968 resultados para Environmental sample
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Abstract: Traditionally, pollution risk assessment is based on the measurement of a pollutant's total concentration in a sample. The toxicity of a given pollutant in the environment, however, is tightly linked to its bioavailability, which may differ significantly from the total amount. Physico-chemical and biological parameters strongly influence pollutant fate in terms of leaching, sequestration and biodegradation. Bacterial sensorreporters, which consist of living micro-organisms genetically engineered to produce specific output in response to target chemicals, offer an interesting alternative to monitoring approaches. Bacterial sensor-reporters detect bioavailable and/or bioaccessible compound fractions in samples. Currently, a variety of environmental pollutants can be targeted by specific biosensor-reporters. Although most of such strains are still confined to the lab, several recent reports have demonstrated utility of bacterial sensing-reporting in the field, with method detection limits in the nanomolar range. This review illustrates the general design principles for bacterial sensor-reporters, presents an overview of the existing biosensor-reporter strains with emphasis on organic compound detection. A specific focus throughout is on the concepts of bioavailability and bioaccessibility, and how bacteria-based sensing-reporting systems can help to improve our basic understanding of the different processes at work.
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The aim of this study was to apply a molecular protocol to detect leptospiral DNA in environmental water samples. The study was carried out in a peri-urban settlement in Petrópolis, state of Rio de Janeiro. A multiplex PCR method employing the primers LipL32 and 16SrRNA was used. Three out of 100 analysed samples were positive in the multiplex PCR, two were considered to have saprophytic leptospires and one had pathogenic leptospires. The results obtained supported the idea that multiplex PCR can be used to detect Leptospira spp in water samples. This method was also able to differentiate between saprophytic and pathogenic leptospires and was able to do so much more easily than conventional methodologies.
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We explain the choice between franchising and vertical integration by estimating a model of relative performance in a sample of 250 Spanish car distributors, controlling for self-selection and including environmental factors. The method allows us to estimate performance counterfactuals. Organizational choice seemingly aims to contain moral hazard for both distributors and manufacturers but it is subject to start-up constraints and switching costs. While the market for franchises remained underdeveloped, information asymmetries led to the opening of integrated outlets. Their subsequent conversion into franchised outlets probably involved prohibitive transaction costs. Consequently, they performed worse than would have been expected had they been independent, as confirmed by the systematic improvement observed when they were in fact converted. The timing of such conversions suggests that switching costs were prohibitive until firms developed a substantial cushion of temporary contracts, previously forbidden by regulation.
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OBJECTIVETo compare the total sleep time of premature infant in the presence or absence of reducing sensory and environmental stimuli in the neonatal unit.METHODLongitudinal study in a Neonatal Intermediate Care Unit of a public hospital in Sao Paulo. The sample consisted of 13 premature infants. We used polysomnograph and unstructured observation for data collection. We analyzed 240 and 1200 minutes corresponding to the periods of the presence and absence of environmental management, respectively. Data were compared in proportion to the total sleep time in the two moments proposed by the study.RESULTSThe total sleep time in periods without environmental management was on average 696.4 (± 112.1) minutes and with management 168.5 (± 27.9) minutes, proportionally premature infant slept an average of 70.2% during periods with no intervention and 58.0% without management (p=0.002).CONCLUSIONReducing stimulation and handling of premature infant environment periods was effective to provide greater total sleep time.
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Structural equation models (SEM) are commonly used to analyze the relationship between variables some of which may be latent, such as individual ``attitude'' to and ``behavior'' concerning specific issues. A number of difficulties arise when we want to compare a large number of groups, each with large sample size, and the manifest variables are distinctly non-normally distributed. Using an specific data set, we evaluate the appropriateness of the following alternative SEM approaches: multiple group versus MIMIC models, continuous versus ordinal variables estimation methods, and normal theory versus non-normal estimation methods. The approaches are applied to the ISSP-1993 Environmental data set, with the purpose of exploring variation in the mean level of variables of ``attitude'' to and ``behavior''concerning environmental issues and their mutual relationship across countries. Issues of both theoretical and practical relevance arise in the course of this application.
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Nickel, although essential to plants, may be toxic to plants and animals. It is mainly assimilated by food ingestion. However, information about the average levels of elements (including Ni) in edible vegetables from different regions is still scarce in Brazil. The objectives of this study were to: (a) evaluate and optimize a method for preparation of vegetable tissue samples for Ni determination; (b) optimize the analytical procedures for determination by Flame Atomic Absorption Spectrometry (FAAS) and by Electrothermal Atomic Absorption (ETAAS) in vegetable samples and (c) determine the Ni concentration in vegetables consumed in the cities of Lorena and Taubaté in the Vale do Paraíba, State of São Paulo, Brazil. By means of the analytical technique for determination by ETAAS or FAAS, the results were validated by the test of analyte addition and recovery. The most viable method tested for quantification of this element was HClO4-HNO3 wet digestion. All samples but carrot tissue collected in Lorena contained Ni levels above the permitted by the Brazilian Ministry of Health. The most disturbing results, requiring more detailed studies, were the Ni concentrations measured in carrot samples from Taubaté, where levels were five times higher than permitted by Brazilian regulations.
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There is a great lack of information from soil surveys in the southern part of the State of Amazonas, Brazil. The use of tools such as geostatistics may improve environmental planning, use and management. In this study, we aimed to use scaled semivariograms in sample design of soil physical properties of some environments in Amazonas. We selected five areas located in the south of the state of Amazonas, Brazil, with varied soil uses, such as forest, archaeological dark earth (ADE), pasture, sugarcane cropping, and agroforestry. Regular mesh grids were set up in these areas with 64 sample points spaced at 10 m from each other. At these points, we determined the particle size composition, soil resistance to penetration, moisture, soil bulk density and particle density, macroporosity, microporosity, total porosity, and aggregate stability in water at a depth of 0.00-0.20 m. Descriptive and geostatistical analyses were performed. The sample density requirements were lower in the pasture area but higher in the forest. We concluded that managed-environments had differences in their soil physical properties compared to the natural forest; notably, the soil in the ADE environment is physically improved in relation to the others. The physical properties evaluated showed a structure of spatial dependence with a slight variability of the forest compared to the others. The use of the range parameter of the semivariogram analysis proved to be effective in determining an ideal sample density.
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Antibiotic resistance is an increasing global problem resulting from the pressure of antibiotic usage, greater mobility of the population, and industrialization. Many antibiotic resistance genes are believed to have originated in microorganisms in the environment, and to have been transferred to other bacteria through mobile genetic elements. Among others, ß-lactam antibiotics show clinical efficacy and low toxicity, and they are thus widely used as antimicrobials. Resistance to ß-lactam antibiotics is conferred by ß-lactamase genes and penicillin-binding proteins, which are chromosomal- or plasmid-encoded, although there is little information available on the contribution of other mobile genetic elements, such as phages. This study is focused on three genes that confer resistance to ß-lactam antibiotics, namely two ß-lactamase genes (blaTEM and blaCTX-M9) and one encoding a penicillin-binding protein (mecA) in bacteriophage DNA isolated from environmental water samples. The three genes were quantified in the DNA isolated from bacteriophages collected from 30 urban sewage and river water samples, using quantitative PCR amplification. All three genes were detected in the DNA of phages from all the samples tested, in some cases reaching 104 gene copies (GC) of blaTEM or 102 GC of blaCTX-M and mecA. These values are consistent with the amount of fecal pollution in the sample, except for mecA, which showed a higher number of copies in river water samples than in urban sewage. The bla genes from phage DNA were transferred by electroporation to sensitive host bacteria, which became resistant to ampicillin. blaTEM and blaCTX were detected in the DNA of the resistant clones after transfection. This study indicates that phages are reservoirs of resistance genes in the environment.
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Purpose (1) To identify work related stressors that are associated with psychiatric symptoms in a Swiss sample of policemen and (2) to develop a model for identifying officers at risk for developing mental health problems. Method The study design is cross sectional. A total of 354 male police officers answered a questionnaire assessing a wide spectrum of work related stressors. Psychiatric symptoms were assessed using the "TST questionnaire" (Langner in J Health Hum Behav 4, 269-276, 1962). Logistic regression with backward procedure was used to identify a set of variables collectively associated with high scores for psychiatric symptoms. Results A total of 42 (11.9%) officers had a high score for psychiatric symptoms. Nearly all potential stressors considered were significantly associated (at P < 0.05) with a high score for psychiatric symptoms. A significant model including 6 independent variables was identified: lack of support from superior and organization OR = 3.58 (1.58-8.13), self perception of bad quality work OR = 2.99 (1.35-6.59), inadequate work schedule OR = 2.84 (1.22-6.62), high mental/intellectual demand OR = 2.56 (1.12-5.86), age (in decades) OR = 1.82 (1.21-2.73), and score for physical environment complaints OR = 1.30 (1.03-1.64). Conclusions Most of work stressors considered are associated with psychiatric symptoms. Prevention should target the most frequent stressors with high association to symptoms. Complaints of police officers about stressors should receive proper consideration by the management of public administration. Such complaints might be the expression of psychiatric caseness requiring medical assistance. Particular attention should be given to police officers complaining about many stressors identified in this study's multiple model. [Authors]
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The book presents the state of the art in machine learning algorithms (artificial neural networks of different architectures, support vector machines, etc.) as applied to the classification and mapping of spatially distributed environmental data. Basic geostatistical algorithms are presented as well. New trends in machine learning and their application to spatial data are given, and real case studies based on environmental and pollution data are carried out. The book provides a CD-ROM with the Machine Learning Office software, including sample sets of data, that will allow both students and researchers to put the concepts rapidly to practice.
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BACKGROUND: Dried blood spots (DBS) sampling has gained popularity in the bioanalytical community as an alternative to conventional plasma sampling, as it provides numerous benefits in terms of sample collection and logistics. The aim of this work was to show that these advantages can be coupled with a simple and cost-effective sample pretreatment, with subsequent rapid LC-MS/MS analysis for quantitation of 15 benzodiazepines, six metabolites and three Z-drugs. For this purpose, a simplified offline procedure was developed that consisted of letting a 5-µl DBS infuse directly into 100 µl of MeOH, in a conventional LC vial. RESULTS: The parameters related to the DBS pretreatment, such as extraction time or internal standard addition, were investigated and optimized, demonstrating that passive infusion in a regular LC vial was sufficient to quantitatively extract the analytes of interest. The method was validated according to international criteria in the therapeutic concentration ranges of the selected compounds. CONCLUSION: The presented strategy proved to be efficient for the rapid analysis of the selected drugs. Indeed, the offline sample preparation was reduced to a minimum, using a small amount of organic solvent and consumables, without affecting the accuracy of the method. Thus, this approach enables simple and rapid DBS analysis, even when using a non-DBS-dedicated autosampler, while lowering the costs and environmental impact.
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Genetic variants influence the risk to develop certain diseases or give rise to differences in drug response. Recent progresses in cost-effective, high-throughput genome-wide techniques, such as microarrays measuring Single Nucleotide Polymorphisms (SNPs), have facilitated genotyping of large clinical and population cohorts. Combining the massive genotypic data with measurements of phenotypic traits allows for the determination of genetic differences that explain, at least in part, the phenotypic variations within a population. So far, models combining the most significant variants can only explain a small fraction of the variance, indicating the limitations of current models. In particular, researchers have only begun to address the possibility of interactions between genotypes and the environment. Elucidating the contributions of such interactions is a difficult task because of the large number of genetic as well as possible environmental factors.In this thesis, I worked on several projects within this context. My first and main project was the identification of possible SNP-environment interactions, where the phenotypes were serum lipid levels of patients from the Swiss HIV Cohort Study (SHCS) treated with antiretroviral therapy. Here the genotypes consisted of a limited set of SNPs in candidate genes relevant for lipid transport and metabolism. The environmental variables were the specific combinations of drugs given to each patient over the treatment period. My work explored bioinformatic and statistical approaches to relate patients' lipid responses to these SNPs, drugs and, importantly, their interactions. The goal of this project was to improve our understanding and to explore the possibility of predicting dyslipidemia, a well-known adverse drug reaction of antiretroviral therapy. Specifically, I quantified how much of the variance in lipid profiles could be explained by the host genetic variants, the administered drugs and SNP-drug interactions and assessed the predictive power of these features on lipid responses. Using cross-validation stratified by patients, we could not validate our hypothesis that models that select a subset of SNP-drug interactions in a principled way have better predictive power than the control models using "random" subsets. Nevertheless, all models tested containing SNP and/or drug terms, exhibited significant predictive power (as compared to a random predictor) and explained a sizable proportion of variance, in the patient stratified cross-validation context. Importantly, the model containing stepwise selected SNP terms showed higher capacity to predict triglyceride levels than a model containing randomly selected SNPs. Dyslipidemia is a complex trait for which many factors remain to be discovered, thus missing from the data, and possibly explaining the limitations of our analysis. In particular, the interactions of drugs with SNPs selected from the set of candidate genes likely have small effect sizes which we were unable to detect in a sample of the present size (<800 patients).In the second part of my thesis, I performed genome-wide association studies within the Cohorte Lausannoise (CoLaus). I have been involved in several international projects to identify SNPs that are associated with various traits, such as serum calcium, body mass index, two-hour glucose levels, as well as metabolic syndrome and its components. These phenotypes are all related to major human health issues, such as cardiovascular disease. I applied statistical methods to detect new variants associated with these phenotypes, contributing to the identification of new genetic loci that may lead to new insights into the genetic basis of these traits. This kind of research will lead to a better understanding of the mechanisms underlying these pathologies, a better evaluation of disease risk, the identification of new therapeutic leads and may ultimately lead to the realization of "personalized" medicine.
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Recently, three new polyomaviruses (KI, WU and Merkel cell polyomavirus) have been reported to infect humans. It has also been suggested that lymphotropic polyomavirus, a virus of simian origin, infects humans. KI and WU polyomaviruses have been detected mainly in specimens from the respiratory tract while Merkel cell polyomavirus has been described in a very high percentage of Merkel cell carcinomas. The distribution, excretion level and transmission routes of these viruses remain unknown. Here we analyzed the presence and characteristics of newly described human polyomaviruses in urban sewage and river water in order to assess the excretion level and the potential role of water as a route of transmission of these viruses. Nested-PCR assays were designed for the sensitive detection of the viruses studied and the amplicons obtained were confirmed by sequencing analysis. The viruses were concentrated following a methodology previously developed for the detection of JC and BK human polyomaviruses in environmental samples. JC polyomavirus and human adenoviruses were used as markers of human contamination in the samples. Merkel cell polyomavirus was detected in 7/8 urban sewage samples collected and in 2/7 river water samples. Also one urine sample from a pregnant woman, out of 4 samples analyzed, was positive for this virus. KI and WU polyomaviruses were identified in 1/8 and 2/8 sewage samples respectively. The viral strains detected were highly homologous with other strains reported from several other geographical areas. Lymphotropic polyomavirus was not detected in any of the 13 sewage neither in 9 biosolid/sludge samples analyzed. This is the first description of a virus isolated from sewage and river water with a strong association with cancer. Our data indicate that the Merkel cell polyomavirus is prevalent in the population and that it may be disseminated through the fecal/urine contamination of water. The procedure developed may constitute a useful tool for studying the excreted strains, prevalence and transmission of these recently described polyomaviruses.
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Ultra-trace amounts of Cu(II) were separated and preconcentrated by solid phase extraction on octadecyl-bonded silica membrane disks modified with a new Schiff,s base (Bis- (2-Hydroxyacetophenone) -2,2-dimethyl-1,3-propanediimine) (SBTD) followed by elution and inductively coupled plasma atomic emission spectrometric detection. The method was applied as a separation and detection method for copper(II) in environmental and biological samples. Extraction efficiency and the influence of sample matrix, flow rate, pH, and type and minimum amount of stripping acid were investigated. The concentration factor and detection limit of the proposed method are 500 and 12.5 pg mL-1, respectively.