Degradation of gaseous hydrocarbons in aerated stirred bioreactors inoculated with Rhodococcus erythropolis: Effect of the carbon source and SIFT-MS method development.

The study of microbial hydrocarbons removal is of great importance for the development of future bioremediation strategies. In this study, we evaluated the removal of a gaseous mixture containing toluene, m-xylene, ethylbenzene, cyclohexane, butane, pentane, hexane and heptane in aerated stirred bioreactors inoculated with Rhodococcus erythropolis and operated under non-sterile conditions. For the real-time measurement of hydrocarbons, a novel systematic approach was implemented using Selected-Ion Flow Tube Mass Spectrometry (SIFT-MS). The effect of the carbon source (∼9.5 ppmv) on (i) the bioreactors' performance (BR1: dosed with only cyclohexane as a single hydrocarbon versus BR2: dosed with a mixture of the 8 hydrocarbons) and (ii) the evolution of microbial communities over time were investigated. The results showed that cyclohexane reached a maximum removal efficiency (RE) of 53% ± 4% in BR1. In BR2, almost complete removal of toluene, m-xylene and ethylbenzene, being the most water-soluble and easy-to-degrade carbon sources, was observed. REs below 32% were obtained for the remaining compounds. By exposing the microbial consortium to only the five most recalcitrant hydrocarbons, REs between 45% ± 5% and 98% ± 1% were reached. In addition, we observed that airborne microorganisms populated the bioreactors and that the type of carbon source influenced the microbial communities developed. The abundance of species belonging to the genus Rhodococcus was below 10% in all bioreactors at the end of the experiments. This work provides fundamental insights to understand the complex behavior of gaseous hydrocarbon mixtures in bioreactors, along with a systematic approach for the development of SIFT-MS methods.

High and low pathogenicity avian influenza virus discrimination and prediction based on volatile organic compounds signature by SIFT-MS: a proof-of-concept study.

High and low pathogenicity avian influenza viruses (HPAIV, LPAIV) are the primary causes of poultry diseases worldwide. HPAIV and LPAIV constitute a major threat to the global poultry industry. Therefore, early detection and well-adapted surveillance strategies are of the utmost importance to control the spread of these viruses. Volatile Organic Compounds (VOCs) released from living organisms have been investigated over the last decades as a diagnostic strategy. Mass spectrometry instruments can analyze VOCs emitted upon viral infection. Selected ion flow tube mass spectrometry (SIFT-MS) enables direct analysis of cell headspace in less than 20 min. As a proof-of-concept study, we investigated the ability of a SIFT-MS coupled sparse Partial Least Square-Discriminant Analysis analytical workflow to discriminate IAV-infected cells. Supernatants of HPAIV, LPAIV, and control cells were collected from 1 to 72 h post-infection and analyzed using our analytical workflow. At each collection point, VOCs' signatures were first identified based on four independent experiments and then used to discriminate the infectious status of external samples. Our results indicate that the identified VOCs signatures successfully discriminate, as early as 1-h post-infection, infected cells from the control cells and differentiated the HPAIV from the LPAIV infection. These results suggest a virus-dependent VOCs signature. Overall, the external samples' status was identified with 96.67% sensitivity, 100% specificity, and 97.78% general accuracy.

Investigation of odor pollution by utilizing selected ion flow tube mass spectrometry (SIFT-MS) and principal component analysis (PCA).

Odor pollution, also referred to as odor nuisance, is a growing environmental concern that is significantly associated with mental health. Once emitted into the air, the concentration of odorous substances varies considerably with wind conditions, leading to difficulties in timely sampling. In the present study, we employed selected ion flow tube mass spectrometry (SIFT-MS) to measure 22 odor-producing molecules continuously in an urban-rural complex city. In addition, we applied statistical analyses, principal component analysis (PCA), and a conditional probability function (CPF) to the datasets obtained from SIFT-MS to identify the odor characteristics at two study sites. At site A, odorants related to livestock farming and industry showed high factor loadings on principal components (PCs) from the PCA. In contrast, we estimated that the odorous gaseous chemicals affecting site B were closely related to sewage treatment and municipal solid waste disposal. Similar CPF patterns of grouped substances from the PCA supported the association between potential odor sources and specific odorants at site B, which helped estimate possible source locations. Consequently, our findings indicate that continuous monitoring of odorous substances using SIFT-MS can be an effective way to provide sufficient information on odor-producing molecules, leading to the clear identification of odor characteristics despite the high variability of odorous substances.

Non-destructive egg breed separation using advanced VOC analytical techniques HSSE-GC-MS, PTR-TOF-MS, and SIFT-MS: Assessment of performance and systems' complementarity.

Over the past decade, advanced analytical techniques have been utilized to examine volatile organic compounds (VOCs) in eggs. These VOCs offer valuable insights into factors such as freshness, fertility, the presence of cracks, embryo sex, and breed. In our study, we assessed three mass spectrometry-based systems (headspace sorptive extraction gas chromatography-mass spectrometry; HSSE-GC-MS, proton transfer reaction time-of-flight-mass spectrometry; PTR-TOF-MS; and selected ion flow tube mass spectrometry; SIFT-MS) to analyze and identify VOCs present in intact hatching eggs from three distinct breeds (Dekalb white layer, Shaver brown layer, and Ross 308 broiler). The eggs were sampled on incubation days 2 and 8, to identify VOCs that distinguish breeds irrespective of incubation day. VOC measurements were conducted on 15 eggs per breed by placing them together with PDMS-coated stir bars inside inert Teflon® air sampling bags. After an accumulation period of 2 h, the headspace was analyzed using PTR-TOF-MS and SIFT-MS, while the VOCs adsorbed onto the stir bars were analyzed using GC-MS for additional compound identification. Partial least squares discriminant analysis (PLS-DA) models were constructed for breed differentiation, and variable selection was performed. As a result, 111 VOCs were identified using HSSE-GC-MS, with alcohols and esters being the most abundant. The PLS-DA models demonstrated the efficacy of breed discrimination, with the HSSE-GC-MS and the PTR-TOF-MS exhibiting the highest balanced accuracy of 95.5 % using a reduced set of 11 VOCs and 5 product ions, respectively. The SIFT-MS model had a balanced accuracy of 92.8 % with a reduced set of 11 product ions. Furthermore, complementarity was observed between HSSE-GC-MS, which primarily selected higher molecular weight VOCs, and PTR-TOF-MS and SIFT-MS. A higher correlation was found for compound abundances between the HSSE-GC-MS and the PTR-TOF-MS relative to the SIFT-MS, indicating that the PTR-TOF-MS was better suited to quantify specific compounds identified by the HSSE-GC-MS. Finally, the findings support the presence of VOCs originating from both synthetic and natural sources, highlighting the ability of the VOC analysis systems to non-destructively perform quality control and reveal differences in management practices or biological information encoded in eggs.

Addition of (bio)surfactants in the biofiltration of hydrophobic volatile organic compounds in air.

The removal of volatile organic compounds (VOCs) in air is of utmost importance to safeguard both environmental quality and human well-being. However, the low aqueous solubility of hydrophobic VOCs results in poor removal in waste gas biofilters (BFs). In this study, we evaluated the addition of (bio)surfactants in three BFs (BF1 and BF2 mixture of compost and wood chips (C + WC), and BF3 filled with expanded perlite) to enhance the removal of cyclohexane and hexane from a polluted gas stream. Experiments were carried out to select two (bio)surfactants (i.e., Tween 80 and saponin) out of five (sodium dodecyl sulfate (SDS), Tween 80, surfactin, rhamnolipid and saponin) from a physical-chemical (i.e., decreasing VOC gas-liquid partitioning) and biological (i.e., the ability of the microbial consortium to grow on the (bio)surfactants) point of view. The results show that adding Tween 80 at 1 critical micelle concentration (CMC) had a slight positive effect on the removal of both VOCs, in BF1 (e.g., 7.0 ± 0.6 g cyclohexane m-3 h-1, 85 ± 2% at 163 s; compared to 6.7 ± 0.4 g cyclohexane m-3 h-1, 76 ± 2% at 163 s and 0 CMC) and BF2 (e.g., 4.3 ± 0.4 g hexane m-3 h-1, 27 ± 2% at 82 s; compared to 3.1 ± 0.7 g hexane m-3 h-1, 16 ± 4% at 82 s and 0 CMC), but a negative effect in BF3 at either 1, 3 and 9 CMC (e.g., 2.4 ± 0.4 g hexane m-3 h-1, 30 ± 4% at 163 s and 1 CMC; compared to 4.6 ± 1.0 g hexane m-3 h-1, 43 ± 8% at 163 s and 0 CMC). In contrast, the performance of all BFs improved with the addition of saponin, particularly at 3 CMC. Notably, in BF3, the elimination capacity (EC) and removal efficiency (RE) doubled for both VOCs (i.e., 9.1 ± 0.6 g cyclohexane m-3 h-1, 49 ± 3%; 4.3 ± 0.3 g hexane m-3 h-1, 25 ± 3%) compared to no biosurfactant addition (i.e., 4.5 ± 0.4 g cyclohexane m-3 h-1, 23 ± 3%; hexane 2.2 ± 0.5 g m-3 h-1, 10 ± 2%) at 82 s. Moreover, the addition of the (bio)surfactants led to a shift in the microbial consortia, with a different response in BF1-BF2 compared to BF3. This study evaluates for the first time the use of saponin in BFs, it demonstrates that cyclohexane and hexane RE can be improved by (bio)surfactant addition, and it provides recommendations for future studies in this field.

Effect of pH, Reducing Sugars, and Protein on Roasted Sunflower Seed Aroma Volatiles.

Sunflower seeds are a popular snack in many countries, such as the United States, China, and Spain. Sunflower seeds are typically roasted to create desirable aromas before being eaten. The desirable aromas are created by the Maillard and lipid oxidation reactions. Increasing the volatiles created by these reactions can create a more desirable product, increasing consumer acceptance of sunflower seeds. Seeds were soaked in solutions at pH 4, 7, and 9 and with added glucose, fructose, whey protein isolate, or whey protein concentrate before roasting. The resulting seeds were evaluated by selected-ion flow tube mass spectrometry to determine the volatile concentrations and by an untrained panel of consumers to determine acceptability. Increasing the pH increased the pyrazines but did not affect other volatiles. Adding reducing sugars or whey protein increased most volatiles. The fructose increased dimethylpyrazines, 2-methylpyrazine, and trimethylpyrazine concentrations more than glucose. However, the glucose increased furfural concentration more than fructose. The whey protein concentrate increased volatile levels more than any other treatment. The total Maillard volatiles and Browning index were increased by the same treatments. Sensory indicated that fructose increased desirable aroma the most, followed by whey protein treatments, and both were liked more than the pH 7 control. Optimizing roasting conditions by increasing the pH and reducing sugar and protein content can favor the Maillard reaction conditions, increasing the positive aromas associated with roasted sunflower seeds.

Robust Automated SIFT-MS Quantitation of Volatile Compounds in Air Using a Multicomponent Gas Standard.

Selected ion flow tube mass spectrometry, SIFT-MS, has been widely used in industry and research since its introduction in the mid-1990s. Previously described quantitation methods have been advanced to include a gas standard for a more robust and repeatable analytical performance. The details of this approach to calculate the concentrations from ion-molecule reaction kinetics based on reaction times and instrument calibration functions determined from known concentrations in the standard mix are discussed. Important practical issues such as the overlap of product ions are outlined, and best-practice approaches are presented to enable them to be addressed during method development. This review provides a fundamental basis for a plethora of studies in broad application areas that are possible with SIFT-MS instruments.

Effect of inoculum type, packing material and operational conditions on the biofiltration of a mixture of hydrophobic volatile organic compounds in air.

The emission of volatile organic compounds (VOCs) into the atmosphere causes negative environmental and health effects. Biofiltration is known to be an efficient and cost-effective treatment technology for the removal of VOCs in waste gas streams. However, little is known on the removal of VOC mixtures and the effect of operational conditions, particularly for hydrophobic VOCs, and on the microbial populations governing the biofiltration process. In this study, we evaluated the effect of inoculum type (acclimated activated sludge (A-AS) versus Rhodococcus erythropolis) and packing material (mixture of compost and wood chips (C + WC) versus expanded perlite) on the removal of a mixture of hydrophobic VOCs (toluene, cyclohexane and hexane) in three biofilters (BFs), i.e., BF1: C + WC and R. erythropolis; BF2: C + WC and A-AS; and BF3: expanded perlite and R. erythropolis. The BFs were operated for 374 days at varying inlet loads (ILs) and empty bed residence times (EBRTs). The results showed that the VOCs were removed in the following order: toluene > cyclohexane > hexane, which corresponds to their air-water partitioning coefficient and thus bioavailability of each VOC. Toluene is the most hydrophilic VOC, while hexane is the most hydrophobic. BF2 outperformed BF1 and BF3 in each operational phase, with average maximum elimination capacities (ECmax) of 21 ± 3 g toluene m-3 h-1 (removal efficiency (RE): 100 %; EBRT: 82 s), 11 ± 2 g cyclohexane m-3 h-1 (RE: 86 ± 6 %; EBRT: 163 s) and 6.2 ± 0.9 g hexane m-3 h-1 (RE: 96 ± 4 %; EBRT: 245 s). Microbial analysis showed that despite having different inocula, the genera Rhodococcus, Mycobacterium and/or Pseudonocardia dominated in all BFs but at different relative abundances. This study provides new insights into the removal of difficult-to-degrade VOC mixtures with limited research to date on biofiltration.

Breath analysis combined with cardiopulmonary exercise testing and echocardiography for monitoring heart failure patients: the AEOLUS protocol.

This paper describes the AEOLUS pilot study which combines breath analysis with cardiopulmonary exercise testing (CPET) and an echocardiographic examination for monitoring heart failure (HF) patients. Ten consecutive patients with a prior clinical diagnosis of HF with reduced left ventricular ejection fraction were prospectively enrolled together with 15 control patients with cardiovascular risk factors, including hypertension, type II diabetes or chronic ischemic heart disease. Breath samples were collected at rest and during CPET coupled with exercise stress echocardiography (CPET-ESE) protocol by means of needle trap micro-extraction and were analyzed through gas-chromatography coupled with mass spectrometry. The protocol also involved using of a selected ion flow tube mass spectrometer for a breath-by-breath isoprene and acetone analysis during exercise. At rest, HF patients showed increased breath levels of acetone and pentane, which are related to altered oxidation of fatty acids and oxidative stress, respectively. A significant positive correlation was observed between acetone and the gold standard biomarker NT-proBNP in plasma (r= 0.646,p< 0.001), both measured at rest. During exercise, some exhaled volatiles (e.g., isoprene) mirrored ventilatory and/or hemodynamic adaptation, whereas others (e.g., sulfide compounds and 3-hydroxy-2-butanone) depended on their origin. At peak effort, acetone levels in HF patients differed significantly from those of the control group, suggesting an altered myocardial and systemic metabolic adaptation to exercise for HF patients. These preliminary data suggest that concomitant acquisition of CPET-ESE and breath analysis is feasible and might provide additional clinical information on the metabolic maladaptation of HF patients to exercise. Such information may refine the identification of patients at higher risk of disease worsening.

Selected-ion flow-tube mass spectrometry for the identification of volatile spoilage markers for fresh pork packaged under modified atmospheres.

Microbial behavior during meat storage leads to the generation of volatile organic compounds (VOCs) and unpleasant off-odors. This study focused on a novel real-time analytical method, selected-ion flow-tube mass spectrometry (SIFT-MS), to monitor VOC quality and identify spoilage indicators for fresh pork stored under different packaging atmospheres (air, 70/0/30, 70/30/0, 5/30/65, 0/30/70 - v/v% O2/CO2/N2) at 4 °C. A comprehensive selection methodology was used to identify compounds with good instrumental data quality as well as a strong relationship with microbial growth and olfactory rejection. Based on the volatolome quantified by SIFT-MS, storage periods and conditions can be discriminated using multivariate statistics. Acetoin (or ethyl acetate) represented a significant pork quality marker for high-O2 conditions, whereas ethanol, 3-methylbutanal and sulfur compounds can indicate the anaerobic storage progress. Considering the applicability in monitoring different VOC profiles, SIFT-MS is expected to be promising in many storage scenarios to improve analytical efficiency and ensure reliability.

Recent developments and applications of selected ion flow tube mass spectrometry (SIFT-MS).

Selected ion flow tube mass spectrometry (SIFT-MS) is now recognized as the most versatile analytical technique for the identification and quantification of trace gases down to the parts-per-trillion by volume, pptv, range. This statement is supported by the wide reach of its applications, from real-time analysis, obviating sample collection of very humid exhaled breath, to its adoption in industrial scenarios for air quality monitoring. This review touches on the recent extensions to the underpinning ion chemistry kinetics library and the alternative challenge of using nitrogen carrier gas instead of helium. The addition of reagent anions in the Voice200 series of SIFT-MS instruments has enhanced the analytical capability, thus allowing analyses of volatile trace compounds in humid air that cannot be analyzed using reagent cations alone, as clarified by outlining the anion chemistry involved. Case studies are reviewed of breath analysis and bacterial culture volatile organic compound (VOC), emissions, environmental applications such as air, water, and soil analysis, workplace safety such as transport container fumigants, airborne contamination in semiconductor fabrication, food flavor and spoilage, drugs contamination and VOC emissions from packaging to demonstrate the stated qualities and uniqueness of the new generation SIFT-MS instrumentation. Finally, some advancements that can be made to improve the analytical capability and reach of SIFT-MS are mentioned.

Long-term biofiltration of gaseous N,N-dimethylformamide: Operational performance and microbial diversity analysis at different conditions.

N,N-Dimethylformamide (DMF) is an organic solvent produced in large quantities worldwide. It is considered as a hazardous air pollutant and its emission should be controlled. However, only a limited number of studies have been performed on the removal of gaseous DMF by biological technologies. In this paper, we evaluate the removal of DMF under mesophilic and thermophilic conditions in a lab-scale biofilter for 472 days. The results show that, at ambient temperature, the biofilter achieved an average removal efficiency (RE) of 99.7 ± 0.3 % at Inlet Loads (ILs) up to 297 ± 52 g DFM m-3 h-1 (Empty Bed Residence Time (EBRTs) of 10.7 s). However, a decrease in EBRT (6.4 s) led to an unstable outlet concentration and, thus, to a drop in the biofilter performance (average RE: 90 ± 9 %). Moreover, an increase in temperature up to 65 °C led to a gradual decrease in RE (till 91 ± 7 %). Microbial analysis indicates that once the microorganisms encountered DMF, Rhizobiaceae dominated followed by Alcaligenaceae. Afterwards, a strong decrease in Rhizobiaceae was observed at every increase in temperature, and at 65 °C, the taxa were more heterogeneous. Overall, our experimental results indicate that biofiltration is a promising technique to remove DMF from waste gas streams.

The potential of NO+ and O2 +• in switchable reagent ion proton transfer reaction time-of-flight mass spectrometry.

Selected ion flow tube mass spectrometry (SIFT-MS) and proton transfer reaction mass spectrometry with switchable reagent ion capability (PTR+SRI-MS) are analytical techniques for real-time qualification and quantification of compounds in gas samples with trace level concentrations. In the detection process, neutral compounds-mainly volatile organic compounds-are ionized via chemical ionization with ionic reagents or primary ions. The most common reagent ions are H3 O+ , NO+ and O2 +• . While ionization with H3 O+ occurs by means of proton transfer, the ionization via NO+ and O2 +• offers a larger variety on ionization pathways, as charge transfer, hydride abstraction and so on are possible. The distribution of the reactant into various reaction channels depends not only on the usage of either NO+ or O2 +• , but also on the class of analyte compounds. Furthermore, the choice of the reaction conditions as well as the choice of either SIFT-MS or PTR+SRI-MS might have a large impact on the resulting products. Therefore, an overview of both NO+ and O2 +• as reagent ions is given, showing differences between SIFT-MS and PTR+SRI-MS as used analytical methods revealing the potential how the knowledge obtained with H3 O+ for different classes of compounds can be extended with the usage of NO+ and O2 +• .

A novel approach to discriminate the volatilome of Vitis vinifera berries by selected ion flow tube mass Spectrometry analysis and chemometrics.

This study investigated a quick way to discriminate grape varieties based on their composition in volatile compounds through a SIFT-MS scan coupled with simple chemometrics approaches such as analysis of variance (ANOVA), principal component analysis (PCA) and hierarchical ascendant classification (HAC). The 23 studied grape varieties were distinguishable using O2+, H3O+ and NO+ as reagent ions, and the combination of these three ions. For its ability to ionize most compounds, to efficiently fragment them to generate ions with distinct m/z ratio, and to enhance the differentiation of compounds of similar masses, O2+ reagent ion should be preferentially considered. The use of one single ion rather than three enables to limit the time of analysis and the number of variables to be treated. The technique allowed the distinction of high and low aroma compounds producers as confirmed by headspace solid-phase microextraction followed by gas chromatography-mass spectrometry (HS-SPME/GC-MS) analyses. SIFT-MS is a quick and interesting tool with potential application in various fields of viticulture such as phenotyping of grape varieties or non-targeted studies on the impact of environmental factors or viticultural practices on grape aroma composition.

Inhalation of VOCs from facial moisturizers and the influence of dose proximity.

Volatile organic compound (VOC) emissions from personal care products (PCPs) contribute to poor indoor air quality. Exposure to indoor VOCs is typically determined through ambient concentration measurements; however, for some PCPs the proximity of use to the nose and mouth may lead to disproportionately large inhaled doses. In this paper, we quantify emission factors for six common PCP ingredient VOCs (ethanol, 2-propanol, benzyl alcohol, 1,3-butanediol, t-butyl alcohol, and the grouping of monoterpenes as limonene) from 16 facial day-moisturizers using headspace analysis and selected ion flow-tube mass spectrometry. A wide range of emissions rates were observed across the range of products tested (e.g., ethanol 3.3-6.9 × 102  µg s-1  g[product]-1 , limonene 1.3 × 10-1 -4.1 × 10-1  µg s-1  g[product]-1 ). We use a mannequin head with reconstructed nose and mouth airways to sample VOCs from facial application at typical respiration volumes. A single facial application of moisturizer can lead to a much larger inhaled VOC dose than would be inhaled from typical indoor ambient air over 24 h (e.g., limonene up to ~×16 greater via facial application, ethanol up to ~×300). Emissions from facially applied PCPs typically decayed to background concentrations over periods ranging from 5 to 150 min.

Volatile fingerprint of food products with untargeted SIFT-MS data coupled with mixOmics methods for profile discrimination: Application case on cheese.

Volatile organic compounds (VOCs) emitted by food products are decisive for the perception of aroma and taste. The analysis of gaseous matrices is traditionally done by detection and quantification of few dozens of characteristic markers. Emerging direct injection mass spectrometry technologies offer rapid analysis based on a soft ionisation of VOCs without previous separation. The recent increase of selectivity offered by the use of several precursor ions coupled with untargeted analysis increases the potential power of these instruments. However, the analysis of complex gaseous matrix results in a large number of ion conflicts, making the quantification of markers difficult, and in a large volume of data. In this work, we present the exploitation of untargeted SIFT-MS volatile fingerprints of ewe PDO cheeses in a real farm model, using mixOmics methods allowing us to illustrate the typicality, the manufacturing processes reproducibility and the impact of the animals' diet on the final product.

Hyphenated Mass Spectrometry versus Real-Time Mass Spectrometry Techniques for the Detection of Volatile Compounds from the Human Body.

Mass spectrometry (MS) is an analytical technique that can be used for various applications in a number of scientific areas including environmental, security, forensic science, space exploration, agri-food, and numerous others. MS is also continuing to offer new insights into the proteomic and metabolomic fields. MS techniques are frequently used for the analysis of volatile compounds (VCs). The detection of VCs from human samples has the potential to aid in the diagnosis of diseases, in monitoring drug metabolites, and in providing insight into metabolic processes. The broad usage of MS has resulted in numerous variations of the technique being developed over the years, which can be divided into hyphenated and real-time MS techniques. Hyphenated chromatographic techniques coupled with MS offer unparalleled qualitative analysis and high accuracy and sensitivity, even when analysing complex matrices (breath, urine, stool, etc.). However, these benefits are traded for a significantly longer analysis time and a greater need for sample preparation and method development. On the other hand, real-time MS techniques offer highly sensitive quantitative data. Additionally, real-time techniques can provide results in a matter of minutes or even seconds, without altering the sample in any way. However, real-time MS can only offer tentative qualitative data and suffers from molecular weight overlap in complex matrices. This review compares hyphenated and real-time MS methods and provides examples of applications for each technique for the detection of VCs from humans.

The peppermint breath test benchmark for PTR-MS and SIFT-MS.

A major challenge for breath research is the lack of standardization in sampling and analysis. To address this, a test that utilizes a standardized intervention and a defined study protocol has been proposed to explore disparities in breath research across different analytical platforms and to provide benchmark values for comparison. Specifically, thePeppermint Experimentinvolves the targeted analysis in exhaled breath of volatile constituents of peppermint oil after ingestion of the encapsulated oil. Data from thePeppermint Experimentperformed by proton transfer reaction mass spectrometry (PTR-MS) and selected ion flow tube mass spectrometry (SIFT-MS) are presented and discussed herein, including the product ions associated with the key peppermint volatiles, namely limonene,α- andß-pinene, 1,8-cineole, menthol, menthone and menthofuran. The breath washout profiles of these compounds from 65 individuals were collected, comprising datasets from five PTR-MS and two SIFT-MS instruments. The washout profiles of these volatiles were evaluated by comparing the log-fold change over time of the product ion intensities associated with each volatile. Benchmark values were calculated from the lower 95% confidence interval of the linear time-to-washout regression analysis for all datasets combined. Benchmark washout values from PTR-MS analysis were 353 min for the sum of monoterpenes and 1,8-cineole (identical product ions), 173 min for menthol, 330 min for menthofuran, and 218 min for menthone; from SIFT-MS analysis values were 228 min for the sum of monoterpenes, 281 min for the sum of monoterpenes and 1,8-cineole, and 370 min for menthone plus 1,8-cineole. Large inter- and intra-dataset variations were observed, whereby the latter suggests that biological variability plays a key role in how the compounds are absorbed, metabolized and excreted from the body via breath. This variability seems large compared to the influence of sampling and analytical procedures, but further investigations are recommended to clarify the effects of these factors.

Cross Platform Analysis of Volatile Organic Compounds Using Selected Ion Flow Tube and Proton-Transfer-Reaction Mass Spectrometry.

Volatile breath metabolites serve as potential disease biomarkers. Online mass spectrometry (MS) presents real-time quantification of breath volatile organic compounds (VOCs). The study aims to assess the relationship between two online analytical mass spectrometry techniques in the quantification of target breath metabolites: selected ion flow tube mass spectrometry (SIFT-MS) and proton-transfer-reaction time-of-flight mass spectrometry (PTR-ToF-MS). The two following techniques were employed: (i) direct injection with bag sampling using SIFT-MS and PTR-ToF-MS and (ii) direct injection and thermal desorption (TD) tube comparison using PTR-ToF-MS. The concentration of abundant breath metabolites, acetone and isoprene, demonstrated a strong positive linear correlation between both mass spectrometry techniques (r = 0.97, r = 0.89, respectively; p < 0.001) and between direct injection and TD tube (r = 0.97, r = 0.92, respectively; p < 0.001) breath sampling techniques. This was reflected for the majority of short chain fatty acids and alcohols tested (r > 0.80, p < 0.001). Analyte concentrations were notably higher with the direct injection of a sampling bag compared to the TD method. All metabolites produced a high degree of agreement in the detection range of VOCs between SIFT-MS and PTR-ToF-MS, with the majority of compounds falling within 95% of the limits of agreement with Bland-Altman analysis. The cross platform analysis of exhaled breath demonstrates strong positive correlation coefficients, linear regression, and agreement in target metabolite detection rates between both breath sampling techniques. The study demonstrates the transferability of using data outputs between SIFT-MS and PTR-ToF-MS. It supports the implementation of a TD platform in multi-site studies for breath biomarker research in order to facilitate sample transport between clinics and the laboratory.

Exploring Volatile Organic Compounds in Breath for High-Accuracy Prediction of Lung Cancer.

(1) Background: Lung cancer is silent in its early stages and fatal in its advanced stages. The current examinations for lung cancer are usually based on imaging. Conventional chest X-rays lack accuracy, and chest computed tomography (CT) is associated with radiation exposure and cost, limiting screening effectiveness. Breathomics, a noninvasive strategy, has recently been studied extensively. Volatile organic compounds (VOCs) derived from human breath can reflect metabolic changes caused by diseases and possibly serve as biomarkers of lung cancer. (2) Methods: The selected ion flow tube mass spectrometry (SIFT-MS) technique was used to quantitatively analyze 116 VOCs in breath samples from 148 patients with histologically confirmed lung cancers and 168 healthy volunteers. We used eXtreme Gradient Boosting (XGBoost), a machine learning method, to build a model for predicting lung cancer occurrence based on quantitative VOC measurements. (3) Results: The proposed prediction model achieved better performance than other previous approaches, with an accuracy, sensitivity, specificity, and area under the curve (AUC) of 0.89, 0.82, 0.94, and 0.95, respectively. When we further adjusted the confounding effect of environmental VOCs on the relationship between participants' exhaled VOCs and lung cancer occurrence, our model was improved to reach 0.92 accuracy, 0.96 sensitivity, 0.88 specificity, and 0.98 AUC. (4) Conclusion: A quantitative VOCs databank integrated with the application of an XGBoost classifier provides a persuasive platform for lung cancer prediction.