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Yang C, He C, Zhuo H, Wang J, Yong T, Gan L, Yang X, Nie L, Xi S, Liu Z, Liao G, Shi T. Cost-effective microfluidic flow cytometry for precise and gentle cell sorting. LAB ON A CHIP 2025; 25:698-713. [PMID: 39895391 DOI: 10.1039/d4lc00900b] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/04/2025]
Abstract
Microfluidic flow cytometry (MFCM) is considered to be an effective substitute for traditional flow cytometry, because of its advantages in terms of higher integration, smaller device size, lower cost, and higher cell sorting activity. However, MFCM still faces challenges in balancing parameters such as sorting throughput, viability, sorting efficiency, and cost. Here, we demonstrate a cost-effective and high-performance microfluidic cytometry cell sorting system, along with a customized microfluidic chip that integrates hydrodynamic focusing, droplet encapsulation, and sorting for precise cell manipulation. An innovative photon incremental counting-based fluorescence detection method is proposed, which requires only one-fiftieth of the data compared to traditional methods. This significantly simplifies the structure of the system and substantially reduces costs. The system exhibits detection recoveries exceeding 95% across sample solution flow rates ranging from 10 to 80 μL min-1. Moreover, it accurately achieves individual droplet deflections at a droplet generation frequency of 1600 Hz. Ultimately, our cell sorting system offers an impressive sorting efficiency of 90.7% and a high cell viability of 94.3% when operating at a droplet generation frequency of 1316 Hz, highlighting its accuracy and gentleness throughout the entire process. Our work will enhance advances in the life sciences, thereby creating a boom in great applications in single-cell cloning, single-cell analysis, drug screening, etc.
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Affiliation(s)
- Canfeng Yang
- State Key Laboratory of Digital Manufacturing Equipment and Technology, School of Mechanical Science & Engineering, Huazhong University of Science and Technology, Wuhan 430074, China.
| | - Chunhua He
- State Key Laboratory of Digital Manufacturing Equipment and Technology, School of Mechanical Science & Engineering, Huazhong University of Science and Technology, Wuhan 430074, China.
| | - Huasheng Zhuo
- State Key Laboratory of Digital Manufacturing Equipment and Technology, School of Mechanical Science & Engineering, Huazhong University of Science and Technology, Wuhan 430074, China.
| | - Jianxin Wang
- State Key Laboratory of Digital Manufacturing Equipment and Technology, School of Mechanical Science & Engineering, Huazhong University of Science and Technology, Wuhan 430074, China.
| | - Tuying Yong
- National Engineering Research Center for Nanomedicine, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan 430074, China
| | - Lu Gan
- National Engineering Research Center for Nanomedicine, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan 430074, China
| | - Xiangliang Yang
- National Engineering Research Center for Nanomedicine, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan 430074, China
| | - Lei Nie
- School of Mechanical Engineering, Hubei University of Technology, Wuhan 430068, China
| | - Shuang Xi
- College of Mechanical and Electronic Engineering, Nanjing Forestry University, Nanjing, 210037, China
| | - Zhiyong Liu
- State Key Laboratory of Digital Manufacturing Equipment and Technology, School of Mechanical Science & Engineering, Huazhong University of Science and Technology, Wuhan 430074, China.
| | - Guanglan Liao
- State Key Laboratory of Digital Manufacturing Equipment and Technology, School of Mechanical Science & Engineering, Huazhong University of Science and Technology, Wuhan 430074, China.
| | - Tielin Shi
- State Key Laboratory of Digital Manufacturing Equipment and Technology, School of Mechanical Science & Engineering, Huazhong University of Science and Technology, Wuhan 430074, China.
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Zhang S, Staples AE. Microfluidic-based systems for the management of diabetes. Drug Deliv Transl Res 2024; 14:2989-3008. [PMID: 38509342 PMCID: PMC11445324 DOI: 10.1007/s13346-024-01569-y] [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] [Accepted: 03/04/2024] [Indexed: 03/22/2024]
Abstract
Diabetes currently affects approximately 500 million people worldwide and is one of the most common causes of mortality in the United States. To diagnose and monitor diabetes, finger-prick blood glucose testing has long been used as the clinical gold standard. For diabetes treatment, insulin is typically delivered subcutaneously through cannula-based syringes, pens, or pumps in almost all type 1 diabetic (T1D) patients and some type 2 diabetic (T2D) patients. These painful, invasive approaches can cause non-adherence to glucose testing and insulin therapy. To address these problems, researchers have developed miniaturized blood glucose testing devices as well as microfluidic platforms for non-invasive glucose testing through other body fluids. In addition, glycated hemoglobin (HbA1c), insulin levels, and cellular biomechanics-related metrics have also been considered for microfluidic-based diabetes diagnosis. For the treatment of diabetes, insulin has been delivered transdermally through microdevices, mostly through microneedle array-based, minimally invasive injections. Researchers have also developed microfluidic platforms for oral, intraperitoneal, and inhalation-based delivery of insulin. For T2D patients, metformin, glucagon-like peptide 1 (GLP-1), and GLP-1 receptor agonists have also been delivered using microfluidic technologies. Thus far, clinical studies have been widely performed on microfluidic-based diabetes monitoring, especially glucose sensing, yet technologies for the delivery of insulin and other drugs to diabetic patients with microfluidics are still mostly in the preclinical stage. This article provides a concise review of the role of microfluidic devices in the diagnosis and monitoring of diabetes, as well as the delivery of pharmaceuticals to treat diabetes using microfluidic technologies in the recent literature.
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Affiliation(s)
- Shuyu Zhang
- Virginia Tech-Wake Forest School of Biomedical Engineering and Sciences, Blacksburg, VA, 24061, USA.
- Department of Biomedical Engineering and Mechanics, Virginia Tech, Blacksburg, VA, 24061, USA.
| | - Anne E Staples
- Virginia Tech-Wake Forest School of Biomedical Engineering and Sciences, Blacksburg, VA, 24061, USA
- Department of Biomedical Engineering and Mechanics, Virginia Tech, Blacksburg, VA, 24061, USA
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Electrochemiluminescent immunoassay for insulin by using a quencher pair consisting of CdS:Eu nanoclusters loaded with multiwalled carbon nanotubes on reduced graphene oxide nanoribbons and gold nanoparticle-loaded octahedral Cu2O. Mikrochim Acta 2019; 186:505. [DOI: 10.1007/s00604-019-3640-1] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2019] [Accepted: 06/26/2019] [Indexed: 11/26/2022]
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Abstract
Good glucose management through an insulin dose regime based on the metabolism of glucose helps millions of people worldwide manage their diabetes. Since Banting and Best extracted insulin, glucose management has improved due to the introduction of insulin analogues that act from 30 minutes to 28 days, improved insulin dose regimes, and portable glucose meters, with a current focus on alternative sampling sites that are less invasive. However, a piece of the puzzle is still missing-the ability to measure insulin directly in a Point-of-Care device. The ability to measure both glucose and insulin concurrently will enable better glucose control by providing an improved estimate for insulin sensitivity, minimizing variability in control, and maximizing safety from hypoglycaemia. However, direct detection of free insulin has provided a challenge due to the size of the molecule, the low concentration of insulin in blood, and the selectivity against interferants in blood. This review summarizes current insulin detection methods from immunoassays to analytical chemistry, and sensors. We also discuss the challenges and potential of each of the methods towards Point-of-Care insulin detection.
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Sun H, Wu S, Zhou X, Zhao M, Wu H, Luo R, Ding S. Electrochemical sandwich immunoassay for insulin detection based on the use of gold nanoparticle-modified MoS2 nanosheets and the hybridization chain reaction. Mikrochim Acta 2018; 186:6. [DOI: 10.1007/s00604-018-3124-8] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2018] [Accepted: 11/27/2018] [Indexed: 10/27/2022]
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Ranjan A, Wendt SL, Schmidt S, Madsbad S, Holst JJ, Madsen H, Knudsen CB, Jørgensen JB, Nørgaard K. Relationship between Optimum Mini-doses of Glucagon and Insulin Levels when Treating Mild Hypoglycaemia in Patients with Type 1 Diabetes - A Simulation Study. Basic Clin Pharmacol Toxicol 2017; 122:322-330. [DOI: 10.1111/bcpt.12907] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2017] [Accepted: 09/06/2017] [Indexed: 12/28/2022]
Affiliation(s)
- Ajenthen Ranjan
- Department of Endocrinology; Copenhagen University Hospital Hvidovre; Hvidovre Denmark
- Danish Diabetes Academy; Odense Denmark
| | - Sabrina L. Wendt
- Department of Bioanalysis and Pharmacokinetics; Zealand Pharma A/S; Glostrup Denmark
- Department of Applied Mathematics and Computer Science; Technical University of Denmark; Kgs. Lyngby Denmark
| | - Signe Schmidt
- Department of Endocrinology; Copenhagen University Hospital Hvidovre; Hvidovre Denmark
- Danish Diabetes Academy; Odense Denmark
| | - Sten Madsbad
- Department of Endocrinology; Copenhagen University Hospital Hvidovre; Hvidovre Denmark
- NFF Center for Basic Metabolic Research and Department of Biomedical Sciences; University of Copenhagen; Copenhagen Denmark
| | - Jens J. Holst
- NFF Center for Basic Metabolic Research and Department of Biomedical Sciences; University of Copenhagen; Copenhagen Denmark
| | - Henrik Madsen
- Department of Applied Mathematics and Computer Science; Technical University of Denmark; Kgs. Lyngby Denmark
| | - Carsten B. Knudsen
- Department of Bioanalysis and Pharmacokinetics; Zealand Pharma A/S; Glostrup Denmark
| | - John B. Jørgensen
- Department of Applied Mathematics and Computer Science; Technical University of Denmark; Kgs. Lyngby Denmark
| | - Kirsten Nørgaard
- Department of Endocrinology; Copenhagen University Hospital Hvidovre; Hvidovre Denmark
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