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Li X, Xue X, Xie P. Smart Dressings and Their Applications in Chronic Wound Management. Cell Biochem Biophys 2024; 82:1965-1977. [PMID: 38969950 DOI: 10.1007/s12013-024-01402-w] [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] [Accepted: 07/02/2024] [Indexed: 07/07/2024]
Abstract
During chronic wound healing, the inflammatory phase can endure for extended periods, heavily impeding or halting the process. Regular inspections and dressing changes are crucial. Modern dressings like hydrogels, hydrocolloids, and foam provide protection and an optimal healing environment. However, they have limitations in offering real-time wound bed status and healing rate. Evaluation relies heavily on direct observation, and passive dressings fail to identify subtle healing differences, preventing adaptive adjustments in biological factors and drug concentrations. In recent years, the clinical field recognizes the value of integrating intelligent diagnostic tools into wound dressings. By monitoring biomarkers linked to chronic wounds' inflammatory state, real-time data can be captured, reducing medical interventions and enabling more effective treatment plans. This fosters innovation in chronic wound care. Researchers have developed smart dressings with sensing, active drug delivery, and self-adjustment capabilities. These dressings detect inflammatory markers like temperature, pH, and oxygen content, enhancing drug bioavailability on the wound surface. As wound healing technology evolves, these smart dressings hold immense potential in chronic wound care and treatment. This comprehensive review updates our understanding on the role and mechanism of action of the smart dressings in chronic refractory wounds by summarizing and discussing the latest research progresses, including the intelligent monitoring of wound oxygen content, temperature, humidity, pH, infection, and enzyme kinetics; intelligent drug delivery triggered by temperature, pH, near-infrared, and electricity; as well as the intelligent self-adjustment of pressure and shape. The review also delves into the constraints and future perspectives of smart dressings in clinical settings, thereby advancing the development of smart wound dressings for chronic wound healing and their practical application in clinical practice.
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Affiliation(s)
- Xiaodong Li
- Center for Cosmetic Surgery, General Hospital of Lanzhou Petrochemical Company (The Fourth Affiliated Hospital of Gansu University of Chinese Medicine), Lanzhou, 730060, Gansu, China
| | - Xiaodong Xue
- Department of Plastic Surgery, People's Hospital of Gansu Province, Lanzhou, 730000, Gansu, China
| | - Peilin Xie
- Department of Plastic Surgery, People's Hospital of Gansu Province, Lanzhou, 730000, Gansu, China.
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Chimene D, Queener KMK, Ko BS, McShane M, Daniele M. Insertable Biosensors: Combining Implanted Sensing Materials with Wearable Monitors. Annu Rev Biomed Eng 2024; 26:197-221. [PMID: 38346276 DOI: 10.1146/annurev-bioeng-110222-101045] [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: 07/05/2024]
Abstract
Insertable biosensor systems are medical diagnostic devices with two primary components: an implantable biosensor within the body and a wearable monitor that can remotely interrogate the biosensor from outside the body. Because the biosensor does not require a physical connection to the electronic monitor, insertable biosensor systems promise improved patient comfort, reduced inflammation and infection risk, and extended operational lifetimes relative to established percutaneous biosensor systems. However, the lack of physical connection also presents technical challenges that have necessitated new innovations in developing sensing chemistries, transduction methods, and communication modalities. In this review, we discuss the key developments that have made insertables a promising option for longitudinal biometric monitoring and highlight the essential needs and existing development challenges to realizing the next generation of insertables for extended-use diagnostic and prognostic devices.
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Affiliation(s)
- David Chimene
- Department of Biomedical Engineering, Texas A&M University, College Station, Texas, USA;
| | - Kirstie M K Queener
- Joint Department of Biomedical Engineering, North Carolina State University and University of North Carolina at Chapel Hill, Raleigh, North Carolina, USA
| | - Brian S Ko
- Department of Biomedical Engineering, Texas A&M University, College Station, Texas, USA;
| | - Mike McShane
- Department of Biomedical Engineering, Texas A&M University, College Station, Texas, USA;
- Department of Materials Science and Engineering, Texas A&M University, College Station, Texas, USA
| | - Michael Daniele
- Joint Department of Biomedical Engineering, North Carolina State University and University of North Carolina at Chapel Hill, Raleigh, North Carolina, USA
- Department of Electrical and Computer Engineering, North Carolina State University, Raleigh, North Carolina, USA;
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Thota C, Jackson Samuel D, Musa Jaber M, Kamruzzaman MM, Ravi RV, Gnanasigamani LJ, Premalatha R. Image Smart Segmentation Analysis Against Diabetic Foot Ulcer Using Internet of Things with Virtual Sensing. BIG DATA 2024; 12:155-172. [PMID: 37289808 DOI: 10.1089/big.2022.0283] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
Diabetic foot ulcer (DFU) is a problem worldwide, and prevention is crucial. The image segmentation analysis of DFU identification plays a significant role. This will produce different segmentation of the same idea, incomplete, imprecise, and other problems. To address these issues, a method of image segmentation analysis of DFU through internet of things with the technique of virtual sensing for semantically similar objects, the analysis of four levels of range segmentation (region-based, edge-based, image-based, and computer-aided design-based range segmentation) for deeper segmentation of images is implemented. In this study, the multimodal is compressed with the object co-segmentation for semantical segmentation. The result is predicting the better validity and reliability assessment. The experimental results demonstrate that the proposed model can efficiently perform segmentation analysis, with a lower error rate, than the existing methodologies. The findings on the multiple-image dataset show that DFU obtains an average segmentation score of 90.85% and 89.03% correspondingly in two types of labeled ratios before DFU with virtual sensing and after DFU without virtual sensing (i.e., 25% and 30%), which is an increase of 10.91% and 12.22% over the previous best results. In live DFU studies, our proposed system improved by 59.1% compared with existing deep segmentation-based techniques and its average image smart segmentation improvements over its contemporaries are 15.06%, 23.94%, and 45.41%, respectively. Proposed range-based segmentation achieves interobserver reliability by 73.9% on the positive test namely likelihood ratio test set with only a 0.25 million parameters at the pace of labeled data.
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Affiliation(s)
| | | | - Mustafa Musa Jaber
- Department of Medical Instruments Engineering Techniques, Al-Turath University College, Baghdad, Iraq
| | - M M Kamruzzaman
- Department of Computer Science, College of Computer and Information Sciences, Jouf University, Sakakah, Saudi Arabia
| | - Renjith V Ravi
- Department of Electronics and Communication Engineering, M.E.A. Engineering College, Malappuram, Kerala, India
| | - Lydia J Gnanasigamani
- School of Computer Science and Engineering, Vellore Institute of Technology, Vellore, Tamil Nadu, India
| | - R Premalatha
- IFET College of Engineering, Villupuram, Tamil Nadu, India
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Witthauer L, Roussakis E, Cascales JP, Goss A, Li X, Cralley A, Yoeli D, Moore HB, Wang Z, Wang Y, Li B, Huang CA, Moore EE, Evans CL. Development and in-vivo validation of a portable phosphorescence lifetime-based fiber-optic oxygen sensor. Sci Rep 2023; 13:14782. [PMID: 37679415 PMCID: PMC10484954 DOI: 10.1038/s41598-023-41917-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2023] [Accepted: 09/04/2023] [Indexed: 09/09/2023] Open
Abstract
Oxygenation is a crucial indicator of tissue viability and function. Oxygen tension ([Formula: see text]), i.e. the amount of molecular oxygen present in the tissue is a direct result of supply (perfusion) and consumption. Thus, measurement of [Formula: see text] is an effective method to monitor tissue viability. However, tissue oximetry sensors commonly used in clinical practice instead rely on measuring oxygen saturation ([Formula: see text]), largely due to the lack of reliable, affordable [Formula: see text] sensing solutions. To address this issue we present a proof-of-concept design and validation of a low-cost, lifetime-based oxygen sensing fiber. The sensor consists of readily-available off-the shelf components such as a microcontroller, a light-emitting diode (LED), an avalanche photodiode (APD), a temperature sensor, as well as a bright in-house developed porphyrin molecule. The device was calibrated using a benchtop setup and evaluated in three in vivo animal models. Our findings show that the new device design in combination with the bright porphyrin has the potential to be a useful and accurate tool for measuring [Formula: see text] in tissue, while also highlighting some of the limitations and challenges of oxygen measurements in this context.
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Affiliation(s)
- Lilian Witthauer
- Wellman Center for Photomedicine, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, 02129, USA
- Department of Diabetes, Endocrinology, Nutritional Medicine and Metabolism, Inselspital, Bern University Hospital and University of Bern, 3010, Bern, Switzerland
| | - Emmanuel Roussakis
- Wellman Center for Photomedicine, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, 02129, USA
| | - Juan Pedro Cascales
- Wellman Center for Photomedicine, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, 02129, USA
| | - Avery Goss
- Wellman Center for Photomedicine, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, 02129, USA
| | - Xiaolei Li
- Wellman Center for Photomedicine, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, 02129, USA
| | - Alexis Cralley
- Department of Surgery, University of Colorado Denver/Anschutz Medical Campus, Aurora, CO, USA
| | - Dor Yoeli
- Department of Surgery, University of Colorado Denver/Anschutz Medical Campus, Aurora, CO, USA
| | - Hunter B Moore
- Department of Surgery, University of Colorado Denver/Anschutz Medical Campus, Aurora, CO, USA
| | - Zhaohui Wang
- Department of Surgery, University of Colorado Denver/Anschutz Medical Campus, Aurora, CO, USA
| | - Yong Wang
- Department of Surgery, University of Colorado Denver/Anschutz Medical Campus, Aurora, CO, USA
| | - Bing Li
- Department of Surgery, University of Colorado Denver/Anschutz Medical Campus, Aurora, CO, USA
| | - Christene A Huang
- Department of Surgery, University of Colorado Denver/Anschutz Medical Campus, Aurora, CO, USA
| | - Ernest E Moore
- Department of Surgery, University of Colorado Denver/Anschutz Medical Campus, Aurora, CO, USA
| | - Conor L Evans
- Wellman Center for Photomedicine, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, 02129, USA.
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Arora S, Nagpal R, Gusain M, Singh B, Pan Y, Yadav D, Ahmed I, Kumar V, Parshad B. Organic-Inorganic Porphyrinoid Frameworks for Biomolecule Sensing. ACS Sens 2023; 8:443-464. [PMID: 36683281 DOI: 10.1021/acssensors.2c02408] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/24/2023]
Abstract
Porphyrinoids and their analogous compounds play an important role in biosensing applications on account of their unique and versatile catalytic, coordination, photophysical, and electrochemical properties. Their remarkable arrays of properties can be finely tuned by synthetically modifying the porphyrinoid ring and varying the various structural parameters such as peripheral functionalization, metal coordination, and covalent or physical conjugation with other organic or inorganic scaffolds such as nanoparticles, metal-organic frameworks, and polymers. Porphyrinoids and their organic-inorganic conjugates are not only used as responsive materials but also utilized for the immobilization and embedding of biomolecules for applications in wearable devices, fast sensing devices, and other functional materials. The present review delineates the impact of different porphyrinoid conjugates on their physicochemical properties and their specificity as biosensors in a range of applications. The newest porphyrinoid types and their synthesis, modification, and functionalization are presented along with their advantages and performance improvements.
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Affiliation(s)
- Smriti Arora
- Institut für Chemie und Biochemie Organische Chemie, Freie Universität Berlin, Takustr. 3, 14195 Berlin, Germany
| | - Ritika Nagpal
- Department of Chemistry, SRM University, 39, Rajiv Gandhi Education City, Delhi-NCR, Sonipat, Haryana 131029, India
| | - Meenakshi Gusain
- Centre of Micro-Nano System, School of Information Science and Technology, Fudan University, 200433 Shanghai, China
| | | | - Yuanwei Pan
- Department of Diagnostic Radiology, Department of Chemical and Biomolecular Engineering, and Department of Biomedical Engineering, Yong Loo Lin School of Medicine and Faculty of Engineering, National University of Singapore, Singapore 119074, Singapore
| | - Deepak Yadav
- Department of Chemistry, Gurugram University, Gurugram, Haryana 122003, India
| | - Ishtiaq Ahmed
- Department of Chemical Engineering and Biotechnology, University of Cambridge, Cambridge CB3 0AS, U.K
| | - Vinod Kumar
- Department of Chemistry, Central University of Haryana, Mahendergarh, Haryana 123031, India
| | - Badri Parshad
- Department of Chemical Engineering and Biotechnology, University of Cambridge, Cambridge CB3 0AS, U.K
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Qi L, Zhang C, Wang B, Yin J, Yan S. Progress in hydrogels for skin wound repair. Macromol Biosci 2022; 22:e2100475. [PMID: 35388605 DOI: 10.1002/mabi.202100475] [Citation(s) in RCA: 62] [Impact Index Per Article: 31.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2021] [Revised: 03/21/2022] [Indexed: 11/08/2022]
Abstract
As the first defensive line between the human body and the outside world, the skin is vulnerable to damage from the external environment. Skin wounds can be divided into acute wounds (mechanical injuries, chemical injuries and surgical wounds, etc.) and chronic wounds (burns, infections, diabetes, etc.). In order to manage skin wound, a variety of wound dressings have been developed, including gauze, films, foams, nanofibers, hydrocolloids and hydrogels. Recently, hydrogels have received much attention because of their natural extracellular matrix (ECM)-mimik structure, tunable mechanical properties, and facile bioactive substance delivery capability. They show great potential application in skin wound repair. This paper first introduces the anatomy and function of the skin, the process of wound healing and conventional wound dressings, and then introduces the composition and construction methods of hydrogels. Next, this paper introduces the necessary properties of hydrogels in skin wound repair and the latest research progress of hydrogel dressings for skin wound repair. Finally, the future development goals of hydrogel materials in the field of wound healing are proposed. This article is protected by copyright. All rights reserved.
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Affiliation(s)
- Liangfa Qi
- Department of Polymer Materials, School of Materials Science and Engineering, Shanghai University, Shanghai, 200444, PR China
| | - Chenlu Zhang
- Department of Polymer Materials, School of Materials Science and Engineering, Shanghai University, Shanghai, 200444, PR China
| | - Bo Wang
- Department of Polymer Materials, School of Materials Science and Engineering, Shanghai University, Shanghai, 200444, PR China
| | - Jingbo Yin
- Department of Polymer Materials, School of Materials Science and Engineering, Shanghai University, Shanghai, 200444, PR China
| | - Shifeng Yan
- Department of Polymer Materials, School of Materials Science and Engineering, Shanghai University, Shanghai, 200444, PR China
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