Breath Analysis Research Articles

Multiwavelength Photoacoustic Breath Analysis Sensor for the Diagnosis of Lung Diseases: COPD and Asthma.

Breath analysis is emerging as a universal diagnostic method for clinical applications. The possibility of breath analysis is being explored vigorously using different analytical techniques. We have designed and assembled a multiwavelength UV photoacoustic spectroscopy (PAS) sensor for the said application. To optimize laser wavelength for sample excitation, photoacoustic signals from disease and normal conditions are recorded with different laser excitations (213, 266, 355, and 532 nm) on exhaled breath samples. Principal component analysis (PCA) of the PA signals has shown that 213, 266, and 355 nm laser excitations are suitable for breath analysis, with reliable descriptive statistics obtained for 266 nm laser. The study has, therefore, been extended for breath samples collected from asthma, chronic obstructive pulmonary disease (COPD), and normal subjects, using 266 nm laser excitation. PCA of the PA data shows good classification among asthma, COPD, and normal subjects. Match/No-match study performed with asthma, COPD, and normal calibration set has demonstrated the potential of using this method for diagnostic application. Sensitivity and specificity are observed as 88 and 89%, respectively. The area under the curve of the ROC curve is found to be 0.948, which justifies the diagnostic capability of the device for lung diseases. The same samples were studied using a commercial E-Nose, and the measurement outcome strongly supports the PAS results.

Development of highly sensitive and selective trace acetone sensor using perovskite yttrium ferrite: Mechanism, kinetics and phase dependence study

Detection and monitoring of exhale breath acetone, bio-marker of diabetes is the need of the day to save millions human life. Trace acetone sensor having capability to detect breath acetone has been developed using perovskite YFeO3 powder (YFO) synthesized through a facile solution combustion technique. It is observed that YFO started to form hexagonal phase at 700 °C (YF-7) and ultimately converted to orthorhombic phase at 1000 °C (YF-10). Amongst others, YF-10 delivered best trace acetone sensing performance including a eight-fold response (S= Rg/Ra∼10.25 folds) to 1ppm acetone with ultrafast response-recovery time (∼0.6s-2s). Further, YF-10 sensor shows excellent selectivity, long-term stability more than 180 days, almost insensitive towards moisture and lower detection limit as low as 100 ppb. X-ray photoelectron spectroscopy (XPS) reveals that along with Fe3+ there exist Fe2+ ions which become maximum at 1000 °C. Formation of Fe2+ gives rise to oxygen vacancies which is maximum for YF-10 which is confirmed by PL and EPR studies. Enhanced acetone sensing performance of orthorhombic YFO is explained using quantitative phase analysis, honey-comb morphology, regulation of oxygen vacancies and bivalency of iron in different phases of yttrium ferrite. Eley−Rideal model has been invoked to explain the affinity towards acetone in comparison with other interfering gases. DFT calculation demonstrate that adsorption energy, a major parameter for gas sensing performance of any materials is lower for orthorhombic phase. In totality, it is observed that YFeO3 powder based sensor have huge potential for exhale breath analysis to monitor diabetes.

Oxygen-functionalized MoSe2 nanoflowers for selective detection of xylene at room temperature

The selective detection of xylene among its chemically similar counter VOCs is very crucial, and challenging and has great implications in breath analysis. At this point, we are introducing MoSe2 nanoflowers, which are synthesized by a one-step hydrothermal method. Later on, the surface functionality of the as-grown MoSe2 was effectively modulated by purging different oxygen concentrations (0.25 to 20 % O2) at 200 °C. Microscopic and spectroscopic characterizations were used to identify the changes in nanostructures after oxygen functionalization. The MoSe2 sensor treated with 2.5 % O2 showed an enhanced response towards xylene (73 % at 100 ppm) that was 14 times higher than the pristine MoSe2 at room temperature. Notably, the 2.5 % O2-treated MoSe2 sensor exhibited an 8 % response in 100 ppb of xylene with a lower detection limit (LOD) of 83 ppb. The cross-sensitivity of the sensor towards xylene as compared to the chemically identical VOCs like benzene and toluene was found to be very high. The selective detection of xylene was attributed to the improved surface reaction sites and catalytic behavior of MoSe2 after oxygen functionalization. The study confirms that the introduction of sufficient oxide or oxidants in 2D selenides like MoSe2 is favorable to accomplishing superior gas sensing characteristics.

Elucidating the Role of Ion Suppression in Secondary Electrospray Ionization.

Ion suppression is a known matrix effect in electrospray ionization (ESI), ambient pressure chemical ionization (APCI), and desorption electrospray ionization (DESI), but its characterization in secondary electrospray ionization (SESI) is lacking. A thorough understanding of this effect is crucial for quantitative applications of SESI, such as breath analysis. In this study, gas standards were generated by using an evaporation-based system to assess the susceptibility and suppression potential of acetone, deuterated acetone, deuterated acetic acid, and pyridine. Gas-phase effects were found to dominate ion suppression, with pyridine exhibiting the most significant suppressive effect, which is potentially linked to its gas-phase basicity. The impact of increased acetone levels on the volatiles from exhaled breath condensate was also examined. In humid conditions, a noticeable decrease in intensity of approximately 30% was observed for several features at an acetone concentration of 1 ppm. Considering that this concentration is expected for breath analysis, it becomes crucial to account for this effect when SESI is utilized to quantitatively determine specific compounds.

A Polymer‐Based Chemiresistive Gas Sensor for Selective Detection of Ammonia Gas

AbstractBreath analysis is a non‐invasive tool used in medical diagnosis. However, the current generation of breath analyzers is expensive, time‐consuming, and requires sample gas separation. In this work, a simple, yet effective, low‐cost ammonia gas sensor based on poly(2‐acrylamido‐2‐methyl‐1‐propanesulfonic acid) is presented for non‐invasive medical diagnosis. The designed sensor has a broad detection range to ammonia gas up to 1000 ppm with a limit of detection of 30 ppb. This is a robust sensor, which functions at high relative humidity (RH) (>90%) and exhibits consistent electrical responses under different test conditions. The result of a blind test validates the sensor's selective response to ammonia in the presence of other gases such as carbon dioxide. Furthermore, it is viable to integrate this sensor into a mask for real‐time ammonia gas detection accurately. Overall, this study demonstrates the feasibility of developing a simple, non‐invasive, and cost‐effective sensor for real‐time monitoring of ammonia gas with high potential in applications such as medical diagnostics, food safety, and environmental conditions.

Non-Invasive Method of Human Exhaled Breath Analysis for Diabetes Detection Using Bidirectional Long-Short-Term Memory Algorithm

Volatile organic compounds (VOCs) have the potential to be used as biomarkers for pathophysiological and physical abnormalities associated with several disorders. A promising non-invasive metabolic monitoring method is the Analysis of VOCs in exhaled breath. It may also be used to monitor the development of certain diseases and their early detection. Diabetes is a metabolic disease and a complicated syndrome. The relationship between oxidative stress, inflammatory syndrome, hypertension, and diabetes is complicated. This study describes the creation of an Internet of Things (IoT) based breath analyzer to identify and track diseases using exhaled breath. Diabetic breath biomarkers and breath analysis are the main topics of discussion. A group of 25 diabetic patients and 15 non-diabetic individuals were tested using this system. Data is initially gathered using the wired module and the Cool Term software. The system is created for both wired and wireless devices. A deep learning algorithm analyses the disease characteristics after data collection. It clearly distinguishes between samples with diabetes and those without with 84% accuracy. This technology could detect a non-transmissible or transmissible disease early, preventing infection to others.

Ultrasensitive Bio-H2S Gas Sensor Based on Cu2O-MWCNT Heterostructures.

Developing a respiratory analysis disease diagnosis platform for the H2S biomarker has great significance for the real-time detection of various diseases. However, achieving highly sensitive and rapid detection of H2S gas at the parts per billion level at low temperatures is one of the most critical challenges for developing portable exhaled gas sensors. Herein, Cu2O-multiwalled carbon nanotube (MWCNT) heterostructures with excellent gas sensitivity to H2S at room temperature and a lower temperature were successfully synthesized by a facile two-dimensional (2D) electrodeposition in situ assembly method. The combination of Cu2O and MWCNTs via the principle of optimal conductance growth not only reduced the initial resistance of the material but also provided an ideal interfacial barrier structure. Compared to the response of the pure Cu2O sensor, that of the Cu2O-MWCNT sensor to 1 ppm of H2S increased nearly 800 times at room temperature, and the response time decreased by more than 500 s. In addition to the excellent sensitivity with detection limits as low as 1 ppb, the Cu2O-MWCNT sensor was extremely selective with low-temperature adaptability. The sensor had a response value of 80.6 to 0.1 ppm of H2S at -10 °C, which is difficult to achieve with sensors based on oxygen adsorption/desorption mechanisms. The sensor was used for the detection of real oral exhaled breath, confirming its feasibility as a real-time disease monitoring sensor. The Cu2O-MWCNT heterostructures maximized the advantages of the individual components and laid the experimental foundation for future applications of highly sensitive portable breath analysis platforms for monitoring H2S.

A New Gas Analysis Method Based on Single-Beam Excitation Stimulated Raman Scattering in Hollow Core Photonic Crystal Fiber Enhanced Raman Spectroscopy.

We previously developed a hollow-core photonic crystal fiber (HCPCF) based Raman scattering enhancement technique for gas/human breath analysis. It enhances photon-gas molecule interactions significantly but is still based on CW laser excitation spontaneous Raman scattering, which is a low-probability phenomenon. In this work, we explored nanosecond/sub-nanosecond pulsed laser excitation in HCPCF based fiber enhanced Raman spectroscopy (FERS) and successfully induced stimulated Raman scattering (SRS) enhancement. Raman measurements of simple and complex gases were performed using the new system to assess its feasibility for gas analysis. We studied the gas Raman scattering characteristics, the relationship between Raman intensities and pump energies, and the energy threshold for the transition from spontaneous Raman scattering to SRS. H2, CO2, and propene (C3H6) were used as test gases. Our results demonstrated that a single-beam pulsed pump combined with FERS provides an effective Raman enhancement technique for gas analysis. Furthermore, an energy threshold for SRS initiation was experimentally observed. The SRS-capable FERS system, utilizing a single-beam pulsed pump, shows great potential for analyzing complex gases such as propene, which is a volatile organic compound (VOC) gas, serving as a biomarker in human breath for lung cancer and other human diseases. This work contributes to the advancement of gas analysis and opens alternative avenues for exploring novel Raman enhancement techniques.

Exhaled Breath Analysis Using Selected Ion Flow Tube Mass Spectrometry and Disease Severity in Heart Failure.

Exhaled breath volatile organic compounds (VOCs) are elevated in heart failure (HF). The ability of VOCs to predict long term cardiovascular mortality and morbidity has not been independently verified. In 55 patients admitted with acute decompensated heart failure (ADHF), we measured exhaled breath acetone and pentane levels upon admission and after 48 h of diuresis. In a separate cohort of 51 cardiac patients undergoing cardiopulmonary exercise testing (CPET), we measured exhaled breath acetone and pentane levels before and at peak exercise. In the ADHF cohort, admission acetone levels correlated with lower left ventricular ejection fraction (LVEF, r = -0.297, p = 0.035). Greater weight loss with diuretic therapy correlated with a greater reduction in both acetone levels (r = -0.398, p = 0.003) and pentane levels (r = -0.309, p = 0.021). In patients with above-median weight loss (≥4.5 kg), patients demonstrated significantly greater percentage reduction in acetone (59% reduction vs. 7% increase, p < 0.001) and pentane (23% reduction vs. 2% reduction, p = 0.008). In the CPET cohort, admission acetone and pentane levels correlated with higher VE/VCO2 (r = 0.39, p = 0.005), (r = 0.035, p = 0.014). However, there were no significant correlations between baseline or peak exercise acetone and pentane levels and peak VO2. In longitudinal follow-up with a median duration of 33 months, patients with elevated exhaled acetone and pentane levels experienced higher composite adverse events of death, ventricular assist device implantation, or orthotopic heart transplantation. In patients admitted with ADHF, higher exhaled breath acetone levels are associated with lower LVEF and poorer outcomes, and greater reductions in exhaled breath acetone and pentane tracked with greater weight loss. Exhaled acetone and pentane may be novel biomarkers in heart failure worthy of future investigation.

An insight into the functional alterations in the gut microbiome of healthy adults in response to a multi-strain probiotic intake: a single arm open label trial.

Probiotic supplements, by definition, provide a benefit to the host, but few studies have investigated the effect of probiotic supplements in healthy adult populations. The present, single arm, open label clinical trial, evaluated compositional and functional changes in the fecal microbiome of healthy adults after supplementation with a 14-strain probiotic. We analysed the effect of a 14-strain probiotic blend (Bacillus subtilis NCIMB 30223, Bifidobacterium bifidum NCIMB 30179, B. breve NCIMB 30180, B. infantis NCIMB 30181, B. longum NCIMB 30182, Lactobacillus helveticus NCIMB 30184, L. delbrueckii subsp. bulgaricus NCIMB 30186, Lacticaseibacillus paracasei NCIMB 30185, Lactiplantibacillus plantarum NCIMB 30187, Lacticaseibacillus rhamnosus NCIMB 30188, L. helveticus NCIMB 30224, Lactobacillus salivarius NCIMB 30225, Lactococcus lactis subsp. lactis NCIMB 30222, and Streptococcus thermophilus NCIMB 30189), on the faecal microbiota of healthy young adults (n=41) in a single arm study. The adults consumed 4 capsules daily of the 14 strain blend(8 billion colony forming units/day) for 8 weeks. Compositional and functional changes in faecal microbiota before and after supplementation were assessed using shotgun metagenomic sequencing. Fasting breath analysis, faecal biochemistry and bowel habits were also assessed. In healthy adult participants, no significant changes to the overall alpha- or beta-diversity was observed after 8 weeks of multi-strain probiotic supplementation. However, in a simplified model that considered only time and individual differences, significant decreases (p < 0.05) in family Odoribacteraceae and Bacteroidaceae abundance and a significant increase (p < 0.05) in genus Megamonas abundance were observed. At a functional level, there were significant changes in functional gene abundance related to several functional pathways, including phenylalanine metabolism, O-antigen nucleotide sugar biosynthesis, bacterial chemotaxis, and flagellar assembly. No significant changes in stool form or frequency, fecal biochemistry, or methane and hydrogen breath tests were observed. In healthy young adults, overall alpha- and beta-diversity did not change in response to probiotic intake even though modest compositional changes at the family and genus level were observed. However, at functional level, results identified changes in gene abundance for several functional pathways.

Development of an integrated breath analysis technology for on-chip aerosol capture and molecular analysis

As proven early on in the pandemic, SARS-CoV-2 is mainly transmitted by aerosols. This urged us to develop a silicon impactor that collects the virus particles directly from breath. Performing PCR on these breath samples proved equally sensitive as nasopharyngeal swabs during the first week of an infection [Stakenborg et al., 2022], yet it remained a mostly manual process and PCR turn-around-time was still long. To overcome these drawbacks, we developed a fast and sensitive, fully integrated point-of-need breath test, comprising a novel breath sampler device and PCR instrument. The breath sampler combines virus collection and in-situ RNA amplification. The PCR instrument performs very fast amplification of the released viral RNA. Sample-to-result time was reduced to <20 min with an equal performance as the original manual procedure.

Detection of Bacterial Colonization in Lung Transplant Recipients Using an Electronic Nose.

Bacterial colonization (BC) of the lower airways is common in lung transplant recipients (LTRs) and increases the risk of chronic lung allograft dysfunction. Diagnosis often requires bronchoscopy. Exhaled breath analysis using electronic nose (eNose) technology may noninvasively detect BC in LTRs. Therefore, we aimed to assess the diagnostic accuracy of an eNose to detect BC in LTRs. We performed a cross-sectional analysis within a prospective, single-center cohort study assessing the diagnostic accuracy of detecting BC using eNose technology in LTRs. In the outpatient clinic, consecutive LTR eNose measurements were collected. We assessed and classified the eNose measurements for the presence of BC. Using supervised machine learning, the diagnostic accuracy of eNose for BC was assessed in a random training and validation set. Model performance was evaluated using receiver operating characteristic analysis. In total, 161 LTRs were included with 80 exclusions because of various reasons. Of the remaining 81 patients, 16 (20%) were classified as BC and 65 (80%) as non-BC. eNose-based classification of patients with and without BC provided an area under the curve of 0.82 in the training set and 0.97 in the validation set. Exhaled breath analysis using eNose technology has the potential to noninvasively detect BC.

Prediction of systemic free and total valproic acid by off-line analysis of exhaled breath in epileptic children and adolescents.

Therapeutic drug monitoring (TDM) of medications with a narrow therapeutic window is a common clinical practice to minimize toxic effects and maximize clinical outcomes. Routine analyses rely on the quantification of systemic blood concentrations of drugs. Alternative matrices such as exhaled breath are appealing because of their inherent non-invasive nature. This is especially the case for pediatric patients. We have recently showcased the possibility of predicting systemic concentrations of valproic acid (VPA), an anti-seizure medication by real-time breath analysis in two real clinical settings. This approach, however, comes with the limitation of the patients having to physically exhale into the mass spectrometer. This restricts the possibility of sampling from patients not capable or available to exhale into the mass spectrometer located on the hospital premises. In this work, we developed an alternative method to overcome this limitation by collecting the breath samples in customized bags and subsequently analyzing them by secondary electrospray ionization coupled to high-resolution mass spectrometry (SESI-HRMS). A total ofn= 40 patients (mean ± SD, 11.5 ± 3.5 y.o.) diagnosed with epilepsy and taking VPA were included in this study. The patients underwent three measurements: (i) serum concentrations of total and free VPA, (ii) real-time breath analysis and (iii) off-line analysis of exhaled breath collected in bags. The agreement between the real-time and the off-line breath analysis methods was evaluated using Lin's concordance correlation coefficient (CCC). CCC was computed for ten mass spectral predictors of VPA concentrations. Lin's CCC was >0.6 for all VPA-associated features, except for two low-signal intensity isotopic peaks. Finally, free and total serum VPA concentrations were predicted by cross validating the off-line data set. Support vector machine algorithms provided the most accurate predictions with a root mean square error of cross validation of 29.0 ± 7.4 mg l-1and 3.9 ± 1.4 mg l-1for total and free VPA (mean ± SD), respectively. As a secondary analysis, we explored whether exhaled metabolites previously associated with side-effects and response to medication could be rendered by the off-line analysis method. We found that five features associated with side effects showed a CCC > 0.6, whereas none of the drug response-associated peaks reached this cut-off. We conclude that the clinically relevant free fraction of VPA can be predicted by this combination of off-line breath collection with rapid SESI-HRMS analysis. This opens new possibilities for breath based TDM in clinical settings.

Temperature Modulation of MOS Sensors for Enhanced Detection of Volatile Organic Compounds

Disease diagnosis through biological fluids, particularly exhaled breath analysis, has gained increasing importance. Volatile organic compounds (VOCs) present in exhaled breath offer diagnostic potential as they reflect altered and disease-specific metabolic pathways. While gas chromatography–mass spectrometry (GC–MS) has been traditionally used for VOCs detection, electronic noses have emerged as a promising alternative for disease screening. Metal oxide semiconductor (MOS) sensors play an essential role in these devices due to their simplicity and cost-effectiveness. However, their limited specificity and sensitivity pose challenges for accurate diagnosis at lower VOCs concentrations, typical of exhaled breath. To address specificity and sensitivity issues, temperature modulation (TM) has been proposed in this paper, introducing a custom-developed electronic nose based on multiple and heterogeneous gas sensors located within an analysis chamber. Four different TM patterns (i.e., square, sine, triangular, and a combination of square and triangular) were applied to the gas sensors to test their response to three different analytes at three distinct concentrations. Data were analyzed by extracting meaningful features from the sensor raw data, and dimensionality reduction using principal component analysis (PCA) was performed. The results demonstrated distinct clusters for each experimental condition, indicating successful discrimination of analytes and concentrations. In addition, an analysis of which set of sensors and modulation pattern yielded the best results was performed. In particular, the most promising TM pattern proved to be the square and triangular combination, with optimal discrimination accuracy between both concentrations and analytes. One specific sensor, namely, TGS2600 from Figaro USA, Inc., provided the best performance. While preliminary results highlighted the potential of TM to improve the sensitivity of gas sensors in electronic nose devices, paving the way for further advancements in the field of exhaled breath analysis.

Infrared Non‐Invasive Exhaled Biomarker Sensing: A Review

AbstractExhaled breath analysis is considered an effective tool for diagnosing the patient's metabolic status because of its non‐invasive nature. Gas chromatography‐mass spectrometry (GC‐MS) and other mass spectrometry techniques are widely used for exhaled breath analysis. Nevertheless, the requirement of a handheld device for real‐time analysis and rapid processing time of multiple samples leads to advancing infrared (IR) based breath gas sensing techniques. Herein, the IR gas sensing technologies are discussed with a focus on non‐dispersive infrared (NDIR), photoacoustic (PAS), and tunable diode laser absorption spectroscopy (TDLAS) gas sensing technologies because of their highly selective gas detection among compound gases (mixture of VOCs), as well as their corresponding sensing mechanisms and characteristics, for real‐time monitoring of exhaled biomarkers. Carbon dioxide, acetone, ammonia, nitric oxide, methane, and ethylene are the significant biomarkers elaborated in this work with their respective clinical applications and the significance of non‐invasive real‐time monitoring using IR detectors. Challenges in selectivity and clinical trials leads to focus on this review. Current market analysis, present status of different techniques to detect specific biomarkers and other challenges with their possible solutions discussed in this review aid in developing highly selective IR‐based handheld breath VOC analyzers for early diagnosis and screening.

JS-06 Analysis of Heart Rate and Breathing in Non-Contact Condition with Micro Doppler Radar Sensor

JS-06 Analysis of Heart Rate and Breathing in Non-Contact Condition with Micro Doppler Radar Sensor

Alveolar gradients in breath analysis. A pilot study with comparison of room air and inhaled air by simultaneous measurements using ion mobility spectrometry

Analyzing exhaled breath samples, especially using a highly sensitive method such as MCC/IMS (multi-capillary column/ion mobility spectrometry), may also detect analytes that are derived from exogenous production. In this regard, there is a discussion about the optimal interpretation of exhaled breath, either by considering volatile organic compounds (VOCs) only in exhaled breath or by additionally considering the composition of room air and calculating the alveolar gradients. However, there are no data on whether the composition and concentration of VOCs in room air are identical to those in truly inhaled air directly before analyzing the exhaled breath. The current study aimed to determine whether the VOCs in room air, which are usually used for the calculation of alveolar gradients, are identical to the VOCs in truly inhaled air. For the measurement of inhaled air and room air, two IMS, each coupled with an MCC that provided a pre-separation of the VOCs, were used in parallel. One device was used for sampling room air and the other for sampling inhaled air. Each device was coupled with a newly invented system that cleaned room air and provided a clean carrier gas, whereas formerly synthetic air had to be used as a carrier gas. In this pilot study, a healthy volunteer underwent three subsequent runs of sampling of inhaled air and simultaneous sampling and analysis of room air. Three of the selected 11 peaks (P4—unknown, P5—1-Butanol, and P9—Furan, 2-methyl-) had significantly higher intensities during inspiration than in room air, and four peaks (P1—1-Propanamine, N-(phenylmethylene), P2—2-Nonanone, P3—Benzene, 1,2,4-trimethyl-, and P11—Acetyl valeryl) had higher intensities in room air. Furthermore, four peaks (P6—Benzaldehyde, P7—Pentane, 2-methyl-, P8—Acetone, and P10—2-Propanamine) showed inconsistent differences in peak intensities between inhaled air and room air. To the best of our knowledge, this is the first study to compare simultaneous sampling of room air and inhaled air using MCC/IMS. The simultaneous measurement of inhaled air and room air showed that using room air for the calculation of alveolar gradients in breath analysis resulted in different alveolar gradient values than those obtained by measuring truly inhaled air.

Beyond the Skin: Reduced Lung Function Associated With Atopic Dermatitis in Infants.

Very few studies have examined lung function parameters using tidal breath analysis (TBA) in atopic dermatitis (AD) with its high potential for progression to asthma. To measure lung functions using TBA in infants with AD and in healthy controls (HCs), and to investigate the effects of disease severity, food sensitivity, and history of recurrent wheezing on TBA parameters in infants with AD. Two hundred thirty infants were included in this prospective cross-sectional study, including an AD group (n= 150) and an HC group (n= 80). Food sensitivity was assessed by means of food-specific IgE or the skin prick test. The severity of the disease was evaluated using the SCORing Atopic Dermatitis. Lung function was assessed using TBA. The following TBA parameters were significantly lower in the AD group than in the HC group (P < .05): time to peak tidal expiratory flow, exhaled volume to peak tidal expiratory flow, ratio of time to peak tidal expiratory flow to expiratory time, ratio of exhaled volume to peak tidal expiratory flow to total expiratory volume, expiratory flow when 25% of tidal volume remains in the lungs, respiratory rate, and minute ventilation. No difference was observed in the AD group when TBA parameters were compared according to disease severity, food sensitivity, and history of recurrent wheezing (P > .05). The receiver-operating characteristic curve demonstrated by the ratio of time to peak tidal expiratory flow to expiratory time yielded an area under the curve of 0.826 (CI, 0.772-0.879), with a cutoff value of 31.65 or higher in differentiating AD, with a sensitivity of 78.7% and a specificity of 77.5%. TBA curves can be a useful tool for demonstrating expiratory airway obstruction in AD and for providing objective information for the clinician. Bronchial obstruction was detected in young children with AD irrespective of the severity of the disease, food sensitivity, and history of recurrent wheezing.

A low-cost internal standard loader for solid-phase sorbing tools

Solid-phase sorption is widely used for the analysis of gaseous specimens as it allows at the same time to preconcentrate target analytes and store samples for relatively long periods. The addition of internal standards (ISs) in the analytical workflow can greatly reduce the variability of the analyses and improve the reliability of the protocols. In this work, we describe the development and testing of a portable system for the reliable production of gaseous mixture of 8D-Toluene in a 1L Silonite canister as well as its reproducible loading into solid-phase sorbing tools as ISs. The portable system was tested using needle trap microextraction, solid-phase extraction, and thin-film microextraction techniques commonly employed for the analysis of gaseous samples. Even though our specific interest is in breath analysis, the system can also be used for the collection of any kind of gaseous specimen. A microcontroller allows the fine control of the sampling flow by a digital mass flow controller. Flow rate and sample volume could be set either through a rotary encoder mounted onto the control board or through a dedicated android app. The variability of the airflow is in the range 5–200 ml min−1 and it is lower than 1%, whereas the variability of the IS (8D-Toluene) concentration dispensed over time by the loader measured by selected-ion flow-tube mass spectrometry (MS) is <3%. This combination resulted in intra- and inter-day precision of the amount loaded in the sorbent tools lower than 15%. No carry-over was detected in the loader after the delivery of the 8D-Toluene measured by gas chromatography–MS. The 8D-Toluene concentration in the canister was stable for up to three weeks at room temperature.

Standard operating procedure to reveal prostate cancer specific volatile organic molecules by infrared spectroscopy

The growing number of prostate cancer cases is a real concern in modern society. Over 1.4 million new cases and about 400 thousand (>26%) deaths were registered worldwide in 2020 due to prostate cancer. The high mortality rate of prostate cancer is due to the lack of reliable early detection of the disease. Till now the most reliable diagnosis of cancer is tissue biopsy, which is an invasive process. A non-invasive or minimally invasive technique could lead to a diagnostic tool that will allow for saving or prolonging the lifespan of millions of lives. Metabolite-based diagnostics may have a better chance of early cancer detection. However, reliable detection techniques need to be developed. Infrared spectroscopy based gaseous-biofluid holds great promise towards the development of non-invasive diagnostics. A pilot study based on breath analysis by infrared spectroscopy showed promising results in distinguishing prostate cancer patients from healthy volunteers. Details of the spectral metabolic analysis are presented.