Detection of trace volatile organic compounds in spiked breath samples: a leap towards breathomics

Breathomics is the future of non-invasive point-of-care devices. The field of breathomics can be split into the isolation of disease-specific volatile organic compounds (VOCs) and their detection. In the present work, an array of five quartz tuning fork (QTF)-based sensors modified by polymer with nanomaterial additive has been utilized. The array has been used to detect samples of human breath spiked with ∼0.5 ppm of known VOCs namely, acetone, acetaldehyde, octane, decane, ethanol, methanol, styrene, propylbenzene, cyclohexanone, butanediol, and isopropyl alcohol which are bio-markers for certain diseases. Polystyrene was used as the base polymer and it was functionalized with 4 different fillers namely, silver nanoparticles-reduced graphene oxide composite, titanium dioxide nanoparticles, zinc ferrite nanoparticles-reduced graphene oxide composite, and cellulose acetate. Each of these fillers enhanced the selectivity of a particular sensor towards a certain VOC compared to the pristine polystyrene-modified sensor. Their interaction with the VOCs in changing the mechanical properties of polymer giving rise to change in the resonant frequency of QTF is used as sensor response for detection. The interaction of functionalized polymers with VOCs was analyzed by FTIR and UV-vis spectroscopy. The collective sensor response of five sensors is used to identify VOCs using an ensemble classifier with 92.8% accuracy of prediction. The accuracy of prediction improved to 96% when isopropyl alcohol, ethanol, and methanol were considered as one class.

Simultaneous Biomechanical and Biochemical Monitoring for Self-Powered Breath Analysis

The high moisture level of exhaled gases unavoidably limits the sensitivity of breath analysis via wearable bioelectronics. Inspired by pulmonary lobe expansion/contraction observed during respiration, a respiration-driven triboelectric sensor (RTS) was devised for simultaneous respiratory biomechanical monitoring and exhaled acetone concentration analysis. A tin oxide-doped polyethyleneimine membrane was devised to play a dual role as both a triboelectric layer and an acetone sensing material. The prepared RTS exhibited excellent ability in measuring respiratory flow rate (2-8 L/min) and breath frequency (0.33-0.8 Hz). Furthermore, the RTS presented good performance in biochemical acetone sensing (2-10 ppm range at high moisture levels), which was validated via finite element analysis. This work has led to the development of a novel real-time active respiratory monitoring system and strengthened triboelectric-chemisorption coupling sensing mechanism.

Highly Sensitive Surface Plasmon Resonance Humidity Sensor Based on a Polyvinyl-Alcohol-Coated Polymer Optical Fiber

A surface-plasmon-resonance-based fiber device is proposed for highly sensitive relative humidity (RH) sensing and human breath monitoring. The device is fabricated by using a polyvinyl alcohol (PVA) film and gold coating on the flat surface of a side-polished polymer optical fiber. The thickness and refractive index of the PVA coating are sensitive to environmental humidity, and thus the resonant wavelength of the proposed device exhibits a redshift as the RH increases. Experimental results demonstrate an average sensitivity of 4.98 nm/RH% across an ambient RH ranging from 40% to 90%. In particular, the sensor exhibits a linear response between 75% and 90% RH, with a sensitivity of 10.15 nm/RH%. The device is suitable for human breath tests and shows an average wavelength shift of up to 228.20 nm, which is 10 times larger than that of a silica-fiber-based humidity sensor. The corresponding response and recovery times are determined to be 0.44 s and 0.86 s, respectively. The proposed sensor has significant potential for a variety of practical applications, such as intensive care and human health analysis.

Accuracy of a breath ketone analyzer to detect ketosis in adults and children with type 1 diabetes

OBJECTIVE

To assess the accuracy of a breath ketone analyzer to detect ketosis in adults and children with type 1 diabetes.

RESEARCH DESIGN AND METHODS

This is a proof-of-concept, prospective study comparing breath ketone analyzer and blood ketone meter to detect ketosis.

RESULTS

A total of 500 measurements from 19 adults and children with type 1 diabetes were analyzed. There was a significant association between the breath ketone analyzer and blood ketone meter results in non-fasting adults (p = 0.0066), but not in children (p = 0.4579). In adults, a cut-off of 3.9 PPM on the breath ketone analyzer maximized the Youden Index with an AUC of 0.73. This cut-off for the breath ketone analyzer had 94.7% sensitivity and 54.2% specificity to detect ketosis (≥0.6 mmol/L in blood ketone meter).

CONCLUSIONS

The breath ketone analyzer may be considered as a non-invasive screening tool to rule out ketosis in adults with type 1 diabetes.

Wearable Collector for Noninvasive Sampling of SARS-CoV-2 from Exhaled Breath for Rapid Detection

Airborne transmission of exhaled virus can rapidly spread, thereby increasing disease progression from local incidents to pandemics. Due to the COVID-19 pandemic, states and local governments have enforced the use of protective masks in public and work areas to minimize the disease spread. Here, we have leveraged the function of protective face coverings toward COVID-19 diagnosis. We developed a user-friendly, affordable, and wearable collector. This noninvasive platform is integrated into protective masks toward collecting airborne virus in the exhaled breath over the wearing period. A viral sample was sprayed into the collector to model airborne dispersion, and then the enriched pathogen was extracted from the collector for further analytical evaluation. To validate this design, qualitative colorimetric loop-mediated isothermal amplification, quantitative reverse transcription polymerase chain reaction, and antibody-based dot blot assays were performed to detect the presence of SARS-CoV-2. We envision that this platform will facilitate sampling of current SARS-CoV-2 and is potentially broadly applicable to other airborne diseases for future emerging pandemics.

Tunable diode laser-based two-line thermometry: a noncontact thermometer for active body temperature measurement

A precise and fast optical thermometer based on a tunable diode laser absorption spectroscopy is developed for breath diagnostics with relevance to noncontact body temperature measurement. As water vapor (H₂O) is the major component in human breath, two optimal absorption lines of H₂O at 1392 nm and 1371 nm are selected for sensitive body temperature measurement by systematically investigating the near-infrared spectral database. The optical thermometer is developed using two distributed feedback diode lasers with the time-division multiplexing technique to achieve real-time measurement. The sensor performance such as accuracy, repeatability, and time response is tested in a custom-designed gas cell with its temperature controlled in the range of 20°C-50°C. By measuring the test air with different water concentrations, the sensor consistently shows a quadratic response to temperature with an R-squared value of 0.9998. Under the readout rate of 1 s, the sensor achieves a measurement precision of 0.16°C, suggesting its potential applications to fast, accurate, and noncontact body temperature measurements.

Cross Platform Analysis of Volatile Organic Compounds Using Selected Ion Flow Tube and Proton-Transfer-Reaction Mass Spectrometry

Volatile breath metabolites serve as potential disease biomarkers. Online mass spectrometry (MS) presents real-time quantification of breath volatile organic compounds (VOCs). The study aims to assess the relationship between two online analytical mass spectrometry techniques in the quantification of target breath metabolites: selected ion flow tube mass spectrometry (SIFT-MS) and proton-transfer-reaction time-of-flight mass spectrometry (PTR-ToF-MS). The two following techniques were employed: (i) direct injection with bag sampling using SIFT-MS and PTR-ToF-MS and (ii) direct injection and thermal desorption (TD) tube comparison using PTR-ToF-MS. The concentration of abundant breath metabolites, acetone and isoprene, demonstrated a strong positive linear correlation between both mass spectrometry techniques (r = 0.97, r = 0.89, respectively; p < 0.001) and between direct injection and TD tube (r = 0.97, r = 0.92, respectively; p < 0.001) breath sampling techniques. This was reflected for the majority of short chain fatty acids and alcohols tested (r > 0.80, p < 0.001). Analyte concentrations were notably higher with the direct injection of a sampling bag compared to the TD method. All metabolites produced a high degree of agreement in the detection range of VOCs between SIFT-MS and PTR-ToF-MS, with the majority of compounds falling within 95% of the limits of agreement with Bland-Altman analysis. The cross platform analysis of exhaled breath demonstrates strong positive correlation coefficients, linear regression, and agreement in target metabolite detection rates between both breath sampling techniques. The study demonstrates the transferability of using data outputs between SIFT-MS and PTR-ToF-MS. It supports the implementation of a TD platform in multi-site studies for breath biomarker research in order to facilitate sample transport between clinics and the laboratory.

Isotopic gas analysis by means of mid-infrared photoacoustic spectroscopy targeting human exhaled air

There is a great need for cost-efficient non-invasive medical diagnostic tools for analyzing humanly exhaled air. Compared to present day methods, photoacoustic spectroscopy (PAS) can provide a compact and portable (bedside), sensitive and inexpensive solution. We demonstrate a novel portable photoacoustic spectroscopic platform for isotopic measurements of methane (CH₄). We identify and discriminate the ¹²CH₄- and ¹³CH₄ isotopologues and determine their mixing ratio. An Allan deviation analysis shows that the noise equivalent concentration for CH₄ is 200 ppt (pmol/mol) at 100 s of integration time, corresponding to a normalized noise equivalent absorption coefficient of 5.1×10^-9Wcm^-1Hz^-1/2, potentially making the PAS sensor a truly disruptive instrument for bedside monitoring using isotope tracers by providing real-time metabolism data to clinical personnel.

Unique Noncontact Monitoring of Human Respiration and Sweat Evaporation Using a CsPb2Br5-Based Sensor

Respiration monitoring and human sweat sensing have promising application prospects in personal healthcare data collection, disease diagnostics, and the effective prevention of human-to-human transmission of fatal viruses. Here, we have introduced a unique respiration monitoring and touchless sensing system based on a CsPb₂Br₅/BaTiO₃ humidity-sensing layer operated by water-induced interfacial polarization and prepared using a facile aerosol deposition process. Based on the relationship between sensing ability and layer thickness, the sensing device with a 1.0 μm thick layer was found to exhibit optimal sensing performance, a result of its ideal microstructure. This sensor also exhibits the highest electrical signal variation at 0.5 kHz due to a substantial polarizability difference between high and low humidity. As a result, the CsPb₂Br₅/BaTiO₃ sensing device shows the best signal variation of all types of breath-monitoring devices reported to date when used to monitor sudden changes in respiratory rates in diverse situations. Furthermore, the sensor can effectively detect sweat evaporation when placed 1 cm from the skin, including subtle changes in capacitance caused by finger area and motion, skin moisture, and contact time. This ultrasensitive sensor, with its fast response, provides a potential new sensing platform for the long-term daily monitoring of respiration and sweat evaporation.

The Ketogenic Diet: Breath Acetone Sensing Technology

The ketogenic diet, while originally thought to treat epilepsy in children, is now used for weight loss due to increasing evidence indicating that fat is burned more rapidly when there is a low carbohydrate intake. This low carbohydrate intake can lead to elevated ketone levels in the blood and breath. Breath and blood ketones can be measured to gauge the level of ketosis and allow for adjustment of the diet to meet the user’s needs. Blood ketone levels have been historically used, but now breath acetone sensors are becoming more common due to less invasiveness and convenience. New technologies are being researched in the area of acetone sensors to capitalize on the rising popularity of the diet. Current breath acetone sensors come in the form of handheld breathalyzer devices. Technologies in development mostly consist of semiconductor metal oxides in different physio-chemical formations. These current devices and future technologies are investigated here with regard to utility and efficacy. Technologies currently in development do not have extensive testing of the selectivity of the sensors including the many compounds present in human breath. While some sensors have undergone human testing, the sample sizes are very small, and the testing was not extensive. Data regarding current devices is lacking and more research needs to be done to effectively evaluate current devices if they are to have a place as medical devices. Future technologies are very promising but are still in early development stages.

Diatom Bio-Silica and Cellulose Nanofibril for Bio-Triboelectric Nanogenerators and Self-Powered Breath Monitoring Masks

The application of biodegradable and biocompatible materials to triboelectric nanogenerators (TENGs) for harvesting energy from motions of the human body has been attracting significant research interest. Herein, we report diatom bio-silica as a biomaterial additive to enhance the output performance of cellulose nanofibril (CNF)-based TENGs. Diatom frustules (DFs), which are tribopositive bio-silica having hierarchically porous three-dimensional structures and high surface area, have hydrogen bonds with CNFs, resulting in enhanced electron-donating capability and a more roughened surface of the DF-CNF composite film. Hence, DFs were applied to form a tribopositive composite film with CNFs. The DF-CNF biocomposite film is mechanically strong, electron-rich, low-cost, and frictionally rough. The DF-CNF TENG showed an output voltage of 388 V and time-averaged power of 85.5 mW/m² in the contact-separation mode with an efficient contact area of 4.9 cm², and the generated power was sufficient for instantaneous illumination of 102 light-emitting diodes. In addition, a cytotoxicity study and biocompatibility tests on rabbit skin suggested that the DF-CNF composite was biologically safe. Moreover, a practical application of the DF-CNF TENG was examined with a self-powered smart mask for human breathing monitoring. This study not only suggests high output performance of biomaterial-based TENGs but also presents the diverse advantages of the DFs in human body-related applications such as self-powered health monitoring masks, skin-attachable power generators, and tactile feedback systems.

Vacuum Ultraviolet Absorption Spectroscopy Analysis of Breath Acetone Using a Hollow Optical Fiber Gas Cell

Human breath is a biomarker of body fat metabolism and can be used to diagnose various diseases, such as diabetes. As such, in this paper, a vacuum ultraviolet (VUV) spectroscopy system is proposed to measure the acetone in exhaled human breath. A strong absorption acetone peak at 195 nm is detected using a simple system consisting of a deuterium lamp source, a hollow-core fiber gas cell, and a fiber-coupled compact spectrometer corresponding to the VUV region. The hollow-core fiber functions both as a long-path and an extremely small-volume gas cell; it enables us to sensitively measure the trace components of exhaled breath. For breath analysis, we apply multiple regression analysis using the absorption spectra of oxygen, water, and acetone standard gas as explanatory variables to quantitate the concentration of acetone in breath. Based on human breath, we apply the standard addition method to obtain the measurement accuracy. The results suggest that the standard deviation is 0.074 ppm for healthy human breath with an acetone concentration of around 0.8 ppm and a precision of 0.026 ppm. We also monitor body fat burn based on breath acetone and confirm that breath acetone increases after exercise because it is a volatile byproduct of lipolysis.

Multiplexed Nanomaterial-Based Sensor Array for Detection of COVID-19 in Exhaled Breath

This article reports on a noninvasive approach in detecting and following-up individuals who are at-risk or have an existing COVID-19 infection, with a potential ability to serve as an epidemic control tool. The proposed method uses a developed breath device composed of a nanomaterial-based hybrid sensor array with multiplexed detection capabilities that can detect disease-specific biomarkers from exhaled breath, thus enabling rapid and accurate diagnosis. An exploratory clinical study with this approach was examined in Wuhan, China, during March 2020. The study cohort included 49 confirmed COVID-19 patients, 58 healthy controls, and 33 non-COVID lung infection controls. When applicable, positive COVID-19 patients were sampled twice: during the active disease and after recovery. Discriminant analysis of the obtained signals from the nanomaterial-based sensors achieved very good test discriminations between the different groups. The training and test set data exhibited respectively 94% and 76% accuracy in differentiating patients from controls as well as 90% and 95% accuracy in differentiating between patients with COVID-19 and patients with other lung infections. While further validation studies are needed, the results may serve as a base for technology that would lead to a reduction in the number of unneeded confirmatory tests and lower the burden on hospitals, while allowing individuals a screening solution that can be performed in PoC facilities. The proposed method can be considered as a platform that could be applied for any other disease infection with proper modifications to the artificial intelligence and would therefore be available to serve as a diagnostic tool in case of a new disease outbreak.

Engineering synthetic breath biomarkers for respiratory disease

Human breath contains many volatile metabolites. However, few breath tests are currently used in the clinic to monitor disease due to bottlenecks in biomarker identification. Here we engineered breath biomarkers for respiratory disease by local delivery of protease-sensing nanoparticles to the lungs. The nanosensors shed volatile reporters upon cleavage by neutrophil elastase, an inflammation-associated protease with elevated activity in lung diseases such as bacterial infection and alpha-1 antitrypsin deficiency. After intrapulmonary delivery into mouse models with acute lung inflammation, the volatile reporters are released and expelled in breath at levels detectable by mass spectrometry. These breath signals can identify diseased mice with high sensitivity as early as 10 min after nanosensor administration. Using these nanosensors, we performed serial breath tests to monitor dynamic changes in neutrophil elastase activity during lung infection and to assess the efficacy of a protease inhibitor therapy targeting neutrophil elastase for the treatment of alpha-1 antitrypsin deficiency.

Constructing an E-Nose Using Metal-Ion-Induced Assembly of Graphene Oxide for Diagnosis of Lung Cancer via Exhaled Breath

A flexible electronic-nose (E-nose) was constructed by assembling graphene oxide (GO) using different types of metal ions (M^x+) with different ratio of GO to M^x+. Owing to the cross-linked networks, the M^x+-induced assembly of graphene films resulted in different porous structures. A chemi-resistive sensor array was constructed by coating the GO-M hybrid films on PET substrate patterned with 8 interdigited electrodes, followed by in situ reduction of GO to rGO with hydrazine vapor. Each of the sensing elements on the sensor array showed a cross-reactive response toward different types of gases at room temperature. Compared to bare rGO, incorporation of metal species into rGO significantly improved sensitivity owing to the additional interaction between metal species and gas analyte. Principle component analysis (PCA) showed that four types of exhaled breath (EB) biomarkers including acetone, isoprene, ammonia, and hydrothion in sub-ppm concentrations can be discriminated well. To overcome the interference from humidity in EB, a protocol to collect and analyze EB gases was established and further validated by simulated EB samples. Finally, clinical EB samples collected from patients with lung cancer and healthy controls were analyzed. In a 106 case study, the healthy group can be accurately distinguished from lung cancer patients by linear discrimination analysis. With the assistance of an artificial neural network, a sensitivity of 95.8% and specificity of 96.0% can be achieved in the diagnosis of lung cancer based on the E-nose. We also find that patients with renal failure can be distinguished through comparison of dynamic response curves between patient and healthy samples on some specific sensing elements. These results demonstrate the proposed E-nose will have great potential in noninvasive disease screening and personalized healthcare management.

Compact plasmonic fiber tip for sensitive and fast humidity and human breath monitoring

We demonstrate a plasmonic fiber tip for relative humidity (RH) detection by integrating a gold nanomembrane onto the end-face of a multimode optical fiber via a flexible and high-efficiency transfer method. Fast water condensation/evaporation is responsible for the high performance of the fiber tip in response to RH. A high sensitivity of 279 pm/%RH is obtained in the range of $ 11\% \sim 92\% {\rm RH} $11%∼92%RH. Taking advantage of the fast dynamics (response and recovery times of 156 ms and 277 ms), the plasmonic fiber tip offers an excellent detection capability to human breaths at varied frequencies and depths. The compact, easy-fabrication, and fast-dynamics plasmonic platform has versatile potential for practical applications, including environmental and healthcare monitoring, as well as biochemical sensing.

Carbon monoxide breath test assessment of mild hemolysis in Gilbert's syndrome

BACKGROUND

Mild hemolysis is difficult to determinate by traditional methods, and its role in Gilbert's syndrome (GS) is unclear. The main aims were to inspect the erythrocyte (RBC) survival in GS by using Levitt's carbon monoxide (CO) breath test and to assess its contribution to unconjugated hyperbilirubinemia.

METHODS

Fifty subjects with GS and 1 with type-II Crigler-Najjar syndrome (CN2) received RBC lifespan measurement with Levitt's CO breath test. Mean RBC lifespan was compared with normal referral value. Correlations of serum total bilirubin (TB) with RBC lifespan, blood panel data, demographic factors, and uridine diphosphate glucuronosyltransferase (UGT1A1) mutation load were calculated by Spearman analysis. Susceptibility factors for mild hemolysis were analyzed by multivariate regression analysis.

RESULTS

The mean RBC lifespan of the GS subjects was significantly shorter than the normal reference value (95.4 ± 28.9 days vs 126 days; t = -7.504, P < .01), with 30.0% below the lower limit of the normal reference range (75 days). The RBC lifespan of the participant with CN2 was 82 days. Serum TB correlated positively with UGT1A1 mutation load (γ = 0.281, P = .048), hemoglobin (γ = .359, P = .010) and hematocrit (γ = 0.365, P = .010), but negatively with RBC lifespan (γ = -0.336, P = .017). No significant susceptibility factors for mild hemolysis were found.

CONCLUSIONS

The results indicate that mild hemolysis indeed, exists in a portion of patients with GS and might serve as an important contributor to unconjugated hyperbilirubinemia in addition to UGT1A1 polymorphism. Further studies on the mechanism and the potential risks in various medical treatments might be wanted.

A sampler prototype for the simultaneous collection of exhaled air and breath condensate

Exhaled air and breath condensate contain a large number of health biomarkers, such as volatile and semi-volatile organic compounds, proteins and lipids. Nowadays, the collection of breath samples is carried out by commercial or lab-made sampling systems that collect only one type of sample (e.g. gaseous or condensate phase), thus limiting the diagnostic capability of breath tests. This work presents a portable prototype optimized for the simultaneous collection of gaseous exhaled breath and exhaled breath condensate within five minutes. The system is fully portable and has a total weight of about 1 Kg. An illustrative determination of ethanol, isoprene, acetone, isopropyl alcohol, 1-propanol, 2-butanone, 2-pentanone, toluene and xylenes in breath, and cortisol and 8-iso-prostaglandin F_2α in breath condensate is discussed.

Accuracy of a portable breath meter test for the detection of halitosis in children and adolescents

OBJECTIVES

This study aimed to determine the accuracy of the Breath-Alert™ portable breath meter (BA) for the detection of halitosis in children and adolescents, considering the organoleptic test (OT) as the gold standard in this assessment.

METHODS

A cross-sectional study was conducted on 150 children (aged 6-12 years). OT was performed by three independent examiners on a single occasion, obtaining three scores of 0-5 points on the Rosenberg's organoleptic scale. The median of the three evaluations for each child was used for analysis. BA was used according to the manufacturer's instructions, with breath odor scored from 0-5 points. Scores ≥2 on both tests were considered indicative of halitosis.

RESULTS

A total of 26 (17.3%) and 23 (15.3%) children were detected with halitosis on the OT and BA tests, respectively. The sensitivity and specificity of the BA scores for the detection of halitosis were 80.76% and 98.38%, respectively. The positive and negative predictive values for BA were 91.3% and 96.06%, respectively.

CONCLUSION

In the present study involving children, who require fast, practical examinations, BA proved to be an auxiliary tool to OT for the detection of halitosis in the practice of pediatric dentistry, demonstrating high sensitivity and specificity.

Electronic Nose Analysis of Exhaled Breath Volatiles to Identify Lung Cancer Cases: A Systematic Review

The purpose of our review was to analyze evidence of the validity of electronic noses to discriminate persons with lung cancer from healthy control subjects and to advance implications for this technology in the care of people living with HIV. A computerized database search of the literature (published 1946-2018) was conducted to identify studies that used electronic nose-generated smellprints to discriminate persons with lung cancer from healthy control subjects. Fifteen articles met the sampling criteria. In 14 studies, mean sensitivity and specificity values from a single training sample were 84.1% and 80.9%, respectively. Five studies applied the prediction model obtained from the training sample to a separate validation sample; mean sensitivity was 88.2%, and mean specificity was 70.2%. Findings suggest that breath smellprints are valid markers of lung cancer and may be useful screening measures for cancer. No studies included people living with HIV; additional studies are needed to assess generalizability to this population.

Smartphone Based Human Breath Analysis from Respiratory Sounds

Human breath analysis plays important role for diagnosis and management of pulmonary diseases to guarantee normal health. The critical task is to distinguish normal and abnormal lung sounds. This research work presents a scheme for breath analysis used to detect irregular patterns occurred in respiratory cycles due to respiratory diseases. After de-noising breath segments using wavelet de-noising method, intrinsic mode functions are extracted with complete ensemble empirical mode decomposition (CEEMD). Instantaneous frequency (IF) and instantaneous envelope are extracted to get robust features for classification. The study contains breath samples captured using smartphone under natural setting. The data set contains 255 breath cycles. For cycle classification, Bag-of-word was applied to group segments based features. The support vector machine (SVM) was applied on randomly partitioned data samples. Experiments resulted with performance accuracy of (75.21%±2) for asthmatic inspiratory cycles and (75.5%±3%) for complete Respiratory Sounds (RS) cycle with diagnostic odds ratio (DOR) of 20.61% and 13.S7% respectively.

Rapid breath analysis for acute respiratory distress syndrome diagnostics using a portable two-dimensional gas chromatography device

Acute respiratory distress syndrome (ARDS) is the most severe form of acute lung injury, responsible for high mortality and long-term morbidity. As a dynamic syndrome with multiple etiologies, its timely diagnosis is difficult as is tracking the course of the syndrome. Therefore, there is a significant need for early, rapid detection and diagnosis as well as clinical trajectory monitoring of ARDS. Here, we report our work on using human breath to differentiate ARDS and non-ARDS causes of respiratory failure. A fully automated portable 2-dimensional gas chromatography device with high peak capacity (> 200 at the resolution of 1), high sensitivity (sub-ppb), and rapid analysis capability (~ 30 min) was designed and made in-house for on-site analysis of patients' breath. A total of 85 breath samples from 48 ARDS patients and controls were collected. Ninety-seven elution peaks were separated and detected in 13 min. An algorithm based on machine learning, principal component analysis (PCA), and linear discriminant analysis (LDA) was developed. As compared to the adjudications done by physicians based on the Berlin criteria, our device and algorithm achieved an overall accuracy of 87.1% with 94.1% positive predictive value and 82.4% negative predictive value. The high overall accuracy and high positive predicative value suggest that the breath analysis method can accurately diagnose ARDS. The ability to continuously and non-invasively monitor exhaled breath for early diagnosis, disease trajectory tracking, and outcome prediction monitoring of ARDS may have a significant impact on changing practice and improving patient outcomes. Graphical abstract.

Exhaled breath analysis in hepatology: State-of-the-art and perspectives

Liver disease is characterized by breath exhalation of peculiar volatile organic compounds (VOCs). Thanks to the availability of sensitive technologies for breath analysis, this empiric approach has recently gained increasing attention in the context of hepatology, following the good results obtained in other fields of medicine. After the first studies that led to the identification of selected VOCs for pathophysiological purposes, subsequent research has progressively turned towards the comprehensive assessment of exhaled breath for potential clinical application. Specific VOC patterns were found to discriminate subjects with liver cirrhosis, to rate disease severity, and, eventually, to forecast adverse clinical outcomes even beyond existing scores. Preliminary results suggest that breath analysis could be useful also for detecting and staging hepatic encephalopathy and for predicting steatohepatitis in patients with nonalcoholic fatty liver disease. However, clinical translation is still hampered by a number of methodological limitations, including the lack of standardization and the consequent poor comparability between studies and the absence of external validation of obtained results. Given the low-cost and easy execution at bedside of the new technologies (e-nose), larger and well-structured studies are expected in order to provide the adequate level of evidence to support VOC analysis in clinical practice.

Validity of a Portable Breath Analyser (AIRE) for the Assessment of Lactose Malabsorption

Hydrogen (H₂) measurement in exhaled breath is a reliable and non-invasive method to diagnose carbohydrate malabsorption. Currently, breath H₂ measurement is typically limited to clinic-based equipment. A portable breath analyser (AIRE, FoodMarble Digestive Health Limited, Dublin, Ireland) is a personalised device marketed for the detection and self-management of food intolerances, including lactose malabsorption (LM). Currently, the validity of this device for breath H₂ analysis is unknown. Individuals self-reporting dairy intolerance (six males and six females) undertook a lactose challenge and a further seven individuals (all females) underwent a milk challenge. Breath samples were collected prior to and at frequent intervals post-challenge for up to 5 h with analysis using both the AIRE and a calibrated breath hydrogen analyser (BreathTracker, QuinTron Instrument Company Inc., Milwaukee, WI, USA). A significant positive correlation (p < 0.001, r > 0.8) was demonstrated between AIRE and BreathTracker H₂ values, after both lactose and milk challenges, although 26% of the AIRE readings demonstrated the maximum score of 10.0 AU. Based on our data, the cut-off value for LM diagnosis (25 ppm H₂) using AIRE is 3.0 AU and it is effective for the identification of a response to lactose-containing foods in individuals experiencing LM, although its upper limit is only 81 ppm.

High-resolution trace gas detection by sub-Doppler noise-immune cavity-enhanced optical heterodyne molecular spectrometry: application to detection of acetylene in human breath

A sensitive high-resolution sub-Doppler detecting spectrometer, based on noise-immune cavity-enhanced optical heterodyne molecular spectrometry (NICE-OHMS), for trace gas detection of species whose transitions have severe spectral overlap with abundant concomitant species is presented. It is designed around a NICE-OHMS instrumentation utilizing balanced detection that provides shot-noise limited Doppler-broadened (Db) detection. By synchronous dithering the positions of the two cavity mirrors, the effect of residual etalons between the cavity and other surfaces in the system could be reduced. An Allan deviation of the absorption coefficient of 2.2 × 10^-13 cm^-1 at 60 s, which, for the targeted transition in C₂H₂, corresponds to a 3σ detection sensitivity of 130 ppt, is demonstrated. It is shown that despite significant spectral interference from CO₂ at the targeted transition, which precludes Db detection of C₂H₂, acetylene could be detected in exhaled breath of healthy smokers.

Sensitivity and specificity of an electronic nose in diagnosing pulmonary tuberculosis among patients with suspected tuberculosis

OBJECTIVE

To investigate the potency of a hand-held point-of-care electronic-nose to diagnose pulmonary tuberculosis (PTB) among those suspected of PTB.

METHODS

Setting: Lung clinics and Dr. Sardjito Hospital, Yogyakarta, Indonesia. Participants: patients with suspected PTB and healthy controls. Sampling: 5 minutes exhaled breath. Sputum-smear-microscopy, culture, chest-radiography, and follow-up for 1.5-2.5 years, were used to classify patients with suspected PTB as active PTB, probably active PTB, probably no PTB, and no PTB. After building a breath model based on active PTB, no PTB, and healthy controls (Calibration phase), we validated the model in all patients with suspected PTB (Validation phase). In each variable (sex, age, Body Mass Index, co-morbidities, smoking status, consumption of alcohol, use of antibiotics, flu symptoms, stress, food and drink intake), one stratum's Receiver Operating Characteristic (ROC)-curve indicating sensitivity and specificity of the breath test was compared with another stratum's ROC-curve. Differences between Area-under-the-Curve between strata (p<0.05) indicated an association between the variable and sensitivity-specificity of the breath test. Statistical analysis was performed using STATA/SE 15.

RESULTS

Of 400 enrolled participants, 73 were excluded due to extra-pulmonary TB, incomplete data, previous TB, and cancer. Calibration phase involved 182 subjects, and the result was validated in 287 subjects. Sensitivity was 85% (95%CI: 75-92%) and 78% (95%CI: 70-85%), specificity was 55% (95%CI: 44-65%) and 42% (95%CI: 34-50%), in calibration and validation phases, respectively. Test sensitivity and specificity were lower in men.

CONCLUSION

The electronic-nose showed modest sensitivity and low specificity among patients with suspected PTB. To improve the sensitivity, a larger calibration group needs to be involved. With its portable form, it could be used for TB screening in remote rural areas and health care settings.

Breath Analysis Using eNose and Ion Mobility Technology to Diagnose Inflammatory Bowel Disease-A Pilot Study

Early diagnosis of inflammatory bowel disease (IBD), including Crohn's disease (CD) and ulcerative colitis (UC), remains a clinical challenge with current tests being invasive and costly. The analysis of volatile organic compounds (VOCs) in exhaled breath and biomarkers in stool (faecal calprotectin (FCP)) show increasing potential as non-invasive diagnostic tools. The aim of this pilot study is to evaluate the efficacy of breath analysis and determine if FCP can be used as an additional non-invasive parameter to supplement breath results, for the diagnosis of IBD. Thirty-nine subjects were recruited (14 CD, 16 UC, 9 controls). Breath samples were analysed using an in-house built electronic nose (Wolf eNose) and commercial gas chromatograph-ion mobility spectrometer (G.A.S. BreathSpec GC-IMS). Both technologies could consistently separate IBD and controls [AUC ± 95%, sensitivity, specificity], eNose: [0.81, 0.67, 0.89]; GC-IMS: [0.93, 0.87, 0.89]. Furthermore, we could separate CD from UC, eNose: [0.88, 0.71, 0.88]; GC-IMS: [0.71, 0.86, 0.62]. Including FCP did not improve distinction between CD vs UC; eNose: [0.74, 1.00, 0.56], but rather, improved separation of CD vs controls and UC vs controls; eNose: [0.77, 0.55, 1.00] and [0.72, 0.89, 0.67] without FCP, [0.81, 0.73, 0.78] and [0.90, 1.00, 0.78] with FCP, respectively. These results confirm the utility of breath analysis to distinguish between IBD-related diagnostic groups. FCP does not add significant diagnostic value to breath analysis within this study.

Nanostructured Gas Sensors for Medical and Health Applications: Low to High Dimensional Materials

Human breath has long been known as a system that can be used to diagnose diseases. With advancements in modern nanotechnology, gas sensors can now diagnose, predict, and monitor a wide range of diseases from human breath. From cancer to diabetes, the need to treat at the earliest stages of a disease to both increase patient outcomes and decrease treatment costs is vital. Therefore, it is the promising candidate of rapid and non-invasive human breath gas sensors over traditional methods that will fulfill this need. In this review, we focus on the nano-dimensional design of current state-of-the-art gas sensors, which have achieved records in selectivity, specificity, and sensitivity. We highlight the methods of fabrication for these devices and relate their nano-dimensional materials to their record performance to provide a pathway for the gas sensors that will supersede.

Single Exhale Biomarker Breathalyzer

A single exhale breathalyzer comprises a gas sensor that satisfies the following stringent conditions: high sensitivity to the target gas, high selectivity, stable response over extended period of time and fast response. Breathalyzer implementation includes a front-end circuit matching the sensitivity of the sensor that provides the readout of the sensor signal. We present here the characterization study of the response stability and response time of a selective Nitric Oxide (NO) sensor using designed data acquisition system that also serves as a foundation for the design of wireless handheld prototype. The experimental results with the described sensor and data acquisition system demonstrate stable response to NO concentration of 200 ppb over the period of two weeks. The experiments with different injection and retraction times of the sensor exposure to constant NO concentration show a fast response time of the sensor (on the order of 15 s) and the adequate recovery time (on the order of 3 min) demonstrating suitability for the single exhale breathalyzer.

Breath water-based doubly labelled water method for the noninvasive determination of CO2 production and energy expenditure in mice

We explored a novel doubly labelled water (DLW) method based on breath water (BW-DLW) in mice to determine whole body CO₂ production and energy expenditure noninvasively. The BW-DLW method was compared to the DLW based on blood plasma. Mice (n = 11, 43.5 ± 4.6 g body mass (BM)) were administered orally a single bolus of doubly labelled water (1.2 g H₂¹⁸O kg BM^-1 and 0.4 g ²H₂O kg BM^-1, 99 atom% (AP) ¹⁸O or ²H). To sample breath water, the mice were placed into a respiration vessel. The exhaled water vapour was condensed in a cold-trap. The isotope enrichments of breath water were compared with plasma samples. The ²H/¹H and ¹⁸O/¹⁶O isotope ratios were measured by means of isotope ratio mass spectrometry. The CO₂ production (RCO₂) was calculated from the ²H and ¹⁸O enrichments in breath water and plasma over 5 days. The isotope enrichments of breath water vs. plasma were correlated (R² = 0.89 for ²H and 0.95 for ¹⁸O) linearly. The RCO₂ determined based on breath water and plasma was not different (113.2 ± 12.7 vs. 111.4 ± 11.0 mmol d^-1), respectively. In conclusion, the novel BW-DLW method is appropriate to obtain reliable estimates of RCO₂ avoiding blood sampling.

Exhaled-breath Testing for Prostate Cancer Based on Volatile Organic Compound Profiling Using an Electronic Nose Device (Aeonose™): A Preliminary Report

BACKGROUND

Prostate biopsy, an invasive examination, is the gold standard for diagnosing prostate cancer (PCa). There is a need for a novel noninvasive diagnostic tool that achieves a significantly high pretest probability for PCa, reducing unnecessary biopsy numbers. Recent studies have shown that volatile organic compounds (VOCs) in exhaled breath can be used to detect different types of cancers via training of an artificial neural network (ANN).

OBJECTIVE

To determine whether exhaled-breath analysis using a handheld electronic nose device can be used to discriminate between VOC patterns between PCa patients and healthy individuals.

DESIGN, SETTING, AND PARTICIPANTS

This prospective pilot study was conducted in the outpatient urology clinic of the Maastricht University Medical Center, the Netherlands. Patients with histologically proven PCa were already included before initial biopsy or during follow-up, with no prior treatment for their PCa. Urological patients with negative biopsies in the past year or patients with prostate enlargement (PE) with low or stable serum prostate-specific antigen were used as controls. Exhaled breath was probed from 85 patients: 32 with PCa and 53 controls (30 having negative biopsies and 23 PE).

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

Patient characteristics were statistically analyzed using independent sample t test and Pearson's chi-square test. Data analysis was performed by Aethena software after data compression using the TUCKER3 algorithm. ANN models were trained and evaluated using the leave-10%-out cross-validation method.

RESULTS AND LIMITATIONS

Our trained ANN showed an accuracy of 0.75, with an area under the curve of 0.79 with sensitivity and specificity of 0.84 (95% confidence interval [CI] 0.66-0.94) and 0.70 (95% CI 0.55-0.81) respectively, comparing PCa with control individuals. The negative predictive value was found to be 0.88. The main limitation is the relatively small sample size.

CONCLUSIONS

Our findings imply that the Aeonose allows us to discriminate between patients with untreated, histologically proven primary PCa and control patients based on exhaled-breath analysis.

PATIENT SUMMARY

We explored the possibility of exhaled-breath analysis using an electronic nose, to be used as a noninvasive tool in clinical practice, as a pretest for diagnosing prostate cancer. We found that the electronic nose was able to discriminate between prostate cancer patients and control individuals.

Guiding Ketogenic Diet with Breath Acetone Sensors

Ketogenic diet (KD; high fat, low carb) is a standard treatment for obesity, neurological diseases (e.g., refractory epilepsy) and a promising method for athletes to improve their endurance performance. Therein, the level of ketosis must be regulated tightly to ensure an effective therapy. Here, we introduce a compact and inexpensive breath sensor to monitor ketosis online and non-invasively. The sensor consists of Si-doped WO₃ nanoparticles that detect breath acetone selectively with non-linear response characteristics in the relevant range of 1 to 66 ppm, as identified by mass spectrometry. When tested on eleven subjects (five women and six men) undergoing a 36-h KD based on the Johns Hopkins protocol, this sensor clearly recognizes the onset and progression of ketosis. This is in good agreement to capillary blood β-hydroxybutyrate (BOHB) measurements. Despite similar dieting conditions, strong inter-subject differences in ketosis dynamics were observed and correctly identified by the sensor. These even included breath acetone patterns that could be linked to low tolerance to that diet. As a result, this portable breath sensor represents an easily applicable and reliable technology to monitor KD, possibly during medical treatment of epilepsy and weight loss.

VOC breath profile in spontaneously breathing awake swine during Influenza A infection

Influenza is one of the most common causes of virus diseases worldwide. Virus detection requires determination of Influenza RNA in the upper respiratory tract. Efficient screening is not possible in this way. Analysis of volatile organic compounds (VOCs) in breath holds promise for non-invasive and fast monitoring of disease progression. Breath VOC profiles of 14 (3 controls and 11 infected animals) swine were repeatedly analyzed during a complete infection cycle of Influenza A under high safety conditions. Breath VOCs were pre-concentrated by means of needle trap micro-extraction and analysed by gas chromatography mass spectrometry before infection, during virus presence in the nasal cavity, and after recovery. Six VOCs could be related to disease progression: acetaldehyde, propanal, n-propyl acetate, methyl methacrylate, styrene and 1,1-dipropoxypropane. As early as on day four after inoculation, when animals were tested positive for Influenza A, differentiation between control and infected animals was possible. VOC based information on virus infection could enable early detection of Influenza A. As VOC analysis is completely non-invasive it has potential for large scale screening purposes. In a perspective, breath analysis may offer a novel tool for Influenza monitoring in human medicine, animal health control or border protection.

Evolution of clinical and environmental health applications of exhaled breath research: Review of methods and instrumentation for gas-phase, condensate, and aerosols

Human breath, along with urine and blood, has long been one of the three major biological media for assessing human health and environmental exposure. In fact, the detection of odor on human breath, as described by Hippocrates in 400 BC, is considered the first analytical health assessment tool. Although less common in comparison to contemporary bio-fluids analyses, breath has become an attractive diagnostic medium as sampling is non-invasive, unlimited in timing and volume, and does not require clinical personnel. Exhaled breath, exhaled breath condensate (EBC), and exhaled breath aerosol (EBA) are different types of breath matrices used to assess human health and disease state. Over the past 20 years, breath research has made many advances in assessing health state, overcoming many of its initial challenges related to sampling and analysis. The wide variety of sampling techniques and collection devices that have been developed for these media are discussed herein. The different types of sensors and mass spectrometry instruments currently available for breath analysis are evaluated as well as emerging breath research topics, such as cytokines, security and airport surveillance, cellular respiration, and canine olfaction.

Miniaturization of breath sampling with silicon chip: application to volatile tobacco markers tracking

This work presents the performances of silicon micro-preconcentrators chips for breath sampling. The silicon chips were coupled to a handheld battery powered system for breath sampling and direct injection in a laboratory gas chromatography mass spectrometry system through thermal desorption (TD). Performances of micro-preconcentrators were first compared to commercial TD for benzene trapping. Similar chromatographic peaks after gas chromatographic separation were observed while the volume of sample needed was reduced by a factor of 5. Repeatability and day to day variability of the micro-preconcentrators were then studied for a 500 ppb synthetic model mixture injected three times a day four days in a row: 8% and 12% were measured respectively. Micro-preconcentrator to micro-preconcentrator variability was not significant compared to day to day variability. In addition, micro-preconcentrators were tested for breath samples collected in Tedlar® bags. Three analyses of the same breath sample displayed relative standard deviations values below 16% for eight of the ten most intense peaks. Finally, the performances of micro-preconcentrators for breath sampling on a single expiration were illustrated with the example of volatile tobacco markers tracking. The signals of three smoking markers in breath, benzene, 2,5-dimethylfuran, and toluene were studied. Concentrations of benzene and toluene were found to be 10 to 100 higher in the breath of smokers. 2,5-dimethylfuran was only found in the breath of smokers. The elimination kinetics of the markers were followed as well during 4 h: a fast decrease of the signal of the three markers in breath was observed 20 min after smoking in good agreement with what is described in the literature. Those results demonstrate the efficiency of silicon chips for breath sampling, compared to the state of the art techniques. Thanks to miniaturization and lower sample volumes needed, micro-preconcentrators could be in the future a key technology towards portable breath sampling and analysis.

Congruent validity and inter-day reliability of two breath by breath metabolic carts to measure resting metabolic rate in young adults

BACKGROUND & AIMS

Achieving high inter-day reliability is a key factor to analyze the magnitude of change in RMR, for instance after an intervention. The aims of this study were: i) to determine the congruent validity of RMR and respiratory quotient (RQ) with two breath by breath commercially available metabolic carts [CCM Express (CCM) and Ultima CardiO2 (MGU)]; and ii) to analyze the inter-day reliability of RMR and RQ measurements.

METHODS & RESULTS

Seventeen young adults participated in the study. RMR measurements were performed during two consecutive 30-min periods, on two consecutive days with both metabolic carts. The 5-min period that met the steady state criteria [Coefficient of variance (CV) < 10% for VO₂, VCO₂, and VE, and CV<5% for RQ] and with the lowest CV average was included in further analysis. RMR values were higher with the MGU than with the CCM on both days (two-way ANOVA, P = 0.021), however, no differences were found on RQ values obtained by both metabolic carts (P = 0.642). Absolute inter-day RMR differences obtained with the MGU were higher than those obtained with the CCM (219 ± 185 vs. 158 ± 154 kcal/day, respectively, P = 0.002; 18.3 ± 17.2% vs. 13.5 ± 15.3%, respectively, P = 0.046). We observed a significant positive association of absolute inter-day differences in RMR obtained with both metabolic carts (β = 0.717; R² = 0.743; P < 0.001).

CONCLUSIONS

The CCM metabolic cart provides lower RMR values and seems more reliable than the MGU in our sample of young adults. Our findings also suggest that a great part of inter-day variability is explained by the individuals.

The Smell of Hypoxia: using an electronic nose at altitude and proof of concept of its role in the prediction and diagnosis of acute mountain sickness

Electronic nose (e-nose) devices may be used to identify volatile organic compounds (VOCs) in exhaled breath. VOCs generated via metabolic processes are candidate biomarkers of (patho)physiological pathways. We explored the feasibility of using an e-nose to generate human "breathprints" at high altitude. Furthermore, we explored the hypothesis that pathophysiological processes involved in the development of acute mountain sickness (AMS) would manifest as altered VOC profiles. Breath analysis was performed on Sherpa and lowlander trekkers at high altitude (3500 m). The Lake Louise Scoring (LLS) system was used to diagnose AMS. Raw data were reduced by principal component (PC) analysis (PCA). Cross validated linear discriminant analysis (CV-LDA) and receiver-operating characteristic area under curve (ROC-AUC) assessed discriminative function. Breathprints suitable for analysis were obtained from 58% (37/64) of samples. PCA showed significant differences between breathprints from participants with, and without, AMS; CV-LDA showed correct classification of 83.8%, ROC-AUC 0.86; PC 1 correlated with AMS severity. There were significant differences between breathprints of participants who remained AMS negative and those whom later developed AMS (CV-LDA 68.8%, ROC-AUC 0.76). PCA demonstrated discrimination between Sherpas and lowlanders (CV-LDA 89.2%, ROC-AUC 0.936). This study demonstrated the feasibility of breath analysis for VOCs using an e-nose at high altitude. Furthermore, it provided proof-of-concept data supporting e-nose utility as an objective tool in the prediction and diagnosis of AMS. E-nose technology may have substantial utility both in altitude medicine and under other circumstances where (mal)adaptation to hypoxia may be important (e.g., critically ill patients).

Automated in Vivo Nanosensing of Breath-Borne Protein Biomarkers

Toxicology and bedside medical condition monitoring is often desired to be both ultrasensitive and noninvasive. However, current biomarker analyses for these purposes are mostly offline and fail to detect low marker quantities. Here, we report a system called dLABer (detection of living animal's exhaled breath biomarker) that integrates living rats, breath sampling, microfluidics, and biosensors for the automated tracking of breath-borne biomarkers. Our data show that dLABer could selectively detect (online) and report differences (of up to 10³-fold) in the levels of inflammation agent interleukin-6 (IL-6) exhaled by rats injected with different ambient particulate matter (PM). The dLABer system was further shown to have an up to 10⁴ higher signal-to-noise ratio than that of the enzyme-linked immunosorbent assay (ELISA) when analyzing the same breath samples. In addition, both blood-borne IL-6 levels analyzed via ELISA in rats injected with different PM extracts and PM toxicity determined by a dithiothreitol (DTT) assay agreed well with those determined by the dLABer system. Video recordings further verified that rats exposed to PM with higher toxicity (according to a DTT assay and as revealed by dLABer) appeared to be less physically active. All the data presented here suggest that the dLABer system is capable of real-time, noninvasive monitoring of breath-borne biomarkers with ultrasensitivity. The dLABer system is expected to revolutionize pollutant health effect studies and bedside disease diagnosis as well as physiological condition monitoring at the single-protein level.

Sensors for Enhanced Detection of Acetone as a Potential Tool for Noninvasive Diabetes Monitoring

Measurement of blood-borne volatile organic compounds (VOCs) occurring in human exhaled breath as a result of metabolic changes or pathological disorders is a promising tool for noninvasive medical diagnosis, such as exhaled acetone measurements in terms of diabetes monitoring. The conventional methods for exhaled breath analysis are based on spectrometry techniques, however, the development of gas sensors has made them more and more attractive from a medical point of view. This review focuses on the latest achievements in gas sensors for exhaled acetone detection. Several different methods and techniques are presented and discussed as well.

Scrutiny of 13C-phenylalanine breath test reproducibility

We evaluated the reproducibility of the ¹³C-phenylalanine breath test (¹³C-PheBT). On three separate days, 21 healthy volunteers (11 F and 10 M) underwent ¹³C-PheBT with 100 mg l-[1-¹³C]phenylalanine taken orally. Short-term reproducibility was evaluated with paired examinations taken 3 days apart; paired examinations separated by 23 days (median) served for the medium-term reproducibility assessment. Expiratory air was sampled at 19 points throughout 3 h. Determined limited reproducibility of the ¹³C-PheBT must be taken into consideration while interpreting the results of this diagnostic tool. The results of this study imply the following conclusions: (i) From among the three parameters examined, the cumulative ¹³C recovery area under the curve (AUC) offers much better reproducibility than the maximum momentary ¹³C recovery in the expiratory air (D_max) or the time to reach the maximum momentary ¹³C recovery (T_max) (ii) Collection of the breath air samples for 2 h results in a much better reproducibility of AUC, than for 1 h only; (iii) Reproducibility of ¹³C-PheBT is affected neither by the duration of the time gap between repeated tests nor by gender; (iv) Comparison with data obtained formerly reveals that reproducibility of the ¹³C-PheBT is worse than either that of of the ¹³C-methacetin (¹³C-MBT) or the ¹³C-alpha-ketoisocaproic acic (¹³C-KICA-BT) breath tests. This finding will have to be taken into consideration while interpreting the results of this diagnostic tool.

Electret filter collects more exhaled albumin than glass condenser: A method comparison based on human study

In recent years, noninvasive diagnosis based on biomarkers in exhaled breath has been extensively studied. The procedure of biomarker collection is a key step. However, the traditional condenser method has low efficacy in collecting nonvolatile compounds especially the protein biomarkers in breath. To solve this deficiency, here we propose an electret filter method.Exhaled breath of 6 volunteers was collected with a glass condenser and an electret filter. The amount of albumin was analyzed. Furthermore, the difference of exhaled albumin between smokers and nonsmokers was evaluated.The electret filter method collected more albumin than the glass condenser method at the same breath volume level (P < .01). Smokers exhaling more albumin than nonsmokers were also observed (P < .01).The electret filter is capable of collecting proteins more effectively than the condenser method. In addition, smokers tend to exhale more albumin than nonsmokers.

Air sampling unit for breath analyzers

The paper presents a portable breath sampling unit (BSU) for human breath analyzers. The developed unit can be used to probe air from the upper airway and alveolar for clinical and science studies. The BSU is able to operate as a patient interface device for most types of breath analyzers. Its main task is to separate and to collect the selected phases of the exhaled air. To monitor the so-called I, II, or III phase and to identify the airflow from the upper and lower parts of the human respiratory system, the unit performs measurements of the exhaled CO₂ (ECO₂) in the concentration range of 0%-20% (0-150 mm Hg). It can work in both on-line and off-line modes according to American Thoracic Society/European Respiratory Society standards. A Tedlar bag with a volume of 5 dm³ is mounted as a BSU sample container. This volume allows us to collect ca. 1-25 selected breath phases. At the user panel, each step of the unit operation is visualized by LED indicators. This helps us to regulate the natural breathing cycle of the patient. There is also an operator's panel to ensure monitoring and configuration setup of the unit parameters. The operation of the breath sampling unit was preliminarily verified using the gas chromatography/mass spectrometry (GC/MS) laboratory setup. At this setup, volatile organic compounds were extracted by solid phase microextraction. The tests were performed by the comparison of GC/MS signals from both exhaled nitric oxide and isoprene analyses for three breath phases. The functionality of the unit was proven because there was an observed increase in the signal level in the case of the III phase (approximately 40%). The described work made it possible to construct a prototype of a very efficient breath sampling unit dedicated to breath sample analyzers.

A detailed comparison of analysis processes for MCC-IMS data in disease classification-Automated methods can replace manual peak annotations

Motivation

Disease classification from molecular measurements typically requires an analysis pipeline from raw noisy measurements to final classification results. Multi capillary column—ion mobility spectrometry (MCC-IMS) is a promising technology for the detection of volatile organic compounds in the air of exhaled breath. From raw measurements, the peak regions representing the compounds have to be identified, quantified, and clustered across different experiments. Currently, several steps of this analysis process require manual intervention of human experts. Our goal is to identify a fully automatic pipeline that yields competitive disease classification results compared to an established but subjective and tedious semi-manual process.

Method

We combine a large number of modern methods for peak detection, peak clustering, and multivariate classification into analysis pipelines for raw MCC-IMS data. We evaluate all combinations on three different real datasets in an unbiased cross-validation setting. We determine which specific algorithmic combinations lead to high AUC values in disease classifications across the different medical application scenarios.

Results

The best fully automated analysis process achieves even better classification results than the established manual process. The best algorithms for the three analysis steps are (i) SGLTR (Savitzky-Golay Laplace-operator filter thresholding regions) and LM (Local Maxima) for automated peak identification, (ii) EM clustering (Expectation Maximization) and DBSCAN (Density-Based Spatial Clustering of Applications with Noise) for the clustering step and (iii) RF (Random Forest) for multivariate classification. Thus, automated methods can replace the manual steps in the analysis process to enable an unbiased high throughput use of the technology.

Passive in-vehicle driver breath alcohol detection using advanced sensor signal acquisition and fusion

OBJECTIVE

The research objective of the present investigation is to demonstrate the present status of passive in-vehicle driver breath alcohol detection and highlight the necessary conditions for large-scale implementation of such a system. Completely passive detection has remained a challenge mainly because of the requirements on signal resolution combined with the constraints of vehicle integration. The work is part of the Driver Alcohol Detection System for Safety (DADSS) program aiming at massive deployment of alcohol sensing systems that could potentially save thousands of American lives annually.

METHOD

The work reported here builds on earlier investigations, in which it has been shown that detection of alcohol vapor in the proximity of a human subject may be traced to that subject by means of simultaneous recording of carbon dioxide (CO₂) at the same location. Sensors based on infrared spectroscopy were developed to detect and quantify low concentrations of alcohol and CO₂. In the present investigation, alcohol and CO₂ were recorded at various locations in a vehicle cabin while human subjects were performing normal in-step procedures and driving preparations. A video camera directed to the driver position was recording images of the driver's upper body parts, including the face, and the images were analyzed with respect to features of significance to the breathing behavior and breath detection, such as mouth opening and head direction.

RESULTS

Improvement of the sensor system with respect to signal resolution including algorithm and software development, and fusion of the sensor and camera signals was successfully implemented and tested before starting the human study. In addition, experimental tests and simulations were performed with the purpose of connecting human subject data with repeatable experimental conditions. The results include occurrence statistics of detected breaths by signal peaks of CO₂ and alcohol. From the statistical data, the accuracy of breath alcohol estimation and timing related to initial driver routines (door opening, taking a seat, door closure, buckling up, etc.) can be estimated. The investigation confirmed the feasibility of passive driver breath alcohol detection using our present system. Trade-offs between timing and sensor signal resolution requirements will become critical. Further improvement of sensor resolution and system ruggedness is required before the results can be industrialized.

CONCLUSIONS

It is concluded that a further important step toward completely passive detection of driver breath alcohol has been taken. If required, the sniffer function with alcohol detection capability can be combined with a subsequent highly accurate breath test to confirm the driver's legal status using the same sensor device. The study is relevant to crash avoidance, in particular driver monitoring systems and driver-vehicle interface design.

Real-Time Quantitative Analysis of Valproic Acid in Exhaled Breath by Low Temperature Plasma Ionization Mass Spectrometry

Real-time analysis of exhaled human breath is a rapidly growing field in analytical science and has great potential for rapid and noninvasive clinical diagnosis and drug monitoring. In the present study, an LTP-MS method was developed for real-time, in-vivo and quantitative analysis of γ-valprolactone, a metabolite of valproic acid (VPA), in exhaled breath without any sample pretreatment. In particular, the effect of working conditions and geometry of the LTP source on the ions of interest, protonated molecular ion at m/z 143 and ammonium adduct ion at m/z 160, were systematically characterized. Tandem mass spectrometry (MS/MS) with collision-induced dissociation (CID) was carried out in order to identify γ-valprolactone molecular ions (m/z 143), and the key fragment ion (m/z 97) was used for quantitation. In addition, the fragmentation of ammonium adduct ions to protonated molecular ions was performed in-source to improve the signal-to-noise ratio. At optimum conditions, signal reproducibility with an RSD of 8% was achieved. The concentration of γ-valprolactone in exhaled breath was determined for the first time to be 4.83 (±0.32) ng/L by using standard addition method. Also, a calibration curve was obtained with a linear range from 0.7 to 22.5 ng/L, and the limit of detection was 0.18 ng/L for γ-valprolactone in standard gas samples. Our results show that LTP-MS is a powerful analytical platform with high sensitivity for quantitative analysis of volatile organic compounds in human breath, and can have potential applications in pharmacokinetics or for patient monitoring and treatment. Graphical Abstract ᅟ.

Halitosis: measurement in daily practice

Bad breath is a widespread but still largely taboo problem. The dentist is often the first point of contact for affected patients. Initially, the diagnosis and quantification of halitosis provides objective evidence and helps to find the underlying causes, but it is equally important for monitoring the treatment progress. Most often, halitosis is caused intraorally, thus the dentist will also be responsible for initiating an appropriate treatment. Apart from the simple organoleptic examination without the need for additional instruments, several devices for the measurement of halitosis are available which provide a differentiated analysis of the exhaled air by determining and quantifying the detected volatile sulfur compounds.

Using a Sniff Controller to Self-Trigger Abdominal Functional Electrical Stimulation for Assisted Coughing Following Cervical Spinal Cord Lesions

Individuals with cervical spinal cord lesions (SCLs) typically depend on caregivers to manually assist in coughing by pressing against their abdominal wall. Coughing can also be assisted by functional electric stimulation (FES) applied to abdominal muscles via surface electrodes. Efficacy of FES, however, depends on precise temporal synchronization. The sniff controller is a trigger that enables paralyzed individuals to precisely control external devices through alterations in nasal airflow. We hypothesized that FES self-triggering by sniff controller may allow for effective cough timing. After optimizing parameters in 16 able-bodied subjects, we measured peak expiratory flow (PEF) in 14 subjects with SCL who coughed with or without assistance. Assistance was either manual assistance of a caregiver, caregiver activated FES, button self-activated FES (for SCL participants who could press a button), or sniff-controlled self-activated FES. We found that all assisted methods provided equally effective improvements, increasing PEF on average by 25 ± 27% (F[4,52] = 7.99, p = 0.00004 ). There was no difference in efficacy between methods of assistance ( F[3,39] = 0.41, p = 0.75 ). Notably, sniff-controlled FES was the only method of those tested that can be activated by all paralyzed patients alone. This provides for added independence that is a critical factor in quality of life following SCL.

Exhaled air analysis using wideband wave number tuning range infrared laser photoacoustic spectroscopy

The infrared laser photoacoustic spectroscopy (LPAS) and the pattern-recognition-based approach for noninvasive express diagnostics of pulmonary diseases on the basis of absorption spectra analysis of the patient’s exhaled air are presented. The study involved lung cancer patients ( N = 9 ), patients with chronic obstructive pulmonary disease ( N = 12 ), and a control group of healthy, nonsmoking volunteers ( N = 11 ). The analysis of the measured absorption spectra was based at first on reduction of the dimension of the feature space using principal component analysis; thereafter, the dichotomous classification was carried out using the support vector machine. The gas chromatography–mass spectrometry method (GC–MS) was used as the reference. The estimated mean value of the sensitivity of exhaled air sample analysis by the LPAS in dichotomous classification was not less than 90% and specificity was not less than 69%; the analogous results of analysis by GC–MS were 68% and 60%, respectively. Also, the approach to differential diagnostics based on the set of SVM classifiers usage is presented.

["HELICARB" - the first Russian breath test kit with 99 % C-urea for Helicobacter pylori: from idea to registration]

The present study was aimed to develop and introduce in medical practice the first Russian kit for the C-urea breath test of Helicobacter pylori. The newly created kit was given the commercial name «HELICARB» and successfully passed technical, toxicological, clinical, and laboratory testing. The optimal dose of 13C-urea was determined and various devices needed to perform the test were compared. The results were approved by the Federal Service for Supervision in the health sector Roszdravnadzor) that issued the Registration certificate № RZN 2016/3773 (order № 1641 of 02.29.2016), which gives the right to manufacture and use the «HELICARB» test kit at the territory of the Russian Federation.