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Journal articles on the topic 'Breathomics'

To see the other types of publications on this topic, follow the link: Breathomics.

Author: Grafiati

Published: 10 March 2023

Last updated: 11 March 2023

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1

van der Schee, Marc Philippe, Tamara Paff, Paul Brinkman, Willem Marinus Christiaan van Aalderen, Eric Gerardus Haarman, and Peter Jan Sterk. "Breathomics in Lung Disease." Chest 147, no. 1 (January 2015): 224–31. http://dx.doi.org/10.1378/chest.14-0781.

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2

Zolkipli-Cunningham, Zarazuela, Jane C. Naviaux, Tomohiro Nakayama, Charlotte M. Hirsch, Jonathan M. Monk, Kefeng Li, Lin Wang, et al. "Metabolic and behavioral features of acute hyperpurinergia and the maternal immune activation mouse model of autism spectrum disorder." PLOS ONE 16, no. 3 (March 18, 2021): e0248771. http://dx.doi.org/10.1371/journal.pone.0248771.

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Since 2012, studies in mice, rats, and humans have suggested that abnormalities in purinergic signaling may be a final common pathway for many genetic and environmental causes of autism spectrum disorder (ASD). The current study in mice was conducted to characterize the bioenergetic, metabolomic, breathomic, and behavioral features of acute hyperpurinergia triggered by systemic injection of the purinergic agonist and danger signal, extracellular ATP (eATP). Responses were studied in C57BL/6J mice in the maternal immune activation (MIA) model and controls. Basal metabolic rates and locomotor activity were measured in CLAMS cages. Plasma metabolomics measured 401 metabolites. Breathomics measured 98 volatile organic compounds. Intraperitoneal eATP dropped basal metabolic rate measured by whole body oxygen consumption by 74% ± 6% (mean ± SEM) and rectal temperature by 6.2˚ ± 0.3˚C in 30 minutes. Over 200 metabolites from 37 different biochemical pathways where changed. Breathomics showed an increase in exhaled carbon monoxide, dimethylsulfide, and isoprene. Metabolomics revealed an acute increase in lactate, citrate, purines, urea, dopamine, eicosanoids, microbiome metabolites, oxidized glutathione, thiamine, niacinamide, and pyridoxic acid, and decreased folate-methylation-1-carbon intermediates, amino acids, short and medium chain acyl-carnitines, phospholipids, ceramides, sphingomyelins, cholesterol, bile acids, and vitamin D similar to some children with ASD. MIA animals were hypersensitive to postnatal exposure to eATP or poly(IC), which produced a rebound increase in body temperature that lasted several weeks before returning to baseline. Acute hyperpurinergia produced metabolic and behavioral changes in mice. The behaviors and metabolic changes produced by ATP injection were associated with mitochondrial functional changes that were profound but reversible.

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3

Peel, Adam M., Yoon K. Loke, and Andrew M. Wilson. "Asthma Breathomics and Biomedium Consideration." Chest 153, no. 5 (May 2018): 1283. http://dx.doi.org/10.1016/j.chest.2018.02.029.

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4

Drera, Giovanni, Sonia Freddi, Aleksei V. Emelianov, Ivan I. Bobrinetskiy, Maria Chiesa, Michele Zanotti, Stefania Pagliara, et al. "Exploring the performance of a functionalized CNT-based sensor array for breathomics through clustering and classification algorithms: from gas sensing of selective biomarkers to discrimination of chronic obstructive pulmonary disease." RSC Advances 11, no. 48 (2021): 30270–82. http://dx.doi.org/10.1039/d1ra03337a.

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5

Kistenev, Yury, Alexey Borisov, Victor Nikolaev, Denis Vrazhnov, and Dmytry Kuzmin. "Laser photoacoustic spectroscopy applications in breathomics." Journal of Biomedical Photonics & Engineering 5, no. 1 (March 28, 2019): 010303. http://dx.doi.org/10.18287/jbpe19.05.010303.

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6

Freddi, Sonia, Camilla Marzuoli, Stefania Pagliara, Giovanni Drera, and Luigi Sangaletti. "Targeting biomarkers in the gas phase through a chemoresistive electronic nose based on graphene functionalized with metal phthalocyanines." RSC Advances 13, no. 1 (2023): 251–63. http://dx.doi.org/10.1039/d2ra07607a.

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An electronic nose based on graphene chemiresistor sensors functionalized with phthalocyanines has been developed to detect selected biomarkers in the gas phase for breathomics, environmental monitoring, and food control applications.

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7

Ivan, Ignatius, Ignatius Ivan, Maureen Miracle Stella, Maureen Miracle Stella, Kevin Tandarto, Kevin Tandarto, Fanny Budiman, Fanny Budiman, Freggy Spicano Joprang, and Freggy Spicano Joprang. "Plasmodium falciparum Breath Metabolomics (Breathomics) Analysis as a Non-Invasive Practical Method to Diagnose Malaria in Pediatric." Indonesian Journal of Tropical and Infectious Disease 9, no. 1 (April 27, 2021): 24. http://dx.doi.org/10.20473/ijtid.v9i1.24069.

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Children under 5 years of age are particularly vulnerable to malaria. Malaria has caused 445,000 deaths worldwide. Currently, rapid diagnostic tests (RDTs) are the fastest method to diagnose malaria. However, there are limitations that exist such as low sensitivity in detecting infections with low parasitemia. Practical, non-invasive and high ability tests to detect parasite are needed to find specific biomarkers for P. falciparum infection to determine the potential of P. falciparum 4 thioether in breathomics analysis by GC-MS as a practical non-invasive method in diagnosing malaria in pediatrics. Literature reviews from Google Scholar and ProQuest were published no later than the last 5 years. The concept of breathomics is that the breath’s volatile organic compounds (VOCs) profile is altered when the health condition changes. Breath samples from individuals infected with P. falciparum malaria were taken by exhalation. Through GC-MS analysis, it was found that 4 thioether compounds (allyl methyl sulfide (AMS), 1-methylthio-propane, (Z) -1-methylthio-1-propene and (E) -1-methylthio-1-propene) underwent a significant change in concentration during the infection. Based on experiments conducted on mice and humans, the breathomics method is known to be able to detect parasitemia levels up to <100 parasites/µL, has a sensitivity level of about 71% to 91% and a specificity of about 75% to 94%. The discovery of 4 thioether compounds by GC-MS is a strong indication of malaria, because it has the potential for high sensitivity and specificity, and the detection power exceeds the ability of RDTs.

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8

Azim, Adnan, Clair Barber, Paddy Dennison, John Riley, and Peter Howarth. "Exhaled volatile organic compounds in adult asthma: a systematic review." European Respiratory Journal 54, no. 3 (July 4, 2019): 1900056. http://dx.doi.org/10.1183/13993003.00056-2019.

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The search for biomarkers that can guide precision medicine in asthma, particularly those that can be translated to the clinic, has seen recent interest in exhaled volatile organic compounds (VOCs). Given the number of studies reporting “breathomics” findings and its growing integration in clinical trials, we performed a systematic review of the literature to summarise current evidence and understanding of breathomics technology in asthma.A PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses)-oriented systematic search was performed (CRD42017084145) of MEDLINE, Embase and the Cochrane databases to search for any reports that assessed exhaled VOCs in adult asthma patients, using the following terms (asthma AND (volatile organic compounds AND exhaled) OR breathomics).Two authors independently determined the eligibility of 2957 unique records, of which 66 underwent full-text review. Data extraction and risk of bias assessment was performed on the 22 studies deemed to fulfil the search criteria. The studies are described in terms of methodology and the evidence narratively summarised under the following clinical headings: diagnostics, phenotyping, treatment stratification, treatment monitoring and exacerbation prediction/assessment.Our review found that most studies were designed to assess diagnostic potential rather than focus on underlying biology or treatable traits. Results are generally limited by a lack of methodological standardisation and external validation and by insufficiently powered studies, but there is consistency across the literature that exhaled VOCs are sensitive to underlying inflammation. Modern studies are applying robust breath analysis workflows to large multi-centre study designs, which should unlock the full potential of measurement of exhaled volatile organic compounds in airways diseases such as asthma.

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9

Brinkman, Paul, Anke-Hilse Maitland-van der Zee, and Ariane H. Wagener. "Breathomics and treatable traits for chronic airway diseases." Current Opinion in Pulmonary Medicine 25, no. 1 (January 2019): 94–100. http://dx.doi.org/10.1097/mcp.0000000000000534.

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10

Ferraro, Valentina Agnese, Silvia Carraro, Paola Pirillo, Antonina Gucciardi, Gabriele Poloniato, Matteo Stocchero, Giuseppe Giordano, Stefania Zanconato, and Eugenio Baraldi. "Breathomics in Asthmatic Children Treated with Inhaled Corticosteroids." Metabolites 10, no. 10 (September 29, 2020): 390. http://dx.doi.org/10.3390/metabo10100390.

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Background: “breathomics” enables indirect analysis of metabolic patterns underlying a respiratory disease. In this study, we analyze exhaled breath condensate (EBC) in asthmatic children before (T0) and after (T1) a three-week course of inhaled beclomethasone dipropionate (BDP). Methods: we recruited steroid-naive asthmatic children for whom inhaled steroids were indicated and healthy children, evaluating asthma control, spirometry and EBC (in asthmatics at T0 and T1). A liquid-chromatography–mass-spectrometry untargeted analysis was applied to EBC and a mass spectrometry-based target analysis to urine samples. Results: metabolomic analysis discriminated asthmatic (n = 26) from healthy children (n = 16) at T0 and T1, discovering 108 and 65 features relevant for the discrimination, respectively. Searching metabolomics databases, seven putative biomarkers with a plausible role in asthma biochemical–metabolic processes were found. After BDP treatment, asthmatic children, in the face of an improved asthma control (p < 0.001) and lung function (p = 0.01), showed neither changes in EBC metabolomic profile nor in urinary endogenous steroid profile. Conclusions: “breathomics” can discriminate asthmatic from healthy children, with prostaglandin, fatty acid and glycerophospholipid as putative markers. The three-week course of BDP—in spite of a significant clinical improvement—was not associated with changes in EBC metabolic arrangement and urinary steroid profile.

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11

Sterk, Peter J., Niki Fens, and G. Elisiana Carpagnano. "Wake-up call by breathomics in sleep apnoea." European Respiratory Journal 42, no. 1 (June 30, 2013): 1–4. http://dx.doi.org/10.1183/09031936.00000113.

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12

FENS, N., R. A. DOUMA, P. J. STERK, and P. W. KAMPHUISEN. "Breathomics as a diagnostic tool for pulmonary embolism." Journal of Thrombosis and Haemostasis 8, no. 12 (December 2010): 2831–33. http://dx.doi.org/10.1111/j.1538-7836.2010.04064.x.

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13

Peel, Adam M., Andrew M. Wilson, and Yoon K. Loke. "Asthma breathomics-promising biomarkers in need of validation." Pediatric Pulmonology 53, no. 3 (January 23, 2018): 263–65. http://dx.doi.org/10.1002/ppul.23941.

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14

Neerincx, Anne H., Susanne J. H. Vijverberg, Lieuwe D. J. Bos, Paul Brinkman, Marc P. van der Schee, Rianne de Vries, Peter J. Sterk, and Anke-Hilse Maitland-van der Zee. "Breathomics from exhaled volatile organic compounds in pediatric asthma." Pediatric Pulmonology 52, no. 12 (October 30, 2017): 1616–27. http://dx.doi.org/10.1002/ppul.23785.

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15

Daniel, DArul Pon, and K. Thangavel. "Breathomics for gastric cancer classification using back-propagation neural network." Journal of Medical Signals & Sensors 6, no. 3 (2016): 172. http://dx.doi.org/10.4103/2228-7477.186879.

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16

Sterk, Peter J. "Modern Inflammatory Phenotyping of Asthma. Breathomics Is Here to Stay." American Journal of Respiratory and Critical Care Medicine 200, no. 4 (August 15, 2019): 405–6. http://dx.doi.org/10.1164/rccm.201904-0733ed.

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17

Bos, Lieuwe D., Peter J. Sterk, and Stephen J. Fowler. "Breathomics in the setting of asthma and chronic obstructive pulmonary disease." Journal of Allergy and Clinical Immunology 138, no. 4 (October 2016): 970–76. http://dx.doi.org/10.1016/j.jaci.2016.08.004.

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18

Ray, Bishakha, Saurabh Parmar, Varsha Vijayan, Satyendra Vishwakarma, and Suwarna Datar. "Detection of trace volatile organic compounds in spiked breath samples: a leap towards breathomics." Nanotechnology 33, no. 20 (February 21, 2022): 205505. http://dx.doi.org/10.1088/1361-6528/ac4c5e.

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Abstract Breathomics is the future of non-invasive point-of-care devices. The field of breathomics can be split into the isolation of disease-specific volatile organic compounds (VOCs) and their detection. In the present work, an array of five quartz tuning fork (QTF)-based sensors modified by polymer with nanomaterial additive has been utilized. The array has been used to detect samples of human breath spiked with ∼0.5 ppm of known VOCs namely, acetone, acetaldehyde, octane, decane, ethanol, methanol, styrene, propylbenzene, cyclohexanone, butanediol, and isopropyl alcohol which are bio-markers for certain diseases. Polystyrene was used as the base polymer and it was functionalized with 4 different fillers namely, silver nanoparticles-reduced graphene oxide composite, titanium dioxide nanoparticles, zinc ferrite nanoparticles-reduced graphene oxide composite, and cellulose acetate. Each of these fillers enhanced the selectivity of a particular sensor towards a certain VOC compared to the pristine polystyrene-modified sensor. Their interaction with the VOCs in changing the mechanical properties of polymer giving rise to change in the resonant frequency of QTF is used as sensor response for detection. The interaction of functionalized polymers with VOCs was analyzed by FTIR and UV–vis spectroscopy. The collective sensor response of five sensors is used to identify VOCs using an ensemble classifier with 92.8% accuracy of prediction. The accuracy of prediction improved to 96% when isopropyl alcohol, ethanol, and methanol were considered as one class.

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19

Lamote, Kevin, Kristiaan Nackaerts, and Jan P. van Meerbeeck. "Strengths, Weaknesses, and Opportunities of Diagnostic Breathomics in Pleural Mesothelioma—A Hypothesis." Cancer Epidemiology Biomarkers & Prevention 23, no. 6 (April 4, 2014): 898–908. http://dx.doi.org/10.1158/1055-9965.epi-13-0737.

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20

Couto, Mariana, Corália Barbosa, Diana Silva, Alisa Rudnitskaya, Luís Delgado, André Moreira, and Sílvia M. Rocha. "Oxidative stress in asthmatic and non-asthmatic adolescent swimmers-A breathomics approach." Pediatric Allergy and Immunology 28, no. 5 (June 14, 2017): 452–57. http://dx.doi.org/10.1111/pai.12729.

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21

Jia, Zhunan, Abhijeet Patra, Viknish Kutty, and Thirumalai Venkatesan. "Critical Review of Volatile Organic Compound Analysis in Breath and In Vitro Cell Culture for Detection of Lung Cancer." Metabolites 9, no. 3 (March 18, 2019): 52. http://dx.doi.org/10.3390/metabo9030052.

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Breath analysis is a promising technique for lung cancer screening. Despite the rapid development of breathomics in the last four decades, no consistent, robust, and validated volatile organic compound (VOC) signature for lung cancer has been identified. This review summarizes the identified VOC biomarkers from both exhaled breath analysis and in vitro cultured lung cell lines. Both clinical and in vitro studies have produced inconsistent, and even contradictory, results. Methodological issues that lead to these inconsistencies are reviewed and discussed in detail. Recommendations on addressing specific issues for more accurate biomarker studies have also been made.

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22

Arasaradnam, R. P., M. McFarlane, K. Ling, S. Wurie, N. O’Connell, C. U. Nwokolo, K. D. Bardhan, J. Skinner, R. S. Savage, and J. A. Covington. "Breathomics—exhaled volatile organic compound analysis to detect hepatic encephalopathy: a pilot study." Journal of Breath Research 10, no. 1 (February 11, 2016): 016012. http://dx.doi.org/10.1088/1752-7155/10/1/016012.

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23

Ridolo, Erminia, Cristoforo Incorvaia, Enrico Heffler, Carlo Cavaliere, Giovanni Paoletti, and Giorgio Walter Canonica. "The Present and Future of Allergen Immunotherapy in Personalized Medicine." Journal of Personalized Medicine 12, no. 5 (May 10, 2022): 774. http://dx.doi.org/10.3390/jpm12050774.

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Allergic diseases are particularly suitable for personalized medicine, because they meet the needs for therapeutic success, which include a known molecular mechanism of the disease, a diagnostic tool for that disease and a treatment that blocks this mechanism. A range of tools is available for personalized allergy diagnosis, including molecular diagnostics, treatable traits and omics (i.e., proteomics, epigenomics, metabolomics, transcriptomics and breathomics), to predict patient response to therapies, detect biomarkers and mediators and assess disease control status. Such tools enhance allergen immunotherapy. Higher diagnostic accuracy results in a significant increase (based on a greater performance achieved with personalized treatment) in efficacy, further increasing the known and unique characteristics of a treatment designed to work on allergy causes.

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24

Freddi, Sonia, and Luigi Sangaletti. "Trends in the Development of Electronic Noses Based on Carbon Nanotubes Chemiresistors for Breathomics." Nanomaterials 12, no. 17 (August 29, 2022): 2992. http://dx.doi.org/10.3390/nano12172992.

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The remarkable potential of breath analysis in medical care and diagnosis, and the consequent development of electronic noses, is currently attracting the interest of the research community. This is mainly due to the possibility of applying the technique for early diagnosis, screening campaigns, or tracking the effectiveness of treatment. Carbon nanotubes (CNTs) are known to be good candidates for gas sensing, and they have been recently considered for the development of electronic noses. The present work has the aim of reviewing the available literature on the development of CNTs-based electronic noses for breath analysis applications, detailing the functionalization procedure used to prepare the sensors, the breath sampling techniques, the statistical analysis methods, the diseases under investigation, and the population studied. The review is divided in two main sections: one focusing on the e-noses completely based on CNTs and one reporting on the e-noses that feature sensors based on CNTs, along with sensors based on other materials. Finally, a classification is presented among studies that report on the e-nose capability to discriminate biomarkers, simulated breath, and animal or human breath.

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25

Campagna, Davide, Fabio Cibella, Pasquale Caponnetto, Maria Domenica Amaradio, Massimo Caruso, Jaymin B. Morjaria, Mario Malerba, and Riccardo Polosa. "Changes in breathomics from a 1-year randomized smoking cessation trial of electronic cigarettes." European Journal of Clinical Investigation 46, no. 8 (July 8, 2016): 698–706. http://dx.doi.org/10.1111/eci.12651.

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26

Li, Wenwen, Yong Liu, Yu Liu, Shouquan Cheng, and Yixiang Duan. "Exhaled isopropanol: new potential biomarker in diabetic breathomics and its metabolic correlations with acetone." RSC Advances 7, no. 28 (2017): 17480–88. http://dx.doi.org/10.1039/c7ra00815e.

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Concomitant findings of acetone (ACE) and isopropanol (IPA) in blood and other biological samples have been reported in diabetic decedents and clinic cases, but exhaled IPA has rarely been studied in breath research.

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27

Kiss, Helga, Zoltán Örlős, Áron Gellért, Zsolt Megyesfalvi, Angéla Mikáczó, Anna Sárközi, Attila Vaskó, Zsuzsanna Miklós, and Ildikó Horváth. "Exhaled Biomarkers for Point-of-Care Diagnosis: Recent Advances and New Challenges in Breathomics." Micromachines 14, no. 2 (February 4, 2023): 391. http://dx.doi.org/10.3390/mi14020391.

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Cancers, chronic diseases and respiratory infections are major causes of mortality and present diagnostic and therapeutic challenges for health care. There is an unmet medical need for non-invasive, easy-to-use biomarkers for the early diagnosis, phenotyping, predicting and monitoring of the therapeutic responses of these disorders. Exhaled breath sampling is an attractive choice that has gained attention in recent years. Exhaled nitric oxide measurement used as a predictive biomarker of the response to anti-eosinophil therapy in severe asthma has paved the way for other exhaled breath biomarkers. Advances in laser and nanosensor technologies and spectrometry together with widespread use of algorithms and artificial intelligence have facilitated research on volatile organic compounds and artificial olfaction systems to develop new exhaled biomarkers. We aim to provide an overview of the recent advances in and challenges of exhaled biomarker measurements with an emphasis on the applicability of their measurement as a non-invasive, point-of-care diagnostic and monitoring tool.

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28

Moninuola, Funmilayo S., Oluwadamilola Oshin, Emmanuel Adetiba, Anthony A. Atayero, Ademola Adeyeye, Victoria Oguntosin, Olushola O. James, et al. "A Review of Technological Progression from Radiomics to Breathomics for Early Detection of Lung Cancer." Journal of Computer Science 17, no. 11 (November 1, 2021): 1071–84. http://dx.doi.org/10.3844/jcssp.2021.1071.1084.

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29

Wang, Peiyu, Qi Huang, Shushi Meng, Teng Mu, Zheng Liu, Mengqi He, Qingyun Li, Song Zhao, Shaodong Wang, and Mantang Qiu. "Identification of lung cancer breath biomarkers based on perioperative breathomics testing: A prospective observational study." eClinicalMedicine 47 (May 2022): 101384. http://dx.doi.org/10.1016/j.eclinm.2022.101384.

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30

de Vries, Rianne, Yennece W. F. Dagelet, Pien Spoor, Erik Snoey, Patrick M. C. Jak, Paul Brinkman, Erica Dijkers, et al. "Clinical and inflammatory phenotyping by breathomics in chronic airway diseases irrespective of the diagnostic label." European Respiratory Journal 51, no. 1 (January 2018): 1701817. http://dx.doi.org/10.1183/13993003.01817-2017.

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Asthma and chronic obstructive pulmonary disease (COPD) are complex and overlapping diseases that include inflammatory phenotypes. Novel anti-eosinophilic/anti-neutrophilic strategies demand rapid inflammatory phenotyping, which might be accessible from exhaled breath.Our objective was to capture clinical/inflammatory phenotypes in patients with chronic airway disease using an electronic nose (eNose) in a training and validation set.This was a multicentre cross-sectional study in which exhaled breath from asthma and COPD patients (n=435; training n=321 and validation n=114) was analysed using eNose technology. Data analysis involved signal processing and statistics based on principal component analysis followed by unsupervised cluster analysis and supervised linear regression.Clustering based on eNose resulted in five significant combined asthma and COPD clusters that differed regarding ethnicity (p=0.01), systemic eosinophilia (p=0.02) and neutrophilia (p=0.03), body mass index (p=0.04), exhaled nitric oxide fraction (p<0.01), atopy (p<0.01) and exacerbation rate (p<0.01). Significant regression models were found for the prediction of eosinophilic (R2=0.581) and neutrophilic (R2=0.409) blood counts based on eNose. Similar clusters and regression results were obtained in the validation set.Phenotyping a combined sample of asthma and COPD patients using eNose provides validated clusters that are not determined by diagnosis, but rather by clinical/inflammatory characteristics. eNose identified systemic neutrophilia and/or eosinophilia in a dose-dependent manner.

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Yishai Aviram, Lilach, Dana Marder, Hagit Prihed, Konstantin Tartakovsky, Daniel Shem-Tov, Regina Sinelnikov, Shai Dagan, and Nitzan Tzanani. "pyAIR—A New Software Tool for Breathomics Applications—Searching for Markers in TD-GC-HRMS Analysis." Molecules 27, no. 7 (March 23, 2022): 2063. http://dx.doi.org/10.3390/molecules27072063.

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Volatile metabolites in exhaled air have promising potential as diagnostic biomarkers. However, the combination of low mass, similar chemical composition, and low concentrations introduces the challenge of sorting the data to identify markers of value. In this paper, we report the development of pyAIR, a software tool for searching for volatile organic compounds (VOCs) markers in multi-group datasets, tailored for Thermal-Desorption Gas-Chromatography High Resolution Mass-Spectrometry (TD-GC-HRMS) output. pyAIR aligns the compounds between samples by spectral similarity coupled with retention times (RT), and statistically compares the groups for compounds that differ by intensity. This workflow was successfully tested and evaluated on gaseous samples spiked with 27 model VOCs at six concentrations, divided into three groups, down to 0.3 nL/L. All analytes were correctly detected and aligned. More than 80% were found to be significant markers with a p-value < 0.05; several were classified as possibly significant markers (p-value < 0.1), while a few were removed due to background level. In all group comparisons, low rates of false markers were found. These results showed the potential of pyAIR in the field of trace-level breathomics, with the capability to differentially examine several groups, such as stages of illness.

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32

Beale, David, Oliver Jones, Avinash Karpe, Saravanan Dayalan, Ding Oh, Konstantinos Kouremenos, Warish Ahmed, and Enzo Palombo. "A Review of Analytical Techniques and Their Application in Disease Diagnosis in Breathomics and Salivaomics Research." International Journal of Molecular Sciences 18, no. 1 (December 23, 2016): 24. http://dx.doi.org/10.3390/ijms18010024.

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33

Smolinska, A., A.-Ch Hauschild, R. R. R. Fijten, J. W. Dallinga, J. Baumbach, and F. J. van Schooten. "Current breathomics—a review on data pre-processing techniques and machine learning in metabolomics breath analysis." Journal of Breath Research 8, no. 2 (April 8, 2014): 027105. http://dx.doi.org/10.1088/1752-7155/8/2/027105.

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34

Covington, J., M. Mcfarlane, L. Kho, S. Wurie, N. O'Connell, R. Savage, C. Nwokolo, KD Bardhan, and R. Arasaradnam. "PWE-110 Breathomics – distinguishing minimal from overt hepatic encephalopathy using volatile organic compound analysis: a pilot study." Gut 64, Suppl 1 (June 2015): A260.2—A261. http://dx.doi.org/10.1136/gutjnl-2015-309861.559.

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35

Huang, Qi, Shaodong Wang, Qingyun Li, Peiyu Wang, Jianfeng Li, Shushi Meng, Hang Li, et al. "Assessment of Breathomics Testing Using High-Pressure Photon Ionization Time-of-Flight Mass Spectrometry to Detect Esophageal Cancer." JAMA Network Open 4, no. 10 (October 5, 2021): e2127042. http://dx.doi.org/10.1001/jamanetworkopen.2021.27042.

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36

Arasaradnam, Ramesh, Ling Kho, Michael McFarlane, Subiatu Wurie, Nicola O'connell, Richard Savage, Chuka Nwokolo, Karna D. Bardhan, and James Covington. "Mo1019 Breathomics - Distinguishing Minimal From Overt Hepatic Encephalopathy by Volatile Organic Compound Detection in Breath: A Pilot Study." Gastroenterology 148, no. 4 (April 2015): S—1064—S—1065. http://dx.doi.org/10.1016/s0016-5085(15)33638-6.

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37

Stavropoulos, Georgios, Daisy M. A. E. Jonkers, Zlatan Mujagic, Ger H. Koek, Ad A. M. Masclee, Marieke J. Pierik, Jan W. Dallinga, Frederik-Jan Van Schooten, and Agnieszka Smolinska. "Implementation of quality controls is essential to prevent batch effects in breathomics data and allow for cross-study comparisons." Journal of Breath Research 14, no. 2 (March 19, 2020): 026012. http://dx.doi.org/10.1088/1752-7163/ab7b8d.

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Henderson, Ben, Guilherme Lopes Batista, Carlo G. Bertinetto, Joris Meurs, Dušan Materić, Coen C. W. G. Bongers, Neeltje A. E. Allard, et al. "Exhaled Breath Reflects Prolonged Exercise and Statin Use during a Field Campaign." Metabolites 11, no. 4 (March 24, 2021): 192. http://dx.doi.org/10.3390/metabo11040192.

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Volatile organic compounds (VOCs) in exhaled breath provide insights into various metabolic processes and can be used to monitor physiological response to exercise and medication. We integrated and validated in situ a sampling and analysis protocol using proton transfer reaction time-of-flight mass spectrometry (PTR-ToF-MS) for exhaled breath research. The approach was demonstrated on a participant cohort comprising users of the cholesterol-lowering drug statins and non-statin users during a field campaign of three days of prolonged and repeated exercise, with no restrictions on food or drink consumption. The effect of prolonged exercise was reflected in the exhaled breath of participants, and relevant VOCs were identified. Most of the VOCs, such as acetone, showed an increase in concentration after the first day of walking and subsequent decrease towards baseline levels prior to walking on the second day. A cluster of short-chain fatty acids including acetic acid, butanoic acid, and propionic acid were identified in exhaled breath as potential indicators of gut microbiota activity relating to exercise and drug use. We have provided novel information regarding the use of breathomics for non-invasive monitoring of changes in human metabolism and especially for the gut microbiome activity in relation to exercise and the use of medication, such as statins.

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Trefz, Phillip, Sibylle C. Schmidt, Pritam Sukul, Jochen K. Schubert, Wolfram Miekisch, and Dagmar-Christiane Fischer. "Non-Invasive Assessment of Metabolic Adaptation in Paediatric Patients Suffering from Type 1 Diabetes Mellitus." Journal of Clinical Medicine 8, no. 11 (October 26, 2019): 1797. http://dx.doi.org/10.3390/jcm8111797.

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An analysis of exhaled volatile organic compounds (VOC) may deliver systemic information quicker than available invasive techniques. Metabolic aberrations in pediatric type 1 diabetes (T1DM) are of high clinical importance and could be addressed via breathomics. Real-time breath analysis was combined with continuous glucose monitoring (CGM) and blood tests in children suffering from T1DM and age-matched healthy controls in a highly standardized setting. CGM and breath-resolved VOC analysis were performed every 5 minutes for 9 hours and blood was sampled at pre-defined time points. Per participant (n = 44) food intake and physical activity were identical and a total of 22 blood samples and 93 minutes of breath samples were investigated. The inter-individual variability of glucose, insulin, glucagon, leptin, and soluble leptin receptor relative to food intake differed distinctly between patients and controls. In T1DM patients, the exhaled amounts of acetone, 2-propanol, and pentanal correlated to glucose concentrations. Of note, the strength of these correlations strongly depended on the interval between food intake and breath sampling. Our data suggests that metabolic adaptation through postprandial hyperglycemia and related oxidative stress is immediately reflected in exhaled breath VOC concentrations. Clinical translations of our findings may enable point-of-care applicability of online breath analysis towards personalized medicine.

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Catino, Annamaria, Gianluigi de Gennaro, Alessia Di Gilio, Laura Facchini, Domenico Galetta, Jolanda Palmisani, Francesca Porcelli, and Niccolò Varesano. "Breath Analysis: A Systematic Review of Volatile Organic Compounds (VOCs) in Diagnostic and Therapeutic Management of Pleural Mesothelioma." Cancers 11, no. 6 (June 14, 2019): 831. http://dx.doi.org/10.3390/cancers11060831.

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Malignant pleural mesothelioma (MPM) is a rare neoplasm related to asbestos exposure and with high mortality rate. The management of patients with MPM is complex and controversial, particularly with regard to early diagnosis. In the last few years, breath analysis has been greatly implemented with this aim. In this review the strengths of breath analysis and preliminary results in searching breath biomarkers of MPM are highlighted and discussed, respectively. Through a systematic electronic literature search, collecting papers published from 2000 until December 2018, fifteen relevant scientific papers were selected. All papers considered were prospective, comparative, observational case–control studies although every single one pilot and based on a relatively small number of samples. The identification of diagnostic VOCs pattern, through breath sample characterization and the statistical data treatment, allows to obtain a strategic information for clinical diagnostics. To date the collected data provide just preliminary information and, despite the promising results and diagnostic accuracy, conclusions cannot be generalized due to the limited number of individuals included in each cohort study. Furthermore none of studies was externally validated, although validation process is a necessary step towards clinical implementation. Breathomics-based biomarker approach should be further explored to confirm and validate preliminary findings and to evaluate its potential role in monitoring the therapeutic response.

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Zanella, Delphine, Julien Guiot, Pierre-Hugues Stefanuto, Laurie Giltay, Monique Henket, Françoise Guissard, Béatrice André, et al. "Breathomics to diagnose systemic sclerosis using thermal desorption and comprehensive two-dimensional gas chromatography high-resolution time-of-flight mass spectrometry." Analytical and Bioanalytical Chemistry 413, no. 14 (April 26, 2021): 3813–22. http://dx.doi.org/10.1007/s00216-021-03333-4.

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Tsou, Ping-Hsien, Zong-Lin Lin, Yu-Chiang Pan, Hui-Chen Yang, Chien-Jen Chang, Sheng-Kai Liang, Yueh-Feng Wen, et al. "Exploring Volatile Organic Compounds in Breath for High-Accuracy Prediction of Lung Cancer." Cancers 13, no. 6 (March 21, 2021): 1431. http://dx.doi.org/10.3390/cancers13061431.

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(1) Background: Lung cancer is silent in its early stages and fatal in its advanced stages. The current examinations for lung cancer are usually based on imaging. Conventional chest X-rays lack accuracy, and chest computed tomography (CT) is associated with radiation exposure and cost, limiting screening effectiveness. Breathomics, a noninvasive strategy, has recently been studied extensively. Volatile organic compounds (VOCs) derived from human breath can reflect metabolic changes caused by diseases and possibly serve as biomarkers of lung cancer. (2) Methods: The selected ion flow tube mass spectrometry (SIFT-MS) technique was used to quantitatively analyze 116 VOCs in breath samples from 148 patients with histologically confirmed lung cancers and 168 healthy volunteers. We used eXtreme Gradient Boosting (XGBoost), a machine learning method, to build a model for predicting lung cancer occurrence based on quantitative VOC measurements. (3) Results: The proposed prediction model achieved better performance than other previous approaches, with an accuracy, sensitivity, specificity, and area under the curve (AUC) of 0.89, 0.82, 0.94, and 0.95, respectively. When we further adjusted the confounding effect of environmental VOCs on the relationship between participants’ exhaled VOCs and lung cancer occurrence, our model was improved to reach 0.92 accuracy, 0.96 sensitivity, 0.88 specificity, and 0.98 AUC. (4) Conclusion: A quantitative VOCs databank integrated with the application of an XGBoost classifier provides a persuasive platform for lung cancer prediction.

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Azim, Adnan, Faisal I. Rezwan, Clair Barber, Matthew Harvey, Ramesh J. Kurukulaaratchy, John W. Holloway, and Peter H. Howarth. "Measurement of Exhaled Volatile Organic Compounds as a Biomarker for Personalised Medicine: Assessment of Short-Term Repeatability in Severe Asthma." Journal of Personalized Medicine 12, no. 10 (October 2, 2022): 1635. http://dx.doi.org/10.3390/jpm12101635.

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The measurement of exhaled volatile organic compounds (VOCs) in exhaled breath (breathomics) represents an exciting biomarker matrix for airways disease, with early research indicating a sensitivity to airway inflammation. One of the key aspects to analytical validity for any clinical biomarker is an understanding of the short-term repeatability of measures. We collected exhaled breath samples on 5 consecutive days in 14 subjects with severe asthma who had undergone extensive clinical characterisation. Principal component analysis on VOC abundance across all breath samples revealed no variance due to the day of sampling. Samples from the same patients clustered together and there was some separation according to T2 inflammatory markers. The intra-subject and between-subject variability of each VOC was calculated across the 70 samples and identified 30.35% of VOCs to be erratic: variable between subjects but also variable in the same subject. Exclusion of these erratic VOCs from machine learning approaches revealed no apparent loss of structure to the underlying data or loss of relationship with salient clinical characteristics. Moreover, cluster evaluation by the silhouette coefficient indicates more distinct clustering. We are able to describe the short-term repeatability of breath samples in a severe asthma population and corroborate its sensitivity to airway inflammation. We also describe a novel variance-based feature selection tool that, when applied to larger clinical studies, could improve machine learning model predictions.

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Freddi, Sonia, Michele Vergari, Stefania Pagliara, and Luigi Sangaletti. "A Chemiresistor Sensor Array Based on Graphene Nanostructures: From the Detection of Ammonia and Possible Interfering VOCs to Chemometric Analysis." Sensors 23, no. 2 (January 12, 2023): 882. http://dx.doi.org/10.3390/s23020882.

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Sensor arrays are currently attracting the interest of researchers due to their potential of overcoming the limitations of single sensors regarding selectivity, required by specific applications. Among the materials used to develop sensor arrays, graphene has not been so far extensively exploited, despite its remarkable sensing capability. Here we present the development of a graphene-based sensor array prepared by dropcasting nanostructure and nanocomposite graphene solution on interdigitated substrates, with the aim to investigate the capability of the array to discriminate several gases related to specific applications, including environmental monitoring, food quality tracking, and breathomics. This goal is achieved in two steps: at first the sensing properties of the array have been assessed through ammonia exposures, drawing the calibration curves, estimating the limit of detection, which has been found in the ppb range for all sensors, and investigating stability and sensitivity; then, after performing exposures to acetone, ethanol, 2-propanol, sodium hypochlorite, and water vapour, chemometric tools have been exploited to investigate the discrimination capability of the array, including principal component analysis (PCA), linear discriminant analysis (LDA), and Mahalanobis distance. PCA shows that the array was able to discriminate all the tested gases with an explained variance around 95%, while with an LDA approach the array can be trained to accurately recognize unknown gas contribution, with an accuracy higher than 94%.

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Holden, Karl A., Wadah Ibrahim, Dahlia Salman, Rebecca Cordell, Teresa McNally, Bharti Patel, Rachael Phillips, et al. "Use of the ReCIVA device in breath sampling of patients with acute breathlessness: a feasibility study." ERJ Open Research 6, no. 4 (October 2020): 00119–2020. http://dx.doi.org/10.1183/23120541.00119-2020.

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IntroductionInvestigating acute multifactorial undifferentiated breathlessness and understanding the driving inflammatory processes can be technically challenging in both adults and children. Being able to validate noninvasive methods such as breath analysis would be a huge clinical advance. The ReCIVA® device allows breath samples to be collected directly onto sorbent tubes at the bedside for analysis of exhaled volatile organic compounds (eVOCs). We aimed to assess the feasibility of using this device in acutely breathless patients.MethodsAdults hospitalised with acute breathlessness and children aged 5–16 years with acute asthma or chronic stable asthma, as well as healthy adult and child volunteers, were recruited. Breath samples were collected onto sorbent tubes using the ReCIVA® device and sent for analysis by means of two-dimensional gas chromatography-mass spectrometry (GCxGC-MS). The NASA Task Load Index (NASA-TLX) was used to assess the perceived task workload of undertaking sampling from the patient's perspective.ResultsData were available for 65 adults and 61 children recruited. In total, 98.4% of adults and 75.4% of children were able to provide the full target breath sample using the ReCIVA® device. NASA-TLX measurements were available in the adult population with mean values of 3.37 for effort, 2.34 for frustration, 3.8 for mental demand, 2.8 for performance, 3.9 for physical demand and 2.8 for temporal demand.DiscussionThis feasibility study demonstrates it is possible and acceptable to collect breath samples from both adults and children at the bedside for breathomics analysis using the ReCIVA® device.

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Fens, Niki, Annelot G. J. van Rossum, Pieter Zanen, Bram van Ginneken, Rob J. van Klaveren, Aeilko H. Zwinderman, and Peter J. Sterk. "Subphenotypes of Mild-to-Moderate COPD by Factor and Cluster Analysis of Pulmonary Function, CT Imaging and Breathomics in a Population-Based Survey." COPD: Journal of Chronic Obstructive Pulmonary Disease 10, no. 3 (March 28, 2013): 277–85. http://dx.doi.org/10.3109/15412555.2012.744388.

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Moninuola, Funmilayo S., Emmanuel Adetiba, Oluwadamilola I. Oshin, Anthony A. Atayero, and Ademola Adeyeye. "A Mini Review of Trends towards Automated and Non-Invasive Techniques for Early Detection of Lung Cancer: From Radiomics through Proteogenomics to Breathomics." Journal of Physics: Conference Series 1378 (December 2019): 032010. http://dx.doi.org/10.1088/1742-6596/1378/3/032010.

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Brinkman, Paul, Waqar M. Ahmed, Cristina Gómez, Hugo H. Knobel, Hans Weda, Teunis J. Vink, Tamara M. Nijsen, et al. "Exhaled volatile organic compounds as markers for medication use in asthma." European Respiratory Journal 55, no. 2 (September 12, 2019): 1900544. http://dx.doi.org/10.1183/13993003.00544-2019.

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IntroductionAsthma is a heterogeneous condition, characterised by chronic inflammation of the airways, typically managed with inhaled bronchodilators and corticosteroids. In the case of uncontrolled asthma, oral corticosteroids (OCSs) are often prescribed. Good adherence and inhalation technique are associated with improved outcomes; however, it is difficult to monitor appropriate drug intake and effectiveness in individual patients. Exhaled breath contains thousands of volatile organic compounds (VOCs) that reflect changes in the body's chemistry and may be useful for monitoring drug pharmacokinetics/pharmacodynamics. We aimed to investigate the association of exhaled VOCs in severe asthma patients from the U-BIOPRED cohort (by gas chromatography coupled with time-of-flight mass spectrometry) with urinary levels of salbutamol and OCSs (by liquid chromatography coupled with high-resolution mass spectrometry).MethodsSamples were collected at baseline and after 12–18 months of follow-up. Statistical analysis was based on univariate and multivariate modelling, followed by area under the receiver operating characteristic curve (AUC) calculation. Results were verified through longitudinal replication and independent validation.ResultsData were available for 78 patients (baseline n=48, replication n=30 and validation n=30). Baseline AUC values were 82.1% (95% CI 70.4–93.9%) for salbutamol and 78.8% (95% CI 65.8–91.8%) for OCS. These outcomes could be adequately replicated and validated. Additional regression analysis between qualified exhaled VOCs and urinary concentrations of salbutamol and prednisone showed statistically significant correlations (p<0.01).ConclusionWe have linked exhaled VOCs to urinary detection of salbutamol and OCSs. This merits further development of breathomics into a point-of-care tool for therapeutic drug monitoring.

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Schmid, S., S. Schouwenburg, E. Stewart, A. F. Fares, P. Bradbury, F. Shepherd, N. Leighl, et al. "1217P Breathomics eNose technology as a non-invasive, inexpensive, point-of-care predictive test to detect early stage lung cancer in never or former light smokers." Annals of Oncology 31 (September 2020): S795. http://dx.doi.org/10.1016/j.annonc.2020.08.1419.

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Póvoa, Pedro, and Luis Coelho. "Which Biomarkers Can Be Used as Diagnostic Tools for Infection in Suspected Sepsis?" Seminars in Respiratory and Critical Care Medicine 42, no. 05 (September 20, 2021): 662–71. http://dx.doi.org/10.1055/s-0041-1735148.

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AbstractThe diagnosis of infection in patients with suspected sepsis is frequently difficult to achieve with a reasonable degree of certainty. Currently, the diagnosis of infection still relies on a combination of systemic manifestations, manifestations of organ dysfunction, and microbiological documentation. In addition, the microbiologic confirmation of infection is obtained only after 2 to 3 days of empiric antibiotic therapy. These criteria are far from perfect being at least in part responsible for the overuse and misuse of antibiotics, in the community and in hospital, and probably the main drive for antibiotic resistance. Biomarkers have been studied and used in several clinical settings as surrogate markers of infection to improve their diagnostic accuracy as well as in the assessment of response to antibiotics and in antibiotic stewardship programs. The aim of this review is to provide a clear overview of the current evidence of usefulness of biomarkers in several clinical scenarios, namely, to diagnose infection to prescribe antibiotics, to exclude infection to withhold antibiotics, and to identify the causative pathogen to target antimicrobial treatment. In recent years, new evidence with “old” biomarkers, like C-reactive protein and procalcitonin, as well as new biomarkers and molecular tests, as breathomics or bacterial DNA identification by polymerase chain reaction, increased markedly in different areas adding useful information for clinical decision making at the bedside when adequately used. The recent evidence shows that the information given by biomarkers can support the suspicion of infection and pathogen identification but also, and not less important, can exclude its diagnosis. Although the ideal biomarker has not yet been found, there are various promising biomarkers that represent true evolutions in the diagnosis of infection in patients with suspected sepsis.

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