Rationale Hospitalisation due to exacerbations of cardiorespiratory disease results in reduced lung function and increased airways obstruction. However, traditional measures of lung function require maximal effort which is difficult when patients are unwell (e.g. FEV1) and may focus on larger airways away from the major part of airways disease (e.g. peak flow). We aimed to measure whole airways function using oscillometry in patients during hospitalisation with cardiorespiratory illness compared with healthy controls. Method Participants (n=310) underwent assessment; 263 were admitted to hospital with acute cardiorespiratory illness (asthma (n=80), COPD (n=75), heart failure (n=46) and pneumonia (n=62)) and 47 healthy controls were included. Participants underwent handheld oscillometry measurements within the first 24 h of admission. Results Oscillometry measurement was feasible in all patients (n=310). There was a significant difference in both absolute and percentage predicted measures of lung mechanics (p<0.05 for all measures), with significantly worse lung mechanics in patients with COPD. Measures of resistance and reactance were worse in those that were more breathless (p<0.0001), had more wheeze (p<0.001) and had low oxygen saturation (p<0.001). No difference was seen based on modified early warning system score or blood biomarkers (eosinophil count, C-reactive protein and brain natriuretic peptide). There were significant improvements in oscillometry measures in those that attended following recovery from acute illness. Conclusion Handheld oscillometry can be feasibly deployed in the acute care setting to obtain information on respiratory mechanics. It demonstrates significant differences in ventilation heterogeneity between patients in the acute care setting and healthy volunteers.

The Peppermint Initiative, established within the International Association of Breath Research, introduced the peppermint protocol, a breath analysis benchmarking effort designed to address the lack of inter-comparability of outcomes across different breath sampling techniques and analytical platforms. Benchmarking with gas chromatography-ion mobility spectrometry (GC-IMS) using peppermint has been previously reported however, coupling micro-thermal desorption (mu TD) to GC-IMS has not yet, been benchmarked for breath analysis. To benchmark mu TD-GC-IMS for breath analysis using the peppermint protocol. Ten healthy participants (4 males and 6 females, aged 20-73 years), were enrolled to give six breath samples into Nalophan bags via a modified peppermint protocol. Breath sampling after peppermint ingestion occurred over 6 h at t = 60, 120, 200, 280, and 360 min. The breath samples (120 cm3) were pre-concentrated in the mu TD before being transferred into the GC-IMS for detection. Data was processed using VOCal, including background subtractions, peak volume measurements, and room air assessment. During peppermint washout, eucalyptol showed the highest change in concentration levels, followed by alpha-pinene and beta-pinene. The reproducibility of the technique for breath analysis was demonstrated by constructing logarithmic washout curves, with the average linearity coefficient of R 2 = 0.99. The time to baseline (benchmark) value for the eucalyptol washout was 1111 min (95% CI: 529-1693 min), obtained by extrapolating the average logarithmic washout curve. The study demonstrated that mu TD-GC-IMS is reproducible and suitable technique for breath analysis, with benchmark values for eucalyptol comparable to the gold standard GC-MS.

This chapter starts with the premise that appropriate statistical and chemometric expertise has been applied to the development of a sampling campaign, for our focus is on the “how” of the acquisition of volatile organic compounds (VOC) from a human participant. Sampling occurs at the moment molecules enter the measurement system, fixing the measurement outcome, and any evaluation of volatilomic data should start with consideration of the sampling technique and the system(s) that move volatile organic compounds (VOC) from the participant to the detector. Just about every substance produced by humans has been analyzed for its VOC profile, and the general principles described in this chapter may be applied to all human emanations. Specifically, though, breath saliva and skin are our focus covering the remits of gas, liquid and solid sample matrices, and our starting point is a reflection on the processes at work within a VOC sampling system.

Young people spend extended periods of time in educational buildings, yet relatively little is known about the air quality in such spaces, or the long-term risks which contaminant exposure places on their health and development. Although standards exist in many countries in relation to indoor air quality in educational buildings, they are rarely subject to detailed post-occupancy evaluation. In this study a novel indoor air quality testing methodology is proposed and demonstrated in the context of assessing the post-occupancy performance of a recently refurbished architecture studio building at Loughborough University, United Kingdom. The approach used provides a monitoring process that was designed to evaluate air quality in accordance with United Kingdom national guidelines (Building Bulletin 101) and international (WELL Building) standards. Additional, scenario-based, testing was incorporated to isolate the presence and source of harmful volatile organic compounds, which were measured using diffusive sampling methods involving analysis by thermal desorption - gas chromatography - mass spectrometry techniques. The findings show that whilst the case-study building appears to perform well in respect to existing national and international standards, these guidelines only assess average CO 2 concentrations and total volatile organic compound limits. The results indicate that existing standards, designed to protect the health and wellbeing of students, are likely to be masking potentially serious indoor air quality problems. The presence of numerous harmful VOCs found in this study indicates that an urgent revaluation of educational building procurement and air quality monitoring guidelines is needed.

Emergency evacuation of critical infrastructures, e.g., airports and high density crowd buildings, like shopping centres or entertainment venues, is considered a critical issue in terms of evacuees' safety; bottlenecks may lead to crowd jamming, causing evacuation delays and possibly putting in danger the evacuees. Vulnerable people, such as people with disabilities are more likely to be injured or killed in an emergency, triggered by a natural or man-made disaster; they are rarely consulted on provisions for their safety and most of them are not prepared for emergencies. This case-study involves the evacuation of people with disabilities at an airport terminal due to a chemical exposure event, under a broader emergency evacuation exercise, targeting at: a) proposing a 'Critical Indicators list' for the inclusion of people with disabilities in evacuation exercises of public buildings; b) providing the lessons learned; and c) reflecting on suggestions regarding preparedness, evacuation and triage in such events.

Background. The SARS-CoV-2 pandemic changed the way the society functioned. The race to develop a rapid, non-invasive, widely available test resulted in multiple studies examining the potential of breath to be that 'game changing test'. Breath sampling is a non-invasive point of care test, but SAR-CoV-2 has introduced a level of danger into collection and analysis that requires a change in workflow to keep staff and participants safe. We developed a SARS-CoV 2 breath test work flow for collection and processing of breath samples in an ambulatory care setting and prospectively evaluated the protocol. Protocol development included testing the effect of respiratory filters on the integrity and reproducibility of breath samples.Methods. Prospective, observational study conducted at community COVID-19 testing sites, collecting breath samples from patients presenting for RT-PCR testing. Breath was collected via Tedlar®, and/or BioVOC-2™ as well as an environmental sample for all participants. Samples were transferred to Tenex tubes, dry purged and analyzed using a Centri automated sample introduction machine, GC, and a Bench-ToF-HD.Results. We successfully collected and processed 528 breath samples from 393 participants at community-based ambulatory COVID-19 test sites. The majority of samples were collected before vaccines were available and throughout the emergence of the Delta Variant. No staff member was infected.Conclusion. We demonstrated a safe workflow for the collection, handling, transport, storage, and analysis of breath samples during the pandemic collecting highly infectious SARS-CoV-2 positive breath samples. This was done without filters as they added complexity to the breath matrix, jeopardizing the sample integrity.

The development of clinical breath-analysis is confounded by the variability of background volatile organic compounds (VOC). Interpretation of clinical breath-data 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 NHS provider trust in the UK over 27 months. 7344 clinical VOC were isolated and 328 VOC and 68 were observed in more than 5% and 30% of samples respectively; associated with exogenous and endogenous sources. 17 VOC were seasonal differentiators. 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-tests. Apart from solvents, and PPE-waxes, exhaled VOC concentrations above 3 µgm-3 are unlikely to arise from room air contamination. This level could be applied as a threshold for inclusion in studies.

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;β-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.

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.

Human flavin-containing monooxygenase 3 (FMO3) in the liver catalyzes a variety of oxygenations of nitrogen- and sulfur-containing medicines and xenobiotic substances. Because of growing interest in drug interactions mediated by polymorphic FMO3, benzydamine N-oxygenation by human FMO3 was investigated as a model reaction. Among the 41 compounds tested, trimethylamine, methimazole, itopride, and tozasertib (50 μM) suppressed benzydamine N-oxygenation at a substrate concentration of 50 μM by approximately 50% after co-incubation. Suppression of N-oxygenation of benzydamine, trimethylamine, itopride, and tozasertib and S-oxygenation of methimazole and sulindac sulfide after co-incubation with the other five of these six substrates was compared using FMO3 proteins recombinantly expressed in bacterial membranes. Apparent competitive inhibition by methimazole (0–50 μM) of sulindac sulfide S-oxygenation was observed with FMO3 proteins. Sulindac sulfide S-oxygenation activity of Arg205Cys variant FMO3 protein was likely to be suppressed more by methimazole than wild-type or Val257Met variant FMO3 protein was. These results suggest that genetic polymorphism in the human FMO3 gene may lead to changes of drug interactions for N- or S-oxygenations of xenobiotics and endogenous substances and that a probe battery system of benzydamine N-oxygenation and sulindac sulfide S-oxygenation activities is recommended to clarify the drug interactions mediated by FMO3.

Acute cardiorespiratory breathlessness accounts for one in eight of all emergency hospitalizations. Early, noninvasive diagnostic testing is a clinical priority that allows rapid triage and treatment. Here, we sought to find and replicate diagnostic breath volatile organic compound (VOC) biomarkers of acute cardiorespiratory disease and understand breath metabolite network enrichment in acute disease, with a view to gaining mechanistic insight of breath biochemical derangements. We collected and analyzed exhaled breath samples from 277 participants presenting acute cardiorespiratory exacerbations and aged-matched healthy volunteers. Topological data analysis phenotypes differentiated acute disease from health and acute cardiorespiratory exacerbation subtypes (acute heart failure, acute asthma, acute chronic obstructive pulmonary disease, and community-acquired pneumonia). A multibiomarker score (101 breath biomarkers) demonstrated good diagnostic sensitivity and specificity (≥80%) in both discovery and replication sets and was associated with all-cause mortality at 2 years. In addition, VOC biomarker scores differentiated metabolic subgroups of cardiorespiratory exacerbation. Louvain clustering of VOCs coupled with metabolite enrichment and similarity assessment revealed highly specific enrichment patterns in all acute disease subgroups, for example, selective enrichment of correlated C5-7 hydrocarbons and C3-5 carbonyls in heart failure and selective depletion of correlated aldehydes in acute asthma. This study identified breath VOCs that differentiate acute cardiorespiratory exacerbations and associated subtypes and metabolic clusters of disease-associated VOCs.

The global increase in agri-food production results in a consequential societal requirement to better manage the unavoidable and copious agri-food waste (AFW) generated throughout the agri-food chain. Currently, attaining a zero AFW status is not feasible due to the inefficiencies in the agri-food chain. However, technologies to recover energy (electricity, heat, biofuel) and value-added biomaterials from AFW exist, and their effective adoption offers significant environmental and economic benefits. However, implementing efficient utilisation and valorisation of AFW at the scale needed is a non-trivial engineering challenge that must accomplish optimised energy yield (and conversion efficiencies) without environmental harm from fugitive emissions and discharge of secondary pollutants. Despite advances in standalone conversion technologies (SCTs), including thermal (incineration), biochemical (fermentation/anaerobic digestion), and thermochemical (pyrolysis, gasification and hydrothermal processes), there are still unresolved challenges (e.g., selectivity, low conversion efficiency, downstream upgrading of energy carriers), exacerbated by the accompanying production of polluting intermediates and by-products that scale with the process; potentially significant sources of GHG emissions and environmental risk if discharged untreated. Integrated conversion technologies (ICTs), that combine SCTs have been proposed as an approach that processes intermediates and by-products for further energy recovery at source. Effective implementation has the potential to enhance conversion efficiencies, energy carriers’ diversification and yield. This critical appraisal of SCTs, advances in SCTs exploitation as ICTs, and developmental challenges describes the opportunities for efficient utilisation of AFW. The resultant characterisation of barriers to adopting efficient conversion technologies for AFW exploitation also aligns with growing country-level assessments of AFW bioenergy potentials and the next generation of clean energy policy priorities.

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.

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. 2023;92: Published https://doi.org/10. 1016/j.ebiom.2023. 104584

Clinical assessment of children with asthma is problematic, and non-invasive biomarkers are needed urgently. Monitoring exhaled volatile organic compounds (VOCs) is an attractive alternative to invasive tests (blood and sputum) and may be used as frequently as required. Standardised reproducible breath-sampling is essential for exhaled-VOC analysis, and although the ReCIVA (Owlstone Medical Limited) breath-sampler was designed to satisfy this requirement, paediatric use was not in the original design brief. The efficacy of the ReCIVA at sampling breath from children has been studied, and 90 breath-samples from 64 children (5-15 years) with, and without asthma (controls), were collected with two different ReCIVA units. Seventy samples (77.8%) contained the specified 1 l of sampled-breath. Median sampling times were longer in children with acute asthma (770.2 s, range: 532.2-900.1 s) compared to stable asthma (690.6 s, range: 477.5-900.1 s; p = 0.01). The ReCIVA successfully detected operational faults, in 21 samples. A leak, caused by a poor fit of the face mask seal was the most common (15); the others were USB communication-faults (5); and, a single instance of a file-creation error. Paediatric breath-profiles were reliably monitored, however synchronisation of sampling to breathing-phases was sometimes lost, causing some breaths not to be sampled, and some to be sampled continuously. This occurred in 60 (66.7%) of the samples and was a source of variability. Importantly, multi-variate modelling of untargeted VOC analysis indicated the absence of significant batch effects for eight operational variables. The ReCIVA appears suitable for paediatric breath-sampling. Post-processing of breath-sample meta-data is recommended to assess the quality of sample-acquisition. Further, future studies should explore the effect of pump-synchronisation faults on recovered VOC profiles, and mask sizes to fit all ages will reduce the potential for leaks and importantly, provide higher levels of comfort to children with asthma.

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 dm(3) 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 mu g.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 cm(3) breath-sample gas chromatography-ion mobility approach was evaluated. The calibrated limit of detection for 3-methylthiophene was 10 mu g.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.

Exhaled breath analysis has the potential to provide valuable insight on the status of various metabolic pathways taking place in the lungs locally and other vital organs, via systemic circulation. For years, volatile organic compounds (VOCs) have been proposed as feasible alternative diagnostic and prognostic biomarkers for different respiratory pathologies. We reviewed the currently published literature on the discovery of exhaled breath VOCs and their utilisation in various respiratory diseases Key barriers in the development of clinical breath tests include the lack of unified consensus for breath collection and analysis and the complexity of understanding the relationship between the exhaled VOCs and the underlying metabolic pathways. We present a comprehensive overview, in light of published literature and our experience from coordinating a national breathomics centre, of the progress made to date and some of the key challenges in the field and ways to overcome them. We particularly focus on the relevance of breathomics to clinicians and the valuable insights it adds to diagnostics and disease monitoring. Breathomics holds great promise and our findings merit further large-scale multicentre diagnostic studies using standardised protocols to help position this novel technology at the centre of respiratory disease diagnostics.

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.