A new reference cigarette, the 3R4F, has been developed to replace the depleting supply of the 2R4F cigarette. The present study was designed to compare mainstream smoke chemistry and toxicity of the two reference cigarettes under the International Organization for Standardization (ISO) machine smoking conditions, and to further compare mainstream smoke chemistry and toxicological activity of the 3R4F cigarette by two different smoking regimens, i.e., the machine smoking conditions specified by ISO and the Health Canada intensive (HCI) smoking conditions.The in vitro cytotoxicity and mutagenicity was determined in the neutral red uptake assay, the Salmonella reverse mutation assay, and the mouse lymphoma thymidine kinase assay. Additionally, a 90-day nose-only inhalation study in rats was conducted to assess the in vivo toxicity. The comparison of smoke chemistry between the two reference cigarettes found practically the same yields of total particulate matter (TPM), ‘tar’, nicotine, carbon monoxide, and most other smoke constituents. For both cigarettes, the in vitro cytotoxicity, mutagenicity, and in vivo toxicity showed the expected smoke-related effects compared to controls without smoke exposure. There were no meaningful differences between the 2R4F and 3R4F regarding these toxicological endpoints. The assessments for the 3R4F cigarette by smoking regimen found as a trivial effect, due to the higher amount of smoke generated per cigarette under HCI conditions, an increased yield of toxicant and higher toxicological activity per cigarette. However, per mg TPM, ‘tar’, or nicotine, the amounts of toxicants and the in vitro toxicity were generally lower under HCI conditions, but the in vivo activity was not different between the two machine smoking conditions. Overall, as the main result, the present study suggests equivalent smoke chemistry and in vitro and in vivo toxicity for the 2R4F and 3R4F reference cigarettes.
While membrane bioreactors (MBR) have proven their large potential to remove bulk organic matter from municipal as well as industrial wastewater, their suitability to remove poorly degradable polar wastewater contaminants is yet unknown. However, this is an important aspect for the achievable effluent quality and in terms of wastewater reuse. We have analyzed two classes of polar sulfur-organic compounds, naphthalene sulfonates and benzothiazoles, by liquid chromatography-electrospray ionization-tandem mass spectrometry (LC-ESI-MS) over a period of 3 weeks in the influent and effluent of a full-scale MBR with external ultrafiltration that treats tannery wastewater. While naphthalene monosulfonates were completely removed, total naphthalene disulfonate removal was limited to about 40%, and total benzothiazoles concentration decreased for 87%. Quantitative as well as qualitative data did not indicate an adaptation to or a more complete removal of these polar aromatic compounds by the MBR as compared to literature data on conventional activated sludge treatment. While quality improvements in receiving waters for bulk organic matter are documented and the same can be anticipated for apolar particle-associated contaminants, these data provide no indication that MBR will improve the removal of polar poorly biodegradable organic pollutants.
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.
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