987 resultados para chemical exposure


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Objectives - This study intended to characterize work environment contamination by particles in 2 waste-sorting plants. Material and Methods - Particles were measured by portable direct-reading equipment. Besides mass concentration in different sizes, data related with the number of particles concentration were also obtained. Results - Both sorting units showed the same distribution concerning the 2 exposure metrics: particulate matter 5 (PM5) and particulate matter 10 (PM10) reached the highest levels and 0.3 μm was the fraction with a higher number of particles. Unit B showed higher (p < 0.05) levels for both exposure metrics. For instance, in unit B the PM10 size is 9-fold higher than in unit A. In unit A, particulate matter values obtained in pre-sorting and in the sequential sorting cabinet were higher without ventilation working. Conclusions - Workers from both waste-sorting plants are exposed to particles. Particle counting provided additional information that is of extreme value for analyzing the health effects of particles since higher values of particles concentration were obtained in the smallest fraction.

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Ochratoxin A (OTA) is a mycotoxin produced by a variety of fungi, such as Penicillium verrucosum and Aspergillium spp., which has been found to have a wide number of potentially deadly toxic effects, and can enter the human organism through a variety of means. It then finds its way into the bloodstream and, after a lengthy process, is eventually excreted through the urine. It can thus be detected in its original form not only in blood samples but also in this biological medium. As such, and in an attempt to evaluate the exposure of the Portuguese population to this mycotoxin, morning urine samples were collected during the Winter of 2007, from each of five geographically distinct Portuguese locations — Bragança, Porto, Coimbra, Alentejo, and Algarve — and subjected to extraction by immunoaffinity columns and to OTA quantification through liquid chromatography coupled with fluorescence detection. Prevalent incidence was higher than 95% with Coimbra being the exception (incidence of 73.3%). In nearly all locations, the OTA content of most samples was found to be above the limit of quantification (LOQ) of 0.008 ng/ml. Indeed, excluding Coimbra, with an OTA content level of 0.014 ng/ml, all regions featured content values over 0.021 ng/ml.

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The occurrence of OTA in fresh and packed wheat and in maize bread and the evaluation of the exposure degree through their consumption in two Portuguese populations from Porto and Coimbra, during the winter of 2007, were studied. One hundred and sixty eight bread samples, 61 maize and 107 wheat, were analysed by liquid chromatography–fluorescence detection (LC–FD). The results showed that 84% of samples were contaminated, with a maximum level of 3.85 ng/g (above the EU maximum limit, 3 ng/g). Fresh wheat bread presented higher levels than packed wheat bread. Moreover, the traditional maize bread, in either city, was consistently more contaminated than wheat bread, 0.25 vs 0.19 ng/g, and 0.48 vs 0.34 ng/ g for Porto and Coimbra, respectively. Avintes maize bread showed the highest mean contamination and maximum levels. The higher estimated daily intake of OTA from both types of bread in the population of Coimbra compared to Porto reflects the higher average contamination of bread in the first city.

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This study reports the levels of nitrate and nitrite of 34 vegetable samples, including different varieties of cabbage, lettuce, spinaches, parsley and turnips, collected in several locations of an intensive agricultural area (Modivas, Vila do Conde, northern Portugal). Nitrate levels ranged between 54 and 2440 mg NO-3 kg-1, while nitrite levels ranged between 1.1 and 57 mg NO-2 kg-1. The maximum residue levels established for nitrate in spinach and lettuce samples were not exceeded. Nitrate and nitrite levels reported in the literature for the same type of samples are reviewed, as well as the contribution of vegetables to nitrate and nitrite dietary exposure of populations.

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OBJECTIVE: To assess the impact of academic life on health status of university students. METHODS: Longitudinal study including 154 undergraduate students from the Universidade de Aveiro, Portugal, with at least two years of follow-up observations. Sociodemographic and behavioral characteristics were collected using questionnaires. Students' weight, height, blood pressure, serum glucose, serum lipids and serum homocysteine levels were measured. Regression analysis was performed using linear mixed-effect models, allowing for random effects at the participant level. RESULTS: A higher rate of dyslipidemia (44.0% vs. 28.6%), overweight (16.3% vs. 12.5%) and smoking (19.3% vs. 0.0%) was found among students exposed to the academic life when compared to freshmen. Physical inactivity was about 80%. Total cholesterol, high density lipoprotein-cholesterol (HDL-C), triglycerides, systolic blood pressure, and physical activity levels were significantly associated with gender (p<0.001). Academic exposure was associated with increased low density lipoprotein-cholesterol (LDL-C) levels (about 1.12 times), and marginally with total cholesterol levels (p=0.041). CONCLUSIONS: High education level does not seem to have a protective effect favoring a healthier lifestyle and being enrolled in health-related areas does not seem either to positively affect students' behaviors. Increased risk factors for non-transmissible diseases in university students raise concerns about their well-being. These results should support the implementation of health promotion and prevention programs at universities.

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Abstract: Ototoxic substances have been associated to damage of the auditory system, and its effects are potentiated by noise exposure. The present study aims at analyzing auditory changes from combined exposure to noise and organic solvents, through a pilot study in the furniture industry sector. Audiological tests were performed on 44 workers, their levels of exposure to toluene, xylene and ethylbenzene were determined and the levels of noise exposure were evaluated. The results showed that workers are generally exposed to high noise levels and cabin priming filler and varnish sector workers have high levels of exposure to toluene. However, no hearing loss was registered among the workers. Workers exposed simultaneously to noise and ototoxic substances do not have a higher degree of hearing loss than those workers exposed only to noise. Thus, the results of this study did not show that the combined exposure to noise and the organic solvent is associated with hearing disorders.

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Pesticide exposure during brain development could represent an important risk factor for the onset of neurodegenerative diseases. Previous studies investigated the effect of permethrin (PERM) administered at 34 mg/kg, a dose close to the no observable adverse effect level (NOAEL) from post natal day (PND) 6 to PND 21 in rats. Despite the PERM dose did not elicited overt signs of toxicity (i.e. normal body weight gain curve), it was able to induce striatal neurodegeneration (dopamine and Nurr1 reduction, and lipid peroxidation increase). The present study was designed to characterize the cognitive deficits in the current animal model. When during late adulthood PERM treated rats were tested for spatial working memory performances in a T-maze-rewarded alternation task they took longer to choose for the correct arm in comparison to age matched controls. No differences between groups were found in anxiety-like state, locomotor activity, feeding behavior and spatial orientation task. Our findings showing a selective effect of PERM treatment on the T-maze task point to an involvement of frontal cortico-striatal circuitry rather than to a role for the hippocampus. The predominant disturbances concern the dopamine (DA) depletion in the striatum and, the serotonin (5-HT) and noradrenaline (NE) unbalance together with a hypometabolic state in the medial prefrontal cortex area. In the hippocampus, an increase of NE and a decrease of DA were observed in PERM treated rats as compared to controls. The concentration of the most representative marker for pyrethroid exposure (3-phenoxybenzoic acid) measured in the urine of rodents 12 h after the last treatment was 41.50 µ/L and it was completely eliminated after 96 h.

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Bisphenol A (BPA) is an endocrine disrupting chemical (EDC) whose migration from food packaging is recognized worldwide. However, the real overall food contamination and related consequences are yet largely unknown. Among humans, children’s exposure to BPA has been emphasized because of the immaturity of their biological systems. The main aim of this study was to assess the reproductive impact of BPA leached from commercially available plastic containers used or related to child nutrition, performing ecotoxicological tests using the biomonitoring species Daphnia magna. Acute and chronic tests, as well as single and multigenerational tests were done. Migration of BPA from several baby bottles and other plastic containers evaluated by GC-MS indicated that a broader range of foodstuff may be contaminated when packed in plastics. Ecotoxicological test results performed using defined concentrations of BPA were in agreement with literature, although a precocious maturity of daphnids was detected at 3.0 mg/L. Curiously, an increased reproductive output (neonates per female) was observed when daphnids were bred in the polycarbonate (PC) containers (145.1±4.3 % to 264.7±3.8 %), both in single as in multigenerational tests, in comparison with the negative control group (100.3±1.6 %). A strong correlated dose-dependent ecotoxicological effect was observed, providing evidence that BPA leached from plastic food packaging materials act as functional estrogen in vivo at very low concentrations. In contrast, neonate production by daphnids cultured in polypropylene and non-PC bottles was slightly but not significantly enhanced (92.5±2.0 % to 118.8±1.8 %). Multigenerational tests also revealed magnification of the adverse effects, not only on fecundity but also on mortality, which represents a worrying trend for organisms that are chronically exposed to xenoestrogens for many generations. Two plausible explanations for the observed results could be given: a non-monotonic dose–response relationship or a mixture toxicity effect.

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The simultaneous presence of fungi and particles in horse stable environment can create a singular exposure condition because particles have been reported has a good carrier for microorganisms and their metabolites. This study intends to characterize this setting and to recognize fungi and particles occupational exposure.

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Phenolic compounds constitute a diverse group of secondary metabolites which are present in both grapes and wine. The phenolic content and composition of grape processed products (wine) are greatly influenced by the technological practice to which grapes are exposed. During the handling and maturation of the grapes several chemical changes may occur with the appearance of new compounds and/or disappearance of others, and consequent modification of the characteristic ratios of the total phenolic content as well as of their qualitative and quantitative profile. The non-volatile phenolic qualitative composition of grapes and wines, the biosynthetic relationships between these compounds, and the most relevant chemical changes occurring during processing and storage will be highlighted in this review.

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This synopsis summarizes the key chemical and bacteriological characteristics of β-lactams, penicillins, cephalosporins, carbanpenems, monobactams and others. Particular notice is given to first-generation to fifth-generation cephalosporins. This reviewalso summarizes the main resistancemechanism to antibiotics, focusing particular attention to those conferring resistance to broad-spectrum cephalosporins by means of production of emerging cephalosporinases (extended-spectrum β-lactamases and AmpC β-lactamases), target alteration (penicillin-binding proteins from methicillin-resistant Staphylococcus aureus) and membrane transporters that pump β-lactams out of the bacterial cell.

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OBJECTIVE: To assess the health risk of exposure to benzene for a community affected by a fuel leak. METHODS: Data regarding the fuel leak accident with, which occurred in the Brasilia, Federal District, were obtained from the Fuel Distributor reports provided to the environmental authority. Information about the affected population (22 individuals) was obtained from focal groups of eight individuals. Length of exposure and water benzene concentration were estimated through a groundwater flow model associated with a benzene propagation model. The risk assessment was conducted according to the Agency for Toxic Substances and Disease Registry methodology. RESULTS: A high risk perception related to the health consequences of the accident was evident in the affected community (22 individuals), probably due to the lack of assistance and a poor risk communication from government authorities and the polluting agent. The community had been exposed to unsafe levels of benzene (> 5 µg/L) since December 2001, five months before they reported the leak. The mean benzene level in drinking water (72.2 µg/L) was higher than that obtained by the Fuel Distributer using the Risk Based Corrective Action methodology (17.2 µg/L).The estimated benzene intake from the consumption of water and food reached a maximum of 0.0091 µg/kg bw/day (5 x 10-7 cancer risk per 106 individuals). The level of benzene in water vapor while showering reached 7.5 µg/m3 for children (1 per 104 cancer risk). Total cancer risk ranged from 110 to 200 per 106 individuals. CONCLUSIONS: The population affected by the fuel leak was exposed to benzene levels that might have represented a health risk. Local government authorities need to develop better strategies to respond rapidly to these types of accidents to protect the health of the affected population and the environment.

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Fungi on crops produce mycotoxins in the field, during handling, and in storage. Exposure of animals and humans are usually through consumption of contaminated feedstuffs or foods. Molds can grow and mycotoxins can be produced either pre-harvest or post-harvest, during storage, transport, processing, or feeding. Worldwide, approximately 25% of crops are affected by mycotoxins annually. Because of this is possible to concluded that mycotoxins occur frequently in a variety of feedstuffs that are given to animals causing several effects: subclinical losses in performance, increases the incidence of disease and reduced reproductive performance. Aim of study: A study was developed intending to know environmental fungal contamination in a Portuguese feed production unit. Corn, wheat and soybeans were the most common cereals used in the feed production.

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Contrary to fungi, exposure to mycotoxins is not usually identified as a risk factor present in occupational settings. This is probably due to the inexistence of limits regarding concentration of airborne mycotoxins, and also due to the fact that these compounds are rarely monitored in occupational environments. Aflatoxin B1 (AFB1) is the most prevalent aflatoxin and is associated with carcinogenicity, teratogenicity, genotoxicity and immunotoxicity but only a few studies examined exposure in occupational settings. Workers can be exposed to high airborne levels during certain operations in specific occupational settings. Aim of study: The study aimed to assess exposure to AFB1 in three settings: poultry, swine production and waste management.

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This Thesis describes the application of automatic learning methods for a) the classification of organic and metabolic reactions, and b) the mapping of Potential Energy Surfaces(PES). The classification of reactions was approached with two distinct methodologies: a representation of chemical reactions based on NMR data, and a representation of chemical reactions from the reaction equation based on the physico-chemical and topological features of chemical bonds. NMR-based classification of photochemical and enzymatic reactions. Photochemical and metabolic reactions were classified by Kohonen Self-Organizing Maps (Kohonen SOMs) and Random Forests (RFs) taking as input the difference between the 1H NMR spectra of the products and the reactants. The development of such a representation can be applied in automatic analysis of changes in the 1H NMR spectrum of a mixture and their interpretation in terms of the chemical reactions taking place. Examples of possible applications are the monitoring of reaction processes, evaluation of the stability of chemicals, or even the interpretation of metabonomic data. A Kohonen SOM trained with a data set of metabolic reactions catalysed by transferases was able to correctly classify 75% of an independent test set in terms of the EC number subclass. Random Forests improved the correct predictions to 79%. With photochemical reactions classified into 7 groups, an independent test set was classified with 86-93% accuracy. The data set of photochemical reactions was also used to simulate mixtures with two reactions occurring simultaneously. Kohonen SOMs and Feed-Forward Neural Networks (FFNNs) were trained to classify the reactions occurring in a mixture based on the 1H NMR spectra of the products and reactants. Kohonen SOMs allowed the correct assignment of 53-63% of the mixtures (in a test set). Counter-Propagation Neural Networks (CPNNs) gave origin to similar results. The use of supervised learning techniques allowed an improvement in the results. They were improved to 77% of correct assignments when an ensemble of ten FFNNs were used and to 80% when Random Forests were used. This study was performed with NMR data simulated from the molecular structure by the SPINUS program. In the design of one test set, simulated data was combined with experimental data. The results support the proposal of linking databases of chemical reactions to experimental or simulated NMR data for automatic classification of reactions and mixtures of reactions. Genome-scale classification of enzymatic reactions from their reaction equation. The MOLMAP descriptor relies on a Kohonen SOM that defines types of bonds on the basis of their physico-chemical and topological properties. The MOLMAP descriptor of a molecule represents the types of bonds available in that molecule. The MOLMAP descriptor of a reaction is defined as the difference between the MOLMAPs of the products and the reactants, and numerically encodes the pattern of bonds that are broken, changed, and made during a chemical reaction. The automatic perception of chemical similarities between metabolic reactions is required for a variety of applications ranging from the computer validation of classification systems, genome-scale reconstruction (or comparison) of metabolic pathways, to the classification of enzymatic mechanisms. Catalytic functions of proteins are generally described by the EC numbers that are simultaneously employed as identifiers of reactions, enzymes, and enzyme genes, thus linking metabolic and genomic information. Different methods should be available to automatically compare metabolic reactions and for the automatic assignment of EC numbers to reactions still not officially classified. In this study, the genome-scale data set of enzymatic reactions available in the KEGG database was encoded by the MOLMAP descriptors, and was submitted to Kohonen SOMs to compare the resulting map with the official EC number classification, to explore the possibility of predicting EC numbers from the reaction equation, and to assess the internal consistency of the EC classification at the class level. A general agreement with the EC classification was observed, i.e. a relationship between the similarity of MOLMAPs and the similarity of EC numbers. At the same time, MOLMAPs were able to discriminate between EC sub-subclasses. EC numbers could be assigned at the class, subclass, and sub-subclass levels with accuracies up to 92%, 80%, and 70% for independent test sets. The correspondence between chemical similarity of metabolic reactions and their MOLMAP descriptors was applied to the identification of a number of reactions mapped into the same neuron but belonging to different EC classes, which demonstrated the ability of the MOLMAP/SOM approach to verify the internal consistency of classifications in databases of metabolic reactions. RFs were also used to assign the four levels of the EC hierarchy from the reaction equation. EC numbers were correctly assigned in 95%, 90%, 85% and 86% of the cases (for independent test sets) at the class, subclass, sub-subclass and full EC number level,respectively. Experiments for the classification of reactions from the main reactants and products were performed with RFs - EC numbers were assigned at the class, subclass and sub-subclass level with accuracies of 78%, 74% and 63%, respectively. In the course of the experiments with metabolic reactions we suggested that the MOLMAP / SOM concept could be extended to the representation of other levels of metabolic information such as metabolic pathways. Following the MOLMAP idea, the pattern of neurons activated by the reactions of a metabolic pathway is a representation of the reactions involved in that pathway - a descriptor of the metabolic pathway. This reasoning enabled the comparison of different pathways, the automatic classification of pathways, and a classification of organisms based on their biochemical machinery. The three levels of classification (from bonds to metabolic pathways) allowed to map and perceive chemical similarities between metabolic pathways even for pathways of different types of metabolism and pathways that do not share similarities in terms of EC numbers. Mapping of PES by neural networks (NNs). In a first series of experiments, ensembles of Feed-Forward NNs (EnsFFNNs) and Associative Neural Networks (ASNNs) were trained to reproduce PES represented by the Lennard-Jones (LJ) analytical potential function. The accuracy of the method was assessed by comparing the results of molecular dynamics simulations (thermal, structural, and dynamic properties) obtained from the NNs-PES and from the LJ function. The results indicated that for LJ-type potentials, NNs can be trained to generate accurate PES to be used in molecular simulations. EnsFFNNs and ASNNs gave better results than single FFNNs. A remarkable ability of the NNs models to interpolate between distant curves and accurately reproduce potentials to be used in molecular simulations is shown. The purpose of the first study was to systematically analyse the accuracy of different NNs. Our main motivation, however, is reflected in the next study: the mapping of multidimensional PES by NNs to simulate, by Molecular Dynamics or Monte Carlo, the adsorption and self-assembly of solvated organic molecules on noble-metal electrodes. Indeed, for such complex and heterogeneous systems the development of suitable analytical functions that fit quantum mechanical interaction energies is a non-trivial or even impossible task. The data consisted of energy values, from Density Functional Theory (DFT) calculations, at different distances, for several molecular orientations and three electrode adsorption sites. The results indicate that NNs require a data set large enough to cover well the diversity of possible interaction sites, distances, and orientations. NNs trained with such data sets can perform equally well or even better than analytical functions. Therefore, they can be used in molecular simulations, particularly for the ethanol/Au (111) interface which is the case studied in the present Thesis. Once properly trained, the networks are able to produce, as output, any required number of energy points for accurate interpolations.