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Poirier AC, Melin AD. Smell throughout the life course. Evol Anthropol 2024; 33:e22030. [PMID: 38704704 DOI: 10.1002/evan.22030] [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: 09/18/2023] [Revised: 04/12/2024] [Accepted: 04/18/2024] [Indexed: 05/07/2024]
Abstract
The sense of smell is an important mediator of health and sociality at all stages of life, yet it has received limited attention in our lineage. Olfaction starts in utero and participates in the establishment of social bonds in children, and of romantic and sexual relationships after puberty. Smell further plays a key role in food assessment and danger avoidance; in modern societies, it also guides our consumer behavior. Sensory abilities typically decrease with age and can be impacted by diseases, with repercussions on health and well-being. Here, we critically review our current understanding of human olfactory communication to refute outdated notions that our sense of smell is of low importance. We provide a summary of the biology of olfaction, give a prospective overview of the importance of the sense of smell throughout the life course, and conclude with an outline of the limitations and future directions in this field.
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Affiliation(s)
- Alice C Poirier
- Department of Anthropology and Archaeology, University of Calgary, Calgary, Alberta, Canada
| | - Amanda D Melin
- Department of Anthropology and Archaeology, University of Calgary, Calgary, Alberta, Canada
- Department of Medical Genetics, University of Calgary, Calgary, Alberta, Canada
- Alberta Children's Hospital Research Institute, Calgary, Alberta, Canada
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2
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Hakizimana A, Devani P, Gaillard EA. Current technological advancement in asthma care. Expert Rev Respir Med 2024; 18:499-512. [PMID: 38992946 DOI: 10.1080/17476348.2024.2380067] [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: 02/24/2024] [Accepted: 07/10/2024] [Indexed: 07/13/2024]
Abstract
INTRODUCTION Asthma is a common chronic respiratory disease affecting 262 million people globally, causing half a million deaths each year. Poor asthma outcomes are frequently due to non-adherence to medication, poor engagement with asthma services, and a lack of objective diagnostic tests. In recent years, technologies have been developed to improve diagnosis, monitoring, and care. AREAS COVERED Technology has impacted asthma care with the potential to improve patient outcomes, reduce healthcare costs, and provide personalized management. We focus on current evidence on home diagnostics and monitoring, remote asthma reviews, and digital smart inhalers. PubMed, Ovid/Embase, Cochrane Library, Scopus and Google Scholar were searched in November 2023 with no limit by year of publication. EXPERT OPINION Advanced diagnostic technologies have enabled early asthma detection and personalized treatment plans. Mobile applications and digital therapeutics empower patients to manage their condition and improve adherence to treatments. Telemedicine platforms and remote monitoring devices have the potential to streamline asthma care. AI algorithms can analyze patient data and predict exacerbations in proof-of-concept studies. Technology can potentially provide precision medicine to a wider patient group in the future, but further development is essential for implementation into routine care which in itself will be a major challenge.
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Affiliation(s)
- Ali Hakizimana
- Department of Paediatric Respiratory Medicine. Leicester Children's Hospital, University Hospitals Leicester, Leicester, UK
| | - Pooja Devani
- Department of Paediatric Respiratory Medicine. Leicester Children's Hospital, University Hospitals Leicester, Leicester, UK
- Department of Respiratory Sciences, Leicester NIHR Biomedical Research Centre (Respiratory Theme), University of Leicester, Leicester, UK
| | - Erol A Gaillard
- Department of Paediatric Respiratory Medicine. Leicester Children's Hospital, University Hospitals Leicester, Leicester, UK
- Department of Respiratory Sciences, Leicester NIHR Biomedical Research Centre (Respiratory Theme), University of Leicester, Leicester, UK
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3
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Long GA, Xu Q, Sunkara J, Woodbury R, Brown K, Huang JJ, Xie Z, Chen X, Fu XA, Huang J. A comprehensive meta-analysis and systematic review of breath analysis in detection of COVID-19 through Volatile organic compounds. Diagn Microbiol Infect Dis 2024; 109:116309. [PMID: 38692202 PMCID: PMC11405072 DOI: 10.1016/j.diagmicrobio.2024.116309] [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: 11/23/2023] [Revised: 04/16/2024] [Accepted: 04/17/2024] [Indexed: 05/03/2024]
Abstract
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.
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Affiliation(s)
- Grace A Long
- Department of Anesthesiology & Perioperative Medicine, University of Louisville, Louisville, KY, USA
| | - Qian Xu
- Biometrics and Data Science, Fosun Pharma, Beijing, PR China
| | - Jahnavi Sunkara
- Department of Anesthesiology & Perioperative Medicine, University of Louisville, Louisville, KY, USA
| | - Reagan Woodbury
- Department of Anesthesiology & Perioperative Medicine, University of Louisville, Louisville, KY, USA
| | - Katherine Brown
- Department of Anesthesiology & Perioperative Medicine, University of Louisville, Louisville, KY, USA
| | | | - Zhenzhen Xie
- Department of Chemical Engineering, University of Louisville, Louisville, KY, USA
| | - Xiaoyu Chen
- Department of Industrial and Systems Engineering, University at Buffalo, Buffalo, NY, USA.
| | - Xiao-An Fu
- Department of Chemical Engineering, University of Louisville, Louisville, KY, USA.
| | - Jiapeng Huang
- Department of Anesthesiology & Perioperative Medicine, University of Louisville, Louisville, KY, USA..
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Dragonieri S, Marco MD, Ahroud M, Quaranta VN, Portacci A, Iorillo I, Montagnolo F, Carpagnano GE. Electronic nose based analysis of exhaled volatile organic compounds spectrum reveals asthmatic shifts and consistency in controls post-exercise and spirometry. J Breath Res 2024; 18:036006. [PMID: 38876093 DOI: 10.1088/1752-7163/ad5864] [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: 05/23/2024] [Accepted: 06/14/2024] [Indexed: 06/16/2024]
Abstract
Analyzing exhaled volatile organic compounds (VOCs) with an electronic nose (e-nose) is emerging in medical diagnostics as a non-invasive, quick, and sensitive method for disease detection and monitoring. This study investigates if activities like spirometry or physical exercise affect exhaled VOCs measurements in asthmatics and healthy individuals, a crucial step for e-nose technology's validation for clinical use. The study analyzed exhaled VOCs using an e-nose in 27 healthy individuals and 27 patients with stable asthma, before and after performing spirometry and climbing five flights of stairs. Breath samples were collected using a validated technique and analyzed with a Cyranose 320 e-nose. In healthy controls, the exhaled VOCs spectrum remained unchanged after both lung function test and exercise. In asthmatics, principal component analysis and subsequent discriminant analysis revealed significant differences post-spirometry (vs. baseline 66.7% cross validated accuracy [CVA],p< 0.05) and exercise (vs. baseline 70.4% CVA,p< 0.05). E-nose measurements in healthy individuals are consistent, unaffected by spirometry or physical exercise. However, in asthma patients, significant changes in exhaled VOCs were detected post-activities, indicating airway responses likely due to constriction or inflammation, underscoring the e-nose's potential for respiratory condition diagnosis and monitoring.
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Affiliation(s)
| | | | - Madiha Ahroud
- Respiratory Diseases, University of Bari, Bari, Italy
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Zha C, Li L, Zhu F, Zhao Y. The Classification of VOCs Based on Sensor Images Using a Lightweight Neural Network for Lung Cancer Diagnosis. SENSORS (BASEL, SWITZERLAND) 2024; 24:2818. [PMID: 38732924 PMCID: PMC11086312 DOI: 10.3390/s24092818] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/15/2024] [Revised: 04/24/2024] [Accepted: 04/26/2024] [Indexed: 05/13/2024]
Abstract
The application of artificial intelligence to point-of-care testing (POCT) disease detection has become a hot research field, in which breath detection, which detects the patient's exhaled VOCs, combined with sensor arrays of convolutional neural network (CNN) algorithms as a new lung cancer detection is attracting more researchers' attention. However, the low accuracy, high-complexity computation and large number of parameters make the CNN algorithms difficult to transplant to the embedded system of POCT devices. A lightweight neural network (LTNet) in this work is proposed to deal with this problem, and meanwhile, achieve high-precision classification of acetone and ethanol gases, which are respiratory markers for lung cancer patients. Compared to currently popular lightweight CNN models, such as EfficientNet, LTNet has fewer parameters (32 K) and its training weight size is only 0.155 MB. LTNet achieved an overall classification accuracy of 99.06% and 99.14% in the own mixed gas dataset and the University of California (UCI) dataset, which are both higher than the scores of the six existing models, and it also offers the shortest training (844.38 s and 584.67 s) and inference times (23 s and 14 s) in the same validation sets. Compared to the existing CNN models, LTNet is more suitable for resource-limited POCT devices.
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Affiliation(s)
| | - Lei Li
- Department of Electronics and Electrical Engineering, Changchun University of Technology, Changchun 130012, China; (C.Z.); (F.Z.); (Y.Z.)
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Alfieri G, Modesti M, Riggi R, Bellincontro A. Recent Advances and Future Perspectives in the E-Nose Technologies Addressed to the Wine Industry. SENSORS (BASEL, SWITZERLAND) 2024; 24:2293. [PMID: 38610504 PMCID: PMC11014050 DOI: 10.3390/s24072293] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/29/2024] [Revised: 03/26/2024] [Accepted: 04/01/2024] [Indexed: 04/14/2024]
Abstract
Electronic nose devices stand out as pioneering innovations in contemporary technological research, addressing the arduous challenge of replicating the complex sense of smell found in humans. Currently, sensor instruments find application in a variety of fields, including environmental, (bio)medical, food, pharmaceutical, and materials production. Particularly the latter, has seen a significant increase in the adoption of technological tools to assess food quality, gradually supplanting human panelists and thus reshaping the entire quality control paradigm in the sector. This process is happening even more rapidly in the world of wine, where olfactory sensory analysis has always played a central role in attributing certain qualities to a wine. In this review, conducted using sources such as PubMed, Science Direct, and Web of Science, we examined papers published between January 2015 and January 2024. The aim was to explore prevailing trends in the use of human panels and sensory tools (such as the E-nose) in the wine industry. The focus was on the evaluation of wine quality attributes by paying specific attention to geographical origin, sensory defects, and monitoring of production trends. Analyzed results show that the application of E-nose-type sensors performs satisfactorily in that trajectory. Nevertheless, the integration of this type of analysis with more classical methods, such as the trained sensory panel test and with the application of destructive instrument volatile compound (VOC) detection (e.g., gas chromatography), still seems necessary to better explore and investigate the aromatic characteristics of wines.
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Affiliation(s)
| | | | | | - Andrea Bellincontro
- Department for Innovation in Biological, Agro-Food and Forest Systems, University of Tuscia, Via S. Camillo de Lellis, 01100 Viterbo, Italy; (G.A.); (M.M.); (R.R.)
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Seidl E, Licht JC, de Vries R, Ratjen F, Grasemann H. Exhaled Breath Analysis Detects the Clearance of Staphylococcus aureus from the Airways of Children with Cystic Fibrosis. Biomedicines 2024; 12:431. [PMID: 38398033 PMCID: PMC10887307 DOI: 10.3390/biomedicines12020431] [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: 01/12/2024] [Revised: 02/09/2024] [Accepted: 02/12/2024] [Indexed: 02/25/2024] Open
Abstract
BACKGROUND Electronic nose (eNose) technology can be used to characterize volatile organic compound (VOC) mixes in breath. While previous reports have shown that eNose can detect lung infections with pathogens such as Staphylococcus aureus (SA) in people with cystic fibrosis (CF), the clinical utility of eNose for longitudinally monitoring SA infection status is unknown. METHODS In this longitudinal study, a cloud-connected eNose, the SpiroNose, was used for the breath profile analysis of children with CF at two stable visits and compared based on changes in SA infection status between visits. Data analysis involved advanced sensor signal processing, ambient correction, and statistics based on the comparison of breath profiles between baseline and follow-up visits. RESULTS Seventy-two children with CF, with a mean (IQR) age of 13.8 (9.8-16.4) years, were studied. In those with SA-positive airway cultures at baseline but SA-negative cultures at follow-up (n = 19), significant signal differences were detected between Baseline and Follow-up at three distinct eNose sensors, i.e., S4 (p = 0.047), S6 (p = 0.014), and S7 (p = 0.014). Sensor signal changes with the clearance of SA from airways were unrelated to antibiotic treatment. No changes in sensor signals were seen in patients with unchanged infection status between visits. CONCLUSIONS Our results demonstrate the potential applicability of the eNose as a non-invasive clinical tool to longitudinally monitor pulmonary SA infection status in children with CF.
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Affiliation(s)
- Elias Seidl
- Division of Respiratory Medicine, Department of Pediatrics, The Hospital for Sick Children, Toronto, ON M5G 1X8, Canada; (E.S.); (J.-C.L.); (F.R.)
- Division of Respiratory Medicine, University Children’s Hospital Zurich, 8032 Zurich, Switzerland
| | - Johann-Christoph Licht
- Division of Respiratory Medicine, Department of Pediatrics, The Hospital for Sick Children, Toronto, ON M5G 1X8, Canada; (E.S.); (J.-C.L.); (F.R.)
| | - Rianne de Vries
- Breathomix BV, Bargelaan 200, 2333 CW Leiden, The Netherlands;
| | - Felix Ratjen
- Division of Respiratory Medicine, Department of Pediatrics, The Hospital for Sick Children, Toronto, ON M5G 1X8, Canada; (E.S.); (J.-C.L.); (F.R.)
- Translational Medicine Program, Research Institute, The Hospital for Sick Children, University of Toronto, Toronto, ON M5G 1X8, Canada
| | - Hartmut Grasemann
- Division of Respiratory Medicine, Department of Pediatrics, The Hospital for Sick Children, Toronto, ON M5G 1X8, Canada; (E.S.); (J.-C.L.); (F.R.)
- Translational Medicine Program, Research Institute, The Hospital for Sick Children, University of Toronto, Toronto, ON M5G 1X8, Canada
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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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Brener S, Snitz K, Sobel N. An electronic nose can identify humans by the smell of their ear. Chem Senses 2024; 49:bjad053. [PMID: 38237638 PMCID: PMC10810274 DOI: 10.1093/chemse/bjad053] [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: 05/28/2023] [Indexed: 01/27/2024] Open
Abstract
Terrestrial mammals identify conspecifics by body odor. Dogs can also identify humans by body odor, and in some instances, humans can identify other humans by body odor as well. Despite the potential for a powerful biometric tool, smell has not been systematically used for this purpose. A question arising in the application of smell to biometrics is which bodily odor source should we measure. Breath is an obvious candidate, but the associated humidity can challenge many sensing devices. The armpit is also a candidate source, but it is often doused in cosmetics. Here, we test the hypothesis that the ear may provide an effective source for odor-based biometrics. The inside of the ear has relatively constant humidity, cosmetics are not typically applied inside the ear, and critically, ears contain cerumen, a potent source of volatiles. We used an electronic nose to identify 12 individuals within and across days, using samples from the armpit, lower back, and ear. In an identification setting where chance was 8.33% (1 of 12), we found that we could identify a person by the smell of their ear within a day at up to ~87% accuracy (~10 of 12, binomial P < 10-5), and across days at up to ~22% accuracy (~3 of 12, binomial P < 0.012). We conclude that humans can indeed be identified from the smell of their ear, but the results did not imply a consistent advantage over other bodily odor sources.
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Affiliation(s)
- Stephanie Brener
- The Azrieli National Center for Human Brain Imaging and Research, Weizmann Institute of Science, Rehovot 7610001, Israel
- The Department for Brain Sciences, Weizmann Institute of Science, Rehovot 7610001, Israel
| | - Kobi Snitz
- The Azrieli National Center for Human Brain Imaging and Research, Weizmann Institute of Science, Rehovot 7610001, Israel
- The Department for Brain Sciences, Weizmann Institute of Science, Rehovot 7610001, Israel
| | - Noam Sobel
- The Azrieli National Center for Human Brain Imaging and Research, Weizmann Institute of Science, Rehovot 7610001, Israel
- The Department for Brain Sciences, Weizmann Institute of Science, Rehovot 7610001, Israel
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Moura PC, Raposo M, Vassilenko V. Breath biomarkers in Non-Carcinogenic diseases. Clin Chim Acta 2024; 552:117692. [PMID: 38065379 DOI: 10.1016/j.cca.2023.117692] [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: 11/10/2023] [Revised: 12/02/2023] [Accepted: 12/03/2023] [Indexed: 12/19/2023]
Abstract
The analysis of volatile organic compounds (VOCs) from human matrices like breath, perspiration, and urine has received increasing attention from academic and medical researchers worldwide. These biological-borne VOCs molecules have characteristics that can be directly related to physiologic and pathophysiologic metabolic processes. In this work, gathers a total of 292 analytes that have been identified as potential biomarkers for the diagnosis of various non-carcinogenic diseases. Herein we review the advances in VOCs with a focus on breath biomarkers and their potential role as minimally invasive tools to improve diagnosis prognosis and therapeutic monitoring.
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Affiliation(s)
- Pedro Catalão Moura
- Laboratory for Instrumentation, Biomedical Engineering and Radiation Physics (LIBPhys-UNL), Department of Physics, NOVA School of Science and Technology, NOVA University of Lisbon, Campus FCT-UNL, 2829-516, Caparica, Portugal.
| | - Maria Raposo
- Laboratory for Instrumentation, Biomedical Engineering and Radiation Physics (LIBPhys-UNL), Department of Physics, NOVA School of Science and Technology, NOVA University of Lisbon, Campus FCT-UNL, 2829-516, Caparica, Portugal.
| | - Valentina Vassilenko
- Laboratory for Instrumentation, Biomedical Engineering and Radiation Physics (LIBPhys-UNL), Department of Physics, NOVA School of Science and Technology, NOVA University of Lisbon, Campus FCT-UNL, 2829-516, Caparica, Portugal.
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Fitzgerald S, Holland L, Ahmed W, Piechulla B, Fowler SJ, Morrin A. Volatilomes of human infection. Anal Bioanal Chem 2024; 416:37-53. [PMID: 37843549 PMCID: PMC10758372 DOI: 10.1007/s00216-023-04986-z] [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: 07/31/2023] [Revised: 09/22/2023] [Accepted: 10/03/2023] [Indexed: 10/17/2023]
Abstract
The human volatilome comprises a vast mixture of volatile emissions produced by the human body and its microbiomes. Following infection, the human volatilome undergoes significant shifts, and presents a unique medium for non-invasive biomarker discovery. In this review, we examine how the onset of infection impacts the production of volatile metabolites that reflects dysbiosis by pathogenic microbes. We describe key analytical workflows applied across both microbial and clinical volatilomics and emphasize the value in linking microbial studies to clinical investigations to robustly elucidate the metabolic species and pathways leading to the observed volatile signatures. We review the current state of the art across microbial and clinical volatilomics, outlining common objectives and successes of microbial-clinical volatilomic workflows. Finally, we propose key challenges, as well as our perspectives on emerging opportunities for developing clinically useful and targeted workflows that could significantly enhance and expedite current practices in infection diagnosis and monitoring.
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Affiliation(s)
- Shane Fitzgerald
- SFI Insight Centre for Data Analytics, School of Chemical Sciences, National Centre for Sensor Research, Dublin City University, Dublin, Ireland
| | - Linda Holland
- School of Biotechnology, Dublin City University, Dublin, Ireland
| | - Waqar Ahmed
- Division of Immunology, Immunity to Infection and Respiratory Medicine, School of Biological Sciences, The University of Manchester, Manchester, UK
| | - Birgit Piechulla
- Institute of Biological Sciences, University of Rostock, Rostock, Germany
| | - Stephen J Fowler
- Division of Immunology, Immunity to Infection and Respiratory Medicine, School of Biological Sciences, The University of Manchester, Manchester, UK
- Respiratory Medicine, Manchester Academic Health Science Centre, Manchester University NHS Foundation Trust, Manchester, UK
| | - Aoife Morrin
- SFI Insight Centre for Data Analytics, School of Chemical Sciences, National Centre for Sensor Research, Dublin City University, Dublin, Ireland.
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Moura PC, Ribeiro PA, Raposo M, Vassilenko V. The State of the Art on Graphene-Based Sensors for Human Health Monitoring through Breath Biomarkers. SENSORS (BASEL, SWITZERLAND) 2023; 23:9271. [PMID: 38005657 PMCID: PMC10674474 DOI: 10.3390/s23229271] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/27/2023] [Revised: 11/13/2023] [Accepted: 11/17/2023] [Indexed: 11/26/2023]
Abstract
The field of organic-borne biomarkers has been gaining relevance due to its suitability for diagnosing pathologies and health conditions in a rapid, accurate, non-invasive, painless and low-cost way. Due to the lack of analytical techniques with features capable of analysing such a complex matrix as the human breath, the academic community has focused on developing electronic noses based on arrays of gas sensors. These sensors are assembled considering the excitability, sensitivity and sensing capacities of a specific nanocomposite, graphene. In this way, graphene-based sensors can be employed for a vast range of applications that vary from environmental to medical applications. This review work aims to gather the most relevant published papers under the scope of "Graphene sensors" and "Biomarkers" in order to assess the state of the art in the field of graphene sensors for the purposes of biomarker identification. During the bibliographic search, a total of six pathologies were identified as the focus of the work. They were lung cancer, gastric cancer, chronic kidney diseases, respiratory diseases that involve inflammatory processes of the airways, like asthma and chronic obstructive pulmonary disease, sleep apnoea and diabetes. The achieved results, current development of the sensing sensors, and main limitations or challenges of the field of graphene sensors are discussed throughout the paper, as well as the features of the experiments addressed.
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Affiliation(s)
| | | | | | - Valentina Vassilenko
- Laboratory for Instrumentation, Biomedical Engineering and Radiation Physics (LIBPhys-NOVA), Department of Physics, NOVA School of Science and Technology, NOVA University of Lisbon, Campus FCT-NOVA, 2829-516 Caparica, Portugal; (P.C.M.); (P.A.R.); (M.R.)
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13
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Seidl E, Licht JC, Wee WB, Post M, Ratjen F, Grasemann H. Exhaled Volatile Organic Compound Profiles Differ between Children with Primary Ciliary Dyskinesia and Cystic Fibrosis. Ann Am Thorac Soc 2023; 20:1667-1672. [PMID: 37555716 DOI: 10.1513/annalsats.202302-165rl] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2023] [Accepted: 08/08/2023] [Indexed: 08/10/2023] Open
Affiliation(s)
- Elias Seidl
- Division of Respiratory Medicine and Department of Pediatrics University of Toronto Toronto, Ontario, Canada
- Department of Pediatrics Ludwig Maximilian University of Munich Munich, Germany
| | - Johann-Christoph Licht
- Division of Respiratory Medicine and Department of Pediatrics University of Toronto Toronto, Ontario, Canada
- Translational Medicine Research Institute Toronto, Ontario, Canada
| | - Wallace B Wee
- Division of Respiratory Medicine and Department of Pediatrics University of Toronto Toronto, Ontario, Canada
| | - Martin Post
- Division of Respiratory Medicine and Department of Pediatrics University of Toronto Toronto, Ontario, Canada
| | - Felix Ratjen
- Division of Respiratory Medicine and Department of Pediatrics University of Toronto Toronto, Ontario, Canada
- Translational Medicine Research Institute Toronto, Ontario, Canada
| | - Hartmut Grasemann
- Division of Respiratory Medicine and Department of Pediatrics University of Toronto Toronto, Ontario, Canada
- Translational Medicine Research Institute Toronto, Ontario, Canada
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14
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Virtanen J, Roine A, Kontunen A, Karjalainen M, Numminen J, Oksala N, Rautiainen M, Kivekäs I. The Detection of Bacteria in the Maxillary Sinus Secretion of Patients With Acute Rhinosinusitis Using an Electronic Nose: A Pilot Study. Ann Otol Rhinol Laryngol 2023; 132:1330-1335. [PMID: 36691987 PMCID: PMC10498650 DOI: 10.1177/00034894231151301] [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] [Indexed: 01/25/2023]
Abstract
OBJECTIVE Detecting bacteria as a causative pathogen of acute rhinosinusitis (ARS) is a challenging task. Electronic nose technology is a novel method for detecting volatile organic compounds (VOCs) that has also been studied in association with the detection of several diseases. The aim of this pilot study was to analyze maxillary sinus secretion with differential mobility spectrometry (DMS) and to determine whether the secretion demonstrates a different VOC profile when bacteria are present. METHODS Adult patients with ARS symptoms were examined. Maxillary sinus contents were aspirated for bacterial culture and DMS analysis. k-Nearest neighbor and linear discriminant analysis were used to classify samples as positive or negative, using bacterial cultures as a reference. RESULTS A total of 26 samples from 15 patients were obtained. After leave-one-out cross-validation, k-nearest neighbor produced accuracy of 85%, sensitivity of 67%, specificity of 94%, positive predictive value of 86%, and negative predictive value of 84%. CONCLUSIONS The results of this pilot study suggest that bacterial positive and bacterial negative sinus secretion release different VOCs and that DMS has the potential to detect them. However, as the results are based on limited data, further conclusions cannot be made. DMS is a novel method in disease diagnostics and future studies should examine whether the method can detect bacterial ARS by analyzing exhaled air.
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Affiliation(s)
- Jussi Virtanen
- Department of Otorhinolaryngology, Head and Neck Surgery, Tampere University Hospital, Tampere, Finland
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Pirkanmaa, Finland
| | - Antti Roine
- Department of Surgery, Tampere University Hospital, Hatanpää Hospital, Tampere, Finland
- Olfactomics Ltd., Tampere, Finland
| | - Anton Kontunen
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Pirkanmaa, Finland
- Olfactomics Ltd., Tampere, Finland
| | - Markus Karjalainen
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Pirkanmaa, Finland
- Olfactomics Ltd., Tampere, Finland
| | - Jura Numminen
- Department of Otorhinolaryngology, Head and Neck Surgery, Tampere University Hospital, Tampere, Finland
| | - Niku Oksala
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Pirkanmaa, Finland
- Olfactomics Ltd., Tampere, Finland
- Vascular Centre, Tampere University Hospital, Tampere, Finland
| | - Markus Rautiainen
- Department of Otorhinolaryngology, Head and Neck Surgery, Tampere University Hospital, Tampere, Finland
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Pirkanmaa, Finland
| | - Ilkka Kivekäs
- Department of Otorhinolaryngology, Head and Neck Surgery, Tampere University Hospital, Tampere, Finland
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Pirkanmaa, Finland
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15
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Licht JC, Seidl E, Slingers G, Waters V, de Vries R, Post M, Ratjen F, Grasemann H. Exhaled breath profiles to detect lung infection with Staphylococcus aureus in children with cystic fibrosis. J Cyst Fibros 2023; 22:888-893. [PMID: 36849333 DOI: 10.1016/j.jcf.2023.02.010] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2022] [Revised: 12/23/2022] [Accepted: 02/20/2023] [Indexed: 02/27/2023]
Abstract
BACKGROUND An electronic nose (eNose) can be used to detect volatile organic compounds (VOCs). Exhaled breath contains numerous VOCs and individuals' VOCs mixtures create distinct breath profiles. Previous reports have shown that eNose can detect lung infections. Whether eNose can detect Staphylococcus aureus airway infections in breath of children with cystic fibrosis (CF) is currently unclear. METHODS In this cross-sectional observational study, a cloud-connected eNose was used for breath profile analysis of clinically stable paediatric CF patients with airway microbiology cultures positive or negative for CF pathogens. Data-analysis involved advanced signal processing, ambient correction and statistics based on linear discriminant and receiver operating characteristics (ROC) analyses. RESULTS Breath profiles from 100 children with CF (median predicted FEV1 91%) were obtained and analysed. CF patients with positive airway cultures for any CF pathogen were distinguishable from no CF pathogens (no growth or usual respiratory flora) with accuracy of 79.0% (AUC-ROC 0.791; 95% CI: 0.669-0.913) and between patients positive for Staphylococcus aureus (SA) only and no CF pathogen with accuracy of 74.0% (AUC-ROC 0.797; 95% CI: 0.698-0.896). Similar differences were seen for Pseudomonas aeruginosa (PA) infection vs no CF pathogens (78.0% accuracy, AUC-ROC 0.876, 95% CI: 0.794-0.958). SA- and PA-specific signatures were driven by different sensors in the SpiroNose suggesting pathogen-specific breath signatures. CONCLUSIONS Breath profiles of CF patients with SA in airway cultures are distinct from those with no infection or PA infection, suggesting the utility of eNose technology in the detection of this early CF pathogen in children with CF.
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Affiliation(s)
- Johann-Christoph Licht
- Division of Respiratory Medicine, Department of Pediatrics, Hospital for Sick Children, Toronto, ON M5G 1 X 8, Canada and University of Toronto; Translational Medicine, Research Institute, Hospital for Sick Children, Toronto, ON M5G 1 × 8, Canada
| | - Elias Seidl
- Division of Respiratory Medicine, Department of Pediatrics, Hospital for Sick Children, Toronto, ON M5G 1 X 8, Canada and University of Toronto
| | - Gitte Slingers
- Breathomix BV, Bargelaan 200, 2333 CW Leiden, the Netherlands
| | - Valerie Waters
- Translational Medicine, Research Institute, Hospital for Sick Children, Toronto, ON M5G 1 × 8, Canada; Division of Infectious Diseases, Department of Pediatrics, Hospital for Sick Children, Toronto, ON M5G 1 X 8, Canada and University of Toronto
| | - Rianne de Vries
- Breathomix BV, Bargelaan 200, 2333 CW Leiden, the Netherlands
| | - Martin Post
- Translational Medicine, Research Institute, Hospital for Sick Children, Toronto, ON M5G 1 × 8, Canada
| | - Felix Ratjen
- Division of Respiratory Medicine, Department of Pediatrics, Hospital for Sick Children, Toronto, ON M5G 1 X 8, Canada and University of Toronto; Translational Medicine, Research Institute, Hospital for Sick Children, Toronto, ON M5G 1 × 8, Canada
| | - Hartmut Grasemann
- Division of Respiratory Medicine, Department of Pediatrics, Hospital for Sick Children, Toronto, ON M5G 1 X 8, Canada and University of Toronto; Translational Medicine, Research Institute, Hospital for Sick Children, Toronto, ON M5G 1 × 8, Canada.
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16
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Tan SY, Ma Q, Li F, Jiang H, Peng XY, Dong J, Ye X, Wang QL, You FM, Fu X, Ren YF. Does the last 20 years paradigm of clinical research using volatile organic compounds to non-invasively diagnose cancer need to change? Challenges and future direction. J Cancer Res Clin Oncol 2023; 149:10377-10386. [PMID: 37273109 DOI: 10.1007/s00432-023-04940-7] [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: 05/02/2023] [Accepted: 05/24/2023] [Indexed: 06/06/2023]
Abstract
PURPOSE Volatile organic compounds (VOCs) have shown great potential as novel biomarkers for cancer detection; however, comprehensive quantitative analysis is lacking. In this study, we performed a bibliometric analysis of non-invasive cancer diagnosis using VOCs to better characterise international trends and to predict future hotspots in this field, and then we focussed on human studies to analyse clinical characteristics for presenting the current controversies and future perspectives of further clinical work. METHODS Publications, from 2002 to 2022, were retrieved from the Web of Science Core Collection database. CiteSpace and VOSviewer were used to generate network maps and identify the annual publications, top countries, authors, institutions, journals, references, and keywords. Then, we further screened clinical trials, and the key information was extracted into Microsoft Excel for further systematical analysis. RESULTS Six hundred and forty-one articles were identified to evaluate research trends, of which 301 clinical trials were selected for further systematical analysis. Overall, the annual publications in this area increased, with an overall upward trend, while the quality of clinical research remains remarkably uneven. CONCLUSION The study of non-invasive cancer diagnosis using VOCs would continue to be an active field. However, without stringent clinical design criteria, most suitable acquisition and analysis devices and statistical approaches, a list of exclusive, specific, reliable and reproducible VOCs to identify a disease and these VOCs appearing in a breath at detectable levels at early stage disease, the clinical utility of VOC tests will be difficult to have any breakthroughs.
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Affiliation(s)
- Shi-Yan Tan
- Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, 610072, Sichuan, China
| | - Qiong Ma
- Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, 610072, Sichuan, China
| | - Fang Li
- Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, 610072, Sichuan, China
| | - Hua Jiang
- Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, 610072, Sichuan, China
| | - Xiao-Yun Peng
- Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, 610072, Sichuan, China
| | - Jing Dong
- Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, 610072, Sichuan, China
| | - Xin Ye
- Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, 610072, Sichuan, China
| | - Qiao-Ling Wang
- Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, 610072, Sichuan, China
| | - Feng-Ming You
- Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, 610072, Sichuan, China
| | - Xi Fu
- Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, 610072, Sichuan, China.
| | - Yi-Feng Ren
- Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, 610072, Sichuan, China.
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17
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Moura PC, Raposo M, Vassilenko V. Breath volatile organic compounds (VOCs) as biomarkers for the diagnosis of pathological conditions: A review. Biomed J 2023; 46:100623. [PMID: 37336362 PMCID: PMC10339195 DOI: 10.1016/j.bj.2023.100623] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2023] [Revised: 06/06/2023] [Accepted: 06/14/2023] [Indexed: 06/21/2023] Open
Abstract
Normal and abnormal/pathological status of physiological processes in the human organism can be characterized through Volatile Organic Compounds (VOCs) emitted in breath. Recently, a wide range of volatile analytes has risen as biomarkers. These compounds have been addressed in the scientific and medical communities as an extremely valuable metabolic window. Once collected and analysed, VOCs can represent a tool for a rapid, accurate, non-invasive, and painless diagnosis of several diseases and health conditions. These biomarkers are released by exhaled breath, urine, faeces, skin, and several other ways, at trace concentration levels, usually in the ppbv (μg/L) range. For this reason, the analytical techniques applied for detecting and clinically exploiting the VOCs are extremely important. The present work reviews the most promising results in the field of breath biomarkers and the most common methods of detection of VOCs. A total of 16 pathologies and the respective database of compounds are addressed. An updated version of the VOCs biomarkers database can be consulted at: https://neomeditec.com/VOCdatabase/.
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Affiliation(s)
- Pedro Catalão Moura
- Laboratory for Instrumentation, Biomedical Engineering and Radiation Physics (LIBPhys-UNL), NOVA School of Science and Technology, NOVA University of Lisbon, Campus FCT-UNL, Caparica, Portugal
| | - Maria Raposo
- Laboratory for Instrumentation, Biomedical Engineering and Radiation Physics (LIBPhys-UNL), NOVA School of Science and Technology, NOVA University of Lisbon, Campus FCT-UNL, Caparica, Portugal.
| | - Valentina Vassilenko
- Laboratory for Instrumentation, Biomedical Engineering and Radiation Physics (LIBPhys-UNL), NOVA School of Science and Technology, NOVA University of Lisbon, Campus FCT-UNL, Caparica, Portugal.
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18
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Dragonieri S, Quaranta VN, Portacci A, Ahroud M, Di Marco M, Ranieri T, Carpagnano GE. Effect of Food Intake on Exhaled Volatile Organic Compounds Profile Analyzed by an Electronic Nose. Molecules 2023; 28:5755. [PMID: 37570725 PMCID: PMC10420885 DOI: 10.3390/molecules28155755] [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: 06/08/2023] [Revised: 07/25/2023] [Accepted: 07/27/2023] [Indexed: 08/13/2023] Open
Abstract
Exhaled breath analysis using an e-nose is a groundbreaking tool for exhaled volatile organic compound (VOC) analysis, which has already shown its applicability in several respiratory and systemic diseases. It is still unclear whether food intake can be considered a confounder when analyzing the VOC-profile. We aimed to assess whether an e-nose can discriminate exhaled breath before and after predefined food intake at different time periods. We enrolled 28 healthy non-smoking adults and collected their exhaled breath as follows: (a) before food intake, (b) within 5 min after food consumption, (c) within 1 h after eating, and (d) within 2 h after eating. Exhaled breath was collected by a formerly validated method and analyzed by an e-nose (Cyranose 320). By principal component analysis, significant variations in the exhaled VOC-profile were shown for principal component 1 (capturing 63.4% of total variance) when comparing baseline vs. 5 min and vs. 1 h after food intake (both p < 0.05). No significance was shown in the comparison between baseline and 2 h after food intake. Therefore, the exhaled VOC-profile seems to be influenced by very recent food intake. Interestingly, two hours might be sufficient to avoid food induced alterations of exhaled VOC-spectrum when sampling for research protocols.
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Affiliation(s)
- Silvano Dragonieri
- Department of Respiratory Diseases, University of Bari “Aldo Moro”, 70121 Bari, Italy; (V.N.Q.); (A.P.); (M.A.); (M.D.M.); (T.R.); (G.E.C.)
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19
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Savito L, Scarlata S, Bikov A, Carratù P, Carpagnano GE, Dragonieri S. Exhaled volatile organic compounds for diagnosis and monitoring of asthma. World J Clin Cases 2023; 11:4996-5013. [PMID: 37583852 PMCID: PMC10424019 DOI: 10.12998/wjcc.v11.i21.4996] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/17/2023] [Revised: 06/08/2023] [Accepted: 07/06/2023] [Indexed: 07/26/2023] Open
Abstract
The asthmatic inflammatory process results in the generation of volatile organic compounds (VOCs), which are subsequently secreted by the airways. The study of these elements through gas chromatography-mass spectrometry (GC-MS), which can identify individual molecules with a discriminatory capacity of over 85%, and electronic-Nose (e-NOSE), which is able to perform a quick onboard pattern-recognition analysis of VOCs, has allowed new prospects for non-invasive analysis of the disease in an "omics" approach. In this review, we aim to collect and compare the progress made in VOCs analysis using the two methods and their instrumental characteristics. Studies have described the potential of GC-MS and e-NOSE in a multitude of relevant aspects of the disease in both children and adults, as well as differential diagnosis between asthma and other conditions such as wheezing, cystic fibrosis, COPD, allergic rhinitis and last but not least, the accuracy of these methods compared to other diagnostic tools such as lung function, FeNO and eosinophil count. Due to significant limitations of both methods, it is still necessary to improve and standardize techniques. Currently, e-NOSE appears to be the most promising aid in clinical practice, whereas GC-MS, as the gold standard for the structural analysis of molecules, remains an essential tool in terms of research for further studies on the pathophysiologic pathways of the asthmatic inflammatory process. In conclusion, the study of VOCs through GC-MS and e-NOSE appears to hold promise for the non-invasive diagnosis, assessment, and monitoring of asthma, as well as for further research studies on the disease.
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Affiliation(s)
- Luisa Savito
- Department of Internal Medicine, Unit of Respiratory Pathophysiology and Thoracic Endoscopy, Fondazione Policlinico Universitario Campus Bio Medico, Rome 00128, Italy
| | - Simone Scarlata
- Department of Internal Medicine, Unit of Respiratory Pathophysiology and Thoracic Endoscopy, Fondazione Policlinico Universitario Campus Bio Medico, Rome 00128, Italy
| | - Andras Bikov
- Wythenshawe Hospital, Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester M13 9WL, United Kingdom
- Division of Infection, Immunity and Respiratory Medicine, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester M13 9PT, United Kingdom
| | - Pierluigi Carratù
- Department of Internal Medicine "A.Murri", University of Bari "Aldo Moro", Bari 70124, Italy
| | | | - Silvano Dragonieri
- Department of Respiratory Diseases, University of Bari, Bari 70124, Italy
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20
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Scotney E, Fleming L, Saglani S, Sonnappa S, Bush A. Advances in the pathogenesis and personalised treatment of paediatric asthma. BMJ MEDICINE 2023; 2:e000367. [PMID: 37841968 PMCID: PMC10568124 DOI: 10.1136/bmjmed-2022-000367] [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: 09/13/2022] [Accepted: 05/05/2023] [Indexed: 10/17/2023]
Abstract
The diversity of pathology of severe paediatric asthma demonstrates that the one-size-fits-all approach characterising many guidelines is inappropriate. The term "asthma" is best used to describe a clinical syndrome of wheeze, chest tightness, breathlessness, and sometimes cough, making no assumptions about underlying pathology. Before personalising treatment, it is essential to make the diagnosis correctly and optimise basic management. Clinicians must determine exactly what type of asthma each child has. We are moving from describing symptom patterns in preschool wheeze to describing multiple underlying phenotypes with implications for targeting treatment. Many new treatment options are available for school age asthma, including biological medicines targeting type 2 inflammation, but a paucity of options are available for non-type 2 disease. The traditional reliever treatment, shortacting β2 agonists, is being replaced by combination inhalers containing inhaled corticosteroids and fast, longacting β2 agonists to treat the underlying inflammation in even mild asthma and reduce the risk of asthma attacks. However, much decision making is still based on adult data extrapolated to children. Better inclusion of children in future research studies is essential, if children are to benefit from these new advances in asthma treatment.
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Affiliation(s)
- Elizabeth Scotney
- National Heart and Lung Institute, Imperial College London, London, UK
- Royal Brompton Hospital, London, UK
| | - Louise Fleming
- National Heart and Lung Institute, Imperial College London, London, UK
- Royal Brompton Hospital, London, UK
- Centre for Paediatrics and Child Health, Imperial College London, London, UK
| | - Sejal Saglani
- National Heart and Lung Institute, Imperial College London, London, UK
- Royal Brompton Hospital, London, UK
- Centre for Paediatrics and Child Health, Imperial College London, London, UK
| | - Samatha Sonnappa
- National Heart and Lung Institute, Imperial College London, London, UK
- Royal Brompton Hospital, London, UK
- Centre for Paediatrics and Child Health, Imperial College London, London, UK
| | - Andrew Bush
- National Heart and Lung Institute, Imperial College London, London, UK
- Royal Brompton Hospital, London, UK
- Centre for Paediatrics and Child Health, Imperial College London, London, UK
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21
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Sas V, Cherecheș-Panța P, Borcau D, Schnell CN, Ichim EG, Iacob D, Coblișan AP, Drugan T, Man SC. Breath Prints for Diagnosing Asthma in Children. J Clin Med 2023; 12:jcm12082831. [PMID: 37109167 PMCID: PMC10146639 DOI: 10.3390/jcm12082831] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2023] [Revised: 04/04/2023] [Accepted: 04/10/2023] [Indexed: 04/29/2023] Open
Abstract
Electronic nose (e-nose) is a new technology applied for the identification of volatile organic compounds (VOC) in breath air. Measuring VOC in exhaled breath can adequately identify airway inflammation, especially in asthma. Its noninvasive character makes e-nose an attractive technology applicable in pediatrics. We hypothesized that an electronic nose could discriminate the breath prints of patients with asthma from controls. A cross-sectional study was conducted and included 35 pediatric patients. Eleven cases and seven controls formed the two training models (models A and B). Another nine cases and eight controls formed the external validation group. Exhaled breath samples were analyzed using Cyranose 320, Smith Detections, Pasadena, CA, USA. The discriminative ability of breath prints was investigated by principal component analysis (PCA) and canonical discriminative analysis (CDA). Cross-validation accuracy (CVA) was calculated. For the external validation step, accuracy, sensitivity and specificity were calculated. Duplicate sampling of exhaled breath was obtained for ten patients. E-nose was able to discriminate between the controls and asthmatic patient group with a CVA of 63.63% and an M-distance of 3.13 for model A and a CVA of 90% and an M-distance of 5.55 for model B in the internal validation step. In the second step of external validation, accuracy, sensitivity and specificity were 64%, 77% and 50%, respectively, for model A, and 58%, 66% and 50%, respectively, for model B. Between paired breath sample fingerprints, there were no significant differences. An electronic nose can discriminate pediatric patients with asthma from controls, but the accuracy obtained in the external validation was lower than the CVA obtained in the internal validation step.
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Affiliation(s)
- Valentina Sas
- Department of Pediatrics, "Iuliu Hațieganu" University of Medicine and Pharmacy Cluj-Napoca, 400124 Cluj-Napoca, Romania
- Clinical Hospital for Pediatric Emergencies, 400124 Cluj-Napoca, Romania
| | - Paraschiva Cherecheș-Panța
- Department of Pediatrics, "Iuliu Hațieganu" University of Medicine and Pharmacy Cluj-Napoca, 400124 Cluj-Napoca, Romania
- Clinical Hospital for Pediatric Emergencies, 400124 Cluj-Napoca, Romania
| | - Diana Borcau
- Clinical Hospital for Pediatric Emergencies, 400124 Cluj-Napoca, Romania
| | - Cristina-Nicoleta Schnell
- Department of Pediatrics, "Iuliu Hațieganu" University of Medicine and Pharmacy Cluj-Napoca, 400124 Cluj-Napoca, Romania
- Clinical Hospital for Pediatric Emergencies, 400124 Cluj-Napoca, Romania
| | - Edita-Gabriela Ichim
- Department of Pediatrics, "Iuliu Hațieganu" University of Medicine and Pharmacy Cluj-Napoca, 400124 Cluj-Napoca, Romania
- Clinical Hospital for Pediatric Emergencies, 400124 Cluj-Napoca, Romania
| | - Daniela Iacob
- Department of Pediatrics, "Iuliu Hațieganu" University of Medicine and Pharmacy Cluj-Napoca, 400124 Cluj-Napoca, Romania
- Clinical Hospital for Pediatric Emergencies, 400124 Cluj-Napoca, Romania
| | - Alina-Petronela Coblișan
- Clinical Hospital for Pediatric Emergencies, 400124 Cluj-Napoca, Romania
- Department of Nursing, "Iuliu Hațieganu" University of Medicine and Pharmacy Cluj-Napoca, 400124 Cluj-Napoca, Romania
| | - Tudor Drugan
- Department of Medical Informatics and Biostatistics, "Iuliu Hațieganu" University of Medicine and Pharmacy Cluj-Napoca, 400124 Cluj-Napoca, Romania
| | - Sorin-Claudiu Man
- Department of Pediatrics, "Iuliu Hațieganu" University of Medicine and Pharmacy Cluj-Napoca, 400124 Cluj-Napoca, Romania
- Clinical Hospital for Pediatric Emergencies, 400124 Cluj-Napoca, Romania
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22
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Li X, Guo J, Xu W, Cao J. Optimization of the Mixed Gas Detection Method Based on Neural Network Algorithm. ACS Sens 2023; 8:822-828. [PMID: 36701636 DOI: 10.1021/acssensors.2c02450] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/27/2023]
Abstract
Real-time mixed gas detection has attracted significant interest for being a key factor for applications of the electronic nose (E-nose). However, mixed gas detection still faces the challenge of long detection time and a large amount of training data. Therefore, in this work, we propose a feasible way to realize low-cost fast detection of mixed gases, which uses only the part response data of the adsorption process as the training set. Our results indicated that the proposed method significantly reduced the number of training sets and the prediction time of mixed gas. Moreover, it can achieve new concentration prediction of mixed gas using only the response data of the first 10 s, and the training set proportion can reduce to 60%. In addition, the convolutional neural network model can realize both the smaller training set but also the higher accuracy of mixed gas. Our findings provide an effective way to improve the detection efficiency and accuracy of E-noses for the experimental measurement.
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Affiliation(s)
- Xiulei Li
- Department of Physics & Hunan Institute of Advanced Sensing and Information Technology, Xiangtan University, Xiangtan411105, PR China
| | - Jiayi Guo
- Department of Physics & Hunan Institute of Advanced Sensing and Information Technology, Xiangtan University, Xiangtan411105, PR China
| | - Wangping Xu
- Department of Physics & Hunan Institute of Advanced Sensing and Information Technology, Xiangtan University, Xiangtan411105, PR China
| | - Juexian Cao
- Department of Physics & Hunan Institute of Advanced Sensing and Information Technology, Xiangtan University, Xiangtan411105, PR China
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23
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Epping R, Koch M. On-Site Detection of Volatile Organic Compounds (VOCs). Molecules 2023; 28:1598. [PMID: 36838585 PMCID: PMC9966347 DOI: 10.3390/molecules28041598] [Citation(s) in RCA: 16] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2023] [Revised: 02/03/2023] [Accepted: 02/05/2023] [Indexed: 02/11/2023] Open
Abstract
Volatile organic compounds (VOCs) are of interest in many different fields. Among them are food and fragrance analysis, environmental and atmospheric research, industrial applications, security or medical and life science. In the past, the characterization of these compounds was mostly performed via sample collection and off-site analysis with gas chromatography coupled to mass spectrometry (GC-MS) as the gold standard. While powerful, this method also has several drawbacks such as being slow, expensive, and demanding on the user. For decades, intense research has been dedicated to find methods for fast VOC analysis on-site with time and spatial resolution. We present the working principles of the most important, utilized, and researched technologies for this purpose and highlight important publications from the last five years. In this overview, non-selective gas sensors, electronic noses, spectroscopic methods, miniaturized gas chromatography, ion mobility spectrometry and direct injection mass spectrometry are covered. The advantages and limitations of the different methods are compared. Finally, we give our outlook into the future progression of this field of research.
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Affiliation(s)
- Ruben Epping
- Division of Organic Trace and Food Analysis, Bundesanstalt für Materialforschung und -Prüfung, 12489 Berlin, Germany
| | - Matthias Koch
- Division of Organic Trace and Food Analysis, Bundesanstalt für Materialforschung und -Prüfung, 12489 Berlin, Germany
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24
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Sun P, Shi Y, Shi Y. Multivariate Regression in Conjunction with GA-BP for Optimization of Data Processing of Trace NO Gas Flow in Active Pumping Electronic Nose. SENSORS (BASEL, SWITZERLAND) 2023; 23:1524. [PMID: 36772572 PMCID: PMC9919135 DOI: 10.3390/s23031524] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/23/2022] [Revised: 01/18/2023] [Accepted: 01/25/2023] [Indexed: 06/18/2023]
Abstract
Exhaled nitric oxide trace gas at the ppb level is a biomarker of human airway inflammation. To detect this, we developed a method for the collection of active pumping electronic nose bionic chamber gas. An optimization algorithm based on multivariate regression (MR) and genetic algorithm-back propagation (GA-BP) was proposed to improve the accuracy of trace-level gas detection. An electronic nose was used to detect NO gas at the ppb level by substituting breathing gas with a sample gas. The impact of the pump suction flow capacity variation on the response of the electronic nose system was determined using an ANOVA. Further, the optimization algorithm based on MR and GA-BP was studied for flow correction. The results of this study demonstrate an increase in the detection accuracy of the system by more than twofold, from 17.40%FS before correction to 6.86%FS after correction. The findings of this research lay the technical groundwork for the practical application of electronic nose systems in the daily monitoring of FeNO.
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Affiliation(s)
- Pengjiao Sun
- The Higher Educational Key Laboratory for Measuring & Control Technology and Instrumentation of Heilongjiang Province, Harbin University of Science and Technology, Harbin 150080, China
- Electronics and Communication Engineering School, Jilin Technology College of Electronic Information, Jilin 132021, China
| | - Yunbo Shi
- The Higher Educational Key Laboratory for Measuring & Control Technology and Instrumentation of Heilongjiang Province, Harbin University of Science and Technology, Harbin 150080, China
- Heilongjiang Province Key Laboratory of Laser Spectroscopy Technology and Application, Harbin University of Science and Technology, Harbin 150080, China
- National Experimental Teaching Demonstration Center for Measurement and Control Technology and Instrumentation, Harbin University of Science and Technology, Harbin 150080, China
| | - Yeping Shi
- The Higher Educational Key Laboratory for Measuring & Control Technology and Instrumentation of Heilongjiang Province, Harbin University of Science and Technology, Harbin 150080, China
- Electronics and Communication Engineering School, Jilin Technology College of Electronic Information, Jilin 132021, China
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Sun P, Shi Y, Shi Y. Bionic sensing system and characterization of exhaled nitric oxide detection based on canine olfaction. PLoS One 2022; 17:e0279003. [PMID: 36534648 PMCID: PMC9762597 DOI: 10.1371/journal.pone.0279003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2022] [Accepted: 11/28/2022] [Indexed: 12/24/2022] Open
Abstract
A quantitative monitoring system for fractional exhaled nitric oxide (FENO) in homes is very important for the control of respiratory diseases such as asthma. To this end, this paper proposes a small bionic sensing system for NO detection in an electronic nose based on analysis of the structure of the canine olfactory system and the airflow pattern in the nasal cavity. The proposed system detected NO at different FENO concentration levels with different bionic sensing systems in the electronic nose, and analyzed the data comparatively. Combined with a backpropagation neural network algorithm, the bionic canine sensing system improved the recognition rate for FENO detection by up to 98.1%. Moreover, electronic noses with a canine bionic sensing system can improve the performance of trace gas detection.
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Affiliation(s)
- Pengjiao Sun
- The Higher Educational Key Laboratory for Measuring & Control Technology and Instrumentation of Heilongjiang Province, Harbin University of Science and Technology, Harbin, China
- Electronics and Communication Engineering School, Jilin Technology College of Electronic Information, Jilin, China
| | - Yunbo Shi
- The Higher Educational Key Laboratory for Measuring & Control Technology and Instrumentation of Heilongjiang Province, Harbin University of Science and Technology, Harbin, China
- Heilongjiang Province Key Laboratory of Laser Spectroscopy Technology and Application, Harbin University of Science and Technology, Harbin, China
- National Experimental Teaching Demonstration Center for Measurement and Control Technology and Instrumentation, Harbin University of Science and Technology, Harbin, China
- * E-mail:
| | - Yeping Shi
- The Higher Educational Key Laboratory for Measuring & Control Technology and Instrumentation of Heilongjiang Province, Harbin University of Science and Technology, Harbin, China
- Electronics and Communication Engineering School, Jilin Technology College of Electronic Information, Jilin, China
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Anzivino R, Sciancalepore PI, Dragonieri S, Quaranta VN, Petrone P, Petrone D, Quaranta N, Carpagnano GE. The Role of a Polymer-Based E-Nose in the Detection of Head and Neck Cancer from Exhaled Breath. SENSORS (BASEL, SWITZERLAND) 2022; 22:6485. [PMID: 36080944 PMCID: PMC9460264 DOI: 10.3390/s22176485] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/16/2022] [Revised: 08/21/2022] [Accepted: 08/22/2022] [Indexed: 06/15/2023]
Abstract
The aim of our study was to assess whether a polymer-based e-nose can distinguish head and neck cancer subjects from healthy controls, as well as from patients with allergic rhinitis. A total number of 45 subjects participated in this study. The first group was composed of 15 patients with histology confirmed diagnosis of head and neck cancer. The second group was made up of 15 patients with diagnoses of allergic rhinitis. The control group consisted of 15 subjects with a negative history of upper airways and/or chest symptoms. Exhaled breath was collected from all participants and sampled by a polymer-based e-nose (Cyranose 320, Sensigent, Pasadena, CA, USA). In the Principal Component Analysis plot, patients with head and neck cancer clustered distinctly from the controls as well as from patients with allergic rhinitis. Using canonical discriminant analysis, the three groups were discriminated, with a cross validated accuracy% of 75.1, p < 0.01. The area under the curve of the receiver operating characteristic curve for the discrimination between head and neck cancer patients and the other groups was 0.87. To conclude, e-nose technology has the potential for application in the diagnosis of head and neck cancer, being an easy, quick, non-invasive and cost-effective tool.
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Affiliation(s)
| | | | - Silvano Dragonieri
- Respiratory Diseases Unit, Department SMBNOS, University of Bari, 70121 Bari, Italy
| | | | | | | | - Nicola Quaranta
- Otolaryngology Unit, Department SMBNOS, University of Bari, 70121 Bari, Italy
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Ali AS, Jacinto JGP, Mϋnchemyer W, Walte A, Kuhla B, Gentile A, Abdu MS, Kamel MM, Ghallab AM. Study on the Discrimination of Possible Error Sources That Might Affect the Quality of Volatile Organic Compounds Signature in Dairy Cattle Using an Electronic Nose. Vet Sci 2022; 9:vetsci9090461. [PMID: 36136677 PMCID: PMC9502780 DOI: 10.3390/vetsci9090461] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2022] [Revised: 08/12/2022] [Accepted: 08/23/2022] [Indexed: 11/25/2022] Open
Abstract
Simple Summary In recent decades, remarkable progress in the development of electronic nose (EN) technologies, particularly for disease detection, has been accomplished through the disclosure of novel methods and associated devices, mainly for the detection of volatile organic compounds (VOCs). Herein, we assessed the ability of a novel EN technology (MENT-EGAS prototype) to respond to direct sampling and to evaluate the influence of possible error sources that might affect the quality of VOC signatures. Principal Component Analyses (PCA) evidenced the presence in the analyzed samples of sufficient information to consent the discrimination of different environmental backgrounds, feed headspaces and exhalated breath between two groups of cows fed with two different types of feed. Moreover, discrimination was also observed within the same group between exhalated breaths sampled before and after feed intake. Based on these findings, we provided evidence that the MENT-EGAS prototype can identify error sources with accuracy. Livestock precision farming technologies are powerful tools for monitoring animal health and welfare parameters in a continuous and automated way. Abstract Electronic nose devices (EN) have been developed for detecting volatile organic compounds (VOCs). This study aimed to assess the ability of the MENT-EGAS prototype-based EN to respond to direct sampling and to evaluate the influence of possible error sources that might affect the quality of VOC signatures. This study was performed on a dairy farm using 11 (n = 11) multiparous Holstein-Friesian cows. The cows were divided into two groups housed in two different barns: group I included six lactating cows fed with a lactating diet (LD), and group II included 5 non-lactating late pregnant cows fed with a far-off diet (FD). Each group was offered 250 g of their respective diet; 10 min later, exhalated breath was collected for VOC determination. After this sampling, 4 cows from each group were offered 250 g of pellet concentrates. Ten minutes later, the exhalated breath was collected once more. VOCs were also measured directly from the feed’s headspace, as well as from the environmental backgrounds of each. Principal component analyses (PCA) were performed and revealed clear discrimination between the two different environmental backgrounds, the two different feed headspaces, the exhalated breath of groups I and II cows, and the exhalated breath within the same group of cows before and after the feed intake. Based on these findings, we concluded that the MENT-EGAS prototype can recognize several error sources with accuracy, providing a novel EN technology that could be used in the future in precision livestock farming.
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Affiliation(s)
- Asmaa S. Ali
- Department of Theriogenology, Faculty of Veterinary Medicine, Cairo University, Giza P.O. Box 12211, Egypt
- Correspondence:
| | - Joana G. P. Jacinto
- Department of Veterinary Medical Sciences, University of Bologna, Ozzano dell’Emilia, 40064 Bologna, Italy
| | | | | | - Björn Kuhla
- Research Institute for Farm Animal Biology (FBN), Institute of Nutritional Physiology ‘Oskar Kellner’, 18196 Dummerstorf, Germany
| | - Arcangelo Gentile
- Department of Veterinary Medical Sciences, University of Bologna, Ozzano dell’Emilia, 40064 Bologna, Italy
| | - Mohamed S. Abdu
- Department of Theriogenology, Faculty of Veterinary Medicine, Cairo University, Giza P.O. Box 12211, Egypt
| | - Mervat M. Kamel
- Department of Animal Management and Behavior, Faculty of Veterinary Medicine, Cairo University, Giza P.O. Box 12211, Egypt
| | - Abdelrauf Morsy Ghallab
- Department of Theriogenology, Faculty of Veterinary Medicine, Cairo University, Giza P.O. Box 12211, Egypt
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Dragonieri S, Quaranta VN, Buonamico E, Battisti C, Ranieri T, Carratu P, Carpagnano GE. Short-Term Effect of Cigarette Smoke on Exhaled Volatile Organic Compounds Profile Analyzed by an Electronic Nose. BIOSENSORS 2022; 12:bios12070520. [PMID: 35884323 PMCID: PMC9313253 DOI: 10.3390/bios12070520] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/25/2022] [Revised: 07/05/2022] [Accepted: 07/11/2022] [Indexed: 05/20/2023]
Abstract
Breath analysis using an electronic nose (e-nose) is an innovative tool for exhaled volatile organic compound (VOC) analysis, which has shown potential in several respiratory and systemic diseases. It is still unclear whether cigarette smoking can be considered a confounder when analyzing the VOC-profile. We aimed to assess whether an e-nose can discriminate exhaled breath before and after smoking at different time periods. We enrolled 24 healthy smokers and collected their exhaled breath as follows: (a) before smoking, (b) within 5 min after smoking, (c) within 30 min after smoking, and (d) within 60 min after smoking. Exhaled breath was collected by a previously validated method and analyzed by an e-nose (Cyranose 320). By principal component analysis, significant variations in the exhaled VOC profile were shown for principal component 1 and 2 before and after smoking. Significance was higher 30 and 60 min after smoking than 5 min after (p < 0.01 and <0.05, respectively). Canonical discriminant analysis confirmed the above findings (cross-validated values: baseline vs. 5 min = 64.6%, AUC = 0.833; baseline vs. 30 min = 83.6%, AUC = 0.927; baseline vs. 60 min = 89.6%, AUC = 0.933). Thus, the exhaled VOC profile is influenced by very recent smoking. Interestingly, the effect seems to be more closely linked to post-cigarette inflammation than the tobacco-related odorants.
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Affiliation(s)
- Silvano Dragonieri
- Respiratory Diseases Unit, Department SMBNOS, University of Bari, 70121 Bari, Italy; (V.N.Q.); (E.B.); (C.B.); (T.R.); (G.E.C.)
- Correspondence:
| | - Vitaliano Nicola Quaranta
- Respiratory Diseases Unit, Department SMBNOS, University of Bari, 70121 Bari, Italy; (V.N.Q.); (E.B.); (C.B.); (T.R.); (G.E.C.)
| | - Enrico Buonamico
- Respiratory Diseases Unit, Department SMBNOS, University of Bari, 70121 Bari, Italy; (V.N.Q.); (E.B.); (C.B.); (T.R.); (G.E.C.)
| | - Claudia Battisti
- Respiratory Diseases Unit, Department SMBNOS, University of Bari, 70121 Bari, Italy; (V.N.Q.); (E.B.); (C.B.); (T.R.); (G.E.C.)
| | - Teresa Ranieri
- Respiratory Diseases Unit, Department SMBNOS, University of Bari, 70121 Bari, Italy; (V.N.Q.); (E.B.); (C.B.); (T.R.); (G.E.C.)
| | | | - Giovanna Elisiana Carpagnano
- Respiratory Diseases Unit, Department SMBNOS, University of Bari, 70121 Bari, Italy; (V.N.Q.); (E.B.); (C.B.); (T.R.); (G.E.C.)
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Volatile Organic Compounds in the Early Diagnosis of Non-healing Surgical Wounds: A Systematic Review. World J Surg 2022; 46:1669-1677. [DOI: 10.1007/s00268-022-06548-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/13/2022] [Indexed: 11/27/2022]
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Bax C, Robbiani S, Zannin E, Capelli L, Ratti C, Bonetti S, Novelli L, Raimondi F, Di Marco F, Dellacà RL. An Experimental Apparatus for E-Nose Breath Analysis in Respiratory Failure Patients. Diagnostics (Basel) 2022; 12:776. [PMID: 35453824 PMCID: PMC9026987 DOI: 10.3390/diagnostics12040776] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2022] [Revised: 03/18/2022] [Accepted: 03/19/2022] [Indexed: 02/01/2023] Open
Abstract
Background: Non-invasive, bedside diagnostic tools are extremely important for tailo ring the management of respiratory failure patients. The use of electronic noses (ENs) for exhaled breath analysis has the potential to provide useful information for phenotyping different respiratory disorders and improving diagnosis, but their application in respiratory failure patients remains a challenge. We developed a novel measurement apparatus for analysing exhaled breath in such patients. Methods: The breath sampling apparatus uses hospital medical air and oxygen pipeline systems to control the fraction of inspired oxygen and prevent contamination of exhaled gas from ambient Volatile Organic Compounds (VOCs) It is designed to minimise the dead space and respiratory load imposed on patients. Breath odour fingerprints were assessed using a commercial EN with custom MOX sensors. We carried out a feasibility study on 33 SARS-CoV-2 patients (25 with respiratory failure and 8 asymptomatic) and 22 controls to gather data on tolerability and for a preliminary assessment of sensitivity and specificity. The most significant features for the discrimination between breath-odour fingerprints from respiratory failure patients and controls were identified using the Boruta algorithm and then implemented in the development of a support vector machine (SVM) classification model. Results: The novel sampling system was well-tolerated by all patients. The SVM differentiated between respiratory failure patients and controls with an accuracy of 0.81 (area under the ROC curve) and a sensitivity and specificity of 0.920 and 0.682, respectively. The selected features were significantly different in SARS-CoV-2 patients with respiratory failure versus controls and asymptomatic SARS-CoV-2 patients (p < 0.001 and 0.046, respectively). Conclusions: the developed system is suitable for the collection of exhaled breath samples from respiratory failure patients. Our preliminary results suggest that breath-odour fingerprints may be sensitive markers of lung disease severity and aetiology.
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Affiliation(s)
- Carmen Bax
- Department of Chemistry, Materials and Chemical Engineering “Giulio Natta” (DCMC), Politecnico di Milano, 20133 Milano, Italy; (C.B.); (C.R.)
| | - Stefano Robbiani
- TechRes Lab, Department of Electronics Information and Bioengineering (DEIB), Politecnico di Milano, 20133 Milano, Italy; (S.R.); (E.Z.); (R.L.D.)
| | - Emanuela Zannin
- TechRes Lab, Department of Electronics Information and Bioengineering (DEIB), Politecnico di Milano, 20133 Milano, Italy; (S.R.); (E.Z.); (R.L.D.)
| | - Laura Capelli
- Department of Chemistry, Materials and Chemical Engineering “Giulio Natta” (DCMC), Politecnico di Milano, 20133 Milano, Italy; (C.B.); (C.R.)
| | - Christian Ratti
- Department of Chemistry, Materials and Chemical Engineering “Giulio Natta” (DCMC), Politecnico di Milano, 20133 Milano, Italy; (C.B.); (C.R.)
| | - Simone Bonetti
- Unit of Pneumology, Azienda Ospedaliera Socio Sanitaria Territoriale Papa Giovanni XXIII, 24127 Bergamo, Italy; (S.B.); (L.N.); (F.R.); (F.D.M.)
- Department of Health Sciences, Università degli Studi di Milano, 20142 Milano, Italy
| | - Luca Novelli
- Unit of Pneumology, Azienda Ospedaliera Socio Sanitaria Territoriale Papa Giovanni XXIII, 24127 Bergamo, Italy; (S.B.); (L.N.); (F.R.); (F.D.M.)
| | - Federico Raimondi
- Unit of Pneumology, Azienda Ospedaliera Socio Sanitaria Territoriale Papa Giovanni XXIII, 24127 Bergamo, Italy; (S.B.); (L.N.); (F.R.); (F.D.M.)
| | - Fabiano Di Marco
- Unit of Pneumology, Azienda Ospedaliera Socio Sanitaria Territoriale Papa Giovanni XXIII, 24127 Bergamo, Italy; (S.B.); (L.N.); (F.R.); (F.D.M.)
- Department of Health Sciences, Università degli Studi di Milano, 20142 Milano, Italy
| | - Raffaele L. Dellacà
- TechRes Lab, Department of Electronics Information and Bioengineering (DEIB), Politecnico di Milano, 20133 Milano, Italy; (S.R.); (E.Z.); (R.L.D.)
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Kopp MV, Weckmann M, Nissen G, Ricklefs I, Härtel C. Two Beer(s) or Not Two Beer(s): The eNose as an Instrument to Pacify the World. KLINISCHE PADIATRIE 2022; 234:301-304. [PMID: 35139542 PMCID: PMC9512582 DOI: 10.1055/a-1714-8895] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
Abstract
Background
Science prizes that are not meant to be very serious, stand-up
evenings, science slams or publications with a scientific twist: science comedy
comes in very different forms. But all variants have one thing in common:
humour. It can be used to hide the seriousness of life or, in this case,
everyday scientific life for a brief moment. Moreover, serious social or ethical
questions are also met. The GPP, a group of German, Austrian and Swiss Pediatric
Pulmonologists (GPP) is a scientific society with regular annual meetings.
Unsystematic observations and preliminary data suggest that beer consumption
increased by some of the participants during this event. Recently, electronic
nose (eNose) devices have been developed as a technology for disease screening
using exhaled-breath analysis. Here we addressed the issue, if the eNose can be
used to differentiate between real beer and fake beer.
Methods
In this single-centre experimental study, 12 different
“real beer” types and one “fake beer” were
analyzed with regard to their emittance of volatile organic compounds (VOCs)
with the eNose as an electronic VOC-sensing technology.
Results
Every single beer type can be identified by a characteristic
VOC-smell print using the eNose. Distinct clusters exist for bottom- and
top-fermented ales. Intriguingly, “Sylter Hopfen”, which is
marketed as a “champagne-beer” and tested as representative of a
“fake beer”, can be clearly differentiated from all other
genuine beer types.
Conclusion
Our study provides the first objective data of beer flavor. In
the long term perspective the eNose might help to overcome the agonizing
controversy about beer flavors and, consequently, pacify the World. In the short
run, however, our results give support to more targeted and reserved beer
consumption during our annual meeting, especially since one specific beer shows
a very similar pattern to indoor air.
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Affiliation(s)
- Matthias Volkmar Kopp
- University Clinic for Pediatrics, Inselspital University Bern, Bern, Switzerland.,Member of the Deutsches Zentrum für Lungenforschung (DZL), Airway Research Center North (ARCN), Luebeck, Germany
| | - Markus Weckmann
- Member of the Deutsches Zentrum für Lungenforschung (DZL), Airway Research Center North (ARCN), Luebeck, Germany.,Department of Pediatric Pulmonology and Allergy, University of Luebeck Human Medicine, Lubeck, Germany
| | - Gyde Nissen
- Member of the Deutsches Zentrum für Lungenforschung (DZL), Airway Research Center North (ARCN), Luebeck, Germany.,Department of Pediatric Pulmonology and Allergy, University of Luebeck Human Medicine, Lubeck, Germany
| | - Isabell Ricklefs
- Member of the Deutsches Zentrum für Lungenforschung (DZL), Airway Research Center North (ARCN), Luebeck, Germany.,Department of Pediatric Pulmonology and Allergy, University of Luebeck Human Medicine, Lubeck, Germany
| | - Christoph Härtel
- Direktor der Kinderklinik und Poliklinik, Julius-Maximilians-Universität Würzburg Medizinische Fakultät, Wurzburg, Germany
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Im C, Shin J, Lee WR, Kim JM. Machine learning-based feature combination analysis for odor-dependent hemodynamic responses of rat olfactory bulb. Biosens Bioelectron 2022; 197:113782. [PMID: 34814029 DOI: 10.1016/j.bios.2021.113782] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2021] [Revised: 10/19/2021] [Accepted: 11/08/2021] [Indexed: 11/29/2022]
Abstract
Rodents have a well-developed sense of smell and are used to detect explosives, mines, illegal substances, hidden currency, and contraband, but it is impossible to keep their concentration constantly. Therefore, there is an ongoing effort to infer odors detected by animals without behavioral readings with brain-computer interface (BCI) technology. However, the invasive BCI technique has the disadvantage that long-term studies are limited by the immune response and electrode movement. On the other hand, near-infrared spectroscopy (NIRS)-based BCI technology is a non-invasive method that can measure neuronal activity without worrying about the immune response or electrode movement. This study confirmed that the NIRS-based BCI technology can be used as an odor detection and identification from the rat olfactory system. In addition, we tried to present features optimized for machine learning models by extracting six features, such as slopes, peak, variance, mean, kurtosis, and skewness, from the hemodynamic response, and analyzing the importance of individuals or combinations. As a result, the feature with the highest F1-Score was indicated as slopes, and it was investigated that the combination of the features including slopes and mean was the most important for odor inference. On the other hand, the inclusion of other features with a low correlation with slopes had a positive effect on the odor inference, but most of them resulted in insignificant or rather poor performance. The results presented in this paper are expected to serve as a basis for suggesting the development direction of the hemodynamic response-based bionic nose in the future.
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Affiliation(s)
- Changkyun Im
- Bio & Medical Health Division, Korea Testing Laboratory, Seoul, 08389, Republic of Korea
| | - Jaewoo Shin
- Hurvitz Brain Sciences Research Program, Biological Sciences, Sunnybrook Research Institute, Toronto, ON, M4N 3M5, Canada; Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ON, M5S 1A8, Canada; Department of Neurosurgery, Brain Research Institute, Yonsei University College of Medicine, Seoul, 03722, Republic of Korea
| | - Woo Ram Lee
- Department of Electronic Engineering, Gyeonggi University of Science and Technology, Siheung, 15073, Republic of Korea.
| | - Jun-Min Kim
- Department of Mechanical Systems Engineering Electronics, Hansung University, Seoul, 02876, Republic of Korea.
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Predicting Early Hospital Readmissions in COPD Patients Using an Electronic Nose. ARCHIVOS DE BRONCONEUMOLOGÍA 2022; 58:663-665. [DOI: 10.1016/j.arbres.2022.01.015] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/29/2021] [Revised: 01/11/2022] [Accepted: 01/17/2022] [Indexed: 11/23/2022]
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Voss A, Schroeder R, Schulz S, Haueisen J, Vogler S, Horn P, Stallmach A, Reuken P. Detection of Liver Dysfunction Using a Wearable Electronic Nose System Based on Semiconductor Metal Oxide Sensors. BIOSENSORS 2022; 12:bios12020070. [PMID: 35200331 PMCID: PMC8869535 DOI: 10.3390/bios12020070] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/29/2021] [Revised: 01/21/2022] [Accepted: 01/24/2022] [Indexed: 05/04/2023]
Abstract
The purpose of this exploratory study was to determine whether liver dysfunction can be generally classified using a wearable electronic nose based on semiconductor metal oxide (MOx) gas sensors, and whether the extent of this dysfunction can be quantified. MOx gas sensors are attractive because of their simplicity, high sensitivity, low cost, and stability. A total of 30 participants were enrolled, 10 of them being healthy controls, 10 with compensated cirrhosis, and 10 with decompensated cirrhosis. We used three sensor modules with a total of nine different MOx layers to detect reducible, easily oxidizable, and highly oxidizable gases. The complex data analysis in the time and non-linear dynamics domains is based on the extraction of 10 features from the sensor time series of the extracted breathing gas measurement cycles. The sensitivity, specificity, and accuracy for distinguishing compensated and decompensated cirrhosis patients from healthy controls was 1.00. Patients with compensated and decompensated cirrhosis could be separated with a sensitivity of 0.90 (correctly classified decompensated cirrhosis), a specificity of 1.00 (correctly classified compensated cirrhosis), and an accuracy of 0.95. Our wearable, non-invasive system provides a promising tool to detect liver dysfunctions on a functional basis. Therefore, it could provide valuable support in preoperative examinations or for initial diagnosis by the general practitioner, as it provides non-invasive, rapid, and cost-effective analysis results.
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Affiliation(s)
- Andreas Voss
- Institute of Innovative Health Technologies IGHT, Ernst-Abbe-Hochschule Jena, 07745 Jena, Germany; (R.S.); (S.S.)
- Institute of Biomedical Engineering and Informatics (BMTI), Technische Universität Ilmenau, 98693 Ilmenau, Germany;
- Correspondence: ; Tel.: +49-3677-69-2861
| | - Rico Schroeder
- Institute of Innovative Health Technologies IGHT, Ernst-Abbe-Hochschule Jena, 07745 Jena, Germany; (R.S.); (S.S.)
- UST Umweltsensortechnik GmbH, 99331 Geratal, Germany
| | - Steffen Schulz
- Institute of Innovative Health Technologies IGHT, Ernst-Abbe-Hochschule Jena, 07745 Jena, Germany; (R.S.); (S.S.)
| | - Jens Haueisen
- Institute of Biomedical Engineering and Informatics (BMTI), Technische Universität Ilmenau, 98693 Ilmenau, Germany;
| | - Stefanie Vogler
- Clinic for Internal Medicine IV, University Hospital Jena, 07747 Jena, Germany; (S.V.); (P.H.); (A.S.); (P.R.)
| | - Paul Horn
- Clinic for Internal Medicine IV, University Hospital Jena, 07747 Jena, Germany; (S.V.); (P.H.); (A.S.); (P.R.)
| | - Andreas Stallmach
- Clinic for Internal Medicine IV, University Hospital Jena, 07747 Jena, Germany; (S.V.); (P.H.); (A.S.); (P.R.)
| | - Philipp Reuken
- Clinic for Internal Medicine IV, University Hospital Jena, 07747 Jena, Germany; (S.V.); (P.H.); (A.S.); (P.R.)
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Pareek V, Chaudhury S, Singh S. Handling non-stationarity in E-nose design: a review. SENSOR REVIEW 2022; 42:39-61. [DOI: 10.1108/sr-02-2021-0038] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/19/2023]
Abstract
Purpose
The electronic nose is an array of chemical or gas sensors and associated with a pattern-recognition framework competent in identifying and classifying odorant or non-odorant and simple or complex gases. Despite more than 30 years of research, the robust e-nose device is still limited. Most of the challenges towards reliable e-nose devices are associated with the non-stationary environment and non-stationary sensor behaviour. Data distribution of sensor array response evolves with time, referred to as non-stationarity. The purpose of this paper is to provide a comprehensive introduction to challenges related to non-stationarity in e-nose design and to review the existing literature from an application, system and algorithm perspective to provide an integrated and practical view.
Design/methodology/approach
The authors discuss the non-stationary data in general and the challenges related to the non-stationarity environment in e-nose design or non-stationary sensor behaviour. The challenges are categorised and discussed with the perspective of learning with data obtained from the sensor systems. Later, the e-nose technology is reviewed with the system, application and algorithmic point of view to discuss the current status.
Findings
The discussed challenges in e-nose design will be beneficial for researchers, as well as practitioners as it presents a comprehensive view on multiple aspects of non-stationary learning, system, algorithms and applications for e-nose. The paper presents a review of the pattern-recognition techniques, public data sets that are commonly referred to as olfactory research. Generic techniques for learning in the non-stationary environment are also presented. The authors discuss the future direction of research and major open problems related to handling non-stationarity in e-nose design.
Originality/value
The authors first time review the existing literature related to learning with e-nose in a non-stationary environment and existing generic pattern-recognition algorithms for learning in the non-stationary environment to bridge the gap between these two. The authors also present details of publicly available sensor array data sets, which will benefit the upcoming researchers in this field. The authors further emphasise several open problems and future directions, which should be considered to provide efficient solutions that can handle non-stationarity to make e-nose the next everyday device.
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Recent Progress in Smart Electronic Nose Technologies Enabled with Machine Learning Methods. SENSORS 2021; 21:s21227620. [PMID: 34833693 PMCID: PMC8619411 DOI: 10.3390/s21227620] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/24/2021] [Revised: 11/08/2021] [Accepted: 11/13/2021] [Indexed: 02/07/2023]
Abstract
Machine learning methods enable the electronic nose (E-Nose) for precise odor identification with both qualitative and quantitative analysis. Advanced machine learning methods are crucial for the E-Nose to gain high performance and strengthen its capability in many applications, including robotics, food engineering, environment monitoring, and medical diagnosis. Recently, many machine learning techniques have been studied, developed, and integrated into feature extraction, modeling, and gas sensor drift compensation. The purpose of feature extraction is to keep robust pattern information in raw signals while removing redundancy and noise. With the extracted feature, a proper modeling method can effectively use the information for prediction. In addition, drift compensation is adopted to relieve the model accuracy degradation due to the gas sensor drifting. These recent advances have significantly promoted the prediction accuracy and stability of the E-Nose. This review is engaged to provide a summary of recent progress in advanced machine learning methods in E-Nose technologies and give an insight into new research directions in feature extraction, modeling, and sensor drift compensation.
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Kim ST, Choi IH, Li H. Identification of multi-concentration aromatic fragrances with electronic nose technology using a support vector machine. ANALYTICAL METHODS : ADVANCING METHODS AND APPLICATIONS 2021; 13:4710-4717. [PMID: 34617937 DOI: 10.1039/d1ay00788b] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
Due to the concentration effect, there is a major challenge for the electronic nose system to identify different odor samples with multiple concentrations. The development of artificial intelligence provides new ways to solve such problems. This article attempts to use support vector machine (SVM) technology to distinguish four fragrance samples with three concentrations, including roman chamomile, jasmine, lavender, and orange. The responses of these samples were collected by an 11-sensor electronic nose. After baseline correction, data smoothing, and removal of non-responsive sensors, the signals of 8 sensors were used for subsequent model analysis. Due to the concentration effect, when the primary signal intensities were used as features, the electronic nose cannot distinguish between different aroma types (accuracy less than 50%). When the normalized maximum signal intensity Xmr was used, the accuracy of the model was greatly improved. Graphic analysis and PCA showed that the normalized feature effectively eliminates the concentration effect, and appropriately reducing some sensors can enhance the ability to distinguish odors. The SVM correctly classified all 14 aromas when feeding 8 sets of data to train the radial kernel C-classification SVM. This showed that the cross-interference of the sensors was reduced, and the resolving power of the electronic nose was enhanced after the feature reduction.
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Affiliation(s)
- Sun-Tae Kim
- Daejeon University, 62 Daehak-Ro, Dong-Gu, Daejeon, 34520, Republic of Korea
| | - Il-Hwan Choi
- Daejeon University, 62 Daehak-Ro, Dong-Gu, Daejeon, 34520, Republic of Korea
| | - Hui Li
- Envors Co., Ltd, Biraeseoro 54-1, Dong Gu, Daejeon, 34528, Republic of Korea.
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Binson VA, Subramoniam M, Mathew L. Discrimination of COPD and lung cancer from controls through breath analysis using a self-developed e-nose. J Breath Res 2021; 15. [PMID: 34243176 DOI: 10.1088/1752-7163/ac1326] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2021] [Accepted: 07/09/2021] [Indexed: 01/22/2023]
Abstract
This work details the application of a metal oxide semiconductor (MOS) sensor based electronic nose (e-nose) system in the discrimination of lung cancer and chronic obstructive pulmonary disease (COPD) from healthy controls. The sensor array integrated with supervised classification algorithms was able to detect and classify exhaled breath samples from healthy controls, patients with COPD, and lung cancer by recognizing the amount of volatile organic compounds present in it. This paper details the e-nose design, participant selection, sampling methods, and data analysis. The clinical feasibility of the system was checked in 32 lung cancer patients, 38 COPD patients, and 72 healthy controls including smokers and non-smokers. One of the advantages of the equipment design was portability and robustness since the system was conditioned with elements that allowed its easy movement. In the discrimination of lung cancer from controls, the k-nearest neighbors gave an acceptable accuracy, sensitivity, and specificity of 91.3%, 84.4%, and 94.4% respectively. The support vector machine gave better results for COPD discrimination from controls with 90.9% accuracy, 81.6% sensitivity, and 95.8% specificity. Even though the attained results were good, further examinations are essential to enhance the sensor array system, investigate the long-run reproducibility, repeatability, and enlarge its relevancy.
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Affiliation(s)
- V A Binson
- Department of Electronics Engineering, Sathyabama Institute of Science and Technology, Chennai, Tamil Nadu, India.,Department of Electronics Engineering, Saintgits College of Engineering, Kottayam, Kerala, India
| | - M Subramoniam
- Department of Electronics Engineering, Sathyabama Institute of Science and Technology, Chennai, Tamil Nadu, India
| | - Luke Mathew
- Department of Pulmonology, Believers Church Medical College Hospital, Thiruvalla, Kerala, India
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Coronel Teixeira R, IJdema D, Gómez C, Arce D, Roman M, Quintana Y, González F, Jiménez de Romero N, Pérez Bejarano D, Aguirre S, Magis-Escurra C. The electronic nose as a rule-out test for tuberculosis in an indigenous population. J Intern Med 2021; 290:386-391. [PMID: 33720468 PMCID: PMC8361912 DOI: 10.1111/joim.13281] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/08/2020] [Accepted: 02/17/2021] [Indexed: 12/27/2022]
Abstract
INTRODUCTION To end the tuberculosis (TB) epidemic, efficient diagnostic tools are needed. In a previous calibration study, a portable 'point of care' electronic nose device (AeonoseTM ) proved to be a promising tool in a hospital setting. We evaluated this technology to detect TB in an indigenous population in Paraguay. METHODS A total of 131 participants were enrolled. eNose results were compared with anamnesis, physical examinations, chest radiography and mycobacterial cultures in individuals with signs and symptoms compatible with TB. The eNose analysis was performed in two stages: first, the training with a combination of a previous study population plus 47 participants from the new cohort (total n = 153), and second, the 'blind prediction' of 84 participants. RESULTS 21% of all participants (n = 131) showed symptoms and/or chest radiography abnormalities suspicious of TB. No sputum samples resulted culture positive for Mycobacterium tuberculosis complex. Only one patient had a positive smell print analysis. In the training model, the specificity was 92% (95% confidence interval (CI): 85%-96%) and the negative predictive value (NPV) was 95%. In the blind prediction model, the specificity and the NPV were 99% (95% CI: 93%-99%) and 100%, respectively. Although the sensitivity and positive predictive value of the eNose could not be assessed in this cohort due to the small sample size, no active TB cases were found during a one year of follow-up period. CONCLUSION The eNose showed promising specificity and negative predictive value and might therefore be developed as a rule-out test for TB in vulnerable populations.
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Affiliation(s)
- R Coronel Teixeira
- From the, National Institute of Respiratory Diseases and the Environment (INERAM), Asunción, Paraguay.,Department of Respiratory Diseases, Radboud University Medical Centre - TB Expert Centre Dekkerswald, Nijmegen - Groesbeek, The Netherlands
| | - D IJdema
- Department of Respiratory Diseases, Radboud University Medical Centre - TB Expert Centre Dekkerswald, Nijmegen - Groesbeek, The Netherlands
| | - C Gómez
- Medical Health Center, Puerto Casado, Chaco, Paraguay
| | - D Arce
- Medical Health Center, Puerto Casado, Chaco, Paraguay
| | - M Roman
- National Tuberculosis Control Program (PCNT), Asunción, Paraguay
| | - Y Quintana
- From the, National Institute of Respiratory Diseases and the Environment (INERAM), Asunción, Paraguay
| | - F González
- From the, National Institute of Respiratory Diseases and the Environment (INERAM), Asunción, Paraguay
| | - N Jiménez de Romero
- From the, National Institute of Respiratory Diseases and the Environment (INERAM), Asunción, Paraguay.,Central Public Health Laboratory (LCSP), Paraguay
| | - D Pérez Bejarano
- From the, National Institute of Respiratory Diseases and the Environment (INERAM), Asunción, Paraguay
| | - S Aguirre
- National Tuberculosis Control Program (PCNT), Asunción, Paraguay
| | - C Magis-Escurra
- Department of Respiratory Diseases, Radboud University Medical Centre - TB Expert Centre Dekkerswald, Nijmegen - Groesbeek, The Netherlands
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Dragonieri S, Quaranta VN, Carratù P, Ranieri T, Buonamico E, Carpagnano GE. Breathing Rhythm Variations during Wash-In Do Not Influence Exhaled Volatile Organic Compound Profile Analyzed by an Electronic Nose. Molecules 2021; 26:molecules26092695. [PMID: 34064506 PMCID: PMC8124182 DOI: 10.3390/molecules26092695] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2021] [Revised: 04/21/2021] [Accepted: 05/03/2021] [Indexed: 11/24/2022] Open
Abstract
E-noses are innovative tools used for exhaled volatile organic compound (VOC) analysis, which have shown their potential in several diseases. Before obtaining a full validation of these instruments in clinical settings, a number of methodological issues still have to be established. We aimed to assess whether variations in breathing rhythm during wash-in with VOC-filtered air before exhaled air collection reflect changes in the exhaled VOC profile when analyzed by an e-nose (Cyranose 320). We enrolled 20 normal subjects and randomly collected their exhaled breath at three different breathing rhythms during wash-in: (a) normal rhythm (respiratory rate (RR) between 12 and 18/min), (b) fast rhythm (RR > 25/min) and (c) slow rhythm (RR < 10/min). Exhaled breath was collected by a previously validated method (Dragonieri et al., J. Bras. Pneumol. 2016) and analyzed by the e-nose. Using principal component analysis (PCA), no significant variations in the exhaled VOC profile were shown among the three breathing rhythms. Subsequent linear discriminant analysis (LDA) confirmed the above findings, with a cross-validated accuracy of 45% (p = ns). We concluded that the exhaled VOC profile, analyzed by an e-nose, is not influenced by variations in breathing rhythm during wash-in.
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Affiliation(s)
- Silvano Dragonieri
- Respiratory Diseases, University of Bari, 70121 Bari, Italy; (T.R.); (E.B.); (G.E.C.)
- Correspondence:
| | | | - Pierluigi Carratù
- Internal Medicine “A. Murri”, University of Bari, 70121 Bari, Italy;
| | - Teresa Ranieri
- Respiratory Diseases, University of Bari, 70121 Bari, Italy; (T.R.); (E.B.); (G.E.C.)
| | - Enrico Buonamico
- Respiratory Diseases, University of Bari, 70121 Bari, Italy; (T.R.); (E.B.); (G.E.C.)
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Belizário JE, Faintuch J, Malpartida MG. Breath Biopsy and Discovery of Exclusive Volatile Organic Compounds for Diagnosis of Infectious Diseases. Front Cell Infect Microbiol 2021; 10:564194. [PMID: 33520731 PMCID: PMC7839533 DOI: 10.3389/fcimb.2020.564194] [Citation(s) in RCA: 39] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2020] [Accepted: 11/16/2020] [Indexed: 01/13/2023] Open
Abstract
Exhaled breath contains thousand metabolites and volatile organic compounds (VOCs) that originated from both respiratory tract and internal organ systems and their microbiomes. Commensal and pathogenic bacteria and virus of microbiomes are capable of producing VOCs of different chemical classes, and some of them may serve as biomarkers for installation and progression of various common human diseases. Here we describe qualitative and quantitative methods for measuring VOC fingerprints generated by cellular and microbial metabolic and pathologic pathways. We describe different chemical classes of VOCs and their role in the host cell-microbial interactions and their impact on infection disease pathology. We also update on recent progress on VOC signatures emitted by isolated bacterial species and microbiomes, and VOCs identified in exhaled breath of patients with respiratory tract and gastrointestinal diseases, and inflammatory syndromes, including the acute respiratory distress syndrome and sepsis. The VOC curated databases and instrumentations have been developed through statistically robust breathomic research in large patient populations. Scientists have now the opportunity to find potential biomarkers for both triage and diagnosis of particular human disease.
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Affiliation(s)
- José E Belizário
- Department of Pharmacology, Institute of Biomedical Sciences, University of São Paulo, São Paulo, Brazil
| | - Joel Faintuch
- Department of Gastroenterology of Medical School, University of Sao Paulo, São Paulo, Brazil
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Licht JC, Grasemann H. Potential of the Electronic Nose for the Detection of Respiratory Diseases with and without Infection. Int J Mol Sci 2020; 21:E9416. [PMID: 33321951 PMCID: PMC7763696 DOI: 10.3390/ijms21249416] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2020] [Revised: 11/16/2020] [Accepted: 11/23/2020] [Indexed: 02/06/2023] Open
Abstract
Respiratory tract infections are common, and when affecting the lower airways and lungs, can result in significant morbidity and mortality. There is an unfilled need for simple, non-invasive tools that can be used to screen for such infections at the clinical point of care. The electronic nose (eNose) is a novel technology that detects volatile organic compounds (VOCs). Early studies have shown that certain diseases and infections can result in characteristic changes in VOC profiles in the exhaled breath. This review summarizes current knowledge on breath analysis by the electronic nose and its potential for the detection of respiratory diseases with and without infection.
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Affiliation(s)
- Johann-Christoph Licht
- Division of Respiratory Medicine, Department of Pediatrics, Hospital for Sick Children, Toronto, ON M5G 1X8, Canada;
- Translational Medicine Research Program, Hospital for Sick Children Research Institute, Toronto, ON M5G 1X8, Canada
- Department of Immunology, University of Toronto, Toronto, ON M5S 1A8, Canada
| | - Hartmut Grasemann
- Division of Respiratory Medicine, Department of Pediatrics, Hospital for Sick Children, Toronto, ON M5G 1X8, Canada;
- Translational Medicine Research Program, Hospital for Sick Children Research Institute, Toronto, ON M5G 1X8, Canada
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Kuo TC, Tan CE, Wang SY, Lin OA, Su BH, Hsu MT, Lin J, Cheng YY, Chen CS, Yang YC, Chen KH, Lin SW, Ho CC, Kuo CH, Tseng YJ. Human Breathomics Database. DATABASE-THE JOURNAL OF BIOLOGICAL DATABASES AND CURATION 2020; 2020:5682403. [PMID: 31976536 PMCID: PMC6978997 DOI: 10.1093/database/baz139] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/19/2019] [Revised: 09/12/2019] [Accepted: 11/13/2019] [Indexed: 12/11/2022]
Abstract
Breathomics is a special branch of metabolomics that quantifies volatile organic compounds (VOCs) from collected exhaled breath samples. Understanding how breath molecules are related to diseases, mechanisms and pathways identified from experimental analytical measurements is challenging due to the lack of an organized resource describing breath molecules, related references and biomedical information embedded in the literature. To provide breath VOCs, related references and biomedical information, we aim to organize a database composed of manually curated information and automatically extracted biomedical information. First, VOCs-related disease information was manually organized from 207 literature linked to 99 VOCs and known Medical Subject Headings (MeSH) terms. Then an automated text mining algorithm was used to extract biomedical information from this literature. In the end, the manually curated information and auto-extracted biomedical information was combined to form a breath molecule database—the Human Breathomics Database (HBDB). We first manually curated and organized disease information including MeSH term from 207 literatures associated with 99 VOCs. Then, an automatic pipeline of text mining approach was used to collect 2766 literatures and extract biomedical information from breath researches. We combined curated information with automatically extracted biomedical information to assemble a breath molecule database, the HBDB. The HBDB is a database that includes references, VOCs and diseases associated with human breathomics. Most of these VOCs were detected in human breath samples or exhaled breath condensate samples. So far, the database contains a total of 913 VOCs in relation to human exhaled breath researches reported in 2766 publications. The HBDB is the most comprehensive HBDB of VOCs in human exhaled breath to date. It is a useful and organized resource for researchers and clinicians to identify and further investigate potential biomarkers from the breath of patients. Database URL: https://hbdb.cmdm.tw
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Affiliation(s)
- Tien-Chueh Kuo
- Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, No. 1, Sec. 4, Roosevelt Road, Taipei 10617, Taiwan.,The Metabolomics Core Laboratory, Centers of Genomic Medicine and Precision Medicine, National Taiwan University, No. 2, Syu-Jhou Road, Taipei 10055, Taiwan.,Drug Research Center, College of Pharmacy, College of Medicine, National Taiwan University, No. 33, Linsen S. Road, Taipei 10055, Taiwan
| | - Cheng-En Tan
- The Metabolomics Core Laboratory, Centers of Genomic Medicine and Precision Medicine, National Taiwan University, No. 2, Syu-Jhou Road, Taipei 10055, Taiwan.,Drug Research Center, College of Pharmacy, College of Medicine, National Taiwan University, No. 33, Linsen S. Road, Taipei 10055, Taiwan.,Department of Computer Science and Information Engineering, National Taiwan University, No. 1, Sec. 4, Roosevelt Road, Taipei 10617, Taiwan
| | - San-Yuan Wang
- The Metabolomics Core Laboratory, Centers of Genomic Medicine and Precision Medicine, National Taiwan University, No. 2, Syu-Jhou Road, Taipei 10055, Taiwan.,Department of Computer Science and Information Engineering, National Taiwan University, No. 1, Sec. 4, Roosevelt Road, Taipei 10617, Taiwan.,Master Program in Clinical Pharmacogenomics and Pharmacoproteomics, College of Pharmacy, Taipei Medical University, No. 250, Wu-Hsing St., Taipei 11031, Taiwan
| | - Olivia A Lin
- Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, No. 1, Sec. 4, Roosevelt Road, Taipei 10617, Taiwan
| | - Bo-Han Su
- Department of Computer Science and Information Engineering, National Taiwan University, No. 1, Sec. 4, Roosevelt Road, Taipei 10617, Taiwan
| | - Ming-Tsung Hsu
- Genome and Systems Biology Degree Program, National Taiwan University and Academia Sinica, No. 1, Sec. 4, Roosevelt Road, Taipei 10617, Taiwan
| | - Jessica Lin
- Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, No. 1, Sec. 4, Roosevelt Road, Taipei 10617, Taiwan
| | - Yu-Yen Cheng
- Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, No. 1, Sec. 4, Roosevelt Road, Taipei 10617, Taiwan.,The Metabolomics Core Laboratory, Centers of Genomic Medicine and Precision Medicine, National Taiwan University, No. 2, Syu-Jhou Road, Taipei 10055, Taiwan
| | - Ciao-Sin Chen
- Department of Pharmacy, School of Pharmacy, College of Medicine, National Taiwan University, No. 33, Linsen S. Road, Taipei 10055, Taiwan
| | - Yu-Chieh Yang
- Department of Obstetrics and Gynecology, National Taiwan University Hospital-Yunlin Branch, No. 579, Sec. 2, Yunlin Road, Douliu, Yunlin County 640, Taiwan
| | - Kuo-Hsing Chen
- Department of Oncology, National Taiwan University Hospital, National Taiwan University Cancer Center, No. 1, Sec. 4, Roosevelt Road, Taipei 10048, Taiwan
| | - Shu-Wen Lin
- Graduate Institute of Clinical Pharmacy, College of Medicine, National Taiwan University, No. 33, Linsen S. Road, Taipei 10055, Taiwan
| | - Chao-Chi Ho
- Department of Internal Medicine, National Taiwan University Hospital, No. 7, Chung-Shan South Road, Taipei 10002, Taiwan
| | - Ching-Hua Kuo
- The Metabolomics Core Laboratory, Centers of Genomic Medicine and Precision Medicine, National Taiwan University, No. 2, Syu-Jhou Road, Taipei 10055, Taiwan.,Drug Research Center, College of Pharmacy, College of Medicine, National Taiwan University, No. 33, Linsen S. Road, Taipei 10055, Taiwan.,Department of Pharmacy, School of Pharmacy, College of Medicine, National Taiwan University, No. 33, Linsen S. Road, Taipei 10055, Taiwan
| | - Yufeng Jane Tseng
- Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, No. 1, Sec. 4, Roosevelt Road, Taipei 10617, Taiwan.,The Metabolomics Core Laboratory, Centers of Genomic Medicine and Precision Medicine, National Taiwan University, No. 2, Syu-Jhou Road, Taipei 10055, Taiwan.,Drug Research Center, College of Pharmacy, College of Medicine, National Taiwan University, No. 33, Linsen S. Road, Taipei 10055, Taiwan.,Department of Computer Science and Information Engineering, National Taiwan University, No. 1, Sec. 4, Roosevelt Road, Taipei 10617, Taiwan
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The Role of Electronic Noses in Phenotyping Patients with Chronic Obstructive Pulmonary Disease. BIOSENSORS-BASEL 2020; 10:bios10110171. [PMID: 33187142 PMCID: PMC7697924 DOI: 10.3390/bios10110171] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/13/2020] [Revised: 11/05/2020] [Accepted: 11/09/2020] [Indexed: 12/12/2022]
Abstract
Chronic obstructive pulmonary disease (COPD) is a common progressive disorder of the respiratory system which is currently the third leading cause of death worldwide. Exhaled breath analysis is a non-invasive method to study lung diseases, and electronic noses have been extensively used in breath research. Studies with electronic noses have proved that the pattern of exhaled volatile organic compounds is different in COPD. More recent investigations have reported that electronic noses could potentially distinguish different endotypes (i.e., neutrophilic vs. eosinophilic) and are able to detect microorganisms in the airways responsible for exacerbations. This article will review the published literature on electronic noses and COPD and help in identifying methodological, physiological, and disease-related factors which could affect the results.
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Krauss E, Haberer J, Barreto G, Degen M, Seeger W, Guenther A. Recognition of breathprints of lung cancer and chronic obstructive pulmonary disease using the Aeonose ® electronic nose. J Breath Res 2020; 14:046004. [PMID: 32325432 DOI: 10.1088/1752-7163/ab8c50] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
OBJECTIVES There is a high unmet need in a non-invasive screening of lung cancer (LC). We conducted this single-center trial to evaluate the effectiveness of the electronic nose Aeonose ® in LC recognition. MATERIALS AND METHODS Exhaled volatile organic compound (VOC) signatures were collected by Aeonose ® in 42 incident and 78 prevalent LC patients, of them 29 LC patients in complete remission (LC CR), 33 healthy controls (HC) and 23 COPD patients. By dichotomous comparison of VOC's between incident LC and HC, a discriminating algorithm was established and also applied to LC CR and COPD subjects. Area under Curve (AUC), sensitivity, specificity and Matthews's correlation coefficient (MC) were used to interpret the data. RESULTS The established algorithm of Aeonose ® signature allowed safe separation of LC and HC, showing an AUC of 0.92, sensitivity of 0.84 and a specificity of 0.97. When tested in a blinded fashion, the device recognized 19 out of 29 LC CR patients (=65.5%) as LC-positive, of which only five developed recurrent LC later on (after 18.6 months [Formula: see text]; mean value [Formula: see text]). Unfortunately, the algorithm also recognized 11 of 24 COPD patients as being LC positive (with only one of the 24 COPD patients developing LC 56 months after the measurement). CONCLUSION The Aeonose ® revealed some potential in distinguishing LC from HC, however, with low specificity when applying the algorithm in a blinded fashion to other disease cohorts. We conclude that relevant VOC signals originating from comorbidities in LC such as COPD may have erroneously led to the separation between LC and controls. CLINICAL TRIAL REGISTRATION (NCT02951416).
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Affiliation(s)
- Ekaterina Krauss
- Universities of Giessen and Marburg Lung Center (UGMLC), Member of the German Center for Lung Research (DZL), Klinikstr. 33, 35392 Giessen, Germany. European IPF Registry & Biobank (eurIPFreg), 35392 Giessen, Germany
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Dragonieri S, Scioscia G, Quaranta VN, Carratu P, Venuti MP, Falcone M, Carpagnano GE, Foschino Barbaro MP, Resta O, Lacedonia D. Exhaled volatile organic compounds analysis by e-nose can detect idiopathic pulmonary fibrosis. J Breath Res 2020; 14:047101. [PMID: 32320958 DOI: 10.1088/1752-7163/ab8c2e] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Abstract
The current diagnostic work-up and monitoring of idiopathic pulmonary fibrosis (IPF) is often invasive and time consuming. Breath analysis by e-nose technology has shown potential in the diagnosis of numerous respiratory diseases. In this pilot study, we investigated whether exhaled breath analysis by an e-nose could discriminate among patients with IPF, healthy controls and COPD. Second, we verified whether these classification could be repeated in a set of newly recruited patients as external validation. Third, we evaluated any significant relationships between exhaled VOCs and Bronchoalveolar lavage fluid (BALF) in IPF patients. We enrolled 32 patients with well-characterized IPF, 33 individuals with COPD and 36 healthy controls. An electronic nose (Cyranose 320) was used to analyze exhaled breath samples. Raw data were processed by Principal component reduction and linear discriminant analysis. External validation in newly recruited patients (10 IPF, 10 COPD and 10 controls) was tested using the previous training set. Exhaled VOC-profiles of patients with IPF were distinct from those of healthy controls (CVA = 98.5%) as well as those with COPD (CVA = 80.0%). External validation confirmed the above findings (IPF vs COPD vs healthy controls, CVA 96.7%). Moreover, a significant inversely proportional correlation was shown between BALF total cell count and both Principal Components 1 and 2 (r = 0.543, r2 = 0.295, p < 0.01; r = 0.501, r2 = 0.251; p < 0.01, respectively). The exhaled breath Volatile Organic Compounds- profile of patients with IPF can be detected by an electronic nose. This suggests that breath analysis has potential for diagnosis and/or monitoring of IPF.
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Affiliation(s)
- Silvano Dragonieri
- Respiratory Diseases, University of Bari, Bari, Italy. Author to whom any correspondence should be addressed
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Abstract
The application of nanotechnology, molecular biotechnologies, and nano-sciences for medical purposes has been termed nanomedicine, a promising growing area of medical research. The aim of this paper is to provide an overview of and discuss nanotechnology applications in the early epochs of life, from transplacental transfer to neonatal/pediatric conditions. Diagnostic and therapeutic applications, mainly related to the respiratory tract, the neurosensory system, and infections, are explored and discussed. Preclinical studies show promising results for a variety of conditions, including for the treatment of pregnancy complications and fetal, neonatal, and pediatric diseases. However, given the complexity of the functions and interactions between the placenta and the fetus, and the complex and incompletely understood determinants of tissue growth and differentiation during early life, there is a need for much more data to confirm the safety and efficacy of nanotechnology in this field.
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Xia Y, Hong Y, Geng R, Li X, Qu A, Zhou Z, Zhang Z. Amine-Functionalized ZIF-8 as a Fluorescent Probe for Breath Volatile Organic Compound Biomarker Detection of Lung Cancer Patients. ACS OMEGA 2020; 5:3478-3486. [PMID: 32118162 PMCID: PMC7045493 DOI: 10.1021/acsomega.9b03793] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/07/2019] [Accepted: 01/28/2020] [Indexed: 05/09/2023]
Abstract
The highly thermally and chemically stable imidazole framework ZIF-8 samples were separately postmodified with amine groups by using N,N'-dimethylethylenediamine (MMEN) and N,N-dimethylaminoethylamine (MAEA), which had the same molecular formula but different structures. The modified ZIF-8 samples (ZIF-8@amine) were thoroughly characterized, including powder X-ray diffractometry, Fourier-transformed infrared spectroscopy, and physical adsorption at 77 K by nitrogen, thermogravimetric analysis, and photophysical characterization. Results showed that after modification, the Brunauer-Emmett-Teller surface area and total pore volume both increased, almost one time higher than those of the original ZIF-8 sample, and followed the order: ZIF-8-MMEN > ZIF-8-MAEA > ZIF-8. Furthermore, the N-H group was successfully grafted into the modified ZIF-8 samples. To examine the sensing properties of the modified ZIF-8@amine samples toward the breath biomarkers of lung cancer, five potential volatile organic compound biomarkers were used as analytes. ZIF-8-MMEN and ZIF-8-MAEA revealed a unique capacity for sensing hexanal, ethylbenzene, and 1-propanol with high efficiency and sensitivity. The three samples all did not show sensing ability toward styrene and isoprene. In addition, ZIF-8, ZIF-8-MMEN, and ZIF-8-MAEA all can sense hexanal with a detection limit as low as 1 ppb.
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Affiliation(s)
- Yuanhan Xia
- Institute
of Mass Spectrometer and Atmospheric Environment, Jinan University, Guangzhou 510632, China
- Guangdong
Provincial Engineering Research Center for Online Source Apportionment
System of Air Pollution, Guangzhou 510632, China
| | - Yi Hong
- Institute
of Mass Spectrometer and Atmospheric Environment, Jinan University, Guangzhou 510632, China
- Guangdong
Provincial Engineering Research Center for Online Source Apportionment
System of Air Pollution, Guangzhou 510632, China
| | - Rongchuang Geng
- College
of Pharmacy, Henan University of Chinese
Medicine, Zhengzhou, Henan 450046, China
| | - Xue Li
- Institute
of Mass Spectrometer and Atmospheric Environment, Jinan University, Guangzhou 510632, China
- Guangdong
Provincial Engineering Research Center for Online Source Apportionment
System of Air Pollution, Guangzhou 510632, China
| | - Ailan Qu
- College
of Chemistry and Materials Science, Jinan
University, Guangzhou 510632, China
| | - Zhen Zhou
- Institute
of Mass Spectrometer and Atmospheric Environment, Jinan University, Guangzhou 510632, China
- Guangdong
Provincial Engineering Research Center for Online Source Apportionment
System of Air Pollution, Guangzhou 510632, China
| | - Zhijuan Zhang
- Institute
of Mass Spectrometer and Atmospheric Environment, Jinan University, Guangzhou 510632, China
- Guangdong
Provincial Engineering Research Center for Online Source Apportionment
System of Air Pollution, Guangzhou 510632, China
- College
of Pharmacy, Henan University of Chinese
Medicine, Zhengzhou, Henan 450046, China
- E-mail: ,
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Abstract
PURPOSE OF REVIEW The long-term management goals of the inflammatory airway diseases asthma and chronic obstructive pulmonary disease (COPD) are similar and focus on symptom control and reduction of exacerbation frequency and severity. Treatable traits have recently been postulated as a management concept which complements the traditional diagnostic labels 'asthma' and 'COPD', thereby focusing on therapy targeted to a patients' individual disease-associated characteristics. Exhaled volatile organic compounds (VOCs) may be utilized as noninvasive biomarker for disease activity or manifestation in asthma and COPD. In this review, we provide an overview of the current achievements concerning exhaled breath analysis in the field of uncontrolled chronic airways diseases. RECENT FINDINGS Monitoring of (airway) inflammation and identification of (molecular) phenotypic characteristics in asthma and COPD through exhaled VOC analysis by either mass spectrometry (MS) based or sensor-driven electronic nose technology (eNose) seems to be feasible, however pending confirmation could hamper the valorization of breathomics into clinical tests. SUMMARY Exhaled VOC analysis and the management of asthma and COPD through the concept of pulmonary treatable traits are an interesting match. To develop exhaled breath analysis into an added value for pulmonary treatable traits, multicentre studies are required following international standards for study populations, sampling methods and analytical strategies enabling external validation.
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