Acute respiratory syndrome after inhalation of waterproofing sprays: a posteriori exposure-response assessment in 102 cases

Waterproofing agents are widely used to protect leather and textiles in both domestic and occupational activities. An outbreak of acute respiratory syndrome following exposure to waterproofing sprays occurred during the winter 2002-2003 in Switzerland. About 180 cases were reported by the Swiss Toxicological Information Centre between October 2002 and March 2003, whereas fewer than 10 cases per year had been recorded previously. The reported cases involved three brands of sprays containing a common waterproofing mixture, that had undergone a formulation change in the months preceding the outbreak. A retrospective analysis was undertaken in collaboration with the Swiss Toxicological Information Centre and the Swiss Registries for Interstitial and Orphan Lung Diseases to clarify the circumstances and possible causes of the observed health effects. Individual exposure data were generated with questionnaires and experimental emission measurements. The collected data was used to conduct numeric simulation for 102 cases of exposure. A classical two-zone model was used to assess the aerosol dispersion in the near- and far-field during spraying. The resulting assessed dose and exposure levels obtained were spread on large scales, of several orders of magnitude. No dose-response relationship was found between exposure indicators and health effects indicators (perceived severity and clinical indicators). Weak relationships were found between unspecific inflammatory response indicators (leukocytes, C-reactive protein) and the maximal exposure concentration. The results obtained disclose a high interindividual response variability and suggest that some indirect mechanism(s) predominates in the respiratory disease occurrence. Furthermore, no threshold could be found to define a safe level of exposure. These findings suggest that the improvement of environmental exposure conditions during spraying alone does not constitute a sufficient measure to prevent future outbreaks of waterproofing spray toxicity. More efficient preventive measures are needed prior to the marketing and distribution of new waterproofing agents.

The Importance of Scale for Spatial-confounding Bias and Precision of Spatial Regression Estimators

Increasingly, regression models are used when residuals are spatially correlated. Prominent examples include studies in environmental epidemiology to understand the chronic health effects of pollutants. I consider the effects of residual spatial structure on the bias and precision of regression coefficients, developing a simple framework in which to understand the key issues and derive informative analytic results. When the spatial residual is induced by an unmeasured confounder, regression models with spatial random effects and closely-related models such as kriging and penalized splines are biased, even when the residual variance components are known. Analytic and simulation results show how the bias depends on the spatial scales of the covariate and the residual; bias is reduced only when there is variation in the covariate at a scale smaller than the scale of the unmeasured confounding. I also discuss how the scales of the residual and the covariate affect efficiency and uncertainty estimation when the residuals can be considered independent of the covariate. In an application on the association between black carbon particulate matter air pollution and birth weight, controlling for large-scale spatial variation appears to reduce bias from unmeasured confounders, while increasing uncertainty in the estimated pollution effect.

Practical Large-Scale Spatio-Temporal Modeling of Particulate Matter Concentrations

The last two decades have seen intense scientific and regulatory interest in the health effects of particulate matter (PM). Influential epidemiological studies that characterize chronic exposure of individuals rely on monitoring data that are sparse in space and time, so they often assign the same exposure to participants in large geographic areas and across time. We estimate monthly PM during 1988-2002 in a large spatial domain for use in studying health effects in the Nurses' Health Study. We develop a conceptually simple spatio-temporal model that uses a rich set of covariates. The model is used to estimate concentrations of PM10 for the full time period and PM2.5 for a subset of the period. For the earlier part of the period, 1988-1998, few PM2.5 monitors were operating, so we develop a simple extension to the model that represents PM2.5 conditionally on PM10 model predictions. In the epidemiological analysis, model predictions of PM10 are more strongly associated with health effects than when using simpler approaches to estimate exposure. Our modeling approach supports the application in estimating both fine-scale and large-scale spatial heterogeneity and capturing space-time interaction through the use of monthly-varying spatial surfaces. At the same time, the model is computationally feasible, implementable with standard software, and readily understandable to the scientific audience. Despite simplifying assumptions, the model has good predictive performance and uncertainty characterization.

A BAYESIAN HIERARCHICAL MODEL FOR CONSTRAINED DISTRIBUTED LAG FUNCTIONS: ESTIMATING THE TIME COURSE OF HOSPITALIZATION ASSOCIATED WITH AIR POLLUTION EXPOSURE

Numerous time series studies have provided strong evidence of an association between increased levels of ambient air pollution and increased levels of hospital admissions, typically at 0, 1, or 2 days after an air pollution episode. An important research aim is to extend existing statistical models so that a more detailed understanding of the time course of hospitalization after exposure to air pollution can be obtained. Information about this time course, combined with prior knowledge about biological mechanisms, could provide the basis for hypotheses concerning the mechanism by which air pollution causes disease. Previous studies have identified two important methodological questions: (1) How can we estimate the shape of the distributed lag between increased air pollution exposure and increased mortality or morbidity? and (2) How should we estimate the cumulative population health risk from short-term exposure to air pollution? Distributed lag models are appropriate tools for estimating air pollution health effects that may be spread over several days. However, estimation for distributed lag models in air pollution and health applications is hampered by the substantial noise in the data and the inherently weak signal that is the target of investigation. We introduce an hierarchical Bayesian distributed lag model that incorporates prior information about the time course of pollution effects and combines information across multiple locations. The model has a connection to penalized spline smoothing using a special type of penalty matrix. We apply the model to estimating the distributed lag between exposure to particulate matter air pollution and hospitalization for cardiovascular and respiratory disease using data from a large United States air pollution and hospitalization database of Medicare enrollees in 94 counties covering the years 1999-2002.

How reliable and robust are current biomarkers for copper status?

Cu is an essential nutrient for man, but can be toxic if intakes are too high. In sensitive populations, marginal over- or under-exposure can have detrimental effects. Malnourished children, the elderly, and pregnant or lactating females may be susceptible for Cu deficiency. Cu status and exposure in the population can currently not be easily measured, as neither plasma Cu nor plasma cuproenzymes reflect Cu status precisely. Some blood markers (such as ceruloplasmin) indicate severe Cu depletion, but do not inversely respond to Cu excess, and are not suitable to indicate marginal states. A biomarker of Cu is needed that is sensitive to small changes in Cu status, and that responds to Cu excess as well as deficiency. Such a marker will aid in monitoring Cu status in large populations, and will help to avoid chronic health effects (for example, liver damage in chronic toxicity, osteoporosis, loss of collagen stability, or increased susceptibility to infections in deficiency). The advent of high-throughput technologies has enabled us to screen for potential biomarkers in the whole proteome of a cell, not excluding markers that have no direct link to Cu. Further, this screening allows us to search for a whole group of proteins that, in combination, reflect Cu status. The present review emphasises the need to find sensitive biomarkers for Cu, examines potential markers of Cu status already available, and discusses methods to identify a novel suite of biomarkers.

Interactions of nanoparticles with pulmonary structures and cellular responses

Combustion-derived and synthetic nano-sized particles (NSP) have gained considerable interest among pulmonary researchers and clinicians for two main reasons: 1) Inhalation exposure to combustion-derived NSP was associated with increased pulmonary and cardiovascular morbidity and mortality as suggested by epidemiological studies. Experimental evidence has provided a mechanistic picture of the adverse health effects associated with inhalation of combustion-derived and synthetic NSP. 2) The toxicological potential of NSP contrasts with the potential application of synthetic NSP in technological as well as medicinal settings with the latter including the use of NSP as diagnostics or therapeutics. In order to shed light on this paradox, this article aims to highlight recent findings about the interaction of inhaled NSP with the structures of the respiratory tract including surfactant and alveolar macrophages and epithelial cells. Cellular responses to NSP exposure include the generation of reactive oxygen species and the induction of an inflammatory response. Furthermore, this review places special emphasis on methodological differences between experimental studies and the caveats associated with the dose metrics and points out ways to overcome inherent methodological problems. Key words: electron tomography, surfactant, translocation, oxidative stress, inflammation.

A newly developed in vitro model of the human epithelial airway barrier to study the toxic potential of nanoparticles

The potential health effects of inhaled engineered nanoparticles are almost unknown. To avoid and replace toxicity studies with animals, a triple cell co-culture system composed of epithelial cells, macrophages and dendritic cells was established, which simulates the most important barrier functions of the epithelial airway. Using this model, the toxic potential of titanium dioxide was assessed by measuring the production of reactive oxygen species and the release of tumour necrosis factor alpha. The intracellular localisation of titanium dioxide nanoparticles was analyzed by energy filtering transmission electron microscopy. Titanium dioxide nanoparticles were detected as single particles without membranes and in membrane-bound agglomerates. Cells incubated with titanium dioxide particles showed an elevated production of reactive oxygen species but no increase of the release of tumour necrosis factor alpha. Our in vitro model of the epithelial airway barrier offers a valuable tool to study the interaction of particles with lung cells at a nanostructural level and to investigate the toxic potential of nanoparticles.

In vitro models of the human epithelial airway barrier to study the toxic potential of particulate matter

BACKGROUND: Several epidemiological studies show that inhalation of particulate matter may cause increased pulmonary morbidity and mortality. Of particular interest are the ultrafine particles that are particularly toxic. In addition more and more nanoparticles are released into the environment; however, the potential health effects of these nanoparticles are yet unknown. OBJECTIVES: To avoid particle toxicity studies with animals many cell culture models have been developed during the past years. METHODS: This review focuses on the most commonly used in vitro epithelial airway and alveolar models to study particle-cell interactions and particle toxicity and highlights advantages and disadvantages of the different models. RESULTS/CONCLUSION: There are many lung cell culture models but none of these models seems to be perfect. However, they might be a great tool to perform basic research or toxicity tests. The focus here is on 3D and co-culture models, which seem to be more realistic than monocultures.

Fish contaminants through the tribal perspective : an ethnography of the Keweenaw Bay Indian Community's tribal fish harvest

It has been well documented that many tribal populations and minority groups across the nation have been identified as being at high risk of the adverse health effects created by consuming fish that have been contaminated with mercury, PCBs, DDT, dioxins, and other chemicals. Although fish consumption advisories are intended to inform fish consumers of risks associated with specific species and water bodies, advisories have been the subject of both environmental injustices and treaty rights’ injustices. This means that understanding fish contaminants, through community perspectives is essential to good environmental policy. This study examined the fish contaminant knowledge, impacts on fishing and fish consumption, and the factors that contribute to harvesting decisions and behaviors in one tribal nation in the Upper Peninsula of Michigan, the Keweenaw Bay Indian Community. Using ethnographic methods, participant observation and semi-structured interviewing, fieldnotes were kept and all interviews were fully transcribed for data analysis. Among seventeen fishermen and women, contaminants are poorly understood, have had a limited impact on subsistence fishing but have had a substantial impact on commercial fishing activity. But ultimately, all decisions and behaviors are based on their own criteria and within a larger context of knowledge and understanding: the historical and cultural context. The historical context revealed that advisories are viewed as another attack on tribal fishing. The cultural context revealed that it is the fundamental guidance and essential framework associated with all harvesting beliefs, values, and traditional lifeways. These results have implications for advisories. ‘Fish’ and ‘contaminants’ appear differently based on the perceptions and priorities of those who encounter them.

Radiation metabolomics. 1. Identification of minimally invasive urine biomarkers for gamma-radiation exposure in mice

Gamma-radiation exposure has both short- and long-term adverse health effects. The threat of modern terrorism places human populations at risk for radiological exposures, yet current medical countermeasures to radiation exposure are limited. Here we describe metabolomics for gamma-radiation biodosimetry in a mouse model. Mice were gamma-irradiated at doses of 0, 3 and 8 Gy (2.57 Gy/min), and urine samples collected over the first 24 h after exposure were analyzed by ultra-performance liquid chromatography-time-of-flight mass spectrometry (UPLC-TOFMS). Multivariate data were analyzed by orthogonal partial least squares (OPLS). Both 3- and 8-Gy exposures yielded distinct urine metabolomic phenotypes. The top 22 ions for 3 and 8 Gy were analyzed further, including tandem mass spectrometric comparison with authentic standards, revealing that N-hexanoylglycine and beta-thymidine are urinary biomarkers of exposure to 3 and 8 Gy, 3-hydroxy-2-methylbenzoic acid 3-O-sulfate is elevated in urine of mice exposed to 3 but not 8 Gy, and taurine is elevated after 8 but not 3 Gy. Gene Expression Dynamics Inspector (GEDI) self-organizing maps showed clear dose-response relationships for subsets of the urine metabolome. This approach is useful for identifying mice exposed to gamma radiation and for developing metabolomic strategies for noninvasive radiation biodosimetry in humans.

Impact of environmental estrogens on Yfish considering the diversity of estrogen signaling.

Research on endocrine disruption in fish has been dominated by studies on estrogen-active compounds which act as mimics of the natural estrogen, 17β-estradiol (E2), and generally exert their biological actions by binding to and activation of estrogen receptors (ERs). Estrogens play central roles in reproductive physiology and regulate (female) sexual differentiation. In line with this, most adverse effects reported for fish exposed to environmental estrogens relate to sexual differentiation and reproduction. E2, however, utilizes a variety of signaling mechanisms, has multifaceted functions and targets, and therefore the toxicological and ecological effects of environmental estrogens in fish will extend beyond those associated with the reproduction. This review first describes the diversity of estrogen receptor signaling in fish, including both genomic and non-genomic mechanisms, and receptor crosstalk. It then considers the range of non-reproductive physiological processes in fish that are known to be responsive to estrogens, including sensory systems, the brain, the immune system, growth, specifically through the growth hormone/insulin-like growth factor system, and osmoregulation. The diversity in estrogen responses between fish species is then addressed, framed within evolutionary and ecological contexts, and we make assessments on their relevance for toxicological sensitivity as well as ecological vulnerability. The diversity of estrogen actions raises questions whether current risk assessment strategies, which focus on reproductive endpoints, and a few model fish species only, are protective of the wider potential health effects of estrogens. Available - although limited - evidence nevertheless suggests that quantitative environmental threshold concentrations for environmental protection derived from reproductive tests with model fish species are protective for non-reproductive effects as well. The diversity of actions of estrogens across divergent physiological systems, however, may lead to and underestimation of impacts on fish populations as their effects are generally considered on one functional process only and this may underrepresent the impact on the different physiological processes collectively.

Responses of lung cells to realistic exposure of primary and aged carbonaceous aerosols

Diesel exhaust and wood burning are important sources of ambient atmospheric particles due to increasing numbers of diesel cars and the importance of wood as a source of renewable energy. Inhalation is the predominant route of entry and uptake for fine and ultrafine particles into the body. Health effects of atmospheric particles are still not completely understood. There is consistent evidence from epidemiology that particle exposure contributes to respiratory and cardiovascular diseases. This study aimed at examining acute responses of airway epithelial cells and luminal macrophages after exposure to freshly emitted and photochemically aged carbonaceous aerosols under realistic atmospheric conditions. In addition to a bronchial epithelial cell line advanced cell cultures namely fully differentiated respiratory epithelia and primary surface macrophages were used. Our results demonstrate that a single exposure of the cells to realistic particle doses of 0.3–3 ng diesel or 3–9 ng wood aerosol per cm2 cell surface induces small, particle-specific responses. The release of interleukin-6 and -8 was found to be decreased in differentiated airway epithelia but not in the other cell models studied. Aerosol exposure decreased macrophage phagocytic activity by 45–90%. Cell and tissue integrity remained unaffected. Overall, primary and aged particles from the same combustion induced similar responses in the cell models tested, whereby particles from diesel exhaust affected the cells more than those from wood combustion.

Biokinetics of nanoparticles and susceptibility to particulate exposure in a murine model of cystic fibrosis.

BACKGROUND Persons with cystic fibrosis (CF) are at-risk for health effects from ambient air pollution but little is known about the interaction of nanoparticles (NP) with CF lungs. Here we study the distribution of inhaled NP in a murine CF model and aim to reveal mechanisms contributing to adverse effects of inhaled particles in susceptible populations. METHODS Chloride channel defective CftrTgH (neoim) Hgu mice were used to analyze lung function, lung distribution and whole body biokinetics of inhaled NP, and inflammatory responses after intratracheal administration of NP. Distribution of 20-nm titanium dioxide NP in lungs was assessed on ultrathin sections immediately and 24 h after a one-hour NP inhalation. NP biokinetics was deduced from total and regional lung deposition and from whole body translocation of inhaled 30-nm iridium NP within 24 h after aerosol inhalation. Inflammatory responses were assessed within 7 days after carbon NP instillation. RESULTS Cftr mutant females had moderately reduced lung compliance and slightly increased airway resistance compared to wild type mice. We found no genotype dependent differences in total, regional and head deposition or in secondary-organ translocation of inhaled iridium NP. Titanium dioxide inhalation resulted in higher NP uptake by alveolar epithelial cells in Cftr mutants. Instillation of carbon NP induced a comparable acute and transient inflammatory response in both genotypes. The twofold increase of bronchoalveolar lavage (BAL) neutrophils in Cftr mutant compared to wild type mice at day 3 but not at days 1 and 7, indicated an impaired capacity in inflammation resolution in Cftr mutants. Concomitant to the delayed decline of neutrophils, BAL granulocyte-colony stimulating factor was augmented in Cftr mutant mice. Anti-inflammatory 15-hydroxyeicosatetraenoic acid was generally significantly lower in BAL of Cftr mutant than in wild type mice. CONCLUSIONS Despite lacking alterations in lung deposition and biokinetics of inhaled NP, and absence of significant differences in lung function, higher uptake of NP by alveolar epithelial cells and prolonged, acute inflammatory responses to NP exposure indicate a moderately increased susceptibility of lungs to adverse effects of inhaled NP in Cftr mutant mice and provides potential mechanisms for the increased susceptibility of CF patients to air pollution.

Toxicity of aged gasoline exhaust particles to normal and diseased airway epithelia

Particulate matter (PM) pollution is a leading cause of premature death, particularly in those with pre-existing lung disease. A causative link between particle properties and adverse health effects remains unestablished mainly due to complex and variable physico-chemical PM parameters. Controlled laboratory experiments are required. Generating atmospherically realistic Aerosols and performing cell-exposure studies at relevant particle-doses are challenging. Here we examine gasoline-exhaust particle toxicity from a Euro-5 passenger car in a uniquely realistic exposure scenario, combining a smog chamber simulating atmospheric ageing, an aerosol enrichment System varying particle number concentration independent of particle chemistry, and an aerosol Deposition chamber physiologically delivering particles on air-liquid interface (ALI) cultures reproducing normal and susceptible health status. Gasoline-exhaust is an important PM source with largely unknown health effects. We investigated acute responses of fully-differentiated normal, distressed (antibiotics treated) normal, and cystic fibrosis human bronchial epithelia (HBE), and a proliferating, single-cell type bronchial epithelial cell-line (BEAS-2B). We show that a single, short-term exposure to realistic doses of atmospherically-aged gasoline-exhaust particles impairs epithelial key-defence mechanisms, rendering it more vulnerable to subsequent hazards. We establish dose-response curves at realistic particle-concentration levels. Significant differences between cell models suggest the use of fully differentiated HBE is most appropriate in future toxicity studies.