Journal of breath research最新文献

Depression is a pervasive and often undetected mental health condition, which poses significant challenges for early diagnosis due to its silent and subtle nature. To evaluate exhaled volatile organic compounds (VOCs) as non-invasive biomarkers for the detection of depression using a virtual surface acoustic wave sensors array (VSAW-SA). A total of 245 participants were recruited from the Hangzhou Community Health Service Center, including 38 individuals diagnosed with depression and 207 control subjects. Breath samples were collected from all participants and subjected to analysis using VSAW-SA. Univariate and multivariate analyses were employed to assess the relationship between VOCs and depression. The findings revealed that the responses of virtual sensor ID 14, 44, 59, and 176, which corresponded respectively to ethanol, trichloroethylene or isoleucine, octanoic acid or lysine, and an unidentified compound, were sensitive to depression. Taking into account potential confounders, these sensor responses were utilized to calculate a depression detection indicator. It has a sensitivity of 81.6% and a specificity of 81.6%, with an area under the curve of 0.870 (95% CI = 0.816-0.923). Conclusions: exhaled VOCs as non-invasive biomarkers of depression could be detected by a VSAW-SA. Large-scale cohort studies should be conducted to confirm the potential ability of the VSAW-SA to diagnose depression.

Patients with respiratory infections (e.g., COVID-19, antimicrobial resistant bacteria) discharge pathogens to the environment, exposing healthcare workers and inpatients to deleterious complications. This study tested the performance of SPEAR-P1 (synchronized personal exhaled air removal system - prototype 1), which actively detects expiration and removes exhaled air using an open, non-sealing lightweight facemask connected to a deep vacuum generating unit (DVGU). Fourteen healthy examinees practiced breathing through facemasks at 30, 25 and 20 breaths per minute; oxygen and nebulized saline were added at later steps. To test the efficacy of removing exhaled air, CO2 was used as a proxy and its level was measured from the outer surface of the open facemask. Compared to the baseline recording, SPEAR-P1 reduced CO2 escaping from the facemask by 66% on average for all study steps and respiratory rates (p<0.001), reaching 85.55% on average at 20 breaths per minute (p<0.001). This study shows that removing exhaled air from examinees using an open, non-sealing lightweight facemask is feasible. Future development of this system will enhance its efficacy and provide a method to remove a patient's contaminating aerosol without the need to "seal" the patient, especially in settings where isolation rooms are not readily available.

Malignant pleural mesothelioma (MPM) is an aggressive cancer associated with asbestos exposure. MPM is often diagnosed late, at a point where limited treatment options are available, but early intervention could improve the chances of successful treatment for MPM patients. Biomarkers to detect MPM in at-risk individuals are needed to implement early diagnosis technologies. Volatile organic compounds (VOCs) have previously shown diagnostic potential as biomarkers when analysed in MPM patient breath. In this study, chorioallantoic membrane (CAM) xenografts of MPM cell lines were used as models of MPM tumour development for VOC biomarker discovery with the aim of generating targets for investigation in breath, biopsies or other complex matrices. VOC headspace analysis of biphasic or epithelioid MPM CAM xenografts was performed using solid-phase microextraction and gas chromatography-mass spectrometry. We successfully demonstrated the capture, analysis and separation of VOC signatures from CAM xenografts and controls. A panel of VOCs was identified that showed discrimination between MPM xenografts generated from biphasic and epithelioid cells and CAM controls. This is the first application of the CAM xenograft model for the discovery of VOC biomarkers associated with MPM histological subtypes. These findings support the potential utility of non-invasive VOC profiling from breath or headspace analysis of tissues for detection and monitoring of MPM.

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.