Label-free microfluidic biosensor for quantification for neutrophil extracellular traps
Neutrophils are integral in our innate immune system. One of the neutrophils critical functions includes release of DNA strands, also known as neutrophil extracellular traps (NETs), which is affected in many diseases including cancer, type 2 diabetes mellitus and infectious diseases. Currently, con...
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| Format: | Final Year Project (FYP) |
| Language: | English |
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Nanyang Technological University
2023
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| Online Access: | https://hdl.handle.net/10356/168242 |
| _version_ | 1826118705975656448 |
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| author | Wong, Siong Onn |
| author2 | Hou Han Wei |
| author_facet | Hou Han Wei Wong, Siong Onn |
| author_sort | Wong, Siong Onn |
| collection | NTU |
| description | Neutrophils are integral in our innate immune system. One of the neutrophils critical functions includes release of DNA strands, also known as neutrophil extracellular traps (NETs), which is affected in many diseases including cancer, type 2 diabetes mellitus and infectious diseases. Currently, conventional methods to quantify the formation of NETs (NETosis) relies on fluorescence antibodies-based labelling or NETs-associated protein detection using ELISA, which are expensive laborious, and time consuming. In this report, the development of a microfluidic biosensor for label-free NETs quantification is demonstrated. By combining NETs trapping pillar arrays with Dean Fractionation Flow (DFF) spiral module for size-based cell sorting, circulating NETs can be continuously concentrated and trapped from purified neutrophils or diluted blood. Next, we also developed a novel “virtual staining” concept for NETs quantification using deep learning neural networks. By training and deploying convolutional neural networks (CNNs) to learn the fundamental morphological features of the trapping arrays and NETs using brightfield images, the model can generate images that virtually stain the DNA content through inference networks, thus eliminating the need for antibodies staining. We first characterised the microfluidic technology using purified neutrophils treated with NETosis inducers including phorbol 12-myristate 13-acetate (PMA), and Calcium Ionophore. Images were used to train the CNN models used and showed high structural similarity and minimal pixel-wise error with actual stained DNA images. Further work includes testing of NETs-specific biomarkers such as myeloperoxidase (MPO). H3Cit, and cell staining using different biofluids (blood, urine etc.). |
| first_indexed | 2024-10-01T04:48:10Z |
| format | Final Year Project (FYP) |
| id | ntu-10356/168242 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T04:48:10Z |
| publishDate | 2023 |
| publisher | Nanyang Technological University |
| record_format | dspace |
| spelling | ntu-10356/1682422023-06-10T16:52:50Z Label-free microfluidic biosensor for quantification for neutrophil extracellular traps Wong, Siong Onn Hou Han Wei School of Mechanical and Aerospace Engineering hwhou@ntu.edu.sg Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence Science::Biological sciences::Molecular biology Neutrophils are integral in our innate immune system. One of the neutrophils critical functions includes release of DNA strands, also known as neutrophil extracellular traps (NETs), which is affected in many diseases including cancer, type 2 diabetes mellitus and infectious diseases. Currently, conventional methods to quantify the formation of NETs (NETosis) relies on fluorescence antibodies-based labelling or NETs-associated protein detection using ELISA, which are expensive laborious, and time consuming. In this report, the development of a microfluidic biosensor for label-free NETs quantification is demonstrated. By combining NETs trapping pillar arrays with Dean Fractionation Flow (DFF) spiral module for size-based cell sorting, circulating NETs can be continuously concentrated and trapped from purified neutrophils or diluted blood. Next, we also developed a novel “virtual staining” concept for NETs quantification using deep learning neural networks. By training and deploying convolutional neural networks (CNNs) to learn the fundamental morphological features of the trapping arrays and NETs using brightfield images, the model can generate images that virtually stain the DNA content through inference networks, thus eliminating the need for antibodies staining. We first characterised the microfluidic technology using purified neutrophils treated with NETosis inducers including phorbol 12-myristate 13-acetate (PMA), and Calcium Ionophore. Images were used to train the CNN models used and showed high structural similarity and minimal pixel-wise error with actual stained DNA images. Further work includes testing of NETs-specific biomarkers such as myeloperoxidase (MPO). H3Cit, and cell staining using different biofluids (blood, urine etc.). Bachelor of Engineering (Mechanical Engineering) 2023-06-08T06:51:42Z 2023-06-08T06:51:42Z 2023 Final Year Project (FYP) Wong, S. O. (2023). Label-free microfluidic biosensor for quantification for neutrophil extracellular traps. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/168242 https://hdl.handle.net/10356/168242 en A056 application/pdf Nanyang Technological University |
| spellingShingle | Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence Science::Biological sciences::Molecular biology Wong, Siong Onn Label-free microfluidic biosensor for quantification for neutrophil extracellular traps |
| title | Label-free microfluidic biosensor for quantification for neutrophil extracellular traps |
| title_full | Label-free microfluidic biosensor for quantification for neutrophil extracellular traps |
| title_fullStr | Label-free microfluidic biosensor for quantification for neutrophil extracellular traps |
| title_full_unstemmed | Label-free microfluidic biosensor for quantification for neutrophil extracellular traps |
| title_short | Label-free microfluidic biosensor for quantification for neutrophil extracellular traps |
| title_sort | label free microfluidic biosensor for quantification for neutrophil extracellular traps |
| topic | Engineering::Computer science and engineering::Computing methodologies::Artificial intelligence Science::Biological sciences::Molecular biology |
| url | https://hdl.handle.net/10356/168242 |
| work_keys_str_mv | AT wongsiongonn labelfreemicrofluidicbiosensorforquantificationforneutrophilextracellulartraps |