169 resultados para Biological pollution
Resumo:
Mutations in the TNF family ligand EDA1 cause X-linked hypohidrotic ectodermal dysplasia (XLHED), a condition characterized by defective development of skin appendages. The EDA1 protein displays a proteolytic processing site responsible for its conversion to a soluble form, a collagen domain, and a trimeric TNF homology domain (THD) that binds the receptor EDAR. In-frame deletions in the collagen domain reduced the thermal stability of EDA1. Removal of the collagen domain decreased its activity about 100-fold, as measured with natural and engineered EDA1-responsive cell lines. The collagen domain could be functionally replaced by multimerization domains or by cross-linking antibodies, suggesting that it functions as an oligomerization unit. Surprisingly, mature soluble EDA1 containing the collagen domain was poorly active when administered in newborn, EDA-deficient (Tabby) mice. This was due to a short stretch of basic amino acids located at the N terminus of the collagen domain that confers EDA1 with proteoglycan binding ability. In contrast to wild-type EDA1, EDA1 with mutations in this basic sequence was a potent inducer of tail hair development in vivo. Thus, the collagen domain activates EDA1 by multimerization, whereas the proteoglycan-binding domain may restrict the distribution of endogeneous EDA1 in vivo.
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AIM: Specific factors responsible for interindividual variability should be identified and their contribution quantified to improve the usefulness of biological monitoring. Among others, age is an easily identifiable determinant, which could play an important impact on biological variability. MATERIALS AND METHODS: A compartmental toxicokinetic model developed in previous studies for a series of metallic and organic compounds was applied to the description of age differences. Young male physiological and metabolic parameters, based on Reference Man information, were taken from preceding studies and were modified to take into account age based on available information about age differences. RESULTS: Numerical simulation using the kinetic model with the modified parameters indicates in some cases important differences due to age. The expected changes are mostly of the order of 10-20%, but differences up to 50% were observed in some cases. CONCLUSION: These differences appear to depend on the chemical and on the biological entity considered. Further work should be done to improve our estimates of these parameters, by considering for example uncertainty and variability in these parameters. [Authors]
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Smoking influences body weight such that smokers weigh less than non-smokers and smoking cessation often leads to weight increase. The relationship between body weight and smoking is partly explained by the effect of nicotine on appetite and metabolism. However, the brain reward system is involved in the control of the intake of both food and tobacco. We evaluated the effect of single-nucleotide polymorphisms (SNPs) affecting body mass index (BMI) on smoking behavior, and tested the 32 SNPs identified in a meta-analysis for association with two smoking phenotypes, smoking initiation (SI) and the number of cigarettes smoked per day (CPD) in an Icelandic sample (N=34,216 smokers). Combined according to their effect on BMI, the SNPs correlate with both SI (r=0.019, P=0.00054) and CPD (r=0.032, P=8.0 × 10(-7)). These findings replicate in a second large data set (N=127,274, thereof 76,242 smokers) for both SI (P=1.2 × 10(-5)) and CPD (P=9.3 × 10(-5)). Notably, the variant most strongly associated with BMI (rs1558902-A in FTO) did not associate with smoking behavior. The association with smoking behavior is not due to the effect of the SNPs on BMI. Our results strongly point to a common biological basis of the regulation of our appetite for tobacco and food, and thus the vulnerability to nicotine addiction and obesity.
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An exhaustive classification of matrix effects occurring when a sample preparation is performed prior to liquid-chromatography coupled to mass spectrometry (LC-MS) analyses was proposed. A total of eight different situations were identified allowing the recognition of the matrix effect typology via the calculation of four recovery values. A set of 198 compounds was used to evaluate matrix effects after solid phase extraction (SPE) from plasma or urine samples prior to LC-ESI-MS analysis. Matrix effect identification was achieved for all compounds and classified through an organization chart. Only 17% of the tested compounds did not present significant matrix effects.
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Astonishing as it may seem, one organism's waste is often ideal food for another. Many waste products generated by human activities are routinely degraded by microorganisms under controlled conditions during waste-water treatment. Toxic pollutants resulting from inadvertent releases, such as oil spills, are also consumed by bacteria, the simplest organisms on Earth. Biodegradation of toxic or particularly persistent compounds, however, remains problematic. What has escaped the attention of many is that bacteria exposed to pollutants can adapt to them by mutating or acquiring degradative genes. These bacteria can proliferate in the environment as a result of the selection pressures created by pollutants. The positive outcome of selection pressure is that harmful compounds may eventually be broken down completely through biodegradation. The downside is that biodegradation may require extremely long periods of time. Although the adaptation process has been shown to be reproducible, it remains very difficult to predict.
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Exposure to various pesticides has been characterized in workers and the general population, but interpretation and assessment of biomonitoring data from a health risk perspective remains an issue. For workers, a Biological Exposure Index (BEI®) has been proposed for some substances, but most BEIs are based on urinary biomarker concentrations at Threshold Limit Value - Time Weighted Average (TLV-TWA) airborne exposure while occupational exposure can potentially occurs through multiple routes, particularly by skin contact (i.e.captan, chlorpyrifos, malathion). Similarly, several biomonitoring studies have been conducted to assess environmental exposure to pesticides in different populations, but dose estimates or health risks related to these environmental exposures (mainly through the diet), were rarely characterized. Recently, biological reference values (BRVs) in the form of urinary pesticide metabolites have been proposed for both occupationally exposed workers and children. These BRVs were established using toxicokinetic models developed for each substance, and correspond to safe levels of absorption in humans, regardless of the exposure scenario. The purpose of this chapter is to present a review of a toxicokinetic modeling approach used to determine biological reference values. These are then used to facilitate health risk assessments and decision-making on occupational and environmental pesticide exposures. Such models have the ability to link absorbed dose of the parent compound to exposure biomarkers and critical biological effects. To obtain the safest BRVs for the studied population, simulations of exposure scenarios were performed using a conservative reference dose such as a no-observed-effect level (NOEL). The various examples discussed in this chapter show the importance of knowledge on urine collections (i.e. spot samples and complete 8-h, 12-h or 24-h collections), sampling strategies, metabolism, relative proportions of the different metabolites in urine, absorption fraction, route of exposure and background contribution of prior exposures. They also show that relying on urinary measurements of specific metabolites appears more accurate when applying this approach to the case of occupational exposures. Conversely, relying on semi-specific metabolites (metabolites common to a category of pesticides) appears more accurate for the health risk assessment of environmental exposures given that the precise pesticides to which subjects are exposed are often unknown. In conclusion, the modeling approach to define BRVs for the relevant pesticides may be useful for public health authorities for managing issues related to health risks resulting from environmental and occupational exposures to pesticides.
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Through genome-wide association meta-analyses of up to 133,010 individuals of European ancestry without diabetes, including individuals newly genotyped using the Metabochip, we have increased the number of confirmed loci influencing glycemic traits to 53, of which 33 also increase type 2 diabetes risk (q < 0.05). Loci influencing fasting insulin concentration showed association with lipid levels and fat distribution, suggesting impact on insulin resistance. Gene-based analyses identified further biologically plausible loci, suggesting that additional loci beyond those reaching genome-wide significance are likely to represent real associations. This conclusion is supported by an excess of directionally consistent and nominally significant signals between discovery and follow-up studies. Functional analysis of these newly discovered loci will further improve our understanding of glycemic control.
Biological embedding of early-life exposures and disease risk in humans : a role for DNA methylation
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BACKGROUND: Following wider acceptance of 'the thrifty phenotype' hypothesis and the convincing evidence that early-life exposures can influence adult health even decades after the exposure, much interest has been placed on the mechanisms through which early-life exposures become biologically embedded. MATERIALS AND METHODS: In this review, we summarize the current literature regarding biological embedding of early-life experiences. To this end, we conducted a literature search to identify studies investigating early-life exposures in relation to DNA methylation changes. In addition, we summarize the challenges faced in investigations of epigenetic effects, stemming from the peculiarities of this emergent and complex field. A proper systematic review and meta-analyses were not feasible given the nature of the evidence. RESULTS: We identified seven studies on early-life socio-economic circumstances, 10 studies on childhood obesity and six studies on early-life nutrition all relating to DNA methylation changes that met the stipulated inclusion criteria. The pool of evidence gathered, albeit small, favours a role of epigenetics and DNA methylation in biological embedding, but replication of findings, multiple comparison corrections, publication bias and causality are concerns remaining to be addressed in future investigations. CONCLUSIONS: Based on these results, we hypothesize that epigenetics, in particular DNA methylation, is a plausible mechanism through which early-life exposures are biologically embedded. This review describes the current status of the field and acts as a stepping stone for future, better designed investigations on how early-life exposures might become biologically embedded through epigenetic effects.
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Abstract This paper presents the outcomes from a workshop of the European Network on the Health and Environmental Impact of Nanomaterials (NanoImpactNet). During the workshop, 45 experts in the field of safety assessment of engineered nanomaterials addressed the need to systematically study sets of engineered nanomaterials with specific metrics to generate a data set which would allow the establishment of dose-response relations. The group concluded that international cooperation and worldwide standardization of terminology, reference materials and protocols are needed to make progress in establishing lists of essential metrics. High quality data necessitates the development of harmonized study approaches and adequate reporting of data. Priority metrics can only be based on well-characterized dose-response relations derived from the systematic study of the bio-kinetics and bio-interactions of nanomaterials at both organism and (sub)-cellular levels. In addition, increased effort is needed to develop and validate analytical methods to determine these metrics in a complex matrix.
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This study investigated the contribution of sources and establishment characteristics, on the exposure to fine particulate matter (PM(2.5)) in the non-smoking sections of bars, cafes, and restaurants in central Zurich. PM(2.5)-exposure was determined with a nephelometer. A random sample of hospitality establishments was investigated on all weekdays, from morning until midnight. Each visit lasted 30 min. Numbers of smokers and other sources, such as candles and cooking processes, were recorded, as were seats, open windows, and open doors. Ambient air pollution data were obtained from public authorities. Data were analysed using robust MM regression. Over 14 warm, sunny days, 102 establishments were measured. Average establishment PM(2.5) concentrations were 64.7 microg/m(3) (s.d. = 73.2 microg/m(3), 30-min maximum 452.2 microg/m(3)). PM(2.5) was significantly associated with the number of smokers, percentage of seats occupied by smokers, and outdoor PM. Each smoker increased PM(2.5) on average by 15 microg/m(3). No associations were found with other sources, open doors or open windows. Bars had more smoking guests and showed significantly higher concentrations than restaurants and cafes. Smokers were the most important PM(2.5)-source in hospitality establishments, while outdoor PM defined the baseline. Concentrations are expected to be even higher during colder, unpleasant times of the year. PRACTICAL IMPLICATIONS: Smokers and ambient air pollution are the most important sources of fine airborne particulate matter (PM(2.5)) in the non-smoking sections of bars, restaurants, and cafes. Other sources do not significantly contribute to PM(2.5)-levels, while opening doors and windows is not an efficient means of removing pollutants. First, this demonstrates the impact that even a few smokers can have in affecting particle levels. Second, it implies that creating non-smoking sections, and using natural ventilation, is not sufficient to bring PM(2.5) to levels that imply no harm for employees and non-smoking clients. [Authors]
Resumo:
Human biomonitoring is a widely used method in the assessment of occupational exposure to chemical substances and recommended biological limits are published periodically for interpretation and decision-making. However, it is increasingly recognized that a large variability is associated with biological monitoring, making interpretation less efficient than assumed. In order to improve the applicability of biological monitoring, specific factors responsible for this variability should be identified and their contribution quantified. Among these factors, age and sex are easily identifiable, and present knowledge about pharmaceutical chemicals suggests that they play an important role on the toxicokinetics of occupational chemical agents, and therefore on the biological monitoring results.The aim of the present research project was to assess the influence of age and sex on biological indicators corresponding to organic solvents. This has been done experimentally and by toxicokinetic computer simulation. Another purpose was to explore the effect of selected CYP2E1 polymorphisms on the toxicokinetic profile.Age differences were identified by numerical simulations using a general toxicokinetic model from a previous study which was applied to 14 chemicals, representing 21 specific biological entities, with, among others, toluene, phenol, lead and mercury. These models were runn with the modified parameters, indicating in some cases important differences due to age. The expected changes are mostly of the order of 10-20 %, but differences up to 50 % were observed in some cases. These differences appear to depend on the chemical and on the biological entity considered.Sex differences were quantified by controlled human exposures, which were carried out in a 12 m3 exposure chamber for three organic solvents separately: methyl ethyl ketone, 1-methoxy-2-propanol and 1,1,1-trichloroethane. The human volunteer groups were composed 12 of ten young men and fifteen young women, the latter subdivided into those with and without hormonal contraceptive. They were exposed during six hours at rest and at half of the threshold limit value. The kinetics of the parent compounds (organic volatiles) and their metabolite(s) were followed in blood, urine and expired air over time. Analyses of the solvent and their metabolites were performed by using headspace gas chromatography, CYP2E1 genotypes by using PCR-based RFLP methods. Experimental data were used to calibrate the toxicokinetic models developed for the three solvents. The results obtained for the different biomarkers of exposure mainly showed an effect on the urinary levels of several biomarkers among women due to the use of hormonal contraceptive, with an increase of about 50 % in the metabolism rate. The results also showed a difference due to the genotype CYP2E1*6, when exposed to methyl ethyl ketone, with a tendency to increase CYP2E1 activity when volunteers were carriers of the mutant allele. Simulations showed that it is possible to use simple toxicokinetic tools in order to predict internal exposure when exposed to organic solvents. Our study suggests that not only physiological differences but also exogenous sex hormones could influence CYP2E1 enzyme activity. The variability among the urinary biological indicators levels gives evidence of an interindividual susceptibility, an aspect that should have its place in the approaches for setting limits of occupational exposure.
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This second section of the first ECCO pathogenesis workshop on anti-TNF therapy failures in inflammatory bowel diseases addresses the biological roles of TNFα and the effects and mechanisms of action of TNFα antagonists. Mechanisms underlying their failure, including induction of TNF-independent inflammatory pathways and phenomena of paradoxical inflammation are discussed.
Resumo:
Compartmental and physiologically based toxicokinetic modeling coupled with Monte Carlo simulation were used to quantify the impact of biological variability (physiological, biochemical, and anatomic parameters) on the values of a series of bio-indicators of metal and organic industrial chemical exposures. A variability extent index and the main parameters affecting biological indicators were identified. Results show a large diversity in interindividual variability for the different categories of biological indicators examined. Measurement of the unchanged substance in blood, alveolar air, or urine is much less variable than the measurement of metabolites, both in blood and urine. In most cases, the alveolar flow and cardiac output were identified as the prime parameters determining biological variability, thus suggesting the importance of workload intensity on absorbed dose for inhaled chemicals.