Noninvasive detection of soft tissue sarcoma using volatile organic compounds in exhaled breath: a pilot study.

Aim: The aim of this pilot study was to assess whether an electronic nose can detect patients with soft tissue sarcoma (STS) based on volatile organic compound profiles in exhaled breath. Patients & methods: In this cross-sectional pilot study, patients with primary STS and healthy controls, matched on sex and age, were included for breath analysis. Machine learning techniques were used to develop the best-fitting model. Results: Fifty-nine breath samples were collected (29 STS and 30 control) from March 2018 to March 2022. The final model yielded a c-statistic of 0.85 with a sensitivity of 83% and specificity of 60%. Conclusion: This study suggests that exhaled volatile organic compound analysis could serve as a noninvasive diagnostic biomarker for the detection of STS with a good performance.

Diagnosing soft tissue sarcoma (STS) among the large number of benign soft tissue tumors is challenging. There is a serious need for a novel and easy tool that could accurately detect patients with STS. This study aimed to assess how well an easy-to-use electronic nose could differentiate between patients with STS and those without STS based on their exhaled breath. This is the first pilot study to reveal that an electronic nose could serve as a diagnostic tool for the detection of STS with a good performance. Future studies are needed to validate the findings in larger cohorts.

Unravelling the controversy with small intestinal bacterial overgrowth.

PURPOSE OF REVIEW: The aim of this review is to summarize the current and emergent approaches to characterize the small intestinal microbiota and discuss the treatment options for management of small intestinal bacterial overgrowth (SIBO). RECENT FINDINGS: This review captures the growing body of evidence for the role of SIBO, a type of small intestinal dysbiosis in the pathophysiology various gastrointestinal and extraintestinal disorders. We have highlighted the drawbacks of the available methods for characterizing the small intestinal microbiota and focus on the new culture-independent techniques to diagnose SIBO. Although recurrence is common, targeted modulation of the gut microbiome as a therapeutic option for management of SIBO is associated with improvement in symptoms and quality of life. SUMMARY: As a first step to precisely characterize the potential link between SIBO and various disorders, we need to address the methodological limitations of the available traditional tests for diagnosing SIBO. There is an urgency to develop culture independent techniques that can be routinely used in clinical setting, that will enable characterization of the gastrointestinal microbiome and explore the response to antimicrobial therapy including the links between long-lasting symptom resolution and the microbiome.

Evaluation of the One-Hour ¹³C-Propionate Breath Test in 49 Patients from a Single Center in Japan to Detect Vitamin B12 Deficiency.

BACKGROUND Given the unavailability of reliable biomarkers for vitamin B12 (VB12) deficiency in clinical settings, the usefulness of the ¹³C-propionate breath test (PBT), utilizing VB12 as a coenzyme of methylmalonyl-CoA in propionate metabolism, as a diagnostic modality for VB12 deficiency has been studied. However, a collection time of 2 h reduces its convenience. Hence, we evaluated the effectiveness of 1-h PBT for detecting VB12 deficiency in 49 patients with suspected VB12 deficiency. MATERIAL AND METHODS We collected 100-200 mL breath gas every 10 min until 1 h after the administration of 1 g of ¹³C-propionate from 49 patients (31 men, 18 women; median age, 70 years) with clinically suspected VB12 deficiency and calculated the ¹³CO2 recovered in the breath per hour as the recovery rate (RR [%dose/h]) from ¹³CO2/¹²CO2 using infrared isotope spectrometry. We compared the RRs between groups: (1) with serum VB12 levels ≥145 pg/mL and <145 pg/mL, (2) with mean corpuscular volume ≤100 fL and >100 fL, and 3) pre- and post-VB12 supplementation. RESULTS The RRs peaked within 30 min. The RRs at 20 min (RR20) and 30 min (RR30) were significantly lower in macrocytotic patients (41.28 vs 50.07, p=0.026 and 37.82 vs 43.93, P=0.003). The RR30 was higher in the supplemented patients (41.93 vs 32.84, P=0.024). There was no significant difference in RRs between the patients with normal and low serum VB12 levels. CONCLUSIONS The 1-h PBT can be a diagnostic modality for VB12 deficiency because 1 h is a sufficient collection time.

Urea Breath Testing to Detect Helicobacter pylori in Patients with Peptic Ulcer Bleeding During Proton Pump Inhibitor Treatment.

This was a descriptive study carried out from January to December 2021, at Quanzhou First Hospital, an affiliated hospital of Fujian Medical University, to investigate the efficacy of the urea breath test in detecting Helicobacter pylori infection in patients with peptic ulcer bleeding affected with proton pump inhibitors. A total of 77 patients with peptic ulcer bleeding, who underwent urea breath testing after active bleeding, were divided into two groups. The Helicobacter pylori infection positivity rate in patients with peptic ulcer bleeding was 66.2%. The time from bleeding to detection and from admission to detection was not significantly different between the Helicobacter pylori-positive and -negative groups (p=0.840 and 0.285, respectively). Even with high-dose proton pump inhibitor treatment, a urea breath test can be performed after peptic ulcer bleeding ceases and results in an acceptable positivity rate. There was no significant difference in the accuracy of Helicobacter pylori detection between the time from bleeding to testing and from admission to testing. Key Words: Peptic ulcer, Helicobacter pylori, Upper gastrointestinal bleeding, Urea breath test, Proton pump inhibitor.

The ADEM2 project: early pathogenic mechanisms of preschool wheeze and a randomised controlled trial assessing the gain in health and cost-effectiveness by application of the breath test for the diagnosis of asthma in wheezing preschool children.

BACKGROUND: The prevalence of asthma-like symptoms in preschool children is high. Despite numerous efforts, there still is no clinically available diagnostic tool to discriminate asthmatic children from children with transient wheeze at preschool age. This leads to potential overtreatment of children outgrowing their symptoms, and to potential undertreatment of children who turn out to have asthma. Our research group developed a breath test (using GC-tof-MS for VOC-analysis in exhaled breath) that is able to predict a diagnosis of asthma at preschool age. The ADEM2 study assesses the improvement in health gain and costs of care with the application of this breath test in wheezing preschool children. METHODS: This study is a combination of a multi-centre, parallel group, two arm, randomised controlled trial and a multi-centre longitudinal observational cohort study. The preschool children randomised into the treatment arm of the RCT receive a probability diagnosis (and corresponding treatment recommendations) of either asthma or transient wheeze based on the exhaled breath test. Children in the usual care arm do not receive a probability diagnosis. Participants are longitudinally followed up until the age of 6 years. The primary outcome is disease control after 1 and 2 years of follow-up. Participants of the RCT, together with a group of healthy preschool children, also contribute to the parallel observational cohort study developed to assess the validity of alternative VOC-sensing techniques and to explore numerous other potential discriminating biological parameters (such as allergic sensitisation, immunological markers, epigenetics, transcriptomics, microbiomics) and the subsequent identification of underlying disease pathways and relation to the discriminative VOCs in exhaled breath. DISCUSSION: The potential societal and clinical impact of the diagnostic tool for wheezing preschool children is substantial. By means of the breath test, it will become possible to deliver customized and high qualitative care to the large group of vulnerable preschool children with asthma-like symptoms. By applying a multi-omics approach to an extensive set of biological parameters we aim to explore (new) pathogenic mechanisms in the early development of asthma, creating potentially interesting targets for the development of new therapies. TRIAL REGISTRATION: Netherlands Trial Register, NL7336, Date registered 11-10-2018.

Diagnostic performance of eNose technology in COVID-19 patients after hospitalization.

BACKGROUND: Volatile organic compounds (VOCs) produced by human cells reflect metabolic and pathophysiological processes which can be detected with the use of electronic nose (eNose) technology. Analysis of exhaled breath may potentially play an important role in diagnosing COVID-19 and stratification of patients based on pulmonary function or chest CT. METHODS: Breath profiles of COVID-19 patients were collected with an eNose device (SpiroNose) 3 months after discharge from the Leiden University Medical Centre and matched with breath profiles from healthy individuals for analysis. Principal component analysis was performed with leave-one-out cross validation and visualised with receiver operating characteristics. COVID-19 patients were stratified in subgroups with a normal pulmonary diffusion capacity versus patients with an impaired pulmonary diffusion capacity (DLCOc < 80% of predicted) and in subgroups with a normal chest CT versus patients with COVID-19 related chest CT abnormalities. RESULTS: The breath profiles of 135 COVID-19 patients were analysed and matched with 174 healthy controls. The SpiroNose differentiated between COVID-19 after hospitalization and healthy controls with an AUC of 0.893 (95-CI, 0.851-0.934). There was no difference in VOCs patterns in subgroups of COVID-19 patients based on diffusion capacity or chest CT. CONCLUSIONS: COVID-19 patients have a breath profile distinguishable from healthy individuals shortly after hospitalization which can be detected using eNose technology. This may suggest ongoing inflammation or a common repair mechanism. The eNose could not differentiate between subgroups of COVID-19 patients based on pulmonary diffusion capacity or chest CT.

Quantitatively Visualizing Airborne Disease Transmission Risks of Different Exhalation Activities through CO2 Imaging.

Aerosol transmission has played a leading role in COVID-19 pandemic. However, there is still a poor understanding about how it is transmitted. This work was designed to study the exhaled breath flow dynamics and transmission risks under different exhaling modes. Using an infrared photography device, exhaled flow characteristics of different breathing activities, such as deep breathing, dry coughing, and laughing, together with the roles of mouth and nose were characterized by imaging CO2 flow morphologies. Both mouth and nose played an important role in the disease transmission though in the downward direction for the nose. In contrast to the trajectory commonly modeled, the exhaled airflows appeared with turbulent entrainments and obvious irregular movements, particularly the exhalations involving mouth were directed horizontal and had a higher propagation capacity and transmission risk. While the cumulative risk was high for deep breathing, those transient ones from dry coughing, yawning, and laughing were also shown to be significant. Various protective measures including masks, canteen table shields, and wearable devices were visually demonstrated to be effective for altering the exhaled flow directions. This work is useful to understanding the risk of aerosol infection and guiding the formulation of its prevention and control strategies. Experimental data also provide important information for refining model boundary conditions.

Analysis of exhaled breath to identify critically ill patients with ventilator-associated pneumonia.

Ventilator-associated pneumonia commonly occurs in critically ill patients. Clinical suspicion results in overuse of antibiotics, which in turn promotes antimicrobial resistance. Detection of volatile organic compounds in the exhaled breath of critically ill patients might allow earlier detection of pneumonia and avoid unnecessary antibiotic prescription. We report a proof of concept study for non-invasive diagnosis of ventilator-associated pneumonia in intensive care (the BRAVo study). Mechanically ventilated critically ill patients commenced on antibiotics for clinical suspicion of ventilator-associated pneumonia were recruited within the first 24 h of treatment. Paired exhaled breath and respiratory tract samples were collected. Exhaled breath was captured on sorbent tubes and then analysed using thermal desorption gas chromatography-mass spectrometry to detect volatile organic compounds. Microbiological culture of a pathogenic bacteria in respiratory tract samples provided confirmation of ventilator-associated pneumonia. Univariable and multivariable analyses of volatile organic compounds were performed to identify potential biomarkers for a 'rule-out' test. Ninety-six participants were enrolled in the trial, with exhaled breath available from 92. Of all compounds tested, the four highest performing candidate biomarkers were benzene, cyclohexanone, pentanol and undecanal with area under the receiver operating characteristic curve ranging from 0.67 to 0.77 and negative predictive values from 85% to 88%. Identified volatile organic compounds in the exhaled breath of mechanically ventilated critically ill patients show promise as a useful non-invasive 'rule-out' test for ventilator-associated pneumonia.

Breath analysis by ultra-sensitive broadband laser spectroscopy detects SARS-CoV-2 infection.

Rapid testing is essential to fighting pandemics such as coronavirus disease 2019 (COVID-19), the disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Exhaled human breath contains multiple volatile molecules providing powerful potential for non-invasive diagnosis of diverse medical conditions. We investigated breath detection of SARS-CoV-2 infection using cavity-enhanced direct frequency comb spectroscopy (CE-DFCS), a state-of-the-art laser spectroscopic technique capable of a real-time massive collection of broadband molecular absorption features at ro-vibrational quantum state resolution and at parts-per-trillion volume detection sensitivity. Using a total of 170 individual breath samples (83 positive and 87 negative with SARS-CoV-2 based on reverse transcription polymerase chain reaction tests), we report excellent discrimination capability for SARS-CoV-2 infection with an area under the receiver-operating-characteristics curve of 0.849(4). Our results support the development of CE-DFCS as an alternative, rapid, non-invasive test for COVID-19 and highlight its remarkable potential for optical diagnoses of diverse biological conditions and disease states.

Online Detection of HCN in Humid Exhaled Air by Gas Flow-Assisted Negative Photoionization Mass Spectrometry.

Hydrogen cyanide (HCN) is a well-known toxic compound in many fields. The trace amount of endogenous HCN in human exhalation has been associated with the presence of Pseudomonas aeruginosa (PA) infection in cystic fibrosis (CF) patients. Online monitoring of HCN profile is promising to screen PA infection rapidly and accurately. In this study, a gas flow-assisted negative photoionization (NPI) mass spectrometry method was developed for monitoring the single-exhalation HCN profile. The sensitivity could be optimized by introducing helium to eliminate the humidity influence and reduce the low mass cutoff effect, with improvements of a factor 150 observed. By employing a purging gas procedure and minimizing the length of the sample line, the residual and response time were greatly reduced. The limit of detection (LOD) of 0.3 ppbv and time resolution of 0.5 s were achieved. HCN profiles of exhalations from different volunteers before or after gargling with water were detected to show the performance of the method. All profiles showed a sharp peak and a stable end-tidal plateau, representing the concentration of oral cavity and end-tidal gas, respectively. The HCN concentration based on the plateau of the profile showed better reproducibility and accuracy, which indicates this method has potential application in the detection of PA infection in CF patients.

Single count breath test for the evaluation of respiratory function in Myasthenia Gravis: A systematic review.

BACKGROUND: Myasthenia gravis (MG) can have a variety of respiratory presentations, ranging from mild symptoms through to respiratory failure. The evaluation of respiratory function in MG can be limited by accessibility to testing facilities, availability of medical equipment, and facial weakness. The single count breath test (SCBT) may be a useful adjunct in the evaluation of respiratory function in MG. METHOD: A systematic review of the databases PubMed, EMBASE, and the Cochrane Library was conducted from inception to October 2022 in accordance with PRISMA guidelines and was registered on PROSPERO. RESULTS: There were 6 studies that fulfilled the inclusion criteria. The described method of evaluating SCBT involves inhaling deeply, then counting at two counts per second, in English or Spanish, sitting upright, with normal vocal register, until another breath needs to be taken. The identified studies support that the SCBT has a moderate correlation with forced vital capacity. These results also support that SCBT can assist the identification of MG exacerbation, including via assessment over the telephone. The included studies support a threshold count of ≥ 25 as consistent with normal respiratory muscle function. Although further analysis is needed, the included studies describe the SCBT as a quick bedside tool that is inexpensive and well tolerated. CONCLUSIONS: The results of this review support the clinical utility of the SCBT in assessing respiratory function in MG and describe the most current and effective methods of administration.

GC-MS analysis of exhaled gas for fine detection of inflammatory diseases.

Exhaled gas analysis is a non-invasive test ideal for continuous monitoring of biological metabolic information. We analyzed the exhaled gas of patients with inflammatory diseases for trace gas components that could serve as biomarkers that enable early detection of inflammatory diseases and assessment of treatment efficacy. Furthermore, we examined the clinical potential of this method. We enrolled 34 patients with inflammatory disease and 69 healthy participants. Volatile components from exhaled gas were collected and analyzed by a gas chromatography-mass spectrometry system, and the data were examined for gender, age, inflammatory markers, and changes in markers before and after treatment. The data were tested for statistical significance through discriminant analysis by Volcano plot, Analysis of variance test, principal component analysis, and cluster analysis comparing healthy and patient groups. There were no significant differences in the trace components of exhaled gas by gender or age. However, we found differences in some components of the exhaled gas between healthy and untreated patients. In addition, after treatment, gas patterns including the patient-specific components changed to a state closer to the inflammation-free status. We identified trace components in the exhaled gas of patients with inflammatory diseases and found that some of these regressed after treatment.

Evaluation of small intestinal bacterial overgrowth.

INTRODUCTION: There has been phenomenal interest concerning gut microbiota dysbiosis including small intestinal bacterial overgrowth (SIBO). However, the diagnostic methods for SIBO are still unsatisfactory. AREAS COVERED: The current review covers the different invasive and noninvasive tests to diagnose SIBO, their methodology, interpretation, sensitivity, specificity, and limitations based on the selected articles from literature search using searchterms 'small intestinal bacterial overgrowth' AND 'digestive diseases' OR'diagnosis' OR 'hydrogen breath test' in PubMed in December 2022. The current review will cover some potential methods for diagnosis of SIBO that may be of clinical utility in the future. EXPERT OPINION: SIBO was conventionally defined as a total bacterial count >105 colony forming units (CFU) per mL on quantitative culture of upper gut aspirate. The threshold for the diagnosis of SIBO has been reduced to >103CFU per mL of aspirate recently. Considering the invasiveness of collecting upper gut aspirate, need for laboratory infrastructure and manpower to culture it, noninvasive hydrogen breath tests (HBT) became popular. However, due to the poor sensitivity and specificity of HBT to diagnose SIBO, their utility is being challenged. A new technology of measuring intra-luminal hydrogen gas has a potential to bring a paradigm shift in the diagnostic tests for SIBO.

Association between one-year exposure to air pollution and the prevalence of pulmonary nodules in China.

PM2.5is a well-known airborne hazard to cause various diseases. Evidence suggests that air pollution exposure contributes to the occurrence of pulmonary nodules. Pulmonary nodules detected on the computed tomography scans can be malignant or progress to malignant during follow-up. But the evidence of the association between PM2.5exposure and pulmonary nodules was limited. To examine potential associations of exposures to PM2.5and its major chemical constituents with the prevalence of pulmonary nodules. A total of 16 865 participants were investigated from eight physical examination centers in China from 2014 to 2017. The daily concentrations of PM2.5and its five components were estimated by high-resolution and high-quality spatiotemporal datasets of ground-level air pollutants in China. The logistic regression and the quantile-based g-computation models were used to assess the single and mixture impact of air pollutant PM2.5and its components on the risk of pulmonary nodules, respectively. Each 1 mg m-3increase in PM2.5(OR 1.011 (95% CI: 1.007-1.014)) was positively associated with pulmonary nodules. Among five PM2.5components, in single-pollutant effect models, every 1µg m-3increase in organic matter (OM), black carbon (BC), and NO3-elevated the risk of pulmonary nodule prevalence by 1.040 (95% CI: 1.025-1.055), 1.314 (95% CI: 1.209-1.407) and 1.021 (95% CI: 1.007-1.035) fold, respectively. In mixture-pollutant effect models, the joint effect of every quintile increase in PM2.5components was 1.076 (95% CI: 1.023-1.133) fold. Notably, NO3-BC and OM contributed higher risks of pulmonary nodules than other PM2.5components. And the NO3-particles were identified to have the highest contribution. The impacts of PM2.5components on pulmonary nodules were consistent across gender and age.These findings provide important evidence for the positive correlation between exposure to PM2.5and pulmonary nodules in China and identify that NO3-particles have the highest contribution to the risk.

Emissions and uptake of volatiles by sampling components in breath analysis.

The first and most crucial step in breath research is adequate sampling, which plays a pivotal role in quality assurance of breath datasets. In particular, the emissions or uptake of volatile organic compounds (VOCs) by sampling interface materials present a risk of disrupting breath gas samples. This study investigated emissions and uptake by three interface components, namely a silicon facemask, a reusable 3D-printed mouthpiece adapter, and a pulmonary function test filter compatible with the commercial Respiration Collector forIn-VitroAnalysis (ReCIVA) breath sampling device. Emissions were examined before and after (hydro-)thermal treatment of the components, and uptake was assessed by exposing each material to 12 representative breath VOCs comprising alcohols, aldehydes, ketones, carboxylic acids, terpenes, sulphurous and nitrogenous compounds at different target concentration ranges (∼10 ppbVand ∼100 ppbV). Chemical analyses of VOCs were performed using proton transfer reaction-time-of-flight-mass spectrometry (PTR-TOFMS) with supporting analyses via thermal desorption comprehensive two-dimensional gas chromatography-TOFMS (TD-GC×GC-TOFMS). The filter exhibited the lowest overall emissions compared to the mask or adapter, which both had equivalently high emissions (albeit for different compounds). Treatment of the materials reduced the total VOC emissions by 62% in the mask, 89% in the filter and 99% in the adapter. Uptakes of compounds were lowest for the adapter and most pronounced in the mask. In particular, 1-butanol, acetone, 2-butanone, 1,8-cineole and dimethyl sulphide showed negligible uptake across all materials, whereas ethanol, nonanal, acetic acid, butanoic acid, limonene and indole exhibited marked losses. Knowledge of emissions and/or uptake by sampling components is key to reducing the likelihood of erroneous data interpretation, ultimately expediting progress in the field of breath test development.

Volatolomics analysis of exhaled breath and gastric-endoluminal gas for distinguishing early upper gastrointestinal cancer from benign.

Exhaled breath and gastric-endoluminal gas (volatile products of diseased tissues) contain a large number of volatile organic compounds, which are valuable for early diagnosis of upper gastrointestinal (UGI) cancer. In this study, exhaled breath and gastric-endoluminal gas of patients with UGI cancer and benign disease were analyzed by gas chromatography-mass spectrometry (GC-MS) and ultraviolet photoionization time-of-flight mass spectrometry (UVP-TOFMS) to construct UGI cancer diagnostic models. Breath samples of 116 UGI cancer and 77 benign disease subjects and gastric-endoluminal gas samples of 114 UGI cancer and 76 benign disease subjects were collected. Machine learning (ML) algorithms were used to construct UGI cancer diagnostic models. Classification models based on exhaled breath for distinguishing UGI cancer from the benign group have area under the curve (AUC) of receiver operating characteristic curve values of 0.959 and 0.994 corresponding to GC-MS and UVP-TOFMS analysis, respectively. The AUC values of models based on gastric-endoluminal gas for UGI cancer and benign group classification are 0.935 and 0.929 corresponding to GC-MS and UVP-TOFMS analysis, respectively. This work indicates that volatolomics analysis of exhaled breath and gastric-endoluminal diseased tissues have great potential in early screening of UGI cancer. Moreover, gastric-endoluminal gas can be a means of gas biopsy to provide auxiliary information for the examination of tissue lesions during gastroscopy.

Longitudinal hierarchical Bayesian models of covariate effects on airway and alveolar nitric oxide.

Biomarkers such as exhaled nitric oxide (FeNO), a marker of airway inflammation, have applications in the study of chronic respiratory disease where longitudinal studies of within-participant changes in the biomarker are particularly relevant. A cutting-edge approach to assessing FeNO, called multiple flow FeNO, repeatedly assesses FeNO across a range of expiratory flow rates at a single visit and combines these data with a deterministic model of lower respiratory tract NO to estimate parameters quantifying airway wall and alveolar NO sources. Previous methodological work for multiple flow FeNO has focused on methods for data from a single participant or from cross-sectional studies. Performance of existing ad hoc two-stage methods for longitudinal multiple flow FeNO in cohort or panel studies has not been evaluated. In this paper, we present a novel longitudinal extension to a unified hierarchical Bayesian (L_U_HB) model relating longitudinally assessed multiple flow FeNO to covariates. In several simulation study scenarios, we compare the L_U_HB method to other unified and two-stage frequentist methods. In general, L_U_HB produced unbiased estimates, had good power, and its performance was not sensitive to the magnitude of the association with a covariate and correlations between NO parameters. In an application relating height to longitudinal multiple flow FeNO in schoolchildren without asthma, unified analysis methods estimated positive, statistically significant associations of height with airway and alveolar NO concentrations and negative associations with airway wall diffusivity while estimates from two-stage methods were smaller in magnitude and sometimes non-significant.

CuMoO4 nanorods-based acetone chemiresistor-enabled non-invasive breathomic-diagnosis of human diabetes and environmental monitoring.

A nano-enabled low-trace monitoring system for acetone has the potential to revolutionize breath omics-based non-invasive diagnosis of human diabetes and environmental monitoring technologies. This unprecedented study presents the state-of-the-art facile and economic template-assisted hydrothermal route to fabricate novel CuMoO4 nanorods for room temperature breath and airborne acetone detection. Physicochemical attribute analysis reveals the formation of crystalline CuMoO4 nanorods with diameters ranging from 90 to 150 nm, and an optical band gap of approximately 3.87 eV. CuMoO4 nanorods-based chemiresistor demonstrates excellent acetone monitoring performance, with a sensitivity of approximately 33.85 at a concentration of 125 ppm. Acetone detection is rapid, with a response time of 23 s and fast recovery within 31 s. Furthermore, the chemiresistor exhibits long-term stability and selectivity towards acetone, compared to other interfering volatile organic compounds (VOCs) commonly found in human breath such as ethanol, propanol, formaldehyde, humidity, and ammonia. The linear detection range of acetone from 25 to 125 ppm achieved by the fabricated sensor is well-suited for human breath-based diagnosis of diabetes. This work represents a significant advancement in the field, as it offers a promising alternative to time-consuming and costly invasive biomedical diagnostics, with the potential for application in cleanroom facilities for indoor contamination monitoring. The utilization of CuMoO4 nanorods as sensing nanoplatform opens new possibilities for the development of nano-enabled, low-trace acetone monitoring technologies for non-invasive diabetes diagnosis and environmental sensing applications.

Serial fractional exhaled nitric oxide measurements at and off work may help to identify immunologic occupational asthma in cases with complex exposures.

Serial measurements of fractional exhaled nitric oxide (FeNO) at home and at work have been described to provide complementary information for the diagnosis of occupational asthma (OA) when specific inhalation challenge (SIC) is missing or doubtful. We describe two cases in which serial FeNO measurements enabled the detection of probable OA after complex exposures. A 25-year-old industrial painter with exposure to a variety of paints suffered from work-related airway symptoms for five years. Lung function was normal, and she was not atopic. SIC with hexamethylene diisocyanate was negative. A 47-year-old sign maker (screen printing, foils) suffering from work-related dyspnoea for seven years. Moderate airway obstruction, but no atopy was detectable. Due to the complex exposures SIC was not performed. Both patients performed FeNO measurements once daily during a 2-week-holiday and a subsequent 2-week-work period. In both cases elevated baseline FeNO decreased to normal (25 ppb) during holidays and increased after resuming work (case 1: 125 ppb, case 2: 45 ppb).