The Impact of a Graded Maximal Exercise Protocol on Exhaled Volatile Organic Compounds: A Pilot Study.

Exhaled volatile organic compounds (VOCs) are of interest due to their minimally invasive sampling procedure. Previous studies have investigated the impact of exercise, with evidence suggesting that breath VOCs reflect exercise-induced metabolic activity. However, these studies have yet to investigate the impact of maximal exercise to exhaustion on breath VOCs, which was the main aim of this study. Two-litre breath samples were collected onto thermal desorption tubes using a portable breath collection unit. Samples were collected pre-exercise, and at 10 and 60 min following a maximal exercise test (VO2MAX). Breath VOCs were analysed by thermal desorption-gas chromatography-mass spectrometry using a non-targeted approach. Data showed a tendency for reduced isoprene in samples at 10 min post-exercise, with a return to baseline by 60 min. However, inter-individual variation meant differences between baseline and 10 min could not be confirmed, although the 10 and 60 min timepoints were different (p = 0.041). In addition, baseline samples showed a tendency for both acetone and isoprene to be reduced in those with higher absolute VO2MAX scores (mL(O2)/min), although with restricted statistical power. Baseline samples could not differentiate between relative VO2MAX scores (mL(O2)/kg/min). In conclusion, these data support that isoprene levels are dynamic in response to exercise.

VOCCluster: Untargeted Metabolomics Feature Clustering Approach for Clinical Breath Gas Chromatography/Mass Spectrometry Data.

Metabolic profiling of breath analysis involves processing, alignment, scaling, and clustering of thousands of features extracted from gas chromatography/mass spectrometry (GC/MS) data from hundreds of participants. The multistep data processing is complicated, operator error-prone, and time-consuming. Automated algorithmic clustering methods that are able to cluster features in a fast and reliable way are necessary. These accelerate metabolic profiling and discovery platforms for next-generation medical diagnostic tools. Our unsupervised clustering technique, VOCCluster, prototyped in Python, handles features of deconvolved GC/MS breath data. VOCCluster was created from a heuristic ontology based on the observation of experts undertaking data processing with a suite of software packages. VOCCluster identifies and clusters groups of volatile organic compounds (VOCs) from deconvolved GC/MS breath with similar mass spectra and retention index profiles. VOCCluster was used to cluster more than 15 000 features extracted from 74 GC/MS clinical breath samples obtained from participants with cancer before and after a radiation therapy. Results were evaluated against a panel of ground truth compounds and compared to other clustering methods (DBSCAN and OPTICS) that were used in previous metabolomics studies. VOCCluster was able to cluster those features into 1081 groups (including endogenous and exogenous compounds and instrumental artifacts) with an accuracy rate of 96% (±0.04 at 95% confidence interval).

Dynamic vapor generator that simulates transient odor emissions of victims entrapped in the voids of collapsed buildings.

The design, development, and validation of a dynamic vapor generator are presented. The generator simulates human scent (odor) emissions from trapped victims in the voids of collapsed buildings. The validation of the device was carried out using a reference detector: a quadrupole mass spectrometer equipped with a pulsed sampling (PS-MS) system. A series of experiments were conducted for evaluating the simulator's performance, defining types and weights of different factors, and proposing further optimization of the device. The developed device enabled the production of stable and transient odor profiles in a controllable and reproducible way (relative standard deviation, RSD < 11%) at ppbv to low ppmv concentrations and allowed emission durations up to 30 min. Moreover, the factors affecting its optimum performance (i.e., evaporation chamber temperature, air flow rate through the mixing chamber, air flow rate through the evaporation chamber, and type of compound) were evaluated through an analysis of variance (ANOVA) tool revealing the next steps toward optimizing the generator. The developed simulator, potentially, can also serve the need for calibrating and evaluating the performance of analytical devices (e.g., gas chromatographers, ion mobility spectrometers, mass spectrometers, sensors, e-noses) in the field. Furthermore, it can contribute in better training of urban search and rescue (USaR) canines.

High throughput volatile fatty acid skin metabolite profiling by thermal desorption secondary electrospray ionisation mass spectrometry.

The non-invasive nature of volatile organic compound (VOC) sampling from skin makes this a priority in the development of new screening and diagnostic assays. Evaluation of recent literature highlights the tension between the analytical utility of ambient ionisation approaches for skin profiling and the practicality of undertaking larger campaigns (higher statistical power), or undertaking research in remote locations. This study describes how VOC may be sampled from skin and recovered from a polydimethylsilicone sampling coupon and analysed by thermal desorption (TD) interfaced to secondary electrospray ionisation (SESI) time-of-flight mass spectrometry (MS) for the high throughput screening of volatile fatty acids (VFAs) from human skin. Analysis times were reduced by 79% compared to gas chromatography-mass spectrometry methods (GC-MS) and limits of detection in the range 300 to 900 pg cm(-2) for VFA skin concentrations were obtained. Using body odour as a surrogate model for clinical testing 10 Filipino participants, 5 high and 5 low odour, were sampled in Manilla and the samples returned to the UK and screened by TD-SESI-MS and TD-GC-MS for malodour precursors with greater than >95% agreement between the two analytical techniques. Eight additional VFAs were also identified by both techniques with chains 4 to 15 carbons long being observed. TD-SESI-MS appears to have significant potential for the high throughput targeted screening of volatile biomarkers in human skin.

Detection of metabolites of trapped humans using ion mobility spectrometry coupled with gas chromatography.

For the first time, ion mobility spectrometry coupled with rapid gas chromatography, using multicapillary columns, was applied for the development of a pattern of signs of life for the localization of entrapped victims after disaster events (e.g., earthquake, terroristic attack). During a simulation experiment with entrapped volunteers, 12 human metabolites could be detected in the air of the void with sufficient sensitivity to enable a valid decision on the presence of a living person. Using a basic normalized summation of the measured concentrations, all volunteers involved in the particular experiments could be recognized only few minutes after they entered the simulation void and after less than 3 min of analysis time. An additional independent validation experiment enabled the recognition of a person in a room of ∼25 m(3) after ∼30 min with sufficiently high sensitivity to detect even a person briefly leaving the room. Undoubtedly, additional work must be done on analysis time and weight of the equipment, as well as on validation during real disaster events. However, the enormous potential of the method as a significantly helpful tool for search-and-rescue operations, in addition to trained canines, could be demonstrated.

Gas-phase and solution studies of three resorcin[4]arene derivatives using electrospray time-of-flight mass spectrometry.

Electrospray ionisation mass spectrometry (ESI-MS) has been used to study the relative gas-phase proton and alkali metal (Li, Na, K and Cs) binding affinities of three different resorcin[4]arenes using the kinetic method. Collision-induced dissociation (CID) was used to study the fragmentation of resorcin[4]arene heterodimer sandwich complexes, allowing the relative binding affinity order to be established. All the alkali metal cations have the same gas-phase binding affinity order with the resorcin[4]arene host molecules. At collision energies of > or = 13eV, one of the [resorcin[4]arene+Metal]+, (Metal = Li, Na, K) ions fragmented through break-up of the resorcin[4]arene, whilst the other host resorcin[4]arene remained intact, causing an apparent change in binding affinity at high collision energy. This effect was not observed with caesium, since all complex ions dissociated readily under CID by displacement of the caesium cation. The binding affinity for the protonated resorcin[4]arenes was found to be different from the alkali metal cation binding affinity because of the higher proton affinity of the nitrogen-containing resorcin[4]arenes. It is shown that resorcin[4]arenes containing an oxazine ring can be converted into a ring-opened derivative via an Eschweiler-CLarke reaction in the presence of formic acid. A second ring-opening process also occurs, including a hydrolysis reaction that results in apparent Losses of 12 mass units from the intact resorcin[4]arene. Both these reactions occur in solution before mass spectrometric investigation and cannot be achieved by CID. This observation was confirmed by inducing the Eschweiter-CLarke reaction in a model benzoxazine compound.

Breath testing for SARS-CoV-2 infection.

BACKGROUND: From a public health perspective, the identification of individuals with mild respiratory symptoms due to SARS-CoV-2 infection is important to contain the spread of the disease. The objective of this study was to identify volatile organic compounds (VOCs) in exhaled breath common to infection with different variants of the SARS-CoV-2 virus to inform the development of a point-of-care breath test to detect infected individuals with mild symptoms. METHODS: A prospective, real-world, observational study was conducted on mildly symptomatic out-patients presenting to community test-sites for RT-qPCR SARS-CoV-2 testing when the Alpha, Beta, and Delta variants were driving the COVID-19 pandemic. VOCs in exhaled breath were compared between PCR-positive and negative individuals using TD-GC-ToF-MS. Candidate VOCs were tested in an independent set of samples collected during the Omicron phase of the pandemic. FINDINGS: Fifty breath samples from symptomatic RT-qPCR positive and 58 breath samples from test-negative, but symptomatic participants were compared. Of the 50 RT-qPCR-positive participants, 22 had breath sampling repeated 8-12 weeks later. PCA-X model yielded 12 distinct VOCs that discriminated SARS-CoV-2 active infection compared to recovery/convalescence period, with an area under the receiver operator characteristic curve (AUROC), of 0.862 (0.747-0.977), sensitivity, and specificity of 82% and 86%, respectively. PCA-X model from 50 RT-qPCR positive and 58 negative symptomatic participants, yielded 11 VOCs, with AUROC of 0.72 (0.604-0.803) and sensitivity of 72%, specificity 65.5%. The 11 VOCs were validated in a separate group of SARS-CoV-2 Omicron positive patients' vs healthy controls demonstrating an AUROC of 0.96 (95% CI 0.827-0.993) with sensitivity of 80% specificity of 90%. INTERPRETATION: Exhaled breath analysis is a promising non-invasive, point-of-care method to detect mild COVID-19 infection. FUNDING: Funding for this study was a competitive grant awarded from the Vancouver Coastal Research Institute as well as funding from the BC Cancer Foundation.

Sampling and characterisation of volatile organic compound profiles in human saliva using a polydimethylsiloxane coupon placed within the oral cavity.

Evaluation of published methods reveals that existing methods for saliva sampling do not address the physical-chemical attributes of volatile organic compounds (VOCs). This study describes and presents evidence for adopting in situ sampling of salivary VOCs directly from the oral cavity using a polydimethylsiloxane (PDMS) based sampler. In vitro studies indicated that the vapour pressure of analytes was a factor in both the recovery of analytes and the precision of the recovery. The highest recoveries were observed for VOCs with the lowest vapour pressures, for example 5-nonanol (vapour pressure (P(v)) = 14 Pa) recoveries were approximately 20 times greater than those observed for octane (P(v) = 1726 Pa). Similarly, relative standard deviations reduced with vapour pressure, with the RSD for 5-nonanol responses observed to be 2.7% when compared to RSD = 26% for octane. Evaluation of VOCs recovered from 6 in vivo samples indicated that VOC concentrations in saliva may follow log-normal distributions; log-normal RSDs falling between 4.4% and 18.2% across the range of volatilities encountered. Increasing sampling time from 1 to 30 minutes indicated that the recovery of VOC into the sampler was affected by interaction between different physical-chemical properties and biogenic flux. A sampling time of 10 min was found to offer an acceptable compromise that enabled a representative sample to be acquired for the widest range of observed VOC behaviours with the sampler. The potential to 'tune' the sampling protocol for targeted analysis based on these factors was also noted. Comparison with passive drool saliva collection revealed up to 10(5) enhancement with reduced variability compared to drooled samples. This approach to in situ saliva sampling appears to have significant analytical utility for studying volatile signatures in humans.

Control of dopants/modifiers in differential mobility spectrometry using a piezoelectric injector.

A piezoelectric injector has been interfaced to a differential mobility spectrometer to enable fast and reversible control of dopant/transport-gas modifier levels within the reaction region of the instrument. Operating at 1 Hz with optimised bipolar waveforms for the piezoelectric injector and gas flows within the injector, steady-state 2-butanol mass fluxes of 21 to 1230 ng min(-1) and 1-bromohexane mass fluxes of 149 to 2644 ng min(-1) were delivered to the differential mobility cell. Control of split-flow and transport-gas flow rates enabled rapid and flexible control of the dopant concentrations. The system was consistently reproducible with a relative standard deviation (RSD) of 7.9% at every mass- flux level studied. Stable responses were achieved between 3 to 5 s following a change in the control levels and no significant hysteresis effects were observed. In the positive mode it was possible to control the extent of formation protonated monomer and proton bound cluster ions, tentatively assigned to{C(4)H(9)OH(H(2)O)(n)H}(+) and {(C(4)H(9)OH)(2)(H(2)O)(n)H}(+) and similar control was possible in the negative mode where the concentration relationship for the formation of bromide clusters indicated the presence of multiple ionisation mechanisms. A dopant formulation for the simultaneous control of ions in both the positive and negative modes was demonstrated by the injection of a 50%/50% v/v solution of 2-butanol/1-bromohexane with mass fluxes of 2-butanol in the mixture of between 11 and 1161 ng min(-1) and between 13 and 1325 ng min(-1) for 1-bromohexane.

Fast and automated biomarker detection in breath samples with machine learning.

Volatile organic compounds (VOCs) in human breath can reveal a large spectrum of health conditions and can be used for fast, accurate and non-invasive diagnostics. Gas chromatography-mass spectrometry (GC-MS) is used to measure VOCs, but its application is limited by expert-driven data analysis that is time-consuming, subjective and may introduce errors. We propose a machine learning-based system to perform GC-MS data analysis that exploits deep learning pattern recognition ability to learn and automatically detect VOCs directly from raw data, thus bypassing expert-led processing. We evaluate this new approach on clinical samples and with four types of convolutional neural networks (CNNs): VGG16, VGG-like, densely connected and residual CNNs. The proposed machine learning methods showed to outperform the expert-led analysis by detecting a significantly higher number of VOCs in just a fraction of time while maintaining high specificity. These results suggest that the proposed novel approach can help the large-scale deployment of breath-based diagnosis by reducing time and cost, and increasing accuracy and consistency.

Peppermint protocol: first results for gas chromatography-ion mobility spectrometry.

ThePeppermint Initiativeseeks to inform the standardisation of breath analysis methods. FivePeppermint Experimentswith gas chromatography-ion mobility spectrometry (GC-IMS), operating in the positive mode with a tritium3H 5.68 keV, 370 MBq ionisation source, were undertaken to provide benchmarkPeppermint Washoutdata for this technique, to support its use in breath-testing, analysis, and research. Headspace analysis of a peppermint-oil capsule by GC-IMS with on-column injection (0.5 cm3) identified 12 IMS responsive compounds, of which the four most abundant were: eucalyptol;ß-pinene;α-pinene; and limonene. Elevated concentrations of these four compounds were identified in exhaled-breath following ingestion of a peppermint-oil capsule. An unidentified compound attributed as a volatile catabolite of peppermint-oil was also observed. The most intense exhaled peppermint-oil component was eucalyptol, which was selected as a peppermint marker for benchmarking GC-IMS. Twenty-five washout experiments monitored levels of exhaled eucalyptol, by GC-IMS with on-column injection (0.5 cm3), att= 0 min, and then att+ 60,t+ 90,t+ 165,t+ 285 andt+ 360 min from ingestion of a peppermint capsule resulting in 148 peppermint breath analyses. Additionally, thePeppermint Washoutdata was used to evaluate clinical deployments with a further five washout tests run in clinical settings generating an additional 35 breath samples. Regression analysis yielded an average extrapolated time taken for exhaled eucalyptol levels to return to baseline values to be 429 ± 62 min (±95% confidence-interval). The benchmark value was assigned to the lower 95% confidence-interval, 367 min. Further evaluation of the data indicated that the maximum number of volatile organic compounds discernible from a 0.5 cm3breath sample was 69, while the use of an in-line biofilter appeared to reduce this to 34.

Assessment of the feasibility of the use of conductive polymers in the fabrication of ion mobility spectrometers.

The development of an ion mobility spectrometer with an injection molded plastic drift tube made from carbon-loaded nylon and the cyclo-olefinpolymer Zeonex is described. Thermogravimetric assessment combined with headspace analysis by ion mobility spectrometry and gas chromatography-mass spectrometry indicated that Zeonex encapsulated carbon-loaded nylon could be used to fabricate a snap-together injection molded stacked ring drift tube, 4.25 cm long that could be substituted for a conventional wire-wound heated ceramic drift tube of the same length into a high temperature ion mobility spectrometer. Temperature stability experiments indicated that such a combination of polymers produced stable water-based reactant ion peaks [(H(2)O)(n)H](+) up to a temperature of approximately 50 °C. Above this temperature, ammonia appeared to outgas, resulting in the production of [(H(2)O)(n)(NH(4))(m)H](+) type species before, at higher temperatures, the release of oligomeric entities suppressed resolved ion responses. Surface charging effects were also observed, and over a period of continuous operation of 4 h, these caused suppression of the signal intensity (1.11-0.954 V) and an apparent mobility shift in the observed responses (K(0) = 1.86-1.90 cm(2) V(-1) s(-1)). Substituting nylon, a polymer with a significantly lower surface resistivity, for the Zeonex demonstrated how surface charging phenomena could be managed though control of surface resistivity in future polymer formulations. The device was challenged successfully with test atmospheres of hexan-1-ol (K(0) = 1.66 cm(2) V(-1) s(-1) (monomer) and 1.32 cm(2) V(-1) s(-1)(dimer)) and dimethylmethyl phosphonate (K(0) = 1.70 cm(2) V(-1) s(-1) (monomer) and 1.44 cm(2) V(-1) s(-1) (dimer)). The potential advantages of developing polymeric systems using more advanced polymer formulations are discussed.

IABR Symposium 2021 meeting report: breath standardization, sampling, and testing in a time of COVID-19.

Due to COVID-19 travel disruptions, the International Association of Breath Research hosted the planned 2021 Breath Summit virtually as a symposium with oral and poster presentations. The event was comprised of a week-long social media asynchronous online event for sharing research abstracts, posters and discussions. Subsequently, there were two days of real-time webinar platform interactions each featuring three technical presentations, open forum questions, answers, and commentary. The symposium was well attended and well received. It allowed the breath community to share new research and to reconnect with colleagues and friends. This report presents an overview of the topics presented and various salient discussion points.

Volatile organic compounds in a headspace sampling system and asthmatics sputum samples.

The headspace of a biological sample contains exogenous volatile organic compounds (VOCs) present within the sampling environment which represent the background signal. This study aimed to characterise the background signal generated from a headspace sampling system in a clinical site, to evaluate intra- and inter-day variation of background VOC and to understand the impact of a sample itself upon commonly reported background VOC using sputum headspace samples from severe asthmatics. The headspace, in absence of a biological sample, was collected hourly from 11am to 3pm within a day (time of clinical samples acquisition), and from Monday to Friday in a week, and analysed by thermal desorption-gas chromatography-mass spectrometry (TD-GC-MS). Chemometric analysis identified 1120 features, 37 of which were present in at least the 80% of all the samples. The analyses of intra- and inter-day background variations were performed on 13 of the most abundant features, ubiquitously present in headspace samples. The concentration ratios relative to background were reported for the selected abundant VOC in 36 asthmatic sputum samples, acquired from 36 stable severe asthma patients recruited at Glenfield Hospital, Leicester, UK. The results identified no significant intra- or inter-day variations in compounds levels and no systematic bias ofz-scores, with the exclusion of benzothiazole, whose abundance increased linearly between 11am and 3pm with a maximal intra-day fold change of 2.13. Many of the identified background features are reported in literature as components of headspace of biological samples and are considered potential biomarkers for several diseases. The selected background features were identified in headspace of all severe asthma sputum samples, albeit with varying levels of enrichment relative to background. Our observations support the need to consider the background signal derived from the headspace sampling system when developing and validating headspace biomarker signatures using clinical samples.

The variability of volatile organic compounds in the indoor air of clinical environments.

The development of clinical breath-analysis is confounded by the variability of background volatile organic compounds (VOCs). Reliable interpretation of clinical breath-analysis at individual, and cohort levels requires characterisation of clinical-VOC levels and exposures. Active-sampling with thermal-desorption/gas chromatography-mass spectrometry recorded and evaluated VOC concentrations in 245 samples of indoor air from three sites in a large National Health Service (NHS) provider trust in the UK over 27 months. Data deconvolution, alignment and clustering isolated 7344 features attributable to VOC and described the variability (composition and concentration) of respirable clinical VOC. 328 VOC were observed in more than 5% of the samples and 68 VOC appeared in more than 30% of samples. Common VOC were associated with exogenous and endogenous sources and 17 VOC were identified as seasonal differentiators. The presence of metabolites from the anaesthetic sevoflurane, and putative-disease biomarkers in room air, indicated that exhaled VOC were a source of background-pollution in clinical breath-testing activity. With the exception of solvents, and waxes associated with personal protective equipment (PPE), exhaled VOC concentrations above 3µg m-3are unlikely to arise from room air contamination, and in the absence of extensive survey-data, this level could be applied as a threshold for inclusion in studies, removing a potential environmental confounding-factor in developing breath-based diagnostics.

Novel noninvasive identification of biomarkers by analytical profiling of chronic wounds using volatile organic compounds.

A complex profile of volatile organic compounds ("VOC"s) emanates from human skin, which is altered by changes in the body's metabolic or hormonal state, the external environment, and the bacterial species colonizing the skin surface. The aim of this study was to compare VOC profiles sampled from chronic leg wounds with those from asymptomatic skin. Five participants with chronic arterial leg ulcers were selected. VOC samples were obtained using polydimethylsilicone membranes ("skin-patch method") and analyzed by gas chromatography-ion trap mass spectrometry. Resultant data were analyzed using multivariate analysis and mass spectral matches were compared against the National Institute of Standards and Technology database. Principal component analysis showed differences in profiles obtained from healthy skin and boundary areas and between profiles from healthy skin and lesion samples (p<0.05). Partial least squares for discriminant analysis gave an average prediction accuracy of 73.3% (p<0.05). Mass spectral matching (verified against microbial swab results) identified unique VOCs associated with each sample area, wound bacterial colonization, and ingested medications. This study showcases a reproducible, robust, noninvasive methodology that is applicable in a clinical setting and may offer a new, hitherto unexplored, class of biochemical markers underpinning the metabolism of chronic wounds.

Optimisation of secondary electrospray ionisation (SESI) for the trace determination of gas-phase volatile organic compounds.

An electrospray ionisation triple quadrupole mass spectrometer (Varian 1200 L) was modified to accept nitrogen samples containing low concentrations of volatile organic compounds. Six candidate probe compounds, methyl decanoate, octan-3-one, 2-ethylhexanoic acid, 1,4-diaminobutane, dimethyl methylphosphonate, and 2,3-butanediol, at concentrations below 50 ppb(v) were generated with permeation tubes in a test atmosphere generator. The concept of using a set of molecular probes to evaluate gas-phase electrospray ionisation of volatile analytes was assessed and the feasibility of adopting a unified ionisation approach for gas and liquid contamination of exobiotic environments established. 450 experiments were run in a five-replicate, fifteen-level, three-factor, central-composite-design with exponential dilution for each of the six probe compounds studied. The three factors studied were ionisation voltage, drying-gas flow and nebulising-gas flow. Parametric modelling by regression analysis enabled the differences in the ionisation behaviours of the probe compounds to be described by the optimisation models. Regression coefficients were in the range 0.91 to 0.99, indicating satisfactory levels of precision in the optimisation models. A wide range in ionisation efficiency was observed, with different optimised conditions required for the probe compounds. It was evident that no one factor appeared to dominate the response and the different factors produced different effects on the responses for the different molecules. 1,4-Butanediamine and dimethyl methylphosphonate required significantly lower ionisation voltages (1.2 kV) than the other four, which achieved optimised sensitivity towards the maximum voltage used in this design (5 to 6 kV). Drying-gas flow rates were found to be more important than nebulising-gas flow rates. However, variations in the constant term B(0) in the optimisation models indicated that other factors, not included in this study, were also likely to be involved in the ionisation process. Electrolyte-flow rate and ionisation temperature were proposed for follow up studies. Exponential dilution data indicated sensitive and analytically useful responses in the target range of 5 to 50 ppb(v) for all six compounds. Significantly, responses were seen at concentrations significantly below 5 ppb(v), with sub ppt(v) responses observed for 1,4-butanediamine, 2-ethylhexanoic acid, dimethylmethylphosphonate, and 1,3-butanediol. Responses in the ppt(v) to ppb(v) range were observed for the remaining two compounds. The observations from this study demonstrated the utility of adopting a set of probe compounds to evaluate electrospray ionisation performance for volatile organic compound based assays; indicated the existence of multiple ionisation mechanisms; and revealed potential sensitivity at the parts per quadrillion level ppq(v).

Non-invasive metabolomic analysis of breath using differential mobility spectrometry in patients with chronic obstructive pulmonary disease and healthy smokers.

The rapid, accurate and non-invasive diagnosis of respiratory disease represents a challenge to clinicians, and the development of new treatments can be confounded by insufficient knowledge of lung disease phenotypes. Exhaled breath contains a complex mixture of volatile organic compounds (VOCs), some of which could potentially represent biomarkers for lung diseases. We have developed an adaptive sampling methodology for collecting concentrated samples of exhaled air from participants with impaired respiratory function, against which we employed two-stage thermal desorption gas chromatography-differential mobility spectrometry (GC-DMS) analysis, and showed that it was possible to discriminate between participants with and without chronic obstructive pulmonary disease (COPD). A 2.5 dm(3) volume of end tidal breath was collected onto adsorbent traps (Tenax TA/Carbotrap), from participants with severe COPD and healthy volunteers. Samples were thermally desorbed and analysed by GC-DMS, and the chromatograms analysed by univariate and multivariate analyses. Kruskal-Wallis ANOVA indicated several discriminatory (p < 0.01) signals, with good classification performance (receiver operator characteristic area up to 0.82). Partial least squares discriminant analysis using the full DMS chromatograms also gave excellent discrimination between groups (alpha = 19% and beta = 12.4%).

Sensors' array of aspiration ion mobility spectrometer as a tool for bacteria discrimination.

The possibility of achieving bacterial discrimination using a miniaturized aspiration ion mobility spectrometer model ChemPro-100i (Environics Oy) has been tested by interrogating the headspace air samples above in vitro bacterial cultures of three species - Escherichia coli, Bacillus subtilis and Staphylococcus aureus, respectively. The ChemPro-100i highly integrated seven sensor array, composed of one a-IMS cell, three MOS (metal oxide sensors), one FET (field effect transistor) sensor and two SC (semiconductor) sensors, provided enough analytical information to discriminate between the three bacterial species. Statistical data processing using either principal component analysis (PCA) or partial least squares discriminant analysis (PLS-DA) was accomplished. We concluded that although the data from the aspiration-type ion mobility sensor, with its 16 ion detectors, is absolutely sufficient to discriminate between various bacteria using their volatile compounds' chemical profile, the other six sensors deliver additional, valuable information.

Breath markers for therapeutic radiation.

Radiation dose is important in radiotherapy. Too little, and the treatment is not effective, too much causes radiation toxicity. A biochemical measurement of the effect of radiotherapy would be useful in personalisation of this treatment. This study evaluated changes in exhaled breath volatile organic compounds (VOC) associated with radiotherapy with thermal desorption gas chromatography mass-spectrometry followed by data processing and multivariate statistical analysis. Further the feasibility of adopting gas chromatography ion mobility spectrometry for radiotherapy point-of-care breath was assessed. A total of 62 participants provided 240 end-tidal 1 dm3 breath samples before radiotherapy and at 1, 3, and 6 h post-exposure, that were analysed by thermal-desorption/gas-chromatography/quadrupole mass-spectrometry. Data were registered by retention-index and mass-spectra before multivariate statistical analyses identified candidate markers. A panel of sulfur containing compounds (thio-VOC) were observed to increase in concentration over the 6 h following irradiation. 3-methylthiophene (80 ng.m-3 to 790 ng.m-3) had the lowest abundance while 2-thiophenecarbaldehyde(380 ng.m-3 to 3.85 µg.m-3) the highest; note, exhaled 2-thiophenecarbaldehyde has not been observed previously. The putative tumour metabolite 2,4-dimethyl-1-heptene concentration reduced by an average of 73% over the same time. Statistical scoring based on the signal intensities thio-VOC and 3-methylthiophene appears to reflect individuals' responses to radiation exposure from radiotherapy. The thio-VOC are hypothesised to derive from glutathione and Maillard-based reactions and these are of interest as they are associated with radio-sensitivity. Further studies with continuous monitoring are needed to define the development of the breath biochemistry response to irradiation and to determine the optimum time to monitor breath for radiotherapy markers. Consequently, a single 0.5 cm3 breath-sample gas chromatography-ion mobility approach was evaluated. The calibrated limit of detection for 3-methylthiophene was 10 µg.m-3 with a lower limit of the detector's response estimated to be 210 fg.s-1; the potential for a point-of-care radiation exposure study exists.