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A standard procedure for exhaled breath condensate (EBC) collection is still lacking. The aim of this study was to compare the concentration of several biomarkers in whole (W-EBC) and fractionated EBC (A-EBC), the latter collected starting from CO₂ ≥ 50% increase during exhalation. Forty-five healthy non-smokers or asymptomatic light smokers were enrolled. Total protein concentrations in W-EBC and A-EBC were overlapping (median: 0.7 mg l⁻¹ in both cases), whereas mitochondrial DNA was higher in A-EBC (0.021 versus 0.011 ng ml⁻¹), indicating a concentration rather than a dilution of lining fluid droplets in the last portion of exhaled air. H₂O₂ (0.13 versus 0.08 µM), 8-isoprostane (4.9 versus 4.4 pg ml⁻¹), malondialdehyde (MDA) (4.2 versus 3.2 nM) and 4-hydroxy-2-nonhenal (HNE) (0.78 versus 0.66 nM) were all higher in W-EBC, suggesting a contribution from the upper airways to oxidative stress biomarkers in apparently healthy subjects. NH₄⁺ was also higher in W-EBC (median: 590 versus 370 µM), with an estimated increase over alveolar and bronchial air by a factor 1.5. pH was marginally, but significantly higher in W-EBC (8.05 versus 8.01). In conclusion, the fractionation of exhaled air may be promising in clinical and occupational medicine.

This study sought to identify if detectable changes in human breath profiles may be observed following a psychological intervention designed to induce stress, a paced auditory serial addition test (PASAT). Breath samples were collected from 22 participants (10 male and 12 female) following a double cross-over randomized design with two experimental interventions. One intervention required participants to listen to classical music chosen to be neutral. The other intervention required participants to undertake a PASAT that induced cardiovascular responses consistent with acute stress. Both interventions also involved two sequences of cognitive function tests. Blood-pressure and heart-rate were recorded throughout each intervention and distal breath samples were collected onto Tenax® TA/Carbograph 1 thermal desorption tubes, using an adaptive breath sampler. Samples were collected before and after the PASAT. Breath samples were analysed by thermal desorption gas chromatography-mass spectrometry. Data registration using retention indexing and peak deconvolution followed by partial least-squares discriminant analysis identified six stress sensitive compounds. A principal components analysis model based on these components generated a model that predicted post-PASAT versus post-neutral intervention samples with a sensitivity of 83.3% and a selectivity of 91.6% for females, compared to 100% sensitivity and 90% selectivity for males. Of the six compounds indole, 2-hydroxy-1-phenylethanone, benzaldehyde, and 2-ethylhexan-1-ol were identified on the basis of mass spectral, retention indexing and confirmation against pure standards. 2-methylpentadecane was tentatively identified from mass spectral and retention indexing, whilst one component has yet to be assigned, although the mass spectrum is indicative of a terpene. Indole and 2-methylpentadecane concentrations increased in response to the PASAT intervention, while the other compounds reduced in their abundance in human breath, possibly as a result of ventilation effects.

Electronic noses (e-noses), artificial sensor systems generally consisting of chemical sensor arrays for the detection of volatile compound profiles, have potential applications in respiratory medicine. We assessed within-day and between-day repeatability of an e-nose made from 32 sensors in patients with stable chronic obstructive pulmonary disease (COPD). We also compared between-day repeatability of an e-nose, fraction of exhaled nitric oxide (F_ENO) and pulmonary function testing. Within-day and between-day repeatability for the e-nose was assessed in two breath samples collected 30 min and seven days apart, respectively. Repeatability was expressed as an intraclass correlation coefficient (ICC). All sensors had ICC above 0.5, a value that is considered acceptable for repeatability. Regarding within-day repeatability, ICC ranged from 0.75 to 0.84 (mean = 0.80 ± 0.004). Sensors 6 and 19 were the most reproducible sensors (both, ICC = 0.84). Regarding between-day repeatability, ICC ranged from 0.57 to 0.76 (mean = 0.68 ± 0.01). Sensor 19 was the most reproducible sensor (ICC = 0.76). Within-day e-nose repeatability was greater than between-day repeatability (P < 0.0001). Between-day repeatability of F_ENO (ICC = 0.91) and spirometry (ICC range = 0.94–0.98) was greater than that of e-nose (mean ICC = 0.68). In patients with stable COPD, the e-nose used in this study has acceptable within-day and between-day repeatability which varies between different sensors.

There is still an unexplored potential for exhaled nitric oxide (NO) in many clinical applications. This study presents an overview of the currently available methods for monitoring NO in exhaled breath and the use of the modelling of NO production and transport in the lung in clinical practice. Three technologies are described, namely chemiluminescence, electrochemical sensing and laser-based detection with their advantages and limitations. Comparisons are made in terms of sensitivity, time response, size, costs and suitability for clinical purposes. The importance of the flow rate for NO sampling is discussed from the perspective of the recent recommendations for standardized procedures for online and offline NO measurement. The measurement of NO at one flow rate, such as 50 ml s⁻¹, can neither determine the alveolar site/peripheral contribution nor quantify the difference in NO diffusion from the airways walls. The use of NO modelling (linear or non-linear approach) can solve this problem and provide useful information about the source of NO. This is of great value in diagnostic procedures of respiratory diseases and in treatment with anti-inflammatory drugs.

Hydrogen cyanide (HCN) in exhaled breath has been proposed as a biomarker for airway inflammation, and also a marker of the presence in the airways of specific organisms, especially Pseudomonas aeruginosa. However the production of HCN by salivary peroxidase in the oral cavity increases orally exhaled concentrations, and may not reflect the condition of the lower airways. Using SIFT-MS we aimed to determine an appropriate single-exhalation breathing maneuver which avoids the interference of HCN produced in the oral cavity. We have established that the SIFT-MS Voice200™ is suitable for the online measurement of HCN in exhaled breath. In healthy volunteers a significantly higher end exhaled HCN concentration was measured in oral exhalations compared to nasal exhalations (mean ± SD) 4.5 ± 0.6 ppb versus 2.4 ± 0.3 ppb, p < 0.01. For the accurate and reproducible quantification of end exhaled HCN in breath a nasal inhalation to full vital capacity and nasal exhalation at controlled flow is recommended. This technique was subsequently used to measure exhaled HCN in a group of patients with chronic suppurative lung disease (CSLD) and known microbiological colonization status to determine utility of HCN measurement to detect P. aeruginosa. Median nasal end exhaled HCN concentrations were higher in patients with CSLD (3.7 ppb) than normal subjects (2.0 ppb). However no differences between exhaled HCN concentrations of subjects colonized with P. aeruginosa and other organisms were identified, indicating that breath HCN is not a suitable biomarker of P. aeruginosa colonization.

Throughout the development of breath analysis research, there has been interest in how the concentrations of trace compounds in exhaled breath are related to their concentrations in the ambient inhaled air. In considering this, Phillips introduced the concept of 'alveolar gradient' and judged that the measured exhaled concentrations of volatile organic compounds should be diminished by an amount equal to their concentrations in the inhaled ambient air. The objective of the work described in this paper was to investigate this relationship quantitatively. Thus, experiments have been carried out in which inhaled air was polluted by seven compounds of interest in breath research, as given below, and exhaled breath has been analysed by SIFT-MS as the concentrations of these compounds in the inhaled air were reduced. The interesting result obtained is that all the exogenous compounds are partially retained in the exhaled breath and there are close linear relationships between the exhaled and inhaled air concentrations for all seven compounds. Thus, retention coefficients, a, have been derived for the following compounds: pentane, 0.76 ± 0.09; isoprene, 0.66 ± 0.04; acetone, 0.17 ± 0.03; ammonia, 0.70 ± 0.13, methanol, 0.29 ± 0.02; formaldehyde, 0.06 ± 0.03; deuterated water (HDO), 0.09 ± 0.02. From these data, correction to breath analyses for inhaled concentration can be described by coefficients specific to each compound, which can be close to 1 for hydrocarbons, as applied by Phillips, or around 0.1, meaning that inhaled concentrations of such compounds can essentially be neglected. A further deduction from the experimental data is that under conditions of the inhalation of clean air, the measured exhaled breath concentrations of those compounds should be increased by a factor of 1/(1 − a) to correspond to gaseous equilibrium with the compounds dissolved in the mixed venous blood entering the alveoli. Thus, for isoprene, this is a factor of 3, which we have confirmed experimentally by re-breathing experiments.

Volatile organic compounds (VOCs) in exhaled breath originate from current or previous environmental exposures (exogenous compounds) and internal metabolic (anabolic and catabolic) production (endogenous compounds). The origins of certain VOCs in breath presumed to be endogenous have been proposed to be useful as preclinical biomarkers of various undiagnosed diseases including lung cancer, breast cancer, and cardio-pulmonary disease. The usual approach is to develop difference algorithms comparing VOC profiles from nominally healthy controls to cohorts of patients presenting with a documented disease, and then to apply the resulting rules to breath profiles of subjects with unknown disease status. This approach to diagnosis has a progression of sophistication; at the most rudimentary level, all measurable VOCs are included in the model. The next level corrects exhaled VOC concentrations for current inspired air concentrations. At the highest level, VOCs exhibiting discriminatory value also require a plausible biochemical pathway for their production before inclusion. Although these approaches have all shown some level of success, there is concern that pattern recognition is prone to error from environmental contamination and between-subject variance. In this paper, we explore the underlying assumptions for the interpretation and assignment of endogenous compounds with probative value for assessing changes. Specifically, we investigate the influence of previous exposures, elimination mechanisms and partitioning of exogenous compounds as confounders of true endogenous compounds. We provide specific examples based on a simple classical pharmacokinetic approach to identify potential misinterpretations of breath data and propose some remedies.

This report proposes a potentially sensitive and simple physiological method to detect early changes and to follow disease progression in obstructive pulmonary disease (COPD) based upon the usual pulmonary function test. Pulmonary function testing is a simple, although relatively insensitive, method to detect and follow COPD. As a proof-of-concept, we have examined the slope of the plateau for carbon dioxide during forced expiratory capnography in healthy (n = 10) and COPD subjects (n = 10). We compared the change in the rate of exhalation of carbon dioxide over time as a marker of heterogeneous ventilation of the lung. All subjects underwent pulmonary function testing, body-plethysmography, and forced exhalation capnography. The subjects with COPD also underwent high-resolution computed tomography of the chest. Regression lines were fitted to the slopes of the forced exhalation capnogram curves. There was no difference in the mean levels of exhaled carbon dioxide between the COPD and the healthy groups (p > 0.48). We found a significant difference in the mean slope of the forced exhalation capnogram for the COPD subjects compared to the healthy subjects (p = 0.01). Most important, for the COPD subjects, there was a significant positive correlation between the slope of the forced exhaled capnogram and a defined radiodensity measurement of the lung by high-resolution computed tomography (r² = 0.49, p = 0.02). The slope of the forced exhalation capnogram may be a simple way to determine physiological changes in the lungs in patients with COPD that are not obtainable with standard pulmonary function tests. Forced exhalation capnography would be of great clinical benefit if it can identify early disease changes and at-risk individuals.

Ammonia concentrations in exhaled breath (eNH₃) and skin gas of 20 healthy subjects were measured on-line with a commercial cavity ring-down spectrometer and compared to saliva pH and plasma ammonium ion (NH⁺₄), urea and creatinine concentrations. Special attention was given to mouth, nose and skin sampling procedures and the accurate quantification of ammonia in humid gas samples. The obtained median concentrations were 688 parts per billion by volume (ppbv) for mouth-eNH₃, 34 ppbv for nose-eNH₃, and 21 ppbv for both mouth- and nose-eNH₃ after an acidic mouth wash (MW). The median ammonia emission rate from the lower forearm was 0.3 ng cm⁻² min⁻¹. Statistically significant (p < 0.05) correlations between the breath, skin and plasma ammonia/ammonium concentrations were not found. However, mouth-eNH₃ strongly (p < 0.001) correlated with saliva pH. This dependence was also observed in detailed measurements of the diurnal variation and the response of eNH₃ to the acidic MW. It is concluded that eNH₃ as such does not reflect plasma but saliva and airway mucus NH⁺₄ concentrations and is affected by saliva and airway mucus pH. After normalization with saliva pH using the Henderson–Hasselbalch equation, mouth-eNH₃ correlated with plasma NH⁺₄, which points to saliva and plasma NH⁺₄ being linked via hydrolysis of salivary urea.

We report on the search for low molecular weight molecules—possibly accumulated in the bloodstream and body—in the exhaled breath of uremic patients with kidney malfunction. We performed non-invasive analysis of the breath gas of 96 patients shortly before and several times after kidney transplantation using proton-transfer-reaction mass spectrometry (PTR-MS), a very sensitive technique for detecting trace amounts of volatile organic compounds. A total of 642 individual breath analyses which included at least 41 different chemical components were carried out. Correlation analysis revealed one particular breath component with a molecular mass of 114 u (unified atomic mass units) that clearly correlated with blood serum creatinine, which is the currently accepted marker for assessing the function of the kidney. In particular, daily urine production showed good correlation with the identified breath marker. An independent set of seven samples taken from three patients at the onset of dialysis and three controls with normal kidney function confirmed a significant difference in concentration between patients and controls for a compound with a molecular mass of 114.1035 u using high mass resolving proton-transfer-reaction time-of-flight mass spectrometry (PTR-TOF-MS). A chemical composition of C₇H₁₄O was derived for the respective component. Fragmentation experiments on the same samples using proton-transfer-reaction triple-quadrupole tandem mass spectrometry (PTR-QqQ-MS) suggested that this breath marker is a C₇-ketone or a branched C₇-aldehyde. Non-invasive real-time monitoring of the kidney function via this breath marker could be a possible future procedure in the clinical setting.

Carbon monoxide (CO), a low molecular weight gas, is a ubiquitous environmental product of organic combustion, which is also produced endogenously in the body, as the byproduct of heme metabolism. CO binds to hemoglobin, resulting in decreased oxygen delivery to bodily tissues at toxicological concentrations. At physiological concentrations, CO may have endogenous roles as a potential signaling mediator in vascular function and cellular homeostasis. Exhaled CO (eCO), similar to exhaled nitric oxide (eNO), has been evaluated as a candidate breath biomarker of pathophysiological states, including smoking status, and inflammatory diseases of the lung and other organs. eCO values have been evaluated as potential indicators of inflammation in asthma, stable COPD and exacerbations, cystic fibrosis, lung cancer, or during surgery or critical care. The utility of eCO as a marker of inflammation and its potential diagnostic value remain incompletely characterized. Among other candidate 'medicinal gases' with therapeutic potential, (e.g., NO and H₂S), CO has been shown to act as an effective anti-inflammatory agent in preclinical animal models of inflammatory disease, acute lung injury, sepsis, ischemia/reperfusion injury and organ graft rejection. Current and future clinical trials will evaluate the clinical applicability of this gas as a biomarker and/or therapeutic in human disease.

The prospects for exploiting proton transfer reaction-time of flight-mass spectrometry (PTR-ToF-MS) in medical diagnostics are illustrated through a series of case studies. Measurements of acetone levels in the breath of 68 healthy people are presented along with a longitudinal study of a single person over a period of 1 month. The median acetone concentration across the population was 484 ppbV with a geometric standard deviation (GSD) of 1.6, whilst the average GSD during the single subject longtitudinal study was 1.5. An additional case study is presented which highlights the potential of PTR-ToF-MS in pharmacokinetic studies, based upon the analysis of online breath samples of a person following the consumption of ethanol. PTR-ToF-MS comes into its own when information across a wide mass range is required, particularly when such information must be gathered in a short time during a breathing cycle. To illustrate this property, multicomponent breath analysis in a small study of cystic fibrosis patients is detailed, which provides tentative evidence that online PTR-ToF-MS analysis of tidal breath can distinguish between active infection and non-infected patients.

Asthma and chronic obstructive pulmonary disease (COPD) are distinct but clinically overlapping airway disorders which often create diagnostic and therapeutic dilemmas. Current strategies to discriminate these diseases are limited by insensitivity and poor performance due to biologic variability. We tested the hypothesis that a gas chromatograph/differential mobility spectrometer (GC/DMS) sensor could distinguish between clinically well-defined groups with airway disorders based on the volatile organic compounds (VOCs) obtained from exhaled breath. After comparing VOC profiles obtained from 13 asthma, 5 COPD and 13 healthy control subjects, we found that VOC profiles distinguished asthma from healthy controls and also a subgroup of asthmatics taking the drug omalizumab from healthy controls. The VOC profiles could not distinguish between COPD and any of the other groups. Our results show a potential application of the GC/DMS for non-invasive and bedside diagnostics of asthma and asthma therapy monitoring. Future studies will focus on larger sample sizes and patient cohorts.

The levels of compounds in exhaled mouth air do not necessarily reflect levels in the systemic circulation as bacteria can bio-transform substrates to produce compounds within the mouth. This should be of concern to researchers measuring breath volatiles with the aim of diagnosing systemic or metabolic conditions as very little is known about the origin of many compounds detected on the breath. This pilot study investigated the production of volatile compounds by bacterial communities present within the mouth. Solid-phase micro-extraction was used to extract volatiles from the headspace gas of two Gram-positive and two Gram-negative bacterial cultures known to be present within the mouth and from tongue biofilm microflora. Analyses were undertaken using gas chromatography mass spectrometry. Between 64 and 82 volatile compounds were detected from sampling the headspace gas above each of the cultures. Gram-negative anaerobes were found to produce more volatile sulfur compounds (VSCs) and amines. Solobacterium moorei, a Gram-positive species was however found to produce higher levels of acids, hydrocarbons, alcohols and aldehydes than the other species studied. Tongue-scrape biofilm systems at lower pH gave more hydrocarbons, ketones and fatty acids whilst at higher pH more alcohols, aldehydes, VSCs and amines were detected in the headspace. The results show that a number of compounds detected in mouth breath are produced by anaerobic bacteria in tongue biofilms. Thus, the contribution of volatiles from oral anaerobes cannot be ignored and more research is required to identify the major source of breath compounds as this will help determine their clinical significance as indicators of systemic disease or metabolic disorders in the body.

The evolution of breath composition during oral glucose tolerance tests (OGTTs) was analysed by thermal desorption/gas chromatography/mass spectrometry in 16 subjects and correlated to blood glucose levels. The glucose tolerance tests classified five of the subjects as diabetics, eight as affected by impaired glucose tolerance and three as normoglycaemic. Acetone levels were generally higher in diabetics (average concentration values: diabetics, 300 ± 40 ppbv; impaired glucose tolerance, 350 ± 30 ppbv; normoglycaemic, 230 ± 20 ppbv) but the large inter-individual variability did not allow us to identify the three groups by this parameter alone. The exhalation of 3-hydroxy-butan-2-one and butane-2,3-dione, likely due to the metabolization of glucose by bacteria in the mouth, was also observed. Future work will involve the extension of the analyses to other volatile compounds by attempting to improve the level of discrimination between the various classes of subjects.

Patients with end-stage renal disease (ESRD) are at risk for a numerous complications. This study was intended to evaluate breath analysis for monitoring and therapy initiation under haemodialysis (HD). Exhaled alveolar air from 30 ESRD patients during 4 h thrice-weekly HD was analysed by means of HS-SPME-GC-MS. Venous blood samples were taken for determination of conventional serum parameters. Exhaled concentrations of isoprene (10–589 ppbV) were dropped at initiation of HD and increased at the end of HD. Isoprene concentration changes were similar to changes of serum LDH activities. Variation of exhaled acetone concentrations (59 to 8509 ppbV) was significantly lower in diabetic patients when compared to non-diabetics. Exhaled pentane (0.3 to 12 ppbV) increased at onset of HD and returned to baseline levels afterwards. Benzene concentrations showed typical washout characteristics. Ethanol and DMS concentrations remained constant during HD. Breath analysis can be used to recognize oxidative stress, metabolic conditions and haemolysis during HD. Hence, non-invasive breath testing could be used to monitor ESRD patients under HD and prevent them from being affected by well-known detrimental side effects of renal replacement therapy.

Lung transplantation is the only available treatment for some end-stage lung diseases. However, patients following lung transplantation need tight control to prevent serious complications, but mainly invasive techniques are available. An electronic nose is a non-invasive way to measure exhaled volatiles. In this study we investigated the potential of electronic nose measurements in lung transplant patients and compared the 'breathprint' with clinical parameters. Sixteen patients with lung transplant and 33 healthy subjects participated in the study. Exhaled breath was collected; laboratory tests and lung function measurements were carried out. Breath samples were processed by an electronic nose, analysed using principal component analysis and compared to blood (CRP, tacrolimus) and lung function parameters. Significant differences were found in exhaled breath volatile compound pattern between healthy subjects and lung transplant recipients. The plasma level of tacrolimus showed significant relationship with 'breathprint' in lung transplanted patients. Patients living with transplanted lungs can be discriminated from healthy subjects by exhaled breath volatile organic compounds' profile. Treatment after lung transplantation needs to be taken into consideration when using an electronic nose as medication may have profound influence on breathprints.

The discovery of nitric oxide (NO) as a signalling and regulatory molecule and its subsequent detection in the exhaled breath has not only yielded new mechanistic insights but also diagnostic opportunities and therapeutic targets in several important medical conditions. In diseases involving chronic pulmonary inflammation such as asthma that affects millions worldwide, exhaled NO has achieved spectacular successes with patients currently owning handheld devices and monitoring inflammatory aspects of their conditions in their own homes. This has been facilitated by recognition by regulatory bodies, scientific and clinical societies and insurance companies. While characteristic changes in exhaled NO have also been observed in acute lung injury (ALI), the promise of exhaled NO as a surrogate biomarker of this life-threatening disease has not been achieved. In this work, we have analysed factors contributing to successes of exhaled NO in the asthma field and contrasted these on the ALI field. We provide a snapshot of current status of exhaled NO field in ALI and propose a framework for definite evaluation of exhaled NO as a clinically useful biomarker.

Recently, we have shown that the (+)-[¹³C]-pantoprazole is more dependent on CYP2C19 metabolic status than (−)-[¹³C]-pantoprazole. In this study, we tested the hypothesis that (+)-[¹³C]-pantoprazole is a more sensitive and selective probe for evaluating CYP2C19 enzyme activity than the racemic mixture. (+)-[¹³C]-pantoprazole (95 mg) was administered orally in a sodium bicarbonate solution to healthy volunteers. Breath and plasma samples were collected before and up to 720 min after dosing. The ¹³CO₂ in exhaled breath samples was measured by infrared spectrometry. Ratios of ¹³CO₂/¹²CO₂ after (+)-[¹³C]-pantoprazole relative to ¹³CO₂/¹²CO₂ at baseline were expressed as delta over baseline (DOB). (+)-[¹³C]-pantoprazole concentrations were measured by HPLC. Genomic DNA extracted from whole blood was genotyped for CYP2C19*2, *3 and *17 using Taqman assays. Statistically significant differences in the area under the plasma concentration time curve (AUC_{plasma(0-∞)} (p < 0.001) and oral clearance (<0.01) of (+)-[¹³C]-pantoprazole as well as in the breath test indices (delta over baseline, DOB₃₀; and area under the DOB versus time curve, AUC_DOB(0–120)) (p < 0.01) were observed among poor, intermediate and extensive metabolizer of CYP2C19. DOB₃₀ and AUC_DOB(0–120) adequately distinguished poor metabolizer from intermediate and extensive metabolizer of CYP2C19. Breath test indices significantly correlated with plasma elimination parameters of (+)-[¹³C]-pantoprazole (Pearson correlations: −0.68 to −0.73). Although relatively higher breath test indices were observed after administration of (+)-[¹³C]-pantoprazole (this study) than after (±)-[¹³C]-pantoprazole (previous study), the performance of the racemic and the enantiomer as marker of CYP2C19 activity remained similar. Our data confirm that the metabolism of (+)-[¹³C]-pantoprazole is highly dependent on CYP2C19 metabolic status, but the breath test derived from it is not superior to the racemic [¹³C]-pantoprazole in evaluating CYP2C19 activity in vivo. Thus, racemic [¹³C]-pantoprazole which is relatively easy to synthesize and more stable than (+)-[¹³C]-pantoprazole is adequate as a probe of this enzyme.

Many (multi-centre) breath-analysis studies require transport and storage of samples. We aimed to test the effect of transportation and storage using sorbent tubes of exhaled breath samples for diagnostic accuracy of eNose and GC-MS analysis. As a reference standard for diagnostic accuracy, breath samples of asthmatic patients and healthy controls were analysed by three eNose devices. Samples were analysed by GC-MS and eNose after 1, 7 and 14 days of transportation and storage using sorbent tubes. The diagnostic accuracy for eNose and GC-MS after storage was compared to the reference standard. As a validation, the stability was assessed of 15 compounds known to be related to asthma, abundant in breath or related to sampling and analysis. The reference test discriminated asthma and healthy controls with a median AUC (range) of 0.77 (0.72–0.76). Similar accuracies were achieved at t₁ (AUC eNose 0.78; GC-MS 0.84), t₇ (AUC eNose 0.76; GC-MS 0.79) and t₁₄ (AUC eNose 0.83; GC-MS 0.84). The GC-MS analysis of compounds showed an adequate stability for all 15 compounds during the 14 day period. Short-term transportation and storage using sorbent tubes of breath samples does not influence the diagnostic accuracy for discrimination between asthma and health by eNose and GC-MS.

The identification of bacteria by their volatilomes is of interest to many scientists and clinicians as it holds the promise of diagnosing infections in situ, particularly lung infections via breath analysis. While there are many studies reporting various bacterial volatile biomarkers or fingerprints using in vitro experiments, it has proven difficult to translate these data to in vivo breath analyses. Therefore, we aimed to create secondary electrospray ionization-mass spectrometry (SESI-MS) pathogen fingerprints directly from the breath of mice with lung infections. In this study we demonstrated that SESI-MS is capable of differentiating infected versus uninfected mice, P. aeruginosa-infected versus S. aureus-infected mice, as well as distinguish between infections caused by P. aeruginosa strains PAO1 versus FRD1, with statistical significance (p < 0.05). In addition, we compared in vitro and in vivo volatiles and observed that only 25–34% of peaks are shared between the in vitro and in vivo SESI-MS fingerprints. To the best of our knowledge, these are the first breath volatiles measured for P. aeruginosa PAO1, FRD1, and S. aureus RN450, and the first comparison of in vivo and in vitro volatile profiles from the same strains using the murine infection model.

A classification of various categories of entrapped people under the ruins of collapsed buildings after earthquakes, technical failures or explosions is proposed. Type and degree of injury at the moment of building collapse and duration of entrapment are the two basic parameters in this classification. The aim is to provide sources and types of volatile organic compounds (VOCs) that can be used for establishing a new method for locating entrapped victims based on human chemical signatures. Potential target compounds, among others, are ammonia, acetone, isoprene, dimethylsulfide, dimethyldisulfide and trimethylamine. In this context, the possible neuroendocrine, metabolic and physical responses of potential victims during the different types of entrapment are correlated with the sources of VOCs such as expired air, urine, blood and sweat. The proposed classification scheme was developed as part of an integrated research project which investigates the use of combined audio, video and chemical methods for the early location of entrapped people under the ruins of collapsed buildings.