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Zhu R, Zhou Q, Tian Q, Zhao S, Qin W, Wu X, Xu S, Zhang Y. Ppb-Level Ammonia Sensor for Exhaled Breath Diagnosis Based on UV-DOAS Combined with Spectral Reconstruction Fitting Neural Network. ACS Sens 2024. [PMID: 39077941 DOI: 10.1021/acssensors.4c01525] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/31/2024]
Abstract
Ammonia (NH3) in exhaled breath (EB) has been a biomarker for kidney function, and accurate measurement of NH3 is essential for early screening of kidney disease. In this work, we report an optical sensor that combines ultraviolet differential optical absorption spectroscopy (UV-DOAS) and spectral reconstruction fitting neural network (SRFNN) for detecting NH3 in EB. UV-DOAS is introduced to eliminate interference from slow change absorption in the EB spectrum while spectral reconstruction fitting is proposed for the first time to map the original spectra onto the sine function spectra by the principle of least absolute deviations. The sine function spectra are then fitted by the least-squares method to eliminate noise signals and the interference of exhaled nitric oxide. Finally, the neural network is built to enable the detection of NH3 in EB at parts per billion (ppb) level. The laboratory results show that the detection range is 9.50-12425.82 ppb, the mean absolute percentage error (MAPE) is 0.83%, and the detection accuracy is 0.42%. Experimental results prove that the sensor can detect breath NH3 and identify EB in simulated patients and healthy people. Our sensor will serve as a new and effective system for detecting breath NH3 with high accuracy and stability in the medical field.
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Affiliation(s)
- Rui Zhu
- School of Electrical Engineering, Yanshan University, Qinhuangdao 066004, China
| | - Qiwen Zhou
- School of Electrical Engineering, Yanshan University, Qinhuangdao 066004, China
| | - Qi Tian
- Department of Pulmonary and Critical Care Medicine, The First Hospital of Qinhuangdao, Qinhuangdao, Hebei 066000, China
| | - Shuo Zhao
- School of Electrical Engineering, Yanshan University, Qinhuangdao 066004, China
| | - Wanyi Qin
- School of Electrical Engineering, Yanshan University, Qinhuangdao 066004, China
| | - Xijun Wu
- School of Electrical Engineering, Yanshan University, Qinhuangdao 066004, China
| | - Shufeng Xu
- Department of Pulmonary and Critical Care Medicine, The First Hospital of Qinhuangdao, Qinhuangdao, Hebei 066000, China
| | - Yungang Zhang
- School of Electrical Engineering, Yanshan University, Qinhuangdao 066004, China
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2
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Liu J, Qin M, Shi Y, Jiang R, Wang Z, Zhang L, Zhao Y, Gao H, Li M, Huang C. Volatile carbonyl metabolites analysis of nanoparticle exposed lung cells in an organ-on-a-chip system. Talanta 2024; 274:126066. [PMID: 38599125 DOI: 10.1016/j.talanta.2024.126066] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2023] [Revised: 03/29/2024] [Accepted: 04/05/2024] [Indexed: 04/12/2024]
Abstract
The evaluation of nanoparticles (NPs) cytotoxicity is crucial for advancing nanotechnology and assessing environmental pollution. However, existing methods for NPs cytotoxicity evaluation suffer from limited accuracy and inadequate information content. In the study, we developed a novel detection platform that enables the identification of cellular carbonyl metabolites at the organ level. The platform is integrated with a cell co-culture lung organ chip (LOC) and a micropillar concentrator. Notably, our work represents the successful measurement of the amounts of cellular metabolites on LOC system. The volatile carbonyl metabolites (VCMs) generated by cells exposure to various types of NPs with different concentrations were captured and detected by high-resolution mass spectrometry (MS). Compared with conventional cell viability and reactive oxygen species (ROS) analysis, our method discerns the toxicological impact of NPs at low concentrations by analyzed VCM at levels as low as ppb level. The LOC system based metabolic gas detection confirmed that low concentrations of NPs have a toxic effect on the cell model, which was not reflected in the fluorescence detection, and the effect of NP material is more significant than the size effect. Furthermore, this method can distinguish different NPs acting on cell models through cluster analysis of multiple VCMs.
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Affiliation(s)
- Jinlong Liu
- Institute of Microelectronics of the Chinese Academy of Sciences, China; University of Chinese Academy of Science, China
| | - Meiyan Qin
- Institute of Microelectronics of the Chinese Academy of Sciences, China; University of Chinese Academy of Science, China
| | - Yimin Shi
- Institute of Microelectronics of the Chinese Academy of Sciences, China; University of Chinese Academy of Science, China
| | - Rui Jiang
- Institute of Microelectronics of the Chinese Academy of Sciences, China; University of Chinese Academy of Science, China
| | - Zizhen Wang
- Institute of Microelectronics of the Chinese Academy of Sciences, China; University of Chinese Academy of Science, China
| | - Lingqian Zhang
- Institute of Microelectronics of the Chinese Academy of Sciences, China
| | - Yang Zhao
- Institute of Microelectronics of the Chinese Academy of Sciences, China
| | - Hang Gao
- Institute of Microelectronics of the Chinese Academy of Sciences, China
| | - Mingxiao Li
- Institute of Microelectronics of the Chinese Academy of Sciences, China.
| | - Chengjun Huang
- Institute of Microelectronics of the Chinese Academy of Sciences, China; University of Chinese Academy of Science, China
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Xie Z, Morris JD, Pan J, Cooke EA, Sutaria SR, Balcom D, Marimuthu S, Parrish LW, Aliesky H, Huang JJ, Rai SN, Arnold FW, Huang J, Nantz MH, Fu XA. Detection of COVID-19 by quantitative analysis of carbonyl compounds in exhaled breath. Sci Rep 2024; 14:14568. [PMID: 38914586 PMCID: PMC11196736 DOI: 10.1038/s41598-024-61735-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2023] [Accepted: 05/09/2024] [Indexed: 06/26/2024] Open
Abstract
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.
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Affiliation(s)
- Zhenzhen Xie
- Department of Chemical Engineering, University of Louisville, Louisville, KY, USA
| | - James D Morris
- Department of Chemical Engineering, University of Louisville, Louisville, KY, USA
| | - Jianmin Pan
- Division of Biostatistics and Bioinformatics, Department of Environmental and Public Health Sciences, University of Cincinnati College of Medicine, Cincinnati, OH, USA
- The Cancer Data Science Center, University of Cincinnati College of Medicine, Cincinnati, OH, USA
- Biostatistics and Informatics Shared Resource, University of Cincinnati Cancer Center, Cincinnati, OH, USA
| | - Elizabeth A Cooke
- Department of Anesthesiology and Perioperative Medicine, University of Louisville, Louisville, KY, USA
| | - Saurin R Sutaria
- Department of Chemistry, University of Louisville, Louisville, KY, USA
| | - Dawn Balcom
- Division of Infectious Diseases, Department of Medicine, University of Louisville, Louisville, KY, USA
| | - Subathra Marimuthu
- Division of Infectious Diseases, Department of Medicine, University of Louisville, Louisville, KY, USA
| | - Leslie W Parrish
- Division of Infectious Diseases, Department of Medicine, University of Louisville, Louisville, KY, USA
| | - Holly Aliesky
- Division of Infectious Diseases, Department of Medicine, University of Louisville, Louisville, KY, USA
| | | | - Shesh N Rai
- Division of Biostatistics and Bioinformatics, Department of Environmental and Public Health Sciences, University of Cincinnati College of Medicine, Cincinnati, OH, USA
- The Cancer Data Science Center, University of Cincinnati College of Medicine, Cincinnati, OH, USA
- Biostatistics and Informatics Shared Resource, University of Cincinnati Cancer Center, Cincinnati, OH, USA
| | - Forest W Arnold
- Division of Infectious Diseases, Department of Medicine, University of Louisville, Louisville, KY, USA
| | - Jiapeng Huang
- Department of Anesthesiology and Perioperative Medicine, University of Louisville, Louisville, KY, USA.
| | - Michael H Nantz
- Department of Chemistry, University of Louisville, Louisville, KY, USA.
| | - Xiao-An Fu
- Department of Chemical Engineering, University of Louisville, Louisville, KY, USA.
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Bartold K, Iskierko Z, Sharma PS, Lin HY, Kutner W. Idiopathic pulmonary fibrosis (IPF): Diagnostic routes using novel biomarkers. Biomed J 2024; 47:100729. [PMID: 38657859 DOI: 10.1016/j.bj.2024.100729] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2023] [Revised: 03/19/2024] [Accepted: 04/14/2024] [Indexed: 04/26/2024] Open
Abstract
Idiopathic pulmonary fibrosis (IPF) diagnosis is still the diagnosis of exclusion. Differentiating from other forms of interstitial lung diseases (ILDs) is essential, given the various therapeutic approaches. The IPF course is now unpredictable for individual patients, although some genetic factors and several biomarkers have already been associated with various IPF prognoses. Since its early stages, IPF may be asymptomatic, leading to a delayed diagnosis. The present review critically examines the recent literature on molecular biomarkers potentially useful in IPF diagnostics. The examined biomarkers are grouped into breath and sputum biomarkers, serologically assessed extracellular matrix neoepitope markers, and oxidative stress biomarkers in lung tissue. Fibroblasts and complete blood count have also gained recent interest in that respect. Although several biomarker candidates have been profiled, there has yet to be a single biomarker that proved specific to the IPF disease. Nevertheless, various IPF biomarkers have been used in preclinical and clinical trials to verify their predictive and monitoring potential.
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Affiliation(s)
- Katarzyna Bartold
- Institute of Physical Chemistry, Polish Academy of Sciences, Warsaw, Poland
| | - Zofia Iskierko
- Institute of Physical Chemistry, Polish Academy of Sciences, Warsaw, Poland
| | | | - Hung-Yin Lin
- Department of Chemical and Materials Engineering, National University of Kaohsiung, Taiwan
| | - Wlodzimierz Kutner
- Institute of Physical Chemistry, Polish Academy of Sciences, Warsaw, Poland; Faculty of Mathematics and Natural Sciences, School of Sciences, Cardinal Stefan Wyszynski University in Warsaw, Warsaw, Poland.
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Taylor MJ, Chitwood CP, Xie Z, Miller HA, van Berkel VH, Fu XA, Frieboes HB, Suliman SA. Disease diagnosis and severity classification in pulmonary fibrosis using carbonyl volatile organic compounds in exhaled breath. Respir Med 2024; 222:107534. [PMID: 38244700 DOI: 10.1016/j.rmed.2024.107534] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/09/2023] [Revised: 01/12/2024] [Accepted: 01/15/2024] [Indexed: 01/22/2024]
Abstract
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.
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Affiliation(s)
- Matthew J Taylor
- Division of Pulmonary Medicine, University of Louisville, Louisville, KY, USA
| | - Corey P Chitwood
- Department of Bioengineering, University of Louisville, Louisville, KY, USA
| | - Zhenzhen Xie
- Department of Chemical Engineering, University of Louisville, Louisville, KY, USA
| | - Hunter A Miller
- Department of Bioengineering, University of Louisville, Louisville, KY, USA
| | - Victor H van Berkel
- Department of Cardiovascular and Thoracic Surgery, University of Louisville, Louisville, KY, USA
| | - Xiao-An Fu
- Department of Chemical Engineering, University of Louisville, Louisville, KY, USA.
| | - Hermann B Frieboes
- Department of Bioengineering, University of Louisville, Louisville, KY, USA; Department of Pharmacology/Toxicology, University of Louisville, Louisville, KY, USA; James Graham Brown Cancer Center, University of Louisville, Louisville, KY, USA; Center for Predictive Medicine, University of Louisville, Louisville, KY, USA.
| | - Sally A Suliman
- Banner University Medical Center, Phoenix, AZ, USA; Formerly at: Division of Pulmonary Medicine, University of Louisville, Louisville, KY, USA.
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Wang W, Yang Y, Chen Z, Wang X, Zhang GL, He T, Tong L, Tang B. Simultaneous Detection of Aldehyde Metabolites by Light-Assisted Ambient Ionization Mass Spectrometry. Anal Chem 2024; 96:787-793. [PMID: 38170819 DOI: 10.1021/acs.analchem.3c04124] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2024]
Abstract
In the clinic, small-molecule metabolites (SMMs) in blood are highly convincing indicators for disease diagnosis, such as cancer. However, challenges still exist for detection of SMMs due to their low concentration and complicated components in blood. In this work, we report the design of a novel "selenium signature" nanoprobe (Se nanoprobe) for efficient identification of multiple aldehyde metabolites in blood. This Se nanoprobe consists of magnetic nanoparticles that can enrich aldehyde metabolites from a complex environment, functionalized with photosensitive "selenium signature" hydrazide molecules that can react with aldehyde metabolites. Upon irradiation with UV, the aldehyde derivatives can be released from the Se nanoprobe and further sprayed by mass spectrometry through ambient ionization (AIMS). By quantifying the selenium isotope distribution (MS/MS) from the derivatization product, accurate detection of several aldehyde metabolites, including valeraldehyde (Val), heptaldehyde (Hep), 2-furaldehyde (2-Fur), 10-undecenal aldehyde (10-Und), and benzaldehyde (Ben), is realized. This strategy reveals a new solution for quick and accurate cancer diagnosis in the clinic.
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Affiliation(s)
- Weiqing Wang
- College of Chemistry, Chemical Engineering and Materials Science, Collaborative Innovation Centre of Functionalized Probes for Chemical Imaging in Universities of Shandong, Key Laboratory of Molecular and Nano Probes, Ministry of Education, Shandong Normal University, Jinan 250014, China
| | - Yanmei Yang
- College of Chemistry, Chemical Engineering and Materials Science, Collaborative Innovation Centre of Functionalized Probes for Chemical Imaging in Universities of Shandong, Key Laboratory of Molecular and Nano Probes, Ministry of Education, Shandong Normal University, Jinan 250014, China
| | - Zhenzhen Chen
- College of Chemistry, Chemical Engineering and Materials Science, Collaborative Innovation Centre of Functionalized Probes for Chemical Imaging in Universities of Shandong, Key Laboratory of Molecular and Nano Probes, Ministry of Education, Shandong Normal University, Jinan 250014, China
| | - Xiaoxiao Wang
- College of Chemistry, Chemical Engineering and Materials Science, Collaborative Innovation Centre of Functionalized Probes for Chemical Imaging in Universities of Shandong, Key Laboratory of Molecular and Nano Probes, Ministry of Education, Shandong Normal University, Jinan 250014, China
| | - Guang-Lu Zhang
- College of Chemistry, Chemical Engineering and Materials Science, Collaborative Innovation Centre of Functionalized Probes for Chemical Imaging in Universities of Shandong, Key Laboratory of Molecular and Nano Probes, Ministry of Education, Shandong Normal University, Jinan 250014, China
| | - Tairan He
- College of Chemistry, Chemical Engineering and Materials Science, Collaborative Innovation Centre of Functionalized Probes for Chemical Imaging in Universities of Shandong, Key Laboratory of Molecular and Nano Probes, Ministry of Education, Shandong Normal University, Jinan 250014, China
| | - Lili Tong
- College of Chemistry, Chemical Engineering and Materials Science, Collaborative Innovation Centre of Functionalized Probes for Chemical Imaging in Universities of Shandong, Key Laboratory of Molecular and Nano Probes, Ministry of Education, Shandong Normal University, Jinan 250014, China
| | - Bo Tang
- College of Chemistry, Chemical Engineering and Materials Science, Collaborative Innovation Centre of Functionalized Probes for Chemical Imaging in Universities of Shandong, Key Laboratory of Molecular and Nano Probes, Ministry of Education, Shandong Normal University, Jinan 250014, China
- Laoshan Laboratory, Qingdao 266237, P. R. China
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Katsaros G, Smith SA, Shacklette S, Trivedi J, Garr S, Parrish LW, Xie Z, Fu XA, Powell K, Pantalos G, van Berkel V. Identification of a marker of infection in the breath using a porcine pneumonia model. JTCVS OPEN 2023; 16:1063-1069. [PMID: 38204632 PMCID: PMC10775109 DOI: 10.1016/j.xjon.2023.10.025] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/22/2023] [Revised: 09/22/2023] [Accepted: 10/14/2023] [Indexed: 01/12/2024]
Abstract
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.
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Affiliation(s)
- Gianna Katsaros
- Department of Cardiovascular and Thoracic Surgery, University of Louisville School of Medicine, Louisville, Ky
| | - Susan Ansley Smith
- Department of Surgery, University of Louisville School of Medicine, Louisville, Ky
| | - Sienna Shacklette
- Department of Bioengineering, University of Louisville Speed School of Engineering, Louisville, Ky
| | - Jaimin Trivedi
- Department of Cardiovascular and Thoracic Surgery, University of Louisville School of Medicine, Louisville, Ky
| | - Stephanie Garr
- Department of Medicine, University of Louisville School of Medicine, Louisville, Ky
| | - Leslie Wolf Parrish
- Department of Medicine, University of Louisville School of Medicine, Louisville, Ky
| | - Zhenzhen Xie
- Department of Chemical Engineering, University of Louisville Speed School of Engineering, Louisville, Ky
| | - Xiao-An Fu
- Department of Chemical Engineering, University of Louisville Speed School of Engineering, Louisville, Ky
| | - Karen Powell
- Comparative Medicine Research Unit, University of Louisville, Louisville, Ky
| | - George Pantalos
- Department of Cardiovascular and Thoracic Surgery, University of Louisville School of Medicine, Louisville, Ky
| | - Victor van Berkel
- Department of Cardiovascular and Thoracic Surgery, University of Louisville School of Medicine, Louisville, Ky
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Sutaria SR, Morris JD, Xie Z, Cooke EA, Silvers SM, Long GA, Balcom D, Marimuthu S, Parrish LW, Aliesky H, Arnold FW, Huang J, Fu XA, Nantz MH. A feasibility study on exhaled breath analysis using UV spectroscopy to detect COVID-19. J Breath Res 2023; 18:016004. [PMID: 37875100 PMCID: PMC10620812 DOI: 10.1088/1752-7163/ad0646] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2023] [Revised: 09/14/2023] [Accepted: 10/24/2023] [Indexed: 10/26/2023]
Abstract
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.
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Affiliation(s)
- Saurin R Sutaria
- Departments of Chemistry, University of Louisville, Louisville, KY 40292, United States of America
| | - James D Morris
- Chemical Engineering, University of Louisville, Louisville, KY 40292, United States of America
| | - Zhenzhen Xie
- Chemical Engineering, University of Louisville, Louisville, KY 40292, United States of America
| | - Elizabeth A Cooke
- Anesthesiology and Perioperative Medicine, University of Louisville, Louisville, KY 40292, United States of America
| | - Shavonne M Silvers
- Anesthesiology and Perioperative Medicine, University of Louisville, Louisville, KY 40292, United States of America
| | - Grace A Long
- Anesthesiology and Perioperative Medicine, University of Louisville, Louisville, KY 40292, United States of America
| | - Dawn Balcom
- Division of Infectious Diseases, Department of Medicine, University of Louisville, Louisville, KY 40292, United States of America
| | - Subathra Marimuthu
- Division of Infectious Diseases, Department of Medicine, University of Louisville, Louisville, KY 40292, United States of America
| | - Leslie W Parrish
- Division of Infectious Diseases, Department of Medicine, University of Louisville, Louisville, KY 40292, United States of America
| | - Holly Aliesky
- Division of Infectious Diseases, Department of Medicine, University of Louisville, Louisville, KY 40292, United States of America
| | - Forest W Arnold
- Division of Infectious Diseases, Department of Medicine, University of Louisville, Louisville, KY 40292, United States of America
| | - Jiapeng Huang
- Anesthesiology and Perioperative Medicine, University of Louisville, Louisville, KY 40292, United States of America
| | - Xiao-An Fu
- Chemical Engineering, University of Louisville, Louisville, KY 40292, United States of America
| | - Michael H Nantz
- Departments of Chemistry, University of Louisville, Louisville, KY 40292, United States of America
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