Chemical analysis of flotsam ambergris.

The natural product ambergris is only found rarely on beaches, as jetsam. Even more scarce, or even absent, are accounts of flotsam ambergris. Here, we report the chemical analysis of a rare, large piece (>100kg) of flotsam found in the Atlantic in 2019. About 95% of subsamples from the outside of the coprolith was soluble in dichloromethane. Of this, FTIR spectroscopy, APCI-MS and GC-MS indicated the presence of ambrein. Radiocarbon dating indicated that the sample was post 1950s in age. The 13C/12C isotope ratio (-22.5 ‰) was typical of those reported to date for whale 'body' ambergris. Metals of ambergris have hardly been reported previously. The distribution found here for the flotsam, was dominated by copper and zinc, which is similar to that of several squid species. This is also consistent with the presence of squid beaks in the coprolith. Squid are a major prey species of sperm whales.

Fulfilling the Promise of Breathomics: Considerations for the Discovery and Validation of Exhaled Volatile Biomarkers.

The exhaled breath represents an ideal matrix for non-invasive biomarker discovery, and exhaled metabolomics have the potential to be clinically useful in the era of precision medicine. In this concise translational review we will specifically address volatile organic compounds in the breath, with a view towards fulfilling the promise of these as actionable biomarkers, in particular for lung diseases. We review the literature paying attention to seminal work linked to key milestones in breath research; discuss potential applications for breath biomarkers across disease areas and healthcare systems, including the perspectives of industry; and outline critical aspects of study design that will need to be considered for any pivotal research going forward, if breath analysis is to provide robust validated biomarkers that meet the requirements for future clinical implementation.

Discovery and Validation of a Volatile Signature of Eosinophilic Airway Inflammation in Asthma.

RATIONALE: Volatile organic compounds (VOCs) in asthmatic breath may be associated with sputum eosinophilia. We developed a volatile biomarker-signature to predict sputum eosinophilia in asthma. METHODS: VOCs emitted into the space above sputum samples (headspace) from severe asthmatics (n=36) were collected onto sorbent tubes and analysed using thermal desorption gas chromatography-mass spectrometry (TD-GC-MS). Elastic net regression identified stable VOCs associated with sputum eosinophilia ≥3% and generated a volatile biomarker signature. This VOC signature was validated in breath samples from: (I) acute asthmatics according to blood eosinophilia ≥0.3x109cells/L or sputum eosinophilia of ≥ 3% in the UK EMBER consortium (n=65) and U-BIOPRED-IMI consortium (n=42). Breath samples were collected onto sorbent tubes (EMBER) or Tedlar bags (U-BIOPRED) and analysed by gas-chromatography-mass spectrometry (GC×GC-MS -EMBER or GC-MS -U-BIOPRED). MAIN RESULTS: The in vitro headspace identified 19 VOCs associated with sputum eosinophilia and the derived VOC signature yielded good diagnostic accuracy for sputum eosinophilia ≥ 3% in headspace (AUROC (95% CI) 0.90(0.80-0.99), p<0.0001), correlated inversely with sputum eosinophil % (rs= -0.71, p<0.0001) and outperformed FeNO (AUROC (95% CI) 0.61(0.35-0.86). Analysis of exhaled breath in replication cohorts yielded a VOC signature AUROC (95% CI) for acute asthma exacerbations of 0.89(0.76-1.0) (EMBER cohort) with sputum eosinophilia and 0.90(0.75-1.0) in U-BIOPRED - again outperforming FeNO in U-BIOPRED 0.62 (0.33-0.90). CONCLUSIONS: We have discovered and provided early-stage clinical validation of a volatile biomarker signature associated with eosinophilic airway inflammation. Further work is needed to translate our discovery using point of care clinical sensors.

If speed is of the essence: rapid analysis of ambergris by APCI compact mass spectrometry.

The use of atmospheric pressure chemical ionisation (APCI) compact mass spectrometry (CMS) was investigated for the analysis of jetsam and museum-archived ambergris and of ambergris components in perfumes. The data were compared with those from existing methods. Authentic samples of some individual ambergris constituents (ambrein, coprostanol, epicoprostanol and coprostanone), were also examined. Rapid APCI CMS was achieved using either a solids probe or a probe with solutions held in capillary melting point tubes. Interpretation is made of the spectra of the principal natural product components, the relative ion responses were measured and the elemental composition of key ions in the spectra confirmed using high resolution accurate mass APCI MS. Rapid analysis of ambergris by APCI CMS may prove to be a further convenient method of identifying ambrein, of measuring the relative ratios of ambrein and steroids in ambergris and even of quantifying the latter, with minimal sample preparation.

The EBM+ movement.

In this paper, I provide an introduction for biostatisticians and others to some recent work in the philosophy of medicine. Firstly, I give an overview of some philosophical arguments that are thought to create problems for a prominent approach towards establishing causal claims in medicine, namely, the Evidence-Based Medicine (EBM) approach. Secondly, I provide an overview of further recent work in the philosophy of medicine, which argues that mechanistic studies can help to address these problems. Lastly, I describe a novel approach for establishing causal claims in medicine that has been informed by this recent work in the philosophy of medicine, namely, the EBM+ approach.

Visualization of exhaled breath metabolites reveals distinct diagnostic signatures for acute cardiorespiratory breathlessness.

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.

An integrated analysis and comparison of serum, saliva and sebum for COVID-19 metabolomics.

The majority of metabolomics studies to date have utilised blood serum or plasma, biofluids that do not necessarily address the full range of patient pathologies. Here, correlations between serum metabolites, salivary metabolites and sebum lipids are studied for the first time. 83 COVID-19 positive and negative hospitalised participants provided blood serum alongside saliva and sebum samples for analysis by liquid chromatography mass spectrometry. Widespread alterations to serum-sebum lipid relationships were observed in COVID-19 positive participants versus negative controls. There was also a marked correlation between sebum lipids and the immunostimulatory hormone dehydroepiandrosterone sulphate in the COVID-19 positive cohort. The biofluids analysed herein were also compared in terms of their ability to differentiate COVID-19 positive participants from controls; serum performed best by multivariate analysis (sensitivity and specificity of 0.97), with the dominant changes in triglyceride and bile acid levels, concordant with other studies identifying dyslipidemia as a hallmark of COVID-19 infection. Sebum performed well (sensitivity 0.92; specificity 0.84), with saliva performing worst (sensitivity 0.78; specificity 0.83). These findings show that alterations to skin lipid profiles coincide with dyslipidaemia in serum. The work also signposts the potential for integrated biofluid analyses to provide insight into the whole-body atlas of pathophysiological conditions.

Association of gut-related metabolites with respiratory symptoms in COVID-19: A proof-of-concept study.

Gut-related metabolites have been linked with respiratory disease. The crosstalk between the gut and lungs suggests that gut health may be compromised in COVID-19. The aims of the present study were to analyze a panel of gut-related metabolites (acetyl-L-carnitine, betaine, choline, L-carnitine, trimethylamine, and trimethylamine N-oxide) in patients with COVID-19, matched with healthy individuals and patients with non-COVID-19 respiratory symptoms. As results, metabolites from this panel were impaired in patients with COVID-19 and were associated with the symptoms of breathlessness and temperature, and it was possible to differentiate between COVID-19 and asthma. Preliminary results showed that lower levels of betaine appeared to be associated with poor outcomes in patients with COVID-19, suggesting betaine as a marker of gut microbiome health.

Systematic review with meta-analysis of diagnostic test accuracy for COVID-19 by mass spectrometry.

BACKGROUND: The global COVID-19 pandemic has led to extensive development in many fields, including the diagnosis of COVID-19 infection by mass spectrometry. The aim of this systematic review and meta-analysis was to assess the accuracy of mass spectrometry diagnostic tests developed so far, across a wide range of biological matrices, and additionally to assess risks of bias and applicability in studies published to date. METHOD: 23 retrospective observational cohort studies were included in the systematic review using the PRISMA-DTA framework, with a total of 2858 COVID-19 positive participants and 2544 controls. Risks of bias and applicability were assessed via a QUADAS-2 questionnaire. A meta-analysis was also performed focusing on sensitivity, specificity, diagnostic accuracy and Youden's Index, in addition to assessing heterogeneity. FINDINGS: Sensitivity averaged 0.87 in the studies reviewed herein (interquartile range 0.81-0.96) and specificity 0.88 (interquartile range 0.82-0.98), with an area under the receiver operating characteristic summary curve of 0.93. By subgroup, the best diagnostic results were achieved by viral proteomic analyses of nasopharyngeal swabs and metabolomic analyses of plasma and serum. The performance of other sampling matrices (breath, sebum, saliva) was less good, indicating that these protocols are currently insufficiently mature for clinical application. CONCLUSIONS: This systematic review and meta-analysis demonstrates the potential for mass spectrometry and 'omics in achieving accurate test results for COVID-19 diagnosis, but also highlights the need for further work to optimize and harmonize practice across laboratories before these methods can be translated to clinical applications.

Breaking bad news: A randomized controlled trial to test a novel interactive course for medical students using blended learning.

OBJECTIVE: Breaking bad news (BBN) is challenging for physicians and patients and specific communication strategies aim to improve these situations. This study evaluates whether an E-learning assignment could improve medical students' accurate recognition of BBN communication techniques. METHODS: This randomized controlled trial was conducted at the University of Basel. After a lecture on BBN, 4th year medical students were randomized to an intervention receiving an E-learning assignment on BBN or to a control group. Both groups then worked on an examination video and identified previously taught BBN elements shown in a physician-patient interaction. The number of correctly, misclassified and incorrectly identified BBN communication elements as well as missed opportunities were assessed in the examination video. RESULTS: We included 160 medical students (55% female). The number of correctly identified BBN elements did not differ between control and intervention group (mean [SD] 3.51 [2.50] versus 3.72 [2.34], p = 0.58). However, the mean number of inappropriate BBN elements was significantly lower in the intervention than in the control group (2.33 [2.57] versus 3.33 [3.39], p = 0.037). CONCLUSIONS: Use of an E-learning tool reduced inappropriate annotations regarding BBN communication techniques. PRACTICE IMPLICATIONS: This E-learning might help to further advance communication skills in medical students.

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.

A systematic review of the diagnostic accuracy of volatile organic compounds in airway diseases and their relation to markers of type-2 inflammation.

BACKGROUND: Asthma and COPD continue to cause considerable diagnostic and treatment stratification challenges. Volatile organic compounds (VOCs) have been proposed as feasible diagnostic and monitoring biomarkers in airway diseases. AIMS: To 1) conduct a systematic review evaluating the diagnostic accuracy of VOCs in diagnosing airway diseases; 2) understand the relationship between reported VOCs and biomarkers of type-2 inflammation; 3) assess the standardisation of reporting according to STARD and TRIPOD criteria; 4) review current methods of breath sampling and analysis. METHODS: A PRISMA-oriented systematic search was conducted (January 1997 to December 2020). Search terms included: "asthma", "volatile organic compound(s)", "VOC" and "COPD". Two independent reviewers examined the extracted titles against review objectives. RESULTS: 44 full-text papers were included; 40/44 studies were cross-sectional and four studies were interventional in design; 17/44 studies used sensor-array technologies (e.g. eNose). Cross-study comparison was not possible across identified studies due to the heterogeneity in design. The commonest airway diseases differentiating VOCs belonged to carbonyl-containing classes (i.e. aldehydes, esters and ketones) and hydrocarbons (i.e. alkanes and alkenes). Although individual markers that are associated with clinical biomarkers of type-2 inflammation were recognised (i.e. ethane and 3,7-dimethylnonane for asthma and α-methylstyrene and decane for COPD), these were not consistently identified across studies. Only 3/44 reported following STARD or TRIPOD criteria for diagnostic accuracy and multivariate reporting, respectively. CONCLUSIONS: Breath VOCs show promise as diagnostic biomarkers of airway diseases and for type-2 inflammation profiling. However, future studies should focus on transparent reporting of diagnostic accuracy and multivariate models and continue to focus on chemical identification of volatile metabolites.

Assessing the feasibility and acceptability of online measurements of exhaled volatile organic compounds (VOCs) in children with preschool wheeze: a pilot study.

Background: Investigating airway inflammation and pathology in wheezy preschool children is both technically and ethically challenging. Identifying and validating non-invasive tests would be a huge clinical advance. Real-time analysis of exhaled volatile organic compounds (VOCs) in adults is established, however, the feasibility of this non-invasive method in young children remains undetermined. Aim: To determine the feasibility and acceptability of obtaining breath samples from preschool children by means of real-time mass spectrometry analysis of exhaled VOCs. Methods: Breath samples from preschool children were collected and analysed in real time by proton transfer reaction-time of flight-mass spectrometry (PTR-TOF-MS) capturing unique breath profiles. Acetone (mass channel m/z 59) was used as a reference profile to investigate the breath cycle in more detail. Dynamic time warping (DTW) was used to compare VOC profiles from adult breath to those we obtained in preschool children. Results: 16 children were recruited in the study, of which eight had acute doctor-diagnosed wheeze (mean (range) age 3.2 (1.9-4.5) years) and eight had no history of wheezing (age 3.3 (2.2-4.1) years). Fully analysable samples were obtained in 11 (68%). DTW was used to ascertain the distance between the time series of mass channel m/z 59 (acetone) and the other 193 channels. Commonality of 12 channels (15, 31, 33, 41, 43, 51, 53, 55, 57, 60, 63 and 77) was established between adult and preschool child samples despite differences in the breathing patterns. Conclusion: Real-time measurement of exhaled VOCs by means of PTR-MS is feasible and acceptable in preschool children. Commonality in VOC profiles was found between adult and preschool children.

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

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

Diagnosis of COVID-19 by exhaled breath analysis using gas chromatography-mass spectrometry.

BACKGROUND: The ongoing coronavirus disease 2019 (COVID-19) pandemic has claimed over two and a half million lives worldwide so far. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is perceived to be seasonally recurrent, and a rapid noninvasive biomarker to accurately diagnose patients early on in their disease course will be necessary to meet the operational demands for COVID-19 control in the coming years. OBJECTIVE: The aim of this study was to evaluate the role of exhaled breath volatile biomarkers in identifying patients with suspected or confirmed COVID-19 infection, based on their underlying PCR status and clinical probability. METHODS: A prospective, real-world, observational study was carried out, recruiting adult patients with suspected or confirmed COVID-19 infection. Breath samples were collected using a standard breath collection bag, modified with appropriate filters to comply with local infection control recommendations, and samples were analysed using gas chromatography-mass spectrometry (TD-GC-MS). RESULTS: 81 patients were recruited between April 29 and July 10, 2020, of whom 52 out of 81 (64%) tested positive for COVID-19 by reverse transcription-polymerase chain reaction (RT-PCR). A regression analysis identified a set of seven exhaled breath features (benzaldehyde, 1-propanol, 3,6-methylundecane, camphene, beta-cubebene, iodobenzene and an unidentified compound) that separated PCR-positive patients with an area under the curve (AUC): 0.836, sensitivity: 68%, specificity: 85%. CONCLUSIONS: GC-MS-detected exhaled breath biomarkers were able to identify PCR-positive COVID-19 patients. External replication of these compounds is warranted to validate these results.

Changes to the sebum lipidome upon COVID-19 infection observed via rapid sampling from the skin.

BACKGROUND: The COVID-19 pandemic has led to an unprecedented demand for testing - for diagnosis and prognosis - as well as for investigation into the impact of the disease on the host metabolism. Sebum sampling has the potential to support both needs by looking at what the virus does to us, rather than looking for the virus itself. METHODS: In this pilot study, sebum samples were collected from 67 hospitalised patients (30 COVID-19 positive and 37 COVID-19 negative) by gauze swab. Lipidomics analysis was carried out using liquid chromatography mass spectrometry, identifying 998 reproducible features. Univariate and multivariate statistical analyses were applied to the resulting feature set. FINDINGS: Lipid levels were depressed in COVID-19 positive participants, indicative of dyslipidemia; p-values of 0·022 and 0·015 were obtained for triglycerides and ceramides respectively, with effect sizes of 0·44 and 0·57. Partial Least Squares-Discriminant Analysis showed separation of COVID-19 positive and negative participants with sensitivity of 57% and specificity of 68%, improving to 79% and 83% respectively when controlled for confounding comorbidities. INTERPRETATION: COVID-19 dysregulates many areas of metabolism; in this work we show that the skin lipidome can be added to the list. Given that samples can be provided quickly and painlessly, we conclude that sebum is worthy of future consideration for clinical sampling. FUNDING: The authors acknowledge funding from the EPSRC Impact Acceleration Account for sample collection and processing, as well as EPSRC Fellowship Funding EP/R031118/1, the University of Surrey and BBSRC BB/T002212/1. Mass Spectrometry was funded under EP/P001440/1.

Breathomics for the clinician: the use of volatile organic compounds in respiratory diseases.

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 diseasesKey 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.

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.

Use of the ReCIVA device in breath sampling of patients with acute breathlessness: a feasibility study.

INTRODUCTION: Investigating acute multifactorial undifferentiated breathlessness and understanding the driving inflammatory processes can be technically challenging in both adults and children. Being able to validate noninvasive methods such as breath analysis would be a huge clinical advance. The ReCIVA® device allows breath samples to be collected directly onto sorbent tubes at the bedside for analysis of exhaled volatile organic compounds (eVOCs). We aimed to assess the feasibility of using this device in acutely breathless patients. METHODS: Adults hospitalised with acute breathlessness and children aged 5-16 years with acute asthma or chronic stable asthma, as well as healthy adult and child volunteers, were recruited. Breath samples were collected onto sorbent tubes using the ReCIVA® device and sent for analysis by means of two-dimensional gas chromatography-mass spectrometry (GCxGC-MS). The NASA Task Load Index (NASA-TLX) was used to assess the perceived task workload of undertaking sampling from the patient's perspective. RESULTS: Data were available for 65 adults and 61 children recruited. In total, 98.4% of adults and 75.4% of children were able to provide the full target breath sample using the ReCIVA® device. NASA-TLX measurements were available in the adult population with mean values of 3.37 for effort, 2.34 for frustration, 3.8 for mental demand, 2.8 for performance, 3.9 for physical demand and 2.8 for temporal demand. DISCUSSION: This feasibility study demonstrates it is possible and acceptable to collect breath samples from both adults and children at the bedside for breathomics analysis using the ReCIVA® device.