31 resultados para Linear alkylation benzene

em Université de Lausanne, Switzerland


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Studies evaluating the mechanical behavior of the trabecular microstructure play an important role in our understanding of pathologies such as osteoporosis, and in increasing our understanding of bone fracture and bone adaptation. Understanding of such behavior in bone is important for predicting and providing early treatment of fractures. The objective of this study is to present a numerical model for studying the initiation and accumulation of trabecular bone microdamage in both the pre- and post-yield regions. A sub-region of human vertebral trabecular bone was analyzed using a uniformly loaded anatomically accurate microstructural three-dimensional finite element model. The evolution of trabecular bone microdamage was governed using a non-linear, modulus reduction, perfect damage approach derived from a generalized plasticity stress-strain law. The model introduced in this paper establishes a history of microdamage evolution in both the pre- and post-yield regions

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Characterize ethylbenzene and xylene air concentrations, and explore the biological exposure markers (urinary t,t-muconic acid (t,t-MA) and unmetabolized toluene) among petroleum workers offshore. Offshore workers have increased health risks due to simultaneous exposures to several hydrocarbons present in crude oil. We discuss the pooled benzene exposure results from our previous and current studies and possible co-exposure interactions. BTEX air concentrations were measured during three consecutive 12-h work shifts among 10 tank workers, 15 process operators, and 18 controls. Biological samples were collected pre-shift on the first day of study and post-shift on the third day of the study. The geometric mean exposure over the three work shifts were 0.02 ppm benzene, 0.05 ppm toluene, 0.03 ppm ethylbenzene, and 0.06 ppm xylene. Benzene in air was significantly correlated with unmetabolized benzene in blood (r = 0.69, p < 0.001) and urine (r = 0.64, p < 0.001), but not with urinary t,t-MA (r = 0.27, p = 0.20). Toluene in air was highly correlated with the internal dose of toluene in both blood (r = 0.70, p < 0.001) and urine (r = 0.73, p < 0.001). Co-exposures were present; however, an interaction of metabolism was not likely at these low benzene and toluene exposures. Urinary benzene, but not t,t-MA, was a reliable biomarker for benzene at low exposure levels. Urinary toluene was a useful biomarker for toluene exposure. Xylene and ethylbenzene air levels were low. Dermal exposure assessment needs to be performed in future studies among these workers.

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PURPOSE: To determine the local control and complication rates for children with papillary and/or macular retinoblastoma progressing after chemotherapy and undergoing stereotactic radiotherapy (SRT) with a micromultileaf collimator. METHODS AND MATERIALS: Between 2004 and 2008, 11 children (15 eyes) with macular and/or papillary retinoblastoma were treated with SRT. The mean age was 19 months (range, 2-111). Of the 15 eyes, 7, 6, and 2 were classified as International Classification of Intraocular Retinoblastoma Group B, C, and E, respectively. The delivered dose of SRT was 50.4 Gy in 28 fractions using a dedicated micromultileaf collimator linear accelerator. RESULTS: The median follow-up was 20 months (range, 13-39). Local control was achieved in 13 eyes (87%). The actuarial 1- and 2-year local control rates were both 82%. SRT was well tolerated. Late adverse events were reported in 4 patients. Of the 4 patients, 2 had developed focal microangiopathy 20 months after SRT; 1 had developed a transient recurrence of retinal detachment; and 1 had developed bilateral cataracts. No optic neuropathy was observed. CONCLUSIONS: Linear accelerator-based SRT for papillary and/or macular retinoblastoma in children resulted in excellent tumor control rates with acceptable toxicity. Additional research regarding SRT and its intrinsic organ-at-risk sparing capability is justified in the framework of prospective trials.

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Significant progress has been made with regard to the quantitative integration of geophysical and hydrological data at the local scale. However, extending the corresponding approaches to the scale of a field site represents a major, and as-of-yet largely unresolved, challenge. To address this problem, we have developed downscaling procedure based on a non-linear Bayesian sequential simulation approach. The main objective of this algorithm is to estimate the value of the sparsely sampled hydraulic conductivity at non-sampled locations based on its relation to the electrical conductivity logged at collocated wells and surface resistivity measurements, which are available throughout the studied site. The in situ relationship between the hydraulic and electrical conductivities is described through a non-parametric multivariatekernel density function. Then a stochastic integration of low-resolution, large-scale electrical resistivity tomography (ERT) data in combination with high-resolution, local-scale downhole measurements of the hydraulic and electrical conductivities is applied. The overall viability of this downscaling approach is tested and validated by comparing flow and transport simulation through the original and the upscaled hydraulic conductivity fields. Our results indicate that the proposed procedure allows obtaining remarkably faithful estimates of the regional-scale hydraulic conductivity structure and correspondingly reliable predictions of the transport characteristics over relatively long distances.

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Solid phase microextraction (SPME) has been widely used for many years in various applications, such as environmental and water samples, food and fragrance analysis, or biological fluids. The aim of this study was to suggest the SPME method as an alternative to conventional techniques used in the evaluation of worker exposure to benzene, toluene, ethylbenzene, and xylene (BTEX). Polymethylsiloxane-carboxen (PDMS/CAR) showed as the most effective stationary phase material for sorbing BTEX among other materials (polyacrylate, PDMS, PDMS/divinylbenzene, Carbowax/divinylbenzene). Various experimental conditions were studied to apply SPME to BTEX quantitation in field situations. The uptake rate of the selected fiber (75 microm PDMS/CAR) was determined for each analyte at various concentrations, relative humidities, and airflow velocities from static (calm air) to dynamic (> 200 cm/s) conditions. The SPME method also was compared with the National Institute of Occupational Safety and Health method 1501. Unlike the latter, the SPME approach fulfills the new requirement for the threshold limit value-short term exposure limit (TLV-STEL) of 2.5 ppm for benzene (8 mg/m(3))

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BACKGROUND: We sought to improve upon previously published statistical modeling strategies for binary classification of dyslipidemia for general population screening purposes based on the waist-to-hip circumference ratio and body mass index anthropometric measurements. METHODS: Study subjects were participants in WHO-MONICA population-based surveys conducted in two Swiss regions. Outcome variables were based on the total serum cholesterol to high density lipoprotein cholesterol ratio. The other potential predictor variables were gender, age, current cigarette smoking, and hypertension. The models investigated were: (i) linear regression; (ii) logistic classification; (iii) regression trees; (iv) classification trees (iii and iv are collectively known as "CART"). Binary classification performance of the region-specific models was externally validated by classifying the subjects from the other region. RESULTS: Waist-to-hip circumference ratio and body mass index remained modest predictors of dyslipidemia. Correct classification rates for all models were 60-80%, with marked gender differences. Gender-specific models provided only small gains in classification. The external validations provided assurance about the stability of the models. CONCLUSIONS: There were no striking differences between either the algebraic (i, ii) vs. non-algebraic (iii, iv), or the regression (i, iii) vs. classification (ii, iv) modeling approaches. Anticipated advantages of the CART vs. simple additive linear and logistic models were less than expected in this particular application with a relatively small set of predictor variables. CART models may be more useful when considering main effects and interactions between larger sets of predictor variables.

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Petroleum hydrocarbons are common contaminants in marine and freshwater aquatic habitats, often occurring as a result of oil spillage. Rapid and reliable on-site tools for measuring the bioavailable hydrocarbon fractions, i.e., those that are most likely to cause toxic effects or are available for biodegradation, would assist in assessing potential ecological damage and following the progress of cleanup operations. Here we examined the suitability of a set of different rapid bioassays (2-3 h) using bacteria expressing the LuxAB luciferase to measure the presence of short-chain linear alkanes, monoaromatic and polyaromatic compounds, biphenyls, and DNA-damaging agents in seawater after a laboratory-scale oil spill. Five independent spills of 20 mL of NSO-1 crude oil with 2 L of seawater (North Sea or Mediterranean Sea) were carried out in 5 L glass flasks for periods of up to 10 days. Bioassays readily detected ephemeral concentrations of short-chain alkanes and BTEX (i.e., benzene, toluene, ethylbenzene, and xylenes) in the seawater within minutes to hours after the spill, increasing to a maximum of up to 80 muM within 6-24 h, after which they decreased to low or undetectable levels. The strong decrease in short-chain alkanes and BTEX may have been due to their volatilization or biodegradation, which was supported by changes in the microbial community composition. Two- and three-ring PAHs appeared in the seawater phase after 24 h with a concentration up to 1 muM naphthalene equivalents and remained above 0.5 muM for the duration of the experiment. DNA-damage-sensitive bioreporters did not produce any signal with the oil-spilled aqueous-phase samples, whereas bioassays for (hydroxy)biphenyls showed occasional responses. Chemical analysis for alkanes and PAHs in contaminated seawater samples supported the bioassay data, but did not show the typical ephemeral peaks observed with the bioassays. We conclude that bacterium-based bioassays can be a suitable alternative for rapid on-site quantitative measurement of hydrocarbons in seawater.

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Knowledge of the genetic structure of plant populations is necessary for the understanding of the dynamics of major ecological processes. It also has applications in conservation biology and risk assessment for genetically modified crops. This paper reports the genetic structure of a linear population of sea beet, Beta vulgaris ssp. maritima (the wild relative of sugar beet), on Furzey Island, Poole Harbour. The relative spatial positions of the plants were accurately mapped and the plants were scored for variation at isozyme and RFLP loci. Structure was analysed by repeated subdivision of the population to find the average size of a randomly mating group. Estimates of F-ST between randomly mating units were then made, and gave patterns consistent with the structure of the population being determined largely by founder effects. The implications of these results for the monitoring of transgene spread in wild sea beet populations are discussed.

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An important statistical development of the last 30 years has been the advance in regression analysis provided by generalized linear models (GLMs) and generalized additive models (GAMs). Here we introduce a series of papers prepared within the framework of an international workshop entitled: Advances in GLMs/GAMs modeling: from species distribution to environmental management, held in Riederalp, Switzerland, 6-11 August 2001.We first discuss some general uses of statistical models in ecology, as well as provide a short review of several key examples of the use of GLMs and GAMs in ecological modeling efforts. We next present an overview of GLMs and GAMs, and discuss some of their related statistics used for predictor selection, model diagnostics, and evaluation. Included is a discussion of several new approaches applicable to GLMs and GAMs, such as ridge regression, an alternative to stepwise selection of predictors, and methods for the identification of interactions by a combined use of regression trees and several other approaches. We close with an overview of the papers and how we feel they advance our understanding of their application to ecological modeling.