Analysis of a Broad Range of Carbonyl Metabolites in Exhaled Breath by UHPLC-MS.

Analysis of volatile organic compounds (VOCs) in exhaled breath (EB) has shown great potential for disease detection including lung cancer, infectious respiratory diseases, and chronic obstructive pulmonary disease. Although many breath sample collection and analytical methods have been developed for breath analysis, analysis of metabolic VOCs in exhaled breath is still a challenge for clinical application. Many carbonyl compounds in exhaled breath are related to the metabolic processes of diseases. This work reports a method of ultrahigh-performance liquid chromatography coupled with high-resolution mass spectrometry (UHPLC-MS) for the analysis of a broad range of carbonyl metabolites in exhaled breath. Carbonyl compounds in the exhaled breath were captured by a fabricated silicon microreactor with a micropillar array coated with 2-(aminooxy)ethyl-N,N,N-trimethylammonium (ATM) triflate. A total of six subgroups consisting of saturated aldehydes and ketones, hydroxy-aldehydes, and hydroxy-ketones, unsaturated 2-alkenals, and 4-hydroxy-2-alkenals were identified in the exhaled breath. The combination of a silicon microreactor for the selective capture of carbonyl compounds with UHPLC-MS analysis may provide a quantitative method for the analysis of carbonyls to identify disease markers in exhaled breath.

Effect of Thiol Molecular Structure on the Sensitivity of Gold Nanoparticle-Based Chemiresistors toward Carbonyl Compounds.

Increasing both the sensitivity and selectivity of thiol-functionalized gold nanoparticle chemiresistors remains a challenging issue in the quest to develop real-time gas sensors. The effects of thiol molecular structure on such sensor properties are not well understood. This study investigates the effects of steric as well as electronic effects in a panel of substituted thiol-urea compounds on the sensing properties of thiolate monolayer-protected gold nanoparticle chemiresistors. Three series of urea-substituted thiols with different peripheral end groups were synthesized for the study and used to prepare gold nanoparticle-based chemiresistors. The responses of the prepared sensors to trace volatile analytes were significantly affected by the urea functional motifs. The largest response for sensing acetone among the three series was observed for the thiol-urea sensor featuring a tert-butyl end group. Furthermore, the ligands fitted with N, N'-dialkyl urea moieties exhibit a much larger response to carbonyl analytes than the more acidic urea series containing N-alkoxy-N'-alkyl urea and N, N'-dialkoxy urea groups with the same peripheral end groups. The results show that the peripheral molecular structure of thiolate-coated gold nanoparticles plays a critical role in sensing target analytes.

The Influence of ß-Ammonium Substitution on the Reaction Kinetics of Aminooxy Condensations with Aldehydes and Ketones.

The click-chemistry capture of volatile aldehydes and ketones by ammonium aminooxy compounds has proven to be an efficient means of analyzing the carbonyl subset in complex mixtures, such as exhaled breath or environmental air. In this work, we examine the carbonyl condensation reaction kinetics of three aminooxy compounds with varying ß-ammonium ion substitution using Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR-MS). We determined the activation energies for the reactions of the aminooxy compounds ATM, ADMH and AMAH with a panel of ketones and aldehydes that included acrolein and crotonaldehyde. The measurements indicate that the activation energies for the oximation reactions are quite low, less than 75 kJ mol-1 . ADMH is observed to react the fastest with the carbonyls studied. We postulate this result may be attributed to the ADMH ammonium proton effecting a Brønsted-Lowry acid-catalyzed elimination of water during the rate-determining step of oxime ether formation. A theoretical study of oxime ether formation is presented to explain the enhanced reactivity of ADMH relative to the tetraalkylammonium analog ATM.

Cesium ion-guided detection of trichloroethylene in air.

Whereas the close associations of cesium ion with organochlorine compounds have been previously documented, the present report is the first attempt to exploit these interactions to create a trichloroethylene (TCE)-selective sensor. Gold monolayer-protected clusters peripherally functionalized with Cs+ ions were used to prepare a chemiresistance film on MEMS-fabricated interdigitated electrodes. Vapor sensing properties of the cesium-rich chemiresistor were determined using a panel of chlorinated hydrocarbons including TCE as well as polar and non-polar VOCs for comparison. The sensor was selective and highly sensitive toward VOCs containing a 1,2-dichloro group at concentrations as low as 0.1 ppm. The results suggest the key interaction contributing to sensor response is a bidentate, metallocycle-like coordination of the 1,2-dichloro group to the cesium cations at the sensor surface.

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.

A comprehensive meta-analysis and systematic review of breath analysis in detection of COVID-19 through Volatile organic compounds.

BACKGROUND: The COVID-19 pandemic had profound global impacts on daily lives, economic stability, and healthcare systems. Diagnosis of COVID-19 infection via RT-PCR was crucial in reducing spread of disease and informing treatment management. While RT-PCR is a key diagnostic test, there is room for improvement in the development of diagnostic criteria. Identification of volatile organic compounds (VOCs) in exhaled breath provides a fast, reliable, and economically favorable alternative for disease detection. METHODS: This meta-analysis analyzed the diagnostic performance of VOC-based breath analysis in detection of COVID-19 infection. A systematic review of twenty-nine papers using the grading criteria from Newcastle-Ottawa Scale (NOS) and PRISMA guidelines was conducted. RESULTS: The cumulative results showed a sensitivity of 0.92 (95 % CI, 90 %-95 %) and a specificity of 0.90 (95 % CI 87 %-93 %). Subgroup analysis by variant demonstrated strong sensitivity to the original strain compared to the Omicron and Delta variant in detection of SARS-CoV-2 infection. An additional subgroup analysis of detection methods showed eNose technology had the highest sensitivity when compared to GC-MS, GC-IMS, and high sensitivity-MS. CONCLUSION: Overall, these results support the use of breath analysis as a new detection method of COVID-19 infection.

Detection of COVID-19 by quantitative analysis of carbonyl compounds in exhaled breath.

COVID-19 has caused a worldwide pandemic, creating an urgent need for early detection methods. Breath analysis has shown great potential as a non-invasive and rapid means for COVID-19 detection. The objective of this study is to detect patients infected with SARS-CoV-2 and even the possibility to screen between different SARS-CoV-2 variants by analysis of carbonyl compounds in breath. Carbonyl compounds in exhaled breath are metabolites related to inflammation and oxidative stress induced by diseases. This study included a cohort of COVID-19 positive and negative subjects confirmed by reverse transcription polymerase chain reaction between March and December 2021. Carbonyl compounds in exhaled breath were captured using a microfabricated silicon microreactor and analyzed by ultra-high-performance liquid chromatography-mass spectrometry (UHPLC-MS). A total of 321 subjects were enrolled in this study. Of these, 141 (85 males, 60.3%) (mean ± SD age: 52 ± 15 years) were COVID-19 (55 during the alpha wave and 86 during the delta wave) positive and 180 (90 males, 50%) (mean ± SD age: 45 ± 15 years) were negative. Panels of a total of 34 ketones and aldehydes in all breath samples were identified for detection of COVID-19 positive patients. Logistic regression models indicated high accuracy/sensitivity/specificity for alpha wave (98.4%/96.4%/100%), for delta wave (88.3%/93.0%/84.6%) and for all COVID-19 positive patients (94.7%/90.1%/98.3%). The results indicate that COVID-19 positive patients can be detected by analysis of carbonyl compounds in exhaled breath. The technology for analysis of carbonyl compounds in exhaled breath has great potential for rapid screening and detection of COVID-19 and for other infectious respiratory diseases in future pandemics.

Harnessing the cation-π interactions of metalated gold monolayer-protected clusters to detect aromatic volatile organic compounds.

The strong, non-covalent interactions between π-systems and cations have been the focus of numerous studies on biomolecule structure and catalysis. These interactions, however, have yet to be explored as a sensing mechanism for detecting trace levels of volatile organic compounds (VOCs). In this article, we provide evidence that cation-π interactions can be used to elicit sensitive and selective chemiresistor responses to aromatic VOCs. The chemiresistors are fitted with carboxylate-linked alkali metals bound to the surface of gold monolayer-protected clusters formulated on microfabricated interdigitated electrodes. Sensor responses to aromatic and non-aromatic VOCs are consistent with a model for cation-π interactions arising from association of electron-rich aromatic π-systems to metal ions with the relative strength of attraction following the order K+ > Na+ > Li+. The results point toward cation-π interactions as a promising research avenue to explore for developing aromatic VOC-selective sensors.

A feasibility study on exhaled breath analysis using UV spectroscopy to detect COVID-19.

A 23-subject feasibility study is reported to assess how UV absorbance measurements on exhaled breath samples collected from silicon microreactors can be used to detect COVID-19. The silicon microreactor technology chemoselectively preconcentrates exhaled carbonyl volatile organic compounds and subsequent methanol elution provides samples for analysis. The underlying scientific rationale that viral infection will induce an increase in exhaled carbonyls appears to be supported by the results of the feasibility study. The data indicate statistically significant differences in measured UV absorbance values between healthy and symptomatic COVID-19 positive subjects in the wavelength range from 235 nm to 305 nm. Factors such as subject age were noted as potential confounding variables.

Identification of a marker of infection in the breath using a porcine pneumonia model.

Objective: Pneumonia, both in the community and the hospital setting, represents a significant cause of morbidity and mortality in the cardiothoracic patient population. Diagnosis of pneumonia can be masked by other disease processes and is often diagnosed after the patient is already experiencing the disease. A noninvasive, sensitive test for pneumonia could decrease hospitalizations and length of stay for patients. We have developed a porcine model of pneumonia and evaluated the exhaled breath of infected pigs for biomarkers of infection. Methods: Anesthetized 60-kg adult pigs were intubated, and a bronchoscope was used to instill a solution containing 12 × 108 cfu of methicillin-sensitive Staphylococcus aureus or a control solution without bacteria (Sham) into the distal airways. The pigs were then reintubated on postoperative days 3, 6, and 9, with bronchoscopic bronchial lavages taken at each time point. At each time point, a 500-mL breath was captured from each pig. The breath was evacuated over a silicon microchip, with the volatile carbonyl compounds from the breath captured via oximation reaction, and the results of this capture were analyzed by ultra-high performance liquid chromatography mass spectrometry. Results: A total of 64% of the pigs inoculated with methicillin-sensitive S. aureus demonstrated consolidation on chest radiography and increasing counts of methicillin-sensitive S. aureus in the bronchial lavages over the span of the experiment, consistent with development of pneumonia. Analysis of the exhaled breath demonstrated 1 carbonyl compound (2-pentenal) that increased 10-fold over the span of the experiment, from an average of 0.0294 nmol/L before infection to an average of 0.3836 nmol/L on postoperative day 9. The amount of 2-pentenal present was greater in the breath of infected pigs than in the noninfected pigs or the sham inoculated pigs at postoperative days 6 and 9. Using an elevated concentration of 2-pentenal as a marker of infection yielded a sensitivity of 88% and specificity of 92% at postoperative day 6, and a sensitivity and specificity of 100% at postoperative day 9. Conclusions: We were able to successfully develop a clinical pneumonia in adult 60-kg pigs. The concentration of 2-pentenal correlated with the presence of pneumonia, demonstrating the potential for this compound to function as a biomarker for methicillin-sensitive S. aureus infection in pigs.

Preconcentration and analysis of trace volatile carbonyl compounds.

We describe a preconcentration device that may be suitable for quantitative analysis of trace volatile ketones and aldehydes in ambient air as well as in human breath. The approach is based on microreactor chips fabricated from silicon wafers. The microreactors have thousands of micropillars in microfluidic channels for uniformly distributing a gaseous sample flowing through the chips. The surfaces of the micropillars are functionalized with a quaternary ammonium aminooxy salt, [2-(aminooxy)ethyl]-N,N,N-trimethylammonium iodide (ATM), for trapping trace ketones and aldehydes by means of oximation reactions. ATM adducts and unreacted ATM are eluted from the microreactor with less than 40 µL of methanol and directly analyzed by nanospray Fourier transform ion cyclotron resonance (FTICR) mass spectrometry (MS). Ketones and aldehydes at levels of 1 ppbv have been detected using this microreactor and FTICR-MS system.

Integration of a micropreconcentrator with solid-phase microextraction for analysis of trace volatile organic compounds by gas chromatography-mass spectrometry.

The analysis of toxic volatile organic compounds (VOCs) in environmental air is important because toxic VOCs induce adverse effects on human health. Although gas chromatography- mass spectrometry (GC-MS) is the standard instrument for analysis of trace VOCs in air, this mode of analysis requires preconcentration and cryogenic processes. The preconcentration and subsequent thermal desorption of VOCs require special instruments and a long time of processing sample that significantly limit applications of GC-MS for monitoring indoor and outdoor VOC levels. Using a microfabricated preconcentrator for VOC analysis also has the challenge of a large sample volume for concentration. Using solid-phase microextraction (SPME) for VOC analysis by GC-MS often approaches the limit of detection of the GC-MS instrument for trace VOCs in air. This work reports a simple method to integrate microfabricated preconcentrators with commercial SPME fibers in a two-stage concentration processes to achieve rapid and reliable measurement of trace VOCs in air by GC-MS. We designed and fabricated a preconcentrator with micropillars in a microfluidic chamber to support sorbents and to increase the heat transfer rate to the sorbents for rapid thermal desorption. The effects of air flow rates through the preconcentrator on VOCs adsorption and thermal desorption were optimized for increasing analytical accuracy of VOCs measurements. The integration of a micropreconcentrator with SPME enabled measurements of sub-ppb levels of benzene, toluene, ethylbenzene, and xylene (BTEX), and trichloroethylene (TCE) in environmental air by GC-MS.

Multigroup prediction in lung cancer patients and comparative controls using signature of volatile organic compounds in breath samples.

Early detection of lung cancer is a crucial factor for increasing its survival rates among the detected patients. The presence of carbonyl volatile organic compounds (VOCs) in exhaled breath can play a vital role in early detection of lung cancer. Identifying these VOC markers in breath samples through innovative statistical and machine learning techniques is an important task in lung cancer research. Therefore, we proposed an experimental approach for generation of VOC molecular concentration data using unique silicon microreactor technology and further identification and characterization of key relevant VOCs important for lung cancer detection through statistical and machine learning algorithms. We reported several informative VOCs and tested their effectiveness in multi-group classification of patients. Our analytical results indicated that seven key VOCs, including C4H8O2, C13H22O, C11H22O, C2H4O2, C7H14O, C6H12O, and C5H8O, are sufficient to detect the lung cancer patients with higher mean classification accuracy (92%) and lower standard error (0.03) compared to other combinations. In other words, the molecular concentrations of these VOCs in exhaled breath samples were able to discriminate the patients with lung cancer (n = 156) from the healthy smoker and nonsmoker controls (n = 193) and patients with benign pulmonary nodules (n = 65). The quantification of carbonyl VOC profiles from breath samples and identification of crucial VOCs through our experimental approach paves the way forward for non-invasive lung cancer detection. Further, our experimental and analytical approach of VOC quantitative analysis in breath samples may be extended to other diseases, including COVID-19 detection.

Lipid Peroxidation Produces a Diverse Mixture of Saturated and Unsaturated Aldehydes in Exhaled Breath That Can Serve as Biomarkers of Lung Cancer-A Review.

The peroxidation of unsaturated fatty acids is a widely recognized metabolic process that creates a complex mixture of volatile organic compounds including aldehydes. Elevated levels of reactive oxygen species in cancer cells promote random lipid peroxidation, which leads to a variety of aldehydes. In the case of lung cancer, many of these volatile aldehydes are exhaled and are of interest as potential markers of the disease. Relevant studies reporting aldehydes in the exhaled breath of lung cancer patients were collected for this review by searching the PubMed and SciFindern databases until 25 May 2022. Information on breath test results, including the biomarker collection, preconcentration, and quantification methods, was extracted and tabulated. Overall, 44 studies were included spanning a period of 34 years. The data show that, as a class, aldehydes are significantly elevated in the breath of lung cancer patients at all stages of the disease relative to healthy control subjects. The type of aldehyde detected and/or deemed to be a biomarker is highly dependent on the method of exhaled breath sampling and analysis. Unsaturated aldehydes, detected primarily when derivatized during preconcentration, are underrepresented as biomarkers given that they are also likely products of lipid peroxidation. Pentanal, hexanal, and heptanal were the most reported aldehydes in studies of exhaled breath from lung cancer patients.

A novel microreactor approach for analysis of ketones and aldehydes in breath.

We report a fabricated microreactor with thousands of micropillars in channels. Each micropillar surface is chemically functionalized to selectively preconcentrate gaseous ketones and aldehydes of exhaled breath and to enhance ultra-trace, rapid analysis by direct-infusion Fourier transform-ion cyclotron resonance (FT-ICR) mass spectrometry (MS). The micropillar reactive coating contains the quaternary ammonium aminooxy salt 2-(aminooxy)ethyl-N,N,N-trimethylammonium iodide (ATM) for capturing trace carbonyl VOCs by means of an oximation reaction. We demonstrate the utility of this approach for detection of C(1) to C(12) aldehydes and ketones in exhaled breath, but the approach is applicable to any gaseous sample.

A novel technology to integrate imaging and clinical markers for non-invasive diagnosis of lung cancer.

This study presents a non-invasive, automated, clinical diagnostic system for early diagnosis of lung cancer that integrates imaging data from a single computed tomography scan and breath bio-markers obtained from a single exhaled breath to quickly and accurately classify lung nodules. CT imaging and breath volatile organic compounds data were collected from 47 patients. Spherical Harmonics-based shape features to quantify the shape complexity of the pulmonary nodules, 7th-Order Markov Gibbs Random Field based appearance model to describe the spatial non-homogeneities in the pulmonary nodule, and volumetric features (size) of pulmonary nodules were calculated from CT images. 27 VOCs in exhaled breath were captured by a micro-reactor approach and quantied using mass spectrometry. CT and breath markers were input into a deep-learning autoencoder classifier with a leave-one-subject-out cross validation for nodule classification. To mitigate the limitation of a small sample size and validate the methodology for individual markers, retrospective CT scans from 467 patients with 727 pulmonary nodules, and breath samples from 504 patients were analyzed. The CAD system achieved 97.8% accuracy, 97.3% sensitivity, 100% specificity, and 99.1% area under curve in classifying pulmonary nodules.

Characterization of DNPH-coated microreactor chip for analysis of trace carbonyls with application for breath analysis.

The analysis of trace carbonyls including aldehydes and ketones is important for monitoring environmental air quality, determining toxicity of aerosol of electronic cigarette, and detecting diseases by breath analysis. This work reports investigation of a single microreactor chip with HClO4-acidified DNPH coating for capture and analysis of carbonyls in air and exhaled breath. Three aldehydes and three ketones were spiked into one liter synthetic air in Tedlar bags serving as gaseous carbonyl standard for characterization of capture efficiency (CE). The HClO4-acidified DNPH showed higher CE of carbonyls than conventionally-used acid including H3PO4 and H2SO4 acidified DNPH under the microreactor conditions. The microreactor conditions including HClO4 to DNPH molar ratio, DNPH to carbonyls molar ratio, and gaseous sample flow rate through the microreactor were studied in detail and thereby optimized. Under the optimized conditions, 100% of CEs for aldehydes and above 80% for ketones were obtained. The microreactor chips were applied to determine acetone concentration in exhaled breath.

Very thin poly-SiC films for micro/nano devices.

We report characterization of nitrogen-doped, very thin, low-stress polycrystalline silicon carbide (poly-SiC) films suitable for fabricating micro/nano devices. The poly-SiC films are deposited on 100 mm-diameter (100) silicon wafers in a large-scale, hot-wall, horizontal LPCVD furnace using SiH2Cl2 and C2H2 as precursors and NH, as doping gas. The deposition temperature and pressure are fixed at 900 degrees C and 4 Torr, respectively. The deposition rate increases substantially in the first 50 minutes, transitioning to a limiting value thereafter. The deposited films exhibit (111)-orientated polycrystalline 3C-SiC texture. HR-TEM indicates a 1 nm to 4 nm amorphous SiC layer at the SiC/silicon interface. The residual stress and the resistivity of the films are found to be thickness dependent in the range of 100 nm to 1 microm. Films with thickness less than 100 nm suffer from voids or pinholes. Films thicker than 100 nm are shown to be suitable for fabricating micro/nano devices.

Analysis of Carbonyl Compounds in Ambient Air by a Microreactor Approach.

Aldehydes including formaldehyde, acetaldehyde, and acrolein are toxic organic components of air pollution that cause lung cancer and cardiovascular disease with chronic exposure. The commonly used method for determining the levels of carbonyl compounds based on the derivatizing agent 2,4-dinitrophenylhydrazine is of limited use for ketones and unsaturated aldehydes because of issues such as low capture efficiencies, unstable derivatives, and long sample collection times. This work details the analysis of carbonyls in ambient air by a microreactor approach. The microreactor is fabricated on a silicon wafer and has thousands of micropillars in a microfluidic channel for uniformly distributing the air flow through the channel. The surfaces of the micropillars are coated with a quaternary ammonium aminooxy reagent, 2-(aminooxy)ethyl-N,N,N-trimethylammonium iodide (ATM), for chemoselective capture of carbonyl compounds by means of oximation reactions. ATM-carbonyl adducts are eluted from the microreactor and directly analyzed by Fourier transform ion cyclotron resonance mass spectrometry and ultrahigh-performance liquid chromatography-mass spectrometry. More than 20 carbonyls were detected in ambient air samples. Acetone, 2-butanone, acetaldehyde, and formaldehyde were the most abundant carbonyls in ambient air of the studied urban areas.

Imparting sensitivity and selectivity to a gold nanoparticle chemiresistor through thiol monolayer functionalization for sensing acetone.

Chemiresistor-based gas sensors for detection of target volatile organic compounds (VOCs) in air face common challenges of poor sensitivity and selectivity as well as suffering from interference by other constituent gases and/or humidity. This work demonstrates that functionalizing gold nanoparticles (AuNPs) with a designed thiol monolayer improves sensitivity and selectivity of the derived AuNPs gas sensor. We report the synthesis and application of a thiol ligand fitted with both a urea motif and a tert-butyl end group for functionalizing AuNPs. The AuNPs sensor prepared using the urea thiol ligand demonstrated significantly increased acetone sensing in comparison with tested commercially available thiol-functionalized AuNPs. The sensor worked under ambient temperature and high humidity conditions, and demonstrated a linear relationship between the sensor response and the common logarithm of analyte concentration.