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Wei S, Li Z, Murugappan K, Li Z, Lysevych M, Vora K, Tan HH, Jagadish C, Karawdeniya BI, Nolan CJ, Tricoli A, Fu L. Nanowire Array Breath Acetone Sensor for Diabetes Monitoring. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2024; 11:e2309481. [PMID: 38477429 PMCID: PMC11109654 DOI: 10.1002/advs.202309481] [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: 12/05/2023] [Revised: 02/18/2024] [Indexed: 03/14/2024]
Abstract
Diabetic ketoacidosis (DKA) is a life-threatening acute complication of diabetes characterized by the accumulation of ketone bodies in the blood. Breath acetone, a ketone, directly correlates with blood ketones. Therefore, monitoring breath acetone can significantly enhance the safety and efficacy of diabetes care. In this work, the design and fabrication of an InP/Pt/chitosan nanowire array-based chemiresistive acetone sensor is reported. By incorporation of chitosan as a surface-functional layer and a Pt Schottky contact for efficient charge transfer processes and photovoltaic effect, self-powered, highly selective acetone sensing is achieved. The sensor has exhibited an ultra-wide acetone detection range from sub-ppb to >100 000 ppm level at room temperature, covering those in the exhaled breath from healthy individuals (300-800 ppb) to people at high risk of DKA (>75 ppm). The nanowire sensor has also been successfully integrated into a handheld breath testing prototype, the Ketowhistle, which can successfully detect different ranges of acetone concentrations in simulated breath samples. The Ketowhistle demonstrates the immediate potential for non-invasive ketone monitoring for people living with diabetes, in particular for DKA prevention.
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Affiliation(s)
- Shiyu Wei
- Australian Research Council Centre of Excellence for Transformative Meta‐Optical SystemsDepartment of Electronic Materials EngineeringResearch School of PhysicsThe Australian National UniversityCanberraACT2600Australia
| | - Zhe Li
- Australian Research Council Centre of Excellence for Transformative Meta‐Optical SystemsDepartment of Electronic Materials EngineeringResearch School of PhysicsThe Australian National UniversityCanberraACT2600Australia
| | - Krishnan Murugappan
- Commonwealth Scientific and Industrial Research Organisation (CSIRO)Mineral ResourcesPrivate Bag 10Clayton SouthVIC3169Australia
- Nanotechnology Research LaboratoryResearch School of ChemistryCollege of ScienceThe Australian National UniversityCanberraACT2600Australia
| | - Ziyuan Li
- Australian Research Council Centre of Excellence for Transformative Meta‐Optical SystemsDepartment of Electronic Materials EngineeringResearch School of PhysicsThe Australian National UniversityCanberraACT2600Australia
| | - Mykhaylo Lysevych
- Australian National Fabrication FacilityThe Australian National UniversityCanberraACT2600Australia
| | - Kaushal Vora
- Australian National Fabrication FacilityThe Australian National UniversityCanberraACT2600Australia
| | - Hark Hoe Tan
- Australian Research Council Centre of Excellence for Transformative Meta‐Optical SystemsDepartment of Electronic Materials EngineeringResearch School of PhysicsThe Australian National UniversityCanberraACT2600Australia
| | - Chennupati Jagadish
- Australian Research Council Centre of Excellence for Transformative Meta‐Optical SystemsDepartment of Electronic Materials EngineeringResearch School of PhysicsThe Australian National UniversityCanberraACT2600Australia
| | - Buddini I Karawdeniya
- Australian Research Council Centre of Excellence for Transformative Meta‐Optical SystemsDepartment of Electronic Materials EngineeringResearch School of PhysicsThe Australian National UniversityCanberraACT2600Australia
| | - Christopher J Nolan
- School of Medicine and PsychologyCollege of Health and MedicineThe Australian National UniversityCanberraACT2600Australia
- Department of Diabetes and EndocrinologyThe Canberra HospitalGarranACT2605Australia
| | - Antonio Tricoli
- Nanotechnology Research LaboratoryResearch School of ChemistryCollege of ScienceThe Australian National UniversityCanberraACT2600Australia
- Nanotechnology Research LaboratoryFaculty of EngineeringThe University of SydneyCamperdown2006Australia
| | - Lan Fu
- Australian Research Council Centre of Excellence for Transformative Meta‐Optical SystemsDepartment of Electronic Materials EngineeringResearch School of PhysicsThe Australian National UniversityCanberraACT2600Australia
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Das P, Marvi PK, Ganguly S, Tang XS, Wang B, Srinivasan S, Rajabzadeh AR, Rosenkranz A. MXene-Based Elastomer Mimetic Stretchable Sensors: Design, Properties, and Applications. NANO-MICRO LETTERS 2024; 16:135. [PMID: 38411801 PMCID: PMC10899156 DOI: 10.1007/s40820-024-01349-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/03/2023] [Accepted: 01/09/2024] [Indexed: 02/28/2024]
Abstract
Flexible sensors based on MXene-polymer composites are highly prospective for next-generation wearable electronics used in human-machine interfaces. One of the motivating factors behind the progress of flexible sensors is the steady arrival of new conductive materials. MXenes, a new family of 2D nanomaterials, have been drawing attention since the last decade due to their high electronic conductivity, processability, mechanical robustness and chemical tunability. In this review, we encompass the fabrication of MXene-based polymeric nanocomposites, their structure-property relationship, and applications in the flexible sensor domain. Moreover, our discussion is not only limited to sensor design, their mechanism, and various modes of sensing platform, but also their future perspective and market throughout the world. With our article, we intend to fortify the bond between flexible matrices and MXenes thus promoting the swift advancement of flexible MXene-sensors for wearable technologies.
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Affiliation(s)
- Poushali Das
- School of Biomedical Engineering, McMaster University, 1280 Main Street West, Hamilton, ON, L8S 4L8, Canada
| | - Parham Khoshbakht Marvi
- School of Biomedical Engineering, McMaster University, 1280 Main Street West, Hamilton, ON, L8S 4L8, Canada
| | - Sayan Ganguly
- Department of Chemistry and Waterloo Institute for Nanotechnology (WIN), University of Waterloo, 200 University Ave West, Waterloo, ON, Canada
- Centre for Eye and Vision Research (CEVR), 17W Hong Kong Science Park, Shatin, Hong Kong, People's Republic of China
| | - Xiaowu Shirley Tang
- Department of Chemistry and Waterloo Institute for Nanotechnology (WIN), University of Waterloo, 200 University Ave West, Waterloo, ON, Canada
- Centre for Eye and Vision Research (CEVR), 17W Hong Kong Science Park, Shatin, Hong Kong, People's Republic of China
| | - Bo Wang
- Chair of Functional Materials, Department of Materials Science and Engineering, Saarland University, Saarbrücken, Germany
| | - Seshasai Srinivasan
- School of Biomedical Engineering, McMaster University, 1280 Main Street West, Hamilton, ON, L8S 4L8, Canada.
- W Booth School of Engineering Practice and Technology, McMaster University, 1280 Main Street West, Hamilton, ON, L8S 4L7, Canada.
| | - Amin Reza Rajabzadeh
- School of Biomedical Engineering, McMaster University, 1280 Main Street West, Hamilton, ON, L8S 4L8, Canada.
- W Booth School of Engineering Practice and Technology, McMaster University, 1280 Main Street West, Hamilton, ON, L8S 4L7, Canada.
| | - Andreas Rosenkranz
- Department for Chemical Engineering, Biotechnology and Materials, University of Chile, Santiago, Chile.
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Gudiño-Ochoa A, García-Rodríguez JA, Ochoa-Ornelas R, Cuevas-Chávez JI, Sánchez-Arias DA. Noninvasive Diabetes Detection through Human Breath Using TinyML-Powered E-Nose. SENSORS (BASEL, SWITZERLAND) 2024; 24:1294. [PMID: 38400451 PMCID: PMC10891698 DOI: 10.3390/s24041294] [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: 01/31/2024] [Revised: 02/14/2024] [Accepted: 02/15/2024] [Indexed: 02/25/2024]
Abstract
Volatile organic compounds (VOCs) in exhaled human breath serve as pivotal biomarkers for disease identification and medical diagnostics. In the context of diabetes mellitus, the noninvasive detection of acetone, a primary biomarker using electronic noses (e-noses), has gained significant attention. However, employing e-noses requires pre-trained algorithms for precise diabetes detection, often requiring a computer with a programming environment to classify newly acquired data. This study focuses on the development of an embedded system integrating Tiny Machine Learning (TinyML) and an e-nose equipped with Metal Oxide Semiconductor (MOS) sensors for real-time diabetes detection. The study encompassed 44 individuals, comprising 22 healthy individuals and 22 diagnosed with various types of diabetes mellitus. Test results highlight the XGBoost Machine Learning algorithm's achievement of 95% detection accuracy. Additionally, the integration of deep learning algorithms, particularly deep neural networks (DNNs) and one-dimensional convolutional neural network (1D-CNN), yielded a detection efficacy of 94.44%. These outcomes underscore the potency of combining e-noses with TinyML in embedded systems, offering a noninvasive approach for diabetes mellitus detection.
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Affiliation(s)
- Alberto Gudiño-Ochoa
- Electronics Department, Tecnológico Nacional de México/Instituto Tecnológico de Ciudad Guzmán, Ciudad Guzmán 49100, Mexico; (A.G.-O.); (J.I.C.-C.); (D.A.S.-A.)
| | - Julio Alberto García-Rodríguez
- Centro Universitario del Sur, Departamento de Ciencias Computacionales e Innovación Tecnológica, Universidad de Guadalajara, Ciudad Guzmán 49000, Mexico
| | - Raquel Ochoa-Ornelas
- Systems and Computation Department, Tecnológico Nacional de México/Instituto Tecnológico de Ciudad Guzmán, Ciudad Guzmán 49100, Mexico;
| | - Jorge Ivan Cuevas-Chávez
- Electronics Department, Tecnológico Nacional de México/Instituto Tecnológico de Ciudad Guzmán, Ciudad Guzmán 49100, Mexico; (A.G.-O.); (J.I.C.-C.); (D.A.S.-A.)
| | - Daniel Alejandro Sánchez-Arias
- Electronics Department, Tecnológico Nacional de México/Instituto Tecnológico de Ciudad Guzmán, Ciudad Guzmán 49100, Mexico; (A.G.-O.); (J.I.C.-C.); (D.A.S.-A.)
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Koktavá M, Prysiazhnyi V, Preisler J, Bednařík A. Comparison of Cu +, Ag +, and Au + Ions as Ionization Agents of Volatile Organic Compounds at Subatmospheric Pressure. JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY 2024; 35:307-316. [PMID: 38265025 PMCID: PMC10853958 DOI: 10.1021/jasms.3c00370] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/20/2023] [Revised: 12/15/2023] [Accepted: 01/08/2024] [Indexed: 01/25/2024]
Abstract
Ionization of volatile organic compounds (VOCs) by coinage metal ions (Cu+, Ag+, and Au+) generated by laser desorption and ionization (LDI) of a metal nanolayer in subatmospheric conditions is explored. The study was performed in a commercial subatmospheric dual MALDI/ESI ion source. Five compounds representing different VOC classes were chosen for a detailed study of the metal ionization mechanism: ethanol, acetone, acetic acid, xylene, and cyclohexane. In the gas phase, ion molecular complexes of all three metal ions were formed, typically with two ligand molecules. The successful detection of the metal complexes with VOCs strongly depended on the applied voltages across the ion source, minimizing the in-source fragmentation. The employed orbital trap with ultrahigh resolving power and sub-parts-per-million mass accuracy allowed unambiguous identification of the formed complexes based on their molecular formulas. The detection limits of the studied compounds in the gas were in the range 0.1-1.4 nmol/L. Compared to Cu+ and Ag+ ions, Au+ ions exhibited the highest reactivity, often complicating spectra by side products of reactions. On the other hand, they also allowed detecting saturated hydrocarbons, which did not produce any signals with Ag+ and Cu+.
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Affiliation(s)
- Monika Koktavá
- Department of Chemistry,
Faculty of Science, Masaryk University, 625 00 Brno, Czech Republic
| | - Vadym Prysiazhnyi
- Department of Chemistry,
Faculty of Science, Masaryk University, 625 00 Brno, Czech Republic
| | - Jan Preisler
- Department of Chemistry,
Faculty of Science, Masaryk University, 625 00 Brno, Czech Republic
| | - Antonín Bednařík
- Department of Chemistry,
Faculty of Science, Masaryk University, 625 00 Brno, Czech Republic
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5
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Mohamadbeigi N, Shooshtari L, Fardindoost S, Vafaiee M, Iraji Zad A, Mohammadpour R. Self-powered triboelectric nanogenerator sensor for detecting humidity level and monitoring ethanol variation in a simulated exhalation environment. Sci Rep 2024; 14:1562. [PMID: 38238422 PMCID: PMC10796746 DOI: 10.1038/s41598-024-51862-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2023] [Accepted: 01/10/2024] [Indexed: 01/22/2024] Open
Abstract
Respiration stands as a vital process reflecting physiological and pathological human health status. Exhaled breath analysis offers a facile, non-invasive, swift, and cost-effective approach for diagnosing and monitoring diseases by detecting concentration changes of specific biomarkers. In this study, we employed Polyethylene oxide/copper (I) oxide composite nanofibers (PCNFs), synthesized via the electrospinning method as the sensing material to measure ethanol levels (1-200 ppm) in an exhaled breath simulator environment. The integrated contact-separation triboelectric nanogenerator was utilized to power the self-powered PCNFs exhaled breath sensor. The PCNFs-based gas sensor demonstrates promising results with values of 0.9 and 3.2 for detecting 5 ppm and 200 ppm ethanol, respectively, in the presence of interfering gas at 90% relative humidity (RH). Notably, the sensor displayed remarkable ethanol selectivity, with ratios of 10:1 to methanol and 25:1 to acetone. Response and recovery times for 200 ppm ethanol at 90 RH% were rapid, at 2.7 s and 5.8 s, respectively. The PCNFs-based exhaled breath sensor demonstrated consistent and stable performance in practical conditions, showcasing its potential for integration into wearable devices. This self-powered breath sensor enabling continuous monitoring of lung cancer symptoms and facilitating compliance checks with legal alcohol consumption limits.
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Affiliation(s)
- Nima Mohamadbeigi
- Center for Nanoscience and Nanotechnology, Institute for Convergence Science and Technology, Sharif University of Technology, Tehran, Iran
| | - Leyla Shooshtari
- Center for Nanoscience and Nanotechnology, Institute for Convergence Science and Technology, Sharif University of Technology, Tehran, Iran
| | - Somayeh Fardindoost
- Center for Nanoscience and Nanotechnology, Institute for Convergence Science and Technology, Sharif University of Technology, Tehran, Iran
- Faculty of Engineering, Department of Mechanical Engineering, University of Victoria, P.O. Box 1700 STN CSC, Victoria, BC, V8W 2Y2, Canada
| | - Mohaddese Vafaiee
- Center for Nanoscience and Nanotechnology, Institute for Convergence Science and Technology, Sharif University of Technology, Tehran, Iran
| | - Azam Iraji Zad
- Center for Nanoscience and Nanotechnology, Institute for Convergence Science and Technology, Sharif University of Technology, Tehran, Iran.
- Department of Physics, Sharif University of Technology, Azadi Street, P.O. Box 11365-9161, Tehran, Iran.
| | - Raheleh Mohammadpour
- Center for Nanoscience and Nanotechnology, Institute for Convergence Science and Technology, Sharif University of Technology, Tehran, Iran.
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6
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Khokhar M. Non-invasive detection of renal disease biomarkers through breath analysis. J Breath Res 2024; 18:024001. [PMID: 38099568 DOI: 10.1088/1752-7163/ad15fb] [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: 07/10/2023] [Accepted: 12/14/2023] [Indexed: 01/06/2024]
Abstract
Breath biomarkers are substances found in exhaled breath that can be used for non-invasive diagnosis and monitoring of medical conditions, including kidney disease. Detection techniques include mass spectrometry (MS), gas chromatography (GC), and electrochemical sensors. Biosensors, such as GC-MS or electronic nose (e-nose) devices, can be used to detect volatile organic compounds (VOCs) in exhaled breath associated with metabolic changes in the body, including the kidneys. E-nose devices could provide an early indication of potential kidney problems through the detection of VOCs associated with kidney dysfunction. This review discusses the sources of breath biomarkers for monitoring renal disease during dialysis and different biosensor approaches for detecting exhaled breath biomarkers. The future of using various types of biosensor-based real-time breathing diagnosis for renal failure is also discussed.
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Affiliation(s)
- Manoj Khokhar
- Department of Biochemistry, All India Institute of Medical Sciences, Jodhpur, Rajasthan, India
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Jadhav MR, Wankhede PR, Srivastava S, Bhargaw HN, Singh S. Breath-based biosensors and system development for noninvasive detection of diabetes: A review. Diabetes Metab Syndr 2024; 18:102931. [PMID: 38171153 DOI: 10.1016/j.dsx.2023.102931] [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: 12/23/2022] [Revised: 12/15/2023] [Accepted: 12/15/2023] [Indexed: 01/05/2024]
Abstract
BACKGROUND AND AIMS In recent years, noninvasive techniques are becoming conspicuous for diabetes detection. Sweat, tear, saliva, urine and breath-based methods showing prominent results in breath acetone detection which is considered as a biomarker of diabetes. A concrete relationship between breath acetone and BG helps in the development of devices for diabetes detection. METHODS The primary source for this study includes scholarly publications that primarily focus on the development of biosensors and systems for diabetes detection using acetone present in breath. Articles were analysed to examine various types of biosensors with their sensing materials to provide acetone detection limits. Recent noninvasive systems and products have been investigated and determine the relationship between breath acetone and BG levels. RESULTS Breath-based biosensor technologies are capable for diabetes detection. The acetone biosensor detection ranges from 100 ppb to 100 ppm, and it can applicable from room temperature to 400 °C. In healthy volunteers, acetone level ranges from 0.32 to 2.19 ppm, while patients with diabetes exhibit a wider range of 0.22-21 ppm depending on the biosensor, detection method, and clinical circumstances of patients and lab conditions. CONCLUSION This manuscript presents an extensive analysis of breath-based biosensors and their potential for detection of diabetes. Acetone detection methods are promising but unable to provide concrete correlation between breath acetone and blood glucose levels. The present study motivates the continued research and development of biosensors, and electronic devices to provide linear relationship of breath acetone and BG for noninvasive diabetes detection applications.
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Affiliation(s)
- Mahendra R Jadhav
- CSIR-Advanced Materials and Processes Research Institute, Bhopal, 462026, Madhya Pradesh, India.
| | - P R Wankhede
- CSMSS Chh. Shahu College of Engineering, Chhatrapati Sambhajinagar, 431001, Maharashtra, India
| | - Satyam Srivastava
- CSIR-Central Electronics Engineering Research Institute, Pilani, 333031, Rajasthan, India
| | - Hari N Bhargaw
- CSIR-Advanced Materials and Processes Research Institute, Bhopal, 462026, Madhya Pradesh, India
| | - Samarth Singh
- CSIR-Advanced Materials and Processes Research Institute, Bhopal, 462026, Madhya Pradesh, India
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Sola-Martínez RA, Zeng J, Awchi M, Gisler A, Arnold K, Singh KD, Frey U, Díaz MC, de Diego Puente T, Sinues P. Preservation of exhaled breath samples for analysis by off-line SESI-HRMS: proof-of-concept study. J Breath Res 2023; 18:011002. [PMID: 38029449 DOI: 10.1088/1752-7163/ad10e1] [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: 08/28/2023] [Accepted: 11/29/2023] [Indexed: 12/01/2023]
Abstract
Secondary electrospray ionization-high resolution mass spectrometry (SESI-HRMS) is an established technique in the field of breath analysis characterized by its short analysis time, as well as high levels of sensitivity and selectivity. Traditionally, SESI-HRMS has been used for real-time breath analysis, which requires subjects to be at the location of the analytical platform. Therefore, it limits the possibilities for an introduction of this methodology in day-to-day clinical practice. However, recent methodological developments have shown feasibility on the remote sampling of exhaled breath in Nalophan® bags prior to measurement using SESI-HRMS. To further explore the range of applications of this method, we conducted a proof-of-concept study to assess the impact of the storage time of exhaled breath in Nalophan® bags at different temperatures (room temperature and dry ice) on the relative intensities of the compounds. In addition, we performed a detailed study of the storage effect of 27 aldehydes related to oxidative stress. After 2 h of storage, the mean of intensity of allm/zsignals relative to the samples analyzed without prior storage remained above 80% at both room temperature and dry ice. For the 27 aldehydes, the mean relative intensity losses were lower than 20% at 24 h of storage, remaining practically stable since the first hour of storage following sample collection. Furthermore, the mean relative intensity of most aldehydes in samples stored at room temperature was higher than those stored in dry ice, which could be related to water vapor condensation issues. These findings indicate that the exhaled breath samples could be preserved for hours with a low percentage of mean relative intensity loss, thereby allowing more flexibility in the logistics of off-line SESI-HRMS studies.
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Affiliation(s)
- Rosa A Sola-Martínez
- Department of Biochemistry and Molecular Biology B and Immunology, University of Murcia, Murcia, Spain
| | - Jiafa Zeng
- University of Basel Children's Hospital (UKBB), Basel, Switzerland
- Department of Biomedical Engineering, University of Basel, Allschwil, Switzerland
| | - Mo Awchi
- University of Basel Children's Hospital (UKBB), Basel, Switzerland
- Department of Biomedical Engineering, University of Basel, Allschwil, Switzerland
| | - Amanda Gisler
- University of Basel Children's Hospital (UKBB), Basel, Switzerland
| | - Kim Arnold
- University of Basel Children's Hospital (UKBB), Basel, Switzerland
- Department of Biomedical Engineering, University of Basel, Allschwil, Switzerland
| | - Kapil Dev Singh
- University of Basel Children's Hospital (UKBB), Basel, Switzerland
- Department of Biomedical Engineering, University of Basel, Allschwil, Switzerland
| | - Urs Frey
- University of Basel Children's Hospital (UKBB), Basel, Switzerland
- Pediatric Respiratory Medicine, Department of Pediatrics, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
- Department of Biomedical Engineering, University of Basel, Allschwil, Switzerland
| | - Manuel Cánovas Díaz
- Department of Biochemistry and Molecular Biology B and Immunology, University of Murcia, Murcia, Spain
| | - Teresa de Diego Puente
- Department of Biochemistry and Molecular Biology B and Immunology, University of Murcia, Murcia, Spain
| | - Pablo Sinues
- University of Basel Children's Hospital (UKBB), Basel, Switzerland
- Department of Biomedical Engineering, University of Basel, Allschwil, Switzerland
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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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Kapur R, Kumar Y, Sharma S, Rastogi V, Sharma S, Kanwar V, Sharma T, Bhavsar A, Dutt V. DiabeticSense: A Non-Invasive, Multi-Sensor, IoT-Based Pre-Diagnostic System for Diabetes Detection Using Breath. J Clin Med 2023; 12:6439. [PMID: 37892575 PMCID: PMC10607308 DOI: 10.3390/jcm12206439] [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: 08/23/2023] [Revised: 09/13/2023] [Accepted: 09/25/2023] [Indexed: 10/29/2023] Open
Abstract
Diabetes mellitus is a widespread chronic metabolic disorder that requires regular blood glucose level surveillance. Current invasive techniques, such as finger-prick tests, often result in discomfort, leading to infrequent monitoring and potential health complications. The primary objective of this study was to design a novel, portable, non-invasive system for diabetes detection using breath samples, named DiabeticSense, an affordable digital health device for early detection, to encourage immediate intervention. The device employed electrochemical sensors to assess volatile organic compounds in breath samples, whose concentrations differed between diabetic and non-diabetic individuals. The system merged vital signs with sensor voltages obtained by processing breath sample data to predict diabetic conditions. Our research used clinical breath samples from 100 patients at a nationally recognized hospital to form the dataset. Data were then processed using a gradient boosting classifier model, and the performance was cross-validated. The proposed system attained a promising accuracy of 86.6%, indicating an improvement of 20.72% over an existing regression technique. The developed device introduces a non-invasive, cost-effective, and user-friendly solution for preliminary diabetes detection. This has the potential to increase patient adherence to regular monitoring.
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Affiliation(s)
- Ritu Kapur
- Indian Knowledge System and Mental Health Applications Centre, Indian Institute of Technology Mandi, Kamand 175075, Himachal Pradesh, India; (R.K.); (Y.K.); (S.S.); (V.R.); (S.S.); (A.B.)
| | - Yashwant Kumar
- Indian Knowledge System and Mental Health Applications Centre, Indian Institute of Technology Mandi, Kamand 175075, Himachal Pradesh, India; (R.K.); (Y.K.); (S.S.); (V.R.); (S.S.); (A.B.)
| | - Swati Sharma
- Indian Knowledge System and Mental Health Applications Centre, Indian Institute of Technology Mandi, Kamand 175075, Himachal Pradesh, India; (R.K.); (Y.K.); (S.S.); (V.R.); (S.S.); (A.B.)
| | - Vedant Rastogi
- Indian Knowledge System and Mental Health Applications Centre, Indian Institute of Technology Mandi, Kamand 175075, Himachal Pradesh, India; (R.K.); (Y.K.); (S.S.); (V.R.); (S.S.); (A.B.)
| | - Shivani Sharma
- Indian Knowledge System and Mental Health Applications Centre, Indian Institute of Technology Mandi, Kamand 175075, Himachal Pradesh, India; (R.K.); (Y.K.); (S.S.); (V.R.); (S.S.); (A.B.)
| | - Vikrant Kanwar
- All India Institute of Medical Science Bilaspur, Noa 174001, Himachal Pradesh, India; (V.K.); (T.S.)
| | - Tarun Sharma
- All India Institute of Medical Science Bilaspur, Noa 174001, Himachal Pradesh, India; (V.K.); (T.S.)
| | - Arnav Bhavsar
- Indian Knowledge System and Mental Health Applications Centre, Indian Institute of Technology Mandi, Kamand 175075, Himachal Pradesh, India; (R.K.); (Y.K.); (S.S.); (V.R.); (S.S.); (A.B.)
| | - Varun Dutt
- Indian Knowledge System and Mental Health Applications Centre, Indian Institute of Technology Mandi, Kamand 175075, Himachal Pradesh, India; (R.K.); (Y.K.); (S.S.); (V.R.); (S.S.); (A.B.)
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Jang WB, Yi D, Nguyen TM, Lee Y, Lee EJ, Choi J, Kim YH, Choi EJ, Oh JW, Kwon SM. Artificial Neural Processing-Driven Bioelectronic Nose for the Diagnosis of Diabetes and Its Complications. Adv Healthc Mater 2023; 12:e2300845. [PMID: 37449876 DOI: 10.1002/adhm.202300845] [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: 03/16/2023] [Revised: 07/10/2023] [Accepted: 07/11/2023] [Indexed: 07/18/2023]
Abstract
Diabetes and its complications affect the younger population and are associated with a high mortality rate; however, early diagnosis can contribute to the selection of appropriate treatment regimens that can reduce mortality. Although diabetes diagnosis via exhaled breath has great potential for early diagnosis, research on such diagnosis is restricted to disease detection, requiring in-depth examination to diagnose and classify diseases and their complications. This study demonstrates the use of an artificial neural processing-based bioelectronic nose to accurately diagnose diabetes and classify diabetic types (type I and II) and their complications, such as heart disease. Specifically, an M13 phage-based electronic nose (e-nose) is used to explore the features of subjects with diabetes at various levels of cellular and organismal organization (cells, liver organoids, and mice). Exhaled breath samples are collected during culturing and exposed to the phage-based e-nose. Compared with cells, liver organoids cultured under conditions mimicking a diabetic environment display properties that closely resemble the characteristics of diabetic mice. Using neural pattern separation, the M13 phage-based e-nose achieves a classification success rate of over 86% for four conditions in mice, namely, type 1 diabetes, type 2 diabetes, diabetic cardiomyopathy, and cardiomyopathy.
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Affiliation(s)
- Woong Bi Jang
- Laboratory for Vascular Medicine and Stem Cell Biology, Department of Physiology, Medical Research Institute, School of Medicine, Pusan National University, Yangsan, 50612, Republic of Korea
- Convergence Stem Cell Research Center, Pusan National University, Yangsan, 50612, Republic of Korea
| | - Dongwon Yi
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Pusan National University Yangsan Hospital, Pusan National University School of Medicine, Yangsan, 50612, Republic of Korea
| | - Thanh Mien Nguyen
- Bio-IT Fusion Technology Research Institute, Pusan National University, Busan, 46241, Republic of Korea
| | - Yujin Lee
- Department of Nano Fusion Technology, Pusan National University, Busan, 46214, Republic of Korea
| | - Eun Ji Lee
- Laboratory for Vascular Medicine and Stem Cell Biology, Department of Physiology, Medical Research Institute, School of Medicine, Pusan National University, Yangsan, 50612, Republic of Korea
- Convergence Stem Cell Research Center, Pusan National University, Yangsan, 50612, Republic of Korea
| | - Jaewoo Choi
- Laboratory for Vascular Medicine and Stem Cell Biology, Department of Physiology, Medical Research Institute, School of Medicine, Pusan National University, Yangsan, 50612, Republic of Korea
- Convergence Stem Cell Research Center, Pusan National University, Yangsan, 50612, Republic of Korea
| | - You Hwan Kim
- Department of Nano Fusion Technology, Pusan National University, Busan, 46214, Republic of Korea
| | - Eun-Jung Choi
- Department of Nano Fusion Technology, Pusan National University, Busan, 46214, Republic of Korea
| | - Jin-Woo Oh
- Bio-IT Fusion Technology Research Institute, Pusan National University, Busan, 46241, Republic of Korea
- Department of Nano Fusion Technology, Pusan National University, Busan, 46214, Republic of Korea
- Korea Nanobiotechnology Center, Pusan National University, Busan, 46241, Republic of Korea
| | - Sang-Mo Kwon
- Laboratory for Vascular Medicine and Stem Cell Biology, Department of Physiology, Medical Research Institute, School of Medicine, Pusan National University, Yangsan, 50612, Republic of Korea
- Convergence Stem Cell Research Center, Pusan National University, Yangsan, 50612, Republic of Korea
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12
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Swargiary K, Jitpratak P, Pathak AK, Viphavakit C. Low-Cost ZnO Spray-Coated Optical Fiber Sensor for Detecting VOC Biomarkers of Diabetes. SENSORS (BASEL, SWITZERLAND) 2023; 23:7916. [PMID: 37765971 PMCID: PMC10536205 DOI: 10.3390/s23187916] [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: 08/07/2023] [Revised: 09/09/2023] [Accepted: 09/14/2023] [Indexed: 09/29/2023]
Abstract
A non-invasive optical fiber sensor for detecting volatile organic compounds (VOCs) as biomarkers of diabetes is proposed and experimentally demonstrated. It offers a low-cost and straightforward fabrication approach by implementing a one-step spray coating of a ZnO colloidal solution on a glass optical fiber. The structure of the optical fiber sensor is based on a single-mode fiber-coreless silica fiber-single-mode fiber (SMF-CSF-SMF) structure, where the CSF is the sensor region spliced between two SMFs. The ZnO layer of a higher refractive index coated over the sensing region improves the light interaction with the surrounding medium, leading to sensitivity enhancement. The optical properties, morphology, and elemental composition of the ZnO layer were analyzed. The sensing mechanism of the developed sensor is based on a wavelength interrogation technique showing wavelength shifts when the sensor is exposed to various VOC vapor concentration levels. Various concentrations of the three VOCs (including acetone, isopropanol, and ethanol) ranging from 20% to 100% were tested and analyzed. The sensor noticeably shows a significant response towards acetone vapor, with a better sensitivity of 0.162 nm/% vapor than for isopropanol (0.082 nm/% vapor) and ethanol (0.075 nm/% vapor) vapors. The high sensitivity and selectivity towards acetone, a common biomarker for diabetes, offers the potential for further development of this sensor as a smart healthcare system for monitoring diabetic conditions.
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Affiliation(s)
- Kankan Swargiary
- International School of Engineering (ISE), Intelligent Control Automation of Process Systems Research Unit, Chulalongkorn University, Bangkok 10330, Thailand
| | - Pannathorn Jitpratak
- Biomedical Engineering Program, Faculty of Engineering, Chulalongkorn University, Bangkok 10330, Thailand
| | - Akhilesh Kumar Pathak
- Center for Smart Structures and Materials, Department of Mechanical Engineering, Northwestern University, Evanston, IL 60208, USA
| | - Charusluk Viphavakit
- International School of Engineering (ISE), Intelligent Control Automation of Process Systems Research Unit, Chulalongkorn University, Bangkok 10330, Thailand
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13
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Yeganegi A, Yazdani K, Tasnim N, Fardindoost S, Hoorfar M. Microfluidic integrated gas sensors for smart analyte detection: a comprehensive review. Front Chem 2023; 11:1267187. [PMID: 37767341 PMCID: PMC10520252 DOI: 10.3389/fchem.2023.1267187] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2023] [Accepted: 08/28/2023] [Indexed: 09/29/2023] Open
Abstract
The utilization of gas sensors has the potential to enhance worker safety, mitigate environmental issues, and enable early diagnosis of chronic diseases. However, traditional sensors designed for such applications are often bulky, expensive, difficult to operate, and require large sample volumes. By employing microfluidic technology to miniaturize gas sensors, we can address these challenges and usher in a new era of gas sensors suitable for point-of-care and point-of-use applications. In this review paper, we systematically categorize microfluidic gas sensors according to their applications in safety, biomedical, and environmental contexts. Furthermore, we delve into the integration of various types of gas sensors, such as optical, chemical, and physical sensors, within microfluidic platforms, highlighting the resultant enhancements in performance within these domains.
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Affiliation(s)
| | | | | | | | - Mina Hoorfar
- School of Engineering and Computer Science, University of Victoria, Victoria, BC, Canada
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14
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Han B, Zhang X, Wang Y, Wang W, Wang B, Li S, Wang H, Yan Y, Han J, Wang C, Wang C. Real-time detection of isoprene marker gas based on micro-integrated chromatography system with GOQDs-modified μGC column and metal oxide gas detector. NANOTECHNOLOGY 2023; 34:455501. [PMID: 37536300 DOI: 10.1088/1361-6528/aced10] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/09/2023] [Accepted: 08/03/2023] [Indexed: 08/05/2023]
Abstract
Isoprene is a typical physiological marker that can be used to screen for chronic liver disease. This work developed a portable micro-integrated chromatography analysis system based on micro-electromechanical system technology, nanomaterials technology and embedded microcontroller technology. The system integrated components such as graphene oxide quantum dots modified semi-packed microcolumn, In2O3nanoflower (NF) gas-sensitive detector and 3D printed miniature solenoid valve group. The effectiveness of the separation effect of the micro-integrated system was verified by gas mixture test; the laws of the influence of carrier gas pressure and column temperature on the chromatographic separation performance, respectively, were investigated, and the working conditions (column temperature 90 °C and carrier gas pressure 7.5 kPa) for system testing were determined. The percentages of relative standard deviation of the peak areas and retention times obtained for the separated gases were in the range of 0.95%-6.06%, indicating the good reproducibility of the system. Meanwhile, the microintegrated system could detect isoprene down to 50 ppb at small injection volume (1 ml). The system response increased with increasing isoprene concentration and was linearly correlated with isoprene concentration (R2= 0.986), indicating that the system was expected to be used for trace detection of isoprene, a marker gas for liver disease, in the future.
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Affiliation(s)
- Baoqing Han
- School of Mechano- Electronic Engineering, Xidian University, Xi'an 710071, People's Republic of China
- State Key Laboratory for Manufacturing Systems Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, People's Republic of China
| | - Xinyu Zhang
- School of Mechano- Electronic Engineering, Xidian University, Xi'an 710071, People's Republic of China
| | - Yan Wang
- School of Information and Control Engineering, Xi'an University of Architecture and Technology, Xi'an, 710055, People's Republic of China
| | - Wenjuan Wang
- School of Mechano- Electronic Engineering, Xidian University, Xi'an 710071, People's Republic of China
| | - Benben Wang
- School of Mechano- Electronic Engineering, Xidian University, Xi'an 710071, People's Republic of China
| | - Shuai Li
- School of Mechano- Electronic Engineering, Xidian University, Xi'an 710071, People's Republic of China
| | - Hairong Wang
- State Key Laboratory for Manufacturing Systems Engineering, Xi'an Jiaotong University, Xi'an, Shaanxi 710049, People's Republic of China
| | - Yuefei Yan
- Guangzhou Institute of Technology, Xidian University, Guangzhou 510555, People's Republic of China
| | - Jiusheng Han
- Guangzhou Institute of Technology, Xidian University, Guangzhou 510555, People's Republic of China
| | - Chuanliu Wang
- Quzhou Peoples Hosp, Dept Neurol, 2 Zhongloudi Rd, Quzhou 324000, People's Republic of China
| | - Congsi Wang
- School of Mechano- Electronic Engineering, Xidian University, Xi'an 710071, People's Republic of China
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15
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Raymundo-Pereira PA. Biosensors for Monitoring of Biologically Relevant Molecules. BIOSENSORS 2023; 13:738. [PMID: 37504136 PMCID: PMC10377342 DOI: 10.3390/bios13070738] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/10/2023] [Accepted: 07/11/2023] [Indexed: 07/29/2023]
Abstract
Since the creation of the glucose enzyme sensor in the early 1960s by Clark and Lyons [...].
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16
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Lagopati N, Valamvanos TF, Proutsou V, Karachalios K, Pippa N, Gatou MA, Vagena IA, Cela S, Pavlatou EA, Gazouli M, Efstathopoulos E. The Role of Nano-Sensors in Breath Analysis for Early and Non-Invasive Disease Diagnosis. CHEMOSENSORS 2023; 11:317. [DOI: 10.3390/chemosensors11060317] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/11/2023]
Abstract
Early-stage, precise disease diagnosis and treatment has been a crucial topic of scientific discussion since time immemorial. When these factors are combined with experience and scientific knowledge, they can benefit not only the patient, but also, by extension, the entire health system. The development of rapidly growing novel technologies allows for accurate diagnosis and treatment of disease. Nanomedicine can contribute to exhaled breath analysis (EBA) for disease diagnosis, providing nanomaterials and improving sensing performance and detection sensitivity. Through EBA, gas-based nano-sensors might be applied for the detection of various essential diseases, since some of their metabolic products are detectable and measurable in the exhaled breath. The design and development of innovative nanomaterial-based sensor devices for the detection of specific biomarkers in breath samples has emerged as a promising research field for the non-invasive accurate diagnosis of several diseases. EBA would be an inexpensive and widely available commercial tool that could also be used as a disease self-test kit. Thus, it could guide patients to the proper specialty, bypassing those expensive tests, resulting, hence, in earlier diagnosis, treatment, and thus a better quality of life. In this review, some of the most prevalent types of sensors used in breath-sample analysis are presented in parallel with the common diseases that might be diagnosed through EBA, highlighting the impact of incorporating new technological achievements in the clinical routine.
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Affiliation(s)
- Nefeli Lagopati
- Laboratory of Biology, Department of Basic Medical Sciences, Medical School, National and Kapodistrian University of Athens, 11527 Athens, Greece
- Biomedical Research Foundation, Academy of Athens, 11527 Athens, Greece
| | - Theodoros-Filippos Valamvanos
- Laboratory of Biology, Department of Basic Medical Sciences, Medical School, National and Kapodistrian University of Athens, 11527 Athens, Greece
- Medical Physics Unit, 2nd Department of Radiology, Medical School, National and Kapodistrian University of Athens, Attikon University Hospital, 12462 Athens, Greece
| | - Vaia Proutsou
- Laboratory of Biology, Department of Basic Medical Sciences, Medical School, National and Kapodistrian University of Athens, 11527 Athens, Greece
- Medical Physics Unit, 2nd Department of Radiology, Medical School, National and Kapodistrian University of Athens, Attikon University Hospital, 12462 Athens, Greece
| | - Konstantinos Karachalios
- Laboratory of Biology, Department of Basic Medical Sciences, Medical School, National and Kapodistrian University of Athens, 11527 Athens, Greece
- Medical Physics Unit, 2nd Department of Radiology, Medical School, National and Kapodistrian University of Athens, Attikon University Hospital, 12462 Athens, Greece
| | - Natassa Pippa
- Section of Pharmaceutical Technology, Department of Pharmacy, School of Health Sciences, National and Kapodistrian University of Athens, 15771 Athens, Greece
| | - Maria-Anna Gatou
- Laboratory of General Chemistry, School of Chemical Engineering, National Technical University of Athens, Zografou Campus, 15772 Athens, Greece
| | - Ioanna-Aglaia Vagena
- Laboratory of Biology, Department of Basic Medical Sciences, Medical School, National and Kapodistrian University of Athens, 11527 Athens, Greece
| | - Smaragda Cela
- Laboratory of Biology, Department of Basic Medical Sciences, Medical School, National and Kapodistrian University of Athens, 11527 Athens, Greece
- Medical Physics Unit, 2nd Department of Radiology, Medical School, National and Kapodistrian University of Athens, Attikon University Hospital, 12462 Athens, Greece
| | - Evangelia A. Pavlatou
- Laboratory of General Chemistry, School of Chemical Engineering, National Technical University of Athens, Zografou Campus, 15772 Athens, Greece
| | - Maria Gazouli
- Laboratory of Biology, Department of Basic Medical Sciences, Medical School, National and Kapodistrian University of Athens, 11527 Athens, Greece
- School of Science and Technology, Hellenic Open University, 26335 Patra, Greece
| | - Efstathios Efstathopoulos
- Biomedical Research Foundation, Academy of Athens, 11527 Athens, Greece
- School of Science and Technology, Hellenic Open University, 26335 Patra, Greece
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17
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Lee S, Kim M, Ahn BJ, Jang Y. Odorant-responsive biological receptors and electronic noses for volatile organic compounds with aldehyde for human health and diseases: A perspective review. JOURNAL OF HAZARDOUS MATERIALS 2023; 455:131555. [PMID: 37156042 DOI: 10.1016/j.jhazmat.2023.131555] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/15/2023] [Revised: 04/19/2023] [Accepted: 05/01/2023] [Indexed: 05/10/2023]
Abstract
Volatile organic compounds (VOCs) are gaseous chemicals found in ambient air and exhaled breath. In particular, highly reactive aldehydes are frequently found in polluted air and have been linked to various diseases. Thus, extensive studies have been carried out to elucidate disease-specific aldehydes released from the body to develop potential biomarkers for diagnostic purposes. Mammals possess innate sensory systems, such as receptors and ion channels, to detect these VOCs and maintain physiological homeostasis. Recently, electronic biosensors such as the electronic nose have been developed for disease diagnosis. This review aims to present an overview of natural sensory receptors that can detect reactive aldehydes, as well as electronic noses that have the potential to diagnose certain diseases. In this regard, this review focuses on eight aldehydes that are well-defined as biomarkers in human health and disease. It offers insights into the biological aspects and technological advances in detecting aldehyde-containing VOCs. Therefore, this review will aid in understanding the role of aldehyde-containing VOCs in human health and disease and the technological advances for improved diagnosis.
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Affiliation(s)
- Solpa Lee
- Department of Medical and Digital Engineering, College of Engineering, Hanyang University, Seoul 04736, South Korea
| | - Minwoo Kim
- Department of Medical and Digital Engineering, College of Engineering, Hanyang University, Seoul 04736, South Korea
| | - Bum Ju Ahn
- Department of Pharmacology, College of Medicine, Hanyang University, Seoul 04736, South Korea
| | - Yongwoo Jang
- Department of Medical and Digital Engineering, College of Engineering, Hanyang University, Seoul 04736, South Korea; Department of Pharmacology, College of Medicine, Hanyang University, Seoul 04736, South Korea.
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18
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Soggiu F, Sabbatinelli J, Giuliani A, Benedetti R, Marchegiani A, Sgarangella F, Tibaldi A, Corsi D, Procopio AD, Calgaro S, Olivieri F, Spaterna A, Zampieri R, Rippo MR. Sensitivity and specificity of in vivo COVID-19 screening by detection dogs: Results of the C19-Screendog multicenter study. Heliyon 2023; 9:e15640. [PMID: 37251897 PMCID: PMC10209336 DOI: 10.1016/j.heliyon.2023.e15640] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2022] [Revised: 03/24/2023] [Accepted: 04/17/2023] [Indexed: 05/31/2023] Open
Abstract
Trained dogs can recognize the volatile organic compounds contained in biological samples of patients with COVID-19 infection. We assessed the sensitivity and specificity of in vivo SARS-CoV-2 screening by trained dogs. We recruited five dog-handler dyads. In the operant conditioning phase, the dogs were taught to distinguish between positive and negative sweat samples collected from volunteers' underarms in polymeric tubes. The conditioning was validated by tests involving 16 positive and 48 negative samples held or worn in such a way that the samples were invisible to the dog and handler. In the screening phase the dogs were led by their handlers to a drive-through facility for in vivo screening of volunteers who had just received a nasopharyngeal swab from nursing staff. Each volunteer who had already swabbed was subsequently tested by two dogs, whose responses were recorded as positive, negative, or inconclusive. The dogs' behavior was constantly monitored for attentiveness and wellbeing. All the dogs passed the conditioning phase, their responses showing a sensitivity of 83-100% and a specificity of 94-100%. The in vivo screening phase involved 1251 subjects, of whom 205 had a COVID-19 positive swab and two dogs per each subject to be screened. Screening sensitivity and specificity were respectively 91.6-97.6% and 96.3-100% when only one dog was involved, whereas combined screening by two dogs provided a higher sensitivity. Dog wellbeing was also analyzed: monitoring of stress and fatigue suggested that the screening activity did not adversely impact the dogs' wellbeing. This work, by screening a large number of subjects, strengthen recent findings that trained dogs can discriminate between COVID-19 infected and healthy human subjects and introduce two novel research aspects: i) assessement of signs of fatigue and stress in dogs during training and testing, and ii) combining screening by two dogs to improve detection sensitivity and specificity. Using some precautions to reduce the risk of infection and spillover, in vivo COVID-19 screening by a dog-handler dyad can be suitable to quickly screen large numbers of people: it is rapid, non-invasive and economical, since it does not involve actual sampling, lab resources or waste management, and is suitable to screen large numbers of people.
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Affiliation(s)
- Francesca Soggiu
- Dipartimento di Prevenzione, ATS Sardegna, Italy
- Progetto Serena APS, Cinto Caomaggiore, Italy
| | - Jacopo Sabbatinelli
- Department of Clinical and Molecular Sciences, DISCLIMO, Università Politecnica delle Marche, Ancona, Italy
| | - Angelica Giuliani
- Department of Clinical and Molecular Sciences, DISCLIMO, Università Politecnica delle Marche, Ancona, Italy
| | | | - Andrea Marchegiani
- School of Biosciences and Veterinary Medicine, University of Camerino, Matelica, Italy
| | | | | | | | - Antonio Domenico Procopio
- Department of Clinical and Molecular Sciences, DISCLIMO, Università Politecnica delle Marche, Ancona, Italy
- Clinical Laboratory and Molecular Diagnostic, IRCCS INRCA, Ancona, Italy
| | | | - Fabiola Olivieri
- Department of Clinical and Molecular Sciences, DISCLIMO, Università Politecnica delle Marche, Ancona, Italy
- Clinical Laboratory and Molecular Diagnostic, IRCCS INRCA, Ancona, Italy
| | - Andrea Spaterna
- School of Biosciences and Veterinary Medicine, University of Camerino, Matelica, Italy
| | | | - Maria Rita Rippo
- Department of Clinical and Molecular Sciences, DISCLIMO, Università Politecnica delle Marche, Ancona, Italy
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19
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P H, Rangarajan M, Pandya HJ. Breath VOC analysis and machine learning approaches for disease screening: a review. J Breath Res 2023; 17. [PMID: 36634360 DOI: 10.1088/1752-7163/acb283] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2022] [Accepted: 01/12/2023] [Indexed: 01/14/2023]
Abstract
Early disease detection is often correlated with a reduction in mortality rate and improved prognosis. Currently, techniques like biopsy and imaging that are used to screen chronic diseases are invasive, costly or inaccessible to a large population. Thus, a non-invasive disease screening technology is the need of the hour. Existing non-invasive methods like gas chromatography-mass spectrometry, selected-ion flow-tube mass spectrometry, and proton transfer reaction-mass-spectrometry are expensive. These techniques necessitate experienced operators, making them unsuitable for a large population. Various non-invasive sources are available for disease detection, of which exhaled breath is preferred as it contains different volatile organic compounds (VOCs) that reflect the biochemical reactions in the human body. Disease screening by exhaled breath VOC analysis can revolutionize the healthcare industry. This review focuses on exhaled breath VOC biomarkers for screening various diseases with a particular emphasis on liver diseases and head and neck cancer as examples of diseases related to metabolic disorders and diseases unrelated to metabolic disorders, respectively. Single sensor and sensor array-based (Electronic Nose) approaches for exhaled breath VOC detection are briefly described, along with the machine learning techniques used for pattern recognition.
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Affiliation(s)
- Haripriya P
- Department of Electronic Systems Engineering, Indian Institute of Science, Bangalore 560012, India
| | - Madhavan Rangarajan
- Department of Electronic Systems Engineering, Indian Institute of Science, Bangalore 560012, India
| | - Hardik J Pandya
- Department of Electronic Systems Engineering, Indian Institute of Science, Bangalore 560012, India.,Centre for Product Design and Manufacturing, Indian Institute of Science, Bangalore 560012, India
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20
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Peña A, Aguilera JD, Matatagui D, de la Presa P, Horrillo C, Hernando A, Marín P. Real-Time Monitoring of Breath Biomarkers with A Magnetoelastic Contactless Gas Sensor: A Proof of Concept. BIOSENSORS 2022; 12:871. [PMID: 36291006 PMCID: PMC9599754 DOI: 10.3390/bios12100871] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/19/2022] [Revised: 09/26/2022] [Accepted: 10/10/2022] [Indexed: 06/16/2023]
Abstract
In the quest for effective gas sensors for breath analysis, magnetoelastic resonance-based gas sensors (MEGSs) are remarkable candidates. Thanks to their intrinsic contactless operation, they can be used as non-invasive and portable devices. However, traditional monitoring techniques are bound to slow detection, which hinders their application to fast bio-related reactions. Here we present a method for real-time monitoring of the resonance frequency, with a proof of concept for real-time monitoring of gaseous biomarkers based on resonance frequency. This method was validated with a MEGS based on a Metglass 2826 MB microribbon with a polyvinylpyrrolidone (PVP) nanofiber electrospun functionalization. The device provided a low-noise (RMS = 1.7 Hz), fast (<2 min), and highly reproducible response to humidity (Δf = 46−182 Hz for 17−95% RH), ammonia (Δf = 112 Hz for 40 ppm), and acetone (Δf = 44 Hz for 40 ppm). These analytes are highly important in biomedical applications, particularly ammonia and acetone, which are biomarkers related to diseases such as diabetes. Furthermore, the capability of distinguishing between breath and regular air was demonstrated with real breath measurements. The sensor also exhibited strong resistance to benzene, a common gaseous interferent in breath analysis.
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Affiliation(s)
- Alvaro Peña
- Instituto de Magnetismo Aplicado (IMA), Universidad Complutense de Madrid-Administrador de Infraestructuras Ferroviarias (UCM-ADIF), 28230 Las Rozas, Spain
| | - Juan Diego Aguilera
- Instituto de Magnetismo Aplicado (IMA), Universidad Complutense de Madrid-Administrador de Infraestructuras Ferroviarias (UCM-ADIF), 28230 Las Rozas, Spain
| | - Daniel Matatagui
- Instituto de Magnetismo Aplicado (IMA), Universidad Complutense de Madrid-Administrador de Infraestructuras Ferroviarias (UCM-ADIF), 28230 Las Rozas, Spain
- Departamento de Física de Materiales, Universidad Complutense de Madrid (UCM), 28040 Madrid, Spain
- Grupo de Tecnología de Sensores Avanzados (SENSAVAN), Instituto de Tecnologías Físicas y de la Información (ITEFI), Consejo Superior de Investigaciones Científicas (CSIC), 28006 Madrid, Spain
| | - Patricia de la Presa
- Instituto de Magnetismo Aplicado (IMA), Universidad Complutense de Madrid-Administrador de Infraestructuras Ferroviarias (UCM-ADIF), 28230 Las Rozas, Spain
- Departamento de Física de Materiales, Universidad Complutense de Madrid (UCM), 28040 Madrid, Spain
| | - Carmen Horrillo
- Grupo de Tecnología de Sensores Avanzados (SENSAVAN), Instituto de Tecnologías Físicas y de la Información (ITEFI), Consejo Superior de Investigaciones Científicas (CSIC), 28006 Madrid, Spain
| | - Antonio Hernando
- Instituto de Magnetismo Aplicado (IMA), Universidad Complutense de Madrid-Administrador de Infraestructuras Ferroviarias (UCM-ADIF), 28230 Las Rozas, Spain
- Donostia International Physics Center, 20018 Donostia, Spain
- Instituto Madrileño de Estudios Avanzados (IMDEA) Nanociencia, 28049 Madrid, Spain
- Departamento de Ingeniería, Universidad de Nebrija, 28015 Madrid, Spain
| | - Pilar Marín
- Instituto de Magnetismo Aplicado (IMA), Universidad Complutense de Madrid-Administrador de Infraestructuras Ferroviarias (UCM-ADIF), 28230 Las Rozas, Spain
- Departamento de Física de Materiales, Universidad Complutense de Madrid (UCM), 28040 Madrid, Spain
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21
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Todaro B, Begarani F, Sartori F, Luin S. Is Raman the best strategy towards the development of non-invasive continuous glucose monitoring devices for diabetes management? Front Chem 2022; 10:994272. [PMID: 36226124 PMCID: PMC9548653 DOI: 10.3389/fchem.2022.994272] [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: 07/14/2022] [Accepted: 08/24/2022] [Indexed: 11/27/2022] Open
Abstract
Diabetes has no well-established cure; thus, its management is critical for avoiding severe health complications involving multiple organs. This requires frequent glycaemia monitoring, and the gold standards for this are fingerstick tests. During the last decades, several blood-withdrawal-free platforms have been being studied to replace this test and to improve significantly the quality of life of people with diabetes (PWD). Devices estimating glycaemia level targeting blood or biofluids such as tears, saliva, breath and sweat, are gaining attention; however, most are not reliable, user-friendly and/or cheap. Given the complexity of the topic and the rise of diabetes, a careful analysis is essential to track scientific and industrial progresses in developing diabetes management systems. Here, we summarize the emerging blood glucose level (BGL) measurement methods and report some examples of devices which have been under development in the last decades, discussing the reasons for them not reaching the market or not being really non-invasive and continuous. After discussing more in depth the history of Raman spectroscopy-based researches and devices for BGL measurements, we will examine if this technique could have the potential for the development of a user-friendly, miniaturized, non-invasive and continuous blood glucose-monitoring device, which can operate reliably, without inter-patient variability, over sustained periods.
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Affiliation(s)
- Biagio Todaro
- NEST Laboratory, Scuola Normale SuperiorePisa, Italy
- Correspondence: Biagio Todaro, ; Stefano Luin,
| | - Filippo Begarani
- P.B.L. SRL, Solignano, PR, Italy
- Omnidermal Biomedics SRL, Solignano, PR, Italy
| | - Federica Sartori
- P.B.L. SRL, Solignano, PR, Italy
- Omnidermal Biomedics SRL, Solignano, PR, Italy
| | - Stefano Luin
- NEST Laboratory, Scuola Normale SuperiorePisa, Italy
- NEST, Istituto Nanoscienze, CNR, Pisa, Italy
- Correspondence: Biagio Todaro, ; Stefano Luin,
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Prasanth A, Getachew S, Shewa T, Velumani M, Meher SR, Alex ZC. A Bilayer SnO2/MoS2-Coated Evanescent Wave Fiber Optic Sensor for Acetone Detection—An Experimental Study. BIOSENSORS 2022; 12:bios12090734. [PMID: 36140119 PMCID: PMC9496449 DOI: 10.3390/bios12090734] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/27/2022] [Revised: 08/19/2022] [Accepted: 09/01/2022] [Indexed: 11/24/2022]
Abstract
The need for sensors that measure the acetone content of exhaled breath for diabetes severity has recently increased. Clinical researchers have reported less than 0.8 ppm acetone concentration in the exhaled breath of an average individual, while that for a diabetic patient is higher than 1.8 ppm. This work reports the development of two sets of evanescent wave-based fiber optic sensor coated with SnO2 thin film and bilayer of SnO2/MoS2 to detect different acetone concentrations (0–250 ppm). In each set, we have studied the effect of clad thickness (chemical etch time 5min, 10 min, 15 min, 25 min, 40 min, and complete clad removal) to optimize the clad thickness for a better response. In Set 1, SnO2 thin film was used as the sensing layer, while in Set 2 a bilayer of SnO2 thin film/ MoS2 was used. Enhanced sensor response of ~23.5% is observed in the Set 2 probe with a response and recovery time of ~14 s/~17 s. A SnO2/MoS2-coated sensor prototype is developed using LEDs of different wavelength and intensity detector; its potential to detect different concentrations of acetone is tested. X-ray Diffraction (XRD), Scanning Electron Microscope (SEM), Ultraviolet (UV) Spectroscopy, and Ellipsometry were used to study the structural, morphological and optical properties of the sensing layers. The present study indicates that the SnO2/MoS2-coated sensor has the potential to create a handheld sensor system for monitoring diabetes.
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Affiliation(s)
- A. Prasanth
- Department of Sensor and Biomedical Technology, School of Electronics Engineering, Vellore Institute of Technology, Vellore 632014, India
| | - Selamawit Getachew
- Department of Sensor and Biomedical Technology, School of Electronics Engineering, Vellore Institute of Technology, Vellore 632014, India
| | - Tseganesh Shewa
- Department of Sensor and Biomedical Technology, School of Electronics Engineering, Vellore Institute of Technology, Vellore 632014, India
| | - M. Velumani
- Department of ECE, Madanapalle Institute of Technology and Science, Madanapalle 517325, India
| | - S. R. Meher
- Department of Physics, School of Advanced Sciences, Vellore Institute of Technology, Vellore 632014, India
| | - Z. C. Alex
- Department of Sensor and Biomedical Technology, School of Electronics Engineering, Vellore Institute of Technology, Vellore 632014, India
- Correspondence:
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Fu L, Lu P, Sima C, Zhao J, Pan Y, Li T, Zhang X, Liu D. Small-volume highly-sensitive all-optical gas sensor using non-resonant photoacoustic spectroscopy with dual silicon cantilever optical microphones. PHOTOACOUSTICS 2022; 27:100382. [PMID: 36068799 PMCID: PMC9441265 DOI: 10.1016/j.pacs.2022.100382] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/01/2022] [Revised: 06/22/2022] [Accepted: 06/27/2022] [Indexed: 05/22/2023]
Abstract
A small-volume highly-sensitive photoacoustic spectroscopy (PAS) methane detection system based on differential silicon cantilever optical microphones (SCOMs) is proposed and experimentally demonstrated. The system contains a compact non-resonant photoacoustic cell with a small volume of 1.2 mL and symmetrically-located dual SCOMs, as well as a distributed feedback laser at 1650.96 nm. The two identical SCOMs utilize the Fabry-Perot interferometric fiber-optic structure, with the differential Q-point demodulation algorithm to suppress the external vibration noise. Experimental results show that the SCOM has a high displacement sensitivity about 7.1 µm/Pa at 150 Hz and within 2.5 dB fluctuation between 5 Hz and 250 Hz. In the PAS gas sensing experiment, the normalized noise equivalent absorption coefficient of the PAS system is estimated to be 1.2 × 10-9 cm-1·W·Hz-1/2 and the minimum detection limit for methane is about 111.2 ppb with 1 s integration time. External disturbance is also applied to the dual SCOM system and results show excellent stability and noise resistance. The proposed PAS system exhibits superiorities of low gas consumption, high sensitivity and immunity to vibration and electromagnetic interference, which has an enormous potential in medicine, industry and environment.
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Affiliation(s)
- Lujun Fu
- Wuhan National Laboratory for Optoelectronics (WNLO) and National Engineering Research Center for Next Generation Internet Access System, School of Optical and Electronic Information, Huazhong University of Science and Technology, Wuhan 430074, China
- Shenzhen Huazhong University of Science and Technology Research Institute, Shenzhen 518000, China
| | - Ping Lu
- Wuhan National Laboratory for Optoelectronics (WNLO) and National Engineering Research Center for Next Generation Internet Access System, School of Optical and Electronic Information, Huazhong University of Science and Technology, Wuhan 430074, China
- Shenzhen Huazhong University of Science and Technology Research Institute, Shenzhen 518000, China
- Wuhan OV Optical Networking Technology Co, Ltd, China
- Corresponding authors at: Wuhan National Laboratory for Optoelectronics (WNLO) and National Engineering Research Center for Next Generation Internet Access System, School of Optical and Electronic Information, Huazhong University of Science and Technology, Wuhan 430074, China.
| | - Chaotan Sima
- Wuhan National Laboratory for Optoelectronics (WNLO) and National Engineering Research Center for Next Generation Internet Access System, School of Optical and Electronic Information, Huazhong University of Science and Technology, Wuhan 430074, China
- Shenzhen Huazhong University of Science and Technology Research Institute, Shenzhen 518000, China
- Corresponding authors at: Wuhan National Laboratory for Optoelectronics (WNLO) and National Engineering Research Center for Next Generation Internet Access System, School of Optical and Electronic Information, Huazhong University of Science and Technology, Wuhan 430074, China.
| | - Jinbiao Zhao
- Wuhan National Laboratory for Optoelectronics (WNLO) and National Engineering Research Center for Next Generation Internet Access System, School of Optical and Electronic Information, Huazhong University of Science and Technology, Wuhan 430074, China
| | - Yufeng Pan
- Wuhan National Laboratory for Optoelectronics (WNLO) and National Engineering Research Center for Next Generation Internet Access System, School of Optical and Electronic Information, Huazhong University of Science and Technology, Wuhan 430074, China
| | - Tailin Li
- Wuhan National Laboratory for Optoelectronics (WNLO) and National Engineering Research Center for Next Generation Internet Access System, School of Optical and Electronic Information, Huazhong University of Science and Technology, Wuhan 430074, China
| | - Xiaohang Zhang
- Wuhan National Laboratory for Optoelectronics (WNLO) and National Engineering Research Center for Next Generation Internet Access System, School of Optical and Electronic Information, Huazhong University of Science and Technology, Wuhan 430074, China
| | - Deming Liu
- Wuhan National Laboratory for Optoelectronics (WNLO) and National Engineering Research Center for Next Generation Internet Access System, School of Optical and Electronic Information, Huazhong University of Science and Technology, Wuhan 430074, China
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Analysis of volatile organic compounds from deep airway in the lung through intubation sampling. Anal Bioanal Chem 2022; 414:7647-7658. [PMID: 36018334 DOI: 10.1007/s00216-022-04295-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2022] [Revised: 08/14/2022] [Accepted: 08/17/2022] [Indexed: 11/09/2022]
Abstract
Exhaled volatile organic compounds (VOCs) have been widely applied for the study of disease biomarkers. Oral exhalation and nasal exhalation are two of the most common sampling methods. However, VOCs released from food residues and bacteria in the mouth or upper respiratory tract were also sampled and usually mistaken as that produced from body metabolism. In this study, exhalation from deep airway was first directly collected through intubation sampling and analyzed. The exhalation samples of 35 subjects were collected through a catheter, which was inserted into the trachea or bronchus through the mouth and upper respiratory tract. Then, the VOCs in these samples were detected by proton transfer reaction mass spectrometry (PTR-MS). In addition, fast gas chromatography proton transfer reaction mass spectrometry (FGC-PTR-MS) was used to further determine the VOCs with the same mass-to-charge ratios. The results showed that there was methanol, acetonitrile, ethanol, methyl mercaptan, acetone, isoprene, and phenol in the deep airway. Compared with that in oral exhalation, ethanol, methyl mercaptan, and phenol had lower concentrations. In detail, the median concentrations of ethanol, methyl mercaptan, and phenol were 7.3, 0.6, and 23.9 ppbv, while those in the oral exhalation were 80.0, 5.1, and 71.3 ppbv, respectively, which meant the three VOCs mainly originated from the food residues and bacteria in the mouth or upper respiratory tract, rather than body metabolism. The research results in our study can provide references for expiratory VOC research based on oral and nasal exhalation samplings, which are more feasible in clinical practice.
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Franco FF, Hogg RA, Manjakkal L. Cu 2O-Based Electrochemical Biosensor for Non-Invasive and Portable Glucose Detection. BIOSENSORS 2022; 12:bios12030174. [PMID: 35323444 PMCID: PMC8946795 DOI: 10.3390/bios12030174] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/16/2022] [Revised: 03/09/2022] [Accepted: 03/12/2022] [Indexed: 05/14/2023]
Abstract
Electrochemical voltammetric sensors are some of the most promising types of sensors for monitoring various physiological analytes due to their implementation as non-invasive and portable devices. Advantages in reduced analysis time, cost-effectiveness, selective sensing, and simple techniques with low-powered circuits distinguish voltammetric sensors from other methods. In this work, we developed a Cu2O-based non-enzymatic portable glucose sensor on a graphene paste printed on cellulose cloth. The electron transfer of Cu2O in a NaOH alkaline medium and sweat equivalent solution at very low potential (+0.35 V) enable its implementation as a low-powered portable glucose sensor. The redox mechanism of the electrodes with the analyte solution was confirmed through cyclic voltammetry, differential pulse voltammetry, and electrochemical impedance spectroscopy studies. The developed biocompatible, disposable, and reproducible sensors showed sensing performance in the range of 0.1 to 1 mM glucose, with a sensitivity of 1082.5 ± 4.7% µA mM-1 cm-2 on Cu2O coated glassy carbon electrode and 182.9 ± 8.83% µA mM-1 cm-2 on Cu2O coated graphene printed electrodes, making them a strong candidate for future portable, non-invasive glucose monitoring devices on biodegradable substrates. For portable applications we demonstrated the sensor on artificial sweat in 0.1 M NaOH solution, indicating the Cu2O nanocluster is selective to glucose from 0.0 to +0.6 V even in the presence of common interference such as urea and NaCl.
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Affiliation(s)
- Fabiane Fantinelli Franco
- Water and Environment Group, Infrastructure and Environment Division, James Watt School of Engineering, University of Glasgow, Glasgow G12 8LT, UK;
| | - Richard A. Hogg
- Electronic and Nanoscale Engineering, James Watt School of Engineering, University of Glasgow, Glasgow G12 8LT, UK;
| | - Libu Manjakkal
- Electronic and Nanoscale Engineering, James Watt School of Engineering, University of Glasgow, Glasgow G12 8LT, UK;
- Correspondence:
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Velusamy P, Su CH, Ramasamy P, Arun V, Rajnish N, Raman P, Baskaralingam V, Senthil Kumar SM, Gopinath SCB. Volatile Organic Compounds as Potential Biomarkers for Noninvasive Disease Detection by Nanosensors: A Comprehensive Review. Crit Rev Anal Chem 2022; 53:1828-1839. [PMID: 35201946 DOI: 10.1080/10408347.2022.2043145] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Abstract
Biomarkers are biological molecules associated with physiological changes of the body and aids in the detecting the onset of disease in patients. There is an urgent need for self-monitoring and early detection of cardiovascular and other health complications. Several blood-based biomarkers have been well established in diagnosis and monitoring the onset of diseases. However, the detection level of biomarkers in bed-side analysis is difficult and complications arise due to the endothelial dysfunction. Currently single volatile organic compounds (VOCs) based sensors are available for the detection of human diseases and no dedicated nanosensor is available for the elderly. Moreover, accuracy of the sensors based on a single analyte is limited. Hence, breath analysis has received enormous attention in healthcare due to its relatively inexpensive, rapid, and noninvasive methods for detecting diseases. This review gives a detailed analysis of how biomarker imprinted nanosensor can be used as a noninvasive method for detecting VOC to health issues early using exhaled breath analysis.
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Affiliation(s)
- Palaniyandi Velusamy
- Research and Development Wing, Sree Balaji Medical College and Hospital (SBMCH), Bharath Institute of Higher Education and Research (BIHER), Chennai, Tamil Nadu, India
| | - Chia-Hung Su
- Department of Chemical Engineering, Ming Chi University of Technology, Taishan, Taipei, Taiwan
| | - Palaniappan Ramasamy
- Research and Development Wing, Sree Balaji Medical College and Hospital (SBMCH), Bharath Institute of Higher Education and Research (BIHER), Chennai, Tamil Nadu, India
| | - Viswanathan Arun
- Department of Biotechnology SRFBMST, Sri Ramachandra Institute of Higher Education & Research, Chennai, Tamil Nadu, India
| | - Narayanan Rajnish
- Department of Biotechnology, School of Bioengineering, SRM Institute of Science and Technology, Kattankulathur, Tamil Nadu, India
| | - Pachaiappan Raman
- Department of Biotechnology, School of Bioengineering, SRM Institute of Science and Technology, Kattankulathur, Tamil Nadu, India
| | - Vaseeharan Baskaralingam
- Nanobiosciences and Nanopharmacology Division, Biomaterials and Biotechnology in Animal Health Lab, Department of Animal Health and Management, Alagappa University, Karaikudi, Tamil Nadu, India
| | - Sakkarapalayam Murugesan Senthil Kumar
- Electroorganic and Materials Electrochemistry Division, CSIR-Central Electrochemical Research Institute, Karaikudi, Tamil Nadu, India
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad, India
| | - Subash C B Gopinath
- Faculty of Chemical Engineering Technology and Institute of Nano Electronic Engineering, Universiti Malaysia Perlis, Arau, Perlis, Malaysia
- Centre of Excellence for Nanobiotechnology and Nanomedicine (CoExNano), Faculty of Applied Sciences, AIMST University, Semeling, Kedah, Malaysia
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Breath Sensor Technology for the Use in Mechanical Lung Ventilation Equipment for Monitoring Critically Ill Patients. Diagnostics (Basel) 2022; 12:diagnostics12020430. [PMID: 35204521 PMCID: PMC8870831 DOI: 10.3390/diagnostics12020430] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2021] [Revised: 02/05/2022] [Accepted: 02/06/2022] [Indexed: 12/31/2022] Open
Abstract
Background: The need for mechanical lung ventilation is common in critically ill patients, either with COVID-19 infection or due to other causes. Monitoring of patients being ventilated is essential for timely and improved management. We here propose the use of a novel breath volatile organic compound sensor technology to be used in a mechanical lung ventilation machine for this purpose; the technology was evaluated in critically ill COVID-19 patients on mechanical lung ventilation. Methods: Based on the consistency results of our study data, the breath sensor device with metal oxide gas sensors and environment-controlling sensors was mounted on the ventilation exhaust port of the ventilation machine; this allowed to ensure additional safety since the device was placed outside the contour between the patient and equipment. Results: The sensors allowed stable registration of the signals for up to several weeks for 10 patients in total, depending on the storage amount; a proportion of patients were intubated or received tracheostoma during the evaluation period. Future studies are on the way to correlate sensor readings to other parameters characterizing the severity of the patient condition and outcome. Conclusions: We suppose that such technology will allow patient monitoring in real-time for timely identification of deterioration, potentially requiring some change of management. The obtained results are preliminary and further studies are needed to examine their clinical significance.
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Paleczek A, Rydosz AM. Review of the algorithms used in exhaled breath analysis for the detection of diabetes. J Breath Res 2022; 16. [PMID: 34996056 DOI: 10.1088/1752-7163/ac4916] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2021] [Accepted: 01/07/2022] [Indexed: 11/11/2022]
Abstract
Currently, intensive work is underway on the development of truly noninvasive medical diagnostic systems, including respiratory analysers based on the detection of biomarkers of several diseases including diabetes. In terms of diabetes, acetone is considered as a one of the potential biomarker, although is not the single one. Therefore, the selective detection is crucial. Most often, the analysers of exhaled breath are based on the utilization of several commercially available gas sensors or on specially designed and manufactured gas sensors to obtain the highest selectivity and sensitivity to diabetes biomarkers present in the exhaled air. An important part of each system are the algorithms that are trained to detect diabetes based on data obtained from sensor matrices. The prepared review of the literature showed that there are many limitations in the development of the versatile breath analyser, such as high metabolic variability between patients, but the results obtained by researchers using the algorithms described in this paper are very promising and most of them achieve over 90% accuracy in the detection of diabetes in exhaled air. This paper summarizes the results using various measurement systems, feature extraction and feature selection methods as well as algorithms such as Support Vector Machines, k-Nearest Neighbours and various variations of Neural Networks for the detection of diabetes in patient samples and simulated artificial breath samples.
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Affiliation(s)
- Anna Paleczek
- Institute of Electronics, AGH University of Science and Technology Faculty of Computer Science Electronics and Telecommunications, al. A. Mickiewicza 30, Krakow, 30-059, POLAND
| | - Artur Maciej Rydosz
- Institute of Electronics, AGH University of Science and Technology Faculty of Computer Science Electronics and Telecommunications, Al. Mickiewicza 30, Krakow, 30-059, POLAND
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Xue Y, Thalmayer AS, Zeising S, Fischer G, Lübke M. Commercial and Scientific Solutions for Blood Glucose Monitoring-A Review. SENSORS (BASEL, SWITZERLAND) 2022; 22:425. [PMID: 35062385 PMCID: PMC8780031 DOI: 10.3390/s22020425] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/23/2021] [Revised: 12/27/2021] [Accepted: 12/29/2021] [Indexed: 12/25/2022]
Abstract
Diabetes is a chronic and, according to the state of the art, an incurable disease. Therefore, to treat diabetes, regular blood glucose monitoring is crucial since it is mandatory to mitigate the risk and incidence of hyperglycemia and hypoglycemia. Nowadays, it is common to use blood glucose meters or continuous glucose monitoring via stinging the skin, which is classified as invasive monitoring. In recent decades, non-invasive monitoring has been regarded as a dominant research field. In this paper, electrochemical and electromagnetic non-invasive blood glucose monitoring approaches will be discussed. Thereby, scientific sensor systems are compared to commercial devices by validating the sensor principle and investigating their performance utilizing the Clarke error grid. Additionally, the opportunities to enhance the overall accuracy and stability of non-invasive glucose sensing and even predict blood glucose development to avoid hyperglycemia and hypoglycemia using post-processing and sensor fusion are presented. Overall, the scientific approaches show a comparable accuracy in the Clarke error grid to that of the commercial ones. However, they are in different stages of development and, therefore, need improvement regarding parameter optimization, temperature dependency, or testing with blood under real conditions. Moreover, the size of scientific sensing solutions must be further reduced for a wearable monitoring system.
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Affiliation(s)
| | | | | | - Georg Fischer
- Institute for Electronics Engineering, Friedrich-Alexander-Universität Erlangen-Nürnberg, Cauerstr. 9, 91058 Erlangen, Germany; (Y.X.); (A.S.T.); (S.Z.)
| | - Maximilian Lübke
- Institute for Electronics Engineering, Friedrich-Alexander-Universität Erlangen-Nürnberg, Cauerstr. 9, 91058 Erlangen, Germany; (Y.X.); (A.S.T.); (S.Z.)
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