Dataset Information

Development of Combining of Human Bronchial Mucosa Models with XposeALI® for Exposure of Air Pollution Nanoparticles.

ABSTRACT:

Background

Exposure to agents via inhalation is of great concerns both in workplace environment and in the daily contact with particles in the ambient air. Reliable human airway exposure systems will most likely replace animal experiment in future toxicity assessment studies of inhaled agents.

Methods

In this study, we successfully established a combination of an exposure system (XposeALI) with 3D models mimicking both healthy and chronic bronchitis-like mucosa by co-culturing human primary bronchial epithelial cells (PBEC) and fibroblast at air-liquid interface (ALI). Light-, confocal microscopy, scanning- and transmission electron microscopy, transepithelial electrical resistance (TEER) measurement and RT-PCR were performed to identify how the PBEC differentiated under ALI culture condition. Both models were exposed to palladium (Pd) nanoparticles which sized 6-10 nm, analogous to those released from modern car catalysts, at three different concentrations utilizing the XposeALI module of the PreciseInhale® exposure system.

Results

Exposing the 3D models to Pd nanoparticles induced increased secretion of IL-8, yet the chronic bronchitis-like model released significantly more IL-8 than the normal model. The levels of IL-8 in basal medium (BM) and apical lavage medium (AM) were in the same ranges, but the secretion of MMP-9 was significantly higher in the AM compared to the BM.

Conclusion

This combination of relevant human bronchial mucosa models and sophisticated exposure system can mimic in vivo conditions and serve as a useful alternative animal testing tool when studying adverse effects in humans exposed to aerosols, air pollutants or particles in an occupational setting.

SUBMITTER: Ji J

PROVIDER: S-EPMC5249057 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

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Publications

Development of Combining of Human Bronchial Mucosa Models with XposeALI® for Exposure of Air Pollution Nanoparticles.

Ji Jie J Hedelin Anna A Malmlöf Maria M Kessler Vadim V Seisenbaeva Gulaim G Gerde Per P Palmberg Lena L

PloS one 20170120 1

<h4>Background</h4>Exposure to agents via inhalation is of great concerns both in workplace environment and in the daily contact with particles in the ambient air. Reliable human airway exposure systems will most likely replace animal experiment in future toxicity assessment studies of inhaled agents.<h4>Methods</h4>In this study, we successfully established a combination of an exposure system (XposeALI) with 3D models mimicking both healthy and chronic bronchitis-like mucosa by co-culturing hum ...[more]

PMID: 28107509

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Project description:BackgroundThe era of big data has enabled sophisticated models to predict air pollution concentrations over space and time. Historically these models have been evaluated using overall metrics that measure how close predictions are to monitoring data. However, overall methods are not designed to distinguish error at timescales most relevant for epidemiologic studies, such as day-to-day errors that impact studies of short-term health associations.MethodsWe introduce frequency band model performance, which quantifies health estimation capacity of air quality prediction models for time series studies of air pollution and health. Frequency band model performance uses a discrete Fourier transform to evaluate prediction models at timescales of interest. We simulated fine particulate matter (PM2.5), with errors at timescales varying from acute to seasonal, and health time series data. To compare evaluation approaches, we use correlations and root mean squared error (RMSE). Additionally, we assess health estimation capacity through bias and RMSE in estimated health associations. We apply frequency band model performance to PM2.5 predictions at 17 monitors in 8 US cities.ResultsIn simulations, frequency band model performance rates predictions better (lower RMSE, higher correlation) when there is no error at a particular timescale (e.g., acute) and worse when error is added to that timescale, compared to overall approaches. Further, frequency band model performance is more strongly associated (R2 = 0.95) with health association bias compared to overall approaches (R2 = 0.57). For PM2.5 predictions in Salt Lake City, UT, frequency band model performance better identifies acute error that may impact estimated short-term health associations.ConclusionsFor epidemiologic studies, frequency band model performance provides an improvement over existing approaches because it evaluates models at the timescale of interest and is more strongly associated with bias in estimated health associations. Evaluating prediction models at timescales relevant for health studies is critical to determining whether model error will impact estimated health associations.

Project description:BackgroundBecause fine particulate matter [PM, with aerodynamic diameter ≤2.5μm (PM2.5)] is a ubiquitous environmental exposure, small changes in cognition associated with PM2.5 exposure could have great societal costs. Prior studies have demonstrated a relationship between in utero PM2.5 exposure and cognitive development in urban populations, but it is not known whether these effects are similar in rural populations and whether they persist into late childhood.ObjectivesIn this study, we tested for associations between prenatal PM2.5 exposure and both full-scale and subscale measures of IQ among a longitudinal cohort at age 10.5 y.MethodsThis analysis used data from 568 children enrolled in the Center for the Health Assessment of Mothers and Children of Salinas (CHAMACOS), a birth cohort study in California's agricultural Salinas Valley. Exposures were estimated at residential addresses during pregnancy using state of the art, modeled PM2.5 surfaces. IQ testing was performed by bilingual psychometricians in the dominant language of the child.ResultsA 3-μg/m3 higher average PM2.5 over pregnancy was associated with -1.79 full-scale IQ points [95% confidence interval (CI): -2.98, -0.58], with decrements specifically in Working Memory IQ (WMIQ) and Processing Speed IQ (PSIQ) subscales [WMIQ -1.72 (95% CI: -2.98, -0.45) and PSIQ -1.19 (95% CI: -2.54, 0.16)]. Flexible modeling over the course of pregnancy illustrated mid-to-late pregnancy (months 5-7) as particularly susceptible times, with sex differences in the timing of susceptible windows and in which subscales were most affected [Verbal Comprehension IQ (VCIQ) and WMIQ in males; and PSIQ in females].DiscussionWe found that small increases in outdoor PM2.5 exposure in utero were associated with slightly lower IQ in late childhood, robust to many sensitivity analyses. In this cohort there was a larger effect of PM2.5 on childhood IQ than has previously been observed, perhaps due to differences in PM composition or because developmental disruption could alter the cognitive trajectory and thus appear more pronounced as children get older. https://doi.org/10.1289/EHP10812.

Dataset Information

Development of Combining of Human Bronchial Mucosa Models with XposeALI® for Exposure of Air Pollution Nanoparticles.

Background

Methods

Results

Conclusion

Publications

Development of Combining of Human Bronchial Mucosa Models with XposeALI® for Exposure of Air Pollution Nanoparticles.

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