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Lombardi M, Segreti A, Miglionico M, Pennazza G, Tocca L, Amendola L, Vergallo R, Di Sciascio G, Porto I, Grigioni F, Antonelli Incalzi R. Breath Analysis via Gas Chromatography-Mass Spectrometry (GC-MS) in Chronic Coronary Syndrome (CCS): A Proof-of-Concept Study. J Clin Med 2024; 13:5857. [PMID: 39407917 PMCID: PMC11477340 DOI: 10.3390/jcm13195857] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2024] [Revised: 09/22/2024] [Accepted: 09/26/2024] [Indexed: 10/20/2024] Open
Abstract
Background: This proof-of-concept study aimed to assess the diagnostic potential of gas chromatography-mass spectrometry (GC-MS) in profiling volatile organic compounds (VOCs) from exhaled breath as a diagnostic tool for the chronic coronary syndrome (CCS). Methods: Exhaled air was collected from patients undergoing invasive coronary angiography (ICA), with all samples obtained prior to ICA. Post hoc, patients were divided into groups based on coronary lesion severity and indications for revascularization. VOCs in the breath samples were analyzed using GC-MS. Results: This study included 23 patients, of whom 11 did not require myocardial revascularization and 12 did. GC-MS analysis successfully classified 10 of the 11 patients without the need for revascularization (sensitivity of 91%), and 7 of the 12 patients required revascularization (specificity 58%). In subgroup analysis, GC-MS demonstrated 100% sensitivity in identifying patients with significant coronary lesions requiring intervention when the cohort was divided into three groups. A total of 36 VOCs, including acetone, ethanol, and phenol, were identified as distinguishing markers between patient groups. Conclusions: Patients with CCS exhibited a unique fingerprint of exhaled breath, which was detectable with GC-MS. These findings suggest that GC-MS analysis could be a reliable and non-invasive diagnostic tool for CCS. Further studies with larger cohorts are necessary to validate these results and explore the potential integration of VOC analysis into clinical practice.
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Affiliation(s)
- Marco Lombardi
- Department of Internal Medicine, University of Genova, 16132 Genova, Italy; (M.L.); (R.V.); (I.P.)
| | - Andrea Segreti
- Research Unit of Cardiovascular Science, Department of Medicine and Surgery, Università Campus Bio-Medico di Roma, 00128 Rome, Italy; (M.M.); (G.D.S.); (F.G.)
- Cardiology Unit, Fondazione Policlinico Universitario Campus Bio-Medico, 00128 Rome, Italy
- Department of Movement, Human and Health Sciences, University of Rome “Foro Italico”, 00135 Rome, Italy
| | - Marco Miglionico
- Research Unit of Cardiovascular Science, Department of Medicine and Surgery, Università Campus Bio-Medico di Roma, 00128 Rome, Italy; (M.M.); (G.D.S.); (F.G.)
- Cardiology Unit, Fondazione Policlinico Universitario Campus Bio-Medico, 00128 Rome, Italy
| | - Giorgio Pennazza
- Unit of Electronics for Sensor Systems, Department of Engineering, Università Campus Bio-Medico di Roma, 00128 Rome, Italy;
| | - Lorenzo Tocca
- Dipartimento Prevenzione e Laboratorio Integrato, A.R.P.A. Lazio, 00173 Rome , Italy; (L.T.); (L.A.)
| | - Luca Amendola
- Dipartimento Prevenzione e Laboratorio Integrato, A.R.P.A. Lazio, 00173 Rome , Italy; (L.T.); (L.A.)
| | - Rocco Vergallo
- Department of Internal Medicine, University of Genova, 16132 Genova, Italy; (M.L.); (R.V.); (I.P.)
- Cardiothoracic and Vascular Department (DICATOV), IRCCS Ospedale Policlinico San Martino, Viale Benedetto XV, 6, 16132 Genova, Italy
| | - Germano Di Sciascio
- Research Unit of Cardiovascular Science, Department of Medicine and Surgery, Università Campus Bio-Medico di Roma, 00128 Rome, Italy; (M.M.); (G.D.S.); (F.G.)
- Cardiology Unit, Fondazione Policlinico Universitario Campus Bio-Medico, 00128 Rome, Italy
| | - Italo Porto
- Department of Internal Medicine, University of Genova, 16132 Genova, Italy; (M.L.); (R.V.); (I.P.)
- Cardiothoracic and Vascular Department (DICATOV), IRCCS Ospedale Policlinico San Martino, Viale Benedetto XV, 6, 16132 Genova, Italy
| | - Francesco Grigioni
- Research Unit of Cardiovascular Science, Department of Medicine and Surgery, Università Campus Bio-Medico di Roma, 00128 Rome, Italy; (M.M.); (G.D.S.); (F.G.)
- Cardiology Unit, Fondazione Policlinico Universitario Campus Bio-Medico, 00128 Rome, Italy
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Prokopiuk A, Wojtas J. Accelerating the Diagnosis of Pandemic Infection Based on Rapid Sampling Algorithm for Fast-Response Breath Gas Analyzers. SENSORS (BASEL, SWITZERLAND) 2024; 24:6164. [PMID: 39409204 PMCID: PMC11478416 DOI: 10.3390/s24196164] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/27/2024] [Revised: 09/21/2024] [Accepted: 09/23/2024] [Indexed: 10/20/2024]
Abstract
This paper presents a novel technique for extracting the alveolar part of human breath. Gas exchange occurs between blood and inhaled air in the alveoli, which is helpful in medical diagnostics based on breath analysis. Consequently, the alveolar portion of the exhaled air contains specific concentrations of endogenous EVOC (exogenous volatile organic compound), which, among other factors, depend on the person's health condition. As this part of the breath enables the screening for diseases, accurate sample collection for testing is crucial. Inaccurate sampling can significantly alter the composition of the specimen, alter the concentration of EVOC (biomarkers) and adversely affect the diagnosis. Furthermore, the volume of alveolar air is minimal (usually <350 mL), especially in the case of people affected by respiratory system problems. For these reasons, precise sampling is a key factor in the effectiveness of medical diagnostic systems. A new technique ensuring high accuracy and repeatability is presented in the article. It is based on analyzing the changes in carbon dioxide concentration in human breath using a fast and compensated non-dispersive infrared (NDIR) sensor and the simple moving adjacent average (SMAA) algorithm. Research has shown that this method accurately identifies exhalation phases with an uncertainty as low as 20 ms. This provides around 350 ms of breath duration for carrying out additional stages of the diagnostic process using various types of analyzers.
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Affiliation(s)
| | - Jacek Wojtas
- Institute of Optoelectronics, Military University of Technology, 2 Kaliskiego Str., 00-908 Warsaw, Poland
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Chou H, Godbeer L, Allsworth M, Boyle B, Ball ML. Progress and challenges of developing volatile metabolites from exhaled breath as a biomarker platform. Metabolomics 2024; 20:72. [PMID: 38977623 PMCID: PMC11230972 DOI: 10.1007/s11306-024-02142-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/26/2024] [Accepted: 06/13/2024] [Indexed: 07/10/2024]
Abstract
BACKGROUND The multitude of metabolites generated by physiological processes in the body can serve as valuable biomarkers for many clinical purposes. They can provide a window into relevant metabolic pathways for health and disease, as well as be candidate therapeutic targets. A subset of these metabolites generated in the human body are volatile, known as volatile organic compounds (VOCs), which can be detected in exhaled breath. These can diffuse from their point of origin throughout the body into the bloodstream and exchange into the air in the lungs. For this reason, breath VOC analysis has become a focus of biomedical research hoping to translate new useful biomarkers by taking advantage of the non-invasive nature of breath sampling, as well as the rapid rate of collection over short periods of time that can occur. Despite the promise of breath analysis as an additional platform for metabolomic analysis, no VOC breath biomarkers have successfully been implemented into a clinical setting as of the time of this review. AIM OF REVIEW This review aims to summarize the progress made to address the major methodological challenges, including standardization, that have historically limited the translation of breath VOC biomarkers into the clinic. We highlight what steps can be taken to improve these issues within new and ongoing breath research to promote the successful development of the VOCs in breath as a robust source of candidate biomarkers. We also highlight key recent papers across select fields, critically reviewing the progress made in the past few years to advance breath research. KEY SCIENTIFIC CONCEPTS OF REVIEW VOCs are a set of metabolites that can be sampled in exhaled breath to act as advantageous biomarkers in a variety of clinical contexts.
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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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Xie Z, Morris JD, Pan J, Cooke EA, Sutaria SR, Balcom D, Marimuthu S, Parrish LW, Aliesky H, Huang JJ, Rai SN, Arnold FW, Huang J, Nantz MH, Fu XA. Detection of COVID-19 by quantitative analysis of carbonyl compounds in exhaled breath. Sci Rep 2024; 14:14568. [PMID: 38914586 PMCID: PMC11196736 DOI: 10.1038/s41598-024-61735-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2023] [Accepted: 05/09/2024] [Indexed: 06/26/2024] Open
Abstract
COVID-19 has caused a worldwide pandemic, creating an urgent need for early detection methods. Breath analysis has shown great potential as a non-invasive and rapid means for COVID-19 detection. The objective of this study is to detect patients infected with SARS-CoV-2 and even the possibility to screen between different SARS-CoV-2 variants by analysis of carbonyl compounds in breath. Carbonyl compounds in exhaled breath are metabolites related to inflammation and oxidative stress induced by diseases. This study included a cohort of COVID-19 positive and negative subjects confirmed by reverse transcription polymerase chain reaction between March and December 2021. Carbonyl compounds in exhaled breath were captured using a microfabricated silicon microreactor and analyzed by ultra-high-performance liquid chromatography-mass spectrometry (UHPLC-MS). A total of 321 subjects were enrolled in this study. Of these, 141 (85 males, 60.3%) (mean ± SD age: 52 ± 15 years) were COVID-19 (55 during the alpha wave and 86 during the delta wave) positive and 180 (90 males, 50%) (mean ± SD age: 45 ± 15 years) were negative. Panels of a total of 34 ketones and aldehydes in all breath samples were identified for detection of COVID-19 positive patients. Logistic regression models indicated high accuracy/sensitivity/specificity for alpha wave (98.4%/96.4%/100%), for delta wave (88.3%/93.0%/84.6%) and for all COVID-19 positive patients (94.7%/90.1%/98.3%). The results indicate that COVID-19 positive patients can be detected by analysis of carbonyl compounds in exhaled breath. The technology for analysis of carbonyl compounds in exhaled breath has great potential for rapid screening and detection of COVID-19 and for other infectious respiratory diseases in future pandemics.
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Affiliation(s)
- Zhenzhen Xie
- Department of Chemical Engineering, University of Louisville, Louisville, KY, USA
| | - James D Morris
- Department of Chemical Engineering, University of Louisville, Louisville, KY, USA
| | - Jianmin Pan
- Division of Biostatistics and Bioinformatics, Department of Environmental and Public Health Sciences, University of Cincinnati College of Medicine, Cincinnati, OH, USA
- The Cancer Data Science Center, University of Cincinnati College of Medicine, Cincinnati, OH, USA
- Biostatistics and Informatics Shared Resource, University of Cincinnati Cancer Center, Cincinnati, OH, USA
| | - Elizabeth A Cooke
- Department of Anesthesiology and Perioperative Medicine, University of Louisville, Louisville, KY, USA
| | - Saurin R Sutaria
- Department of Chemistry, University of Louisville, Louisville, KY, USA
| | - Dawn Balcom
- Division of Infectious Diseases, Department of Medicine, University of Louisville, Louisville, KY, USA
| | - Subathra Marimuthu
- Division of Infectious Diseases, Department of Medicine, University of Louisville, Louisville, KY, USA
| | - Leslie W Parrish
- Division of Infectious Diseases, Department of Medicine, University of Louisville, Louisville, KY, USA
| | - Holly Aliesky
- Division of Infectious Diseases, Department of Medicine, University of Louisville, Louisville, KY, USA
| | | | - Shesh N Rai
- Division of Biostatistics and Bioinformatics, Department of Environmental and Public Health Sciences, University of Cincinnati College of Medicine, Cincinnati, OH, USA
- The Cancer Data Science Center, University of Cincinnati College of Medicine, Cincinnati, OH, USA
- Biostatistics and Informatics Shared Resource, University of Cincinnati Cancer Center, Cincinnati, OH, USA
| | - Forest W Arnold
- Division of Infectious Diseases, Department of Medicine, University of Louisville, Louisville, KY, USA
| | - Jiapeng Huang
- Department of Anesthesiology and Perioperative Medicine, University of Louisville, Louisville, KY, USA.
| | - Michael H Nantz
- Department of Chemistry, University of Louisville, Louisville, KY, USA.
| | - Xiao-An Fu
- Department of Chemical Engineering, University of Louisville, Louisville, KY, USA.
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Gupta-Wright A, Denkinger CM. Advances in TB diagnostics: A critical element for the elimination toolkit. Indian J Med Res 2024; 159:391-394. [PMID: 39382418 PMCID: PMC11463239 DOI: 10.25259/ijmr_261_2024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2024] [Indexed: 10/10/2024] Open
Affiliation(s)
- Ankur Gupta-Wright
- Division of Infectious Diseases and Tropical Medicine, Heidelberg University, Heidelberg, Germany
- Department of Infectious Diseases, Imperial College London, London, United Kingdom
- Department of Infectious Diseases, North Bristol NHS Trust, Bristol, United Kingdom
| | - Claudia Maria Denkinger
- Division of Infectious Diseases and Tropical Medicine, Heidelberg University, Heidelberg, Germany
- German Centre for Infection Research (DZIF), Partner Site Heidelberg, Heidelberg, Germany
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Charles M, Ruszkiewicz D, Eckbo E, Bryce E, Zurberg T, Meister A, Aksu L, Navas L, Myers R. The science behind the nose: correlating volatile organic compound characterisation with canine biodetection of COVID-19. ERJ Open Res 2024; 10:00007-2024. [PMID: 38770004 PMCID: PMC11103684 DOI: 10.1183/23120541.00007-2024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2024] [Accepted: 02/20/2024] [Indexed: 05/22/2024] Open
Abstract
Background The SARS-CoV-2 pandemic stimulated the advancement and research in the field of canine scent detection of COVID-19 and volatile organic compound (VOC) breath sampling. It remains unclear which VOCs are associated with positive canine alerts. This study aimed to confirm that the training aids used for COVID-19 canine scent detection were indeed releasing discriminant COVID-19 VOCs detectable and identifiable by gas chromatography (GC-MS). Methods Inexperienced dogs (two Labradors and one English Springer Spaniel) were trained over 19 weeks to discriminate between COVID-19 infected and uninfected individuals and then independently validated. Getxent tubes, impregnated with the odours from clinical gargle samples, used during the canines' maintenance training process were also analysed using GC-MS. Results Three dogs were successfully trained to detect COVID-19. A principal components analysis model was created and confirmed the ability to discriminate between VOCs from positive and negative COVID-19 Getxent tubes with a sensitivity of 78% and a specificity of 77%. Two VOCs were found to be very predictive of positive COVID-19 cases. When comparing the dogs with GC-MS, F1 and Matthew's correlation coefficient, correlation scores of 0.69 and 0.37 were observed, respectively, demonstrating good concordance between the two methods. Interpretation This study provides analytical confirmation that canine training aids can be safely and reliably produced with good discrimination between positive samples and negative controls. It is also a further step towards better understanding of canine odour discrimination of COVID-19 as the scent of interest and defining what VOC elements the canines interpret as "essential".
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Affiliation(s)
- Marthe Charles
- Division of Medical Microbiology, Vancouver Coastal Health, Vancouver, BC, Canada
- University of British Columbia, Faculty of Medicine, Vancouver, BC, Canada
| | - Dorota Ruszkiewicz
- University of British Columbia, Faculty of Medicine, Vancouver, BC, Canada
- British Columbia Cancer Research Institute, Vancouver, BC, Canada
| | - Eric Eckbo
- Division of Medical Microbiology, Vancouver Coastal Health, Vancouver, BC, Canada
- University of British Columbia, Faculty of Medicine, Vancouver, BC, Canada
| | - Elizabeth Bryce
- Division of Medical Microbiology, Vancouver Coastal Health, Vancouver, BC, Canada
- Quality and Patient Safety, Vancouver Coastal Health, Vancouver, BC, Canada
| | - Teresa Zurberg
- Quality and Patient Safety, Vancouver Coastal Health, Vancouver, BC, Canada
| | - Austin Meister
- University of British Columbia, Faculty of Medicine, Vancouver, BC, Canada
| | - Lâle Aksu
- Quality and Patient Safety, Vancouver Coastal Health, Vancouver, BC, Canada
| | - Leonardo Navas
- Quality and Patient Safety, Vancouver Coastal Health, Vancouver, BC, Canada
| | - Renelle Myers
- University of British Columbia, Faculty of Medicine, Vancouver, BC, Canada
- British Columbia Cancer Research Institute, Vancouver, BC, Canada
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Bajo-Fernández M, Souza-Silva ÉA, Barbas C, Rey-Stolle MF, García A. GC-MS-based metabolomics of volatile organic compounds in exhaled breath: applications in health and disease. A review. Front Mol Biosci 2024; 10:1295955. [PMID: 38298553 PMCID: PMC10828970 DOI: 10.3389/fmolb.2023.1295955] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2023] [Accepted: 12/05/2023] [Indexed: 02/02/2024] Open
Abstract
Exhaled breath analysis, with particular emphasis on volatile organic compounds, represents a growing area of clinical research due to its obvious advantages over other diagnostic tests. Numerous pathologies have been extensively investigated for the identification of specific biomarkers in exhalates through metabolomics. However, the transference of breath tests to clinics remains limited, mainly due to deficiency in methodological standardization. Critical steps include the selection of breath sample types, collection devices, and enrichment techniques. GC-MS is the reference analytical technique for the analysis of volatile organic compounds in exhalates, especially during the biomarker discovery phase in metabolomics. This review comprehensively examines and compares metabolomic studies focusing on cancer, lung diseases, and infectious diseases. In addition to delving into the experimental designs reported, it also provides a critical discussion of the methodological aspects, ranging from the experimental design and sample collection to the identification of potential pathology-specific biomarkers.
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Affiliation(s)
- María Bajo-Fernández
- Centro de Metabolómica y Bioanálisis (CEMBIO), Facultad de Farmacia, Universidad San Pablo-CEU, CEU Universities, Urbanización Montepríncipe, Boadilla del Monte, Spain
| | - Érica A. Souza-Silva
- Centro de Metabolómica y Bioanálisis (CEMBIO), Facultad de Farmacia, Universidad San Pablo-CEU, CEU Universities, Urbanización Montepríncipe, Boadilla del Monte, Spain
- Departmento de Química, Universidade Federal de São Paulo (UNIFESP), Diadema, Brazil
| | - Coral Barbas
- Centro de Metabolómica y Bioanálisis (CEMBIO), Facultad de Farmacia, Universidad San Pablo-CEU, CEU Universities, Urbanización Montepríncipe, Boadilla del Monte, Spain
| | - Ma Fernanda Rey-Stolle
- Centro de Metabolómica y Bioanálisis (CEMBIO), Facultad de Farmacia, Universidad San Pablo-CEU, CEU Universities, Urbanización Montepríncipe, Boadilla del Monte, Spain
| | - Antonia García
- Centro de Metabolómica y Bioanálisis (CEMBIO), Facultad de Farmacia, Universidad San Pablo-CEU, CEU Universities, Urbanización Montepríncipe, Boadilla del Monte, Spain
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