Exhaled Breath Concentrations Research Articles

An efficient convolutional neural network-extreme gradient boosting hybrid deep learning model for disease detection applications

In this paper, we present an efficient deep-learning hybrid model comprising an extreme gradient boosting (XGBoost) supervised learning algorithm and convolutional neural networks (CNN) for the automated detection of diseases. The proposed model is implemented and tested to detect type-2 diabetes by measuring the acetone concentration in the exhaled breath. Acetone will be present in much higher concentrations in type-2 diabetic patients compared to non-diabetic people. A novel sensing module is designed and implemented in our study to measure the acetone concentration in exhaled breath. The proposed approach delivered good results, with a classification accuracy of 97.14%. The findings of this study show how effectively the proposed detection module functions in disease diagnosis applications. As the detection process is simple and non-invasive, people can undergo routine checks for diabetes with the proposed detection module.

Boosting acetone response of p-type Co3O4 sensor via Sn and Ni co-doping for diabetes diagnosis

The hole accumulation layer (HAL) configuration of p-type oxides (including Co3O4) in ambient air causes intrinsically low gas response and hinders their promising applications in exhaled gas analysis. Herein, Sn and Ni co-doping has been proposed to trigger the response of chemiresistive Co3O4 sensor toward acetone (biomarker of diabetes). Via incorporating 1 at% Sn and 0.5 at% Ni doping (Co2.95Sn0.03Ni0.02O4), the response to 100 ppm acetone has been boosted ∼2 orders (from 1.24 to 125.6) at 70 °C, the limit of detection (LoD) has been reduced ∼4 times (from 47.9 to 12.4 ppb), the optimal operation temperature has been decreased from 130 °C to ∼70 °C. Various characterizations suggest that co-doping induced abundant surface asymmetric oxygen vacancy defects (Co-□-Ni, Sn-□-Ni), which facilitate the catalytic oxidation of acetone molecules at relatively low operation temperature. In addition to excellent reproducibility and long-term stability, Co2.95Sn0.03Ni0.02O4 sensor could also operate under highly humid air background and reliably detect acetone concentration in exhaled breath at 150 °C, opening the opportunity for the practical application of p-type oxide sensors for diabetes diagnosis.

Complexity of Translating Analytics to Recent Cannabis Use and Impairment.

While current analytical methodologies can readily identify cannabis use, definitively establishing recent use within the impairment window has proven to be far more complex, requiring a new approach. Recent studies have shown no direct relationship between impairment and Δ9-tetra-hydrocannabinol (Δ9-THC) concentrations in blood or saliva, making legal "per se" Δ9-THC limits scientifically unjustified. Current methods that focus on Δ9-THC and/or metabolite concentrations in blood, saliva, urine, or exhaled breath can lead to false positive results for recent use due to the persistence of Δ9-THC well outside of the typical three to four-hour window of potential impairment following cannabis inhalation. There is also the issue of impairment due to other intoxicating substances- just because a subject exhibits signs of impairment and cannabis use is detected does not rule out the involvement of other drugs. Compounding the matter is the increasing popularity of hemp-derived cannabidiol (CBD) products following passage of the 2018 Farm Bill, which legalized industrial hemp in the U.S. Many of these products contain varying levels of Δ9-THC, which can lead to false positive tests for cannabis use. Furthermore, hemp-derived CBD is used to synthesize Δ8-THC, which possesses psychoactive properties similar to Δ9-THC and is surrounded by legal controversy. For accuracy, analytical methods must be able to distinguish the various THC isomers, which have identical masses and exhibit immunological cross-reactivity. A new testing approach has been developed based on exhaled breath and blood sampling that incorporates kinetic changes and the presence of key cannabinoids to detect recent cannabis use within the impairment window without the false positive results seen with other methods. The complexity of determining recent cannabis use that may lead to impairment demands such a comprehensive method so that irresponsible users can be accurately detected without falsely accusing responsible users who may unjustly suffer harsh, life-changing consequences.

The Association Between Personal Air Pollution Exposures and Fractional Exhaled Nitric Oxide (FeNO): A Systematic Review.

Airway inflammation is a common biological response to many types of environmental exposures and can lead to increased nitric oxide (NO) concentrations in exhaled breath. In recent years, several studies have evaluated airway inflammation using fractional exhaled nitric oxide (FeNO) as a biomarker of exposures to a range of air pollutants. This systematic review aims to summarize the studies that collected personal-level air pollution data to assess the air pollution-induced FeNO responses and to determine if utilizing personal-level data resulted in an improved characterization of the relationship between air pollution exposures and FeNO compared to using only ambient air pollution exposure data. Thirty-six eligible studies were identified. Overall, the studies included in this review establish that an increase in personal exposure to particulate and gaseous air pollutants can significantly increase FeNO. Nine out of the 12 studies reported statistically significant FeNO increases with increasing personal PM2.5 exposures, and up to 11.5% increase in FeNO per IQR increase in exposure has also been reported between FeNO and exposure to gas-phase pollutants, such as ozone, NO2, and benzene. Furthermore, factors such as chronic respiratory diseases, allergies, and medication use were found to be effect modifiers for air pollution-induced FeNO responses. About half of the studies that compared the effect estimates using both personal and ambient air pollution exposure methods reported that only personal exposure yielded significant associations with FeNO response. The evidence from the reviewed studies confirms that FeNO is a sensitive biomarker for air pollutant-induced airway inflammation. Personal air pollution exposure assessment is recommended to accurately assess the air pollution-induced FeNO responses. Furthermore, comprehensive adjustments for the potential confounding factors including the personal exposures of the co-pollutants, respiratory disease status, allergy status, and usage of medications for asthma and allergies are recommended while assessing the air pollution-induced FeNO responses.

Detection of PPB-Level H2S Concentrations in Exhaled Breath Using Au Nanosheet Sensors with Small Variability, High Selectivity, and Long-Term Stability.

The continuous monitoring of hydrogen sulfide (H2S) in exhaled breath enables the detection of health issues such as halitosis and gastrointestinal problems. However, H2S sensors with high selectivity and parts per billion-level detection capability, which are essential for breath analysis, and facile fabrication processes for their integration with other devices are lacking. In this study, we demonstrated Au nanosheet H2S sensors with high selectivity, ppb-level detection capability, and high uniformity by optimizing their fabrication processes: (1) insertion of titanium nitride (TiN) as an adhesion layer to prevent Au agglomeration on the oxide substrate and (2) N2 annealing to improve nanosheet crystallinity. The fabricated Au nanosheets successfully detected H2S at concentrations as low as 5.6 ppb, and the estimated limit of detection was 0.5 ppb, which is superior to that of the human nose (8-13 ppb). In addition, the sensors detected H2S in the exhaled breath of simulated patients at concentrations as low as 175 ppb while showing high selectivity against interfering molecules, such as H2, alcohols, and humidity. Since Au nanosheets with uniform sensor characteristics enable easy device integration, the proposed sensor will be useful for facile health checkups based on breath analysis upon its integration into mobile devices.

Exhaled breath is found to be better than blood samples for determining propofol concentrations in the brain tissues of rats

The correlation between propofol concentration in exhaled breath (C E) and plasma (C P) has been well-established, but its applicability for estimating the concentration in brain tissues (C B) remains unknown. Given the impracticality of directly sampling human brain tissues, rats are commonly used as a pharmacokinetic model due to their similar drug-metabolizing processes to humans. In this study, we measured C E, C P, and C B in mechanically ventilated rats injected with propofol. Exhaled breath samples from the rats were collected every 20 s and analyzed using our team’s developed vacuum ultraviolet time-of-flight mass spectrometry. Additionally, femoral artery blood samples and brain tissue samples at different time points were collected and measured using high-performance liquid chromatography mass spectrometry. The results demonstrated that propofol concentration in exhaled breath exhibited stronger correlations with that in brain tissues compared to plasma levels, suggesting its potential suitability for reflecting anesthetic action sites’ concentrations and anesthesia titration. Our study provides valuable animal data supporting future clinical applications.

Octane in exhaled breath to diagnose acute respiratory distress syndrome in invasively ventilated intensive care unit patients.

The concentration of exhaled octane has been postulated as a reliable biomarker for acute respiratory distress syndrome (ARDS) using metabolomics analysis with gas chromatography and mass spectrometry (GC-MS). A point-of-care (POC) breath test was developed in recent years to accurately measure octane at the bedside. The aim of the present study was to validate the diagnostic accuracy of exhaled octane for ARDS using a POC breath test in invasively ventilated intensive care unit (ICU) patients. This was an observational cohort study of consecutive patients receiving invasive ventilation for at least 24 h, recruited in two university ICUs. GC-MS and POC breath tests were used to quantify the exhaled octane concentration. ARDS was assessed by three experts following the Berlin definition and used as the reference standard. The area under the receiver operating characteristic curve (AUC) was used to assess diagnostic accuracy. 519 patients were included and 190 (37%) fulfilled the criteria for ARDS. The median (interquartile range) concentration of octane using the POC breath test was not significantly different between patients with ARDS (0.14 (0.05-0.37) ppb) and without ARDS (0.11 (0.06-0.26) ppb; p=0.64). The AUC for ARDS based on the octane concentration in exhaled breath using the POC breath test was 0.52 (95% CI 0.46-0.57). Analysis of exhaled octane with GC-MS showed similar results. Octane in exhaled breath has insufficient diagnostic accuracy for ARDS. This disqualifies the use of octane as a biomarker in the diagnosis of ARDS and challenges most of the research performed up to now in the field of exhaled breath metabolomics.

Low-Order Mechanistic Models for Volumetric and Temporal Capnography: Development, Validation, and Application.

The airflow model's single "alveolar" compartment has compliance and inertance, and feeds a resistive unperfused airway comprising a laminar-flow region followed by a turbulent-mixing region. The gas-mixing model tracks mixing-region CO 2 concentration, which is fitted breath-by-breath to the measured capnogram, yielding estimates of model parameters that characterize the capnogram. For the 17 examined records (310 breaths) of airflow, airway pressure and Tcap from ventilated adult patients, the models fit closely (mean rmse 1% of end-tidal cŞoncentration on Vcap; 1.7% on Tcap). The associated parameters (4 for Vcap, 5 for Tcap) for each exhalation, and airflow parameters for the corresponding forced inhalation, are robustly estimated, and consonant with each other and literature values. The models also allow, using Tcap alone, estimation of the entire exhaled airflow waveform to within a scaling. This suggests new Tcap-based tests, analogous to spirometry but with normal breathing, for discriminating chronic obstructive pulmonary disease (COPD) from congestive heart failure (CHF). A version trained on 15 exhalations from each of 24 COPD/24 CHF Tcap records from one hospital, then tested 100 times with 15 random exhalations from each of 27 COPD/31 CHF Tcap records at another, gave mean accuracy 80.6% (stdev 2.1%). Another version, tested on 29 COPD/32 CHF, yielded AUROC 0.84. Our mechanistic models closely fit Tcap and Vcap measurements, and yield subject-specific parameter estimates. This can inform cardiorespiratory care.

1-Year Prospective Study of the Relationship of Serial Exhaled Nitric Oxide Level and Asthma Control.

Previous studies found that the fractional nitric oxide concentration in exhaled breath (FeNO) levels in healthy Chinese adults was higher than in White adults. More understanding of serial changes of FeNO levels with asthma control in a real-life clinical setting would be important to explore the utility of this biomarker in routine asthma management. This study assessed the FeNO levels of Chinese asthma subjects with different levels of asthma control and the serial changes with respect to the changes in asthma control over 1 year. A 12-month prospective study (subjects recruited between November 2019 and January 2021) with serial measurement of FeNO levels at baseline, 4, 8 and 12 months. Asthma control was assessed by the Global Initiative for Asthma classification, Asthma Control Test (ACT) and Asthma Control Questionnaire (ACQ). Altogether, 136 subjects (mean age 51.51±15.09 years, 46[33.8%] male) had successful baseline FeNO measurements. At baseline, the FeNO levels did not show a statistically significant difference for controlled, partly controlled and uncontrolled asthma according to GINA classification, ACT and ACQ. FeNO levels decreased with improving asthma control and stayed at similar levels with unchanged or worsening asthma control for all subjects. For subjects with baseline blood eosinophil levels ≥300 cells/µL(n=59), FeNO levels decreased with improving asthma control, stayed similar without change for asthma control and increased with worsening asthma control. Receiver operating characteristic (ROC) analysis with the highest area under curve (AUC) for changes in FeNO levels for improving asthma control was between ≤ -10 to -25 ppb at various time points in the 12-month study. Changes in FeNO levels over time were associated with changes in clinical asthma control, particularly in those with higher blood eosinophil count and are likely more useful than a single time point measurement in managing asthma.

Biomarkers of particulate matter exposure in patients with chronic obstructive pulmonary disease: a systematic review.

In recent years, ambient particulate matter (PM) exposure has been strongly linked with health effects. Elevated levels of PM in polluted air have been correlated with the onset and development of chronic obstructive pulmonary disease (COPD). This systematic review was conducted to evaluate biomarkers that could reflect the effects of PM exposure in patients with COPD. We performed a systematic review of studies published on biomarkers associated with PM exposure in patients with COPD between January 01, 2012 and June 30, 2022 in PubMed/MEDLINE, EMBASE, and Cochrane databases. Studies that included data on biomarkers with COPD exposed PM were eligible for inclusion. Biomarkers were classified into 4 groups according to their mechanisms. Of the 105 studies identified, 22 were included in this study. Nearly 50 biomarkers have been proposed in the studies included in this review, and the most studied in relation to PM are several interleukins. Various mechanisms have been reported by which PM induces and aggravates COPD. Six studies related to oxidative stress, one related to direct effect of innate and adaptive immune systems, 16 associated with genetic regulation of inflammation, and two related to epigenetic regulation of physiology and susceptibility were found. Biomarkers related to these mechanisms were detected in serum, sputum, urine, exhaled breath concentration (EBC), and showed various correlations with PM in COPD. Various biomarkers have shown potential in predicting the extent of PM exposure in COPD patients. Future studies are needed to establish recommendations for regulation to reduce airborne PM, which could be used to develop strategies for prevention and management of environmental respiratory diseases.

Early Chronic Pulmonary Diseases Prediction System

Smart breath analyzers are developed as sensing terminals of a telemedicine architecture devoted to remote monitoring of patients suffering from Chronic Obstructive Pulmonary Disease (COPD). The devices based on different sensors CO2, smoke sensor and Volatile Organic Compounds (VOCs), relative humidity and temperature (R.H. & T) and heart rate, respiration sensors) monitor the breath air exhaled into the expiratory line of the bi-tube patient breathing circuit. The sensor raw signals are transmitted to national health service units / Doctor by TCP/IP communication through a cloud remote platform using IoT module space.The work is a proof-of-concept of a sensors-based IoT system with the perspective to predict continuously the effectiveness of monitoring and/or any state of exacerbation of the disease requiring healthcare. By a gas-mixing bench towards gas, smoke in environment and acetone concentrations in exhaled breath collected in a sampling bag were carried out to test the realized prototypes. The paper reports on the longitudinal use of health tags among high- risk COPD patients in the indoor & outdoor environment using PIC16F877A microcontroller. Key Word: Chronic Obstructive Pulmonary Disease (COPD); exacerbation ; Buprenorphine; Nalbuphine; Postoperative.

Metabolomics-based Sleepiness Markers for Risk Prevention and Traffic Safety (ME-SMART): a monocentric, controlled, randomized, crossover trial

BackgroundToo little sleep and the consequences thereof are a heavy burden in modern societies. In contrast to alcohol or illicit drug use, there are no quick roadside or workplace tests for objective biomarkers for sleepiness. We hypothesize that changes in physiological functions (such as sleep–wake regulation) are reflected in changes of endogenous metabolism and should therefore be detectable as a change in metabolic profiles. This study will allow for creating a reliable and objective panel of candidate biomarkers being indicative for sleepiness and its behavioral outcomes.MethodsThis is a monocentric, controlled, randomized, crossover, clinical study to detect potential biomarkers. Each of the anticipated 24 participants will be allocated in randomized order to each of the three study arms (control, sleep restriction, and sleep deprivation). These only differ in the amount of hours slept per night. In the control condition, participants will adhere to a 16/8 h wake/sleep regime. In both sleep restriction and sleep deprivation conditions, participants will accumulate a total sleep deficit of 8 h, achieved by different wake/sleep regimes that simulate real-life scenarios. The primary outcome is changes in the metabolic profile (i.e., metabolome) in oral fluid. Secondary outcome measures will include driving performance, psychomotor vigilance test, d2 Test of Attention, visual attention test, subjective (situational) sleepiness, electroencephalographic changes, behavioral markers of sleepiness, changes in metabolite concentrations in exhaled breath and finger sweat, and correlation of metabolic changes among biological matrices.DiscussionThis is the first trial of its kind that investigates complete metabolic profiles combined with performance monitoring in humans over a multi-day period involving different sleep–wake schedules. Hereby, we aim to establish a candidate biomarker panel being indicative for sleepiness and its behavioral outcomes. To date, there are no robust and easily accessible biomarkers for the detection of sleepiness, even though the vast damage on society is well known. Thus, our findings will be of high value for many related disciplines.Trial registrationClinicalTrials.gov Identifier NCT05585515, released on 18.10.2022; Swiss National Clinical Trial Portal SNCTP000005089, registered on 12 August 2022.

Au modified PrFeO3 with hollow tubular structure can be efficient sensing material for H2S detection.

The H2S concentration in exhaled breath increases marginally with the progress of periodontal disease, and H2S is considered to be one of the most important gases related to meat and seafood decomposition; however, the concentration of H2S is low and difficult to detect in such scenarios. In this study, Au–PrFeO3 nanocrystalline powders with high specific surface areas and porosities were prepared using an electrospinning method. Our experimental results show that loading Au on the material provides an effective way to increase its gas sensitivity. Au doping can decrease the material’s resistance by adjusting its energy band, allowing more oxygen ions to be adsorbed onto the material’s surface due to a spillover effect. Compared with pure PrFeO3, the response of 3 wt% Au–PrFeO3 is improved by more than 10 times, and the response time is more than 10 s shorter. In addition, the concentration of H2S due to the decomposition of shrimp was detected using the designed gas sensor, where the error was less than 15%, compared with that obtained using a GC-MS method. This study fully demonstrates the potential of Au–PrFeO3 for H2S concentration detection.

A portable acetone detector based on SmFeO3 can pre-diagnose diabetes through breath analysis

Breath analysis using gas sensors is becoming one of the important supplementing ways for an early diagnosis of diseases. The feasibility of detecting acetone concentration in exhaled breath using a SmFeO3-based sensor has been studied herein. The detection limits of acetone using a SmFeO3-based sensor are extremely low (1.56–0.01 ppm; 1.87–0.02 ppm; 2.39–0.05 ppm; 3.22–0.1 ppm; 4.1–0.2 ppm; 4.79–0.5 ppm; 5.92–1 ppm). To remove the effects of carbon dioxide and relative humidity (RH), a mathematical model between the response and acetone concentration, carbon dioxide concentration and RH in a person’s exhaled breath is established via machine learning. Volunteer studies have proved the accuracy of this mathematical model. Compare with the acetone concentration obtained by GC-MS method, the accuracy of the proposed method exceeded 85 %. Finally, a portable acetone detector based on the SmFeO3 sensor is designed and realized to monitor the dynamic change in acetone concentration in the exhaled breath of volunteers before and after meals, and the experimental results have proved that the method based on the gas sensor and Machine learning (ML) is feasible and effective in accurately detecting acetone concentration in persons’ exhaled breath.

Effect of airway clearance therapies on mucociliary clearance in adults with cystic fibrosis: A randomized controlled trial.

Cystic fibrosis (CF) is an inherited disorder causing impaired mucociliary clearance within the respiratory tract, and is associated with bronchiectasis, chronic respiratory infections, and early death. Airway clearance therapies have long been a cornerstone of management of individuals with CF, although evidence supporting their use is lacking. We designed a randomized controlled trial to quantitatively compare the effects of different forms of airway clearance on mucociliary clearance. Three different physiotherapy methods to augment cough-clearance were studied in addition to cough-clearance alone: high-frequency chest-wall oscillating vest, oscillatory positive expiratory pressure, and whole-body vibration. We used gamma scintigraphy after inhalation of radiolabeled particles to quantify mucus clearance before, during, and after physiotherapy. As secondary endpoints, we measured concentrations of small molecules in exhaled breath that may impact mucus clearance. Ten subjects were enrolled and completed study procedures. No differences were identified between any method of airway clearance, including cough clearance alone. We did identify changes in certain small molecule concentrations in exhaled breath following airway clearance. Due to the limitations of this study, we do not believe the negative results suggest a change in clinical practice with regard to airway clearance. Findings pertaining to small molecules in exhaled breath may serve as future opportunities for study.

Breath octane and acetaldehyde as markers for acute respiratory distress syndrome in invasively ventilated patients suspected to have ventilator-associated pneumonia.

RationaleThe concentration of octane and acetaldehyde in exhaled breath has good diagnostic accuracy for acute respiratory distress syndrome (ARDS). We aimed to determine whether breath octane and acetaldehyde are able to distinguish the presence and absence of ARDS in critically ill patients suspected to have ventilator-associated pneumonia (VAP).MethodsThis is a secondary analysis of a prospective observational study into exhaled breath analysis using gas chromatography–time-of-flight mass spectrometry. Difference in the relative abundance of octane and acetaldehyde in exhaled breath was compared between patients with and without ARDS using the Mann–Whitney U-test and the association was quantified using logistic regression. The discriminative accuracy of octane and acetaldehyde, alone or in combination, was calculated using the area under the receiver operating characteristic curve (AUROCC).ResultsWe included 98 patients, of whom 32 had ARDS and 66 did not. The area under the acetaldehyde peak was higher in patients with ARDS (p=0.03), and associated with the presence of ARDS (OR 1.06 per 100 000 count change, 95% CI 1.02–1.13 per 100 000 count change; p=0.01). A combined model with octane and acetaldehyde showed a high specificity and low sensitivity (90% and 40.6%, respectively), with a low accuracy (AUROCC 0.65, 95% CI 0.53–0.78).ConclusionPatients suspected to have VAP with ARDS had a higher acetaldehyde concentration in exhaled breath than patients suspected to have VAP without ARDS. However, in this patient population, discrimination of these breath biomarkers for ARDS was poor, indicating the difficulty of translating diagnostic tests between clinical settings.

Characterizing exposure to benzene, toluene, and naphthalene in firefighters wearing different types of new or laundered PPE.

The fire service has become more aware of the potential for adverse health outcomes due to occupational exposure to hazardous combustion byproducts. Because of these concerns, personal protective equipment (PPE) manufacturers have developed new protection concepts like particulate-blocking hoods to reduce firefighters' exposures. Additionally, fire departments have implemented exposure reduction interventions like routine laundering of PPE after fire responses. This study utilized a fireground exposure simulator (FES) with 24 firefighters performing firefighting activities on three consecutive days wearing one of three PPE ensembles (stratified by hood design and treatment of PPE): 1) new knit hood, new turnout jacket and new turnout pants 2) new particulate-blocking hood, new turnout jacket and new turnout pants or 3) laundered particulate-blocking hood, laundered turnout jacket and laundered turnout pants. As firefighters performed the firefighting activities, personal air sampling on the outside and inside the turnout jacket was conducted to quantify exposures to volatile organic compounds (VOCs) and naphthalene. Pre- and immediately post-fire exhaled breath samples were collected to characterize the absorption of VOCs. Benzene, toluene, and naphthalene were found to diffuse through and/or around the turnout jacket, as inside jacket benzene concentrations were often near levels reported outside the turnout jacket (9.7-11.7% median benzene reduction from outside the jacket to inside the jacket). The PPE ensemble did not appear to affect the level of contamination found inside the jacket for the compounds evaluated here. Benzene concentrations in exhaled breath increased significantly from pre to post-fire for all three groups (p-values < 0.05). The difference of pre-to post-fire benzene exhaled breath concentrations were positively associated with inside jacket and outside jacket benzene concentrations, even though self-contained breathing apparatus (SCBA) were worn during each response. This suggests the firefighters can absorb these compounds via the dermal route.

Point-of-care detection of sevoflurane anesthetics in exhaled breath using a miniature TOFMS for diagnosis of postoperative agitation symptoms in children.

In the operation using sevoflurane as an anesthetic, some patients, especially children, will have agitation symptoms after awakening from anesthesia. The incidence of agitation is about 20%, and current detection methods cannot predict the probability of a patient with agitation. In this paper, a magnetic field enhanced photoelectron ionization (MEPEI) miniature time-of-flight mass spectrometer (TOFMS) was developed for point-of-care detection and verification of the relationship between postoperative agitation symptoms and sevoflurane concentration in exhaled breath. The MEPEI source is water vapor resistant and can directly ionize sevoflurane via capillary sampling and obtain its characteristic ion [C4H3F6O]+ (m/z 181), and the analysis time of exhaled breath is only 60 s. Three standard curves of 0.5-80 ppmv, 80-2000 ppmv and 2000-15 000 ppmv were formulated to quantitatively detect sevoflurane in different scenarios, the coefficient of determination (R2) was higher than 0.9882 and the relative standard deviation (RSD) of signal intensity was only 1.24%. The results indicated that four of the 46 child patients had agitation symptoms. Partial least squares-discriminant analysis (PLS-DA) was performed to analyze the data, and an identification and treatment strategy was established for child patients with agitation symptoms. The new miniature MEPEI-TOFMS was also successfully used to evaluate the concentration of sevoflurane in a medical environment. The real-time monitoring of sevoflurane concentration in exhalation indicates the potential of this method for low-cost and convenient point-of-care (POC) detection and diagnosis of agitation symptoms.

Prediction of potential passive exposure from commercial electronic nicotine delivery systems using exhaled breath analysis and computational fluid dynamic techniques

Use of computational fluid dynamic (CFD) modeling to predict temporal and spatial constituent exposure for non-electronic nicotine delivery systems (ENDS) users (passive exposure) provides a more efficient methodology compared to conducting actual exposure studies. We conducted a clinical study measuring exhaled breath concentrations of glycerin, propylene glycol, nicotine, benzoic acid, formaldehyde, acetaldehyde, acrolein, menthol and carbon monoxide from use of eight different commercial ENDS devices and a non-menthol and menthol cigarette. Because baseline adjusted levels of other constituents were not consistently above the limit of detection, the mean minimum and maximum per puff exhaled breath concentrations (N = 20/product) of glycerin (158.7–260.9 µg), propylene glycol (0.941–3.58 µg), nicotine (0.10–1.06 µg), and menthol (0.432–0.605 µg) from use of the ENDS products were used as input parameters to predict temporal and spatial concentrations in an environmental chamber, office, restaurant, and car using different ENDS use scenarios. Among these indoor locations and ENDS use scenarios, the car with closed windows resulted in the greatest concentrations while opening the car windows produced the lowest concentrations. The CFD predicted average maximum glycerin and propylene glycol concentration ranged from 0.25 to 1068 µg m−3 and 1.5 pg m−3 to 13.56 µg m−3, respectively. For nicotine and menthol the CFD predicted maximum concentration ranged from 0.16 pg m−3 to 4.02 µg m−3 and 0.068 pg m−3 to 2.43 µg m−3, respectively. There was better agreement for CFD-predicted nicotine concentrations than glycerin and propylene glycol with published reports highlighting important experimental and computational variables. Maximum measured nicotine levels from environmental tobacco smoke in offices, restaurants, and cars exceeded our maximum average CFD predictions by 7–97 times. For all the measured exhaled breath constituents and CFD predicted constituents, except for propylene glycol and glycerin, concentrations were less from use of ENDS products compared to combustible cigarettes. NCT number: NCT04143256

A Bio-Fluorometric Acetone Gas Imaging System for the Dynamic Analysis of Lipid Metabolism in Human Breath

We constructed an imaging system to measure the concentration of acetone gas by acetone reduction using secondary alcohol dehydrogenase (S-ADH). Reduced nicotinamide adenine dinucleotide (NADH) was used as an electron donor, and acetone was imaged by fluorescence detection of the decrease in the autofluorescence of NADH. In this system, S-ADH–immobilized membranes wetted with buffer solution containing NADH were placed in a dark box, and UV-LED excitation sheets and a high-sensitivity camera were installed on both sides of the optical axis to enable loading of acetone gas. A hydrophilic polytetrafluoroethylene (H-PTFE) membrane with low autofluorescence was used as a substrate, and honeycomb-like through-hole structures were fabricated using a CO2 laser device. After loading the enzyme membrane with acetone gas standards, a decrease in fluorescence intensity was observed in accordance with the concentration of acetone gas. The degree of decrease in fluorescence intensity was calculated using image analysis software; it was possible to quantify acetone gas at concentrations of 50–2000 ppb, a range that includes the exhaled breath concentration of acetone in healthy subjects. We applied this imaging system to measure the acetone gas in the air exhaled by a healthy individual during fasting.