Analysis of exhaled breath from smokers,passive smokers and non‐smokers by solid‐phase microextraction gas chromatography/mass spectrometry

In this study, 38 samples of expired air were collected and analyzed from 20 non‐smoking volunteers, four passive smokers and 14 smokers (21 women and 17 men). Measurements were carried out using solid‐phase microextraction (SPME) as an isolation and preconcentration technique. The determination and identification were accomplished by gas chromatography coupled with mass spectrometry (GC/MS). Our data showed that ca 32% of all identified compounds in the breath of healthy non‐smokers were saturated hydrocarbons. In the breath of smoking and passive smoking volunteers hydrocarbons were predominant, but also present were more exogenous analytes such as furan, acetonitrile and benzene than in the breath of non‐smokers. Acetonitrile, furan, 3‐methylfuran, 2,5‐dimethylfuran, 2‐butanone, octane and decane were identified in breath of smoking and passive smoking persons. Copyright © 2008 John Wiley & Sons, Ltd.     

HS-SPME-GC-MS法测定合成纤维中单体残留

纤维制品聚合过程中的合成单体残留的持续释放可能导致潜在的环境和健康危害,尽管其在纺织品中的残留会因纺织品加工时的洗涤、漂染等处理过程中被除去,纺织品中这些挥发性有机物（VOCs）导致的环境问题仍然不容忽视。长期以来,人们对纤维制品上的合成单体残留能否导致人体不可逆损害一直争论不休。随着欧盟2002／371／EC生态标签（Eco-label）和生态纺织品标准100（DOko-Tex Standard 100）依据巴塞尔公约中有机溶剂的生产及使用技术准则,对VOCs在纺织品生产和制造中的使用和释放进行了限制。     

Human exhaled air analytics: biomarkers of diseases

Over the last few years, breath analysis for the routine monitoring of metabolic disorders has attracted a considerable amount of scientific interest, especially since breath sampling is a non-invasive technique, totally painless and agreeable to patients. The investigation of human breath samples with various analytical methods has shown a correlation between the concentration patterns of volatile organic compounds (VOCs) and the occurrence of certain diseases. It has been demonstrated that modern analytical instruments allow the determination of many compounds found in human breath both in normal and anomalous concentrations. The composition of exhaled breath in patients with, for example, lung cancer, inflammatory lung disease, hepatic or renal dysfunction and diabetes contains valuable information. Furthermore, the detection and quantification of oxidative stress, and its monitoring during surgery based on composition of exhaled breath, have made considerable progress. This paper gives an overview of the analytical techniques used for sample collection, preconcentration and analysis of human breath composition. The diagnostic potential of different disease-marking substances in human breath for a selection of diseases and the clinical applications of breath analysis are discussed.     

Applications of Hadamard transform-gas chromatography/mass spectrometry to online detection of exhaled breath after drinking or smoking

A Hadamard transform-gas chromatography/mass spectrometry (HT-GC/MS) technique was employed for the online detection of ethanol or toluene in exhaled breath after drinking or smoking, respectively. Exhaled breath samples, collected from volunteers, were directly injected into the GC inlet by a Hadamard-injector without any pretreatment. In the case of breath from a drinker, using a conventional single injection, a small ion peak (corresponding to ∼0.1 ng of ethanol), the intensity of which was approximately equal to or less than the limit of detection. When the HT technique was applied, the signal-to-noise (S/N) ratio was dramatically improved. Furthermore, in the case of breath from a smoker, using conventional injection, a weak ion peak (corresponding to ∼0.7 pg of toluene) was marginally detected. However, the HT technique led to an improvement in the S/N ratio, with the peak corresponding to the limit of detection. In both cases, the HT technique permitted specific components in exhaled breath to be determined, without the need for any extraction procedures.     

Ultrafast gas chromatography coupled to electronic nose to identify volatile biomarkers in exhaled breath from chronic obstructive pulmonary disease patients: A pilot study

An analytical method to identify volatile organic compounds (VOCs) in the exhaled breath from patients with a diagnosis of chronic obstructive pulmonary disease (COPD) using a ultrafast gas chromatography system equipped with an electronic nose detector (FGC eNose) has been developed. A prospective study was performed in 23 COPD patients and 33 healthy volunteers; exhalation breathing tests were performed with Tedlar bags. Each sample was analyzed by FCG eNose and the identification of VOCs was based on the Kovats index. Raw data were reduced by principal component analysis (PCA) and canonical discriminant analysis [canonical analysis of principal coordinates (CAP)]. The FCG eNose technology was able to identify 17 VOCs that distinguish COPD patients from healthy volunteers. At all stages of PCA and CAP the discrimination between groups was obvious. Chemical prints were correctly classified up to 82.2%, and were matched with 78.9% of the VOCs detected in the exhaled breath samples. Receiver operating characteristic curve analysis indicated the sensitivity and specificity to be 96% and 91%, respectively. This pilot study demonstrates that FGC eNose is a useful tool to identify VOCs as biomarkers in exhaled breath from COPD patients. Further studies should be performed to enhance the clinical relevance of this quick and ease methodology for COPD diagnosis.     

Comparison of Targeted and Untargeted Approaches in Breath Analysis for the Discrimination of Lung Cancer from Benign Pulmonary Diseases and Healthy Persons

The aim of the present study was to compare the efficiency of targeted and untargeted breath analysis in the discrimination of lung cancer (Ca+) patients from healthy people (HC) and patients with benign pulmonary diseases (Ca−). Exhaled breath samples from 49 Ca+ patients, 36 Ca− patients and 52 healthy controls (HC) were analyzed by an SPME–GC–MS method. Untargeted treatment of the acquired data was performed with the use of the web-based platform XCMS Online combined with manual reprocessing of raw chromatographic data. Machine learning methods were applied to estimate the efficiency of breath analysis in the classification of the participants. Results: Untargeted analysis revealed 29 informative VOCs, from which 17 were identified by mass spectra and retention time/retention index evaluation. The untargeted analysis yielded slightly better results in discriminating Ca+ patients from HC (accuracy: 91.0%, AUC: 0.96 and accuracy 89.1%, AUC: 0.97 for untargeted and targeted analysis, respectively) but significantly improved the efficiency of discrimination between Ca+ and Ca− patients, increasing the accuracy of the classification from 52.9 to 75.3% and the AUC from 0.55 to 0.82. Conclusions: The untargeted breath analysis through the inclusion and utilization of newly identified compounds that were not considered in targeted analysis allowed the discrimination of the Ca+ from Ca− patients, which was not achieved by the targeted approach.     

Diagnosis of Helicobacter pylori infection with the (13)C-urea breath test by means of GC-MS analysis

The diagnosis of Helicobacter pylori (H. pylori) infection by GC-MS detection of the (13)CO(2) enrichment in (13)C-urea breath test ((13)C-UBT) samples is reported. This study aimed to optimize the (13)C-UBT with regards to the diagnostic cut-off value, sampling time, and frequency. The H. pylori status of 103 dyspeptic patients was obtained by histological examination, the rapid urease test as well as with the GC-MS (13)C-UBT. Analytical and diagnostic accuracies were determined by comparison of the GC-MS (13)C-UBT results with that of the analytical and diagnostic gold standards, namely GC-isotope ratio MS (IRMS) and histology. The (13)CO(2) enrichment values obtained with GC-MS analysis, correlated favorably (r(2) = 0.993) with those obtained by GC-IRMS analysis. When compared to histology, the GC-MS (13)C-UBT had a diagnostic sensitivity of 92% and a specificity of 93%. The positive predictive value (PPV), negative predictive value (NPV), and accuracy were 95, 89, and 92%, respectively. It was concluded that SIM GC-MS is capable of analyzing nonradioactive (13)C-UBT samples, with a precision and accuracy sufficient to distinguish between H. pylori positive and negative patients.     

Investigation of bacterial viability from incubated saliva by application of flow cytometry and hyphenated separation techniques

The aim of the study was determination of bacterial viability in saliva samples and finding a correlation between microbiological and volatile profiles of saliva depending on incubation time. Bacteria colonizing healthy oral cavities were also identified. Twelve healthy adults donated unstimulated saliva samples. Flow cytometry, optical density measurements and colony‐forming unit (CFU) counting method were employed for analyses of native and inoculated saliva after 0, 1, 2, 24, and 48 h of incubation. Volatile profiles were acquired using headspace‐solid phase microextraction‐gas chromatography/mass spectrometry (HS‐SPME‐GC/MS). Oral bacteria were the most viable within 2 h after collection of saliva. Extension of incubation time to 48 h caused considerable decrease in live bacteria counts and sharp increase in dead bacteria counts. The most prevalent strain was Sphingomonas paucimobilis (26.67%). The number of volatiles raised from 5 to 27 with incubation time and most of them were putrefaction products, such as methanethiol, indole and pyrrole. HS‐SPME‐GC/MS method is insufficient for volatile profiling of “fresh” saliva and should be directed rather to investigation of bacterial metabolites.     

Analysis of aldehydes in human exhaled breath condensates by in-tube SPME-HPLC

In this paper, polypyrrole/graphene (PPy/G) composite coating was prepared by a facile electrochemical polymerization strategy on the inner surface of a stainless steel (SS) tube. Based on the coating tube, a novel online in-tube solid-phase microextraction -high performance liquid chromatography (IT-SPME-HPLC) was developed and applied for the extraction of aldehydes in the human exhaled breath condensates (EBC). The hybrid PPy/G nanocomposite exhibits remarkable chemical and mechanical stability, high selectivity, and satisfactory extraction performance toward aldehyde compounds. Moreover, the proposed online IT-SPME-HPLC method possesses numerous superiorities, such as time and cost saving, process simplicity, high precision and sensitivity. Some parameters related to extraction efficiency were optimized systematically. Under the optimal conditions, the recoveries of the aldehyde compounds at three spiked concentration levels varied in the range of 85%–117%. Good linearity was obtained with excellent correlation coefficients (R²) being larger than 0.994. The relative standard deviations (n = 5) of the method ranged from 1.8% to 11.3% and the limits of detection were between 2.3 and 3.3 nmol L⁻¹. The successful application of the proposed method in human EBC indicated that it is a promising approach for the determination of trace aldehyde metabolites in complex EBC samples.     

Gas chromatography-tandem mass spectrometry analysis of gabapentin in serum

A new highly sensitive analytical method for determining gabapentin [1-(aminomethyl) cyclohexaneacetic acid; Neurontin] in serum using gas chromatography/tandem mass spectrometry (GC-MS/MS) was developed. GC-MS/MS was applied to determine the levels of gabapentin in serum samples of mice at 1 and 6 h after oral or intraperitoneal treatment (300 mg/kg). At 1 h, the concentrations of the drug were 4.02 +/- 0.42 and 4.32 +/- 0.28 microg/mL in mice treated orally and intraperitoneally, respectively. At 6 h, drug levels decreased by about 66% in both groups. The method, coupling two stages of mass analysis, could be very useful in identifying the drug in complex mixtures such as blood and urine. Moreover, it is easy and rapid to perform, and sensitive enough to allow the presence of the drug to be determined at very low detection limits. It is a very reliable method for both clinical and experimental monitoring of gabapentin.     

Application of solid-phase microextraction and gas chromatography-mass spectrometry for the determination of chlorophenols in leather

This paper proposes a new analytical procedure based on the headspace solid‐phase microextraction (HS‐SPME) technique and gas chromatography‐selected ion monitoring‐mass spectrometry (GC‐SIM‐MS) for the determination of 16 phenols extracted from leather samples. The optimized conditions for the HS‐SPME were obtained through two experimental designs – a two‐level fractional factorial design followed by a central composite design – using the commercial SPME fiber polyacrylate 85 μm (PA). The best extraction conditions were as follows: 200 μL of derivatizing agent (acetic anhydride), 20 mL of saturated aqueous NaCl solution and extraction time and temperature of 50 min and 75°C, respectively. All optimized conditions were obtained with fixed leather sample mass (250 mg), vial volume (40 mL) and phosphate buffer pH (12) and concentration (50 mmol/L). Detection limits ranging from 0.03 to 0.20 ng/g, and relative standard deviation (RSD) lower than 10.23% (n=6) for a concentration of 800 ng/g (chlorophenols) and 1325 ng/g (2‐phenylphenol) in the splitless mode were obtained. The recovery was studied at three concentration levels by adding different amounts of phenols to the leather sample and excellent recoveries ranging from 90.0 to 107.2% were obtained. The validated method was shown to be suitable for the quantification of phenols in leather samples, as it is simple, relatively fast and sensitive.     

Selective Determination of Se4+ and Se6+ Using SPME and GC/MS

A method for the selective determination of Se⁴⁺ and Se⁶⁺ using solid phase microextraction (SPME) and GC/MS analysis is presented. Se⁴⁺ is selectively derivatized by reaction with 4,5-dichloro-1,2-phenylenediamine to form the corresponding piazselenolo complex, extracted by the SPME fiber, and determined by GC/MS. The RSD at a 5 μg/L concentration was 9.88% and the theoretical detection limit 6 ng/L. The method was employed to test real matrices; tap and river water were analyzed before and after spiking giving a recovery rate of 102% in river water and 97% in tap water.     

Simple and automatic determination of aldehydes and acetone in water by headspace solid-phase microextraction and gas chromatography-mass spectrometry

We describe a simple and automatic method to determine nine aldehydes and acetone simultaneously in water. This method is based on derivatization with 2,2,2-trifluoroethylhydrazine (TFEH) and consecutive headspace-solid-phase microextraction and gas chromatography-mass spectrometry. Acetone-d(6) was used as the internal standard. Aldehydes and acetone in water reacted for 30 min at 40°C with TFEH in a headspace vial and the formed TFEH derivatives were simultaneously vaporized and adsorbed on polydimethylsiloxane-divinylbenzene. Under the established condition, the method detection limit was 0.1-0.5 μg/L in 4 mL water and the relative standard deviation was less than 13% at concentrations of 0.25 and 0.05 mg/L. This method was applied to determine aldehydes and acetone in 5 mineral water and 114 surface water samples. All mineral water samples had detectable levels of methanal (24.0-61.8 μg/L), ethanal (57.7-110.9 μg/L), propanal (11.5-11.7 μg/L), butanal, pentanal (3.3-3.4 μg/L) and nonanal (0.3-0.4 μg/L). Methanal and ethanal were also detected in concentration range of 2.7-117.2 and 1.2-11.9 μg/L, respectively, in surface water of 114 monitoring sites in Korea.     

Methyl benzoate as a marker for the detection of mold in indoor building materials

A convenient analytical method to quantify volatile organic compounds (VOCs) emitted from various building materials has not been addressed yet. This work presents a new and rapid automated method using SPME combined with GC/MS. Methyl benzoate - as a metabolic biomarker for mold growth-was used to indicate VOCs and to determine and assess mold growth on damp samples. Gypsum board and wall-board paper were used as examples of common indoor building materials. Optimized extraction conditions were carried out manually, using a GC/flame ionization detector. Moldy samples were analyzed using an automated SPME-GC/MS analysis under optimized conditions. The amount of methyl benzoate emitted from the studied samples ranged from 32 to 46 ppb, where the density of the fungal biomass was found to be 8 x 10(4) cells/mL. A relationship between the amount of fungal biomass and the emitted concentration of methyl benzoate was found and assessed based upon cultured mold samples taken from indoor building sites. The analytical method shows promise for the compound methyl benzoate, which can easily be identified at low detection limits (LOD = 3 ppb) and good linearity (>0.988), and its extraction and detection can be accomplished cleanly by current extraction techniques. Results suggest that this method with easy sample preparation can be used for quantitation and, of importance, minimal matrix effects are observed.     

Response surface optimisation applied to a headspace-solid phase microextraction-gas chromatography-mass spectrometry method for the analysis of volatile organic compounds in water matrices

A new method for the simultaneous determination of 12 volatile organic compounds (trans-1,2-dichloroethene, 1,1,1-trichloroethane, benzene, 1,2-dichloroethane, trichloroethene, toluene, 1,1,2-trichloroethane, tetrachloroethene, ethylbenzene, m-, p-, o-xylene) in water samples by headspace solid phase microextraction (HS–SPME)–gas chromatography mass spectrometry (GC–MS) was described, using a 100?µm PDMS (polydimethylsiloxane) coated fibre. The response surface methodology was used to optimise the effect of the extraction time and temperature, as well as the influence of the salt addition in the extraction process. Optimal conditions were extraction time and temperature of 30?min and ?20°C, respectively, and NaCl concentration of 4?mol?L^?1. The detection limits were in the range of 1.1?×?10^?3–2.3?µg?L^?1 for the 12 volatile organic compounds (VOCs). Global uncertainties were in the range of 4–68%, when concentrations decrease from 250?µg?L^?1 down to the limits of quantification. The method proved adequate to detect VOCs in six river samples.     

The Influence of Smoking Status on Exhaled Breath Profiles in Asthma and COPD Patients

Breath analysis using eNose technology can be used to discriminate between asthma and COPD patients, but it remains unclear whether results are influenced by smoking status. We aim to study whether eNose can discriminate between ever- vs. never-smokers and smoking <24 vs. >24 h before the exhaled breath, and if smoking can be considered a confounder that influences eNose results. We performed a cross-sectional analysis in adults with asthma or chronic obstructive pulmonary disease (COPD), and healthy controls. Ever-smokers were defined as patients with current or past smoking habits. eNose measurements were performed by using the SpiroNose. The principal component (PC) described the eNose signals, and linear discriminant analysis determined if PCs classified ever-smokers vs. never-smokers and smoking <24 vs. >24 h. The area under the receiver–operator characteristic curve (AUC) assessed the accuracy of the models. We selected 593 ever-smokers (167 smoked <24 h before measurement) and 303 never-smokers and measured the exhaled breath profiles of discriminated ever- and never-smokers (AUC: 0.74; 95% CI: 0.66–0.81), and no cigarette consumption <24h (AUC 0.54, 95% CI: 0.43–0.65). In healthy controls, the eNose did not discriminate between ever or never-smokers (AUC 0.54; 95% CI: 0.49–0.60) and recent cigarette consumption (AUC 0.60; 95% CI: 0.50–0.69). The eNose could distinguish between ever and never-smokers in asthma and COPD patients, but not recent smokers. Recent smoking is not a confounding factor of eNose breath profiles.     

Resolving co-eluting chromatographic patterns by means of dissimilarity analysis in iterative target transformation factor analysis

The initialization of concentration vector for iterative target transformation factor analysis (ITTFA) and identification of pure or key variables are the important issue in MCR. In this study, dissimilarity analysis and evolving factor analysis (EFA) are combined to find the selective or key variables and subsequently obtain initial estimates of the concentration vectors for resolution of gas chromatography/mass spectrometry (GC/MS) data by ITTFA. For systems containing components with highly similar mass spectra, a new constraint setting the elements out of elution window to 0 is used to improve convergence rate and accuracy of results. Tested by standard mixture of two wax esters and real GC/MS data of gasoline 97#, dissimilarity based ITTFA could obtain accurate results (average Dot product of concentration vectors, average deviation of peak area ratio and average similarity of mass spectra are 0.9929, 0.0228 and 981.0, respectively).     

Stable isotope dilution analysis of wine fermentation products by HS-SPME-GC-MS

The aim of this study was to quantify, in a single analysis, 31 volatile fermentation-derived products that contribute to the aroma of red and white wine. We developed a multi-component method based on headspace solid-phase microextraction coupled with gas chromatography mass spectrometry (HS-SPME-GC-MS). The 31 volatile compounds analysed include ethyl esters, acetates, acids and alcohols. Although these compounds have a range of functional groups, chemical properties, volatilities, affinities for the SPME fibre, and are found in wine at various concentrations, the accuracy of the analysis was achieved with the use of polydeuterated internal standards for stable isotope dilution analyses (SIDA). Nine of the labelled standards were commercially available, while 22 were synthesised. The method was validated by a series of duplicate spiked standard additions to model, white and red wine matrices over the concentration range relevant for each compound in wine. This demonstrated that the appropriate use of SIDA helped to account for matrix effects, for instance potential sources of variation such as the relative response to the MS detector, ionic strength, ethanol content and pH of different wine matrices. The resultant calibration functions had correlation coefficients (R²) ranging from 0.995 to 1.000. Each compound could be quantified at levels below its aroma threshold in wine. Relative standard deviations were all <5%. The method was optimised for the best compromise (over the 31 compounds) of wine dilution factor, level of sodium chloride addition, SPME fibre, SPME temperature, SPME time, GC column and MS conditions. Confirmation of identity was achieved by retention time and peak shape, and measurement of at least three ions for each analyte and internal standard with the MS operating in selected ion monitoring mode to facilitate more precise quantitation with a high sampling rate. The method is a valuable research tool with many relevant applications. A novel method for the combined chiral separation and SIDA quantification of 2- and 3-methylbutanoic acid is also demonstrated.