepatic ALP, increased excretion of d-glucaric acid or of 6 beta-hydroxycortisol). In some cases, induction of some pathways (e.g. increase of high-density lipoprotein cholesterol or of conjugated bilirubin) might even be a beneficial side-effect, however enzyme induction is considered rather a detrimental aspect for an AED, as induction is generally a broad and a non-specific phenomenon. The new AEDs have generally less induction potential than the older agents. Yet some (felbamate, topiramate, oxcarbazepine and lamotrigine) have the potential for inducing enzymes, whereas others (levetiracetam, gabapentin and vigabatrin) appear to be completely devoid of enzyme inducing characteristics, at least as far as the enzymes investigated are concerned.
