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Malic L, Clime L, Moon BU, Nassif C, Da Fonte D, Brassard D, Lukic L, Geissler M, Morton K, Charlebois D, Veres T. Sample-to-answer centrifugal microfluidic droplet PCR platform for quantitation of viral load. LAB ON A CHIP 2024. [PMID: 39301752 DOI: 10.1039/d4lc00533c] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/22/2024]
Abstract
Droplet digital polymerase chain reaction (ddPCR) stands out as a highly sensitive diagnostic technique that is gaining traction in infectious disease diagnostics due to its ability to quantitate very low numbers of viral gene copies. By partitioning the sample into thousands of droplets, ddPCR enables precise and absolute quantification without relying on a standard curve. However, current ddPCR systems often exhibit relatively low levels of integration, and the analytical process remains dependent on elaborate workflows for up-front sample preparation. Here, we introduce a fully-integrated system seamlessly combining viral lysis, RNA extraction, emulsification, reverse transcription (RT) ddPCR, and fluorescence readout in a sample-to-answer format. The system comprises a disposable microfluidic cartridge housing buffers and reagents required for the assay, and a centrifugal platform that allows for pneumatic actuation of liquids during rotation, enabling automation of the workflow. Highly monodisperse droplets (∼50 μm in diameter) are produced using centrifugal step emulsification and automatically transferred to an integrated heating module for target amplification. The platform is equipped with a miniature fluorescence imaging system enabling on-chip read-out of droplets after RT-ddPCR. We demonstrate sample-to-answer detection of SARS-CoV-2 N and E genes, along with RNase P endogenous reference, using hydrolysis probes and multiplexed amplification within single droplets for concentrations as low as 0.1 copy per μL. We also tested 14 nasopharyngeal swab specimens from patients and were able to distinguish positive and negative SARS-CoV-2 samples with 100% accuracy, surpassing results obtained by conventional real-time amplification.
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Affiliation(s)
- Lidija Malic
- Life Sciences Division, National Research Council of Canada (NRC), 75 de Mortagne Boulevard, Boucherville, QC, J4B 6Y4, Canada.
- Center for Research and Applications of Fluidic Technologies (CRAFT) @ NRC and University of Toronto, Canada
- Department of Biomedical Engineering, McGill University, 775 Rue University, Suite 316, Montreal, QC, H3A 2B4, Canada
| | - Liviu Clime
- Life Sciences Division, National Research Council of Canada (NRC), 75 de Mortagne Boulevard, Boucherville, QC, J4B 6Y4, Canada.
- Center for Research and Applications of Fluidic Technologies (CRAFT) @ NRC and University of Toronto, Canada
| | - Byeong-Ui Moon
- Life Sciences Division, National Research Council of Canada (NRC), 75 de Mortagne Boulevard, Boucherville, QC, J4B 6Y4, Canada.
- Center for Research and Applications of Fluidic Technologies (CRAFT) @ NRC and University of Toronto, Canada
| | - Christina Nassif
- Life Sciences Division, National Research Council of Canada (NRC), 75 de Mortagne Boulevard, Boucherville, QC, J4B 6Y4, Canada.
- Center for Research and Applications of Fluidic Technologies (CRAFT) @ NRC and University of Toronto, Canada
| | - Dillon Da Fonte
- Life Sciences Division, National Research Council of Canada (NRC), 75 de Mortagne Boulevard, Boucherville, QC, J4B 6Y4, Canada.
- Center for Research and Applications of Fluidic Technologies (CRAFT) @ NRC and University of Toronto, Canada
| | - Daniel Brassard
- Life Sciences Division, National Research Council of Canada (NRC), 75 de Mortagne Boulevard, Boucherville, QC, J4B 6Y4, Canada.
- Center for Research and Applications of Fluidic Technologies (CRAFT) @ NRC and University of Toronto, Canada
| | - Ljuboje Lukic
- Life Sciences Division, National Research Council of Canada (NRC), 75 de Mortagne Boulevard, Boucherville, QC, J4B 6Y4, Canada.
- Center for Research and Applications of Fluidic Technologies (CRAFT) @ NRC and University of Toronto, Canada
| | - Matthias Geissler
- Life Sciences Division, National Research Council of Canada (NRC), 75 de Mortagne Boulevard, Boucherville, QC, J4B 6Y4, Canada.
- Center for Research and Applications of Fluidic Technologies (CRAFT) @ NRC and University of Toronto, Canada
| | - Keith Morton
- Life Sciences Division, National Research Council of Canada (NRC), 75 de Mortagne Boulevard, Boucherville, QC, J4B 6Y4, Canada.
- Center for Research and Applications of Fluidic Technologies (CRAFT) @ NRC and University of Toronto, Canada
| | - Denis Charlebois
- Canadian Space Agency, 6767 Route de l'Aéroport, Saint-Hubert, QC, J3Y 8Y9, Canada
| | - Teodor Veres
- Life Sciences Division, National Research Council of Canada (NRC), 75 de Mortagne Boulevard, Boucherville, QC, J4B 6Y4, Canada.
- Center for Research and Applications of Fluidic Technologies (CRAFT) @ NRC and University of Toronto, Canada
- Department of Mechanical and Industrial Engineering, University of Toronto, 5 King's College Road, Toronto, ON, M5S 3G8, Canada
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Mirabile A, Sangiorgio G, Bonacci PG, Bivona D, Nicitra E, Bonomo C, Bongiorno D, Stefani S, Musso N. Advancing Pathogen Identification: The Role of Digital PCR in Enhancing Diagnostic Power in Different Settings. Diagnostics (Basel) 2024; 14:1598. [PMID: 39125474 PMCID: PMC11311727 DOI: 10.3390/diagnostics14151598] [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: 06/06/2024] [Revised: 07/19/2024] [Accepted: 07/20/2024] [Indexed: 08/12/2024] Open
Abstract
Digital polymerase chain reaction (dPCR) has emerged as a groundbreaking technology in molecular biology and diagnostics, offering exceptional precision and sensitivity in nucleic acid detection and quantification. This review highlights the core principles and transformative potential of dPCR, particularly in infectious disease diagnostics and environmental surveillance. Emphasizing its evolution from traditional PCR, dPCR provides accurate absolute quantification of target nucleic acids through advanced partitioning techniques. The review addresses the significant impact of dPCR in sepsis diagnosis and management, showcasing its superior sensitivity and specificity in early pathogen detection and identification of drug-resistant genes. Despite its advantages, challenges such as optimization of experimental conditions, standardization of data analysis workflows, and high costs are discussed. Furthermore, we compare various commercially available dPCR platforms, detailing their features and applications in clinical and research settings. Additionally, the review explores dPCR's role in water microbiology, particularly in wastewater surveillance and monitoring of waterborne pathogens, underscoring its importance in public health protection. In conclusion, future prospects of dPCR, including methodological optimization, integration with innovative technologies, and expansion into new sectors like metagenomics, are explored.
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Affiliation(s)
- Alessia Mirabile
- Department of Biomedical and Biotechnological Sciences (BIOMETEC), University of Catania, 95125 Catania, Italy; (A.M.); (G.S.); (P.G.B.); (D.B.); (E.N.); (C.B.); (S.S.); (N.M.)
| | - Giuseppe Sangiorgio
- Department of Biomedical and Biotechnological Sciences (BIOMETEC), University of Catania, 95125 Catania, Italy; (A.M.); (G.S.); (P.G.B.); (D.B.); (E.N.); (C.B.); (S.S.); (N.M.)
| | - Paolo Giuseppe Bonacci
- Department of Biomedical and Biotechnological Sciences (BIOMETEC), University of Catania, 95125 Catania, Italy; (A.M.); (G.S.); (P.G.B.); (D.B.); (E.N.); (C.B.); (S.S.); (N.M.)
| | - Dalida Bivona
- Department of Biomedical and Biotechnological Sciences (BIOMETEC), University of Catania, 95125 Catania, Italy; (A.M.); (G.S.); (P.G.B.); (D.B.); (E.N.); (C.B.); (S.S.); (N.M.)
| | - Emanuele Nicitra
- Department of Biomedical and Biotechnological Sciences (BIOMETEC), University of Catania, 95125 Catania, Italy; (A.M.); (G.S.); (P.G.B.); (D.B.); (E.N.); (C.B.); (S.S.); (N.M.)
| | - Carmelo Bonomo
- Department of Biomedical and Biotechnological Sciences (BIOMETEC), University of Catania, 95125 Catania, Italy; (A.M.); (G.S.); (P.G.B.); (D.B.); (E.N.); (C.B.); (S.S.); (N.M.)
| | - Dafne Bongiorno
- Department of Biomedical and Biotechnological Sciences (BIOMETEC), University of Catania, 95125 Catania, Italy; (A.M.); (G.S.); (P.G.B.); (D.B.); (E.N.); (C.B.); (S.S.); (N.M.)
| | - Stefania Stefani
- Department of Biomedical and Biotechnological Sciences (BIOMETEC), University of Catania, 95125 Catania, Italy; (A.M.); (G.S.); (P.G.B.); (D.B.); (E.N.); (C.B.); (S.S.); (N.M.)
- U.O.C. Laboratory Analysis Unit, University Hospital Policlinico-San Marco, Via Santa Sofia 78, 95123 Catania, Italy
| | - Nicolò Musso
- Department of Biomedical and Biotechnological Sciences (BIOMETEC), University of Catania, 95125 Catania, Italy; (A.M.); (G.S.); (P.G.B.); (D.B.); (E.N.); (C.B.); (S.S.); (N.M.)
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Kim SE, Yun S, Doh J, Kim HN. Imaging-Based Efficacy Evaluation of Cancer Immunotherapy in Engineered Tumor Platforms and Tumor Organoids. Adv Healthc Mater 2024:e2400475. [PMID: 38815251 DOI: 10.1002/adhm.202400475] [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: 02/06/2024] [Revised: 05/16/2024] [Indexed: 06/01/2024]
Abstract
Cancer immunotherapy is used to treat tumors by modulating the immune system. Although the anticancer efficacy of cancer immunotherapy has been evaluated prior to clinical trials, conventional in vivo animal and endpoint models inadequately replicate the intricate process of tumor elimination and reflect human-specific immune systems. Therefore, more sophisticated models that mimic the complex tumor-immune microenvironment must be employed to assess the effectiveness of immunotherapy. Additionally, using real-time imaging technology, a step-by-step evaluation can be applied, allowing for a more precise assessment of treatment efficacy. Here, an overview of the various imaging-based evaluation platforms recently developed for cancer immunotherapeutic applications is presented. Specifically, a fundamental technique is discussed for stably observing immune cell-based tumor cell killing using direct imaging, a microwell that reproduces a confined space for spatial observation, a droplet assay that facilitates cell-cell interactions, and a 3D microphysiological system that reconstructs the vascular environment. Furthermore, it is suggested that future evaluation platforms pursue more human-like immune systems.
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Affiliation(s)
- Seong-Eun Kim
- Brain Science Institute, Korea Institute of Science and Technology (KIST), Seoul, 02792, South Korea
| | - Suji Yun
- Interdisciplinary Program for Bioengineering, Seoul National University, Seoul, 08826, South Korea
| | - Junsang Doh
- Interdisciplinary Program for Bioengineering, Seoul National University, Seoul, 08826, South Korea
- Department of Materials Science and Engineering, Research Institute of Advanced Materials, Institute of Engineering Research, Bio-MAX institute, Soft Foundry Institute, Seoul National University, Seoul, 08826, South Korea
| | - Hong Nam Kim
- Brain Science Institute, Korea Institute of Science and Technology (KIST), Seoul, 02792, South Korea
- Division of Bio-Medical Science and Technology, KIST School, Korea University of Science and Technology, Seoul, 02792, Republic of Korea
- School of Mechanical Engineering, Yonsei University, Seoul, 03722, Republic of Korea
- Yonsei-KIST Convergence Research Institute, Yonsei University, Seoul, 03722, Republic of Korea
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张 一, 陈 波, 李 家, 梁 业, 张 华, 吴 文, 张 煜. [A digital droplet PCR detection technique based on filter faster R-CNN]. NAN FANG YI KE DA XUE XUE BAO = JOURNAL OF SOUTHERN MEDICAL UNIVERSITY 2024; 44:344-353. [PMID: 38501420 PMCID: PMC10954537 DOI: 10.12122/j.issn.1673-4254.2024.02.17] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Subscribe] [Scholar Register] [Received: 10/30/2023] [Indexed: 03/20/2024]
Abstract
OBJECTIVE To propose a method for mitigate the impact of anomaly points (such as dust, bubbles, scratches on the chip surface, and minor indentations) in images on the results of digital droplet PCR (ddPCR) detection to achieve high-throughput, stable, and accurate detection. METHODS We propose a Filter Faster R-CNN ddPCR detection model, which employs Faster R-CNN to generate droplet prediction boxes followed by removing the anomalies within the positive droplet prediction boxes using an outlier filtering module (Filter). Using a plasmid carrying a norovirus fragment as the template, we established a ddPCR dataset for model training (2462 instances, 78.56%) and testing (672 instances, 21.44%). Ablation experiments were performed to test the effectiveness of 3 filtering branches of the Filter for anomaly removal on the validation dataset. Comparative experiments with other ddPCR droplet detection models and absolute quantification experiments of ddPCR were conducted to assess the performance of the Filter Faster R-CNN model. RESULTS In low-dust and dusty environments, the Filter Faster R-CNN model achieved detection accuracies of 98.23% and 88.35% for positive droplets, respectively, with composite F1 scores reaching 99.15% and 99.14%, obviously superior to the other models. The introduction of the filtering module significantly enhanced the positive accuracy of the model in dusty environments. In the absolute quantification experiments, a regression line was plotted using the results from commercial flow cytometry equipment as the standard concentration. The results show a regression line slope of 1.0005, an intercept of -0.025, and a determination coefficient of 0.9997, indicating high consistency between the two results. CONCLUSION The ddPCR detection technique using the Filter Faster R-CNN model provides a robust detection method for ddPCR under various environmental conditions.
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Affiliation(s)
- 一鹏 张
- 南方医科大学生物医学工程学院,广东 广州 520515School of Biomedical Engineering, Southern Medical University, Guangzhou 510515, China
- 广东省医学图像处理重点研究室,广东 广州 520515Guangdong Provincial Key Laboratory of Medical Image Processing, Guangzhou 510515, China
- 广东省科学院生物与医学工程研究所,广东 广州 510316Institute of Biological and Medical Engineering, Guangdong Academy of Sciences, Guangzhou 510316, China
| | - 波 陈
- 广东省科学院生物与医学工程研究所,广东 广州 510316Institute of Biological and Medical Engineering, Guangdong Academy of Sciences, Guangzhou 510316, China
- 五邑大学应用物理与材料学院,广东 江门 529000School of Applied Physics and Materials, Wuyi University, Jiangmen 529000, China
| | - 家奇 李
- 广东省科学院生物与医学工程研究所,广东 广州 510316Institute of Biological and Medical Engineering, Guangdong Academy of Sciences, Guangzhou 510316, China
- 五邑大学生物科技与大健康学院,广东 江门 529020School of Biotechnology and Health Sciences, Wuyi University, Jiangmen 529020, China
| | - 业东 梁
- 南方医科大学生物医学工程学院,广东 广州 520515School of Biomedical Engineering, Southern Medical University, Guangzhou 510515, China
- 广东省医学图像处理重点研究室,广东 广州 520515Guangdong Provincial Key Laboratory of Medical Image Processing, Guangzhou 510515, China
- 广东省医学成像与诊断技术工程实验室,广东 广州 520515Guangdong Province Engineering Laboratory for Medical Imaging and Diagnostic Technology, Guangzhou 510515, China
- 广东省科学院生物与医学工程研究所,广东 广州 510316Institute of Biological and Medical Engineering, Guangdong Academy of Sciences, Guangzhou 510316, China
| | - 华剑 张
- 广东省科学院生物与医学工程研究所,广东 广州 510316Institute of Biological and Medical Engineering, Guangdong Academy of Sciences, Guangzhou 510316, China
| | - 文明 吴
- 广东省科学院生物与医学工程研究所,广东 广州 510316Institute of Biological and Medical Engineering, Guangdong Academy of Sciences, Guangzhou 510316, China
| | - 煜 张
- 南方医科大学生物医学工程学院,广东 广州 520515School of Biomedical Engineering, Southern Medical University, Guangzhou 510515, China
- 广东省医学图像处理重点研究室,广东 广州 520515Guangdong Provincial Key Laboratory of Medical Image Processing, Guangzhou 510515, China
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Kim HE, Schuck A, Park H, Chung DR, Kang M, Kim YS. Dual-Mode Graphene Field-Effect Transistor Biosensor with Isothermal Nucleic Acid Amplification. BIOSENSORS 2024; 14:91. [PMID: 38392010 PMCID: PMC10886465 DOI: 10.3390/bios14020091] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/28/2023] [Revised: 02/06/2024] [Accepted: 02/06/2024] [Indexed: 02/24/2024]
Abstract
Despite a substantial increase in testing facilities during the pandemic, access remains a major obstacle, particularly in low-resource and remote areas. This constraint emphasizes the need for high-throughput potential point-of-care diagnostic tools in environments with limited resources. Loop-mediated isothermal amplification (LAMP) is a promising technique, but improvements in sensitivity are needed for accurate detection, especially in scenarios where the virus is present in low quantities. To achieve this objective, we present a highly sensitive detection approach of a dual-mode graphene-based field-effect transistor (G-FET) biosensor with LAMP. The G-FET biosensor, which has a transparent graphene microelectrode array on a glass substrate, detects LAMP products in less than 30 min using both observable color changes and Dirac point voltage measurements, even in samples with low viral concentrations. This dual-mode G-FET biosensor emerges as a potential alternative to conventional RT-PCR for severe acute respiratory syndrome-associated coronavirus (SARS-CoV)-2 detection or point-of-care testing, particularly in resource-constrained scenarios such as developing countries. Moreover, its capacity for colorimetric detection with the naked eye enhances its applicability in diverse settings.
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Affiliation(s)
- Hyo Eun Kim
- Department of Electrical and Computer Engineering, Sungkyunkwan University, Suwon 16419, Republic of Korea; (H.E.K.)
| | - Ariadna Schuck
- Department of Electrical and Computer Engineering, Sungkyunkwan University, Suwon 16419, Republic of Korea; (H.E.K.)
| | - Hyeonseek Park
- Biomedical Engineering Research Center, Smart Healthcare Research Institute, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Republic of Korea;
- Department of Medical Device Management and Research, Samsung Advanced Institute for Health Science & Technology, Sungkyunkwan University, Seoul 06351, Republic of Korea
| | - Doo Ryeon Chung
- Center for Infection Prevention and Control, Samsung Medical Center, Seoul 06351, Republic of Korea
- Division of Infectious Diseases, Department of Internal Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Republic of Korea
| | - Minhee Kang
- Biomedical Engineering Research Center, Smart Healthcare Research Institute, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 06351, Republic of Korea;
| | - Yong-Sang Kim
- Department of Electrical and Computer Engineering, Sungkyunkwan University, Suwon 16419, Republic of Korea; (H.E.K.)
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Zhang W, Cui L, Wang Y, Xie Z, Wei Y, Zhu S, Nawaz M, Mak WC, Ho HP, Gu D, Zeng S. An Integrated ddPCR Lab-on-a-Disc Device for Rapid Screening of Infectious Diseases. BIOSENSORS 2023; 14:2. [PMID: 38275303 PMCID: PMC10813669 DOI: 10.3390/bios14010002] [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: 11/14/2023] [Revised: 12/14/2023] [Accepted: 12/16/2023] [Indexed: 01/27/2024]
Abstract
Digital droplet PCR (ddPCR) is a powerful amplification technique for absolute quantification of viral nucleic acids. Although commercial ddPCR devices are effective in the lab bench tests, they cannot meet current urgent requirements for on-site and rapid screening for patients. Here, we have developed a portable and fully integrated lab-on-a-disc (LOAD) device for quantitively screening infectious disease agents. Our designed LOAD device has integrated (i) microfluidics chips, (ii) a transparent circulating oil-based heat exchanger, and (iii) an on-disc transmitted-light fluorescent imaging system into one compact and portable box. Thus, droplet generation, PCR thermocycling, and analysis can be achieved in a single LOAD device. This feature is a significant attribute for the current clinical application of disease screening. For this custom-built ddPCR setup, we have first demonstrated the loading and ddPCR amplification ability by using influenza A virus-specific DNA fragments with different concentrations (diluted from the original concentration to 107 times), followed by analyzing the droplets with an external fluorescence microscope as a standard calibration test. The measured DNA concentration is linearly related to the gradient-dilution factor, which validated the precise quantification for the samples. In addition to the calibration tests using DNA fragments, we also employed this ddPCR-LOAD device for clinical samples with different viruses. Infectious samples containing five different viruses, including influenza A virus (IAV), respiratory syncytial virus (RSV), varicella zoster virus (VZV), Zika virus (ZIKV), and adenovirus (ADV), were injected into the device, followed by analyzing the droplets with an external fluorescence microscope with the lowest detected concentration of 20.24 copies/µL. Finally, we demonstrated the proof-of-concept detection of clinical samples of IAV using the on-disc fluorescence imaging system in our fully integrated device, which proves the capability of this device in clinical sample detection. We anticipate that this integrated ddPCR-LOAD device will become a flexible tool for on-site disease detection.
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Grants
- GRF14204621, GRF14207920, GRF14207419, GRF14207121, N_CUHK407/16 Hong Kong Research Grants Council
- No.2021A1515220084, No. 2022B1111020001 the National Key Research and Development Program of China
- ZDSYS20210623092001003, GJHZ20200731095604013, JSGG20220301090003004, No. 201906133000069, No. SGLH20180625171602058, and JCYJ20200109120205924 Shenzhen Science and Technology Foundation
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Affiliation(s)
- Wanyi Zhang
- Department of Biomedical Engineering, The Chinese University of Hong Kong, Shatin, Hong Kong SAR 999077, China; (W.Z.); (Z.X.); (Y.W.); (S.Z.); (M.N.); (W.-C.M.)
| | - Lili Cui
- School of Public Health, Guangdong Medical University, Dongguan 523808, China;
- Laboratory Medicine, Shenzhen Key Laboratory of Medical Laboratory and Molecular Diagnostics, Shenzhen Institute of Translational Medicine, The First Affiliated Hospital of Shenzhen University, Shenzhen Second People’s Hospital, Shenzhen 518035, China;
| | - Yuye Wang
- Key Laboratory of Optoelectronic Devices and Systems of Ministry of Education and Guangdong Province, College of Physics and Optoelectronic Engineering, Shenzhen University, Shenzhen 518060, China;
| | - Zhenming Xie
- Department of Biomedical Engineering, The Chinese University of Hong Kong, Shatin, Hong Kong SAR 999077, China; (W.Z.); (Z.X.); (Y.W.); (S.Z.); (M.N.); (W.-C.M.)
| | - Yuanyuan Wei
- Department of Biomedical Engineering, The Chinese University of Hong Kong, Shatin, Hong Kong SAR 999077, China; (W.Z.); (Z.X.); (Y.W.); (S.Z.); (M.N.); (W.-C.M.)
| | - Shaodi Zhu
- Department of Biomedical Engineering, The Chinese University of Hong Kong, Shatin, Hong Kong SAR 999077, China; (W.Z.); (Z.X.); (Y.W.); (S.Z.); (M.N.); (W.-C.M.)
- Light, Nanomaterials & Nanotechnologies (L2n), CNRS-EMR 7004, Université de Technologie de Troyes, 10000 Troyes, France
| | - Mehmood Nawaz
- Department of Biomedical Engineering, The Chinese University of Hong Kong, Shatin, Hong Kong SAR 999077, China; (W.Z.); (Z.X.); (Y.W.); (S.Z.); (M.N.); (W.-C.M.)
| | - Wing-Cheung Mak
- Department of Biomedical Engineering, The Chinese University of Hong Kong, Shatin, Hong Kong SAR 999077, China; (W.Z.); (Z.X.); (Y.W.); (S.Z.); (M.N.); (W.-C.M.)
| | - Ho-Pui Ho
- Department of Biomedical Engineering, The Chinese University of Hong Kong, Shatin, Hong Kong SAR 999077, China; (W.Z.); (Z.X.); (Y.W.); (S.Z.); (M.N.); (W.-C.M.)
| | - Dayong Gu
- Laboratory Medicine, Shenzhen Key Laboratory of Medical Laboratory and Molecular Diagnostics, Shenzhen Institute of Translational Medicine, The First Affiliated Hospital of Shenzhen University, Shenzhen Second People’s Hospital, Shenzhen 518035, China;
| | - Shuwen Zeng
- Light, Nanomaterials & Nanotechnologies (L2n), CNRS-EMR 7004, Université de Technologie de Troyes, 10000 Troyes, France
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