Journal of breath research最新文献

Tetrachloroethylene (PCE) is a widely utilized volatile chemical in industrial applications, including dry cleaning and metal degreasing. Exposure to PCE potentially presents a significant health risk to workers as well as communities near contamination sites. Adverse health effects arise not only from PCE, but also from PCE degradation products, such as trichloroethylene (TCE) and vinyl chloride (VC). PCE, TCE, and VC can contaminate water, soil, and air, leading to exposure through multiple pathways, including inhalation, ingestion, and dermal contact. This study focused on a community setting in Martinsville, Indiana, a working-class Midwestern community in the United States, where extensive PCE contamination has occurred due to multiple contamination sites (referring to 'plumes'), including a Superfund site. Utilizing proton transfer reaction time-of-flight mass spectrometry (PTR-TOF-MS), PCE, TCE, and VC concentrations were measured in the exhaled breath of 73 residents from both within and outside the plume areas. PCE was detected in 66 samples, TCE in 26 samples, and VC in 68 samples. Our results revealed a significant positive correlation between the concentrations of these compounds in exhaled breath and indoor air (Pearson correlation coefficients: PCE = 0.75, TCE = 0.71, and VC = 0.89). This study confirms the presence of PCE and its degradation products in exhaled breath in a community exposure investigation, demonstrating the potential of using exhaled breath analysis in monitoring exposure to environmental contaminants. This study showed the feasibility of utilizing PTR-TOF-MS in community investigations to assess exposure to PCE and its degradation products by measuring these compounds in exhaled breath and indoor air.

Lung cancer subtyping, particularly differentiating adenocarcinoma (ADC) from squamous cell carcinoma (SCC), is paramount for clinicians to develop effective treatment strategies. In this study, we aimed: (i) to discover volatile organic compound (VOC) biomarkers for precise diagnosis of ADC and SCC, (ii) to investigated the impact of risk factors on ADC and SCC prediction, and (iii) to explore the metabolic pathways of VOC biomarkers. Exhaled breath samples from patients with ADC (n= 149) and SCC (n= 94) were analyzed by gas chromatography-mass spectrometry. Both multivariate and univariate statistical analysis method were employed to identify VOC biomarkers. Support vector machine (SVM) prediction models were developed and validated based on these VOC biomarkers. The impact of risk factors on ADC and SCC prediction was investigated. A panel of 13 VOCs was found to differ significantly between ADC and SCC. Utilizing the SVM algorithm, the VOC biomarkers achieved a specificity of 90.48%, a sensitivity of 83.50%, and an area under the curve (AUC) value of 0.958 on the training set. On the validation set, these VOC biomarkers attained a predictive power of 85.71% for sensitivity and 73.08% for specificity, along with an AUC value of 0.875. Clinical risk factors exhibit certain predictive power on ADC and SCC prediction. Integrating these risk factors into the prediction model based on VOC biomarkers can enhance its predictive accuracy. This work indicates that exhaled breath holds the potential to precisely detect ADCs and SCCs. Considering clinical risk factors is essential when differentiating between these two subtypes.

The features of functional constipation (FC)-associated halitosis were identified in the author's previous report. In this report, the author aimed to further investigate its treatment and efficacy. This retrospective study reviewed 100 FC patients, including 82 (82%) halitosis patients and 18 (18%) non-halitosis patients. They underwent the organoleptic test (OLT) to diagnose halitosis, and the organoleptic score (OLS) (0-5) was used to evaluated halitosis severity. The Cleveland Clinical Constipation Score (CCCS) (0-30) was used to evaluate FC severity. Patients were treated with the laxative polyethylene glycol electrolyte powder (PGEP) for four weeks. These tests were performed before and after treatment. The author found that, before treatment, the CCCS was 20.00 (18.00-23.00) for all patients, 21.00 (19.00-24.00) for halitosis patients, and 18.00 (17.00-18.25) for non-halitosis patients. A significant difference was observed between halitosis patients and non-halitosis patients (P< 0.001). The OLS for halitosis patients was 3.00 (3.00-4.00). A positive correlation (r= 0.814, 95% CI: 0.732-0.872,P< 0.001) was found between OLS and CCCS. A CCCS ⩾18 predicted over 50% probability of halitosis. After treatment, the CCCS significantly decreased to 11.50 (6.00-14.75) (P< 0.001), and OLS significantly decreased to 1.00 (0.00-2.00) (P< 0.001). A positive correlation (r= 0.770, 95% CI: 0.673-0.841,P< 0.001) persisted between OLS and CCCS. A pre-treatment CCCS ⩾21 predicted over 50% probability of post-treatment halitosis, while a post-treatment CCCS ⩾12 predicted over 50% probability of post-treatment halitosis. The author concludes that the severity of FC parallels the severity of FC-associated halitosis, and can predict the probability of halitosis. Laxative treatment with PGEP is effective in improving FC-associated halitosis.

Cannabinoids can be detected in breath after cannabis use, but different breath matrices need to be explored as studies to date with filter-based devices that collect breath aerosols have not demonstrated that breath-based measurements can reliably identify recent cannabis use. Exhaled breath condensate (EBC) is an unexplored aqueous breath matrix that contains condensed volatile compounds and water vapor in addition to aerosols. EBC was collected from participants both before and at two time points (0.7 ± 0.2 h and 1.7 ± 0.3 h) after observed cannabis use. Eleven different cannabinoids were monitored with liquid chromatography tandem mass spectrometry. Five different cannabinoids, including Δ⁹-tetrahydrocannabinol (THC), were detected in EBC collected from cannabis users. THC was detected in some EBC samples before cannabis use, despite the requested abstinence period. THC was detected in all EBC samples collected at 0.7 h post use and decreased for all participants at 1.7 h. Non-THC cannabinoids were only detected after cannabis use. THC concentrations in EBC samples collected at 0.7 h showed no trend with sample metrics like mass or number of breaths. EBC sampling devices deserve further investigation with respect to modes of cannabis use (e.g, edibles), post use time points, and optimization of cannabinoid recovery.

Although the associations between a patient's body mass index (BMI) and metabolic diseases, as well as their breath test results, have been studied, the relationship between breath hydrogen/methane levels and metabolic diseases needs to be further clarified. We aimed to investigate how the composition of exhaled breath gases relates to metabolic disorders, such as diabetes mellitus, dyslipidemia, hypertension, and nonalcoholic fatty liver disease (NAFLD), and their key risk factors. An analysis was performed using the medical records, including the lactulose breath test (LBT) data of patients who visited the Ajou University Medical Center, Suwon, Republic of Korea, between January 2016 and December 2021. The patients were grouped according to four different criteria for LBT hydrogen and methane levels. Of 441 patients, 325 (72.1%) had positive results for methane only (hydrogen < 20 parts per million [ppm] and methane ⩾ 3 ppm). BMIs and NAFLD prevalence were higher in patients with only methane positivity than in patients with hydrogen and methane positivity (hydrogen ⩾ 20 ppm and methane ⩾ 3 ppm). According to a multivariate analysis, the odds ratio of only methane positivity was 2.002 (95% confidence interval [CI]: 1.244-3.221,P= 0.004) for NAFLD. Our results demonstrate that breath methane positivity is related to NAFLD and suggest that increased methane gas on the breath tests has the potential to be an easily measurable biomarker for NAFLD diagnosis.

Diagnosing lung infections is often challenging because of the lack of a high-quality specimen from the diseased lung. Since persons with cystic fibrosis are subject to chronic lung infection, there is frequently a need for a lung specimen. In this small, proof of principle study, we determined that PneumoniaCheck^TM, a non-invasive device that captures coughed droplets from the lung on a filter, might help meet this need. We obtained 10 PneumoniaCheck^TMcoughed specimens and 2 sputum specimens from adult CF patients hospitalized with an exacerbation of their illness. We detected amylase (upper respiratory tract) with an enzymatic assay, surfactant A (lower respiratory tract) with an immunoassay, pathogenic bacteria by PCR, and markers of inflammation by a Luminex multiplex immunoassay. The amylase and surfactant A levels suggested that 9/10 coughed specimens were from lower respiratory tract with minimal upper respiratory contamination. The PCR assays detected pathogenic bacteria in 7 of 9 specimens and multiplex Luminex assay detected a variety of cytokines or chemokines. These data indicate that the PneumoniaCheck^TMcoughed specimens can capture good quality lower respiratory tract specimens that have the potential to help in diagnosis, management and understanding of CF exacerbations and other lung disease.

Preservation of the breath sample integrity during storage and transport is one of the biggest challenges in off-line exhaled breath gas analysis. In this context, adsorbent tubes are frequently used as storage containers for use with analytical methods employing gas chromatography with mass spectrometric detection. The key objective of this short communication is to provide data on the recovery of selected breath volatiles from Tenax^®TA adsorbent tubes that were stored at -80 °C for up to 90 d. For this purpose, an Owlstone Medical's ReCIVA^®Breath Sampler was used for exhaled breath collection. The following fifteen compounds, selected to cover a range of chemical properties, were monitored for their stability: isoprene, n-heptane, n-nonane, toluene, p-cymene, allyl methyl sulfide, 1-(methylthio)-propane, 1-(methylthio)-1-propene,α-pinene, DL-limonene,β-pinene,γ-terpinene, 2-pentanone, acetoin and 2,3 butanedione. All compounds, but one (acetoin), were found to be stable during the first 4 weeks of storage (recovery within ± 2 × RSD). Furthermore, n-nonane was stable during the whole of the investigated period.

Noninvasive sample sources of exosomes, such as exhaled breath and sputum, which are in close proximity to the tumor microenvironment and may contain biomarkers indicative of lung cancer, are far more permissive than invasive sample sources for biomarker screening. Standardized exosome extraction and characterization approaches for low-volume noninvasive samples are critically needed. We isolated and characterized exhaled breath condensate (EBC) and sputum exosomes from healthy nonsmokers (n= 30), tobacco smokers (n= 30), and lung cancer patients (n= 40) and correlated the findings with invasive sample sources. EBC samples were collected by using commercially available R-Tubes. To collect sputum samples the participants were directed to take deep breaths, hold their breath, and cough in a collection container. Dynamic light scattering, nanoparticle tracking analysis, and transmission electron microscopy were used to evaluate the exosome morphology. Protein isolation, western blotting, exosome quantification via EXOCET, and Fourier transform infrared spectroscopy were performed for molecular characterization. Exosomes were successfully isolated from EBC and sputum samples, and their yields were adequate and sufficiently pure for subsequent downstream processing and characterization. The exosomes were confirmed based on their size, shape, and surface marker expression. Remarkably, cancer exosomes were the largest in size not only in the plasma subgroups, but also in the EBC (p < 0.05) and sputum (p= 0.0036) subgroups, according to our findings. A significant difference in exosome concentrations were observed between the control sub-groups (p < 0.05). Our research confirmed that exosomes can be extracted from noninvasive sources, such as EBC and sputum, to investigate lung cancer diagnostic biomarkers for research, clinical, and early detection in smokers.

Chronic obstructive pulmonary disease (COPD) and asthma are the most common chronic respiratory diseases. In middle-aged and elderly patients, it is difficult to distinguish between COPD and asthma based on clinical symptoms and pulmonary function examinations in clinical practice. Thus, an accurate and reliable inspection method is required. In this study, we aimed to identify breath biomarkers and evaluate the accuracy of breathomics-based methods for discriminating between COPD and asthma. In this multi-center cross-sectional study, exhaled breath samples were collected from 89 patients with COPD and 73 with asthma and detected on a high-pressure photon ionization time-of-flight mass spectrometry (HPPI-TOFMS) platform from 20 October 2022, to 20 May 2023, in four hospitals. Data analysis was performed from 15 June 2023 to 16 August 2023. The sensitivity, specificity, and accuracy were calculated to assess the overall performance of the volatile organic component (VOC)-based COPD and asthma discrimination models. Potential VOC markers related to COPD and asthma were also analyzed. The age of all participants ranged from to 18-86 years, and 54 (33.3%) were men. The age [median (minimum, maximum)] of COPD and asthma participants were 66.0 (46.0, 86.0), and 44.0 (17.0, 80.0). The male and female ratio of COPD and asthma participants were 14/75 and 40/33, respectively. Based on breathomics feature selection, ten VOCs were identified as COPD and asthma discrimination biomarkers via breath testing. The joint panel of these ten VOCs achieved an area under the curve of 0.843, sensitivity of 75.9%, specificity of 87.5%, and accuracy of 80.0% in COPD and asthma discrimination. Furthermore, the VOCs detected in the breath samples were closely related to the clinical characteristics of COPD and asthma. The VOC-based COPD and asthma discrimination model showed good accuracy, providing a new strategy for clinical diagnosis. Breathomics-based methods may play an important role in the diagnosis of COPD and asthma.

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 (µTD) to GC-IMS has not yet, been benchmarked for breath analysis. To benchmarkµTD-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 att= 60, 120, 200, 280, and 360 min. The breath samples (120 cm³) were pre-concentrated in theµTD 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 byα-pinene andβ-pinene. The reproducibility of the technique for breath analysis was demonstrated by constructing logarithmic washout curves, with the average linearity coefficient ofR²= 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 thatµTD-GC-IMS is reproducible and suitable technique for breath analysis, with benchmark values for eucalyptol comparable to the gold standard GC-MS.