Breath Samples Research Articles

Preventing Impaired Driving Using IoT on Steering Wheels Approach

To drive safely, one must be attentive, coordinated, have good judgment, and be able to respond quickly to changing conditions. In certain countries, improving safety may depend largely on reducing the number of impaired drivers on the road. Therefore, solutions are required to reduce the risk that is posed on the road by drivers who have been consuming alcohol while driving. Previous research has proposed the use of sensors for detecting driver impairment caused by alcohol intoxication. However, relying on a gas sensor alone may not be appropriate for detection. To reduce drunk driving, this study proposes an Internet of Things (IoT)-based tool that measures heart rate and analyzes the breath of a driver for traces of alcohol. The tool represents a vehicle that is made up of a DC motor. In the circumstance that the tool detects a higher than resting heart rate in the driver as well as an amount of alcohol in the driver’s breath sample, the tool will immediately power down the DC motor and send an SMS to the registered emergency contact with the driver’s precise position using the GPS module. The initial prototype demonstrates the tool as a potential aftermarket accessory for vehicles. The implication of this paper is that the designed tool might be of practical use to researchers in their attempts to determine and obtain information on alcohol intoxication. Doi: 10.28991/HIJ-2024-05-02-012 Full Text: PDF

Mechanisms contributing to lactose and sucrose-induced postprandial lipaemia

Fructose-containing sugars can exaggerate postprandial lipaemia and stimulate hepatic de novo lipogenesis (DNL) when compared to glucose-based carbohydrates(1). Galactose has recently been shown to increase postprandial lipaemia compared to glucose(2), but mechanisms remain uncharacterised. The aim of this study was to assess the effect and mechanisms of lactose-induced lipaemia.Twenty-four non-obese adults (12 male and 12 female) completed three trials in a randomised, crossover design (28 ± 7-day washout). During trials, participants consumed test drinks containing 50 g fat with 100 g of carbohydrate. The control carbohydrate was a glucose polymer (maltodextrin), the experimental carbohydrate was galactose-containing carbohydrate (lactose) and the active comparator was fructose-containing carbohydrate (sucrose). Hepatic DNL was assessed by the 2H2O method and [U-13C]-palmitate was added to the test drink to trace the fate of the ingested fat. Blood and breath samples were taken to determine plasma metabolite and hormone concentrations, in addition to plasma and breath 2H and 13C enrichments. Data were converted into incremental under the curve (iAUC) and were checked for normality by visual inspection of residuals. Differences between trials were assessed by one-way ANOVA. Where a main effect of trial was detected, post- hoc t-tests were performed to determine which trials differed from lactose according to the principle of closed-loop testing.The plasma triacylglycerol iAUC (mean ± SD) in response to maltodextrin was 51 ± 68 mmol/L*360 min. Following lactose ingestion, plasma triacylglycerol iAUC increased to 98 ± 88 mmol/L*360 min (p<0.001 vs maltodextrin), which was comparable to sucrose [90 ± 95 mmol/L*360 min (p=0.41 vs lactose)]. Hepatic DNL in response to maltodextrin was 6.6 ± 3.0%. Following ingestion of lactose, hepatic DNL increased to 12.4 ± 6.9% (p=0.02 vs maltodextrin), which was comparable to sucrose [12.2 ± 6.9% (p=0.96 vs lactose)]. Exhaled 13CO2 in response to maltodextrin was 10.4 ± 4.1 mmol/kgFFM*360 min. Following ingestion of lactose, exhaled 13CO2 was 8.8 ± 4.9 mmol/kgFFM*360 min (p=0.09 vs maltodextrin), which was lower than sucrose [11.1 ± 3.9 mmol/kgFFM*360 min (p=0.01 vs lactose)].These data are consistent with the hypothesis that hepatic de novo lipogenesis contributes to both lactose and sucrose-induced lipaemia and provide a rationale to investigate the longer-term effects of lactose and sucrose on metabolism.

Discovery and Validation of a Volatile Signature of Eosinophilic Airway Inflammation in Asthma.

Volatile organic compounds (VOCs) in asthmatic breath may be associated with sputum eosinophilia. We developed a volatile biomarker-signature to predict sputum eosinophilia in asthma. VOCs emitted into the space above sputum samples (headspace) from severe asthmatics (n=36) were collected onto sorbent tubes and analysed using thermal desorption gas chromatography-mass spectrometry (TD-GC-MS). Elastic net regression identified stable VOCs associated with sputum eosinophilia ≥3% and generated a volatile biomarker signature. This VOC signature was validated in breath samples from: (I) acute asthmatics according to blood eosinophilia ≥0.3x109cells/L or sputum eosinophilia of ≥ 3% in the UK EMBER consortium (n=65) and U-BIOPRED-IMI consortium (n=42). Breath samples were collected onto sorbent tubes (EMBER) or Tedlar bags (U-BIOPRED) and analysed by gas-chromatography-mass spectrometry (GC×GC-MS -EMBER or GC-MS -U-BIOPRED). The in vitro headspace identified 19 VOCs associated with sputum eosinophilia and the derived VOC signature yielded good diagnostic accuracy for sputum eosinophilia ≥ 3% in headspace (AUROC (95% CI) 0.90(0.80-0.99), p<0.0001), correlated inversely with sputum eosinophil % (rs= -0.71, p<0.0001) and outperformed FeNO (AUROC (95% CI) 0.61(0.35-0.86). Analysis of exhaled breath in replication cohorts yielded a VOC signature AUROC (95% CI) for acute asthma exacerbations of 0.89(0.76-1.0) (EMBER cohort) with sputum eosinophilia and 0.90(0.75-1.0) in U-BIOPRED - again outperforming FeNO in U-BIOPRED 0.62 (0.33-0.90). We have discovered and provided early-stage clinical validation of a volatile biomarker signature associated with eosinophilic airway inflammation. Further work is needed to translate our discovery using point of care clinical sensors.

Identifying potential breath biomarkers for early diagnosis of papillary thyroid cancer based on solid-phase microextraction gas chromatography-high resolution mass spectrometry with metabolomics.

Thyroid cancer incidence rate has increased substantially worldwide in recent years. Fine needle aspiration biopsy (FNAB) is currently the golden standard of thyroid cancer diagnosis, which however, is invasive and costly. In contrast, breath analysis is a non-invasive, safe and simple sampling method combined with a promising metabolomics approach, which is suitable for early cancer diagnosis in high volume population. This study aims to achieve a more comprehensive and definitive exhaled breath metabolism profile in papillary thyroid cancer patients (PTCs). We studied both end-tidal and mixed expiratory breath, solid-phase microextraction gas chromatography coupled with high resolution mass spectrometry (SPME-GC-HRMS) was used to analyze the breath samples. Multivariate combined univariate analysis was applied to identify potential breath biomarkers. The biomarkers identified in end-tidal and mixed expiratory breath mainly included alkanes, olefins, enols, enones, esters, aromatic compounds, and fluorine and chlorine containing organic compounds. The area under the curve (AUC) values of combined biomarkers were 0.974 (sensitivity: 96.1%, specificity: 90.2%) and 0.909 (sensitivity: 98.0%, specificity: 74.5%), respectively, for the end-tidal and mixed expiratory breath, indicating of reliability of the sampling and analysis method CONCLUSION: This work not only successfully established a standard metabolomic approach for early diagnosis of PTC, but also revealed the necessity of using both the two breath types for comprehensive analysis of the biomarkers.

Impact of breath sample collection method and length of storage of breath samples in Tedlar bags on the level of selected volatiles assessed using gas chromatography-ion mobility spectrometry (GC-IMS)

The analysis of volatile organic compounds (VOCs) in exhaled air has attracted the interest of the scientific community because it provides the possibility of monitoring physiological and metabolic processes and non-invasive diagnostics of various diseases. However, this method remains underused in clinical practice as well as in research because of the lack of standardized procedures for the collection, storage and transport of breath samples, which would guarantee good reproducibility and comparability of results. The method of sampling, as well as the storage time of the breath samples in the polymer bags used for sample storage and transport, affect the composition and concentration of VOCs present in the breath samples. The aim of our study was to compare breath samples obtained using two methods with fully disposable equipment: a Haldane sampling tube intended for direct breath collection and breath samples exhaled into a transparent Tedlar bag. The second task was to monitor the stability of selected compounds of real breath samples stored in a Tedlar bag for 6 h. Gas chromatography coupled with ion mobility spectrometry (GC-IMS) implemented in the BreathSpec® device was used to analyse exhaled breath. Our results showed a significant difference in the signal intensity of some volatiles when taking a breath sample with a Haldane tube and a Tedlar bag. Due to its endogenous origin, acetone levels were significantly higher when the Haldane tube sampler was used while elevated levels of 2-propanol and unidentified VOC (designated as VOC 3) in the Tedlar bag samples likely originated from contamination of the Tedlar bags. The VOC stability study revealed compound-specific signal intensity changes of the selected VOCs with storage time in the Tedlar bags, with some volatiles showing increasing signal intensity during storage in Tedlar bags. This limits the use of Tedlar bags only for very limited time and carefully selected purpose. Our results highlight the importance of careful design and implementation of experiments and clinical protocols to obtain relevant and reliable results.

Halitosis in young patients with chronic kidney disease: findings from a randomized controlled trial

BackgroundChronic kidney disease (CKD) directly affects oral health. Yet data about halitosis in young CKD patients and the impact of dental prophylaxis is limited. Therefore, as part of this randomized clinical trial, halitosis in young CKD patients undergoing intensive or standard oral preventive procedures was to be explored.MethodsThree volatile sulfur compounds (hydrogen sulfide, methyl mercaptan and dimethyl sulfide) were measured in 30 young patients with CKD (mean age 14.2 years; 16 males, 14 females). Breath samples were taken after 3 and 6 months and analyzed with selective gas chromatography (OralChroma). Tongue coating (Winkel Index) and clinical indices to determine local inflammation or oral hygiene (Papillary Bleeding Index and Quigley-Hein Index) were assessed. Within an extended anamnesis, patients and their mothers and nurses were questioned about the perceived halitosis. Corresponding quotes were noted verbatim. Patients were randomized to either intensive need-related oral health care measures (oral preventative program, OPP) or a one-stage standard prevention (treatment as usual, TAU).ResultsWhile there were no differences in volatile sulfur compound levels between TAU and OPP at the three time points of measurements (p > 0.05), there was a tendency towards a reduction in dimethyl sulfide and hydrogen sulfide of affected patients within the OPP group over time. Looking at potential differences between both groups with regard to tongue coating, significant differences were observed between baseline and 3 months after study start in the OPP group, and between baseline and 6 months after study start in the TAU group (p < 0.05). The burden of halitosis was frequently reported by patients’ mothers and nurses.ConclusionsYoung CKD patients regularly suffered from halitosis and dimethyl sulfide was its main source. Preventive measures mainly resulted in a reduction of tongue coating. Trial registration: The German Clinical Trial Register (# DRKS00010580).

Characterization of the SPIRITAS: A Disposable Sampling Setup for Volatile Organic Compound Collection and Analysis

Analyzing exhaled breath for volatile organic compounds (VOCs) using thermal desorption–gas chromatography–mass spectrometry (TD-GC-MS) offers a non-invasive diagnostic approach for various diseases. Despite its promise, the method faces challenges like sampling heterogeneity and high costs. Following the European Respiratory Society’s advocacy for methodological standardization, we developed the SPIRITAS (Standardized Product for Inexpensive Respiratory InvesTigation: A breath Sampler), a low-cost, disposable breath sampler. This study evaluates the SPIRITAS’s effectiveness in detecting targeted VOCs. We tested the SPIRITAS using the Peppermint Experiment, a standardized protocol that allows for comparison between different breath sampling and analytical practices by assessing the ability to detect five peppermint-specific VOCs after ingestion of a 200-milligram peppermint oil capsule. We included ten subjects and performed six breath samples per participant, including a baseline measurement taken before ingestion. We used the Wilcoxon signed-rank test to evaluate whether baseline values were significantly lower than the peak values of the targeted VOCs. Additionally, we conducted an experiment utilizing humidified medical-grade air to identify any VOCs attributable to the SPIRITAS setup itself. Results showed successful detection of four out of five targeted “peppermint-associated” VOCs: alpha-pinene (p ≤ 0.01), beta-pinene (p ≤ 0.01), menthone (p = 0.01), and menthol (p = 0.02), indicating significant differences between the baseline and peak values in the volunteers’ breath. However, detection of eucalyptol was inconsistent. In addition, we identified 16 VOCs that were released by the SPIRITAS, one of which remains unidentified. Our findings underscore the SPIRITAS’s potential for clinical applications, paving the way for broader biomarker research. The combination of ease of use, low cost, reduced risk of contamination, and standardization makes SPIRITAS very suitable for large-scale international studies. Furthermore, we have demonstrated the SPIRITAS’s effectiveness in detecting specific VOCs and identified 16 compounds originating from the SPIRITAS, ensuring that these compounds would not be mis-qualified as potential biomarkers in future clinical studies.

Validation and application of an automated multitarget LC-MS/MS method for drugs of abuse testing using exhaled breath as specimen

Aerosol microparticles in exhaled breath carry non-volatile compounds from the deeper parts of the lung. When captured and analyzed, these aerosol microparticles constitute a non-invasive and readily available specimen for drugs of abuse testing. The present study aimed to evaluate a simple breath collection device in a clinical setting. The device divides a breath sample into three parallel “collectors” that can be individually analyzed. Urine was used as the reference specimen, and parallel specimens were collected from 99 patients undergoing methadone maintenance treatment. Methadone was used as the primary validation parameter. A sensitive multi-analyte method using tandem liquid chromatography – mass spectrometry was developed and validated as part of the project. The method was successfully validated for 36 analytes with a limit of detection of 1 pg/collector for most compounds. Based on the validation results tetrahydrocannabinol THC), cannabidiol (CBD), and lysergic acid diethylamide (LSD) are suitable for qualitative analysis, but all other analytes can be quantitively assessed by the method. Methadone was positive in urine in 97 cases and detected in exhaled breath in 98 cases. Median methadone concentration was 64 pg/collector. The methadone metabolite 2-ethylidene-1,5-dimethyl-3,3-diphenylpyrrolidine (EDDP) was detected in 90 % of the cases but below 10 pg/collector in most. Amphetamine was also present in the urine in 17 cases and in exhaled breath in 16 cases. Several other substances were detected in the exhaled breath and urine samples, but at a lower frequency. This study concluded that the device provides a specimen from exhaled breath, that is useful for drugs of abuse testing. The results show that high analytical sensitivity is needed to achieve good detectability and detection time after intake.

Gastric emptying is slower in women than men with type 2 diabetes and impacts on postprandial glycaemia.

To evaluate sex differences in gastric emptying and the glycaemic response to a glucose drink and a high carbohydrate meal in type 2 diabetes (T2D). In cohort 1, 70 newly diagnosed, treatment-naïve Chinese patients with T2D (44 men) recruited from a diabetes outpatient clinic ingested a 75-g glucose drink containing 150 mg 13C-acetate. In cohort 2, 101 Australian patients with T2D (67 male) recruited from the community, managed by diet and/or metformin monotherapy, ingested a semi-solid mashed potato meal, labelled with 100 μl 13C-octanoic acid. Breath samples were collected over 3 and 4 h, respectively, for assessment of gastric emptying, and venous blood was sampled for evaluation of glycaemia (with and without adjustment for each participant's estimated total blood volume). Gastric emptying was slower in female than male subjects in both cohorts (both p < .01). Multiple linear regression analyses revealed that gastric emptying was independently associated with sex (both p < .05). Without adjustment for blood volume, the glycaemic responses to oral glucose and the mixed meal were greater in female subjects (both p < .001). However, after adjustment for blood volume, the glycaemic responses were greater in men (both p < .05). Gastric emptying is slower in women than men with T2D, associated with a reduced blood volume-adjusted glycaemic response to oral glucose and a mixed meal in women. These observations highlight the sex difference in postprandial glucose handling, which is relevant to the personalized management of postprandial glycaemia in T2D.

The potential of volatile organic compounds to diagnose primary sclerosing cholangitis

IntroductionPrimary sclerosing cholangitis (PSC) is a chronic cholestatic liver disease characterized by progressive inflammation and fibrosis of the bile ducts. PSC is a complex disease of largely unknown aetiology with a strong association with inflammatory bowel disease (IBD). Diagnosis, especially at early stage, is difficult and to date there is no diagnostic biomarker. The present study aimed to assess the diagnostic potential of Volatile Organic Compounds (VOCs) in exhaled breath to detect (early) PSC in an IBD population. MethodsBreath samples were obtained from 16 PSC, 47 PSC with IBD, and 53 IBD patients during outpatient clinic visit. Breath sampling was performed using the ReCIVA breath sampler and subsequently analysed by gas chromatography mass spectrometry. Random Forest modelling was performed to find discriminatory VOCs and create a predictive model that was tested using an independent test set. ResultsThe final model to discriminate PSC patients with or without IBD versus IBD only patients included twenty VOCs and achieved a sensitivity, specificity, and area under the receiver operating curve on the test set of 77%, 83%, and 0.84 respectively. Three VOCs (isoprene, 2-octanone and undecane) together correlated significantly to the Amsterdam-Oxford score for PSC disease prognosis. A sensitivity analysis showed stable results across early stage PSC including those with normal alkaline phosphatase levels, as well as further progressed PSC. ConclusionThe present study demonstrates that exhaled breath can distinguish PSC cases from IBD and has potential as a non-invasive clinical breath test for (early) PSC. Impact and ImplicationsPrimary Sclerosing Cholangitis (PSC) is a complex chronic liver disease, which ultimately results in cirrhosis, liver failure, and death. Detection especially in early disease can be challenging, and therefore therapy typically starts when there is already some irreversible damage. The current study shows that metabolites in exhaled breath, so called Volatile Organic Compounds, hold promise to non-invasively detect PSC also at early stages.

Identification of exhaled volatile organic compounds that characterize asthma phenotypes: A J-VOCSA study

BackgroundAsthma is characterized by phenotypes of different clinical, demographic, and pathological characteristics. Identifying the profile of exhaled volatile organic compounds (VOCs) in asthma phenotypes may facilitate establishing biomarkers and understanding asthma background pathogenesis. This study aimed to identify exhaled VOCs that characterize severe asthma phenotypes among patients with asthma. MethodsThis was a multicenter cross-sectional study of patients with severe asthma in Japan. Clinical data were obtained from medical records, and questionnaires were collected. Exhaled breath was sampled and subjected to thermal desorption gas chromatography-mass spectrometry (GC/MS). ResultsUsing the decision tree established in the previous nationwide asthma cohort study, 245 patients with asthma were divided into five phenotypes and subjected to exhaled VOC analysis with 50 healthy controls (HCs). GC/MS detected 243 VOCs in exhaled breath samples, and 142 frequently detected VOCs (50% of all samples) were used for statistical analyses. Cluster analysis assigning the groups with similar VOC profile patterns showed the highest similarities between phenotypes 3 and 4 (early-onset asthma phenotypes), followed by the similarities between phenotypes 1 and 2 (late-onset asthma phenotypes). Comparisons between phenotypes 1–5 and HC revealed 19 VOCs, in which only methanesulfonic anhydride showed p < 0.05 adjusted by false discovery rate (FDR). Comparison of these phenotypes yielded several VOCs showing different trends (p < 0.05); however, no VOCs showed p < 0.05 adjusted by FDR. ConclusionsExhaled VOC profiles may be useful for distinguishing asthma and asthma phenotypes; however, these findings need to be validated, and their pathological roles should be clarified.

Effect of sleeve gastrectomy on the levels of oral volatile sulfur compounds and halitosis-related bacteria

BackgroundThe association between sleeve gastrectomy and halitosis remains relatively unknown. Therefore, this study aimed to evaluate the effect of sleeve gastrectomy on halitosis and the oral bacterial species associated with halitosis in patients with obesity. MethodsThis was a prospective longitudinal cohort study that examined patients before and after sleeve gastrectomy and followed the patients at three time intervals (1, 3, and 6 months) after sleeve gastrectomy. Clinical periodontal measurements (plaque index [PI], gingival index [GI], and probing depth [PD]) were obtained. In addition, plaque samples were collected for quantification of the periodontopathogenic bacteria: Porphyromonas gingivalis, Tannerella forsythia, Treponema denticola, and Fusobacterium nucleatum using real-time quantitative polymerase chain reaction (qPCR). In addition, breath samples were collected to analyze the concentration of volatile sulfur compounds (VSCs), namely hydrogen sulfide (H2S), methyl mercaptan (CH3SH), and dimethyl sulfide (CH3SCH3), via portable gas chromatography (Oral Chroma™). ResultsOf the 43 patients initially included, 39 completed the study, with a mean age of 32.2 ± 10.4 years. For PI and GI repeated measurements one way analysis of variance showed a significant increase (p-value < 0.001 for both) one month after surgery, with mean values of 1.3 and 1.59, respectively, compared to the baseline. During the same period, the number of P. gingivalis increased, with a p-value = 0.04. Similarly, the levels of hydrogen sulfide (H2S) and methyl mercaptan (CH3SH) increased significantly in the first month after surgery (p-value = 0.02 and 0.01, respectively). ConclusionThis study demonstrated that sleeve gastrectomy may lead to increased halitosis one month post-surgery, attributed to elevated and P. gingivalis counts, contributing to the development of gingivitis in obese patients who underwent sleeve gastrectomy. This emphasizes the importance of including oral health professionals in the multidisciplinary team for the management of patients undergoing bariatric surgery

Exhaled volatolomics profiling facilitates personalized screening for gastric cancer

Gastric cancer (GC) is one of the most fatal cancers, characterized by non-specific early symptoms and difficulty in detection. However, there are no valid non-invasive screening tools available for GC. Here we establish a non-invasive method that employs exhaled volatolomics and ensemble learning to detect GC. We developed a comprehensive mass spectrometry-based procedure and determined of a wide range of volatolomics from 314 breath samples. The discovery, identification and verification research screened a biomarker panel to distinguish GC from controls. This panel has achieved 0.90 (0.87–0.94, 95%CI) accuracy, with an area under curve (AUC) of 0.92 (0.89–0.94, 95%CI) in discovery cohort and 0.88 (0.83–0.91, 95%CI) accuracy with an AUC of 0.91 (0.87–0.93, 95%CI) in replication cohort, which outperformed traditional serum markers. Single-cell sequencing and gene set enrichment analysis revealed that these exhaled markers originated from aldehyde oxidation and pyruvate metabolism. Our approach advances the design of exhaled analysis for GC detection and holds promise as a non-invasive method to the clinic.

The science behind the nose: correlating volatile organic compound characterisation with canine biodetection of COVID-19.

The SARS-CoV-2 pandemic stimulated the advancement and research in the field of canine scent detection of COVID-19 and volatile organic compound (VOC) breath sampling. It remains unclear which VOCs are associated with positive canine alerts. This study aimed to confirm that the training aids used for COVID-19 canine scent detection were indeed releasing discriminant COVID-19 VOCs detectable and identifiable by gas chromatography (GC-MS). Inexperienced dogs (two Labradors and one English Springer Spaniel) were trained over 19 weeks to discriminate between COVID-19 infected and uninfected individuals and then independently validated. Getxent tubes, impregnated with the odours from clinical gargle samples, used during the canines' maintenance training process were also analysed using GC-MS. Three dogs were successfully trained to detect COVID-19. A principal components analysis model was created and confirmed the ability to discriminate between VOCs from positive and negative COVID-19 Getxent tubes with a sensitivity of 78% and a specificity of 77%. Two VOCs were found to be very predictive of positive COVID-19 cases. When comparing the dogs with GC-MS, F1 and Matthew's correlation coefficient, correlation scores of 0.69 and 0.37 were observed, respectively, demonstrating good concordance between the two methods. This study provides analytical confirmation that canine training aids can be safely and reliably produced with good discrimination between positive samples and negative controls. It is also a further step towards better understanding of canine odour discrimination of COVID-19 as the scent of interest and defining what VOC elements the canines interpret as "essential".

Enhanced selectivity of novel sea urchin-like h-/m-WO3 hetero nanoflowers for highly sensitive detection of ammonia by double filtration method

Real-time monitoring of toxic gases and breath markers can be performed by metal oxide semiconductor-based chemo-resistive gas sensors due to their simple structures, low cost, and faster and better recovery and response. Due to the effective electron-hole separation, tuning the development of phase junctions of the metal oxide is an efficient method for improving their gas sensing properties. In this study, two distinct hydrothermal methods were used to synthesize h-/m-WO3 hetero-nanoflowers. In the first method, L-Cysteine was used to facilitate the formation of phase junctions between h-WO3 and m-WO3 nanostructures, whereas Thiourea was used in the second. Various characterisation approaches validated the hexagonal-monoclinic phase junction development in the nanoflowers. The sensing material fabricated using Thiourea with a concentration of 0.01M performed better than other sensors. At 350°C, the selected sample displayed outstanding ammonia sensing capacity with the experimental detection limit of 1 ppm (response=3.33). The theoretical detection limit is determined to be 27 ppb. The selectivity of the sensor towards NH3 over H2S and acetone is increased by combining the devices with a double filtration setup. The effectiveness of the selected h-/m-WO3 sensor for diagnosing kidney dysfunction was evaluated by analyzing simulated breath samples.

Colorectal Cancer Diagnosis through Breath Test Using a Portable Breath Analyzer-Preliminary Data.

Screening methods available for colorectal cancer (CRC) to date are burdened by poor reliability and low patient adherence and compliance. An altered pattern of volatile organic compounds (VOCs) in exhaled breath has been proposed as a non-invasive potential diagnostic tool for distinguishing CRC patients from healthy controls (HC). The aim of this study was to evaluate the reliability of an innovative portable device containing a micro-gas chromatograph in enabling rapid, on-site CRC diagnosis through analysis of patients' exhaled breath. In this prospective trial, breath samples were collected in a tertiary referral center of colorectal surgery, and analysis of the chromatograms was performed by the Biomedical Engineering Department. The breath of patients with CRC and HC was collected into Tedlar bags through a Nafion filter and mouthpiece with a one-way valve. The breath samples were analyzed by an automated portable gas chromatography device. Relevant volatile biomarkers and discriminant chromatographic peaks were identified through machine learning, linear discriminant analysis and principal component analysis. A total of 68 subjects, 36 patients affected by histologically proven CRC with no evidence of metastases and 32 HC with negative colonoscopies, were enrolled. After testing a training set (18 CRC and 18 HC) and a testing set (18 CRC and 14 HC), an overall specificity of 87.5%, sensitivity of 94.4% and accuracy of 91.2% in identifying CRC patients was found based on three VOCs. Breath biopsy may represent a promising non-invasive method of discriminating CRC patients from HC.

347 Aerodynamic Size Distribution of SARS-CoV-2 Aerosol Shedding

OBJECTIVES/GOALS: We designed the Biocascade Exhaled Breath Sampler (BEBS) to characterize viral aerosol shedding among individuals with influenza and other respiratory virus infections. We first aimed to test the BEBS on volunteer COVID-19 cases and report the aerodynamic size distribution of exhaled breath aerosol particles carrying SARS-CoV-2 RNA. METHODS/STUDY POPULATION: From June 15 through December 15, 2022, we recruited 27 PCR-confirmed COVID-19 cases from a college campus and the surrounding community to provide 30-minute breath samples into a well-validated Gesundheit-II (G-II) exhaled breath aerosol sampler. Among these individuals, 17 provided an additional exhaled breath sample into the newly designed BEBS. We quantified samples for viral RNA using reverse transcription digital polymerase chain reaction (RT-dPCR) and determined the viral RNA copies collected within two aerosol size fractions (≤5 µm and &gt;5 µm in diameter) from the G-II, and four aerosol size fractions (&lt;1.15 µm, 1.15–3.2 µm, 3.3–8.2 µm, and &gt;8.2 µm) from the BEBS. RESULTS/ANTICIPATED RESULTS: Individuals with a SARS-CoV-2 Omicron BA.4 or BA.5 infection shed virus in aerosols at an average rate of 7.5x103 RNA copies per 30-minute G-II sample, with 78% of the total RNA in aerosols ≤5 µm in diameter. Among the BEBS samples, 10% of the total viral RNA was detected in aerosols &lt;1.15 µm, 43% in 1.15–3.2 µm, 37% in 3.3–8.2 µm, and 10% in the &gt;8.2 µm size fraction. Based on viral RNA loads, our results indicate that exhaled aerosols ≤3.2 µm contribute the majority of SARS-CoV-2 inhalation exposure. DISCUSSION/SIGNIFICANCE: Our data provide additional evidence that respirable aerosols contribute to the spread of SARS-CoV-2. Thus, our data suggest that mitigation measures designed to reduce infectious aerosol inhalation, such as ventilation and the use of air cleaners and respirators, are needed to control the spread.

Identification of chronic obstructive pulmonary disease using graph convolutional network in electronic nose

Chronic obstructive pulmonary disease (COPD) is a progressive lung dysfunction that can be triggered by exposure to chemicals. This disease can be identified with spirometry, but the patient feels uncomfortable, affecting the diagnosis results. Other disease markers are being investigated, including exhaled breath. This method can be applied easily, is non-invasive, has minimal side effects, and provides accurate results. This study applies the electronic nose method to distinguish healthy people and COPD suspects using exhaled breath samples. Twenty semiconductor gas sensors combined with machine learning algorithms were employed as an electronic nose system. Experimental results show that the frequency feature of the sensor responses used by the principal component analysis (PCA) method combined with graph convolutional network (GCN) can provide the highest accuracy value of 97.5% in distinguishing between healthy and COPD subjects. This method can improve the detection performance of electronic nose systems, which can help diagnose COPD.

The Identification of Acetic Acid-Ethanol Mixture Using Gas Sensor Array and Ensemble Regression

Identification of acetic acid-ethanol mixtures using a commercial gas sensor array equipped with ensemble regression has been carried out. The gas sensor analysis was simple, rapid, and fast since it did not require any sample preparation. A quantitative analysis of the acetic acid-ethanol mixture was carried out to determine the sensitivity and selectivity of the sensor in distinguishing the concentration of the acetic acid and ethanol mixture. This study focuses on the coefficient of determination of 80% of the calibration data set and recovery of 20% of the testing data set. The models showed excellent performance,specifically, the Bagging and Random Forest r2 for the ethanol calibration data reached 0.91 and 0.94, respectively. The corresponding ethanol test recoveries were 99.95% and 97.84%, indicating the robustness of the model in accurately predicting ethanol concentration. Acetic acid test recoveries were 100.56% and 101.38% with r2 of 0.89 and 0.93 for Bagging and Random Forest regression, respectively. Hence, the commercial gas sensor array equipped with ensemble regression can be applied to the quantification of the acetic acid – ethanol mixture and demonstrate opportunities for the practical use of this gas sensor array in analyzing real samples, i.e. human breath or environmental monitoring samples.

Can scent-detection dogs detect the stress associated with trauma cue exposure in people with trauma histories? A proof-of-concept study.

Post-traumatic stress disorder (PTSD) is an impairing mental health condition with high prevalence among military and general populations alike. PTSD service dogs are a complementary and alternative intervention needing scientific validation. We investigated whether dogs can detect putative stress-related volatile organic compounds (VOCs) in the breath of people with trauma histories (54% with PTSD) exposed to personalized trauma cues. Breath samples were collected from 26 humans over 40 experimental sessions during a calm (control breath sample) and stressed state induced by trauma cue exposure (target breath sample). Two scent detection canines were presented with the samples in a two alternative forced choice (2AFC) discrimination and yes/no detection task. The 2AFC task assessed the dogs' ability to discriminate between the two states within the breath samples of one individual. The detection task determined their ability to generalize the target odour across different individuals and different stressful events of one individual. Signal Detection Theory was applied to assess dogs' sensitivity, specificity, precision, and response bias. The dogs performed at ∼90% accuracy across all sample sets in the discrimination experiment, and at 74% and 81% accuracy, respectively, in the detection experiment. Further analysis of dog olfactory performance in relation to human donor self-reported emotional responses to trauma cue exposure suggested the dogs may have been detecting distinct endocrine stress markers. One dog's performance correlated with the human donors' self-reported fear responses and the other dog's performance correlated with the human donors' self-reported shame responses. Based on these correlations between dog performance and donor self-report measures, we speculate that the VOCs each dog was detecting likely originated from the sympathetico-adreno-medullary axis (SAM; adrenaline, noradrenaline) in the case of the first dog and the hypothalamo-pituitary-adrenal axis (HPA; glucocorticoids) in the case of the second dog. Our proof-of-concept study is the first to demonstrate that some dogs can detect putative VOCs emitted by people with trauma histories when experiencing distress theoretically associated with the intrusion and arousal/reactivity symptoms of PTSD. Results have potential to improve the effectiveness and training protocol of PTSD service dogs with a focus on enhancing their alert function.