Analytic comparison of talc in commercially available baby powder and in pelvic tissues resected from ovarian carcinoma patients.

OBJECTIVE: Measure the size and shape of talc particles in talcum powder and compare this data to the size and shape of talc particles found in surgically resected tissues from patients with ovarian carcinoma. METHODS: Using polarized light microscopy (PLM) and scanning electron microscopy (SEM), we measured the size and shape of talc particles in samples of talc-containing baby powder (TCBP) and surgically resected pelvic tissues (hysterectomies) from talc-exposed patients with ovarian carcinoma. RESULTS: The most frequent class of particles in TCBP can be unequivocally identified as talc, using both polarized light microscopy and scanning electron microscopy with energy dispersive X-ray analysis (SEM/EDX). The talc particles found in resected tissues from ovarian carcinoma patients are similar in size and shape to the most abundant morphological class of particles in TCBP. CONCLUSIONS: This finding, combined with previous epidemiological literature and tissue-based analytical studies, provides further evidence that the small, isodiametric particles that dominate TCBP can migrate from the perineum and become lodged in distal structures in the female reproductive tract, where they may lead to an increased risk of developing ovarian carcinoma.

The effect of talc particles on phagocytes in co-culture with ovarian cancer cells.

Talc and titanium dioxide are naturally occurring water-insoluble mined products usually available in the form of particulate matter. This study was prompted by epidemiological observations suggesting that perineal use of talc powder is associated with increased risk of ovarian cancer, particularly in a milieu with higher estrogen. We aimed to test the effects of talc vs. control particles on the ability of prototypical macrophage cell lines to curb the growth of ovarian cancer cells in culture in the presence of estrogen. We found that murine ovarian surface epithelial cells (MOSEC), a prototype of certain forms of ovarian cancer, were present in larger numbers after co-culture with macrophages treated to a combination of talc and estradiol than to either agent alone or vehicle. Control particles (titanium dioxide, concentrated urban air particulates or diesel exhaust particles) did not have this effect. Co-exposure of macrophages to talc and estradiol has led to increased production of reactive oxygen species and changes in expression of macrophage genes pertinent in cancer development and immunosurveillance. These findings suggest that in vitro exposure to talc, particularly in a high-estrogen environment, may compromise immunosurveillance functions of macrophages and prompt further studies to elucidate this mechanism.

Analysis of particles from hamster lungs following pulmonary talc exposures: implications for pathogenicity.

BACKGROUND: Talc, a hydrous magnesium silicate, often used for genital hygiene purposes, is associated with ovarian carcinoma in case-control studies. Its potential to cause inflammation, injury, and functional changes in cells has been described. A complication of such studies is that talc preparations may be contaminated with other materials. A previous study by (Beck et al. Toxicol Appl Pharmacol 87:222-34, 1987) used a hamster model to study talc and granite dust exposure effects on various biochemical and cellular inflammatory markers. Our current study accessed key materials used in that 1987 study; we re-analyzed the original talc dust with contemporary scanning electron microscopy and energy dispersive x-ray analysis (SEM/EDX) for contaminants. We also examined the original bronchoalveolar lavage (BAL) cells with polarized light microscopy to quantify cell-associated birefringent particles to gain insight into the talc used. RESULTS: SEM/EDX analyses showed that asbestos fibers, quartz, and toxic metal particulates were below the limits of detection in the original talc powder. However, fibers with aspect ratios ≥3:1 accounted for 22% of instilled material, mostly as fibrous talc. Talc (based on Mg/Si atomic weight % ratio) was the most abundant chemical signature, and magnesium silicates with various other elements made up the remainder. BAL cell counts confirmed the presence of acute inflammation, which followed intratracheal instillation. Measurements of cell associated birefringent particles phagocytosis revealed significant differences among talc, granite, and control exposures with high initial uptake of talc compared to granite, but over the 14-day experiment, talc phagocytosis by lavaged cells was significantly less than that of granite. Phagocytosis of talc fibers by macrophages was observed, and birefringent particles were found in macrophages, neutrophils, and multinucleate giant cells in lavaged cells from talc-exposed animals. CONCLUSION: Our data support the contention that talc, even without asbestos and other known toxic contaminants, may elicit inflammation and contribute to lung disease. Our findings support the conclusions of (Beck et al. Toxicol Appl Pharmacol 87:222-34, 1987) study. By analyzing particulate exposures with polarized light microscopy and SEM/EDX, fibrous talc was identified and a distinctive pattern of impaired particulate ingestion was demonstrated.

Inhalation of printer-emitted particles impairs cardiac conduction, hemodynamics, and autonomic regulation and induces arrhythmia and electrical remodeling in rats.

BACKGROUND: Using engineered nanomaterial-based toners, laser printers generate aerosols with alarming levels of nanoparticles that bear high bioactivity and potential health risks. Yet, the cardiac impacts of printer-emitted particles (PEPs) are unknown. Inhalation of particulate matter (PM) promotes cardiovascular morbidity and mortality, and ultra-fine particulates (< 0.1 µm aerodynamic diameter) may bear toxicity unique from larger particles. Toxicological studies suggest that PM impairs left ventricular (LV) performance; however, such investigations have heretofore required animal restraint, anesthesia, or ex vivo preparations that can confound physiologic endpoints and/or prohibit LV mechanical assessments during exposure. To assess the acute and chronic effects of PEPs on cardiac physiology, male Sprague Dawley rats were exposed to PEPs (21 days, 5 h/day) while monitoring LV pressure (LVP) and electrocardiogram (ECG) via conscious telemetry, analyzing LVP and heart rate variability (HRV) in four-day increments from exposure days 1 to 21, as well as ECG and baroreflex sensitivity. At 2, 35, and 70 days after PEPs exposure ceased, rats received stress tests. RESULTS: On day 21 of exposure, PEPs significantly (P < 0.05 vs. Air) increased LV end systolic pressure (LVESP, + 18 mmHg) and rate-pressure-product (+ 19%), and decreased HRV indicating sympathetic dominance (root means squared of successive differences [RMSSD], - 21%). Overall, PEPs decreased LV ejection time (- 9%), relaxation time (- 3%), tau (- 5%), RMSSD (- 21%), and P-wave duration (- 9%). PEPs increased QTc interval (+ 5%) and low:high frequency HRV (+ 24%; all P < 0.05 vs. Air), while tending to decrease baroreflex sensitivity and contractility index (- 15% and - 3%, P < 0.10 vs. Air). Relative to Air, at both 2 and 35 days after PEPs, ventricular arrhythmias increased, and at 70 days post-exposure LVESP increased. PEPs impaired ventricular repolarization at 2 and 35 days post-exposure, but only during stress tests. At 72 days post-exposure, PEPs increased urinary dopamine 5-fold and protein expression of ventricular repolarizing channels, Kv1.5, Kv4.2, and Kv7.1, by 50%. CONCLUSIONS: Our findings suggest exposure to PEPs increases cardiovascular risk by augmenting sympathetic influence, impairing ventricular performance and repolarization, and inducing hypertension and arrhythmia. PEPs may present significant health risks through adverse cardiovascular effects, especially in occupational settings, among susceptible individuals, and with long-term exposure.

Secondary particles formed from the exhaust of vehicles using ethanol-gasoline blends increase the production of pulmonary and cardiac reactive oxygen species and induce pulmonary inflammation.

BACKGROUND: Ethanol vehicles release exhaust gases that contribute to the formation of secondary organic aerosols (SOA). OBJECTIVE: To determine in vivo toxicity resulting from exposure to SOA derived from vehicles using different ethanol-gasoline blends (E0, E10, E22, E85W, E85S, E100). METHODS: Exhaust emissions from vehicles using ethanol blends were delivered to a photochemical chamber and reacted to produce SOA. The aerosol samples were collected on filters, extracted, and dispersed in an aqueous solutions and intratracheally instilled into Sprague Dawley rats in doses of 700 µg/0.2 ml. After 45 min and 4 h pulmonary and cardiac chemiluminescence (CL) was measured to estimate the amount of reactive oxygen species (ROS) produced in the lungs and heart. Inflammation was measured by differential cell count in bronchoalveolar lavages (BAL). RESULTS: Statistically and biologically significant differences in response to secondary particles from the different fuel formulations were detected. Compared to the control group, animals exposed to SOA from gasoline (E0) showed a significantly higher average CL in the lungs at 45 min. The highest CL averages in the heart were observed in the groups exposed to SOA from E10 and pure ethanol (E100) at 45 min. BAL of animals exposed to SOA from E0 and E85S had a significant increased number of macrophages at 45 min. BAL neutrophil count was increased in the groups exposed to E85S (45 min) and E0 (4 h). Animals exposed to E0 and E85W had increased BAL lymphocyte count compared to the control and the other exposed groups. DISCUSSION: Our results suggest that SOA generated by gasoline (E0), followed by ethanol blends E85S and E85W, substantially induce oxidative stress measured by ROS generation and pulmonary inflammation measured by the recruitment of white blood cells in BAL.

Magnesium/silicon atomic weight percent ratio standards for the tissue identification of talc by scanning electron microscopy and energy dispersive X-ray analysis.

Talc may lodge in human tissues through various routes, and has been associated with the development of ovarian carcinoma in case control epidemiologic studies. Talc is detected in tissues with scanning electron microscopy and energy dispersive X-ray analysis (SEM/EDS), with expected magnesium (Mg) and silicon (Si) peaks. The theoretical atomic weight % Mg/Si ratio for talc is 0.649, and for diagnostic purposes, a range of ± 5% (~0.617 to 0.681) is often used as a standard. Our goal was to establish empirically the quantitative range for talc identification by SEM/EDS using two source materials: a Johnson's Baby PowderTM (cosmetic-grade) consumer sample, and talc from Sigma-Aldrich (particle-grade material intended for scientific use). We examined 401 Mg-Si particles with SEM/EDS across the two samples, using two different SEM microscopes. Overall, we found a mean Mg/Si atomic weight % ratio of 0.645, with minimal differences between study subsets. The standard deviation was 0.025; (± 1σ = 0.620-0.670). The currently used ± 5% diagnostic range (Mg/Si 0.617-0.681) is thus reasonably close to this study's ± 1σ range, and well within a ± 2 σ confidence interval span (Mg/Si 0.595-0.695). The ± 5% range is thus an appropriately conservative standard whose continued use seems justified.

Correlative polarizing light and scanning electron microscopy for the assessment of talc in pelvic region lymph nodes.

Perineal talc use is associated with ovarian carcinoma in many case-control studies. Such talc may migrate to pelvic organs and regional lymph nodes, with both clinical and legal significance. Our goal was to differentiate talc in pelvic lymph nodes due to exposure, versus contamination with talc in the laboratory. We studied 22 lymph nodes from ovarian tumor patients, some of which had documented talc exposure, to quantify talc using digestion of tissue taken from paraffin blocks and scanning electron microscopy/energy dispersive X-ray analysis (SEM/EDX). Talc particles correlated significantly with surface contamination assessments using polarized light microscopy. After adjusting for surface contamination, talc burdens in nodes correlated strongly with perineal talc use. In a separate group of lymph nodes, birefringent particles within the same plane of focus as the tissues in histological sections were highly correlated with talc particles within the tissue by in situ SEM/EDX (r = 0.80; p < 0.0001). We conclude that since talc can be a surface contaminant from tissue collection/preparation, digestion measurements may be influenced by contamination. Instead, because they preserve anatomic landmarks and permit identification of particles in cells and tissues, polarized light microscopy and in situ SEM/EDX are recommended to assess talc in lymph nodes.

Identification of Foreign Particles in Human Tissues Using Raman Microscopy.

The goal of this study was to precisely and unambiguously identify foreign particles in human tissues using a combination of polarized light microscopy and Raman microscopy, which provides chemical composition and microstructural characterization of complex materials with submicrometer spatial resolution. This identification for patient care and research has been traditionally studied using polarized light microscopy, electron microscopy with X-ray analysis, and electron diffraction, all with some limitations. We designed a model system of stained and unstained cells that contained birefringent talc particles and systematically investigated the influence of slide and coverslip materials, laser wavelengths, and mounting media on the Raman spectra obtained. Hematoxylin and eosin stained slides did not produce useful results because of fluorescence interference from the stains. Unstained cell samples prepared with standard slides and coverslips produce high quality Raman spectra when excited at 532 nm; the spectra are uniquely assigned to talc. We also obtain high quality Raman spectra specific for talc in unstained tissue samples (pleural tissue following talc pleurodesis and ovarian tissue following long-term perineal talc exposure). Raman microscopy is sufficiently sensitive and compositionally selective to identify particles as small as one micrometer in diameter. Raman spectra have been catalogued for thousands of substances, which suggests that this approach is likely to be successful in identifying other particles of interest in tissues, potentially making Raman microscopy a powerful new tool in pathology.

Heart Rate Variability and Cardiopulmonary Dysfunction in Patients with Duchenne Muscular Dystrophy: A Systematic Review.

Duchenne muscular dystrophy (DMD) is a genetic recessive disorder with progressive muscle weakness. Despite the general muscle wasting, degeneration and necrosis of cardiomyocytes have been the main causes of morbidity and death in individuals with DMD. Cardiac failure is generally preceded by disturbances in heart rate variability (HRV), and non-invasive measurement of the autonomic nervous system has been an important tool to predict adverse cardiovascular events. Hence, the application of HRV to study autonomic modulation in DMD individuals, and the establishment of correlations between HRV and heart/lung diseases, age, and mortality will have the potential to improve quality of life and life expectancy of individuals with DMD. In order to evaluate the state of the art in this field, we conducted a systematic search in Medline/PubMed and BVS (virtual library in health) databases. We selected 8 studies using pre-defined criteria and meta-analysis revealed decreased parasympathetic activity and increased sympathetic predominance in individuals with DMD as major observations. Moreover, there is a strong association between diminished HRV and myocardial fibrosis with DMD. These patterns are evident in patients at early-stage DMD and become more prominent as disease severity and age increase. Thus, data minning clearly indicates that HRV assessment can be used as a predictor for sudden death in individuals with DMD. The use of the HRV, which is inexpensive, ubiquitously available in clinics and hospitals, and a non-invasive analysis tool, can save lives and decrease the morbity in DMD by alerting care givers to consider autonomic nervous system intervention.

Inhaled ambient-level traffic-derived particulates decrease cardiac vagal influence and baroreflexes and increase arrhythmia in a rat model of metabolic syndrome.

BACKGROUND: Epidemiological studies have linked exposures to ambient fine particulate matter (PM2.5) and traffic with autonomic nervous system imbalance (ANS) and cardiac pathophysiology, especially in individuals with preexisting disease. It is unclear whether metabolic syndrome (MetS) increases susceptibility to the effects of PM2.5. We hypothesized that exposure to traffic-derived primary and secondary organic aerosols (P + SOA) at ambient levels would cause autonomic and cardiovascular dysfunction in rats exhibiting features of MetS. Male Sprague Dawley (SD) rats were fed a high-fructose diet (HFrD) to induce MetS, and exposed to P + SOA (20.4 ± 0.9 µg/m3) for 12 days with time-matched comparison to filtered-air (FA) exposed MetS rats; normal diet (ND) SD rats were separately exposed to FA or P + SOA (56.3 ± 1.2 µg/m3). RESULTS: In MetS rats, P + SOA exposure decreased HRV, QTc, PR, and expiratory time overall (mean effect across the entirety of exposure), increased breathing rate overall, decreased baroreflex sensitivity (BRS) on three exposure days, and increased spontaneous atrioventricular (AV) block Mobitz Type II arrhythmia on exposure day 4 relative to FA-exposed animals receiving the same diet. Among ND rats, P + SOA decreased HRV only on day 1 and did not significantly alter BRS despite overall hypertensive responses relative to FA. Correlations between HRV, ECG, BRS, and breathing parameters suggested a role for autonomic imbalance in the pathophysiologic effects of P + SOA among MetS rats. Autonomic cardiovascular responses to P + SOA at ambient PM2.5 levels were pronounced among MetS rats and indicated blunted vagal influence over cardiovascular physiology. CONCLUSIONS: Results support epidemiologic findings that MetS increases susceptibility to the adverse cardiac effects of ambient-level PM2.5, potentially through ANS imbalance.

Repeated Mouse Lung Exposures to Stachybotrys chartarum Shift Immune Response from Type 1 to Type 2.

After a single or multiple intratracheal instillations of Stachybotrys chartarum (S. chartarum or black mold) spores in BALB/c mice, we characterized cytokine production, metabolites, and inflammatory patterns by analyzing mouse bronchoalveolar lavage (BAL), lung tissue, and plasma. We found marked differences in BAL cell counts, especially large increases in lymphocytes and eosinophils in multiple-dosed mice. Formation of eosinophil-rich granulomas and airway goblet cell metaplasia were prevalent in the lungs of multiple-dosed mice but not in single- or saline-dosed groups. We detected changes in the cytokine expression profiles in both the BAL and plasma. Multiple pulmonary exposures to S. chartarum induced significant metabolic changes in the lungs but not in the plasma. These changes suggest a shift from type 1 inflammation after an acute exposure to type 2 inflammation after multiple exposures to S. chartarum. Eotaxin, vascular endothelial growth factor (VEGF), MIP-1α, MIP-1ß, TNF-α, and the IL-8 analogs macrophage inflammatory protein-2 (MIP-2) and keratinocyte chemoattractant (KC), had more dramatic changes in multiple- than in single-dosed mice, and parallel the cytokines that characterize humans with histories of mold exposures versus unexposed control subjects. This repeated exposure model allows us to more realistically characterize responses to mold, such as cytokine, metabolic, and cellular changes.

Bayesian kernel machine regression for estimating the health effects of multi-pollutant mixtures.

Because humans are invariably exposed to complex chemical mixtures, estimating the health effects of multi-pollutant exposures is of critical concern in environmental epidemiology, and to regulatory agencies such as the U.S. Environmental Protection Agency. However, most health effects studies focus on single agents or consider simple two-way interaction models, in part because we lack the statistical methodology to more realistically capture the complexity of mixed exposures. We introduce Bayesian kernel machine regression (BKMR) as a new approach to study mixtures, in which the health outcome is regressed on a flexible function of the mixture (e.g. air pollution or toxic waste) components that is specified using a kernel function. In high-dimensional settings, a novel hierarchical variable selection approach is incorporated to identify important mixture components and account for the correlated structure of the mixture. Simulation studies demonstrate the success of BKMR in estimating the exposure-response function and in identifying the individual components of the mixture responsible for health effects. We demonstrate the features of the method through epidemiology and toxicology applications.

Part 1. Statistical Learning Methods for the Effects of Multiple Air Pollution Constituents.

INTRODUCTION: The United States Environmental Protection Agency (U.S. EPA*) currently regulates individual air pollutants on a pollutant-by-pollutant basis, adjusted for other pollutants and potential confounders. However, the National Academies of Science concluded that a multipollutant regulatory approach that takes into account the joint effects of multiple constituents is likely to be more protective of human health. Unfortunately, the large majority of existing research had focused on health effects of air pollution for one pollutant or for one pollutant with control for the independent effects of a small number of copollutants. Limitations in existing statistical methods are at least partially responsible for this lack of information on joint effects. The goal of this project was to fill this gap by developing flexible statistical methods to estimate the joint effects of multiple pollutants, while allowing for potential nonlinear or nonadditive associations between a given pollutant and the health outcome of interest. METHODS: We proposed Bayesian kernel machine regression (BKMR) methods as a way to simultaneously achieve the multifaceted goals of variable selection, flexible estimation of the exposure-response relationship, and inference on the strength of the association between individual pollutants and health outcomes in a health effects analysis of mixtures. We first developed a BKMR variable-selection approach, which we call component-wise variable selection, to make estimating such a potentially complex exposure-response function possible by effectively using two types of penalization (or regularization) of the multivariate exposure-response surface. Next we developed an extension of this first variable-selection approach that incorporates knowledge about how pollutants might group together, such as multiple constituents of particulate matter that might represent a common pollution source category. This second grouped, or hierarchical, variable-selection procedure is applicable when groups of highly correlated pollutants are being studied. To investigate the properties of the proposed methods, we conducted three simulation studies designed to evaluate the ability of BKMR to estimate environmental mixtures responsible for health effects under potentially complex but plausible exposure-response relationships. An attractive feature of our simulation studies is that we used actual exposure data rather than simulated values. This real-data simulation approach allowed us to evaluate the performance of BKMR and several other models under realistic joint distributions of multipollutant exposure. The simulation studies compared the two proposed variable-selection approaches (component-wise and hierarchical variable selection) with each other and with existing frequentist treatments of kernel machine regression (KMR). After the simulation studies, we applied the newly developed methods to an epidemiologic data set and to a toxicologic data set. To illustrate the applicability of the proposed methods to human epidemiologic data, we estimated associations between short-term exposures to fine particulate matter constituents and blood pressure in the Maintenance of Balance, Independent Living, Intellect, and Zest in the Elderly (MOBILIZE) Boston study, a prospective cohort study of elderly subjects. To illustrate the applicability of these methods to animal toxicologic studies, we analyzed data on the associations between both blood pressure and heart rate in canines exposed to a composition of concentrated ambient particles (CAPs) in a study conducted at the Harvard T. H. Chan School of Public Health (the Harvard Chan School; formerly Harvard School of Public Health; Bartoli et al. 2009). RESULTS: We successfully developed the theory and computational tools required to apply the proposed methods to the motivating data sets. Collectively, the three simulation studies showed that component-wise variable selection can identify important pollutants within a mixture as long as the correlations among pollutant concentrations are low to moderate. The hierarchical variable-selection method was more effective in high-dimension, high-correlation settings. Variable selection in existing frequentist KMR models can incur inflated type I error rates, particularly when pollutants are highly correlated. The analyses of the MOBILIZE data yielded evidence of a linear and additive association of black carbon (BC) or Cu exposure with standing diastolic blood pressure (DBP), and a linear association of S exposure with standing systolic blood pressure (SBP). Cu is thought to be a marker of urban road dust associated with traffic; and S is a marker of power plant emissions or regional long-range transported air pollution or both. Therefore, these analyses of the MOBILIZE data set suggest that emissions from these three source categories were most strongly associated with hemodynamic responses in this cohort. In contrast, in the Harvard Chan School canine study, after controlling for an overall effect of CAPs exposure, we did not observe any associations between DBP or SBP and any elemental concentrations. Instead, we observed strong evidence of an association between Mn concentrations and heart rate in that heart rate increased linearly with increasing concentrations of Mn. According to the positive matrix factorization (PMF) source apportionment analyses of the multipollutant data set from the Harvard Chan School Boston Supersite, Mn loads on the two factors that represent the mobile and road dust source categories. The results of the BKMR analyses in both the MOBILIZE and canine studies were similar to those from existing linear mixed model analyses of the same multipollutant data because the effects have linear and additive forms that could also have been detected using standard methods. CONCLUSIONS: This work provides several contributions to the KMR literature. First, to our knowledge this is the first time KMR methods have been used to estimate the health effects of multipollutant mixtures. Second, we developed a novel hierarchical variable-selection approach within BKMR that is able to account for the structure of the mixture and systematically handle highly correlated exposures. The analyses of the epidemiologic and toxicologic data on associations between fine particulate matter constituents and blood pressure or heart rate demonstrated associations with constituents that are typically associated with traffic emissions, power plants, and long-range transported pollutants. The simulation studies showed that the BKMR methods proposed here work well for small to moderate data sets; more work is needed to develop computationally fast methods for large data sets. This will be a goal of future work.

Effects of fresh and aged vehicular exhaust emissions on breathing pattern and cellular responses--pilot single vehicle study.

The study presented here is a laboratory pilot study using diluted car exhaust from a single vehicle to assess differences in toxicological response between primary emissions and secondary products resulting from atmospheric photochemical reactions of gas phase compounds with O3, OH and other radicals. Sprague Dawley rats were exposed for 5 h to either filtered room air (sham) or one of two different atmospheres: (i) diluted car exhaust (P)+Mt. Saint Helens Ash (MSHA); (ii) P+MSHA+secondary organic aerosol (SOA, formed during simulated photochemical aging of diluted exhaust). Primary and secondary gases were removed using a nonselective diffusion denuder. Continuous respiratory data was collected during the exposure, and bronchoalveolar lavage (BAL) and complete blood counts (CBC) were performed 24 h after exposure. ANOVA models were used to assess the exposure effect and to compare those effects across different exposure types. Total average exposures were 363 ± 66 µg/m³ P+MSHA and 212 ± 95 µg/m³ P+MSHA+SOA. For both exposures, we observed decreases in breathing rate, tidal and minute volumes (TV, MV) and peak and median flows (PIF, PEF and EF50) along with increases in breathing cycle times (Ti, Te) compared to sham. These results indicate that the animals are changing their breathing pattern with these test atmospheres. Exposure to P+MSHA+SOA produced significant increases in total cells, macrophages and neutrophils in the BAL and in vivo chemiluminescence of the lung. There were no significant differences in CBC parameters. Our data suggest that simulated atmospheric photochemistry, producing SOA in the P+MSHA+SOA exposures, enhanced the toxicity of vehicular emissions.

Toxicological evaluation of realistic emission source aerosols (TERESA)-power plant studies: assessment of cellular responses.

The Toxicological Evaluation of Realistic Emission Source Aerosols (TERESA) project assessed primary and secondary particulate by simulating the chemical reactions that a plume from a source might undergo during atmospheric transport and added other atmospheric constituents that might interact with it. Three coal-fired power plants with different coal and different emission controls were used. Male Sprague-Dawley rats were exposed for 6 h to either filtered air or aged aerosol from the power plant. Four exposure scenarios were studied: primary particles (P); primary + secondary (oxidized) particles (PO); primary + secondary (oxidized) particles + SOA (POS); and primary + secondary (oxidized) particles neutralized + SOA (PONS). Exposure concentrations varied by scenario to a maximum concentration of 257.1 ± 10.0 µg/m(3). Twenty-four hours after exposure, pulmonary cellular responses were assessed by bronchoalveolar lavage (BAL), complete blood count (CBC), and histopathology. Exposure to the PONS and POS scenarios produced significant increases in BAL total cells and macrophage numbers at two plants. The PONS and P scenarios were associated with significant increases in BAL neutrophils and the presence of occasional neutrophils and increased macrophages in the airways and alveoli of exposed animals. Univariate analyses and random forest analyses showed that increases in total cell count and macrophage cell count were significantly associated with neutralized sulfate and several correlated measurements. Increases in neutrophils in BAL were associated with zinc. There were no significant differences in CBC parameters or blood vessel wall thickness by histopathology. The association between neutrophils increases and zinc raises the possibility that metals play a role in this response.

Toxicological evaluation of realistic emission source aerosols (TERESA): introduction and overview.

Determining the health impacts of sources and components of fine particulate matter (PM(2.5)) is an important scientific goal. PM(2.5) is a complex mixture of inorganic and organic constituents that are likely to differ in their potential to cause adverse health outcomes. The Toxicological Evaluation of Realistic Emissions of Source Aerosols (TERESA) study focused on two PM sources--coal-fired power plants and mobile sources--and sought to investigate the toxicological effects of exposure to emissions from these sources. The set of papers published here document the power plant experiments. TERESA attempted to delineate health effects of primary particles, secondary (aged) particles, and mixtures of these with common atmospheric constituents. TERESA involved withdrawal of emissions from the stacks of three coal-fired power plants in the United States. The emissions were aged and atmospherically transformed in a mobile laboratory simulating downwind power plant plume processing. Toxicological evaluations were carried out in laboratory rats exposed to different emission scenarios with extensive exposure characterization. The approach employed in TERESA was ambitious and innovative. Technical challenges included the development of stack sampling technology that prevented condensation of water vapor from the power plant exhaust during sampling and transfer, while minimizing losses of primary particles; development and optimization of a photochemical chamber to provide an aged aerosol for animal exposures; development and evaluation of a denuder system to remove excess gaseous components; and development of a mobile toxicology laboratory. This paper provides an overview of the conceptual framework, design, and methods employed in the study.

Laboratory evaluation of a prototype photochemical chamber designed to investigate the health effects of fresh and aged vehicular exhaust emissions.

Laboratory experiments simulating atmospheric aging of motor vehicle exhaust emissions were conducted using a single vehicle and a photochemical chamber. A compact automobile was used as a source of emissions. The vehicle exhaust was diluted with ambient air to achieve carbon monoxide (CO) concentrations similar to those observed in an urban highway tunnel. With the car engine idling, it is expected that the CO concentration is a reasonable surrogate for volatile organic compounds (VOCs) emissions. Varying the amount of dilution of the exhaust gas to produce different CO concentrations, allowed adjustment of the concentrations of VOCs in the chamber to optimize production of secondary organic aerosol (SOA) needed for animal toxicological exposures. Photochemical reactions in the chamber resulted in nitric oxide (NO) depletion, nitrogen dioxide (NO2) formation, ozone (O3) accumulation, and SOA formation. A stable SOA concentration of approximately 40 µg m⁻³ at a chamber mean residence time of 30 min was achieved. This relatively short mean residence time provided adequate chamber flow output for both particle characterization and animal exposures. The chamber was operated as a continuous flow reactor for animal toxicological tests. SOA mass generated from the car exhaust diluted with ambient air was almost entirely in the ultrafine mode. Chamber performance was improved by using different types of seed aerosol to provide a surface for condensation of semivolatile reaction products, thus increasing the yield of SOA. Toxicological studies using Sprague-Dawley rats found significant increases of in vivo chemiluminescence in lungs following exposure to SOA.

The toxicological evaluation of realistic emissions of source aerosols study: statistical methods.

The Toxicological Evaluation of Realistic Emissions of Source Aerosols (TERESA) study involved withdrawal, aging, and atmospheric transformation of emissions of three coal-fired power plants. Toxicological evaluations were carried out in rats exposed to different emission scenarios with extensive exposure characterization. Data generated had multiple levels of resolution: exposure, scenario, and constituent chemical composition. Here, we outline a multilayered approach to analyze the associations between exposure and health effects beginning with standard ANOVA models that treat exposure as a categorical variable. The model assessed differences in exposure effects across scenarios (by plant). To assess unadjusted associations between pollutant concentrations and health, univariate analyses were conducted using the difference between the response means under exposed and control conditions and a single constituent concentration as the predictor. Then, a novel multivariate analysis of exposure composition and health was used based on Random Forests(™), a recent extension of classification and regression trees that were applied to the outcome differences. For each exposure constituent, this approach yielded a nonparametric measure of the importance of that constituent in predicting differences in response on a given day, controlling for the other measured constituent concentrations in the model. Finally, an R(2) analysis compared the relative importance of exposure scenario, plant, and constituent concentrations on each outcome. Peak expiratory flow (PEF) is used to demonstrate how the multiple levels of the analysis complement each other to assess constituents most strongly associated with health effects.

Toxicological evaluation of realistic emission source aerosols (TERESA): summary and conclusions.

The toxicological evaluation of realistic emissions of source aerosols (TERESA) study seeks to delineate health effects of aerosols formed from emissions of particulate matter sources. This series of papers reports the findings of experiments using coal-fired power plants as the source of emissions and this paper summarizes the findings and knowledge acquired from these studies. Emissions were drawn directly from the stacks of three coal-fired power plants in the US, and photochemically aged in a mobile laboratory to simulate downwind power plant plume processing. The power plants used different sources of coal and had different emission controls. Exposure scenarios included primary particles, secondary particles and mixtures of these with common atmospheric constituents (α-pinene and ammonia). Extensive exposure characterization was carried out, and toxicological outcomes were evaluated in Sprague-Dawley rats exposed to different emission scenarios. Breathing pattern, pulmonary inflammatory responses, in vivo pulmonary and cardiac chemiluminescence and cardiac response in a model of acute myocardial infarction were assessed. The results showed no response or relatively mild responses to the inhaled aerosols studied; complex scenarios which included oxidized emissions and α-pinene to simulate biogenic secondary organic aerosol tended to induce more statistically significant responses than scenarios of oxidized and non-oxidized emissions alone. Relating adverse effects to specific components did not consistently identify a toxic constituent. These findings are consistent with most of the previously published studies using pure compounds to model secondary power plant emissions, but importantly add substantial complexity and thus have considerable merit in defining toxicological responses.