Multivariate analysis of mainstream tobacco smoke particulate phase by headspace solid-phase micro extraction coupled with comprehensive two-dimensional gas chromatography-time-of-flight mass spectrometry

Novel chemical contaminants associated with thirdhand smoke in settled house dust

Thirdhand smoke (THS) is the persistent and toxic residue from tobacco smoke in indoor environments. A comprehensive understanding of the chemical constituents of THS is necessary to assess the risks of long-term exposure and to establish reliable THS tracers. The objective of this study was to investigate compounds associated with THS through nontargeted analysis (NTA) of settled house dust samples from smokers' and non-smokers' homes, using comprehensive two-dimensional gas chromatography coupled to time-of-flight mass spectrometry (GC×GC/TOF-MS). Compounds that were either only present in dust from smokers' homes or that had significantly larger abundance than in non-smokers' homes were termed qualified compounds. We identified 140 qualified compounds, and of these, 42 compounds were tentatively identified by searching matching mass spectra in NIST electron impact (EI) mass spectral library including 20 compounds confirmed with their authentic standards. Among the 42 compounds, 26 compounds were statistically more abundant (p < 0.10) in dust from homes of smokers; seven were tobacco-specific compounds, two of which (nornicotyrine, 3-ethenylpyridine) have not been reported before in house dust. Two compounds, tris (2-chloroethyl) phosphate (a toxic compound used as a flame retardant and reported in tobacco) and propanoic acid, 2-methyl-, 1-(1,1-dimethylethyl)-2-methyl-1,3-propanediyl ester (highly abundant and reported in exhaled air of smokers), were found in dust from all smokers' homes and in zero non-smokers' homes, making these potential THS tracers, possibly associated with recent smoking. Benzyl methyl ketone was significantly higher in dust in smokers' homes, and was previously reported not as a product of tobacco but rather as a form of methamphetamine. This compound was recently reported in mainstream tobacco smoke condensate through NTA as well. These identified potential tracers and chemical components of THS in this study can be further investigated for use in developing THS contamination and exposure assessments.

Nontargeted Analysis in Tobacco Research: Challenges and Opportunities

Tobacco products are evolving at a pace that has outstripped tobacco control, leading to a high prevalence of tobacco use in the population. Researchers have been tirelessly developing suitable techniques to assess these products' emissions, toxicity, and public health impact. The nonclinical testing of tobacco products to assess the chemical profile of emissions is needed for evidence-based regulations. This testing has largely relied on targeted analytical methods that focus on constituent lists that may fall short in determining the toxicity of newly designed tobacco products. Nontargeted analysis (NTA), or the process of identifying and quantifying compounds within a complex matrix without prior knowledge of its chemical composition, is a promising technique for tobacco regulation, but it is not without challenges. The lack of standardized methods for sample generation, sample preparation, chromatographic separation, compound identification, and data analysis and reporting must be addressed so that the quality and reproducibility of the data generated by NTA can be benchmarked. This review discusses the challenges and highlights the opportunities of NTA in studying tobacco product constituents and emissions.

Fisher ratio feature selection by manual peak area calculations on comprehensive two-dimensional gas chromatography data using standard mixtures with variable composition, storage, and interferences

Comprehensive two-dimensional gas chromatography (GC×GC) is becoming increasingly more common for non-targeted characterization of complex volatile mixtures. The information gained with higher peak capacity and sensitivity provides additional sample composition information when one-dimensional GC is not adequate. GC×GC generates complex multivariate data sets when using non-targeted analysis to discover analytes. Fisher ratio (FR) analysis is applied to discern class markers, limiting complex GC×GC profiles to the most discriminating compounds between classes. While many approaches for feature selection using FR analysis exist, FR can be calculated relatively easily directly on peak areas after any native software has performed peak detection. This study evaluated the success rates of manual FR calculation and comparison to a critical F-value for samples analyzed by GC×GC with defined concentration differences. Long-term storage of samples and other spiked interferences were also investigated to examine their impact on analyzing mixtures using this FR feature selection strategy. Success rates were generally high with mostly 90-100% success rates and some instances of percentages between 80 and 90%. There were rare cases of false positives present and a low occurrence of false negatives. When errors were made in the selection of a compound, it was typically due to chromatographic artifacts present in chromatograms and not from the FR approach itself. This work provides foundational experimental data on the use of manual FR calculations for feature selection from GC×GC data.

Non-targeted analysis of VOCs by HS-SPME-G C/MS coupled with chemometrics as a potential tool for authentication of White Kołuda oat goose

This study tested the possibility of using non-targeted analysis of volatile organic compounds by headspace solid-phase microextraction-gas chromatography-mass spectrometry coupled with chemometrics as a potential tool for differentiating leg meat of oat- and wheat-fed (ad libitum) White Kołuda geese. Thirty-six classification models were obtained for which the correct classification rate and classification accuracy for oatfed and wheat-fed geese were calculated based on a seven-fold cross-validation. Generally, the most advantageous method of the sample preparation was the high-temperature heat treatment version, whereas the highest correct classification rate was obtained when the chemometric analysis was carried out on the female, then male, and finally male + female variant of group comparisons (P<0.01). Furthermore, log-transformation appeared to be a slightly better data preprocessing technique in comparison to systematic ratio normalization. The obtained classification models can potentially differentiate the meat of oat-fattened from wheat-fattened White Kołuda geese.

Tee-Shaped Sample Introduction Device Coupled with Direct Analysis in Real-Time Mass Spectrometry for Gaseous Analytes

Ambient ionization mass spectrometry (AIMS) is simple to operate for analytes adsorbed on the surface of various shaped probes. However, gaseous substances or liquids that are easy to evaporate, diffuse, and escape in the atmosphere are harder to capture. In this work, a Tee-shaped sample introduction device coupled with direct analysis in real time mass spectrometry (DART-MS) is developed. The Tee-shaped device is placed between the DART ion source and the MS inlet with a heated sample transfer tube. Gaseous samples from either a Tedlar sampling bag or liquids evaporated from a graduated syringe were tested. The Tee-shaped device was used for several volatile organic compounds with a wide range of boiling points, and detection limits of ng/mL to fg/mL were obtained. To test the device for real-life samples, puff-by-puff analysis of a complex gaseous mainstream smoke was performed. Individual puffs can be analyzed rapidly, and there is no cross contamination between consecutive puffs. The dynamic changes of chemical components among different puffs for different types of cigarettes can be observed. This work provides a universal Tee-shaped sampling device to enhance AIMS for the analysis of volatile compounds and gases, which is adapted to different sampling modules applicable for various forms of samples. The device enables direct exploration of chemical components in complex gaseous samples without tedious sample preparation and time-consuming LC or GC separation.

The Chemical Complexity of e-Cigarette Aerosols Compared With the Smoke From a Tobacco Burning Cigarette

Background: As e-cigarette popularity has increased, there is growing evidence to suggest that while they are highly likely to be considerably less harmful than cigarettes, their use is not free of risk to the user. There is therefore an ongoing need to characterise the chemical composition of e-cigarette aerosols, as a starting point in characterising risks associated with their use. This study examined the chemical complexity of aerosols generated by an e-cigarette containing one unflavored and three flavored e-liquids. A combination of targeted and untargeted chemical analysis approaches was used to examine the number of compounds comprising the aerosol. Contributions of e-liquid flavors to aerosol complexity were investigated, and the sources of other aerosol constituents sought. Emissions of 98 aerosol toxicants were quantified and compared to those in smoke from a reference tobacco cigarette generated under two different smoking regimes. Results: Combined untargeted and targeted aerosol analyses identified between 94 and 139 compounds in the flavored aerosols, compared with an estimated 72-79 in the unflavored aerosol. This is significantly less complex (by 1-2 orders of magnitude) than the reported composition of cigarette smoke. Combining both types of analysis identified 5-12 compounds over and above those found by untargeted analysis alone. Gravimetrically, 89-99% of the e-cigarette aerosol composition was composed of glycerol, propylene glycol, water and nicotine, and around 3% comprised other, more minor, constituents. Comparable data for the Ky3R4F reference tobacco cigarette pointed to 58-76% of cigarette smoke "tar" being composed of minor constituents. Levels of the targeted toxicants in the e-cigarette aerosols were significantly lower than those in cigarette smoke, with 68.5->99% reductions under ISO 3308 puffing conditions and 88.4->99% reductions under ISO 20778 (intense) conditions; reductions against the WHO TobReg 9 priority list were around 99%. Conclusion: These analyses showed that the e-cigarette aerosols contain fewer compounds and at significantly lower concentrations than cigarette smoke. The chemical diversity of an e-cigarette aerosol is strongly impacted by the choice of e-liquid ingredients.

The effect of different binders on the comprehensive performance of solid phase microextraction fiber

Binders are significant components for the preparation of solid-phase microextraction (SPME) fibers. However, little attention has been paid to the effect of different binders. Considering their diverse properties, in this work, we select three kinds of commonly used binders including polydimethylsiloxane (PDMS), polyacrylonitrile (PAN) and Nafion, as well as introduce a new binder of poly (vinylidene fluoride) (PVDF) to synthetically study the influence of binders. By using the commercial active carbons (ACs) with different binders, four SPME fibers with uniform morphologies and comparative thicknesses (i.e., ACs-PDMS-coated, ACs-PAN-coated, ACs-Nafion-coated and ACs-PVDF-coated fibers) have been prepared successfully. The effect of binders on the pore structure of ACs is firstly investigated. It is found that PDMS and PAN would cause pore blocking, and the specific surface area of ACs coatings decreases from 1362 m² g^-1 to 280 and 196 m² g^-1, respectively. While the specific surface area of ACs-PVDF composite remains 940 m² g^-1. Based on SPME, the influences of acid/alkali, high temperature and matrix towards different fibers are further systematically surveyed. Finally, the enrichment performance of prepared fibers towards various organic pollutants is preliminarily discussed. The comparison results show that PVDF demonstrates outstanding stability in all aspects. Therefore, PVDF might be an excellent candidate for the preparation of SPME fiber. Moreover, all obtained results are expected to provide the reference value for the further development of novel SPME fibers.

Statistical inference of mass channel purity from Fisher ratio analysis using comprehensive two-dimensional gas chromatography with time of flight mass spectrometry data

Tile-based Fisher ratio (F-ratio) analysis has recently been developed and validated for discovery-based studies of highly complex data collected using comprehensive two-dimensional gas chromatography coupled with time-of-flight mass spectrometry (GC×GC-TOFMS). In previous studies, interpretation and utilization of F-ratio hit lists has relied upon manual decomposition and quantification performed by chemometric methods such as parallel factor analysis (PARAFAC), or via manual translation of the F-ratio hit list information to peak table quantitative information provided by the instrument software (ChromaTOF). Both of these quantification approaches are bottlenecks in the overall workflow. In order to address this issue, a more automatable approach to provide accurate relative quantification for F-ratio analyses was investigated, based upon the mass spectral selectivity provided via the F-ratio spectral output. Diesel fuel spiked with 15 analytes at four concentration levels (80, 40, 20, and 10 ppm) produced three sets of two class comparisons that were submitted to tile-based F-ratio analysis to obtain three hit lists, with an F-ratio spectrum for each hit. A novel algorithm which calculates the signal ratio (S-ratio) between two classes (eg., 80 ppm versus 40 ppm) was applied to all mass channels (m/z) in the F-ratio spectrum for each hit. A lack of fit (LOF) metric was utilized as a measure of peak purity and combined with F-ratio and p-values to study the relationship of each of these metrics with m/z purity. Application of a LOF threshold coupled with a p-value threshold yielded a subset of the most pure m/z for each of the 15 spiked analytes, evident by the low deviations (< 5%) in S-ratio relative to the true concentration ratio. A key outcome of this study was to demonstrate the isolation of pure m/z without the need for higher level signal decomposition algorithms.

Identification of Cigarette Brands by Soft Independent Modeling of Class Analogy of Volatile Substances

INTRODUCTION

This study aimed to develop a method for discriminating cigarette brands based on the profiles of volatile components extracted from the tobacco fraction of the finished cigarettes to authenticate branded cigarettes of unknown origin.

METHODS

An analytical method comprising direct thermal desorption coupled with gas chromatography-quadrupole time-of-flight mass spectrometry was developed for acquiring volatile profiles of cigarettes. About 290 samples of commercially available cigarettes were analyzed. Within this batch, 123 samples represented four popular cigarette brands. They were selected for in-depth characterization. Multivariate analysis was used to investigate the interrelations among volatile compounds of cigarettes and to identify characteristic markers for the cigarette discrimination. Supervised pattern recognition techniques were used for designing classification models.

RESULTS

Principal component analysis covering all detected volatiles allowed the differentiation of cigarettes based on the brand. A number of 56 volatile components were identified as markers with high discrimination power. These compounds were used for establishing classification models. A method of soft independent modeling of class analogy developed for the four studied cigarette brands proved to be efficient in the classification of unknown cigarettes, with accuracy between 95.9% and 100%.

CONCLUSIONS

The data evaluation by soft independent modeling of class analogy was highly accurate in classification of unknown cigarettes with a low rate of false positives and false negatives. The developed models can be used for discrimination of genuine from non-genuine products with high level of probability.

IMPLICATIONS

Profiling of volatiles, which is commonly used for authentication of different food commodities, was applied for the characterization of cigarette tobacco for the purpose of authentication a cigarette brand. Volatile components with a high discrimination power were identified by means of multivariate statistical methods and used for establishing of a classification model. The classification model was able to discriminate genuine from non-genuine cigarettes with a high level of prediction accuracy. This model could be a powerful tool for tobacco control to judge the authenticity of cigarettes.

On the benefits of using multivariate analysis in mass spectrometric studies of combustion-generated aerosols

The intricate chemistry of the carbonaceous particle surface layer (which drives their reactivity, environmental and health impacts) results in complex mass spectra. In this respect, detailed molecular-level analysis of combustion emissions may be challenging even with high-resolution mass spectrometry. Building on a recently proposed comprehensive methodology (encompassing all stages from sampling to data reduction), we propose herein a comparative analysis of soot particles produced by three different sources: a miniCAST standard generator, a laboratory diffusion flame and a single cylinder internal combustion engine. The surface composition is probed by either laser or secondary ion mass spectrometry. Two examples of multivariate analysis, Principal component analysis and hierarchical clustering analysis proved their efficiency in both identifying general trends and evidencing subtle differences that otherwise would remain unnoticed in the plethora of data generated during mass spectrometric analyses. Chemical information extracted from these multivariate statistical procedures contributes to a better understanding of fundamental combustion processes and also opens to practical applications such as the tracing of engine emissions.

Comparison of headspace solid-phase microextraction and solvent extraction method for the simultaneous analysis of various soil fumigants in soil or water by gas chromatography-mass spectrometry

The quantity of soil fumigants has increased globally that has focused attention on their environmental behavior. However, simultaneous analysis of traces of fumigant residues is often unreported because analysis methods are not readily available to measure them at low concentrations. In this study, typical solvent extraction methods were compared with headspace solid-phase microextraction methods. Both methods can be used for simultaneously measuring the concentrations of five commonly used soil fumigants in soil or water. The solvent extraction method showed acceptable recovery (76-103%) and intraday relative standard deviations (0.8-11%) for the five soil fumigants. The headspace solid-phase microextraction method also showed acceptable recovery (72-104%) and precision rates (1.3-17%) for the five soil fumigants. The solvent extraction method was more precise and more suitable for analyzing relatively high fumigant residue levels (0.05-5 μg/g) contained in multiple soil samples. The headspace solid-phase microextraction method, however, had a much lower limits of detection (0.09-2.52 μg/kg or μg/L) than the solvent extraction method (5.8-29.2 μg/kg), making headspace solid-phase microextraction most suitable for trace analysis of these fumigants. The results confirmed that the headspace solid-phase microextraction method was more convenient and sensitive for the determination of fumigants to real soil samples.

Profiling Volatilomes: A Novel Forensic Method for Identification of Confiscated Illegal Wildlife Items

Globally, the rapid decline in wildlife species has many causes. The illegal trafficking of fauna and flora is a major contributor to species decline and continues to grow at an alarming rate. To enable the prosecution of those involved in the trafficking of illegal wildlife, accurate and reliable identification is paramount. Traditionally, morphology and DNA amplification are used. This paper investigates a novel application of volatilome profiling using comprehensive two-dimensional gas chromatography coupled with time of flight mass spectrometry for wildlife sample detection. Known samples of elephant-derived ivory, other dentine samples, and bone (a common ivory substitute) were used as reference samples for volatilome profiling. Subsequently, specimens that were suspected ivory from border control seizures were obtained and analysed. Confirmatory DNA analyses were conducted on seized samples to establish the reliability parameters of volatilome profiling. The volatilome method correctly identified six of the eight seized samples as elephant ivory, which was confirmed through DNA analysis. There was also clear distinction of African elephant ivory parts from the bone and dentine samples from other species, as shown through PCA and discriminant analyses. These preliminary results establish volatilome profiling through GC×GC-TOFMS as a novel screening method used for the identification of unknown wildlife contraband.

Gradual Optimization of Headspace Solid-Phase Microextraction Conditions of Volatiles in Pepper Chicken Soup Combined with Gas Chromatography-Mass Spectrometry and Principal Component Analysis

A single-factor gradual optimization method was developed in this experiment in order to improve the headspace solid-phase microextraction (HS-SPME) effect of volatile compounds in pepper chicken soup. The different extraction conditions included fibers with different coating materials, sample volume, extraction temperature, and extraction time. The total peak areas and the numbers of valid peaks were compared and analyzed as the indicators of condition optimization. Gas chromatography-mass spectrometry (GC-MS) results showed that the four factors all have significant impact on the extraction effect of volatiles in pepper chicken soup. Using the principal component analysis (PCA), the optimal conditions of HS-SPME were inferred below: an extraction fiber of 50/30μm DVB/CAR/PDMS, a sample volume of 7 g, an extraction temperature of 65°C, and an extraction time of 30 min. Compared to the original extraction conditions, the optimized conditions were especially advantageous for the comprehensive analysis of volatiles, which could be potentially used in further study of soup.

Comprehensive comparative compositional study of the vapour phase of cigarette mainstream tobacco smoke and tobacco heating product aerosol

A simple direct sample collection/dilution and introduction method was developed using quartz wool and Tenax/sulficarb sorbents for thermal desorption and comprehensive two-dimensional gas chromatography (TD-GC × GC) analyses of volatile organic compounds from vapour phase (VP) fractions of aerosol produced by tobacco heating products (THP1.0) and 3R4F mainstream tobacco smoke (MTS). Analyses were carried out using flame ionisation detection (FID) for semi-quantification and both low and high resolution time-of-flight mass spectrometry (LR/HR-TOFMS) for qualitative comparison and peak assignment. Qualitative analysis was carried out by combining identification data based on linear retention indices (LRIs) with a match window of ±10 index units, mass spectral forward and reverse library searches (from LR and HRTOFMS spectra) with a match factor threshold of >700 (both forward and reverse), and accurate mass values of ± 3 ppm for increased confidence in peak identification. Using this comprehensive approach of data mining, a total of 79 out of 85 compounds and a total of 198 out of 202 compounds were identified in THP1.0 aerosol and in 3R4F MTS, respectively. Among the identified analytes, a set of 35 compounds was found in both VP sample types. Semi-quantitative analyses were carried out using a chemical class-based external calibration method. Acyclic, alicyclic, aromatic hydrocarbons and ketones appeared to be prominent in 3R4F MTS VP, whereas larger amounts of aldehydes, ketones, heterocyclic hydrocarbons and esters were present in THP1.0 aerosol VP. The results demontsrate the capability and versatility of the method for the characterization and comparison of complex aerosol samples and highlighted the relative chemical simplicity of THP1.0 aerosol in comparison to MTS.

Developing a Method for the Collection and Analysis of Burnt Remains for the Detection and Identification of Ignitable Liquid Residues Using Body Bags, Dynamic Headspace Sampling, and TD-GC×GC-TOFMS

In cases of suspected arson, a body may be intentionally burnt to cause loss of life, dispose of remains, or conceal identification. A primary focus of a fire investigation, particularly involving human remains, is to establish the cause of the fire; this often includes the forensic analysis of fire debris for the detection of ignitable liquid residues (ILRs). Commercial containers for the collection of fire debris evidence include metal cans, glass jars, and polymer/nylon bags of limited size. This presents a complication in cases where the fire debris consists of an intact, or partially intact, human cadaver. This study proposed the use of a body bag as an alternative sampling container. A method was developed and tested for the collection and analysis of ILRs from burnt porcine remains contained within a body bag using dynamic headspace sampling (using an Easy-VOC™ hand-held manually operated grab-sampler and stainless steel sorbent tubes containing Tenax TA) followed by thermal desorption comprehensive two-dimensional gas chromatography–time-of-flight mass spectrometry (TD-GC×GC-TOFMS). The results demonstrated that a body bag containing remains burnt with gasoline tested positive for the presence of gasoline, while blank body bag controls and a body bag containing remains burnt without gasoline tested negative. The proposed method permits the collection of headspace samples from burnt remains before the remains are removed from the crime scene, limiting the potential for contamination and the loss of volatiles during transit and storage.

Identification of key odorants responsible for chestnut-like aroma quality of green teas

A chestnut-like aroma is widely considered an important indicator of an excellent-quality green tea; however, the key odorants responsible for chestnut-like aroma have never been systematically studied and remain unknown. In this study, the aroma components of green teas and Chinese chestnuts were analyzed using comprehensive two-dimensional gas chromatography-time-of-flight mass spectrometry (GC × GC-TOFMS), and 58 compounds were identified as common aroma components among green teas, boiled Chinese chestnuts, roasted Chinese chestnuts and raw Chinese chestnuts. Subsequently, 17 volatiles, including 3-methylbutanal, (E)-3-penten-2-one, ethylbenzene, heptanal, benzaldehyde, 2-pentylfuran, octanal, benzeneacetaldehyde, (E)-2-octenal, (E,E)-3,5-octadien-2-one, linalool, nonanal, (E)-2-nonenal, decanal, (Z)-hex-3-en-1-yl hexanoate, trans-β-ionone and (E)-nerolidol, were identified as the key odorants responsible for chestnut-like aroma based on the odor activity value (OAV) calculation method. Besides, the comparison of OAVs of key odorants between fresh tea leaves and finished teas indicated that all key odorants were present in fresh tea leaves and that their contents increased or decreased during tea processing. Moreover, the comparison between results of OAV and gas chromatography-olfactometry (GC-O) methods showed that ethylbenzene, heptanal, benzaldehyde, 2-pentylfuran, (E,E)-3,5-octadien-2-one, linalool, (Z)-hex-3-en-1-yl hexanoate and trans-β-ionone were the common identified compounds between the two methods. The identification of chestnut-like aroma in green teas will provide a theoretical basis for further research on the directional adjustment and control of tea aroma quality.

Thermal desorption comprehensive two-dimensional gas chromatography coupled to time of flight mass spectrometry for vapour phase mainstream tobacco smoke analysis

A thermal desorption comprehensive two-dimensional gas chromatography coupled to time-of-flight mass spectrometry (TD-GC×GC-TOFMS) method has been developed for the analysis of mainstream tobacco smoke (MTS) vapour phase (VP). The selection process of the sample introduction approach involved comparing the results obtained from three different approaches: a) use of gas sampling bag followed by SPME (Tedlar®-SPME), b) gas sampling bag followed by TD (Tedlar®-TD), and c) sampling directly on TD sorbents (Direct-TD). Six different SPME fibers and six different TD sorbent beds were evaluated for the extraction capacities in terms of total number of peaks and related intensities or peak areas. The best results were obtained for the Direct-TD approach using Tenax TA/Carbograph1TD/Carboxen1003 sorbent tubes. The optimisation of TD tube desorption parameters was carried out using a face-centered central composite experimental design and resulted in the use of the Tenax TA/Carbograph 1TD/Carboxen 1003 sorbent with a 7.5min desorption time, a 60mL/min tube desorption flow, and a 250°C tube desorption temperature. The optimised method was applied to the separation of MTS-VP constituents, with 665 analytes detected. The method precision ranged from 1% to 15% for over 99% of identified peak areas and from 0% to 3% and 0% to 1% for both first (1tR) and second (2tR) dimension retention times, respectively. The method was applied to the analyses of two cigarette types differing in their filter construction. Principal component analysis (PCA) allowed a clear differentiation of the studied cigarette types (PC1 describing 94% of the explained variance). Supervised Fisher ratio analysis permitted the identification of compounds responsible for the chemical differences between the two sample types. A set of 91 most relevant compounds was selected by applying a Fisher ratio cut-off approach and most of them were selectively removed by one of the cigarette filter types.

Headspace solid-phase microextraction coupled to comprehensive two-dimensional gas chromatography-time-of-flight mass spectrometry for the analysis of aerosol from tobacco heating product

A method involving headspace solid-phase microextraction (HS-SPME) and comprehensive two-dimensional gas chromatography coupled to time-of-flight mass spectrometry (GC×GC-TOFMS) was developed and optimised to elucidate the volatile composition of the particulate phase fraction of aerosol produced by tobacco heating products (THPs). Three SPME fiber types were studied in terms of extraction capacity and precision measurements. Divinylbenzene polydimethylsiloxane appeared as the most efficient coating for these measurements. A central composite design of experiment was utilised for the optimization of the extraction conditions. Qualitative and semi-quantitative analysis of the headspace above THP aerosol condensate was carried out using optimised extraction conditions. Semi-quantitative analyses of detected constituents were performed by assuming that their relative response factors to the closest internal standard (itR) were equal to 1. Using deconvoluted mass spectral data (library similarity and reverse match >750) and linear retention indices (match window of ±15 index units), 205 peaks were assigned to individual compounds, 82 of which (including 43 substances previously reported to be present in tobacco) have not been reported previously in tobacco aerosol. The major volatile fraction of the headspace contained ketones, alcohols, aldehydes, alicyclic hydrocarbons alkenes, and alkanes. The method was further applied to compare the volatiles from the particulate phase of aerosol composition of THP with that of reference cigarette smoke and showed that the THP produced a less complex chemical mixture. This new method showed good efficiency and precision for the peak areas and peak numbers from the volatile fraction of aerosol particulate phase for both THP and reference cigarettes.

Advanced method optimization for volatile aroma profiling of beer using two-dimensional gas chromatography time-of-flight mass spectrometry

The complex mixture of volatile organic compounds (VOCs) present in the headspace of Trappist and craft beers was studied to illustrate the efficiency of thermal desorption (TD) comprehensive two-dimensional gas chromatography time-of-flight mass spectrometry (GC×GC-TOFMS) for highlighting subtle differences between highly complex mixtures of VOCs. Headspace solid-phase microextraction (HS-SPME), multiple (and classical) stir bar sorptive extraction (mSBSE), static headspace (SHS), and dynamic headspace (DHS) were compared for the extraction of a set of 21 representative flavor compounds of beer aroma. A Box-Behnken surface response methodology experimental design optimization (DOE) was used for convex hull calculation (Delaunay's triangulation algorithms) of peak dispersion in the chromatographic space. The predicted value of 0.5 for the ratio between the convex hull and the available space was 10% higher than the experimental value, demonstrating the usefulness of the approach to improve optimization of the GC×GC separation. Chemical variations amongst aligned chromatograms were studied by means of Fisher Ratio (FR) determination and F-distribution threshold filtration at different significance levels (α=0.05 and 0.01) and based on z-score normalized area for data reduction. Statistically significant compounds were highlighted following principal component analysis (PCA) and hierarchical cluster analysis (HCA). The dendrogram structure not only provided clear visual information about similarities between products but also permitted direct identification of the chemicals and their relative weight in clustering. The effective coupling of DHS-TD-GC×GC-TOFMS with PCA and HCA was able to highlight the differences and common typical VOC patterns among 24 samples of different Trappist and selected Canadian craft beers.

Optimizing Mass Spectrometry Analyses: A Tailored Review on the Utility of Design of Experiments

Mass spectrometry (MS) has emerged as a tool that can analyze nearly all classes of molecules, with its scope rapidly expanding in the areas of post-translational modifications, MS instrumentation, and many others. Yet integration of novel analyte preparatory and purification methods with existing or novel mass spectrometers can introduce new challenges for MS sensitivity. The mechanisms that govern detection by MS are particularly complex and interdependent, including ionization efficiency, ion suppression, and transmission. Performance of both off-line and MS methods can be optimized separately or, when appropriate, simultaneously through statistical designs, broadly referred to as "design of experiments" (DOE). The following review provides a tutorial-like guide into the selection of DOE for MS experiments, the practices for modeling and optimization of response variables, and the available software tools that support DOE implementation in any laboratory. This review comes 3 years after the latest DOE review (Hibbert DB, 2012), which provided a comprehensive overview on the types of designs available and their statistical construction. Since that time, new classes of DOE, such as the definitive screening design, have emerged and new calls have been made for mass spectrometrists to adopt the practice. Rather than exhaustively cover all possible designs, we have highlighted the three most practical DOE classes available to mass spectrometrists. This review further differentiates itself by providing expert recommendations for experimental setup and defining DOE entirely in the context of three case-studies that highlight the utility of different designs to achieve different goals. A step-by-step tutorial is also provided.

In vitro volatile organic compound profiling using GC×GC-TOFMS to differentiate bacteria associated with lung infections: a proof-of-concept study

Chronic pulmonary infections are the principal cause of morbidity and mortality in individuals with cystic fibrosis (CF). Due to the polymicrobial nature of these infections, the identification of the particular bacterial species responsible is an essential step in diagnosis and treatment. Current diagnostic procedures are time-consuming, and can also be expensive, invasive and unpleasant in the absence of spontaneously expectorated sputum. The development of a rapid, non-invasive methodology capable of diagnosing and monitoring early bacterial infection is desired. Future visions of real-time, in situ diagnosis via exhaled breath testing rely on the differentiation of bacteria based on their volatile metabolites. The objective of this proof-of-concept study was to investigate whether a range of CF-associated bacterial species (i.e. Pseudomonas aeruginosa, Burkholderia cenocepacia, Haemophilus influenzae, Stenotrophomonas maltophilia, Streptococcus pneumoniae and Streptococcus milleri) could be differentiated based on their in vitro volatile metabolomic profiles. Headspace samples were collected using solid phase microextraction (SPME), analyzed using comprehensive two-dimensional gas chromatography-time-of-flight mass spectrometry (GC×GC-TOFMS) and evaluated using principal component analysis (PCA) in order to assess the multivariate structure of the data. Although it was not possible to effectively differentiate all six bacteria using this method, the results revealed that the presence of a particular pattern of VOCs (rather than a single VOC biomarker) is necessary for bacterial species identification. The particular pattern of VOCs was found to be dependent upon the bacterial growth phase (e.g. logarithmic versus stationary) and sample storage conditions (e.g. short-term versus long-term storage at  -18 °C). Future studies of CF-associated bacteria and exhaled breath condensate will benefit from the approaches presented in this study and further facilitate the production of diagnostic tools for the early detection of bacterial lung infections.

Establishing the volatile profile of pig carcasses as analogues for human decomposition during the early postmortem period

Following a mass disaster, it is important that victims are rapidly located as the chances of survival decrease greatly after approximately 48 h. Urban search and rescue (USAR) teams may use a range of tools to assist their efforts but detector dogs still remain one of the most effective search tools to locate victims of mass disasters. USAR teams can choose to deploy human scent dogs (trained to locate living victims) or human remains detection (HRD) dogs (trained to locate deceased victims). However, little is known about the variation between live human scent and postmortem human remains scent and the timeframe during which one type of scent transitions to the other. The aim of the current study was to measure the change in the scent profile of human decomposition analogues during the first 72 h postmortem by measuring the volatile organic compounds (VOCs) that comprise the odour. Three pig carcasses (Sus scrofa domesticus L.) were placed on a soil surface and allowed to decompose under natural conditions. Decomposition odour was sampled frequently up to 75 h postmortem and analysed using comprehensive two-dimensional gas chromatography - time-of-flight mass spectrometry (GC×GC-TOFMS). A total of 105 postmortem VOCs were identified during the early postmortem period. The VOC profile during the early postmortem period was highly dynamic, changing both hourly and daily. A transition period was observed after 43 h postmortem, where the VOC profile appeared to shift from a distinct antemortem odour to a more generalised postmortem odour. These findings are important in informing USAR teams and their use of detector dogs for disaster victim recovery.

Identification of New and Distinctive Exposures from Little Cigars

Little cigar mainstream smoke is less well-characterized than cigarette mainstream smoke in terms of chemical composition. This study compared four popular little cigar products against four popular cigarette products to determine compounds that are either unique to or more abundant in little cigars. These compounds are categorized as new or distinctive exposures, respectively. Total particulate matter samples collected from machine-generated mainstream smoke were extracted with methylene chloride, and the extracts were analyzed using two-dimensional gas chromatography-time-of-flight mass spectrometry. The data were evaluated using novel data-processing algorithms that account for characteristics specific to the selected analytical technique and variability associated with replicate sample analyses. Among more than 25 000 components detected across the complete data set, ambrox was confirmed as a new exposure, and 3-methylbutanenitrile and 4-methylimidazole were confirmed as distinctive exposures. Concentrations of these compounds for the little cigar mainstream smoke were estimated at approximately 0.4, 0.7, and 12 μg/rod, respectively. In achieving these results, this study has demonstrated the capability of a powerful analytical approach to identify previously uncharacterized tobacco-related exposures from little cigars. The same approach could also be applied to other samples to characterize constituents associated with tobacco product classes or specific tobacco products of interest. Such analyses are critical in identifying tobacco-related exposures that may affect public health.