Human exhaled breath analysis

Aggregation-Induced Emission Luminogen: Role in Biopsy for Precision Medicine

Biopsy, including tissue and liquid biopsy, offers comprehensive and real-time physiological and pathological information for disease detection, diagnosis, and monitoring. Fluorescent probes are frequently selected to obtain adequate information on pathological processes in a rapid and minimally invasive manner based on their advantages for biopsy. However, conventional fluorescent probes have been found to show aggregation-caused quenching (ACQ) properties, impeding greater progresses in this area. Since the discovery of aggregation-induced emission luminogen (AIEgen) have promoted rapid advancements in molecular bionanomaterials owing to their unique properties, including high quantum yield (QY) and signal-to-noise ratio (SNR), etc. This review seeks to present the latest advances in AIEgen-based biofluorescent probes for biopsy in real or artificial samples, and also the key properties of these AIE probes. This review is divided into: (i) tissue biopsy based on smart AIEgens, (ii) blood sample biopsy based on smart AIEgens, (iii) urine sample biopsy based on smart AIEgens, (iv) saliva sample biopsy based on smart AIEgens, (v) biopsy of other liquid samples based on smart AIEgens, and (vi) perspectives and conclusion. This review could provide additional guidance to motivate interest and bolster more innovative ideas for further exploring the applications of various smart AIEgens in precision medicine.

Precision detection of select human lung cancer biomarkers and cell lines using honeybee olfactory neural circuitry as a novel gas sensor

Human breath contains biomarkers (odorants) that can be targeted for early disease detection. It is well known that honeybees have a keen sense of smell and can detect a wide variety of odors at low concentrations. Here, we employ honeybee olfactory neuronal circuitry to classify human lung cancer volatile biomarkers at different concentrations and their mixtures at concentration ranges relevant to biomarkers in human breath from parts-per-billion to parts-per-trillion. We also validated this brain-based sensing technology by detecting human non-small cell lung cancer (NSCLC) and small cell lung cancer (SCLC) cell lines using the 'smell' of the cell cultures. Different lung cancer biomarkers evoked distinct spiking response dynamics in the honeybee antennal lobe neurons indicating that those neurons encoded biomarker-specific information. By investigating lung cancer biomarker-evoked population neuronal responses from the honeybee antennal lobe, we classified individual human lung cancer biomarkers successfully (88% success rate). When we mixed six lung cancer biomarkers at different concentrations to create 'synthetic lung cancer' vs. 'synthetic healthy' human breath, honeybee population neuronal responses were able to classify those complex breath mixtures reliably with exceedingly high accuracy (93-100% success rate with a leave-one-trial-out classification method). Finally, we employed this sensor to detect human NSCLC and SCLC cell lines and we demonstrated that honeybee brain olfactory neurons could distinguish between lung cancer vs. healthy cell lines and could differentiate between different NSCLC and SCLC cell lines successfully (82% classification success rate). These results indicate that the honeybee olfactory system can be used as a sensitive biological gas sensor to detect human lung cancer.

Deep-Learning-Based Blood Glucose Detection Device Using Acetone Exhaled Breath Sensing Features of α-Fe2O3-MWCNT Nanocomposites

Owing to the correlation between acetone in human's exhaled breath (EB) and blood glucose, the development of EB acetone gas-sensing devices is important for early diagnosis of diabetes diseases. In this article, a noninvasive blood glucose detection device through acetone sensing in EB, based on an α-Fe2O3-multiwalled carbon nanotube (MWCNT) nanocomposite, was successfully developed. Different amounts of α-Fe2O3 were added to the MWCNTs by a simple solution method. The optimized acetone gas sensor showed a response of 5.15 to 10 ppm acetone gas at 200 °C. Also, the fabricated sensor showed very good sensing properties even in an atmosphere with high relative humidity. Since the EB has high humidity, the proposed sensor is a promising device to exactly detect the amount of acetone in EB with high humidity. The sensor was powered by a 3200 mAh battery with the possibility of charging using mains electricity. To increase the reliability and calibration of the sensing device, a practical test was taken to detect acetone EB from 50 volunteers, and a deep learning algorithm (DLA) was used to detect the effect of various factors on the amount of acetone in each person's acetone EB. The proposed device with ±15 errors had almost 85% correct responses. Also, the proposed device had excellent response, short response time, good selectivity, and good repeatability, leading it to be a suitable candidate for noninvasive blood glucose sensing.

Exhaled breath analysis in adult patients with cystic fibrosis by real-time proton mass spectrometry

BACKGROUND

Proton-transfer reaction time-of-flight mass spectrometry (PTR-TOF-MS) is a promising tool for a rapid online determination of exhaled volatile organic compounds (eVOCs) profiles in patients with cystic fibrosis (CF).

OBJECTIVE

To detect VOC breath signatures specific to adult patients with CF compared with controls using PTR-TOF-MS.

METHODS

102 CF patients (54 M/48, mean age 25.6 ± 7.8 yrs) and 97 healthy controls (56 M/41F, mean age 25.8 ± 6.0 yrs) were examined. Samples from normal quiet breathing and forced expiratory maneuvers were analyzed with PTR-TOF-MS (Ionicon, Austria) to obtain VOC profiles listed as ions at various mass-to-charge ratios (m/z).

RESULTS

PTR-TOF-MS analysis was able to detect 167 features in exhaled breath from CF patients and healthy controls. According to cluster analysis and LASSO regression, patients with CF and controls were separated. The most significant VOCs for CF were indole, phenol, dimethyl sulfide, and not indicated: m/z = 297.0720 ([C12H13N2O7 and C17H13O5]H + ), m/z = 281.0534 ([C19H7NO2, C12H11NO7 and C16H9O5]H + ) during five-fold cross-validation both in forced expiratory maneuver and in normal quiet breathing.

CONCLUSION

PTR-TOF-MS is a promising method for determining the molecular composition of exhaled air specific to CF.

New perspectives on 'Breathomics': metabolomic profiling of non-volatile organic compounds in exhaled breath using DI-FT-ICR-MS

Breath analysis offers tremendous potential for diagnostic approaches, since it allows for easy and non-invasive sample collection. "Breathomics" as one major research field comprehensively analyses the metabolomic profile of exhaled breath providing insights into various (patho)physiological processes. Recent research, however, primarily focuses on volatile compounds. This is the first study that evaluates the non-volatile organic compounds (nVOCs) in breath following an untargeted metabolomic approach. Herein, we developed an innovative method utilizing a filter-based device for metabolite extraction. Breath samples of 101 healthy volunteers (female n = 50) were analysed using DI-FT-ICR-MS and biostatistically evaluated. The characterisation of the non-volatile core breathome identified more than 1100 metabolites including various amino acids, organic and fatty acids and conjugates thereof, carbohydrates as well as diverse hydrophilic and lipophilic nVOCs. The data shows gender-specific differences in metabolic patterns with 570 significant metabolites. Male and female metabolomic profiles of breath were distinguished by a random forest approach with an out-of-bag error of 0.0099. Additionally, the study examines how oral contraceptives and various lifestyle factors, like alcohol consumption, affect the non-volatile breathome. In conclusion, the successful application of a filter-based device combined with metabolomics-analyses delineate a non-volatile breathprint laying the foundation for discovering clinical biomarkers in exhaled breath.

Comb spectroscopy of CO2 produced from microbial metabolism

We have developed a direct frequency comb spectroscopy instrument, which we have tested on Saccharomyces cerevisiae (baker's yeast) by measuring its CO2 output and production rate as we varied the environmental conditions, including the amount and type of feed sugar, the temperature, and the amount of yeast. By feeding isotopically-enhanced sugar to the yeast, we demonstrate the capability of our device to differentiate between two isotopologues of CO2, with a concentration measurement precision of 260 ppm for 12C16O2 and 175 ppm for 13C16O2. We also demonstrate the ability of our spectrometer to measure the proportion of carbon in the feed sugar converted to CO2, and estimate the amount incorporated into the yeast biomass.

Disease diagnosis and severity classification in pulmonary fibrosis using carbonyl volatile organic compounds in exhaled breath

BACKGROUND

Pathophysiological conditions underlying pulmonary fibrosis remain poorly understood. Exhaled breath volatile organic compounds (VOCs) have shown promise for lung disease diagnosis and classification. In particular, carbonyls are a byproduct of oxidative stress, associated with fibrosis in the lungs. To explore the potential of exhaled carbonyl VOCs to reflect underlying pathophysiological conditions in pulmonary fibrosis, this proof-of-concept study tested the hypothesis that volatile and low abundance carbonyl compounds could be linked to diagnosis and associated disease severity.

METHODS

Exhaled breath samples were collected from outpatients with a diagnosis of Idiopathic Pulmonary Fibrosis (IPF) or Connective Tissue related Interstitial Lung Disease (CTD-ILD) with stable lung function for 3 months before enrollment, as measured by pulmonary function testing (PFT) DLCO (%), FVC (%) and FEV1 (%). A novel microreactor was used to capture carbonyl compounds in the breath as direct output products. A machine learning workflow was implemented with the captured carbonyl compounds as input features for classification of diagnosis and disease severity based on PFT (DLCO and FVC normal/mild vs. moderate/severe; FEV1 normal/mild/moderate vs. moderately severe/severe).

RESULTS

The proposed approach classified diagnosis with AUROC=0.877 ± 0.047 in the validation subsets. The AUROC was 0.820 ± 0.064, 0.898 ± 0.040, and 0.873 ± 0.051 for disease severity based on DLCO, FEV1, and FVC measurements, respectively. Eleven key carbonyl VOCs were identified with the potential to differentiate diagnosis and to classify severity.

CONCLUSIONS

Exhaled breath carbonyl compounds can be linked to pulmonary function and fibrotic ILD diagnosis, moving towards improved pathophysiological understanding of pulmonary fibrosis.

An analytical approach for on-site analysis of breath samples for Δ9-tetrahydrocannabinol (THC)

Increased acceptance of cannabis containing the psychoactive component, Δ9-tetrahydrocannabinol (THC), raises concerns about the potential for impaired drivers and increased highway accidents. In contrast to the "breathalyzer" test, which is generally accepted for determining the alcohol level in a driver, there is no currently accepted roadside test for THC in a motorist. There is a need for an easily collectible biological sample from a potentially impaired driver coupled with an accurate on-site test to measure the presence and quantity of THC in a driver. A novel breath collection device is described, which includes three separate sample collectors for collecting identical A, B, and C breath samples from a subject. A simple one-step ethanol extraction of the "A" breath collector sample can be analyzed by UHPLC/selected ion monitoring (SIM) liquid chromatography/mass spectrometry (LC/MS) to provide qualitative and quantitative determination of THC in breath sample in less than 4 min for samples collected up to 6 h after smoking a cannabis cigarette. SIM LC/MS bioanalyses employed d3-THC as the stable isotope internal standard fortified in negative control breath samples for quantitation including replicates of six calibrator standards and three quality control (QC) samples. Subsequent confirmation of the same breath sample in the B collectors was then confirmed by a reference lab by LC/MS/MS analysis. Fit-for-purpose bioanalytical validation consistent with pharmaceutical regulated bioanalyses produced pharmacokinetic (PK) curves for the two volunteer cannabis smokers. These results produced PK curves, which showed a rapid increase of THC in the breath of the subjects in the first hour followed by reduced THC levels in the later time points. A simpler single-point calibration curve procedure with calibrators and QC prepared in ethanol provided similar results. Limitations to this approach include the higher cost and operator skill sets for the instrumentation employed and the inability to actually determine driver impairment.

Microfluidic paper-based colorimetric quantification of malondialdehyde using silver nanoprism toward on-site biomedical analysis: a new platform for the chemical sensing and biosensing of oxidative stress

Malondialdehyde (MDA) is a critical product of polyunsaturated adipose acid peroxidation and represents a common biomarker of oxidative stress. The effect of different MDA concentrations on human biofluids reflects pathological changes, which has been seen in diverse types of sickness, such as leukemia, diabetes, cancer, cardiovascular disease, and age-related macular degeneration and liver disease. In this study, different types of silver nanoparticles, including silver nanoprism (AgNPrs), silver nanowires (AgNWs), and silver nanospheres (AgNSs), were synthesized and used for the chemosensing of MDA by colorimetric and spectrophotometric methods. Colorimetric tests were performed to identify malondialdehyde in the solution as well as the one-droplet-based microfluidic paper substrate as a miniaturization device for the monitoring of analytes in human real samples. The analytical quantification of the MDA was done using the UV-Vis method. Also, the utilization of the designed chemosensor for the analysis of MDA in real sample was evaluated in human urine samples. Using the spectrophotometric method, MDA was deformed in the linear range of 0.01192 to 1.192 mM with a low limit of quantification of 0.12 μM. Essential significant features of this study include the first application of AgNPrs with high stability and great optical properties without any reagent as an optical sensing probe of MDA and optimized OD-μPCD toward on-site and on-demand MDA screening in real samples diagnosis and the innovative time/color semi-analytical recognition strategy. Moreover, the prepared OD-μPCD decorated by AgNPrs could be a prized candidate for commercialization due to the benefits of the low-cost materials used, like paper and paraffin, and portability. This innovative process led to uniform hydrophilic micro-channels on the surface of cellulose, without the use of a UV lamp, clean room, and organic solvents. This report could be a pioneering work, inspiring simple and effective on-site semi-analytical recognition devices for harmful substances or illegal drugs, which simply consist of a piece of lightweight paper and one drop of the required reagent.

Effect of ambient temperature and respiration rate on nasal dominance: preliminary findings from a nostril-specific wearable

The nasal dominance (ND) determination is crucial for nasal synchronized ventilator, optimum nasal drug delivery, identifying brain hemispheric dominance, nasal airway obstruction surgery, mindfulness breathing, and for possible markers of a conscious state. Given these wider applications of ND, it is interesting to understand the patterns of ND with varying temperature and respiration rates. In this paper, we propose a method which measures peak-to-peak temperature oscillations (difference between end-expiratory and end-inspiratory temperature) for the left and right nostrils during nasal breathing. These nostril-specific temperature oscillations are further used to calculate the nasal dominance index (NDI), nasal laterality ratio (NLR), inter-nostril correlation, and mean of peak-to-peak temperature oscillation for inspiratory and expiratory phase at (1) different ambient temperatures of 18 °C, 28 °C, and 38 °C and (2) at three different respiration rate of 6 bpm, 12 bpm, and 18 bpm. The peak-to-peak temperature (Tpp) oscillation range (averaged across participants;n= 8) for the left and right nostril were 3.80 ± 0.57 °C and 2.34 ± 0.61 °C, 2.03 ± 0.20 °C and 1.40 ± 0.26 °C, and 0.20 ± 0.02 °C and 0.29 ± 0.03 °C at the ambient temperature of 18 °C, 28 °C, and 38 °C respectively (averaged across participants and respiration rates). The NDI and NLR averaged across participants and three different respiration rates were 35.67 ± 5.53 and 2.03 ± 1.12; 8.36 ± 10.61 and 2.49 ± 3.69; and -25.04 ± 14.50 and 0.82 ± 0.54 at the ambient temperature of 18 °C, 28 °C, and 38 °C respectively. The Shapiro-Wilk test, and non-parametric Friedman test showed a significant effect of ambient temperature conditions on both NDI and NLR. No significant effect of respiration rate condition was observed on both NDI and NLR. The findings of the proposed study indicate the importance of ambient temperature while determining ND during the diagnosis of breathing disorders such as septum deviation, nasal polyps, nosebleeds, rhinitis, and nasal fractions, and in the intensive care unit for nasal synchronized ventilator.

Development of an analytical chip for colorimetric detection of medium-chain aldehydes by reaction with pararosaniline in porous glass

Medium-chain aldehydes are common human biogases that can be detected in the breath of patients with lung diseases. As such, the measurement of medium-chain aldehyde gases in human breath can provide significant, noninvasive, and diagnostic information related to the potential presence of such diseases. In this study, an analytical chip is developed for the detection of medium-chain aldehydes without interference from short-chain aldehydes. This analytical chip is composed of porous glass impregnated with pararosaniline and an acid (i.e., acetic acid with small amount of phosphoric acid). After exposure to medium-chain aldehydes, the red analytical chip became violet in color, and an absorption peak was observed at 620 nm. It was found that a non-reversible reaction occurred in the porous glass, therefore, the analytical chip functions in a cumulative manner. A linear relationship was determined between the absorbance change of the analytical chip at 620 nm and the nonanal exposure concentration. Importantly, the developed analytical chip successfully detected nonanal at concentrations of 8-270 ppb as calculated from the absorbance change at 620 nm after a 24 h exposure time. In addition, nonanal concentration was estimated using the change in the R value of the analytical chip photograph. This method is suitable for point-of-care breath analysis. Finally, the analytical chip was also found to be active toward octanal and decanal with a relative sensitivity of 0.7 compared to that of nonanal; it was not active toward short-chain aldehydes.

Regulating the Electron Depletion Layer of Au/V2O5/Ag Thin Film Sensor for Breath Acetone as Potential Volatile Biomarker

Human exhaled breath has been utilized to identify biomarkers for diseases such as diabetes and cancer. The existence of these illnesses is indicated by a rise in the level of acetone in the breath. The development of sensing devices capable of identifying the onset of lung cancer or diabetes is critical for the successful monitoring and treatment of these diseases. The goal of this research is to prepare a novel breath acetone sensor made of Ag NPs/V₂O₅ thin film/Au NPs by combining DC/RF sputtering and post-annealing as synthesis methods. The produced material was characterized using X-ray diffraction (XRD), UV-Vis, Raman, and atomic force microscopy (AFM). The results revealed that the sensitivity to 50 ppm acetone of the Ag NPs/V₂O₅ thin film/Au NPs sensor was 96%, which is nearly twice and four times greater than the sensitivity of Ag NPs/V₂O₅ and pristine V₂O₅, respectively. This increase in sensitivity can be attributed to the engineering of the depletion layer of V₂O₅ through the double activation of the V₂O₅ thin films with uniform distribution of Au and Ag NPs that have different work function values.

Nonanal Gas Sensors Using Porous Glass as a Reaction Field for Ammonia-Catalyzed Aldol Condensation

Transmittance in porous-glass gas sensors, which use aldol condensation of vanillin and nonanal as the detection mechanism for nonanal, decreases because of the production of carbonates by the sodium hydroxide catalyst. In this study, the reasons for the decrease in transmittance and the measures to overcome this issue were investigated. Alkali-resistant porous glass with nanoscale porosity and light transparency was employed as a reaction field in a nonanal gas sensor using ammonia-catalyzed aldol condensation. In this sensor, the gas detection mechanism involves measuring the changes in light absorption of vanillin arising from aldol condensation with nonanal. Furthermore, the problem of carbonate precipitation was solved with the use of ammonia as the catalyst, which effectively resolves the issue of reduced transmittance that occurs when a strong base, such as sodium hydroxide, is used as a catalyst. Additionally, the alkali-resistant glass exhibited solid acidity because of the incorporated SiO2 and ZrO2 additives, which supported approximately 50 times more ammonia on the glass surface for a longer duration than a conventional sensor. Moreover, the detection limit obtained from multiple measurements was approximately 0.66 ppm. In summary, the developed sensor exhibits a high sensitivity to minute changes in the absorbance spectrum because of the reduction in the baseline noise of the matrix transmittance.

Pleiotropic Functions of Nitric Oxide Produced by Ascorbate for the Prevention and Mitigation of COVID-19: A Revaluation of Pauling's Vitamin C Therapy

Linus Pauling, who was awarded the Nobel Prize in Chemistry, suggested that a high dose of vitamin C (l-ascorbic acid) might work as a prevention or treatment for the common cold. Vitamin C therapy was tested in clinical trials, but clear evidence was not found at that time. Although Pauling's proposal has been strongly criticized for a long time, vitamin C therapy has continued to be tested as a treatment for a variety of diseases, including coronavirus infectious disease 2019 (COVID-19). The pathogen of COVID-19, SARS-CoV-2, belongs to the β-coronavirus lineage, which includes human coronavirus, severe acute respiratory syndrome (SARS), and Middle East respiratory syndrome (MERS). This review intends to shed new light on vitamin C antiviral activity that may prevent SARS-CoV-2 infection through the chemical production of nitric oxide (NO). NO is a gaseous free radical that is largely produced by the enzyme NO synthase (NOS) in cells. NO produced by upper epidermal cells contributes to the inactivation of viruses and bacteria contained in air or aerosols. In addition to enzymatic production, NO can be generated by the chemical reduction of inorganic nitrite (NO2-), an alternative mechanism for NO production in living organisms. Dietary vitamin C, largely contained in fruits and vegetables, can reduce the nitrite in saliva to produce NO in the oral cavity when chewing foods. In the stomach, salivary nitrite can also be reduced to NO by vitamin C secreted from the epidermal cells of the stomach. The strong acidic pH of gastric juice facilitates the chemical reduction of salivary nitrite to produce NO. Vitamin C contributes in multiple ways to the host innate immune system as a first-line defense mechanism against pathogens. Highlighting chemical NO production by vitamin C, we suggest that controversies on the therapeutic effects of vitamin C in previous clinical trials may partly be due to less appreciation of the pleiotropic functions of vitamin C as a universal bioreductant.

Effects of a Volatile Organic Compound Filter on Breath Profiles Measured by Secondary Electrospray High-Resolution Mass Spectrometry

Environmental volatile organic compounds (VOCs) from the ambient air potentially influence on-line breath analysis measurements by secondary electrospray ionization high-resolution mass spectrometry (SESI-HRMS). The aim of this study was to investigate how inhaling through a VOC filter affects the detected breath profiles and whether it is feasible to integrate such filters into routine measurements. A total of 24 adult participants performed paired breath analysis measurements with and without the use of an activated carbon filter for inspiration. Concordance correlation coefficients (CCCs) and the Bland−Altman analysis were used to assess the agreement between the two methods. Additionally, the effect on a selection of known metabolites and contaminants was analyzed. Out of all the detected features, 78.3% showed at least a moderate agreement before and after filter usage (CCC > 0.9). The decrease in agreement of the remaining m/z features was mostly associated with reduced signal intensities after filter usage. Although a moderate-to-substantial concordance was found for almost 80% of the m/z features, the filter still had an effect by decreasing signal intensities, not only for contaminants, but also for some of the studied metabolites. Operationally, the use of the filter complicated and slowed down the conductance of measurements, limiting its applicability in clinical studies.

Toward Continuous Breath Monitoring on a Mobile Phone Using a Frugal Conducting Cloth-Based Smart Mask

A frugal humidity sensor that can detect changes in the humidity of exhaled breath of individuals has been fabricated. The sensor comprises a humidity-sensitive conducting polymer that is in situ formed on a cloth that acts as a substrate. Interdigitated silver electrodes were screen-printed on the modified cloth, and conducting threads connected the electrodes to the measurement circuit. The sensor's response to changing humidity was measured as a voltage drop across the sensor using a microcontroller. The sensor was capable of discerning between fast, normal, and slow breathing based on the response time. A response time of ∼1.3 s was observed for fast breathing. An Android-based mobile application was designed to collect sensor data via Bluetooth for analysis. A time series classification algorithm was implemented to analyze patterns in breathing. The sensor was later stitched onto a face mask, transforming it into a smart mask that can monitor changes in the breathing pattern at work, play, and sleep.

Overview of the Mechanisms of Oxidative Stress: Impact in Inflammation of the Airway Diseases

Inflammation of the human lung is mediated in response to different stimuli (e.g., physical, radioactive, infective, pro-allergenic or toxic) such as cigarette smoke and environmental pollutants. They often promote an increase in inflammatory activities in the airways that manifest themselves as chronic diseases (e.g., allergic airway diseases, asthma, chronic bronchitis/chronic obstructive pulmonary disease (COPD) or even lung cancer). Increased levels of oxidative stress (OS) reduce the antioxidant defenses, affect the autophagy/mitophagy processes, and the regulatory mechanisms of cell survival, promoting inflammation in the lung. In fact, OS potentiate the inflammatory activities in the lung, favoring the progression of chronic airway diseases. OS increases the production of reactive oxygen species (ROS), including superoxide anions (O₂^-), hydroxyl radicals (OH) and hydrogen peroxide (H₂O₂), by the transformation of oxygen through enzymatic and non-enzymatic reactions. In this manner, OS reduces endogenous antioxidant defenses in both nucleated and non-nucleated cells. The production of ROS in the lung can derive from both exogenous insults (cigarette smoke or environmental pollution) and endogenous sources such as cell injury and/or activated inflammatory and structural cells. In this review, we describe the most relevant knowledge concerning the functional interrelation between the mechanisms of OS and inflammation in airway diseases.

Challenges and Opportunities for Printed Electrical Gas Sensors

Printed electrical gas sensors are a low-cost, lightweight, low-power, and potentially disposable alternative to gas sensors manufactured using conventional methods such as photolithography, etching, and chemical vapor deposition. The growing interest in Internet-of-Things, smart homes, wearable devices, and point-of-need sensors has been the main driver fueling the development of new classes of printed electrical gas sensors. In this Perspective, we provide an insight into the current research related to printed electrical gas sensors including materials, methods of fabrication, and applications in monitoring food quality, air quality, diagnosis of diseases, and detection of hazardous gases. We further describe the challenges and future opportunities for this emerging technology.

Identification of Exhaled Metabolites in Children with Cystic Fibrosis

The early detection of inflammation and infection is important to prevent irreversible lung damage in cystic fibrosis. Novel and non-invasive monitoring tools would be of high benefit for the quality of life of patients. Our group previously detected over 100 exhaled mass-to-charge (m/z) features, using on-line secondary electrospray ionization high-resolution mass spectrometry (SESI-HRMS), which distinguish children with cystic fibrosis from healthy controls. The aim of this study was to annotate as many m/z features as possible with putative chemical structures. Compound identification was performed by applying a rigorous workflow, which included the analysis of on-line MS2 spectra and a literature comparison. A total of 49 discriminatory exhaled compounds were putatively identified. A group of compounds including glycolic acid, glyceric acid and xanthine were elevated in the cystic fibrosis group. A large group of acylcarnitines and aldehydes were found to be decreased in cystic fibrosis. The proposed compound identification workflow was used to identify signatures of volatile organic compounds that discriminate children with cystic fibrosis from healthy controls, which is the first step for future non-invasive and personalized applications.

Metal-organic framework MIL-100(Fe) as a promising sensor for COVID-19 biomarkers detection

The development of fast and non-invasive techniques to detect SARS-CoV-2 virus at the early stage of the infection would be highly desirable to control the COVID-19 outbreak. Metal-organic frameworks (MOFs) are porous materials with uniform porous structures and tunable pore surfaces, which would be essential for the selective sensing of the specific COVID-19 biomarkers. However, the use of MOFs materials to detect COVID-19 biomarkers has not been demonstrated so far. In this work, for the first time, we employed the density functional theory calculations to investigate the specific interactions of MOFs and the targeted biomarkers, in which the interactions were confirmed by experiment. The five dominant COVID-19 biomarkers and common exhaled gases are comparatively studied by exposing them to MOFs, namely MIL-100(Al) and MIL-100(Fe). The adsorption mechanism, binding site, adsorption energy, recovery time, charge transfer, sensing response, and electronic structures are systematically investigated. We found that MIL-100(Fe) has a higher sensing performance than MIL-100(Al) in terms of sensitivity and selectivity. MIL-100(Fe) shows sensitive to COVID-19 biomarkers, namely 2-methylpent-2-enal and 2,4-octadiene with high sensing responses as 7.44 x 10⁵ and 9 x 10⁷ which are exceptionally higher than those of the common gases which are less than 6. The calculated recovery times of 0.19 and 1.84 x 10^-4 s are short enough to be a resuable sensor. An experimental study also showed that the MIL-100(Fe) provides a sensitivity toward 2-methylpent-2-enal. In conclusion, we suggest that MIL-100(Fe) could be used as a potential sensor for the exhaled breath analysis. We hope that our research can aid in the development of a biosensor for quick and easy COVID-19 biomarker detection in order to control the current pandemic.

Prostanoid Metabolites as Biomarkers in Human Disease

Prostaglandins (PGD₂, PGE₂, PGF_2α), prostacyclin (PGI₂), and thromboxane A₂ (TXA₂) together form the prostanoid family of lipid mediators. As autacoids, these five primary prostanoids propagate intercellular signals and are involved in many physiological processes. Furthermore, alterations in their biosynthesis accompany a wide range of pathological conditions, which leads to substantially increased local levels during disease. Primary prostanoids are chemically instable and rapidly metabolized. Their metabolites are more stable, integrate the local production on a systemic level, and their analysis in various biological matrices yields valuable information under different pathological settings. Therefore, prostanoid metabolites may be used as diagnostic, predictive, or prognostic biomarkers in human disease. Although their potential as biomarkers is great and extensive research has identified major prostanoid metabolites that serve as target analytes in different biofluids, the number of studies that correlate prostanoid metabolite levels to disease outcome is still limited. We review the metabolism of primary prostanoids in humans, summarize the levels of prostanoid metabolites in healthy subjects, and highlight existing biomarker studies. Since analysis of prostanoid metabolites is challenging because of ongoing metabolism and limited half-lives, an emphasis of this review lies on the reliable measurement and interpretation of obtained levels.

Volatile Organic Compounds as Potential Biomarkers for Noninvasive Disease Detection by Nanosensors: A Comprehensive Review

Biomarkers are biological molecules associated with physiological changes of the body and aids in the detecting the onset of disease in patients. There is an urgent need for self-monitoring and early detection of cardiovascular and other health complications. Several blood-based biomarkers have been well established in diagnosis and monitoring the onset of diseases. However, the detection level of biomarkers in bed-side analysis is difficult and complications arise due to the endothelial dysfunction. Currently single volatile organic compounds (VOCs) based sensors are available for the detection of human diseases and no dedicated nanosensor is available for the elderly. Moreover, accuracy of the sensors based on a single analyte is limited. Hence, breath analysis has received enormous attention in healthcare due to its relatively inexpensive, rapid, and noninvasive methods for detecting diseases. This review gives a detailed analysis of how biomarker imprinted nanosensor can be used as a noninvasive method for detecting VOC to health issues early using exhaled breath analysis.

Review of the algorithms used in exhaled breath analysis for the detection of diabetes

Currently, intensive work is underway on the development of truly noninvasive medical diagnostic systems, including respiratory analysers based on the detection of biomarkers of several diseases including diabetes. In terms of diabetes, acetone is considered as a one of the potential biomarker, although is not the single one. Therefore, the selective detection is crucial. Most often, the analysers of exhaled breath are based on the utilization of several commercially available gas sensors or on specially designed and manufactured gas sensors to obtain the highest selectivity and sensitivity to diabetes biomarkers present in the exhaled air. An important part of each system are the algorithms that are trained to detect diabetes based on data obtained from sensor matrices. The prepared review of the literature showed that there are many limitations in the development of the versatile breath analyser, such as high metabolic variability between patients, but the results obtained by researchers using the algorithms described in this paper are very promising and most of them achieve over 90% accuracy in the detection of diabetes in exhaled air. This paper summarizes the results using various measurement systems, feature extraction and feature selection methods as well as algorithms such as Support Vector Machines, k-Nearest Neighbours and various variations of Neural Networks for the detection of diabetes in patient samples and simulated artificial breath samples.

Current Insights into Atopic March

The incidence of allergic diseases is increasing, and research on their epidemiology, pathophysiology, and the prevention of onset is urgently needed. The onset of allergic disease begins in infancy with atopic dermatitis and food allergy and develops into allergic asthma and allergic rhinitis in childhood; the process is defined as “atopic march”. Atopic march is caused by multiple immunological pathways, including allergen exposure, environmental pollutants, skin barrier dysfunction, type 2 inflammation, and oxidative stress, which promote the progression of atopic march. Using recent evidence, herein, we explain the involvement of allergic inflammatory conditions and oxidative stress in the process of atopic march, its epidemiology, and methods for prevention of onset.

Micro and Nanoscale Technologies for Diagnosis of Viral Infections

Viral infection is one of the leading causes of mortality worldwide. The growth of globalization significantly increases the risk of virus spreading, making it a global threat to future public health. In particular, the ongoing coronavirus disease 2019 (COVID-19) pandemic outbreak emphasizes the importance of devices and methods for rapid, sensitive, and cost-effective diagnosis of viral infections in the early stages by which their quick and global spread can be controlled. Micro and nanoscale technologies have attracted tremendous attention in recent years for a variety of medical and biological applications, especially in developing diagnostic platforms for rapid and accurate detection of viral diseases. This review addresses advances of microneedles, microchip-based integrated platforms, and nano- and microparticles for sampling, sample processing, enrichment, amplification, and detection of viral particles and antigens related to the diagnosis of viral diseases. Additionally, methods for the fabrication of microchip-based devices and commercially used devices are described. Finally, challenges and prospects on the development of micro and nanotechnologies for the early diagnosis of viral diseases are highlighted.

Highly sensitive and chemically stable NH3 sensors based on an organic acid-sensitized cross-linked hydrogel for exhaled breath analysis

Due to interference by the high moisture content and complicated compositions of human exhaled breath, the trace-level detection of ammonia (NH₃) with desirable selectivity and stability is a large challenge for exhaled breath analysis. Carboxyl-sensitized hydrogels can be activated by moisture to exhibit a significant response and excellent selectivity to NH₃. However, the high activity of carboxyl groups in hydrogels is a double-edged sword, resulting in poor chemical stability during NH₃ detection. Herein, organic acids were embedded into a cross-linked poly(ethylene glycol) diacrylate (PEGDA) hydrogel via thiol-ene photochemistry to form stable hydrogels for NH₃ detection in a humid atmosphere. As a result, under high humidity conditions (80% RH), the optimal sensors exhibited superior selectivity to NH₃ among various interfering gas species, a remarkably high NH₃ response (Z_a/Z_g=6.20) towards 20 ppm NH₃, and an extremely low actual detection limit (50 ppb) at room temperature. Moreover, the sensors exhibited excellent chemical stability due to the moderate equilibrium water content of the hydrogel composites and acid dissociation constant of the acid groups. The moisture-activated NH₃ sensing mechanism was thoroughly investigated by complex impedance spectroscopy (CIS), quartz crystal microbalance (QCM) measurements, Fourier transform infrared (FT-IR) spectroscopy and X-ray photoelectron spectroscopy (XPS). To explore the application prospects of cross-linked hydrogel sensors for detecting NH₃ in exhaled breath, a simulated exhaled breath test was also performed.

Molecular mechanisms of oxidative stress in asthma

The lungs are exposed to reactive oxygen species oxygen (ROS) produced as a result of inhalation of oxygen, as well as smoke and other air pollutants. Cell metabolism and the NADPH oxidases (Nox) generate low levels of intracellular ROS that act as signal transduction mediators by inducing oxidative modifications of histones, enzymes and transcription factors. Redox signalling is also regulated by localised production and sensing of ROS in mitochondria, the endoplasmic reticulum (ER) and inside the nucleus. Intracellular ROS are maintained at low levels through the action of a battery of enzymatic and non-enzymatic antioxidants. Asthma is a heterogeneous airway inflammatory disease with different immune endotypes; these include atopic or non-atopic Th2 type immune response associated with eosinophilia, or a non-Th2 response associated with neutrophilia. Airway remodelling and hyperresponsiveness accompany the inflammatory response in asthma. Over-production of ROS resulting from infiltrating immune cells, particularly eosinophils and neutrophils, and a concomitant impairment of antioxidant responses lead to development of oxidative stress in asthma. Oxidative stress is augmented in severe asthma and during exacerbations, as well as by air pollution and obesity, and causes oxidative damage of tissues promoting airway inflammation and hyperresponsiveness. Furthermore, deregulated Nox activity, mitochondrial dysfunction, ER stress and/or oxidative DNA damage, resulting from exposure to irritants, inflammatory mediators or obesity, may lead to redox-dependent changes in cell signalling. ROS play a central role in airway epithelium-mediated sensing, development of innate and adaptive immune responses, and airway remodelling and hyperresponsiveness. Nonetheless, antioxidant compounds have proven clinically ineffective as therapeutic agents for asthma, partly due to issues with stability and in vivo metabolism of these compounds. The compartmentalised nature of ROS production and sensing, and the role of ROS in homeostatic responses and in the action of corticosteroids and β2-adrenergic receptor agonists, adds another layer of complexity to antioxidant therapy development. Nox inhibitors and mitochondrial-targeted antioxidants are in clinical development for a number of diseases but they have not yet been investigated in asthma. A better understanding of the complex role of ROS in the pathogenesis of asthma will highlight new opportunities for more targeted and effective redox therapies.

Reactive Oxygen Species and Antioxidative Defense in Chronic Obstructive Pulmonary Disease

The respiratory system is continuously exposed to endogenous and exogenous oxidants. Chronic obstructive pulmonary disease (COPD) is characterized by chronic inflammation of the airways, leading to the destruction of lung parenchyma (emphysema) and declining pulmonary function. It is increasingly obvious that reactive oxygen species (ROS) and reactive nitrogen species (RNS) contribute to the progression and amplification of the inflammatory responses related to this disease. First, we described the association between cigarette smoking, the most representative exogenous oxidant, and COPD and then presented the multiple pathophysiological aspects of ROS and antioxidative defense systems in the development and progression of COPD. Second, the relationship between nitric oxide system (endothelial) dysfunction and oxidative stress has been discussed. Third, we have provided data on the use of these biomarkers in the pathogenetic mechanisms involved in COPD and its progression and presented an overview of oxidative stress biomarkers having clinical applications in respiratory medicine, including those in exhaled breath, as per recent observations. Finally, we explained the findings of recent clinical and experimental studies evaluating the efficacy of antioxidative interventions for COPD. Future breakthroughs in antioxidative therapy may provide a promising therapeutic strategy for the prevention and treatment of COPD.

Selective and self-validating breath-level detection of hydrogen sulfide in humid air by gold nanoparticle-functionalized nanotube arrays

We demonstrate the selective detection of hydrogen sulfide at breath concentration levels under humid airflow, using a self-validating 64-channel sensor array based on semiconducting single-walled carbon nanotubes (sc-SWCNTs). The reproducible sensor fabrication process is based on a multiplexed and controlled dielectrophoretic deposition of sc-SWCNTs. The sensing area is functionalized with gold nanoparticles to address the detection at room temperature by exploiting the affinity between gold and sulfur atoms of the gas. Sensing devices functionalized with an optimized distribution of nanoparticles show a sensitivity of 0.122%/part per billion (ppb) and a calculated limit of detection (LOD) of 3 ppb. Beyond the self-validation, our sensors show increased stability and higher response levels compared to some commercially available electrochemical sensors. The cross-sensitivity to breath gases NH₃ and NO is addressed demonstrating the high selectivity to H₂S. Finally, mathematical models of sensors' electrical characteristics and sensing responses are developed to enhance the differentiation capabilities of the platform to be used in breath analysis applications.

ELECTRONIC SUPPLEMENTARY MATERIAL

Supplementary material (details on the dielectrophoretic deposition, AuNP functionalization optimization, full range of experimental and model H₂S sensing response up to 820 ppb, and sensing response to NO gas) is available in the online version of this article at 10.1007/s12274-021-3771-7.

Artificial Breath Classification Using XGBoost Algorithm for Diabetes Detection

Exhaled breath analysis has become more and more popular as a supplementary tool for medical diagnosis. However, the number of variables that have to be taken into account forces researchers to develop novel algorithms for proper data interpretation. This paper presents a system for analyzing exhaled air with the use of various sensors. Breath simulations with acetone as a diabetes biomarker were performed using the proposed e-nose system. The XGBoost algorithm for diabetes detection based on artificial breath analysis is presented. The results have shown that the designed system based on the XGBoost algorithm is highly selective for acetone, even at low concentrations. Moreover, in comparison with other commonly used algorithms, it was shown that XGBoost exhibits the highest performance and recall.

Socio-economic demands and challenges for non-invasive disease diagnosis through a portable breathalyzer by the incorporation of 2D nanosheets and SMO nanocomposites

Breath analysis for non-invasive clinical diagnostics and treatment progression has penetrated the research community owing to the technological developments in novel sensing nanomaterials. The trace level selective detection of volatile organic compounds (VOCs) in breath facilitates the study of physiological disorder and real-time health monitoring. This review focuses on advancements in chemiresistive gas sensor technology for biomarker detection associated with different diseases. Emphasis is placed on selective biomarker detection by semiconducting metal oxide (SMO) nanostructures, 2-dimensional nanomaterials (2DMs) and nanocomposites through various optimization strategies and sensing mechanisms. Their synergistic properties for incorporation in a portable breathalyzer have been elucidated. Furthermore, the socio-economic demands of a breathalyzer in terms of recent establishment of startups globally and challenges of a breathalyzer are critically reviewed. This initiative is aimed at highlighting the challenges and scope for improvement to realize a high performance chemiresistive gas sensor for non-invasive disease diagnosis.

Breath analysis for non-invasive clinical diagnostics and treatment progression has penetrated the research community owing to the technological developments in novel sensing nanomaterials.

Surface Plasmon Resonance-Based Fiber-Optic Metallic Multilayer Biosensors

Accurate and quick sensing of various biomolecules relevant to different health conditions is indispensable in modern diagnosis and treatment procedures. Different multilayer metallic surface plasmon resonance (SPR) biosensor configurations comprising Au, Ag, Al, and Cu are analyzed in this work by employing an N-layer matrix formalism as applied to the fixed-angle spectral SPR sensing methodology. Stringent standards for sensitivity, detection accuracy, and figure of merit (FOM) of the sensor configurations are set to analyze the relative merits of one configuration over another. It is observed that three- and four-layer configurations using Al and Cu provide the best FOM among all sensors that passed the set standard criteria. The highest FOM (1433.82/RIU) is observed for the four-layer Al/Cu/Al/Cu sensor for an analyte refractive index of 1.408. The sensors are best suited for detecting analytes with a refractive index range of 1.350-1.414.

Enhanced ethanol sensing properties of WO3 modified TiO2 nanorods

Pristine and WO3 decorated TiO2 nanorods (NRs) were synthesised to investigate n-n-type heterojunction gas sensing properties. TiO2 NRs were fabricated via hydrothermal method on fluorine-doped tin oxide coated glass (FTO) substrates. Then, tungsten was sputtered on the TiO2 NRs and thermally oxidised to obtain WO3 nanoparticles. The heterostructure was characterised by X-ray diffraction (XRD), scanning electron microscopy (SEM), and energy-dispersive X-ray (EDX) spectroscopy. Fabricated sensor devices were exposed to VOCs such as toluene, xylene, acetone and ethanol, and humidity at different operation temperatures. Experimental results demonstrated that the heterostructure has better sensor response toward ethanol at 200 °C. Enhanced sensing properties are attributed to the heterojunction formation by decorating TiO2 NRs with WO3.

Recent Progress in Graphene Derivatives/Metal Oxides Binary Nanocomposites Based Chemi-resistive Sensors for Disease Diagnosis by Breath Analysis

Background::

The scientific and clinical interest of breath analysis for non-invasive disease diagnosis has been focused by the scientific community over the past decade. This was due to the exhalation of prominent volatile organic compounds (VOCs) corresponding to the metabolic activities in the body and their concentration variation. To identify these biomarkers, various analytical techniques have been used in the past and the threshold concentration was established between a healthy and diseased state. Subsequently, various nanomaterials-based gas sensors were explored for their demand in quantifying these biomarkers for real-time, low cost and portable breathalyzers along with the essential sensor performances.

Methods::

We focus on the classification of graphene derivatives and their composites’ gas sensing efficiency for the application in the development of breathalyzers. The review begins with the feasibility of the application of nanomaterial gas sensors for healthcare applications. Then, we systematically report the gas sensing performance of various graphene derivatives/semiconductor metal oxides (SMO) binary nanocomposites and their optimizing strategies in selective detection of biomarkers specific to diseases. Finally, we provide insights on the challenges, opportunity and future research directions for the development of breathalyzers using other graphene derivatives/SMO binary nanocomposites.

Results::

On the basis of these analyses, graphene and its derivatives/metal oxides based binary nanocomposites have been a choice for gas sensing material owing to their high electrical conductivity and extraordinary thickness-dependent physicochemical properties. Moreover, the presence of oxygen vacancies in SMO does not only alter the conductivity but also accelerates the carrier transport rate and influence the adsorption behavior of target analyte on the sensing materials. Hence researchers are exploring the search of ultrathin graphene and metal oxide counterpart for high sensing performances.

Conclusion::

Their impressive properties compared to their bulk counterpart have been uncovered towards sensitive and selective detection of biomarkers for its use in portable breathalyzers.

The Hidden Burden of Severe Asthma: From Patient Perspective to New Opportunities for Clinicians

Severe asthma is an important topic in respiratory diseases, due to its high impact on morbidity and mortality as well as on health-care resources. The many challenges that still exist in the management of the most difficult-to-treat forms of the disease, and the acknowledgement of the existence of unexplored areas in the pathophysiological mechanisms and the therapeutic targets represent an opportunity to gather experts in the field with the immediate goals to summarize current understanding about the natural history of severe asthma and to identify gaps in knowledge and research opportunities, with the aim to contribute to improved medical care and health outcomes. This article is a consensus document from the “International Course on Severe Asthma” that took place in Palermo, Italy, on May 10–11, 2019. Emerging topics in severe asthma were addressed and discussed among experts, with special focus on patient’s needs and research opportunities, with the aim to highlight the unanswered questions in the diagnostic process and therapeutic approach.

Influence of air pollution on renal activity in patients with childhood-onset systemic lupus erythematosus

BACKGROUND

Childhood-onset systemic lupus erythematosus (cSLE) is an autoimmune and multifactorial disease that can affect the renal system. Exposure to air pollution can trigger systemic inflammation in cSLE patients and increase risk of disease activity. We evaluated effects of individual real-time exposure to air pollutants on renal activity in cSLE patients using the Systemic Lupus Erythematosus Disease Activity Index 2000.

METHODS

Longitudinal panel study of 108 repetitive measures from 9 pediatric lupus patients. Over three consecutive weeks, daily individual levels of fine particulate matter (PM_2.5) and nitrogen dioxide (NO₂) were measured, as well as weekly clinical evaluation and laboratory tests. This was repeated every 10 weeks over a 1-year period. Specific generalized estimating equation models were used to evaluate the impact of these pollutants on risk of nephritis and anti-dsDNA > 20 UI/mL and on 24-h urine protein and serum complement (C3) levels.

RESULTS

An interquartile range (IQR) increase of 18.12 μg/m³ in PM_2.5 daily concentration was associated with increased risk of nephritis and positive results for anti-dsDNA. Moreover, increase in 24-h urine protein and decrease in C3 serum levels also associated with exposure to pollutants. An IQR increase in PM_2.57-day moving average was associated with increased risks of leukocyturia (3.4; 95% CI 2.6:4.3), positive anti-dsDNA (3.1; 95% CI 2.1:4.0), and 36.3-mg increase (95% IC 20.2:52.3) in 24-h urine protein. An IQR increase (63.1 μg/m³) in 7-day cumulative NO₂ levels was associated with decreased serum C3 levels.

CONCLUSIONS

This prospective study suggests exposure to air pollution can trigger renal activity in cSLE patients.

Applications of Near Infrared Photoacoustic Spectroscopy for Analysis of Human Respiration: A Review

In this review, applications of near-infrared photoacoustic spectroscopy are presented as an opportunity to evaluate human respiration because the measurement of breath is fast, intact and simple to implement. Recently, analytical methods for measuring biomarkers in exhaled air have been extensively developed. With laser-based photoacoustic spectroscopy, volatile organic compounds can be identified with high sensitivity, at a high rate, and with very good selectivity. The literature review has shown the applicability of near-infrared photoacoustic spectroscopy to one of the problems of the real world, i.e., human health. In addition, the review will consider and explore different breath sampling methods for human respiration analysis.

CO2 and O2 Detection by Electric Field Sensors

In this work an array of chemical sensors for gas detection has been developed, starting with a commercial sensor platform developed by Microchip (GestIC), which is normally used to detect, trace, and classify hand movements in space. The system is based on electric field changes, and in this work, it has been used as mechanism revealing the adsorption of chemical species CO2 and O2. The system is composed of five electrodes, and their responses were obtained by interfacing the sensors with an acquisition board based on an ATMEGA 328 microprocessor (Atmel MEGA AVR microcontroller). A dedicated measurement chamber was designed and prototyped in acrylonitrile butadiene styrene (ABS) using an Ultimaker3 3D printer. The measurement cell size is 120 × 85 mm. Anthocyanins (red rose) were used as a sensing material in order to functionalize the sensor surface. The sensor was calibrated using different concentrations of oxygen and carbon dioxide, ranging from 5% to 25%, mixed with water vapor in the range from 50% to 90%. The sensor exhibits good repeatability for CO2 concentrations. To better understand the sensor response characteristics, sensitivity and resolution were calculated from the response curves at different working points. The sensitivity is in the order of magnitude of tens to hundreds of µV/% for CO2, and of µV/% in the case of O2. The resolution is in the range of 10-1%-10-3% for CO2, and it is around 10-1% for O2. The system could be specialized for different fields, for environmental, medical, and food applications.

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.

Volatile organic compound breath signatures of children with cystic fibrosis by real-time SESI-HRMS

Early pulmonary infection and inflammation result in irreversible lung damage and are major contributors to cystic fibrosis (CF)-related morbidity. An easy to apply and noninvasive assessment for the timely detection of disease-associated complications would be of high value. We aimed to detect volatile organic compound (VOC) breath signatures of children with CF by real-time secondary electrospray ionisation high-resolution mass spectrometry (SESI-HRMS). A total of 101 children, aged 4-18 years (CF=52; healthy controls=49) and comparable for sex, body mass index and lung function were included in this prospective cross-sectional study. Exhaled air was analysed by a SESI-source linked to a high-resolution time-of-flight mass spectrometer. Mass spectra ranging from m/z 50 to 500 were recorded. Out of 3468 m/z features, 171 were significantly different in children with CF (false discovery rate adjusted p-value of 0.05). The predictive ability (CF versus healthy) was assessed by using a support-vector machine classifier and showed an average accuracy (repeated cross-validation) of 72.1% (sensitivity of 77.2% and specificity of 67.7%). This is the first study to assess entire breath profiles of children with SESI-HRMS and to extract sets of VOCs that are associated with CF. We have detected a large set of exhaled molecules that are potentially related to CF, indicating that the molecular breath of children with CF is diverse and informative.

Toward Continuous Monitoring of Breath Biochemistry: A Paper-Based Wearable Sensor for Real-Time Hydrogen Peroxide Measurement in Simulated Breath

Exhaled breath contains a large amount of biochemical and physiological information concerning one's health and provides an alternative route to noninvasive medical diagnosis of diseases. In the case of lung diseases, hydrogen peroxide (H2O2) is an important biomarker associated with asthma, chronic obstructive pulmonary disease, and lung cancer and can be detected in exhaled breath. The current method of breath analysis involves condensation of exhaled breath, is not continuous or real time, and requires two separate and bulky devices, complicating the periodic or long-term monitoring of a patient. We report the first disposable paper-based electrochemical wearable sensor that can monitor exhaled H2O2 in artificial breath calibration-free and continuously, in real time, and can be integrated into a commercial respiratory mask for on-site testing of exhaled breath. To improve precision for sensing H2O2, we perform differential electrochemical measurement by amperometry in which screen-printed Prussian Blue-mediated and nonmediated carbon electrodes are used for differential analysis. We were able to measure H2O2 in simulated breath in a concentration-dependent manner in real time, confirming its functionality. This proposed system is versatile, and by modifying the chemistry of the sensing electrodes, our method of differential sensing can be extended to continuous monitoring of other analytes in exhaled breath.

Epithelial Alarmins in Serum and Exhaled Breath in Patients with Idiopathic Pulmonary Fibrosis: A Prospective One-Year Follow-Up Cohort Study

Background: Recently, epithelial alarmins have been shown to play important roles in non-allergen driven respiratory diseases like idiopathic pulmonary fibrosis (IPF). Little is known about the expression of the epithelial alarmins in IPF. Methods: This study aimed to prospectively examine interleukin (IL)-25, IL-33, and thymic stromal lymphopoietin (TSLP) levels in the serum and exhaled breath condensate (EBC) in patients with IPF before and after one-year of antifibrotic treatment. A total of 82 volunteers, including 52 patients diagnosed with IPF that qualified for antifibrotic therapy as well as 30 controls, were examined. All study participants underwent baseline peripheral blood and EBC sampling. In 35 out of 52 IPF subjects, a follow-up sampling was performed after 12 months of antifibrotic treatment. Concentrations of alarmins in the serum and EBC were evaluated by means of ELISA. Results: Baseline TSLP concentrations were significantly elevated in patients with IPF compared to controls both in the serum (p < 0.05) and EBC (p < 0.0001). Baseline IL-25 and IL-33 serum and EBC levels did not differ significantly between IPF subjects and controls. Prospective analysis of changes in the epithelial alarmin levels showed significantly decreased IL-25 and TSLP EBC concentrations after 12 months of antifibrotic treatment (p < 0.05), which was observed in the subgroup of IPF patients treated with pirfenidone, but not in those treated with nintedanib. In stable patients with IPF over a study period (absolute forced vital capacity (FVC) % of predicted decline/year ≤ 5%, n = 25), a significant decrease in the EBC levels of both IL-25 and TSLP after 12 months of antifibrotic treatment was noted (p < 0.05), whereas, in progressor IPF patients (absolute FVC % of predicted decline/year > 5%, n = 10), a significant decrease was noted in the IL-25 EBC levels only (p < 0.05). Conclusions: Elevated TSLP levels in patients with IPF and their significant decrease in the lung compartment during antifibrotic therapy in stable patients with IPF, but not in progressors, support its significant contribution to pro-fibrotic type 2 immune responses in IPF. Noted changes in the epithelial alarmins concentration in the lung compartment during pirfenidone therapy may suggest its possible interaction with epithelial alarmins pathways in IPF.

The electronic nose technology in clinical diagnosis: A systematic review

Supplemental Digital Content is available in the text

Background:

Volatile organic compounds (VOC) are end products of human metabolism (normal and disease-associated) that can be mainly excreted in breath, urine, and feces. Therefore, VOC can be very useful as markers of diseases and helpful for clinicians since its sampling is noninvasive, inexpensive, and painless. Electronic noses, or eNoses, provide an easy and inexpensive way to analyze gas samples. Thus, this device may be used for diagnosis, monitoring or phenotyping diseases according to specific breathprints (breath profile).

Objective:

In this review, we summarize data showing the ability of eNose to be used as a noninvasive tool to improve diagnosis in clinical settings.

Methods:

A PRISMA-oriented search was performed in PubMed and Cochrane Library. Only studies performed in humans and published since 2000 were included.

Results:

A total of 48 original articles, 21 reviews, and 7 other documents were eligible and fully analyzed. The quality assessment of the selected studies was conducted according to the Standards for Reporting of Diagnostic Accuracy. Airway obstructive diseases were the most studied and Cyranose 320 was the most used eNose.

Conclusions:

Several case–control studies were performed to test this technology in diverse fields. More than a half of the selected studies showed good accuracy. However, there are some limitations regarding sampling methodology, analysis, reproducibility, and external validation that need to be standardized. Additionally, it is urgent to test this technology in intend-to-treat populations. Thus, it is possible to think in the contribution of VOC analysis by eNoses in a clinical setting.

A comparison of online and offline measurement of exhaled breath for diabetes pre-screening by graphene-based sensor; from powder processing to clinical monitoring prototype

Several breath analysis studies have suggested a correlation between blood glucose (BG) levels and breath acetone, indicating acetone as a primary biomarker in exhaled breath for diabetes diagnosis. Herein, we have (i) fabricated and validated graphene-based chemi-resistive sensors for selective and sensitive detection of acetone, (ii) performed offline breath analysis by a static gas sensing set-up to acquire olfactory signals, and (iii) developed an LED-based portable on/off binary e-nose system for pre-screening diabetes through online analysis. The fabricated sensors showed selective detection for acetone with high sensitivity (5.66 for 1 ppm acetone vapor) and fast response and recovery times (10 s and 12 s) at low concentrations. The sensor responses of end tidal fractional breath (collected in Tedlar bags) in the fasting and postprandial conditions were compared with BG levels and glycated hemoglobin (HbA1c) levels taken at the same time in 30 volunteers (13 healthy and 17 diabetic subjects). The mean sensor responses of the diabetic subjects as obtained by offline analysis were 1.1 times higher than those of the healthy subjects. The optimal regression equation framed with the significant correlating variables for HbA1c estimation achieved an accuracy of 66.67%. The online breath analysis by on/off binary prototype exhibited an accuracy of 60.51%. Though there exists a minimal uncertainty in classification, the on/off type portable prototype is easy to operate, gives a quicker response with a refresh/recovery rate of 19 s and can be used for preliminary diagnosis, and can be used for preliminary diagnosis. This inexpensive sensor technology may revolutionize personalized medicine in the near future and greatly benefit the underprivileged.