Journal of breath research最新文献

The¹³C-sucrose breath test (¹³C-SBT) has been proposed to estimate sucrase-isomaltase (SIM) activity and is a promising test for SIM deficiency, which can cause gastrointestinal symptoms, and for intestinal mucosal damage caused by gut dysfunction or chemotherapy. We previously showed how various summary measures of the¹³C-SBT breath curve reflect SIM inhibition. However, it is uncertain how the performance of these classifiers is affected by test duration. We leveraged¹³C-SBT data from a cross-over study in 16 adults who received 0, 100, and 750 mg of Reducose, an SIM inhibitor. We evaluated the performance of a pharmacokinetic-model-based classifier,ρ, and three empirical classifiers (cumulative percent dose recovered at 90 min (cPDR90), time to 50% dose recovered, and time to peak dose recovery rate), as a function of test duration using receiver operating characteristic (ROC) curves. We also assessed the sensitivity, specificity, and accuracy of consensus classifiers. Test durations of less than 2 h generally failed to accurately predict later breath curve dynamics. The cPDR90 classifier had the highest ROC area-under-the-curve and, by design, was robust to shorter test durations. For detecting mild SIM inhibition,ρhad a higher sensitivity. We recommend¹³C-SBT tests run for at least a 2 h duration. Although cPDR90 was the classifier with highest accuracy and robustness to test duration in this application, concerns remain about its sensitivity to misspecification of the CO₂production rate. More research is needed to assess these classifiers in target populations.

Polymeric bags are a widely applied, simple, and cost-effective method for the storage and offline analysis of gaseous samples. Various materials have been used as sampling bags, all known to contain impurities and differing in their cost, durability, and storage capabilities. Herein, we present a comparative study of several well-known bag materials, Tedlar (PVF), Kynar (PVDF), Teflon (PTFE), and Nalophan (PET), as well as a new material, ethylene vinyl copolymer (EVOH), commonly used for storing food. We investigated the influences of storage conditions, humidity, bag cleaning, and light exposure on volatile organic compound concentration (acetone, acetic acid, isoprene, benzene, limonene, among others) in samples of exhaled human breath stored in bags for up to 48 h. Specifically, we show high losses of short-chain fatty acids (SCFAs) in bags of all materials (for most SCFAs, less than 50% after 8 h of storage). We found that samples in Tedlar, Nalophan, and EVOH bags undergo changes in composition when exposed to UV radiation over a period of 48 h. We report high initial impurity levels in all the bags and their doubling after a period of 48 h. We compare secondary electrospray ionization and proton transfer reaction mass spectrometry in the context of offline analysis after storage in sampling bags. We provide an analytical perspective on the temporal evolution of bag contents by presenting the intensity changes of all significantm/zfeatures. We also present a simple, automated, and cost-effective offline sample introduction system, which enables controlled delivery of collected gaseous samples from polymeric bags into the mass spectrometer. Overall, our findings suggest that sampling bags exhibit high levels of impurities, are sensitive to several environmental factors (e.g. light exposure), and provide low recoveries for some classes of compounds, e.g. SCFAs.

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.