Optical particle analysis for use in simultaneous high throughput flow cytometry
| dc.contributor.author | Cochingco, Jasmin | |
| dc.contributor.examiningcommittee | Bridges, Greg E. (Electrical and Computer Engineering) | |
| dc.contributor.examiningcommittee | Sherif, Sherif (Electrical and Computer Engineering) | |
| dc.contributor.supervisor | Thomson, Douglas J. | |
| dc.date.accessioned | 2024-03-28T17:54:58Z | |
| dc.date.available | 2024-03-28T17:54:58Z | |
| dc.date.issued | 2024-03-28 | |
| dc.date.submitted | 2024-03-28T04:12:14Z | en_US |
| dc.degree.discipline | Electrical and Computer Engineering | en_US |
| dc.degree.level | Master of Science (M.Sc.) | |
| dc.description.abstract | Many methods of single-cell analysis are currently used, and each method provides different characteristics of the cell, such as dielectric and physical properties. In this thesis we investigate the use of optical analysis in tandem with dielectrophoresis analysis in a high throughput flow cytometer system. To examine the viability of combining optical and dielectrophoretic analysis methods, this thesis proposes an optical model using Mie scattering theory, and a data extraction and particle classification algorithm that employs both analysis modalities. The optical model presented here examines the effects of different experimental variables such as particle size and refractive index, the refractive index of the medium, and cytometer components like LED wavelength. The data extraction and particle classification algorithm presented extracts both optical and DEP data and is used to identify and sort particles in mixed population experiments. Combining the information gathered from examining the optical data from particles as well as the dielectric properties from dielectrophoretic measurements provides a more robust and confident classification of particles. In this thesis, the combination of the two methods was applied to both polystyrene polymer sphere (PSS) beads and Chinese hamster ovary (CHO) cell experiments. Particle size data was successfully extracted using optical analysis and used to provide more confidence and robustness to the particle classification conducted using DEP analysis. The findings of this thesis provide a starting point for further use of optical analysis in conjunction with DEP analysis in a high through put flow cytometer system. | |
| dc.description.note | May 2024 | |
| dc.identifier.uri | http://hdl.handle.net/1993/38104 | |
| dc.language.iso | eng | |
| dc.rights | open access | en_US |
| dc.subject | Optical Analysis | |
| dc.subject | Flow Cytometry | |
| dc.subject | Dielectrophoresis | |
| dc.subject | Microfluidics | |
| dc.title | Optical particle analysis for use in simultaneous high throughput flow cytometry | |
| dc.type | master thesis | en_US |
| local.subject.manitoba | no |