In Vitro high-throughput toxicological assessment of E-cigarette flavors on human bronchial epithelial cells and the potential involvement of TRPA1 in cinnamon flavor-induced toxicity.

Electronic cigarettes (ECs) are considered a less hazardous alternative to tobacco smoking but are not harmless. Growing concerns about the safety profiles of flavors in e-liquids underpin the need for this study. Here, we screened 53 nicotine-free flavored e-liquids (across 15 flavor categories) across a 3-point concentration range (0.25%, 0.5%, and 1% v/v) in a high-throughput fashion in human bronchial epithelial (HBEC-3KT) submerged cell cultures to identify 'toxic hits' using in vitro endpoint assays comprising cell count, cell viability, and lactate dehydrogenase (LDH). We observed significant, dose-dependent adverse effects only with cinnamon, vanilla tobacco, and hazelnut e-liquids compared to media-only and PG/VG vehicle controls. Hence, we further analyzed these three flavors for their effects on HBEC-3KT proliferation, mitochondrial health, and oxidative stress. A significant decrease in cell proliferation after 36 h was observed for each e-liquid toxic hit compared to media-only and PG/VG controls. Hazelnut (at all concentrations) and vanilla tobacco (1%) increased cytoplasmic reactive oxygen species generation compared to media-only and PG/VG controls. Conversely, all three flavors at 0.5% and 1% significantly decreased mitochondrial membrane potential compared to PG/VG and media-only controls. Chemical analysis revealed that all three flavors contained volatile organic compounds. We hypothesized that the cytotoxicity of cinnamon might be mediated via TRPA1; however, TRPA1 antagonist AP-18 (10 µM) did not mitigate these effects, and cinnamon significantly increased TRPA1 transcript levels. Therefore, pathways mediating cinnamon's cytotoxicity warrant further investigations. This study could inform public health authorities on the relative health risks assessment following exposure to EC flavor ingredients.

Atmospheric conditions and composition that influence PM2.5 oxidative potential in Beijing, China.

Epidemiological studies have consistently linked exposure to PM2.5 with adverse health effects. The oxidative potential (OP) of aerosol particles has been widely suggested as a measure of their potential toxicity. Several acellular chemical assays are now readily employed to measure OP; however, uncertainty remains regarding the atmospheric conditions and specific chemical components of PM2.5 that drive OP. A limited number of studies have simultaneously utilised multiple OP assays with a wide range of concurrent measurements and investigated the seasonality of PM2.5 OP. In this work, filter samples were collected in winter 2016 and summer 2017 during the atmospheric pollution and human health in a Chinese megacity campaign (APHH-Beijing), and PM2.5 OP was analysed using four acellular methods: ascorbic acid (AA), dithiothreitol (DTT), 2,7-dichlorofluorescin/hydrogen peroxidase (DCFH) and electron paramagnetic resonance spectroscopy (EPR). Each assay reflects different oxidising properties of PM2.5, including particle-bound reactive oxygen species (DCFH), superoxide radical production (EPR) and catalytic redox chemistry (DTT/AA), and a combination of these four assays provided a detailed overall picture of the oxidising properties of PM2.5 at a central site in Beijing. Positive correlations of OP (normalised per volume of air) of all four assays with overall PM2.5 mass were observed, with stronger correlations in winter compared to summer. In contrast, when OP assay values were normalised for particle mass, days with higher PM2.5 mass concentrations (µgm-3) were found to have lower mass-normalised OP values as measured by AA and DTT. This finding supports that total PM2.5 mass concentrations alone may not always be the best indicator for particle toxicity. Univariate analysis of OP values and an extensive range of additional measurements, 107 in total, including PM2.5 composition, gas-phase composition and meteorological data, provided detailed insight into the chemical components and atmospheric processes that determine PM2.5 OP variability. Multivariate statistical analyses highlighted associations of OP assay responses with varying chemical components in PM2.5 for both mass- and volume-normalised data. AA and DTT assays were well predicted by a small set of measurements in multiple linear regression (MLR) models and indicated fossil fuel combustion, vehicle emissions and biogenic secondary organic aerosol (SOA) as influential particle sources in the assay response. Mass MLR models of OP associated with compositional source profiles predicted OP almost as well as volume MLR models, illustrating the influence of mass composition on both particle-level OP and total volume OP. Univariate and multivariate analysis showed that different assays cover different chemical spaces, and through comparison of mass- and volume-normalised data we demonstrate that mass-normalised OP provides a more nuanced picture of compositional drivers and sources of OP compared to volume-normalised analysis. This study constitutes one of the most extensive and comprehensive composition datasets currently available and provides a unique opportunity to explore chemical variations in PM2.5 and how they affect both PM2.5 OP and the concentrations of particle-bound reactive oxygen species.

Using highly time-resolved online mass spectrometry to examine biogenic and anthropogenic contributions to organic aerosol in Beijing.

Organic aerosols, a major constituent of fine particulate mass in megacities, can be directly emitted or formed from secondary processing of biogenic and anthropogenic volatile organic compound emissions. The complexity of volatile organic compound emission sources, speciation and oxidation pathways leads to uncertainties in the key sources and chemistry leading to formation of organic aerosol in urban areas. Historically, online measurements of organic aerosol composition have been unable to resolve specific markers of volatile organic compound oxidation, while offline analysis of markers focus on a small proportion of organic aerosol and lack the time resolution to carry out detailed statistical analysis required to study the dynamic changes in aerosol sources and chemistry. Here we use data collected as part of the joint UK-China Air Pollution and Human Health (APHH-Beijing) collaboration during a field campaign in urban Beijing in the summer of 2017 alongside laboratory measurements of secondary organic aerosol from oxidation of key aromatic precursors (1,3,5-trimethyl benzene, 1,2,4-trimethyl benzene, propyl benzene, isopropyl benzene and 1-methyl naphthalene) to study the anthropogenic and biogenic contributions to organic aerosol. For the first time in Beijing, this study applies positive matrix factorisation to online measurements of organic aerosol composition from a time-of-flight iodide chemical ionisation mass spectrometer fitted with a filter inlet for gases and aerosols (FIGAERO-ToF-I-CIMS). This approach identifies the real-time variations in sources and oxidation processes influencing aerosol composition at a near-molecular level. We identify eight factors with distinct temporal variability, highlighting episodic differences in OA composition attributed to regional influences and in situ formation. These have average carbon numbers ranging from C5-C9 and can be associated with oxidation of anthropogenic aromatic hydrocarbons alongside biogenic emissions of isoprene, α-pinene and sesquiterpenes.