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Huang X, Yao C, Huang S, Zheng S, Liu Z, Liu J, Wang J, Chen HJ, Xie X. Technological Advances of Wearable Device for Continuous Monitoring of In Vivo Glucose. ACS Sens 2024; 9:1065-1088. [PMID: 38427378 DOI: 10.1021/acssensors.3c01947] [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] [Indexed: 03/02/2024]
Abstract
Managing diabetes is a chronic challenge today, requiring monitoring and timely insulin injections to maintain stable blood glucose levels. Traditional clinical testing relies on fingertip or venous blood collection, which has facilitated the emergence of continuous glucose monitoring (CGM) technology to address data limitations. Continuous glucose monitoring technology is recognized for tracking long-term blood glucose fluctuations, and its development, particularly in wearable devices, has given rise to compact and portable continuous glucose monitoring devices, which facilitates the measurement of blood glucose and adjustment of medication. This review introduces the development of wearable CGM-based technologies, including noninvasive methods using body fluids and invasive methods using implantable electrodes. The advantages and disadvantages of these approaches are discussed as well as the use of microneedle arrays in minimally invasive CGM. Microneedle arrays allow for painless transdermal puncture and are expected to facilitate the development of wearable CGM devices. Finally, we discuss the challenges and opportunities and look forward to the biomedical applications and future directions of wearable CGM-based technologies in biological research.
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Affiliation(s)
- Xinshuo Huang
- State Key Laboratory of Optoelectronic Materials and Technologies, Guangdong Province Key Laboratory of Display Material and Technology, School of Electronics and Information Technology, Sun Yat-Sen University, Guangzhou, 510006, China
| | - Chuanjie Yao
- State Key Laboratory of Optoelectronic Materials and Technologies, Guangdong Province Key Laboratory of Display Material and Technology, School of Electronics and Information Technology, Sun Yat-Sen University, Guangzhou, 510006, China
| | - Shuang Huang
- State Key Laboratory of Optoelectronic Materials and Technologies, Guangdong Province Key Laboratory of Display Material and Technology, School of Electronics and Information Technology, Sun Yat-Sen University, Guangzhou, 510006, China
| | - Shantao Zheng
- State Key Laboratory of Optoelectronic Materials and Technologies, Guangdong Province Key Laboratory of Display Material and Technology, School of Electronics and Information Technology, Sun Yat-Sen University, Guangzhou, 510006, China
| | - Zhengjie Liu
- State Key Laboratory of Optoelectronic Materials and Technologies, Guangdong Province Key Laboratory of Display Material and Technology, School of Electronics and Information Technology, Sun Yat-Sen University, Guangzhou, 510006, China
| | - Jing Liu
- The First Affiliated Hospital of Sun Yat-Sen University, Sun Yat-Sen University, Guangzhou, 510006, China
| | - Ji Wang
- The First Affiliated Hospital of Sun Yat-Sen University, Sun Yat-Sen University, Guangzhou, 510006, China
| | - Hui-Jiuan Chen
- State Key Laboratory of Optoelectronic Materials and Technologies, Guangdong Province Key Laboratory of Display Material and Technology, School of Electronics and Information Technology, Sun Yat-Sen University, Guangzhou, 510006, China
| | - Xi Xie
- State Key Laboratory of Optoelectronic Materials and Technologies, Guangdong Province Key Laboratory of Display Material and Technology, School of Electronics and Information Technology, Sun Yat-Sen University, Guangzhou, 510006, China
- The First Affiliated Hospital of Sun Yat-Sen University, Sun Yat-Sen University, Guangzhou, 510006, China
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2
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Sacks DB, Arnold M, Bakris GL, Bruns DE, Horvath AR, Lernmark Å, Metzger BE, Nathan DM, Kirkman MS. Guidelines and Recommendations for Laboratory Analysis in the Diagnosis and Management of Diabetes Mellitus. Diabetes Care 2023; 46:e151-e199. [PMID: 37471273 PMCID: PMC10516260 DOI: 10.2337/dci23-0036] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/19/2023] [Accepted: 05/11/2023] [Indexed: 07/22/2023]
Abstract
BACKGROUND Numerous laboratory tests are used in the diagnosis and management of diabetes mellitus. The quality of the scientific evidence supporting the use of these assays varies substantially. APPROACH An expert committee compiled evidence-based recommendations for laboratory analysis in screening, diagnosis, or monitoring of diabetes. The overall quality of the evidence and the strength of the recommendations were evaluated. The draft consensus recommendations were evaluated by invited reviewers and presented for public comment. Suggestions were incorporated as deemed appropriate by the authors (see Acknowledgments). The guidelines were reviewed by the Evidence Based Laboratory Medicine Committee and the Board of Directors of the American Association for Clinical Chemistry and by the Professional Practice Committee of the American Diabetes Association. CONTENT Diabetes can be diagnosed by demonstrating increased concentrations of glucose in venous plasma or increased hemoglobin A1c (HbA1c) in the blood. Glycemic control is monitored by the people with diabetes measuring their own blood glucose with meters and/or with continuous interstitial glucose monitoring (CGM) devices and also by laboratory analysis of HbA1c. The potential roles of noninvasive glucose monitoring, genetic testing, and measurement of ketones, autoantibodies, urine albumin, insulin, proinsulin, and C-peptide are addressed. SUMMARY The guidelines provide specific recommendations based on published data or derived from expert consensus. Several analytes are found to have minimal clinical value at the present time, and measurement of them is not recommended.
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Affiliation(s)
- David B. Sacks
- Department of Laboratory Medicine, National Institutes of Health, Bethesda, MD
| | - Mark Arnold
- Department of Chemistry, University of Iowa, Iowa City, IA
| | - George L. Bakris
- Department of Medicine, American Heart Association Comprehensive Hypertension Center, Section of Endocrinology, Diabetes and Metabolism, University of Chicago Medicine, Chicago, IL
| | - David E. Bruns
- Department of Pathology, University of Virginia Medical School, Charlottesville, VA
| | - Andrea R. Horvath
- New South Wales Health Pathology Department of Chemical Pathology, Prince of Wales Hospital, Sydney, New South Wales, Australia
| | - Åke Lernmark
- Department of Clinical Sciences, Lund University/CRC, Skane University Hospital Malmö, Malmö, Sweden
| | - Boyd E. Metzger
- Division of Endocrinology, Northwestern University, The Feinberg School of Medicine, Chicago, IL
| | - David M. Nathan
- Massachusetts General Hospital Diabetes Center and Harvard Medical School, Boston, MA
| | - M. Sue Kirkman
- Department of Medicine, University of North Carolina, Chapel Hill, NC
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3
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Sacks DB, Arnold M, Bakris GL, Bruns DE, Horvath AR, Lernmark Å, Metzger BE, Nathan DM, Kirkman MS. Guidelines and Recommendations for Laboratory Analysis in the Diagnosis and Management of Diabetes Mellitus. Clin Chem 2023:hvad080. [PMID: 37473453 DOI: 10.1093/clinchem/hvad080] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2023] [Accepted: 05/12/2023] [Indexed: 07/22/2023]
Abstract
BACKGROUND Numerous laboratory tests are used in the diagnosis and management of diabetes mellitus. The quality of the scientific evidence supporting the use of these assays varies substantially. APPROACH An expert committee compiled evidence-based recommendations for laboratory analysis in screening, diagnosis, or monitoring of diabetes. The overall quality of the evidence and the strength of the recommendations were evaluated. The draft consensus recommendations were evaluated by invited reviewers and presented for public comment. Suggestions were incorporated as deemed appropriate by the authors (see Acknowledgments). The guidelines were reviewed by the Evidence Based Laboratory Medicine Committee and the Board of Directors of the American Association of Clinical Chemistry and by the Professional Practice Committee of the American Diabetes Association. CONTENT Diabetes can be diagnosed by demonstrating increased concentrations of glucose in venous plasma or increased hemoglobin A1c (Hb A1c) in the blood. Glycemic control is monitored by the people with diabetes measuring their own blood glucose with meters and/or with continuous interstitial glucose monitoring (CGM) devices and also by laboratory analysis of Hb A1c. The potential roles of noninvasive glucose monitoring, genetic testing, and measurement of ketones, autoantibodies, urine albumin, insulin, proinsulin, and C-peptide are addressed. SUMMARY The guidelines provide specific recommendations based on published data or derived from expert consensus. Several analytes are found to have minimal clinical value at the present time, and measurement of them is not recommended.
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Affiliation(s)
- David B Sacks
- Department of Laboratory Medicine, National Institutes of Health, Bethesda, MD, United States
| | - Mark Arnold
- Department of Chemistry, University of Iowa, Iowa City, IA, United States
| | - George L Bakris
- Department of Medicine, American Heart Association Comprehensive Hypertension Center, Section of Endocrinology, Diabetes and Metabolism, University of Chicago Medicine, Chicago, ILUnited States
| | - David E Bruns
- Department of Pathology, University of Virginia Medical School, Charlottesville, VA, United States
| | - Andrea R Horvath
- New South Wales Health Pathology Department of Chemical Pathology, Prince of Wales Hospital, Sydney, NSW, Australia
| | - Åke Lernmark
- Department of Clinical Sciences, Lund University/CRC, Skane University Hospital Malmö, Malmö, Sweden
| | - Boyd E Metzger
- Division of Endocrinology, Northwestern University, The Feinberg School of Medicine, Chicago, IL, United States
| | - David M Nathan
- Massachusetts General Hospital Diabetes Center and Harvard Medical School, Boston, MA, United States
| | - M Sue Kirkman
- Department of Medicine, University of North Carolina, Chapel Hill, NC, United States
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4
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Yang L, Zhang Z, Wei X, Yang Y. Glucose diagnosis system combining machine learning and NIR photoacoustic multispectral using a low power CW laser. BIOMEDICAL OPTICS EXPRESS 2023; 14:1685-1702. [PMID: 37078043 PMCID: PMC10110296 DOI: 10.1364/boe.485296] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/12/2023] [Revised: 03/16/2023] [Accepted: 03/19/2023] [Indexed: 05/03/2023]
Abstract
Non-invasive, portable, economical, dynamic blood glucose monitoring device has become a functional requirement for diabetes in his regulating entire life. In a photoacoustic (PA) multispectral near-infrared diagnosis system, the glucose in aqueous solutions was excited by low power (order of milliwatts) CW laser whose wavelengths were from 1500 to 1630 nm. The glucose in aqueous solutions to be analyzed was contained within the photoacoustic cell (PAC). The PA multispectral signals were measured using a piezoelectric detector, and then the voltage signals from the piezoelectric detector were amplified with a precision Lock-in Amplifier (MFLI500K). The continuously tunable lasers were used to verify the various influencing factors of the PA signal, and the PA spectrum of the glucose solution was examined. Subsequently, six wavelengths with high power were selected at approximately equal intervals from 1500 to 1630 nm, and the gaussian process regression of the quadratic rational kernel was used to collect data through these wavelengths to predict the glucose concentration. The experimental results showed that the near-infrared PA multispectral diagnosis system could be engineered for the prediction of the glucose level (more than 92%, zone A of Clarke Error Grid). Subsequently, the model trained with glucose solution was used to predict serum glucose. With the increase of serum glucose content, the prediction results of the model also showed a high linear relationship, indicating that the photoacoustic method was sensitive to the detection of glucose concentration changes. The results of our study have the potential to not only better develop the PA blood glucose meter but also extend the viability into the detection of otherwise blood components.
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Affiliation(s)
- Lifeng Yang
- School of Optoelectronic Science and
Engineering, University of Electronic Science and
Technology of China, Chengdu 610054, China
| | - Zhaojiang Zhang
- School of Optoelectronic Science and
Engineering, University of Electronic Science and
Technology of China, Chengdu 610054, China
| | - Xin Wei
- School of Optoelectronic Science and
Engineering, University of Electronic Science and
Technology of China, Chengdu 610054, China
| | - Yan Yang
- Department of Endocrinology &
Metabolism, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu 610072, China
- Chinese Academy of Sciences
Sichuan Translational Medicine Research Hospital,
Chengdu 610072, China
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Choi W, Park B, Choi S, Oh D, Kim J, Kim C. Recent Advances in Contrast-Enhanced Photoacoustic Imaging: Overcoming the Physical and Practical Challenges. Chem Rev 2023. [PMID: 36642892 DOI: 10.1021/acs.chemrev.2c00627] [Citation(s) in RCA: 24] [Impact Index Per Article: 24.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/17/2023]
Abstract
For decades now, photoacoustic imaging (PAI) has been investigated to realize its potential as a niche biomedical imaging modality. Despite its highly desirable optical contrast and ultrasonic spatiotemporal resolution, PAI is challenged by such physical limitations as a low signal-to-noise ratio (SNR), diminished image contrast due to strong optical attenuation, and a lower-bound on spatial resolution in deep tissue. In addition, contrast-enhanced PAI has faced practical limitations such as insufficient cell-specific targeting due to low delivery efficiency and difficulties in developing clinically translatable agents. Identifying these limitations is essential to the continuing expansion of the field, and substantial advances in developing contrast-enhancing agents, complemented by high-performance image acquisition systems, have synergistically dealt with the challenges of conventional PAI. This review covers the past four years of research on pushing the physical and practical challenges of PAI in terms of SNR/contrast, spatial resolution, targeted delivery, and clinical application. Promising strategies for dealing with each challenge are reviewed in detail, and future research directions for next generation contrast-enhanced PAI are discussed.
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Affiliation(s)
- Wonseok Choi
- Department of Electrical Engineering, Convergence IT Engineering, Mechanical Engineering, and Medical Science and Engineering, Graduate School of Artificial Intelligence, and Medical Device Innovation Center, Pohang University of Science and Technology, 77 Cheongam-Ro, Nam-Gu, Pohang37673, Republic of Korea
| | - Byullee Park
- Department of Electrical Engineering, Convergence IT Engineering, Mechanical Engineering, and Medical Science and Engineering, Graduate School of Artificial Intelligence, and Medical Device Innovation Center, Pohang University of Science and Technology, 77 Cheongam-Ro, Nam-Gu, Pohang37673, Republic of Korea
| | - Seongwook Choi
- Department of Electrical Engineering, Convergence IT Engineering, Mechanical Engineering, and Medical Science and Engineering, Graduate School of Artificial Intelligence, and Medical Device Innovation Center, Pohang University of Science and Technology, 77 Cheongam-Ro, Nam-Gu, Pohang37673, Republic of Korea
| | - Donghyeon Oh
- Department of Electrical Engineering, Convergence IT Engineering, Mechanical Engineering, and Medical Science and Engineering, Graduate School of Artificial Intelligence, and Medical Device Innovation Center, Pohang University of Science and Technology, 77 Cheongam-Ro, Nam-Gu, Pohang37673, Republic of Korea
| | - Jongbeom Kim
- Department of Electrical Engineering, Convergence IT Engineering, Mechanical Engineering, and Medical Science and Engineering, Graduate School of Artificial Intelligence, and Medical Device Innovation Center, Pohang University of Science and Technology, 77 Cheongam-Ro, Nam-Gu, Pohang37673, Republic of Korea
| | - Chulhong Kim
- Department of Electrical Engineering, Convergence IT Engineering, Mechanical Engineering, and Medical Science and Engineering, Graduate School of Artificial Intelligence, and Medical Device Innovation Center, Pohang University of Science and Technology, 77 Cheongam-Ro, Nam-Gu, Pohang37673, Republic of Korea
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Glucose Determination by a Single 1535 nm Pulsed Photoacoustic Technique: A Multiple Calibration for the External Factors. JOURNAL OF HEALTHCARE ENGINEERING 2022; 2022:9593843. [PMID: 36247088 PMCID: PMC9553719 DOI: 10.1155/2022/9593843] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/04/2022] [Accepted: 08/16/2022] [Indexed: 11/17/2022]
Abstract
Photoacoustic spectroscopy has been proved to be a potential method for noninvasive blood glucose detection. We used 1535 nm pulsed laser to excite photoacoustic signal in glucose solution and then explored the influence of different glucose concentration on photoacoustic signal to analyze the sensitivity of photoacoustic signal to glucose at this wavelength. We designed a simple photoacoustic cell structure, which used a focused ultrasonic transducer to receive signals, so as to reduce signal attenuation. In terms of the results, we have found that for high-concentration glucose solutions, the results have strong linearity and discrimination, and when the concentration is close to the human body level, the signal difference is not so obvious. Therefore, we explore the external factors affecting the photoacoustic signal in detail and propose a calibration method. Through calibration, the signal generated by the low-concentration glucose solution also has a good linearity.
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Jeon HJ, Kim HS, Chung E, Lee DY. Nanozyme-based colorimetric biosensor with a systemic quantification algorithm for noninvasive glucose monitoring. Theranostics 2022; 12:6308-6338. [PMID: 36168630 PMCID: PMC9475463 DOI: 10.7150/thno.72152] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2022] [Accepted: 08/20/2022] [Indexed: 11/10/2022] Open
Abstract
Diabetes mellitus accompanies an abnormally high glucose level in the bloodstream. Early diagnosis and proper glycemic management of blood glucose are essential to prevent further progression and complications. Biosensor-based colorimetric detection has progressed and shown potential in portable and inexpensive daily assessment of glucose levels because of its simplicity, low-cost, and convenient operation without sophisticated instrumentation. Colorimetric glucose biosensors commonly use natural enzymes that recognize glucose and chromophores that detect enzymatic reaction products. However, many natural enzymes have inherent defects, limiting their extensive application. Recently, nanozyme-based colorimetric detection has drawn attention due to its merits including high sensitivity, stability under strict reaction conditions, flexible structural design with low-cost materials, and adjustable catalytic activities. This review discusses various nanozyme materials, colorimetric analytic methods and mechanisms, recent machine learning based analytic methods, quantification systems, applications and future directions for monitoring and managing diabetes.
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Affiliation(s)
- Hee-Jae Jeon
- Weldon School of Biomedical Engineering, Purdue University, Indiana 47906, USA
- Department of Mechanical and Biomedical Engineering, Kangwon National University, Chuncheon 24341, Republic of Korea
| | - Hyung Shik Kim
- Department of Bioengineering, College of Engineering, and BK FOUR Biopharmaceutical Innovation Leader for Education and Research Group, Hanyang University, Seoul 04763, Republic of Korea
| | - Euiheon Chung
- Department of Biomedical Science and Engineering, Gwangju Institute of Science and Technology (GIST), Gwangju 61005, Republic of Korea
- AI Graduate School, GIST, Gwangju 61005, Republic of Korea
- Research Center for Photon Science Technology, GIST, Gwangju 61005, Republic of Korea
| | - Dong Yun Lee
- Department of Bioengineering, College of Engineering, and BK FOUR Biopharmaceutical Innovation Leader for Education and Research Group, Hanyang University, Seoul 04763, Republic of Korea
- Institute of Nano Science and Technology (INST), Hanyang University, Seoul 04763, Republic of Korea
- Institute for Bioengineering and Biopharmaceutical Research (IBBR), Hanyang University, Seoul 04763, Republic of Korea
- Elixir Pharmatech Inc., Seoul 07463, Republic of Korea
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8
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Zhai X, Cao Y, Sun W, Cao S, Wang Y, He L, Yao N, Zhao D. Core-shell composite N-doped-Co-MOF@polydopamine decorated with Ag nanoparticles for nonenzymatic glucose sensors. J Electroanal Chem (Lausanne) 2022. [DOI: 10.1016/j.jelechem.2022.116491] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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9
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Cheng W, Zhang X, Duan N, Jiang L, Xu Y, Chen Y, Liu Y, Fan P. Direct-determination of high-concentration sulfate by serial differential spectrophotometry with multiple optical pathlengths. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 811:152121. [PMID: 34871678 DOI: 10.1016/j.scitotenv.2021.152121] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/22/2021] [Revised: 11/17/2021] [Accepted: 11/28/2021] [Indexed: 06/13/2023]
Abstract
Direct-determination is a fast and free of contamination method for analysis of substances in water samples. However, direct-determination of SO42- with high concentration in environmental systems is still challenging due to deviation from Beer-Lambert law is generally observed when a substance with high concentration is directly determined, resulting in poor accuracy, sensitivity, and narrow linear range. In this study, a simple and rapid method for the direct-determination of SO42- with high concentration was proposed. Serial high-absorbance differential spectrophotometry was applied to incrementally widen the determination range under different optical pathlengths. In this process, the effects of optical pathlength and reference concentration on sensitivity were further investigated. The results showed that SO42- could be accurately quantified within a concentration range of 0-4.10 g/L, and the determination range by this method was 10-fold and 19.5-fold wider than those by conventional differential spectrophotometry and conventional spectrophotometry, respectively. And the applicable ranges of sensitivity were obtained at various optical pathlengths by adjusting the reference solution concentration. This approach exhibited several advantages over conventional methods, including high accuracy, excellent precision, low cost, less time consumption, and easy operation. This method is promising and can provide accurate and reliable data support for environmental monitoring and pollution control.
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Affiliation(s)
- Wen Cheng
- State Key Laboratory of Pollution Control and Resources Reuse, College of Environmental Science and Engineering, Tongji University, Shanghai 200092, China
| | - Xuefei Zhang
- School of Materials Science and Engineering, Anhui University of Science & Technology, Huainan, Anhui 232001, China
| | - Ning Duan
- State Key Laboratory of Pollution Control and Resources Reuse, College of Environmental Science and Engineering, Tongji University, Shanghai 200092, China; School of Materials Science and Engineering, Anhui University of Science & Technology, Huainan, Anhui 232001, China.
| | - Linhua Jiang
- State Key Laboratory of Pollution Control and Resources Reuse, College of Environmental Science and Engineering, Tongji University, Shanghai 200092, China; School of Materials Science and Engineering, Anhui University of Science & Technology, Huainan, Anhui 232001, China.
| | - Yanli Xu
- State Key Laboratory of Pollution Control and Resources Reuse, College of Environmental Science and Engineering, Tongji University, Shanghai 200092, China
| | - Ying Chen
- State Key Laboratory of Pollution Control and Resources Reuse, College of Environmental Science and Engineering, Tongji University, Shanghai 200092, China
| | - Yong Liu
- School of Materials Science and Engineering, Anhui University of Science & Technology, Huainan, Anhui 232001, China
| | - Peng Fan
- State Key Laboratory of Pollution Control and Resources Reuse, College of Environmental Science and Engineering, Tongji University, Shanghai 200092, China
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10
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Pullano SA, Greco M, Bianco MG, Foti D, Brunetti A, Fiorillo AS. Glucose biosensors in clinical practice: principles, limits and perspectives of currently used devices. Am J Cancer Res 2022; 12:493-511. [PMID: 34976197 PMCID: PMC8692922 DOI: 10.7150/thno.64035] [Citation(s) in RCA: 26] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2021] [Accepted: 10/31/2021] [Indexed: 12/13/2022] Open
Abstract
The demand of glucose monitoring devices and even of updated guidelines for the management of diabetic patients is dramatically increasing due to the progressive rise in the prevalence of diabetes mellitus and the need to prevent its complications. Even though the introduction of the first glucose sensor occurred decades ago, important advances both from the technological and clinical point of view have contributed to a substantial improvement in quality healthcare. This review aims to bring together purely technological and clinical aspects of interest in the field of glucose devices by proposing a roadmap in glucose monitoring and management of patients with diabetes. Also, it prospects other biological fluids to be examined as further options in diabetes care, and suggests, throughout the technology innovation process, future directions to improve the follow-up, treatment, and clinical outcomes of patients.
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11
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Long H, Chen B, Li W, Xian Y, Peng Z. Blood glucose detection based on Teager-Kaiser main energy of photoacoustic signal. Comput Biol Med 2021; 134:104552. [PMID: 34144363 DOI: 10.1016/j.compbiomed.2021.104552] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2020] [Revised: 06/02/2021] [Accepted: 06/02/2021] [Indexed: 11/27/2022]
Abstract
Real-time blood glucose detection is an essential tool for diabetes monitoring. Non-invasive blood glucose detection technology is one of the current research hotspots in this field. Previous research mainly focused on improving the system's detection capability to obtain signals with low signal-to-noise ratio and high quality, and simple methods are often used in signal processing. Moreover, photoacoustic signal simulation also simplifies the influence of the transmission medium on the signal. In the present study, we built a new simulation model which considers human skin, blood, and the detector's limitations, to obtain a more practical photoacoustic signal. We then proposed a blood glucose detection algorithm based on Teager-Kaiser main energy (TKME) to overcome noise and medium interference and achieve a high detection accuracy at low SNR. Finally, the simulation and actual data were utilised during the experiment, and the detection error was 15 mg/dL (SNR = 10 dB).
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Affiliation(s)
- Hongfeng Long
- School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, 610054, China; Laboratory of Imaging Detection and Intelligent Perception University of Electronic Science and Technology of China, 610054, Chengdu, China
| | - Bingzhang Chen
- School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, 610054, China; Laboratory of Imaging Detection and Intelligent Perception University of Electronic Science and Technology of China, 610054, Chengdu, China.
| | - Wei Li
- School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, 610054, China; Laboratory of Imaging Detection and Intelligent Perception University of Electronic Science and Technology of China, 610054, Chengdu, China
| | - Yongli Xian
- School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, 610054, China; School of Electronic Engineering and Electronic Information, Xihua University, Chengdu, 610039, China
| | - Zhenming Peng
- School of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, 610054, China; Laboratory of Imaging Detection and Intelligent Perception University of Electronic Science and Technology of China, 610054, Chengdu, China.
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Roberts S, Khera E, Choi C, Navaratna T, Grimm J, Thurber GM, Reiner T. Optoacoustic Imaging of Glucagon-like Peptide-1 Receptor with a Near-Infrared Exendin-4 Analog. J Nucl Med 2021; 62:839-848. [PMID: 33097631 PMCID: PMC8729860 DOI: 10.2967/jnumed.120.252262] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2020] [Accepted: 09/18/2020] [Indexed: 11/16/2022] Open
Abstract
Limitations in current imaging tools have long challenged the imaging of small pancreatic islets in animal models. Here, we report the first development and in vivo validation testing of a broad-spectrum and high-absorbance near-infrared optoacoustic contrast agent, E4x12-Cy7. Our near-infrared tracer is based on the amino acid sequence of exendin-4 and targets the glucagon-like peptide-1 receptor (GLP-1R). Cell assays confirmed that E4x12-Cy7 has a high-binding affinity (dissociation constant, Kd, 4.6 ± 0.8 nM). Using the multispectral optoacoustic tomography, we imaged E4x12-Cy7 and optoacoustically visualized β-cell insulinoma xenografts in vivo for the first time. In the future, similar optoacoustic tracers that are specific for β-cells and combines optoacoustic and fluorescence imaging modalities could prove to be important tools for monitoring the pancreas for the progression of diabetes.
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Affiliation(s)
- Sheryl Roberts
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Eshita Khera
- Department of Chemical Engineering, University of Michigan, Ann Arbor, Michigan
| | - Crystal Choi
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Tejas Navaratna
- Department of Chemical Engineering, University of Michigan, Ann Arbor, Michigan
| | - Jan Grimm
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, New York
- Program of Molecular Pharmacology, Memorial Sloan Kettering Cancer Center, New York, New York
- Department of Radiology, Weill Cornell Medical College, New York, New York
- Pharmacology Program, Weill Cornell Medical College, New York, New York
| | - Greg M Thurber
- Department of Chemical Engineering, University of Michigan, Ann Arbor, Michigan
- Department of Biomedical Engineering, University of Michigan, Ann Arbor, Michigan; and
| | - Thomas Reiner
- Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, New York
- Department of Radiology, Weill Cornell Medical College, New York, New York
- Chemical Biology Program, Memorial Sloan Kettering Cancer Center, New York, New York
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13
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A colorimetric and ratiometric glucose sensor based on conformational switch of i-motif DNA. TALANTA OPEN 2020. [DOI: 10.1016/j.talo.2020.100001] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
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Zhang R, Liu S, Jin H, Luo Y, Zheng Z, Gao F, Zheng Y. Noninvasive Electromagnetic Wave Sensing of Glucose. SENSORS (BASEL, SWITZERLAND) 2019; 19:E1151. [PMID: 30866459 PMCID: PMC6427587 DOI: 10.3390/s19051151] [Citation(s) in RCA: 32] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/08/2019] [Revised: 02/01/2019] [Accepted: 02/10/2019] [Indexed: 01/10/2023]
Abstract
Diabetic patients need long-term and frequent glucose monitoring to assist in insulin intake. The current finger-prick devices are painful and costly, which places noninvasive glucose sensors in high demand. In this review paper, we list several advanced electromagnetic (EM)-wave-based technologies for noninvasive glucose measurement, including infrared (IR) spectroscopy, photoacoustic (PA) spectroscopy, Raman spectroscopy, fluorescence, optical coherence tomography (OCT), Terahertz (THz) spectroscopy, and microwave sensing. The development of each method is discussed regarding the fundamental principle, system setup, and experimental results. Despite the promising achievements that have been previously reported, no established product has obtained FDA approval or survived a marketing test. The limitations of, and prospects for, these techniques are presented at the end of this review.
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Affiliation(s)
- Ruochong Zhang
- School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore 639798, Singapore.
| | - Siyu Liu
- School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore 639798, Singapore.
| | - Haoran Jin
- School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore 639798, Singapore.
| | - Yunqi Luo
- School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore 639798, Singapore.
| | - Zesheng Zheng
- School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore 639798, Singapore.
| | - Fei Gao
- School of Information Science and Technology, ShanghaiTech University, Shanghai 201210, China.
| | - Yuanjin Zheng
- School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore 639798, Singapore.
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