A suite of untargeted methods has been applied for the characterization of aerosol from the Tobacco Heating System 2.2 (THS2.2), a heated tobacco product developed by Philip Morris Products S.A. and commercialized under the brand name IQOS®. A total of 529 chemical constituents, excluding water, glycerin, and nicotine, were present in the mainstream aerosol of THS2.2, generated by following the Health Canada intense smoking regimen, at concentrations ≥ 100 ng/item. The majority were present in the particulate phase (n = 402), representing more than 80% of the total mass determined by untargeted screening; a proportion were present in both particulate and gas-vapor phases (39 compounds). The identities for 80% of all chemical constituents (representing > 96% of the total determined mass) were confirmed by the use of authentic analytical reference materials. Despite the uncertainties that are recognized to be associated with aerosol-based untargeted approaches, the reported data remain indicative that the uncharacterized fraction of TPM generated by THS2.2 has been evaluated to the fullest practicable extent. To the best of our knowledge, this work represents the most comprehensive chemical characterization of a heated tobacco aerosol to date.

BackgroundOnly a few exposure systems are presently available that enable cigarette smoke exposure of living cells at the air–liquid interface, of which one of the most versatile is the Vitrocell® system (Vitrocell® Systems GmbH). To assess its performance and optimize the exposure conditions, we characterized a Vitrocell® 24/48 system connected to a 30-port carousel smoking machine. The Vitrocell® 24/48 system allows for simultaneous exposure of 48 cell culture inserts using dilution airflow rates of 0–3.0 L/min and exposes six inserts per dilution. These flow rates represent cigarette smoke concentrations of 7–100%.ResultsBy characterizing the exposure inside the Vitrocell® 24/48, we verified that (I) the cigarette smoke aerosol distribution is uniform across all inserts, (II) the utility of Vitrocell® crystal quartz microbalances for determining the online deposition of particle mass on the inserts, and (III) the amount of particles deposited per surface area and the amounts of trapped carbonyls and nicotine were concentration dependent. At a fixed dilution airflow of 0.5 L/min, the results showed a coefficient of variation of 12.2% between inserts of the Vitrocell® 24/48 module, excluding variations caused by different runs. Although nicotine and carbonyl concentrations were linear over the tested dilution range, particle mass deposition increased nonlinearly. The observed effect on cell viability was well-correlated with increasing concentration of cigarette smoke.ConclusionsOverall, the obtained results highlight the suitability of the Vitrocell® 24/48 system to assess the effect of cigarette smoke on cells under air–liquid interface exposure conditions, which is closely related to the conditions occurring in human airways.

Tobacco smoke is a complex mixture with over 8700 identified constituents. Smoking causes many diseases including lung cancer, cardiovascular disease, and chronic obstructive pulmonary disease. However, the mechanisms of how cigarette smoke impacts disease initiation or progression are not well understood and individual smoke constituents causing these effects are not generally agreed upon. The studies reported here were part of a series of investigations into the contributions of selected smoke constituents to the biological activity of cigarette smoke. In vitro cytotoxicity measured by the neutral red uptake (NRU) assay and in vitro mutagenicity determined in the Ames bacterial mutagenicity assay (BMA) were selected because these assays are known to produce reproducible, quantitative results for cigarette smoke under standardized exposure conditions. In order to determine the contribution of individual cigarette smoke constituents, a fingerprinting method was developed to semi-quantify the mainstream smoke yields. For cytotoxicity, 90% of gas vapor phase (GVP) cytotoxicity of the Kentucky Reference cigarette 1R4F was explained by 3 aldehydes and 40% of the 1R4F particulate phase cytotoxicity by 10 smoke constituents, e.g., hydroquinone. In the microsuspension version of the BMA, 4 aldehydes accounted for approximately 70% of the GVP mutagenicity. Finally, the benefits of performing such studies along with the difficulties in interpretation in the context of smoking are discussed.

Compound identification is widely recognized as a major bottleneck for modern metabolomic approaches and high-throughput nontargeted characterization of complex matrices. To tackle this challenge, an automated platform entitled computer-assisted structure identification (CASI) was designed and developed in order to accelerate and standardize the identification of compound structures. In the first step of the process, CASI automatically searches mass spectral libraries for matches using a NIST MS Search algorithm, which proposes structural candidates for experimental spectra from two-dimensional gas chromatography with time-of-flight mass spectrometry (GC × GC-TOF-MS) measurements, each with an associated match factor. Next, quantitative structure-property relationship (QSPR) models implemented in CASI predict three specific parameters to enhance the confidence for correct compound identification, which were Kovats Index (KI) for the first dimension (1D) separation, relative retention time for the second dimension separation (2DrelRT) and boiling point (BP). In order to reduce the impact of chromatographic variability on the second dimension retention time, a concept based upon hypothetical reference points from linear regressions of a deuterated n-alkanes reference system was introduced, providing a more stable relative retention time measurement. Predicted values for KI and 2DrelRT were calculated and matched with experimentally derived values. Boiling points derived from 1D separations were matched with predicted boiling points, calculated from the chemical structures of the candidates. As a last step, CASI combines the NIST MS Search match factors (NIST MF) with up to three predicted parameter matches from the QSPR models to generate a combined CASI Score representing the measure of confidence for the identification. Threshold values were applied to the CASI Scores assigned to proposed structures, which improved the accuracy for the classification of true/false positives and true/false negatives. Results for the identification of compounds have been validated, and it has been demonstrated that identification using CASI is more accurate than using NIST MS Search alone. CASI is an easily accessible web-interfaced software platform which represents an innovative, high-throughput system that allows fast and accurate identification of constituents in complex matrices, such as those requiring 2D separation techniques.

Nontargeted screening methodologies are powerful approaches for comprehensive chemical characterization of complex matrixes. In order to maximize chemical space coverage, three analytical methods using two-dimensional gas chromatography with time-of-flight mass spectrometry for nonpolar, polar, and volatile compounds have been established. The structural identification process was streamlined with an in-house developed computer-assisted structure identification platform, which facilitated the identification of novel compounds and also delivered semiquantitative concentrations for all compounds. Key performance parameters for this nontargeted platform, including chemical space coverage, confidence for structural identification, accuracy of semiquantification, and performance of differential analysis, were evaluated. The automated structural identification process was assessed using a subset of 243 compounds (out of 2990), which were confirmed to be present in cigarette smoke using reference standards. Consistently high true positive identification rates between 88.2% and 96.2% across the different concentration ranges investigated were demonstrated. Accuracy for semiquantification was assessed by comparison with quantitative data from literature, where a maximum 4-fold deviation from available targeted analysis values was estimated.