Autism spectrum disorder (ASD) has complex neurodevelopmental impairments and origins that are linked to both genetic and environmental factors. Hence, there is an urgency to establish animal models with ASD-like characteristics to understand the underlying mechanisms of ASD. Prenatal exposure to valproic acid (VPA) produced ASD-like symptoms in humans, rats, and recently zebrafish. The present study investigated the use of VPA exposure to generate an ASD model in zebrafish. Early life stage exposures produced ASD-like phenotypes in the developing brain development and behavioral changes in embryonic and larval zebrafish. Our findings revealed that treating zebrafish embryos with VPA starting at 8h post fertilization (hpf) resulted in significant: increase in the ASD macrocephalic phenotype; hyperactivity of embryo/larvae movement behaviors; and increases of ASD-like larval social behaviors. Further analysis showed increases in cell proliferation, the proportion of mature newborn neurons, and neural stem cell proliferation in the brain region, which may contribute to the brain overgrowth and macrocephaly observed following VPA exposure. Our study demonstrated that VPA exposure generates ASD-like phenotypes and behaviors, indicating that zebrafish is an alternative model to investigate underlying ASD mechanisms.

A growing literature explores intra-urban variation in pollution concentrations. Few studies, however, have examined spatial variation during “peak” hours of the day (e.g., rush hours, inversion conditions), which may have strong bearing for source identification and epidemiological analyses. We aimed to capture “peak” spatial variation across a region of complex terrain, legacy industry, and frequent atmospheric inversions. We hypothesized stronger spatial contrast in concentrations during hours prone to atmospheric inversions and heavy traffic, and designed a 2-year monitoring campaign to capture spatial variation in fine particles (PM2.5) and black carbon (BC). Inversion-focused integrated monitoring (0600–1100 hours) was performed during year 1 (2011–2012) and compared with 1-week 24-h integrated results from year 2 (2012–2013). To allocate sampling sites, we explored spatial distributions in key sources (i.e., traffic, industry) and potential modifiers (i.e., elevation) in geographic information systems (GIS), and allocated 37 sites for spatial and source variability across the metropolitan domain (~388 km2). Land use regression (LUR) models were developed and compared by pollutant, season, and sampling method. As expected, we found stronger spatial contrasts in PM2.5 and BC using inversion-focused sampling, suggesting greater differences in peak exposures across urban areas than is captured by most integrated saturation campaigns. Temporal variability, commercial and industrial land use, PM2.5 emissions, and elevation were significant predictors, but did not more strongly predict concentrations during peak hours.

Steam enhanced extraction (SEE) is an in-situ thermal remediation technique used to remove and recover polycyclic aromatic hydrocarbons (PAHs) from contaminated soils. However, limited studies have been conducted on the formation of PAH derivatives during and after SEE of PAH contaminated soils. Creosote contaminated soil samples collected from the Wyckoff-Eagle Harbor Superfund site were remediated with laboratory scale SEE. The samples were quantified for unsubstituted PAHs and their derivatives, and assessed for developmental toxicity, pre-and post-SEE. Following SEE, unsubstituted PAH concentrations decreased, while oxygenated PAH concentrations increased in soil and aqueous extracts. Differences in developmental toxicity were also measured and linked to the formation of PAH derivatives. Additive toxicity was measured when comparing unfractionated extracts to fractionated extracts in pre-and post-SEE samples. SEE is effective in removing unsubstituted PAHs from contaminated soil, but other, potentially more toxic, PAH derivatives are formed.

BackgroundCharacterizing intra-urban variation in air quality is important for epidemiological investigation of health outcomes and disparities. To date, however, few studies have been designed to capture spatial variation during select hours of the day, or to examine the roles of meteorology and complex terrain in shaping intra-urban exposure gradients.MethodsWe designed a spatial saturation monitoring study to target local air pollution sources, and to understand the role of topography and temperature inversions on fine-scale pollution variation by systematically allocating sampling locations across gradients in key local emissions sources (vehicle traffic, industrial facilities) and topography (elevation) in the Pittsburgh area. Street-level integrated samples of fine particulate matter (PM2.5), black carbon (BC), nitrogen dioxide (NO2), sulfur dioxide (SO2), and ozone (O3) were collected during morning rush and probable inversion hours (6-11 AM), during summer and winter. We hypothesized that pollution concentrations would be: 1) higher under inversion conditions, 2) exacerbated in lower-elevation areas, and 3) vary by season.ResultsDuring July - August 2011 and January - March 2012, we observed wide spatial and seasonal variability in pollution concentrations, exceeding the range measured at regulatory monitors. We identified elevated concentrations of multiple pollutants at lower-elevation sites, and a positive association between inversion frequency and NO2 concentration. We examined temporal adjustment methods for deriving seasonal concentration estimates, and found that the appropriate reference temporal trend differs between pollutants.ConclusionsOur time-stratified spatial saturation approach found some evidence for modification of inversion-concentration relationships by topography, and provided useful insights for refining and interpreting GIS-based pollution source indicators for Land Use Regression modeling.

Research on the health effects of fine particulate matter (PM2.5) frequently disregards the differences in particle composition between that measured on an ambient filter versus that measured in the corresponding extraction solution used for toxicological testing. This study presents a novel method for characterizing the differences, in metallic and organic species, between the ambient samples and the corresponding extracted solutions through characterization of extracted PM2.5 suspended on filters. Removal efficiency was found to be 98.0 ± 1.4% when measured using pre- and post-removal filter weights, however, this efficiency was significantly reduced to 80.2 ± 0.8% when measured based on particle mass in the extraction solution. Furthermore, only 47.2 ± 22.3% of metals and 24.8 ± 14.5% of organics measured on the ambient filter were found in the extraction solution. Individual metallic and organic components were extracted with varying efficiency, with many organics being lost entirely during extraction. Finally, extraction efficiencies of specific PM2.5 components were inversely correlated with total mass. This study details a method to assess compositional alterations resulting from extraction of PM2.5 from filters, emphasizing the need for standardized procedures that maintain compositional integrity of ambient samples for use in toxicology studies of PM2.5.