1
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Liang A, Zhao W, Lv T, Zhu Z, Haotian R, Zhang J, Xie B, Yi Y, Hao Z, Sun L, Luo A. Advances in novel biosensors in biomedical applications. Talanta 2024; 280:126709. [PMID: 39151317 DOI: 10.1016/j.talanta.2024.126709] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/25/2023] [Revised: 07/09/2024] [Accepted: 08/13/2024] [Indexed: 08/19/2024]
Abstract
Biosensors, devices capable of detecting biomolecules or bioactive substances, have recently become one of the important tools in the fields of bioanalysis and medical diagnostics. A biosensor is an analytical system composed of biosensitive elements and signal-processing elements used to detect various biological and chemical substances. Biomimetic elements are key to biosensor technology and are the components in a sensor that are responsible for identifying the target analyte. The construction methods and working principles of biosensors based on synthetic biomimetic elements, such as DNAzyme, molecular imprinted polymers and aptamers, and their updated applications in biomedical analysis are summarised. Finally, the technical bottlenecks and future development prospects for biomedical analysis are summarised and discussed.
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Affiliation(s)
- Axin Liang
- Key Laboratory of Molecular Medicine and Biotherapy, The Ministry of Industry and Information Technology, School of Life Science, Beijing Institute of Technology, Beijing, 100081, China
| | - Weidong Zhao
- Key Laboratory of Molecular Medicine and Biotherapy, The Ministry of Industry and Information Technology, School of Life Science, Beijing Institute of Technology, Beijing, 100081, China
| | - Tianjian Lv
- Key Laboratory of Molecular Medicine and Biotherapy, The Ministry of Industry and Information Technology, School of Life Science, Beijing Institute of Technology, Beijing, 100081, China
| | - Ziyu Zhu
- Key Laboratory of Molecular Medicine and Biotherapy, The Ministry of Industry and Information Technology, School of Life Science, Beijing Institute of Technology, Beijing, 100081, China
| | - Ruilin Haotian
- Key Laboratory of Molecular Medicine and Biotherapy, The Ministry of Industry and Information Technology, School of Life Science, Beijing Institute of Technology, Beijing, 100081, China
| | - Jiangjiang Zhang
- Key Laboratory of Molecular Medicine and Biotherapy, The Ministry of Industry and Information Technology, School of Life Science, Beijing Institute of Technology, Beijing, 100081, China
| | - Bingteng Xie
- Key Laboratory of Molecular Medicine and Biotherapy, The Ministry of Industry and Information Technology, School of Life Science, Beijing Institute of Technology, Beijing, 100081, China
| | - Yue Yi
- Key Laboratory of Molecular Medicine and Biotherapy, The Ministry of Industry and Information Technology, School of Life Science, Beijing Institute of Technology, Beijing, 100081, China
| | - Zikai Hao
- Key Laboratory of Molecular Medicine and Biotherapy, The Ministry of Industry and Information Technology, School of Life Science, Beijing Institute of Technology, Beijing, 100081, China
| | - Liquan Sun
- Key Laboratory of Molecular Medicine and Biotherapy, The Ministry of Industry and Information Technology, School of Life Science, Beijing Institute of Technology, Beijing, 100081, China
| | - Aiqin Luo
- Key Laboratory of Molecular Medicine and Biotherapy, The Ministry of Industry and Information Technology, School of Life Science, Beijing Institute of Technology, Beijing, 100081, China.
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2
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Daich Varela M, Sanders Villa A, Pontikos N, Crossland MD, Michaelides M. Digital health and wearable devices for retinal disease monitoring. Graefes Arch Clin Exp Ophthalmol 2024:10.1007/s00417-024-06634-3. [PMID: 39297890 DOI: 10.1007/s00417-024-06634-3] [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: 05/28/2024] [Revised: 07/30/2024] [Accepted: 08/29/2024] [Indexed: 09/21/2024] Open
Abstract
Digital health is wielding a growing influence across all areas of healthcare, encompassing various facets such as telemedicine, artificial intelligence (AI), and electronic healthcare records. In Ophthalmology, digital health innovations can be broadly divided into four categories: (i) self-monitoring home devices and apps, (ii) virtual and augmented reality visual aids, (iii) AI software, and (iv) wearables. Wearable devices can work in the background, collecting large amounts of objective data while we do our day-to-day activities, which may be ecologically more valid and meaningful to patients than that acquired in traditional hospital settings. They can be a watch, wristband, piece of clothing, glasses, cane, smartphone in our pocket, earphones, or any other device with a sensor that we carry with us. Focusing on retinal diseases, a key challenge in developing novel therapeutics has been to prove a meaningful benefit in patients' lives and the creation of objective patient-centred endpoints in clinical trials. In this review, we will discuss wearable devices collecting different aspects of visual behaviour, visual field, central vision, and functional vision, as well as their potential implementation as outcome measures in research/clinical trial settings. The healthcare landscape is facing a paradigm shift. Clinicians have a key role of collaborating with the development and fine-tuning of digital health innovations, as well as identifying opportunities where they can be leveraged to enhance our understanding of retinal diseases and improve patient outcomes.
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Affiliation(s)
- Malena Daich Varela
- Moorfields Eye Hospital, London, UK
- UCL Institute of Ophthalmology, University College London, 11-43 Bath Street, London, EC1V 9EL, UK
| | - Alejandro Sanders Villa
- Facultad de Enfermería y Obstetricia, Universidad Nacional Autónoma de México, Mexico City, México
- Primero Salud, Mexico City, México
| | - Nikolas Pontikos
- Moorfields Eye Hospital, London, UK
- UCL Institute of Ophthalmology, University College London, 11-43 Bath Street, London, EC1V 9EL, UK
| | - Michael D Crossland
- UCL Institute of Ophthalmology, University College London, 11-43 Bath Street, London, EC1V 9EL, UK
| | - Michel Michaelides
- Moorfields Eye Hospital, London, UK.
- UCL Institute of Ophthalmology, University College London, 11-43 Bath Street, London, EC1V 9EL, UK.
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3
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Adedokun G, Alipanah M, Fan ZH. Sample preparation and detection methods in point-of-care devices towards future at-home testing. LAB ON A CHIP 2024; 24:3626-3650. [PMID: 38952234 PMCID: PMC11270053 DOI: 10.1039/d3lc00943b] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/03/2024]
Abstract
Timely and accurate diagnosis is critical for effective healthcare, yet nearly half the global population lacks access to basic diagnostics. Point-of-care (POC) testing offers partial solutions by enabling low-cost, rapid diagnosis at the patient's location. At-home POC devices have the potential to advance preventive care and early disease detection. Nevertheless, effective sample preparation and detection methods are essential for accurate results. This review surveys recent advances in sample preparation and detection methods at POC. The goal is to provide an in-depth understanding of how these technologies can enhance at-home POC devices. Lateral flow assays, nucleic acid tests, and virus detection methods are at the forefront of POC diagnostic technology, offering rapid and sensitive tools for identifying and measuring pathogens, biomarkers, and viral infections. By illuminating cutting-edge research on assay development for POC diagnostics, this review aims to accelerate progress towards widely available, user-friendly, at-home health monitoring tools that empower individuals in personalized healthcare in the future.
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Affiliation(s)
- George Adedokun
- Interdisciplinary Microsystems Group, Department of Mechanical and Aerospace Engineering, University of Florida, P.O. Box 116250, Gainesville, FL 32611, USA.
| | - Morteza Alipanah
- Interdisciplinary Microsystems Group, Department of Mechanical and Aerospace Engineering, University of Florida, P.O. Box 116250, Gainesville, FL 32611, USA.
| | - Z Hugh Fan
- Interdisciplinary Microsystems Group, Department of Mechanical and Aerospace Engineering, University of Florida, P.O. Box 116250, Gainesville, FL 32611, USA.
- J. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, P.O. Box 116131, Gainesville, FL 32611, USA
- Department of Chemistry, University of Florida, P.O. Box 117200, Gainesville, FL 32611, USA
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4
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Yigci D, Bonventre J, Ozcan A, Tasoglu S. Repurposing Sewage and Toilet Systems: Environmental, Public Health, and Person-Centered Healthcare Applications. GLOBAL CHALLENGES (HOBOKEN, NJ) 2024; 8:2300358. [PMID: 39006062 PMCID: PMC11237177 DOI: 10.1002/gch2.202300358] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/22/2023] [Revised: 01/27/2024] [Indexed: 07/16/2024]
Abstract
Global terrestrial water supplies are rapidly depleting due to the consequences of climate change. Water scarcity results in an inevitable compromise of safe hygiene and sanitation practices, leading to the transmission of water-borne infectious diseases, and the preventable deaths of over 800.000 people each year. Moreover, almost 500 million people lack access to toilets and sanitation systems. Ecosystems are estimated to be contaminated by 6.2 million tons of nitrogenous products from human wastewater management practices. It is therefore imperative to transform toilet and sewage systems to promote equitable access to water and sanitation, improve public health, conserve water, and protect ecosystems. Here, the integration of emerging technologies in toilet and sewage networks to repurpose toilet and wastewater systems is reviewed. Potential applications of these systems to develop sustainable solutions to environmental challenges, promote public health, and advance person-centered healthcare are discussed.
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Affiliation(s)
- Defne Yigci
- School of MedicineKoç UniversityIstanbul34450Türkiye
| | - Joseph Bonventre
- Division of Renal MedicineDepartment of Medicine, Brigham and Women's HospitalHarvard Medical SchoolBostonMA02115USA
| | - Aydogan Ozcan
- Electrical and Computer Engineering DepartmentUniversity of CaliforniaLos AngelesCA90095USA
- Bioengineering DepartmentUniversity of CaliforniaLos AngelesCA90095USA
- California NanoSystems Institute (CNSI)University of CaliforniaLos AngelesCA90095USA
- Computer Science DepartmentUniversity of CaliforniaLos AngelesCA90095USA
- Department of SurgeryDavid Geffen School of MedicineUniversity of CaliforniaLos AngelesCA90095USA
| | - Savas Tasoglu
- Department of Mechanical EngineeringKoç UniversitySariyerIstanbul34450Türkiye
- Koç University Translational Medicine Research Center (KUTTAM)Koç UniversityIstanbul34450Türkiye
- Boğaziçi Institute of Biomedical EngineeringBoğaziçi UniversityIstanbul34684Turkey
- Koç University Arçelik Research Center for Creative Industries (KUAR)Koç UniversityIstanbul34450Turkey
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5
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Tezsezen E, Yigci D, Ahmadpour A, Tasoglu S. AI-Based Metamaterial Design. ACS APPLIED MATERIALS & INTERFACES 2024; 16:29547-29569. [PMID: 38808674 PMCID: PMC11181287 DOI: 10.1021/acsami.4c04486] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/19/2024] [Revised: 05/16/2024] [Accepted: 05/16/2024] [Indexed: 05/30/2024]
Abstract
The use of metamaterials in various devices has revolutionized applications in optics, healthcare, acoustics, and power systems. Advancements in these fields demand novel or superior metamaterials that can demonstrate targeted control of electromagnetic, mechanical, and thermal properties of matter. Traditional design systems and methods often require manual manipulations which is time-consuming and resource intensive. The integration of artificial intelligence (AI) in optimizing metamaterial design can be employed to explore variant disciplines and address bottlenecks in design. AI-based metamaterial design can also enable the development of novel metamaterials by optimizing design parameters that cannot be achieved using traditional methods. The application of AI can be leveraged to accelerate the analysis of vast data sets as well as to better utilize limited data sets via generative models. This review covers the transformative impact of AI and AI-based metamaterial design for optics, acoustics, healthcare, and power systems. The current challenges, emerging fields, future directions, and bottlenecks within each domain are discussed.
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Affiliation(s)
- Ece Tezsezen
- Graduate
School of Science and Engineering, Koç
University, Istanbul 34450, Türkiye
| | - Defne Yigci
- School
of Medicine, Koç University, Istanbul 34450, Türkiye
| | - Abdollah Ahmadpour
- Department
of Mechanical Engineering, Koç University
Sariyer, Istanbul 34450, Türkiye
| | - Savas Tasoglu
- Department
of Mechanical Engineering, Koç University
Sariyer, Istanbul 34450, Türkiye
- Koç
University Translational Medicine Research Center (KUTTAM), Koç University, Istanbul 34450, Türkiye
- Bogaziçi
Institute of Biomedical Engineering, Bogaziçi
University, Istanbul 34684, Türkiye
- Koç
University Arçelik Research Center for Creative Industries
(KUAR), Koç University, Istanbul 34450, Türkiye
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6
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Pang Y, Li Y, Chen K, Wu M, Zhang J, Sun Y, Xu Y, Wang X, Wang Q, Ning X, Kong D. Porous Microneedles Through Direct Ink Drawing with Nanocomposite Inks for Transdermal Collection of Interstitial Fluid. SMALL (WEINHEIM AN DER BERGSTRASSE, GERMANY) 2024; 20:e2305838. [PMID: 38258379 DOI: 10.1002/smll.202305838] [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: 07/11/2023] [Revised: 11/19/2023] [Indexed: 01/24/2024]
Abstract
Interstitial fluid (ISF) is an attractive alternative to regular blood sampling for health checks and disease diagnosis. Porous microneedles (MNs) are well suited for collecting ISF in a minimally invasive manner. However, traditional methods of molding MNs from microfabricated templates involve prohibitive fabrication costs and fixed designs. To overcome these limitations, this study presents a facile and economical additive manufacturing approach to create porous MNs. Compared to traditional layerwise build sequences, direct ink drawing with nanocomposite inks can define sharp MNs with tailored shapes and achieve vastly improved fabrication efficiency. The key to this fabrication strategy is the yield-stress fluid ink that is easily formulated by dispersing silica nanoparticles into the cellulose acetate polymer solution. As-printed MNs are solidified into interconnected porous microstructure inside a coagulation bath of deionized water. The resulting MNs exhibit high mechanical strength and high porosity. This approach also allows porous MNs to be easily integrated on various substrates. In particular, MNs on filter paper substrates are highly flexible to rapidly collect ISF on non-flat skin sites. The extracted ISF is used for quantitative analysis of biomarkers, including glucose, = calcium ions, and calcium ions. Overall, the developments allow facile fabrication of porous MNs for transdermal diagnosis and therapy.
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Affiliation(s)
- Yushuang Pang
- College of Engineering and Applied Sciences, Jiangsu Key Laboratory of Artificial Functional Materials, Nanjing University, Nanjing, 210023, China
- State Key Laboratory of Analytical Chemistry for Life Science, Nanjing University, Nanjing, 210023, China
| | - Yanyan Li
- College of Engineering and Applied Sciences, Jiangsu Key Laboratory of Artificial Functional Materials, Nanjing University, Nanjing, 210023, China
- State Key Laboratory of Analytical Chemistry for Life Science, Nanjing University, Nanjing, 210023, China
| | - Kerong Chen
- College of Engineering and Applied Sciences, Jiangsu Key Laboratory of Artificial Functional Materials, Nanjing University, Nanjing, 210023, China
- National Laboratory of Solid State Microstructure, Collaborative Innovation Center of Advanced Microstructures, Chemistry and Biomedicine Innovation Center, Nanjing University, Nanjing, 210093, China
| | - Ming Wu
- Key Laboratory of High Performance Polymer Materials and Technology of Ministry of Education, Department of Polymer Science and Engineering, School of Chemistry and Chemical Engineering, Nanjing University, Nanjing, 210023, China
| | - Jiaxue Zhang
- College of Engineering and Applied Sciences, Jiangsu Key Laboratory of Artificial Functional Materials, Nanjing University, Nanjing, 210023, China
- State Key Laboratory of Analytical Chemistry for Life Science, Nanjing University, Nanjing, 210023, China
| | - Yuping Sun
- College of Engineering and Applied Sciences, Jiangsu Key Laboratory of Artificial Functional Materials, Nanjing University, Nanjing, 210023, China
- State Key Laboratory of Analytical Chemistry for Life Science, Nanjing University, Nanjing, 210023, China
| | - Yurui Xu
- College of Engineering and Applied Sciences, Jiangsu Key Laboratory of Artificial Functional Materials, Nanjing University, Nanjing, 210023, China
- National Laboratory of Solid State Microstructure, Collaborative Innovation Center of Advanced Microstructures, Chemistry and Biomedicine Innovation Center, Nanjing University, Nanjing, 210093, China
| | - Xiaoliang Wang
- Key Laboratory of High Performance Polymer Materials and Technology of Ministry of Education, Department of Polymer Science and Engineering, School of Chemistry and Chemical Engineering, Nanjing University, Nanjing, 210023, China
| | - Qian Wang
- College of Engineering and Applied Sciences, Jiangsu Key Laboratory of Artificial Functional Materials, Nanjing University, Nanjing, 210023, China
- State Key Laboratory of Analytical Chemistry for Life Science, Nanjing University, Nanjing, 210023, China
| | - Xinghai Ning
- College of Engineering and Applied Sciences, Jiangsu Key Laboratory of Artificial Functional Materials, Nanjing University, Nanjing, 210023, China
- National Laboratory of Solid State Microstructure, Collaborative Innovation Center of Advanced Microstructures, Chemistry and Biomedicine Innovation Center, Nanjing University, Nanjing, 210093, China
| | - Desheng Kong
- College of Engineering and Applied Sciences, Jiangsu Key Laboratory of Artificial Functional Materials, Nanjing University, Nanjing, 210023, China
- State Key Laboratory of Analytical Chemistry for Life Science, Nanjing University, Nanjing, 210023, China
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7
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Ahmadpour A, Shojaeian M, Tasoglu S. Deep learning-augmented T-junction droplet generation. iScience 2024; 27:109326. [PMID: 38510144 PMCID: PMC10951907 DOI: 10.1016/j.isci.2024.109326] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2023] [Revised: 01/13/2024] [Accepted: 02/20/2024] [Indexed: 03/22/2024] Open
Abstract
Droplet generation technology has become increasingly important in a wide range of applications, including biotechnology and chemical synthesis. T-junction channels are commonly used for droplet generation due to their integration capability of a larger number of droplet generators in a compact space. In this study, a finite element analysis (FEA) approach is employed to simulate droplet production and its dynamic regimes in a T-junction configuration and collect data for post-processing analysis. Next, image analysis was performed to calculate the droplet length and determine the droplet generation regime. Furthermore, machine learning (ML) and deep learning (DL) algorithms were applied to estimate outputs through examination of input parameters within the simulation range. At the end, a graphical user interface (GUI) was developed for estimation of the droplet characteristics based on inputs, enabling the users to preselect their designs with comparable microfluidic configurations within the studied range.
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Affiliation(s)
- Abdollah Ahmadpour
- Mechanical Engineering Department, School of Engineering, Koç University, Istanbul 34450, Türkiye
| | - Mostafa Shojaeian
- Mechanical Engineering Department, School of Engineering, Koç University, Istanbul 34450, Türkiye
| | - Savas Tasoglu
- Mechanical Engineering Department, School of Engineering, Koç University, Istanbul 34450, Türkiye
- Koç University Arçelik Research Center for Creative Industries (KUAR), Koç University, Istanbul 34450, Türkiye
- Koç University Is Bank Artificial Intelligence Lab (KUIS AILab), Koç University, Sariyer, Istanbul 34450, Türkiye
- Koç University Translational Medicine Research Center (KUTTAM), Koç University, Istanbul 34450, Türkiye
- Boğaziçi Institute of Biomedical Engineering, Boğaziçi University, Istanbul 34684, Türkiye
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8
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Yurkovich JT, Evans SJ, Rappaport N, Boore JL, Lovejoy JC, Price ND, Hood LE. The transition from genomics to phenomics in personalized population health. Nat Rev Genet 2024; 25:286-302. [PMID: 38093095 DOI: 10.1038/s41576-023-00674-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/03/2023] [Indexed: 03/21/2024]
Abstract
Modern health care faces several serious challenges, including an ageing population and its inherent burden of chronic diseases, rising costs and marginal quality metrics. By assessing and optimizing the health trajectory of each individual using a data-driven personalized approach that reflects their genetics, behaviour and environment, we can start to address these challenges. This assessment includes longitudinal phenome measures, such as the blood proteome and metabolome, gut microbiome composition and function, and lifestyle and behaviour through wearables and questionnaires. Here, we review ongoing large-scale genomics and longitudinal phenomics efforts and the powerful insights they provide into wellness. We describe our vision for the transformation of the current health care from disease-oriented to data-driven, wellness-oriented and personalized population health.
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Affiliation(s)
- James T Yurkovich
- Phenome Health, Seattle, WA, USA
- Center for Phenomic Health, The Buck Institute for Research on Aging, Novato, CA, USA
- Department of Bioengineering, University of Texas at Dallas, Richardson, TX, USA
| | - Simon J Evans
- Phenome Health, Seattle, WA, USA
- Center for Phenomic Health, The Buck Institute for Research on Aging, Novato, CA, USA
| | - Noa Rappaport
- Center for Phenomic Health, The Buck Institute for Research on Aging, Novato, CA, USA
- Institute for Systems Biology, Seattle, WA, USA
| | - Jeffrey L Boore
- Phenome Health, Seattle, WA, USA
- Center for Phenomic Health, The Buck Institute for Research on Aging, Novato, CA, USA
| | - Jennifer C Lovejoy
- Phenome Health, Seattle, WA, USA
- Center for Phenomic Health, The Buck Institute for Research on Aging, Novato, CA, USA
- Institute for Systems Biology, Seattle, WA, USA
| | - Nathan D Price
- Institute for Systems Biology, Seattle, WA, USA
- Thorne HealthTech, New York, NY, USA
- Department of Bioengineering, University of Washington, Seattle, WA, USA
- Paul G. Allen School of Computer Science & Engineering, University of Washington, Seattle, WA, USA
| | - Leroy E Hood
- Phenome Health, Seattle, WA, USA.
- Center for Phenomic Health, The Buck Institute for Research on Aging, Novato, CA, USA.
- Institute for Systems Biology, Seattle, WA, USA.
- Department of Bioengineering, University of Washington, Seattle, WA, USA.
- Paul G. Allen School of Computer Science & Engineering, University of Washington, Seattle, WA, USA.
- Department of Immunology, University of Washington, Seattle, WA, USA.
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9
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Wang Z, Yan F, Yu Z, Cao H, Ma Z, YeErKenTai Z, Li Z, Han Y, Zhu Z. Fully Transient 3D Origami Paper-Based Ammonia Gas Sensor Obtained by Facile MXene Spray Coating. ACS Sens 2024; 9:1447-1457. [PMID: 38412069 DOI: 10.1021/acssensors.3c02558] [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: 02/29/2024]
Abstract
Developing high-performance chemiresistive gas sensors with mechanical compliance for environmental or health-related biomarker monitoring has recently drawn increasing research attention. Among them, two-dimensional MXene materials hold great potential for room-temperature hazardous gas (e.g., NH3) monitoring regardless of the complicated fabrication process, insufficient 2D/3D flexibilities, and poor environmental sustainability. Herein, a Ti3C2Tx MXene/gelatin ink was developed for patterning electrodes through a facile spray coating. Particularly, the patterned Ti3C2Tx-based coating exhibited good adhesion on the paper substrate against repeated peeling-off and excellent mechanical flexibility against 1000 cyclic stretching. The porous morphology of the coating facilitated the NH3 sensing ability. As a result, the 2D kirigami-shaped NH3 sensor exhibited a good response of 7% to 50 ppm of NH3 with detectable concentrations ranging from 5-500 ppm, decent selectivity over interferences, etc., which could be well-maintained even at 50% stretched state. In addition, with the help of mechanically guided compressive buckling, 3D mesostructured MXene origamis could be obtained, holding promise for detecting the coming direction and height distribution of hazardous gas, e.g., the NH3. More importantly, the as-fabricated MXene/gelatin origami paper could be fully degraded in PBS/H2O2/cellulase solution within 19 days, demonstrating its potential as a high-performance, shape morphable, and environmentally friendly wearable gas sensor.
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Affiliation(s)
- Zifeng Wang
- School of Health Science and Engineering, University of Shanghai for Science and Technology, 516 Jungong Road, Shanghai 200093, China
| | - Feng Yan
- School of Health Science and Engineering, University of Shanghai for Science and Technology, 516 Jungong Road, Shanghai 200093, China
| | - Zhichao Yu
- School of Health Science and Engineering, University of Shanghai for Science and Technology, 516 Jungong Road, Shanghai 200093, China
| | - Huina Cao
- School of Health Science and Engineering, University of Shanghai for Science and Technology, 516 Jungong Road, Shanghai 200093, China
| | - Zhanying Ma
- School of Health Science and Engineering, University of Shanghai for Science and Technology, 516 Jungong Road, Shanghai 200093, China
| | - ZuNa YeErKenTai
- School of Health Science and Engineering, University of Shanghai for Science and Technology, 516 Jungong Road, Shanghai 200093, China
| | - Zhanhong Li
- School of Health Science and Engineering, University of Shanghai for Science and Technology, 516 Jungong Road, Shanghai 200093, China
| | - Yutong Han
- School of Health Science and Engineering, University of Shanghai for Science and Technology, 516 Jungong Road, Shanghai 200093, China
| | - Zhigang Zhu
- School of Health Science and Engineering, University of Shanghai for Science and Technology, 516 Jungong Road, Shanghai 200093, China
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10
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Mortazavi SMJ, Said-Salman I, Mortazavi AR, El Khatib S, Sihver L. How the adaptation of the human microbiome to harsh space environment can determine the chances of success for a space mission to Mars and beyond. Front Microbiol 2024; 14:1237564. [PMID: 38390219 PMCID: PMC10881706 DOI: 10.3389/fmicb.2023.1237564] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2023] [Accepted: 12/05/2023] [Indexed: 02/24/2024] Open
Abstract
The ability of human cells to adapt to space radiation is essential for the well-being of astronauts during long-distance space expeditions, such as voyages to Mars or other deep space destinations. However, the adaptation of the microbiomes should not be overlooked. Microorganisms inside an astronaut's body, or inside the space station or other spacecraft, will also be exposed to radiation, which may induce resistance to antibiotics, UV, heat, desiccation, and other life-threatening factors. Therefore, it is essential to consider the potential effects of radiation not only on humans but also on their microbiomes to develop effective risk reduction strategies for space missions. Studying the human microbiome in space missions can have several potential benefits, including but not limited to a better understanding of the major effects space travel has on human health, developing new technologies for monitoring health and developing new radiation therapies and treatments. While radioadaptive response in astronauts' cells can lead to resistance against high levels of space radiation, radioadaptive response in their microbiome can lead to resistance against UV, heat, desiccation, antibiotics, and radiation. As astronauts and their microbiomes compete to adapt to the space environment. The microorganisms may emerge as the winners, leading to life-threatening situations due to lethal infections. Therefore, understanding the magnitude of the adaptation of microorganisms before launching a space mission is crucial to be able to develop effective strategies to mitigate the risks associated with radiation exposure. Ensuring the safety and well-being of astronauts during long-duration space missions and minimizing the risks linked with radiation exposure can be achieved by adopting this approach.
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Affiliation(s)
- Seyed Mohammad Javad Mortazavi
- Ionizing and non-ionizing radiation protection research center (INIRPRC), Shiraz University of Medical Sciences, Shiraz, Iran
| | - Ilham Said-Salman
- Department of Biological and Chemical Sciences, School of Arts & Sciences, Lebanese International University, Saida, Lebanon
- Department of Biological and Chemical Sciences, International University of Beirut, Beirut, Lebanon
| | | | - Sami El Khatib
- Department of Biomedical Sciences, School of Arts and Sciences, Lebanese International University, Beirut, Lebanon
- Center for Applied Mathematics and Bioinformatics (CAMB) at Gulf University for Science and Technology, Kuwait City, Kuwait
| | - Lembit Sihver
- Department of Radiation Dosimetry, Nuclear Physics Institute (NPI) of the Czech Academy of Sciences (CAS), Prague, Czechia
- Department of Radiation Physics, Technische Universität Wien Atominstitut, Vienna, Austria
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11
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Abstract
The monitoring of vital signs in patients undergoing anesthesia began with the very first case of anesthesia and has evolved alongside the development of anesthesiology ever since. Patient monitoring started out as a manually performed, intermittent, and qualitative assessment of the patient's general well-being in the operating room. In its evolution, patient monitoring development has responded to the clinical need, for example, when critical incident studies in the 1980s found that many anesthesia adverse events could be prevented by improved monitoring, especially respiratory monitoring. It also facilitated and perhaps even enabled increasingly complex surgeries in increasingly higher-risk patients. For example, it would be very challenging to perform and provide anesthesia care during some of the very complex cardiovascular surgeries that are almost routine today without being able to simultaneously and reliably monitor multiple pressures in a variety of places in the circulatory system. Of course, anesthesia patient monitoring itself is enabled by technological developments in the world outside of the operating room. Throughout its history, anesthesia patient monitoring has taken advantage of advancements in material science (when nonthrombogenic polymers allowed the design of intravascular catheters, for example), in electronics and transducers, in computers, in displays, in information technology, and so forth. Slower product life cycles in medical devices mean that by carefully observing technologies such as consumer electronics, including user interfaces, it is possible to peek ahead and estimate with confidence the foundational technologies that will be used by patient monitors in the near future. Just as the discipline of anesthesiology has, the patient monitoring that accompanies it has come a long way from its beginnings in the mid-19th century. Extrapolating from careful observations of the prevailing trends that have shaped anesthesia patient monitoring historically, patient monitoring in the future will use noncontact technologies, will predict the trajectory of a patient's vital signs, will add regional vital signs to the current systemic ones, and will facilitate directed and supervised anesthesia care over the broader scope that anesthesia will be responsible for.
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Affiliation(s)
- Kai Kuck
- From the Departments of Anesthesiology and Biomedical Engineering, University of Utah, Salt Lake City, Utah
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12
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Ok J, Park S, Jung YH, Kim TI. Wearable and Implantable Cortisol-Sensing Electronics for Stress Monitoring. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2024; 36:e2211595. [PMID: 36917076 DOI: 10.1002/adma.202211595] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/12/2022] [Revised: 02/27/2023] [Indexed: 06/18/2023]
Abstract
Cortisol is a steroid hormone that is released from the body in response to stress. Although a moderate level of cortisol secretion can help the body maintain homeostasis, excessive secretion can cause various diseases, such as depression and anxiety. Conventional methods for cortisol measurement undergo procedures that limit continuous monitoring, typically collecting samples of bodily fluids, followed by separate analysis in a laboratory setting that takes several hours. Thus, recent studies demonstrate wearable, miniaturized sensors integrated with electronic modules that enable wireless real-time analysis. Here, the primary focus is on wearable and implantable electronic devices that continuously measure cortisol concentration. Diverse types of cortisol-sensing techniques, such as antibody-, DNA-aptamer-, and molecularly imprinted polymer-based sensors, as well as wearable and implantable devices that aim to continuously monitor cortisol in a minimally invasive fashion are discussed. In addition to the cortisol monitors that directly measure stress levels, other schemes that indirectly measure stress, such as electrophysiological signals and sweat are also summarized. Finally, the challenges and future directions in stress monitoring and management electronics are reviewed.
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Affiliation(s)
- Jehyung Ok
- School of Chemical Engineering, Sungkyunkwan University (SKKU), Suwon, 16419, Republic of Korea
| | - Sumin Park
- Department of Electronic Engineering, Hanyang University, Seoul, 04763, Republic of Korea
| | - Yei Hwan Jung
- Department of Electronic Engineering, Hanyang University, Seoul, 04763, Republic of Korea
| | - Tae-Il Kim
- School of Chemical Engineering, Sungkyunkwan University (SKKU), Suwon, 16419, Republic of Korea
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13
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Selvaskandan H, Gee PO, Seethapathy H. Technological Innovations to Improve Patient Engagement in Nephrology. ADVANCES IN KIDNEY DISEASE AND HEALTH 2024; 31:28-36. [PMID: 38403391 DOI: 10.1053/j.akdh.2023.11.001] [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: 05/22/2023] [Revised: 11/08/2023] [Accepted: 11/10/2023] [Indexed: 02/27/2024]
Abstract
Technological innovation has accelerated exponentially over the last 2 decades. From the rise of smartphones and social media in the early 2000s to the mainstream accessibility of artificial intelligence (AI) in 2023, digital advancements have transformed the way we live and work. These innovations have permeated health care, covering a spectrum of applications from virtual reality training platforms to AI-powered clinical decision support tools. In this review, we explore fascinating recent innovations that have and can facilitate patient engagement in nephrology. These include integrated care mobile applications, wearable health monitoring tools, virtual/augmented reality consultation and education platforms, AI-powered appointment booking systems, and patient information tools. We also discuss potential pitfalls in implementation and paradigms to adopt that may protect patients from unintended consequences of being cared for in a digitalized health care system.
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Affiliation(s)
- Haresh Selvaskandan
- Mayer IgA Nephropathy Laboratories, Department of Cardiovascular Sciences, University of Leicester, Leicester, UK; John Walls Renal Unit, University Hospitals of Leicester NHS Trust, Leicester, UK.
| | | | - Harish Seethapathy
- Division of Nephrology, Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA
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14
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Esmaeilzadeh P. Older Adults' Perceptions About Using Intelligent Toilet Seats Beyond Traditional Care: Web-Based Interview Survey. JMIR Mhealth Uhealth 2023; 11:e46430. [PMID: 38039065 PMCID: PMC10724815 DOI: 10.2196/46430] [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: 02/11/2023] [Revised: 10/19/2023] [Accepted: 11/06/2023] [Indexed: 12/02/2023] Open
Abstract
BACKGROUND In contemporary society, age tech (age technology) represents a significant advancement in health care aimed at enhancing patient engagement, ensuring sustained independence, and promoting quality of life for older people. One innovative form of age tech is the intelligent toilet seat, which is designed to collect, analyze, and provide insights based on toileting logs and excreta data. Understanding how older people perceive and interact with such technology can offer invaluable insights to researchers, technology developers, and vendors. OBJECTIVE This study examined older adults' perspectives regarding the use of intelligent toilet seats. Through a qualitative methodology, this research aims to unearth the nuances of older people's opinions, shedding light on their preferences, concerns, and potential barriers to adoption. METHODS Data were collected using a web-based interview survey distributed on Amazon Mechanical Turk. The analyzed data set comprised 174 US-based individuals aged ≥65 years who voluntarily participated in this study. The qualitative data were carefully analyzed using NVivo (Lumivero) based on detailed content analysis, ensuring that emerging themes were coded and classified based on the conceptual similarities in the respondents' narratives. RESULTS The analysis revealed 5 dominant themes encompassing the opinions of aging adults. The perceived benefits and advantages of using the intelligent toilet seat were grouped into 3 primary themes: health-related benefits including the potential for early disease detection, continuous health monitoring, and seamless connection to health care insights. Technology-related advantages include the noninvasive nature of smart toilet seats and leveraging unique and innovative data collection and analysis technology. Use-related benefits include ease of use, potential for multiple users, and cost reduction owing to the reduced need for frequent clinical visits. Conversely, the concerns and perceived risks were classified into 2 significant themes: psychological concerns, which included concerns about embarrassment and aging-related stereotypes, and the potential emotional impact of constant health monitoring. Technical performance risks include concerns centered on privacy and security, device reliability, data accuracy, potential malfunctions, and the implications of false positives or negatives. CONCLUSIONS The decision of older adults to incorporate intelligent toilet seats into their daily lives depends on myriad factors. Although the potential health and technological benefits are evident, valid concerns that need to be addressed remain. To foster widespread adoption, it is imperative to enhance the advantages while simultaneously addressing and mitigating the identified risks. This balanced approach will pave the way for a more holistic integration of smart health care devices into the routines of the older population, ensuring that they reap the full benefits of age tech advancements.
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Affiliation(s)
- Pouyan Esmaeilzadeh
- Department of Information Systems and Business Analytics, College of Business, Florida International University, Miami, FL, United States
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15
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Akbari Nakhjavani S, Tokyay BK, Soylemez C, Sarabi MR, Yetisen AK, Tasoglu S. Biosensors for prostate cancer detection. Trends Biotechnol 2023; 41:1248-1267. [PMID: 37147246 DOI: 10.1016/j.tibtech.2023.04.001] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2022] [Revised: 03/22/2023] [Accepted: 04/04/2023] [Indexed: 05/07/2023]
Abstract
Prostate cancer (PC) is one of the most common tumors and a leading cause of mortality among men, resulting in ~375 000 deaths annually worldwide. Various analytical methods have been designed for quantitative and rapid detection of PC biomarkers. Electrochemical (EC), optical, and magnetic biosensors have been developed to detect tumor biomarkers in clinical and point-of-care (POC) settings. Although POC biosensors have shown potential for detection of PC biomarkers, some limitations, such as the sample preparation, should be considered. To tackle such shortcomings, new technologies have been utilized for development of more practical biosensors. Here, biosensing platforms for the detection of PC biomarkers such as immunosensors, aptasensors, genosensors, paper-based devices, microfluidic systems, and multiplex high-throughput platforms, are discussed.
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Affiliation(s)
- Sattar Akbari Nakhjavani
- Department of Mechanical Engineering, Koç University, Sariyer, Istanbul 34450, Turkey; Koç University Translational Medicine Research Center (KUTTAM), Koç University, Istanbul 34450, Turkey
| | - Begum K Tokyay
- Koç University Translational Medicine Research Center (KUTTAM), Koç University, Istanbul 34450, Turkey; Department of Biomedical Sciences and Engineering, Koç University, 34450 Istanbul, Turkey
| | - Cansu Soylemez
- Department of Biomedical Sciences and Engineering, Koç University, 34450 Istanbul, Turkey
| | - Misagh R Sarabi
- Department of Biomedical Sciences and Engineering, Koç University, 34450 Istanbul, Turkey; Physical Intelligence Department, Max Planck Institute for Intelligent Systems, Stuttgart, Germany 70569
| | - Ali K Yetisen
- Department of Chemical Engineering, Imperial College, London SW7 2AZ, UK
| | - Savas Tasoglu
- Department of Mechanical Engineering, Koç University, Sariyer, Istanbul 34450, Turkey; Koç University Translational Medicine Research Center (KUTTAM), Koç University, Istanbul 34450, Turkey; Physical Intelligence Department, Max Planck Institute for Intelligent Systems, Stuttgart, Germany 70569; Koç University Arçelik Research Center for Creative Industries (KUAR), Koç University, Istanbul 34450, Turkey; Boğaziçi Institute of Biomedical Engineering, Boğaziçi University, Istanbul 34684, Turkey.
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16
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Chen J, Ling Y, Yuan X, He Y, Li S, Wang G, Zhang Z, Wang G. Highly Sensitive Detection of Formaldehyde by Laser-Induced Graphene-Coated Silver Nanoparticles Electrochemical Sensing Electrodes. LANGMUIR : THE ACS JOURNAL OF SURFACES AND COLLOIDS 2023; 39:12762-12773. [PMID: 37642387 DOI: 10.1021/acs.langmuir.3c01472] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/31/2023]
Abstract
Formaldehyde (HCHO) poses a grave threat to human health because of its toxicity, but its accurate, sensitive, and rapid detection in aqueous solutions remains a major challenge. This study proposes a novel electrochemical sensor composed of a graphene-based electrode that is prepared via laser induction technology. The precursor material, polyimide, is modified via the metal ion exchange method, and the detective electrode is coated with graphene and silver nanoparticles. And the special structure of graphene-coated Ag was demonstrated using scanning electron microscopy (SEM) and high-resolution transmission electron microscopy (HRTEM), and X-ray diffraction (XRD), Fourier transform infrared (FT-IR), and X-ray photoelectron spectroscopy (XPS) results show that graphene provides more sites for Ag NRs to be exposed and increases the surface area of contact between the solution and the detection object. In addition, differential pulse voltammetry (DPV) analysis exhibits high linearity over the HCHO concentration range from 0.05 to 5 μg/mL, with a detection limit of 0.011 μg/mL (S/N = 3). The Ag NPs in the electrochemical reaction will adsorb the intermediate •CO and •OH, catalyze their combination, and finally convert to CO2 and H2O, respectively. A microdetection device, specially designed for use with commercial micro-workstations, is employed to fully demonstrate the practical application of the electrode, which paves a way for developing formaldehyde electrochemical sensors.
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Affiliation(s)
- Jianyue Chen
- School of Chemical Engineering, Sichuan University, Chengdu 610065, China
| | - Yunhan Ling
- Laboratory of Advanced Materials, School of Materials Sciences and Engineering, Tsinghua University, Beijing 100084, China
| | - Xiaoming Yuan
- Laboratory of Advanced Materials, School of Materials Sciences and Engineering, Tsinghua University, Beijing 100084, China
| | - Yuyang He
- Laboratory of Advanced Materials, School of Materials Sciences and Engineering, Tsinghua University, Beijing 100084, China
| | - Shilin Li
- Laboratory of Advanced Materials, School of Materials Sciences and Engineering, Tsinghua University, Beijing 100084, China
| | - Guan Wang
- School of Chemical Engineering, Sichuan University, Chengdu 610065, China
| | - Zhengjun Zhang
- Laboratory of Advanced Materials, School of Materials Sciences and Engineering, Tsinghua University, Beijing 100084, China
| | - Guixin Wang
- School of Chemical Engineering, Sichuan University, Chengdu 610065, China
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17
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Sarabi MR, Karagoz AA, Yetisen AK, Tasoglu S. 3D-Printed Microrobots: Translational Challenges. MICROMACHINES 2023; 14:1099. [PMID: 37374684 DOI: 10.3390/mi14061099] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/23/2023] [Revised: 05/18/2023] [Accepted: 05/21/2023] [Indexed: 06/29/2023]
Abstract
The science of microrobots is accelerating towards the creation of new functionalities for biomedical applications such as targeted delivery of agents, surgical procedures, tracking and imaging, and sensing. Using magnetic properties to control the motion of microrobots for these applications is emerging. Here, 3D printing methods are introduced for the fabrication of microrobots and their future perspectives are discussed to elucidate the path for enabling their clinical translation.
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Affiliation(s)
| | - Ahmet Agah Karagoz
- School of Biomedical Sciences and Engineering, Koç University, Istanbul 34450, Türkiye
- Koç University Is Bank Artificial Intelligence Lab (KUIS AI Lab), Koç University, Istanbul 34450, Türkiye
| | - Ali K Yetisen
- Department of Chemical Engineering, Imperial College London, London SW7 2AZ, UK
| | - Savas Tasoglu
- Koç University Is Bank Artificial Intelligence Lab (KUIS AI Lab), Koç University, Istanbul 34450, Türkiye
- School of Mechanical Engineering, Koç University, Istanbul 34450, Türkiye
- Koç University Translational Medicine Research Center (KUTTAM), Koç University, Istanbul 34450, Türkiye
- Koç University Arçelik Research Center for Creative Industries (KUAR), Koç University, Istanbul 34450, Türkiye
- Boğaziçi Institute of Biomedical Engineering, Boğaziçi University, Istanbul 34684, Türkiye
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18
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Kim EJ, Kim JY. The Metaverse for Healthcare: Trends, Applications, and Future Directions of Digital Therapeutics for Urology. Int Neurourol J 2023; 27:S3-12. [PMID: 37280754 DOI: 10.5213/inj.2346108.054] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2023] [Accepted: 05/16/2023] [Indexed: 06/08/2023] Open
Abstract
In recent years, the emergence of digital therapeutics as a novel approach to managing conditions has garnered significant attention. This approach involves using evidence-based therapeutic interventions that are facilitated by high-quality software programs to treat, manage, or prevent medical conditions. The incorporation of digital therapeutics into the Metaverse has increased the feasibility of their implementation and application in all areas of medical services. In urology, substantial digital therapeutics are being produced and researched, including mobile apps, bladder devices, pelvic floor muscle trainers, smart toilet systems, mixed reality-guided training and surgery, and training and telemedicine for urological consultations. The purpose of this review article is to provide a comprehensive overview of the current impact of the Metaverse on the field of digital therapeutics and identify its current trends, applications, and future perspectives in the field of urology.
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Affiliation(s)
- Eun Joung Kim
- Culture Contents Technology Institute, Gachon University, Seongnam, Korea
| | - Jung Yoon Kim
- Department of Game Media, College of Future Industry, Gachon University, Seongnam, Korea
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19
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Kim HH, Moon OJ, Seol YH, Lee J. A simple urine test by 3D-plus-3D immunoassay guides precise in vitro cancer diagnosis. Bioeng Transl Med 2023; 8:e10489. [PMID: 37206218 PMCID: PMC10189436 DOI: 10.1002/btm2.10489] [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: 08/25/2022] [Revised: 12/26/2022] [Accepted: 12/29/2022] [Indexed: 01/19/2023] Open
Abstract
Although a variety of urinary cancer markers are available for in vitro diagnosis, inherent problems of urine environment-containing various inorganic/organic ions/molecules that vary in concentration over a 20-fold range or more and significantly attenuate antibody avidity for markers-render conventional immunoassays unsuitable, remaining unresolved and a major challenge. Here we developed a 3D-plus-3D (3p3) immunoassay method, based on a single-step urinary marker detection by 3D-antibody probes, which are free of steric hindrance and capable of omnidirectional capture of markers in a 3D solution. The 3p3 immunoassay showed an excellent performance in the diagnosis of prostate cancer (PCa) through detecting PCa-specific urinary engrailed-2 protein, demonstrating 100% sensitivity and 100% specificity with the urine specimens of PCa-related and other related disease patients and healthy individuals. This innovative approach holds a great potential in opening up a novel clinical route for precise in vitro cancer diagnosis and also pushing urine immunoassay closer to more widespread adoption.
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Affiliation(s)
- Hye Hyun Kim
- Department of Chemical and Biological Engineering, College of EngineeringKorea UniversitySeoulRepublic of Korea
| | - Ok Jeong Moon
- Department of Chemical and Biological Engineering, College of EngineeringKorea UniversitySeoulRepublic of Korea
| | - Yong Hwan Seol
- Department of Chemical and Biological Engineering, College of EngineeringKorea UniversitySeoulRepublic of Korea
| | - Jeewon Lee
- Department of Chemical and Biological Engineering, College of EngineeringKorea UniversitySeoulRepublic of Korea
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20
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Ahmadpour A, Isgor PK, Ural B, Eren BN, Sarabi MR, Muradoglu M, Tasoglu S. Microneedle arrays integrated with microfluidic systems: Emerging applications and fluid flow modeling. BIOMICROFLUIDICS 2023; 17:021501. [PMID: 37153866 PMCID: PMC10162023 DOI: 10.1063/5.0121578] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/18/2022] [Accepted: 02/15/2023] [Indexed: 05/10/2023]
Abstract
Microneedle arrays are patches of needles at micro- and nano-scale, which are competent and versatile technologies that have been merged with microfluidic systems to construct more capable devices for biomedical applications, such as drug delivery, wound healing, biosensing, and sampling body fluids. In this paper, several designs and applications are reviewed. In addition, modeling approaches used in microneedle designs for fluid flow and mass transfer are discussed, and the challenges are highlighted.
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Affiliation(s)
- Abdollah Ahmadpour
- Department of Mechanical Engineering, College of Engineering, Koç University, Türkiye
| | - Pelin Kubra Isgor
- Department of Biomedical Sciences and Engineering, College of Engineering, Koç University, Türkiye
| | - Berk Ural
- Department of Mechanical Engineering, College of Engineering, Koç University, Türkiye
| | - Busra Nimet Eren
- Department of Mechanical Engineering, College of Engineering, Koç University, Türkiye
| | | | - Metin Muradoglu
- Department of Mechanical Engineering, College of Engineering, Koç University, Türkiye
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21
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Ge TJ, Rahimzadeh VN, Mintz K, Park WG, Martinez-Martin N, Liao JC, Park SM. Passive monitoring by smart toilets for precision health. Sci Transl Med 2023; 15:eabk3489. [PMID: 36724240 DOI: 10.1126/scitranslmed.abk3489] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Abstract
Smart toilets are a key tool for enabling precision health monitoring in the home, but such passive monitoring has ethical considerations.
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Affiliation(s)
- T Jessie Ge
- Department of Urology, Stanford University School of Medicine, Stanford, CA 94305, USA
| | | | - Kevin Mintz
- Stanford Center for Biomedical Ethics, Stanford University, Stanford, CA 94305, USA
| | - Walter G Park
- Division of Gastroenterology and Hepatology, Department of Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA
| | | | - Joseph C Liao
- Department of Urology, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Seung-Min Park
- Department of Urology, Stanford University School of Medicine, Stanford, CA 94305, USA.,Department of Radiology, Stanford University School of Medicine, Stanford, CA 94305, USA.,Molecular Imaging Program at Stanford, Stanford University School of Medicine, CA 94305 USA
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22
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Ibrahim NFA, Sabani N, Johari S, Manaf AA, Wahab AA, Zakaria Z, Noor AM. A Comprehensive Review of the Recent Developments in Wearable Sweat-Sensing Devices. SENSORS (BASEL, SWITZERLAND) 2022; 22:7670. [PMID: 36236769 PMCID: PMC9573257 DOI: 10.3390/s22197670] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/23/2022] [Revised: 09/26/2022] [Accepted: 10/02/2022] [Indexed: 06/16/2023]
Abstract
Sweat analysis offers non-invasive real-time on-body measurement for wearable sensors. However, there are still gaps in current developed sweat-sensing devices (SSDs) regarding the concerns of mixing fresh and old sweat and real-time measurement, which are the requirements to ensure accurate the measurement of wearable devices. This review paper discusses these limitations by aiding model designs, features, performance, and the device operation for exploring the SSDs used in different sweat collection tools, focusing on continuous and non-continuous flow sweat analysis. In addition, the paper also comprehensively presents various sweat biomarkers that have been explored by earlier works in order to broaden the use of non-invasive sweat samples in healthcare and related applications. This work also discusses the target analyte's response mechanism for different sweat compositions, categories of sweat collection devices, and recent advances in SSDs regarding optimal design, functionality, and performance.
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Affiliation(s)
- Nur Fatin Adini Ibrahim
- Faculty of Electronic Engineering & Technology, Universiti Malaysia Perlis, Arau 02600, Malaysia
| | - Norhayati Sabani
- Faculty of Electronic Engineering & Technology, Universiti Malaysia Perlis, Arau 02600, Malaysia
- Center of Excellance Micro System Technology, Universiti Malaysia Perlis, Arau 02600, Malaysia
| | - Shazlina Johari
- Faculty of Electronic Engineering & Technology, Universiti Malaysia Perlis, Arau 02600, Malaysia
- Center of Excellance Micro System Technology, Universiti Malaysia Perlis, Arau 02600, Malaysia
| | - Asrulnizam Abd Manaf
- Collaborative Microelectronic Design Excellence Centre, Universiti Sains Malaysia, Gelugor 11800, Malaysia
| | - Asnida Abdul Wahab
- Department of Biomedical Engineering and Health Sciences, Universiti Teknologi Malaysia, Johor Bahru 81310, Malaysia
| | - Zulkarnay Zakaria
- Faculty of Electronic Engineering & Technology, Universiti Malaysia Perlis, Arau 02600, Malaysia
- Sports Engineering Research Center, Universiti Malaysia Perlis, Arau 02600, Malaysia
| | - Anas Mohd Noor
- Faculty of Electronic Engineering & Technology, Universiti Malaysia Perlis, Arau 02600, Malaysia
- Center of Excellance Micro System Technology, Universiti Malaysia Perlis, Arau 02600, Malaysia
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23
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Abstract
Microrobots have attracted the attention of scientists owing to their unique features to accomplish tasks in hard-to-reach sites in the human body. Microrobots can be precisely actuated and maneuvered individually or in a swarm for cargo delivery, sampling, surgery, and imaging applications. In addition, microrobots have found applications in the environmental sector (e.g., water treatment). Besides, recent advancements of three-dimensional (3D) printers have enabled the high-resolution fabrication of microrobots with a faster design-production turnaround time for users with limited micromanufacturing skills. Here, the latest end applications of 3D printed microrobots are reviewed (ranging from environmental to biomedical applications) along with a brief discussion over the feasible actuation methods (e.g., on- and off-board), and practical 3D printing technologies for microrobot fabrication. In addition, as a future perspective, we discussed the potential advantages of integration of microrobots with smart materials, and conceivable benefits of implementation of artificial intelligence (AI), as well as physical intelligence (PI). Moreover, in order to facilitate bench-to-bedside translation of microrobots, current challenges impeding clinical translation of microrobots are elaborated, including entry obstacles (e.g., immune system attacks) and cumbersome standard test procedures to ensure biocompatibility. Microbots have attracted attention due to an ability to reach places and perform tasks which are not possible with conventional techniques in a wide range of applications. Here, the authors review the recent work in the field on the fabrication, application and actuation of 3D printed microbots offering a view of the direction of future microbot research.
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24
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Sarabi MR, Yigci D, Alseed MM, Mathyk BA, Ata B, Halicigil C, Tasoglu S. Disposable Paper-Based Microfluidics for Fertility Testing. iScience 2022; 25:104986. [PMID: 36105592 PMCID: PMC9465368 DOI: 10.1016/j.isci.2022.104986] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Abstract
Fifteen percent of couples of reproductive age suffer from infertility globally and the burden of infertility disproportionately impacts residents of developing countries. Assisted reproductive technologies (ARTs), including in vitro fertilization (IVF) and intracytoplasmic sperm injection (ICSI), have been successful in overcoming various reasons for infertility including borderline and severe male factor infertility which consists of 20%–30% of all infertile cases. Approximately half of male infertility cases stem from suboptimal sperm parameters. Therefore, healthy/normal sperm enrichment and sorting remains crucial in advancing reproductive medicine. Microfluidic technologies have emerged as promising tools to develop in-home rapid fertility tests and point-of-care (POC) diagnostic tools. Here, we review advancements in fabrication methods for paper-based microfluidic devices and their emerging fertility testing applications assessing sperm concentration, sperm motility, sperm DNA analysis, and other sperm functionalities, and provide a glimpse into future directions for paper-based fertility microfluidic systems. Paper-based technologies are emerging to develop in-home rapid fertility tests Fabrication methods for paper-based microfluidic devices are presented Emerging disposable paper-based fertility testing applications are reviewed
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Affiliation(s)
| | - Defne Yigci
- School of Medicine, Koç University, Istanbul, Türkiye 34450
| | - M. Munzer Alseed
- Boğaziçi Institute of Biomedical Engineering, Boğaziçi University, Istanbul, Türkiye 34684
| | - Begum Aydogan Mathyk
- Department of Obstetrics and Gynecology, HCA Healthcare, University of South Florida Morsani College of Medicine GME, Brandon Regional Hospital, Florida 33511, USA
| | - Baris Ata
- School of Medicine, Koç University, Istanbul, Türkiye 34450
- ART Fertility Clinics, Dubai, United Arab Emirates 337-1500
| | - Cihan Halicigil
- Yale School of Medicine, Yale University, Connecticut 06520, USA
| | - Savas Tasoglu
- School of Mechanical Engineering, Koç University, Istanbul, Türkiye 34450
- Boğaziçi Institute of Biomedical Engineering, Boğaziçi University, Istanbul, Türkiye 34684
- Koç University Translational Medicine Research Center (KUTTAM), Koç University, Istanbul, Türkiye 34450
- Koç University Arçelik Research Center for Creative Industries (KUAR), Koç University, Istanbul, Türkiye 34450
- Koç University Is Bank Artificial Intelligence Lab (KUIS AI Lab), Koç University, Istanbul, Türkiye 34450
- Corresponding author
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25
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Rezapour Sarabi M, Nakhjavani SA, Tasoglu S. 3D-Printed Microneedles for Point-of-Care Biosensing Applications. MICROMACHINES 2022; 13:1099. [PMID: 35888916 PMCID: PMC9318629 DOI: 10.3390/mi13071099] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/17/2022] [Revised: 07/08/2022] [Accepted: 07/11/2022] [Indexed: 01/06/2023]
Abstract
Microneedles (MNs) are an emerging technology for user-friendly and minimally invasive injection, offering less pain and lower tissue damage in comparison to conventional needles. With their ability to extract body fluids, MNs are among the convenient candidates for developing biosensing setups, where target molecules/biomarkers are detected by the biosensor using the sample collected with the MNs. Herein, we discuss the 3D printing of microneedle arrays (MNAs) toward enabling point-of-care (POC) biosensing applications.
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Affiliation(s)
- Misagh Rezapour Sarabi
- Mechanical Engineering Department, School of Engineering, Koç University, Istanbul 34450, Turkey; (M.R.S.); (S.A.N.)
| | - Sattar Akbari Nakhjavani
- Mechanical Engineering Department, School of Engineering, Koç University, Istanbul 34450, Turkey; (M.R.S.); (S.A.N.)
- Koç University Translational Medicine Research Center (KUTTAM), Koç University, Istanbul 34450, Turkey
| | - Savas Tasoglu
- Mechanical Engineering Department, School of Engineering, Koç University, Istanbul 34450, Turkey; (M.R.S.); (S.A.N.)
- Koç University Translational Medicine Research Center (KUTTAM), Koç University, Istanbul 34450, Turkey
- Physical Intelligence Department, Max Planck Institute for Intelligent Systems, 70569 Stuttgart, Germany
- Koç University Arçelik Research Center for Creative Industries (KUAR), Koç University, Istanbul 34450, Turkey
- Boğaziçi Institute of Biomedical Engineering, Boğaziçi University, Istanbul 34684, Turkey
- Koç University İş Bank Artificial Intelligence Lab (KUIS AI Lab), Koç University, Sariyer, Istanbul 34450, Turkey
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Abstract
Advances in microfabrication and biomaterials have enabled the development of microfluidic chips for studying tissue and organ models. While these platforms have been developed primarily for modeling human diseases, they are also used to uncover cellular and molecular mechanisms through in vitro studies, especially in the neurovascular system, where physiological mechanisms and three-dimensional (3D) architecture are difficult to reconstruct via conventional assays. An extracellular matrix (ECM) model with a stable structure possessing the ability to mimic the natural extracellular environment of the cell efficiently is useful for tissue engineering applications. Conventionally used techniques for this purpose, for example, Matrigels, have drawbacks of owning complex fabrication procedures, in some cases not efficient enough in terms of functionality and expenses. Here, we proposed a fabrication protocol for a GelMA hydrogel, which has shown structural stability and the ability to imitate the natural environment of the cell accurately, inside a microfluidic chip utilizing co-culturing of two human cell lines. The chemical composition of the synthesized GelMA was identified by Fourier transform infrared spectrophotometry (FTIR), its surface morphology was observed by field emission electron microscopy (FESEM), and the structural properties were analyzed by atomic force microscopy (AFM). The swelling behavior of the hydrogel in the microfluidic chip was imaged, and its porosity was examined for 72 h by tracking cell localization using immunofluorescence. GelMA exhibited the desired biomechanical properties, and the viability of cells in both platforms was more than 80% for seven days. Furthermore, GelMA was a viable platform for 3D cell culture studies and was structurally stable over long periods, even when prepared by photopolymerization in a microfluidic platform. This work demonstrated a viable strategy to conduct co-culturing experiments as well as modeling invasion and migration events. This microfluidic assay may have application in drug delivery and dosage optimization studies.
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Rezapour Sarabi M, Alseed MM, Karagoz AA, Tasoglu S. Machine Learning-Enabled Prediction of 3D-Printed Microneedle Features. BIOSENSORS 2022; 12:bios12070491. [PMID: 35884294 PMCID: PMC9313436 DOI: 10.3390/bios12070491] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Subscribe] [Scholar Register] [Received: 05/20/2022] [Revised: 06/29/2022] [Accepted: 07/04/2022] [Indexed: 05/22/2023]
Abstract
Microneedles (MNs) introduced a novel injection alternative to conventional needles, offering a decreased administration pain and phobia along with more efficient transdermal and intradermal drug delivery/sample collecting. 3D printing methods have emerged in the field of MNs for their time- and cost-efficient manufacturing. Tuning 3D printing parameters with artificial intelligence (AI), including machine learning (ML) and deep learning (DL), is an emerging multidisciplinary field for optimization of manufacturing biomedical devices. Herein, we presented an AI framework to assess and predict 3D-printed MN features. Biodegradable MNs were fabricated using fused deposition modeling (FDM) 3D printing technology followed by chemical etching to enhance their geometrical precision. DL was used for quality control and anomaly detection in the fabricated MNAs. Ten different MN designs and various etching exposure doses were used create a data library to train ML models for extraction of similarity metrics in order to predict new fabrication outcomes when the mentioned parameters were adjusted. The integration of AI-enabled prediction with 3D printed MNs will facilitate the development of new healthcare systems and advancement of MNs' biomedical applications.
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Affiliation(s)
- Misagh Rezapour Sarabi
- Graduate School of Sciences & Engineering, Koç University, Istanbul 34450, Turkey; (M.R.S.); (A.A.K.)
| | - M. Munzer Alseed
- Boğaziçi Institute of Biomedical Engineering, Boğaziçi University, Istanbul 34684, Turkey;
| | - Ahmet Agah Karagoz
- Graduate School of Sciences & Engineering, Koç University, Istanbul 34450, Turkey; (M.R.S.); (A.A.K.)
| | - Savas Tasoglu
- Graduate School of Sciences & Engineering, Koç University, Istanbul 34450, Turkey; (M.R.S.); (A.A.K.)
- Boğaziçi Institute of Biomedical Engineering, Boğaziçi University, Istanbul 34684, Turkey;
- Koç University Translational Medicine Research Center, Koç University, Istanbul 34450, Turkey
- Koç University Arçelik Research Center for Creative Industries, Koç University, Istanbul 34450, Turkey
- Physical Intelligence Department, Max Planck Institute for Intelligent Systems, 70569 Stuttgart, Germany
- Correspondence:
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Abstract
Drug testing, either on animals or on 2D cell cultures, has its limitations due to inaccurate mimicking of human pathophysiology. The liver, as one of the key organs that filters and detoxifies the blood, is susceptible to drug-induced injuries. Integrating 3D bioprinting with microfluidic chips to fabricate organ-on-chip platforms for 3D liver cell cultures with continuous perfusion can offer a more physiologically relevant liver-mimetic platform for screening drugs and studying liver function. The development of organ-on-chip platforms may ultimately contribute to personalized medicine as well as body-on-chip technology that can test drug responses and organ–organ interactions on a single or linked chip model.
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Rabbi F, Dabbagh SR, Angin P, Yetisen AK, Tasoglu S. Deep Learning-Enabled Technologies for Bioimage Analysis. MICROMACHINES 2022; 13:mi13020260. [PMID: 35208385 PMCID: PMC8880650 DOI: 10.3390/mi13020260] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/13/2022] [Revised: 01/31/2022] [Accepted: 02/03/2022] [Indexed: 02/05/2023]
Abstract
Deep learning (DL) is a subfield of machine learning (ML), which has recently demonstrated its potency to significantly improve the quantification and classification workflows in biomedical and clinical applications. Among the end applications profoundly benefitting from DL, cellular morphology quantification is one of the pioneers. Here, we first briefly explain fundamental concepts in DL and then we review some of the emerging DL-enabled applications in cell morphology quantification in the fields of embryology, point-of-care ovulation testing, as a predictive tool for fetal heart pregnancy, cancer diagnostics via classification of cancer histology images, autosomal polycystic kidney disease, and chronic kidney diseases.
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Affiliation(s)
- Fazle Rabbi
- Department of Mechanical Engineering, Koç University, Sariyer, Istanbul 34450, Turkey; (F.R.); (S.R.D.)
| | - Sajjad Rahmani Dabbagh
- Department of Mechanical Engineering, Koç University, Sariyer, Istanbul 34450, Turkey; (F.R.); (S.R.D.)
- Koç University Arçelik Research Center for Creative Industries (KUAR), Koç University, Sariyer, Istanbul 34450, Turkey
- Koc University Is Bank Artificial Intelligence Lab (KUIS AILab), Koç University, Sariyer, Istanbul 34450, Turkey
| | - Pelin Angin
- Department of Computer Engineering, Middle East Technical University, Ankara 06800, Turkey;
| | - Ali Kemal Yetisen
- Department of Chemical Engineering, Imperial College London, London SW7 2AZ, UK;
| | - Savas Tasoglu
- Department of Mechanical Engineering, Koç University, Sariyer, Istanbul 34450, Turkey; (F.R.); (S.R.D.)
- Koç University Arçelik Research Center for Creative Industries (KUAR), Koç University, Sariyer, Istanbul 34450, Turkey
- Koc University Is Bank Artificial Intelligence Lab (KUIS AILab), Koç University, Sariyer, Istanbul 34450, Turkey
- Institute of Biomedical Engineering, Boğaziçi University, Çengelköy, Istanbul 34684, Turkey
- Physical Intelligence Department, Max Planck Institute for Intelligent Systems, 70569 Stuttgart, Germany
- Correspondence:
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