Toxicological assessment of E-cigarette flavored E-liquids aerosols using Calu-3 cells: A 3D lung model approach.

Scientific progress and ethical considerations are increasingly shifting the toxicological focus from in vivo animal models to in vitro studies utilizing physiologically relevant cell cultures. Consequently, we evaluated and validated a three-dimensional (3D) model of the human lung using Calu-3 cells cultured at an air-liquid interface (ALI) for 28 days. Assessment of seven essential genes of differentiation and transepithelial electrical resistance (TEER) measurements, in conjunction with mucin (MUC5AC) staining, validated the model. We observed a time-dependent increase in TEER, genetic markers of mucus-producing cells (muc5ac, muc5b), basal cells (trp63), ciliated cells (foxj1), and tight junctions (tjp1). A decrease in basal cell marker krt5 levels was observed. Subsequently, we utilized this validated ALI-cultured Calu-3 model to investigate the adversity of the aerosols generated from three flavored electronic cigarette (EC) e-liquids: cinnamon, vanilla tobacco, and hazelnut. These aerosols were compared against traditional cigarette smoke (3R4F) to assess their relative toxicity. The aerosols generated from PG/VG vehicle control, hazelnut and cinnamon e-liquids, but not vanilla tobacco, significantly decreased TEER and increased lactate dehydrogenase (LDH) release compared to the incubator and air-only controls. Compared to 3R4F, there were no significant differences in TEER or LDH with the tested flavored EC aerosols other than vanilla tobacco. This starkly contrasted our expectations, given the common perception of e-liquids as a safer alternative to cigarettes. Our study suggests that these results depend on flavor type. Therefore, we strongly advocate for further research, increased user awareness regarding flavors in ECs, and rigorous regulatory scrutiny to protect public health.

Feasibility of low-cost particle sensor types in long-term indoor air pollution health studies after repeated calibration, 2019-2021.

Previous studies have explored using calibrated low-cost particulate matter (PM) sensors, but important research gaps remain regarding long-term performance and reliability. Evaluate longitudinal performance of low-cost particle sensors by measuring sensor performance changes over 2 years of use. 51 low-cost particle sensors (Airbeam 1 N = 29; Airbeam 2 N = 22) were calibrated four times over a 2-year timeframe between 2019 and 2021. Cigarette smoke-specific calibration curves for Airbeam 1 and 2 PM sensors were created by directly comparing simultaneous 1-min readings of a Thermo Scientific Personal DataRAM PDR-1500 unit with a 2.5 µm inlet. Inter-sensor variability in calibration coefficient was high, particularly in Airbeam 1 sensors at study initiation. Calibration coefficients for both sensor types trended downwards over time to < 1 at final calibration timepoint [Airbeam 1 Mean (SD) = 0.87 (0.20); Airbeam 2 Mean (SD) = 0.96 (0.27)]. We lost more Airbeam 1 sensors (N = 27 out of 56, failure rate 48.2%) than Airbeam 2 (N = 2 out of 24, failure rate 8.3%) due to electronics, battery, or data output issues. Evidence suggests degradation over time might depend more on particle sensor type, rather than individual usage. Repeated calibrations of low-cost particle sensors may increase confidence in reported PM levels in longitudinal indoor air pollution studies.

PM2.5 Concentration and Composition in Subway Systems in the Northeastern United States.

OBJECTIVES: The goals of this study were to assess the air quality in subway systems in the northeastern United States and estimate the health risks for transit workers and commuters. METHODS: We report real-time and gravimetric PM2.5 concentrations and particle composition from area samples collected in the subways of Philadelphia, Pennsylvania; Boston, Massachusetts; New York City, New York/New Jersey (NYC/NJ); and Washington, District of Columbia. A total of 71 stations across 12 transit lines were monitored during morning and evening rush hours. RESULTS: We observed variable and high PM2.5 concentrations for on-train and on-platform measurements during morning (from 0600 hours to 1000 hours) and evening (from 1500 hours to 1900 hours) rush hour across cities. Mean real-time PM2.5 concentrations in underground stations were 779±249, 548±207, 341±147, 327±136, and 112±46.7 µg/m3 for the PATH-NYC/NJ; MTA-NYC; Washington, DC; Boston; and Philadelphia transit systems, respectively. In contrast, the mean real-time ambient PM2.5 concentration taken above ground outside the subway stations of PATH-NYC/NJ; MTA-NYC; Washington, DC; Boston; and Philadelphia were 20.8±9.3, 24.1±9.3, 12.01±7.8, 10.0±2.7, and 12.6±12.6 µg/m3, respectively. Stations serviced by the PATH-NYC/NJ system had the highest mean gravimetric PM2.5 concentration, 1,020 µg/m3, ever reported for a subway system, including two 1-h gravimetric PM2.5 values of approximately 1,700 µg/m3 during rush hour at one PATH-NYC/NJ subway station. Iron and total carbon accounted for approximately 80% of the PM2.5 mass in a targeted subset of systems and stations. DISCUSSION: Our results document that there is an elevation in the PM2.5 concentrations across subway systems in the major urban centers of Northeastern United States during rush hours. Concentrations in some subway stations suggest that transit workers and commuters may be at increased risk according to U.S. federal environmental and occupational guidelines, depending on duration of exposure. This concern is highest for the PM2.5 concentrations encountered in the PATH-NYC/NJ transit system. Further research is urgently needed to identify the sources of PM2.5 and factors that contribute to high levels in individual stations and lines and to assess their potential health impacts on workers and/or commuters. https://doi.org/10.1289/EHP7202.