The measurement of trace breath gases is of growing interest for its potential to provide non-invasive physiological information in health and disease. While instrumental techniques such as selected-ion flow-tube mass spectrometry (SIFT-MS) can achieve this, these are less suitable for clinical application. Sensitive sensor-based systems for breath ammonia could be more widely deployed, but have proven challenging to develop. This work demonstrates the sequential analytical validation of an electrochemical impedance-based sensor system for the measurement of ammonia in breath using SIFT-MS. Qualitative and relative responses between the two methods were comparable, although there were consistent differences in absolute concentration. When tested in artificial breath ammonia, sensors had a relative impedance sensitivity of 3.43 × 10ppbvfor each breath in the range of 249-1653 ppbv (= 0.87,< 0.05). When correlated with SIFT-MS using human breath (= 14), ammonia was detected in the range of 100-700 ppbv (= 0.78,< 0.001), demonstrating acceptable sensitivity, reproducibility and dynamic range for clinical application.

To investigate the halitosis level in oral lichen planus (OLP) patients and OLP-free participants. This cross-sectional study recruited 70 participants at the New Zealand's National Centre for Dentistry. Halitosis was determined using the objective measurements (parts per billion (ppb) volatile sulphur compounds (VSCs) in the exhaled air) and subjective measurement (self-reported halitosis questionnaire). The VSCs values of OLP participants (mean ± SD: 144.64 ± 23.85 ppb) were significantly greater than that in the OLP-free participants (105.52 ± 22.31ppb) (mean difference: 39.12 ppb;< 0.05; 95% CI: 27.95, 50.29). The VSCs value of hyperplastic (mean difference: 34.11; 95% CI: 20.07, 48.15;< 0.05) and erosive/ulcerative (mean difference: 57.47; 95% CI: 34.19, 80.76;< 0.05) OLP participants were statistically greater than that of OLP-free participants. No statistical significance was found between hyperplastic and erosive/ulcerative OLP (> 0.05). 'Type (OLP-free/OLP)' has a significant effect on the dependent variable VSCs. 78.6% of OLP and 90.5% of OLP-free brushed their teeth at least twice daily, with a statistically significant observation (Mean square: 1.61; F: 13.13;< 0.05). The levels of VSCs were greater in participants with hyperplastic and erosive/ulcerative OLP than that in the OLP-free participants.

The differentiation between malignant and benign thyroid nodules represents a significant challenge for clinicians globally. The identification of volatile organic compounds (VOCs) has emerged as a novel approach in the field of cancer diagnosis. This prospective pilot study aims to identify VOCs in exhaled breath, blood, and urine that can differentiate benign from malignant thyroid nodules using gas chromatography-ion mobility spectrometry (GC-IMS). Patients with thyroid nodules scheduled for surgery were enrolled at the Maastricht University Medical Center (MUMC+). Breath samples were analyzed using a BreathSpec GC-IMS machine (G.A.S. Dortmund, Germany), specifically designed for breath analysis. All blood and urine samples were analyzed using a separate GC-IMS device, the FlavourSpec® (G.A.S., Dortmund, Germany). In this proof-of-concept study, 70 consecutive patients undergoing thyroid surgery at MUMC+ were included. Of these patients, 29 were confirmed to have thyroid cancer after surgical resection. The overall analysis did not reveal statistically significant differences in VOCs in breath, urine and blood, between patients with benign and malignant thyroid cancer. This proof-of-concept study demonstrated that GC-IMS could not effectively differentiate between the VOC profiles of malignant and benign thyroid nodules. However, due to the small sample size of this study, larger prospective studies are needed to investigate the potential of using VOCs to distinguish between benign and malignant thyroid nodules. Additionally, future research should focus on identifying potential confounding factors that may influence patient VOC profiles. (NCT04883294).

Oral malodor negatively impacts a person's quality of life and may affect up to 50% of the population. The aim of this randomized, placebo and no-product controlled, evaluator-blind, proof-of-concept study was to evaluate the effectiveness and safety of the single use of two experimental lozenges containing the laccase enzyme and green coffee extract (with and without flavor) in reducing intrinsic oral malodor. Following 12-16 h of avoidance of oral hygiene,156 generally healthy subjects presented at screening and baseline visits with a mean organoleptic odor intensity (OI) score of ⩾2 and an OralChromareading of ⩾125 parts per billion (ppb) hydrogen sulfide (HS) gas and were randomly assigned to receive either one of the two experimental lozenges, a placebo lozenge, or no-product. Following the supervised use of the assigned products, subjects' oral malodor was evaluated using OI assessments and OralChromameasurement for volatile sulfur compounds (VSCs) immediately following product use (approximately 5 min), and at 30 min, 1 h, 2 h, 3 h and 4 h. The two experimental lozenges, with and without flavor, showed significant reductions in OI scores compared with the placebo and no-product groups at all time points (< 0.001). At 5 min post-product use, the experimental lozenges, with and without flavor, were significantly better than the no-product group in reducing the VSCs (< 0.04). The results of individual VSC components (hydrogen sulfide, methyl mercaptan and dimethyl sulfide) were variable; both experimental lozenges notably reduced hydrogen sulfide and methyl mercaptan levels in most post-use assessments. Four minor adverse events were reported, none of which were directly linked to the product. In conclusion, the experimental lozenges, whether flavored or not, were safe and effective in reducing oral malodor over a span of 4 h, based on organoleptic OI scores.Clinical Trial No: NCT05950529.

Idiopathic halitosis is an unusual condition of unclear causes, which has never been thoroughly investigated. We aimed to explore the role of small intestinal bacterial overgrowth (SIBO) in the pathogenesis of idiopathic halitosis, and to evaluate the therapeutic efficacy of a probiotic preparation on this condition. This retrospective observational study included 162 idiopathic halitosis patients and 198 healthy controls (HCs). Halitosis was diagnosed using the organoleptic test, and idiopathic halitosis was diagnosed by excluding known causes. SIBO was identified through the hydrogen/methane lactulose breath test, and accordingly, patients were identified as SIBO-positive or SIBO-negative. Idiopathic halitosis patients were treated with the probiotic preparationtriple viable capsule for two months, followed by re-evaluation of halitosis and SIBO. This study found that all cases of idiopathic halitosis were extra-oral. The SIBO positivity rate in idiopathic halitosis patients was significantly higher than that in HCs (74.69% [121/162] vs 3.03% [6/198],< 0.001), with an odds ratio of 94.44% (95% CI: 39.99%-211.35%). After treatment, 80.17% (97/121) of the SIBO-positive patients became SIBO-negative. Moreover, 87.60% (106/121) of the SIBO-positive patients experienced improved halitosis, a rate significantly higher than that observed in SIBO-negative patients (2.75%, 3/41) (< 0.001). In addition, 98.97% (96/97) of the post-treatment SIBO-negative patients experienced improved halitosis, a rate significantly higher than that of post-treatment sustained SIBO-positive patients (41.67%, 10/24) (< 0.001). Our findings suggest that idiopathic halitosis is an extra-oral condition which mostly originates from the small intestine. SIBO is one of its underlying causes. The probiotic preparation can effectively improve idiopathic halitosis, probably through its impact on SIBO.

Several clinical studies have reported promising correlations between propofol concentration in exhaled breath (Ce-pro) and the bispectral index (BIS) in patients, suggesting the potential of exhaled propofol measurement as a non-invasive method for adjusting anesthesia depth. However, these studies are still in the validation phase of instrument effectiveness, often limited by small sample sizes or inappropriate instrument selection, and thus lack convincing results regarding these correlations. In this study, one hundred patients aged 18-65, undergoing elective thyroid surgery under general anesthesia were included. The vacuum ultraviolet photoionization and time-of-flight mass spectrometry was employed to monitor Ce-pro at 20 s intervals, alongside continuous BIS measurement. The association between Ce-pro and BIS was analyzed using linear mixed-effects models, with marginalused to assess the correlation. The threshold of Ce-pro at awakening was also explored. Additionally, the univariate and multifactorial diagnostic model, including end-of-surgery Ce-pro, were employed to assess the accuracy of predicting delayed recovery. A weak correlation was observed between intraoperative Ce-pro and BIS (marginal= 0.348). Predictive models utilizing end-of-surgery Ce-pro levels showed good accuracy (area under the curve (AUC) = 0.75, 95% CI: 0.62-0.89,= 0.003) in predicting delayed recovery, while the model using end-of-surgery Ce-pro combined with gender, sufentanil dosage, the time from the last administration of sufentanil to the end of surgery, and anesthesia duration demonstrated stronger predicting accuracy (AUC = 0.91, 95% CI: 0.85-0.98,< 0.001). This study suggests that Ce-pro alone may not reliably predict the depth of anesthesia in clinical practice, but shows promising accuracy in predicting delayed recovery from anesthesia.

The prevalence of patients with bronchiectasis (BE) has been rising in recent years, which increases the substantial burden on the family and society. Exploring a convenient, effective, and low-cost screening tool for the diagnosis of BE is urgent. We expect to identify the accuracy (ACC) of breath biomarkers (BBs) for the diagnosis of BE through breathomics testing and explore the association between BBs and clinical features of BE. Exhaled breath samples were collected and detected by high-pressure photon ionization time-of-flight mass spectrometry in a cross-sectional study. Exhaled breath samples were from 215 patients with BE and 295 control individuals. The potential BBs were selected via the machine learning (ML) method. The overall performance was assessed for the BBs-based BE detection model. The significant BBs between different subgroups such as the severity of BE, acute or stable stage, combined with hemoptysis or not, with or without nontuberculous mycobacterium (NTM),() isolation or not, and the BBs related to the number of involved lung lobes and lung function were discovered and analyzed. The top ten BBs based ML model achieved an area under the curve of 0.940, sensitivity of 90.7%, specificity of 85%, and ACC of 87.4% in BE diagnosis. Except for the top ten BBs, other BBs were found also related to the severity, acute/stable status, hemoptysis or not, NTM infection,isolation, the number of involved lobes, and three lung functional parameters in BE patients. BBs-based BE detection model showed good ACC for diagnosis. BBs have a close relationship with the clinical features of BE. The breath test method may provide a new strategy for BE screening and personalized management.

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.

For decades, intake monitoring of drugs using urine as the matrix of choice is the gold standard in drug treatment centers. A properly conducted urine drug test can identify recent use of prescribed, non-prescribed and illicit drugs. However, issues like adulteration, substitution and privacy issues have driven the search for alternative matrices. This prospective pilot study evaluates the use of an impaction-based breath sampling device, Breath Explor, as an alternative to traditional urine-based drug monitoring. Breath samples were analyzed using a validated 32-component liquid chromatography-tandem mass spectrometry method. Recovery data represent the efficiency of extracting the analytes from the breath devices. Both automated and manual processing of the Breath Explor® devices showed mean recovery rates ranging from 39.5% to 55.4% for the 32 analytes. Despite the small number of subjects, breath analysis proved to be a convenient and easy-to-use methodology. An overall kappa-values of 0.5 indicated a moderate level of agreement with urine analysis, underscoring its potential as a complementary diagnostic tool. All participants tested positive in their breath sample for methadone (70% methadone and 100% EDDP), while a significant portion (90%) tested positive for 6-monoacetylmorphine. This innovative approach offers several advantages, including non-invasiveness, reduced risk of adulteration, and the ability to perfom repeated automated sampling and confirmation testing. These findings suggest that breath-based substance monitoring could complement or even replace traditional urine-based methods in clinical practice.

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.

Volatile organic compounds (VOCs) produced by human respiratory cells reflect metabolic and pathophysiological processes which can be detected with the use of modern technology. Analysis of exhaled breath or indoor air may potentially play an important role in screening of upper respiratory tract infections such as COVID-19 or influenza in the future. In this experimental study, air samples were collected and analyzed from the headspace of ancell culture infected by selected pathogens (influenza A H1N1 and seasonal coronaviruses OC43 and NL63). VOCs were measured with a real-time proton-transfer-reaction time-of-flight mass spectrometer and a differential mobility spectrometer. Measurements were performed every 12 h for 7 d. Non-infected cells and cell culture media served as references. In H1N1 and OC43 we observed four different VOCs which peaked during the infection. Different, individual VOCs were also observed in both infections. Activity began to clearly increase after 2 d in all analyses. We did not see increased VOC production in cells infected with NL63. VOC analysis seems to be suitable to differentiate the infected cells from those which are not infected as well as different viruses, from another. In the future, this could have practical value in both individual diagnostics and indoor environment screening.

TheC-sucrose breath test (C-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 theC-SBT breath curve reflect SIM inhibition. However, it is uncertain how the performance of these classifiers is affected by test duration. We leveragedC-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 recommendC-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 COproduction rate. More research is needed to assess these classifiers in target populations.

Untargeted analysis of volatile organic compounds (VOCs) from exhaled breath and culture headspace are influenced by several confounding factors not represented in reference standards. In this study, we propose a method of generating pooled quality control (QC) samples for untargeted VOC studies using a split-recollection workflow with thermal desorption tubes. Sample tubes were desorbed and split from each sample and recollected onto a single tube, generating a pooled QC sample. This QC sample was then repeatedly desorbed and recollected with a sequentially lower split ratio allowing injection of multiple QC samples. We found pooled QC samples to be representative of complex mixtures using principal component analysis and may be useful in future longitudinal, multi-centre, and validation studies to assess data quality and adjust for batch effects.

Previous studies have reported volatile organic compounds (VOCs) in the breath as biomarkers of breast cancer. These biomarkers may be derived from cancer-associated fibroblasts, in which oxidative stress degrades polyunsaturated fatty acids to volatile alkanes and methylated alkane derivatives that are excreted in the breath. We evaluated a rapid point-of-care test for breath VOC biomarkers as predictors of breast cancer and abnormal mammograms. We studied 593 women aged⩾18 yr referred to three sites for mammography for a symptomatic breast-related concern (e.g. breast mass, nipple discharge). A rapid point-of-care breath testing system collected and concentrated alveolar breath VOCs on a sorbent trap and analyzed them with gas chromatography and surface acoustic wave detection in <6 min. Breath VOC chromatograms were randomly assigned to a training set or to a validation set. Monte Carlo analysis identified significant breath VOC biomarkers of breast cancer and abnormal mammograms in the training set, and these biomarkers were incorporated into a multivariate algorithm to predict disease in the validation set.50 women had biopsy-proven breast cancer (invasive cancer 41, ductal non-invasive cancer 9)breath VOCs identified breast cancer with 83% accuracy (area under curve of receiver operating characteristic), 82% sensitivity and 77.1% specificity.training set breath VOCs identified breast cancer with 80.3% accuracy, 84% sensitivity and 74.3% specificity. Corresponding values in the validation set were 68%% accuracy, 72.4% sensitivity and 61.5% specificity.breath VOCs identified abnormal mammograms with 76.2% accuracy.breath VOCs identified abnormal mammograms with 74.2% accuracy, 73.3% sensitivity and 60% specificity. Corresponding values in the validation set were 60.5% accuracy, 64.2% sensitivity and 51% specificity. A rapid point-of-care test for breath VOC biomarkers predicted risk of breast cancer and abnormal mammograms in women with breast-related symptoms.

Exhaled breath condensate (EBC) is used as a promising noninvasive diagnostic tool in the field of respiratory medicine. EBC is achieved by cooling exhaled air, which contains aerosolized particles and volatile compounds present in the breath. This method provides useful information on the biochemical and inflammatory state of the airways. In respiratory diseases such as asthma, chronic obstructive pulmonary disease and cystic fibrosis, EBC analysis can reveal elevated levels of biomarkers such as hydrogen peroxide, nitric oxide and various cytokines, which correlate with oxidative stress and inflammation. Furthermore, the presence of certain volatile organic compounds in EBC has been linked to specific respiratory conditions, potentially serving as disease-specific fingerprints. The noninvasive nature of EBC sampling makes it particularly useful for repeated measures and for use in vulnerable populations, including children and the elderly. Despite its potential, the standardization of collection methods, analytical techniques and interpretation of results currently limits its use in clinical practice. Nonetheless, EBC holds significant promise for improving the diagnosis, monitoring and therapy of respiratory diseases. In this tutorial we will present the latest advances in EBC research in airway diseases and future prospects for clinical applications of EBC analysis, including the application of the Omic sciences for its analysis.

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.

Occupational asthma (OA) is divided into allergic asthma (AA) and irritant-induced asthma (IIA). IIA can be divided further into three different phenotypic subtypes. Volatile organic compounds (VOCs) in exhaled breath can reflect metabolic changes in the body, and a wide range of them have been associated with various diseases in the last two decades. This is the first known study to explore breath VOCs in subjects with OA, aimed to identify potential biomarkers to distinguish OA from healthy controls, as well as between different OA subgroups. In a cross-sectional investigation, exhaled breath from 40 patients with OA and 45 respiratory healthy healthcare workers were collected with ReCIVA® Breath Sampler. Samples were analyzed through an untargeted approach using thermal desorption-gas chromatography mass spectrometry (TD-GC-MS), and VOCs were identified according to tier classification. The data underwent analysis using both non-parametric and parametric statistical methods. 536 VOCs were identified. Significance (p<0.05) was observed in several emitted VOCs. Among these, compounds such as 1-hexadecanol, 2,3-butanediol, xylene, phenol, acetone, 3-methylhexane, methylcyclohexane, and isoprene have biological implications or are associated with exposures linked to OA. These VOCs may reflect metabolic changes in the body and the microbiome, as well as external exposures due to occupation. In particular, 1-hexadecanol, 2,3-butanediol, xylene and phenol are associated with reduced nicotinamide adenine dinucleotide (NADH) and production of reactive oxygen species (ROS), mechanisms that can be linked to asthmatic diseases and therefore suggests its potential as biomarkers. This study demonstrates that VOCs detected in exhaled breath could serve as indicators of occupational exposure and enhance diagnostic accuracy for asthma. .

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 (= 149) and SCC (= 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.

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 significant/features. 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.

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 (< 0.001). The OLS for halitosis patients was 3.00 (3.00-4.00). A positive correlation (= 0.814, 95% CI: 0.732-0.872,< 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) (< 0.001), and OLS significantly decreased to 1.00 (0.00-2.00) (< 0.001). A positive correlation (= 0.770, 95% CI: 0.673-0.841,< 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.