Cinnamaldehyde in flavored e-cigarette liquids temporarily suppresses bronchial epithelial cell ciliary motility by dysregulation of mitochondrial function

Aldehydes in cigarette smoke (CS) impair mitochondrial function and reduce ciliary beat frequency (CBF), leading to diminished mucociliary clearance (MCC). However, the effects of aldehyde e-cigarette flavorings on CBF are unknown. The purpose of this study was to investigate whether cinnamaldehyde, a flavoring agent commonly used in e-cigarettes, disrupts mitochondrial function and impairs CBF on well-differentiated human bronchial epithelial (hBE) cells. To this end, hBE cells were exposed to diluted cinnamon-flavored e-liquids and vaped aerosol and assessed for changes in CBF. hBE cells were subsequently exposed to various concentrations of cinnamaldehyde to establish a dose-response relationship for effects on CBF. Changes in mitochondrial oxidative phosphorylation and glycolysis were evaluated by Seahorse Extracellular Flux Analyzer, and adenine nucleotide levels were quantified by HPLC. Both cinnamaldehyde-containing e-liquid and vaped aerosol rapidly yet transiently suppressed CBF, and exposure to cinnamaldehyde alone recapitulated this effect. Cinnamaldehyde impaired mitochondrial respiration and glycolysis in a dosedependent manner, and intracellular ATP levels were significantly but temporarily reduced following exposure. Addition of nicotine had no effect on the cinnamaldehyde-induced suppression of CBF or mitochondrial function. These data indicate that cinnamaldehyde rapidly disrupts mitochondrial function, inhibits bioenergetic processes, and reduces ATP levels, which correlates with impaired CBF. Because normal ciliary motility and MCC are essential respiratory defenses, inhalation of cinnamaldehyde may increase the risk of respiratory infections in e-cigarette users

Exogenous NG-hydroxy-l-arginine causes nitrite production in vascular smooth muscle cells in the absence of nitric oxide synthase activity

AbstractNitric oxide (NO) production from exogenous NG-hydroxy-l-arginine (OH-l-Arg) was investigated in rat aortic smooth muscle cells in culture by measuring nitrite accumulation in the culture medium. As well, the interaction between OH-l-Arg and l-arginine uptake via the y+ cationic amino acid transporter was studied. In cells without NO-synthase activity, OH-l-Arg (1–1000 μM) induced a dose-dependent nitrite production with a half-maximal effective concentration (EC50) of 18.0 ± 1.5 μM (n = 4–7). This nitrite accumulation was not inhibited by the NO-synthase inhibitor NG-nitro-l-arginine methyl ester, l-NAME (300 μM). In contrast, it was abolished by miconazole (100 μM), an inhibitor of cytochrome P450. Incubation of vascular smooth muscle cells with LPS (10 μgml) induced an l-name inhibited nitrite accumulation, but did not enhance the OH-l-Arg induced nitrite production. OH-l-Arg and other cationic amino acids, L-lysine and l-ornithine, competitively inhibited [3H]-l-arginine uptake m rat aortic smooth muscle cells, with inhibition constants of 195 ± 23 μM(n = 12), 260 ± 40 μM(n= 5) and 330 ± 10 μM(n = 5), respectively. These results show that OH-l-Arg is recognized by the cationic l-amino acid carrier present in vascular smooth muscle cells and can be oxidized to NO and nitrite in these cells in the absence of NO-synthase, probably by cytochrome P450 or by a reaction involving a cytochrome P450 byproduct

Scale issues in soil moisture modelling: problems and prospects

Soil moisture storage is an important component of the hydrological cycle and plays a key role in land-surface-atmosphere interaction. The soil-moisture storage equation in this study considers precipitation as an input and soil moisture as a residual term for runoff and evapotranspiration. A number of models have been developed to estimate soil moisture storage and the components of the soil-moisture storage equation. A detailed discussion of the impli cation of the scale of application of these models reports that it is not possible to extrapolate processes and their estimates from the small to the large scale. It is also noted that physically based models for small-scale applications are sufficiently detailed to reproduce land-surface- atmosphere interactions. On the other hand, models for large-scale applications oversimplify the processes. Recently developed physically based models for large-scale applications can only be applied to limited uses because of data restrictions and the problems associated with land surface characterization. It is reported that remote sensing can play an important role in over coming the problems related to the unavailability of data and the land surface characterization of large-scale applications of these physically based models when estimating soil moisture storage.Yeshttps://us.sagepub.com/en-us/nam/manuscript-submission-guideline