1
|
Raj P, Wu L, Arora S, Bhatt R, Zuo Y, Fang Z, Verdoold R, Koch T, Gu L, Barman I. Engineering vascularized skin-mimetic phantom for non-invasive Raman spectroscopy. SENSORS AND ACTUATORS. B, CHEMICAL 2024; 404:135240. [PMID: 38524639 PMCID: PMC10956615 DOI: 10.1016/j.snb.2023.135240] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/26/2024]
Abstract
Recent advances in Raman spectroscopy have shown great potential for non-invasive analyte sensing, but the lack of a standardized optical phantom for these measurements has hindered further progress. While many research groups have developed optical phantoms that mimic bulk optical absorption and scattering, these materials typically have strong Raman scattering, making it difficult to distinguish metabolite signals. As a result, solid tissue phantoms for spectroscopy have been limited to highly scattering tissues such as bones and calcifications, and metabolite sensing has been primarily performed using liquid tissue phantoms. To address this issue, we have developed a layered skin-mimetic phantom that can support metabolite sensing through Raman spectroscopy. Our approach incorporates millifluidic vasculature that mimics blood vessels to allow for diffusion akin to metabolite diffusion in the skin. Furthermore, our skin phantoms are mechanically mimetic, providing an ideal model for development of minimally invasive optical techniques. By providing a standardized platform for measuring metabolites, our approach has the potential to facilitate critical developments in spectroscopic techniques and improve our understanding of metabolite dynamics in vivo.
Collapse
Affiliation(s)
- Piyush Raj
- Department of Mechanical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA
| | - Lintong Wu
- Department of Mechanical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA
| | - Saransh Arora
- Department of Mechanical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA
| | - Raj Bhatt
- Department of Biology, Johns Hopkins University, Baltimore, MD 21218, USA
| | - Yi Zuo
- Department of Materials Science and Engineering, Institute for NanoBioTechnology, Johns Hopkins University, Baltimore, MD 21218, USA
| | - Zhiwei Fang
- Department of Materials Science and Engineering, Institute for NanoBioTechnology, Johns Hopkins University, Baltimore, MD 21218, USA
| | | | - Tanja Koch
- ams OSRAM Innovation and Engineering, Germany
| | - Luo Gu
- Department of Materials Science and Engineering, Institute for NanoBioTechnology, Johns Hopkins University, Baltimore, MD 21218, USA
| | - Ishan Barman
- Department of Mechanical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA
- Department of Oncology, Johns Hopkins University School of Medicine, Baltimore, MD 21218, USA
- Department of Radiology & Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD 21218, USA
| |
Collapse
|
2
|
Tian T, Aaron RE, DuNova AY, Jendle JH, Kerr D, Cengiz E, Drincic A, Pickup JC, Chen KY, Schwartz N, Muchmore DB, Akturk HK, Levy CJ, Schmidt S, Bellazzi R, Wu AHB, Spanakis EK, Najafi B, Chase JG, Seley JJ, Klonoff DC. Diabetes Technology Meeting 2023. J Diabetes Sci Technol 2024:19322968241235205. [PMID: 38528741 DOI: 10.1177/19322968241235205] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 03/27/2024]
Abstract
Diabetes Technology Society hosted its annual Diabetes Technology Meeting from November 1 to November 4, 2023. Meeting topics included digital health; metrics of glycemia; the integration of glucose and insulin data into the electronic health record; technologies for insulin pumps, blood glucose monitors, and continuous glucose monitors; diabetes drugs and analytes; skin physiology; regulation of diabetes devices and drugs; and data science, artificial intelligence, and machine learning. A live demonstration of a personalized carbohydrate dispenser for people with diabetes was presented.
Collapse
Affiliation(s)
- Tiffany Tian
- Diabetes Technology Society, Burlingame, CA, USA
| | | | | | - Johan H Jendle
- School of Medicine and Health, Institute of Medical Sciences, Örebro University, Örebro, Sweden
| | | | - Eda Cengiz
- School of Medicine, University of California, San Francisco, San Francisco, CA, USA
| | | | - John C Pickup
- King's College London School of Medicine, London, UK
| | - Kong Y Chen
- National Institute of Diabetes and Digestive and Kidney Diseases, Bethesda, MD, USA
| | | | | | - Halis K Akturk
- Barbara Davis Center for Diabetes, University of Colorado, Aurora, CO, USA
| | - Carol J Levy
- Division of Endocrinology, Diabetes, and Metabolism, Icahn School of Medicine at Mount Sinai, New York City, NY, USA
| | | | | | - Alan H B Wu
- University of California, San Francisco, San Francisco, CA, USA
| | - Elias K Spanakis
- Baltimore VA Medical Center and School of Medicine, University of Maryland, Baltimore, MD, USA
| | | | | | - Jane Jeffrie Seley
- Division of Endocrinology, Diabetes & Metabolism, Weill Cornell Medicine, New York City, NY, USA
| | - David C Klonoff
- Diabetes Research Institute, Mills-Peninsula Medical Center, San Mateo, CA, USA
| |
Collapse
|
3
|
Mittal R, Koutras N, Maya J, Lemos JRN, Hirani K. Blood glucose monitoring devices for type 1 diabetes: a journey from the food and drug administration approval to market availability. Front Endocrinol (Lausanne) 2024; 15:1352302. [PMID: 38559693 PMCID: PMC10978642 DOI: 10.3389/fendo.2024.1352302] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/07/2023] [Accepted: 02/22/2024] [Indexed: 04/04/2024] Open
Abstract
Blood glucose monitoring constitutes a pivotal element in the clinical management of Type 1 diabetes (T1D), a globally escalating metabolic disorder. Continuous glucose monitoring (CGM) devices have demonstrated efficacy in optimizing glycemic control, mitigating adverse health outcomes, and augmenting the overall quality of life for individuals afflicted with T1D. Recent progress in the field encompasses the refinement of electrochemical sensors, which enhances the effectiveness of blood glucose monitoring. This progress empowers patients to assume greater control over their health, alleviating the burdens associated with their condition, and contributing to the overall alleviation of the healthcare system. The introduction of novel medical devices, whether derived from existing prototypes or originating as innovative creations, necessitates adherence to a rigorous approval process regulated by the Food and Drug Administration (FDA). Diverse device classifications, stratified by their associated risks, dictate distinct approval pathways, each characterized by varying timelines. This review underscores recent advancements in blood glucose monitoring devices primarily based on electrochemical sensors and elucidates their regulatory journey towards FDA approval. The advent of innovative, non-invasive blood glucose monitoring devices holds promise for maintaining stringent glycemic control, thereby preventing T1D-associated comorbidities, and extending the life expectancy of affected individuals.
Collapse
Affiliation(s)
- Rahul Mittal
- Diabetes Research Institute, University of Miami Miller School of Medicine, Miami, FL, United States
| | - Nicole Koutras
- Herbert Wertheim College of Medicine, Florida International University, Miami, FL, United States
| | - Jonathan Maya
- Herbert Wertheim College of Medicine, Florida International University, Miami, FL, United States
| | - Joana R. N. Lemos
- Diabetes Research Institute, University of Miami Miller School of Medicine, Miami, FL, United States
| | - Khemraj Hirani
- Diabetes Research Institute, University of Miami Miller School of Medicine, Miami, FL, United States
| |
Collapse
|
4
|
Nakazawa T, Sekine R, Kitabayashi M, Hashimoto Y, Ienaka A, Morishita K, Fujii T, Ito M, Matsushita F. Non-invasive blood glucose estimation method based on the phase delay between oxy- and deoxyhemoglobin using visible and near-infrared spectroscopy. JOURNAL OF BIOMEDICAL OPTICS 2024; 29:037001. [PMID: 38444669 PMCID: PMC10913690 DOI: 10.1117/1.jbo.29.3.037001] [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: 12/08/2023] [Revised: 01/22/2024] [Accepted: 02/05/2024] [Indexed: 03/07/2024]
Abstract
Significance Many researchers have attempted to estimate blood glucose levels (BGLs) noninvasively using near-infrared (NIR) spectroscopy. However, the optical absorption change induced by blood glucose is weak in the NIR region and often masked by interference from other components such as water and hemoglobin. Aim Instead of using direct optical absorption by glucose, this study proposes an index calculated from oxy- and deoxyhemoglobin signals that shows a good correlation with BGLs while using conventional visible and NIR spectroscopy. Approach The metabolic index, which is based on tissue oxygen consumption, was derived through analytical methods and further verified and reproduced in a series of glucose challenge experiments. Blood glucose estimation units were prototyped by utilizing commercially available smart devices. Results Our experimental results showed that the phase delay between the oxy- and deoxyhemoglobin signals in near-infrared spectroscopy correlates with BGL measured by a conventional continuous glucose monitor. The proposed method was also confirmed to work well with visible spectroscopy systems based on smartphone cameras. The proposed method also demonstrated excellent repeatability in results from a total of 19 oral challenge tests. Conclusions This study demonstrated the feasibility of non-invasive glucose monitoring using existing photoplethysmography sensors for pulse oximeters and smartwatches. Evaluating the proposed method in diabetic or unhealthy individuals may serve to further increase its practicality.
Collapse
Affiliation(s)
| | - Rui Sekine
- Hamamatsu Photonics K.K., Hamamatsu, Japan
| | | | | | | | | | | | - Masaki Ito
- Hamamatsu Photonics K.K., Hamamatsu, Japan
| | | |
Collapse
|
5
|
Sahoo N, Sun B, Tan Y, Zhou K, Zhang L. A Novel Biosensor for the Detection of Glucose Concentration Using the Dual-Peak Long Period Grating in the Near- to Mid-Infrared. SENSORS (BASEL, SWITZERLAND) 2024; 24:1247. [PMID: 38400404 PMCID: PMC10892875 DOI: 10.3390/s24041247] [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: 12/17/2023] [Revised: 02/02/2024] [Accepted: 02/09/2024] [Indexed: 02/25/2024]
Abstract
In this article, we demonstrate an improved efficient fibre sensor with a high sensitivity to measure glucose concentrations in the physiological range of human beings, operating in a broad spectral bandwidth from the near- to mid-infrared. The sensor consists of a dual-peak long period grating (DPLPG) with a period of 150 μm inscribed in an optical fibre with a diameter of 80 μm. The investigation of sensing for refractive index results in a sensitivity of ~-885.7 nm/refractive index unit (RIU) and ~2008.6 nm/RIU in the range of 1.30-1.44. The glucose measurement is achieved by the immobilisation of a layer of enzyme of glucose oxidase (GOD) onto the fibre surface for the selective enhancement of sensitivity for glucose. The sensor can measure glucose concentrations with a maximum sensitivity of -36.25 nm/(mg/mL) in the range of 0.1-3.0 mg/mL. To the best of our knowledge, this is the highest sensitivity ever achieved for a measurement of glucose with a long period grating-based sensor, indicating its potential for many applications including pharmaceutical, biomedical and food industries.
Collapse
Affiliation(s)
- Namita Sahoo
- Aston Institute of Photonic Technologies, Aston University, Birmingham B4 7ET, UK; (K.Z.); (L.Z.)
| | - Bing Sun
- College of Electronic and Optical Engineering, Nanjing University of Posts and Telecommunications, Nanjing 210003, China;
| | - Yidong Tan
- Department of Precision Instrument, Tsinghua University, Beijing 100084, China;
| | - Kaiming Zhou
- Aston Institute of Photonic Technologies, Aston University, Birmingham B4 7ET, UK; (K.Z.); (L.Z.)
| | - Lin Zhang
- Aston Institute of Photonic Technologies, Aston University, Birmingham B4 7ET, UK; (K.Z.); (L.Z.)
| |
Collapse
|
6
|
Naseska M, Globočnik A, Davies S, Yetisen AK, Humar M. Non-contact monitoring of glucose concentration and pH by integration of wearable and implantable hydrogel sensors with optical coherence tomography. OPTICS EXPRESS 2024; 32:92-103. [PMID: 38175065 DOI: 10.1364/oe.506780] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/02/2023] [Accepted: 12/06/2023] [Indexed: 01/05/2024]
Abstract
Optical coherence tomography (OCT) is a noninvasive imaging technique with large penetration depth into the tissue, but limited chemical specificity. By incorporating functional co-monomers, hydrogels can be designed to respond to specific molecules and undergo reversible volume changes. In this study, we present implantable and wearable biocompatible hydrogel sensors combined with OCT to monitor their thickness change as a tool for continuous and real-time monitoring of glucose concentration and pH. The results demonstrate the potential of combining hydrogel biosensors with OCT for non-contact continuous in-vivo monitoring of physiological parameters.
Collapse
|
7
|
Song S, Wang Q, Zou X, Li Z, Ma Z, Jiang D, Fu Y, Liu Q. High-precision prediction of blood glucose concentration utilizing Fourier transform Raman spectroscopy and an ensemble machine learning algorithm. SPECTROCHIMICA ACTA. PART A, MOLECULAR AND BIOMOLECULAR SPECTROSCOPY 2023; 303:123176. [PMID: 37494812 DOI: 10.1016/j.saa.2023.123176] [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: 07/03/2023] [Revised: 07/17/2023] [Accepted: 07/19/2023] [Indexed: 07/28/2023]
Abstract
Raman spectroscopy has gained popularity in analyzing blood glucose levels due to its non-invasive identification and minimal interference from water. However, the challenge lies in how to accurately predict blood glucose concentrations in human blood using Raman spectroscopy. This paper researches a novel integrated machine learning algorithm called Bagging-ABC-ELM. The optimal input weights and biases of extreme learning machine (ELM) model are obtained by artificial bee colony (ABC) algorithm. The bagging algorithm is used to obtain a better the stability of the model and higher performance than ELM algorithm. The results show that the mean value of coefficient of determination is 0.9928, and root mean square error is 0.1928. Compared to other regression models, the Bagging-ABC-ELM model exhibited superior prediction accuracy, robustness, and generalization capability. The Bagging-ABC-ELM model presents a promising alternative for analyzing blood glucose levels in clinical and research settings.
Collapse
Affiliation(s)
- Shuai Song
- College of Information Science and Engineering, Northeastern University, Shenyang, Liaoning Province 110819, China
| | - Qiaoyun Wang
- College of Information Science and Engineering, Northeastern University, Shenyang, Liaoning Province 110819, China; Hebei Key Laboratory of Micro-Nano Precision Optical Sensing and Measurement Technology, Qinhuangdao 066004, China.
| | - Xin Zou
- College of Information Science and Engineering, Northeastern University, Shenyang, Liaoning Province 110819, China
| | - Zhigang Li
- College of Information Science and Engineering, Northeastern University, Shenyang, Liaoning Province 110819, China
| | - Zhenhe Ma
- College of Information Science and Engineering, Northeastern University, Shenyang, Liaoning Province 110819, China
| | - Daying Jiang
- Zhongyou BSS (Qinhuangdao) Petropipe Company Limited, Qinhuangdao 066004, China
| | - YongQing Fu
- Faculty of Engineering and Environment, Northumbria University, Newcastle upon Tyne NE1 8ST, UK
| | - Qiang Liu
- College of Information Science and Engineering, Northeastern University, Shenyang, Liaoning Province 110819, China; Hebei Key Laboratory of Micro-Nano Precision Optical Sensing and Measurement Technology, Qinhuangdao 066004, China
| |
Collapse
|
8
|
Kim SE, Yoon JC, Tae HJ, Muthurasu A. Electrospun Manganese-Based Metal-Organic Frameworks for MnO x Nanostructures Embedded in Carbon Nanofibers as a High-Performance Nonenzymatic Glucose Sensor. ACS OMEGA 2023; 8:42689-42698. [PMID: 38024713 PMCID: PMC10652823 DOI: 10.1021/acsomega.3c05459] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/26/2023] [Revised: 10/15/2023] [Accepted: 10/17/2023] [Indexed: 12/01/2023]
Abstract
Material-specific electrocatalytic activity and electrode design are essential factors in evaluating the performance of electrochemical sensors. Herein, the technique described involves electrospinning manganese-based metal-organic frameworks (Mn-MOFs) to develop MnOx nanostructures embedded in carbon nanofibers. The resulting structure features an electrocatalytic material for an enzyme-free glucose sensor. The elemental composition, morphology, and microstructure of the fabricated electrodes materials were characterized by using energy-dispersive X-ray spectroscopy (EDX), field-emission scanning electron microscopy (FESEM), and transmission electron microscopy (TEM). Cyclic voltammetry (CV) and amperometric i-t (current-time) techniques are characteristically employed to assess the electrochemical performance of materials. The MOF MnOx-CNFs nanostructures significantly improve detection performance for nonenzymatic amperometric glucose sensors, including a broad linear range (0 mM to 9.1 mM), high sensitivity (4080.6 μA mM-1 cm-2), a low detection limit (0.3 μM, S/N = 3), acceptable selectivity, outstanding reproducibility, and stability. The strategy of metal and metal oxide-integrated CNF nanostructures based on MOFs opens interesting possibilities for the development of high-performance electrochemical sensors.
Collapse
Affiliation(s)
- So Eun Kim
- Department
of Emergency Medicine, Research Institute
of Clinical Medicine of Jeonbuk National University and Biomedical
Research Institute of Jeonbuk National University Hospital, Jeonju 54907, Republic of Korea
| | - Jae Chol Yoon
- Department
of Emergency Medicine, Research Institute
of Clinical Medicine of Jeonbuk National University and Biomedical
Research Institute of Jeonbuk National University Hospital, Jeonju 54907, Republic of Korea
| | - Hyun-Jin Tae
- College
of Veterinary Medicine and Biosafety Research Institute, Jeonbuk National University, Iksan 54596, Republic of Korea
| | - Alagan Muthurasu
- Department
of Nano Convergence Technology, Jeonbuk
National University, Jeonju 54907, Republic
of Korea
| |
Collapse
|
9
|
Papadakis VM, Cheimonidi C, Panagopoulou M, Karaglani M, Apalaki P, Katsara K, Kenanakis G, Theodosiou T, Constantinidis TC, Stratigi K, Chatzaki E. Label-Free Human Disease Characterization through Circulating Cell-Free DNA Analysis Using Raman Spectroscopy. Int J Mol Sci 2023; 24:12384. [PMID: 37569759 PMCID: PMC10418917 DOI: 10.3390/ijms241512384] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2023] [Revised: 07/30/2023] [Accepted: 08/01/2023] [Indexed: 08/13/2023] Open
Abstract
Circulating cell-free DNA (ccfDNA) is a liquid biopsy biomaterial attracting significant attention for the implementation of precision medicine diagnostics. Deeper knowledge related to its structure and biology would enable the development of such applications. In this study, we employed Raman spectroscopy to unravel the biomolecular profile of human ccfDNA in health and disease. We established reference Raman spectra of ccfDNA samples from healthy males and females with different conditions, including cancer and diabetes, extracting information about their chemical composition. Comparative observations showed a distinct spectral pattern in ccfDNA from breast cancer patients taking neoadjuvant therapy. Raman analysis of ccfDNA from healthy, prediabetic, and diabetic males uncovered some differences in their biomolecular fingerprints. We also studied ccfDNA released from human benign and cancer cell lines and compared it to their respective gDNA, confirming it mirrors its cellular origin. Overall, we explored for the first time Raman spectroscopy in the study of ccfDNA and provided spectra of samples from different sources. Our findings introduce Raman spectroscopy as a new approach to implementing liquid biopsy diagnostics worthy of further elaboration.
Collapse
Affiliation(s)
- Vassilis M. Papadakis
- Institute of Molecular Biology and Biotechnology, Foundation for Research and Technology, 70013 Heraklion, Greece; (V.M.P.); (C.C.); (P.A.); (K.S.)
- Department of Industrial Design and Production Engineering, University of West Attica, 12244 Athens, Greece
- Institute of Agri-Food and Life Sciences, University Research & Innovation Center, Hellenic Mediterranean University, 71410 Heraklion, Greece; (M.P.); (M.K.)
| | - Christina Cheimonidi
- Institute of Molecular Biology and Biotechnology, Foundation for Research and Technology, 70013 Heraklion, Greece; (V.M.P.); (C.C.); (P.A.); (K.S.)
- Institute of Agri-Food and Life Sciences, University Research & Innovation Center, Hellenic Mediterranean University, 71410 Heraklion, Greece; (M.P.); (M.K.)
| | - Maria Panagopoulou
- Institute of Agri-Food and Life Sciences, University Research & Innovation Center, Hellenic Mediterranean University, 71410 Heraklion, Greece; (M.P.); (M.K.)
- Laboratory of Pharmacology, Medical School, Democritus University of Thrace, 68100 Alexandroupolis, Greece;
| | - Makrina Karaglani
- Institute of Agri-Food and Life Sciences, University Research & Innovation Center, Hellenic Mediterranean University, 71410 Heraklion, Greece; (M.P.); (M.K.)
- Laboratory of Pharmacology, Medical School, Democritus University of Thrace, 68100 Alexandroupolis, Greece;
| | - Paraskevi Apalaki
- Institute of Molecular Biology and Biotechnology, Foundation for Research and Technology, 70013 Heraklion, Greece; (V.M.P.); (C.C.); (P.A.); (K.S.)
| | - Klytaimnistra Katsara
- Institute of Electronic Structure and Laser, Foundation for Research and Technology-Hellas, N. Plastira 100, Vasilika Vouton, 70013 Heraklion, Greece (G.K.)
- Department of Agriculture, Hellenic Mediterranean University—Hellas, Estavromenos, 71410 Heraklion, Greece
| | - George Kenanakis
- Institute of Electronic Structure and Laser, Foundation for Research and Technology-Hellas, N. Plastira 100, Vasilika Vouton, 70013 Heraklion, Greece (G.K.)
| | - Theodosis Theodosiou
- Laboratory of Pharmacology, Medical School, Democritus University of Thrace, 68100 Alexandroupolis, Greece;
| | - Theodoros C. Constantinidis
- Laboratory of Hygiene and Environmental Protection, Medical School, Democritus University of Thrace, 68100 Alexandroupolis, Greece;
| | - Kalliopi Stratigi
- Institute of Molecular Biology and Biotechnology, Foundation for Research and Technology, 70013 Heraklion, Greece; (V.M.P.); (C.C.); (P.A.); (K.S.)
| | - Ekaterini Chatzaki
- Institute of Agri-Food and Life Sciences, University Research & Innovation Center, Hellenic Mediterranean University, 71410 Heraklion, Greece; (M.P.); (M.K.)
- Laboratory of Pharmacology, Medical School, Democritus University of Thrace, 68100 Alexandroupolis, Greece;
| |
Collapse
|