Show simple item record

dc.contributor.advisorKameoka, Jun
dc.creatorSreenivasappa, Harini Bytaraya
dc.date.accessioned2011-02-22T22:24:14Z
dc.date.accessioned2011-02-22T23:48:07Z
dc.date.available2011-02-22T22:24:14Z
dc.date.available2011-02-22T23:48:07Z
dc.date.created2009-12
dc.date.issued2011-02-22
dc.date.submittedDecember 2009
dc.identifier.urihttps://hdl.handle.net/1969.1/ETD-TAMU-2009-12-7590
dc.description.abstractThe objective of the project is to use the RICS analysis technique in complement with confocal microscopy to determine the diffusion coefficient of the selectively labeled green fluorescent protein (GFP), GFP-EGFR and GFP-p53 in cervical cancer cells. This is a collaboration work with MD Anderson Cancer Center. The application of the study is to lay the foundation for further study in understanding the cell metabolism, subcellular morphologic and dynamic biochemical processes to aid in the diagnosis and to potentially screen cancers. Fluorescence microscopy techniques have been developed for the study of cellular processes and molecular signal pathway. However, the spatial resolution to distinguish and resolve the interactions of single molecular complexes or molecule in cells is limited by the wavelength. Hence, indirect image correlation methods complementary to the imaging techniques were developed to obtain the dynamic information within the cell. RICS is one such mathematical image processing method to determine the dynamics of the cell. HeLa cells are transfected with GFP to highlight the protein of interest. These samples were imaged with confocal microscope, Olympus FV1000 with a 60 x 1.2 NA water objective in the pseudo photon counting mode with an excitation of 488 nm argon ion laser. About 100 frames of scan area 256x256 pixels were collected from each sample at scan speed of 12.5 seconds per pixel. The stacks of images were processed with SimFCS software. The images were subjected to immobile subtraction algorithm to remove the immobile features. Consequently, each frame in the stack is subjected to 2D-correlation; then, the average 2D-spatial correlation is calculated. This 2D-spatial correlated data constitutes as RICS data which is then displayed and analyzed by fitting it to specific models. This generates a spatial temporal map of the molecular dynamics of fluorescently labeled probes within the cell. In summary, we apply RICS techniques based on correlation spectroscopy to the image data and quantify diffusion coefficient of protein of interest in cancerous cells with different treatments. This is expected to better understand cellular dynamics of cancerous cells and build better diagnostic biosensor devices for early screening.en
dc.format.mimetypeapplication/pdf
dc.language.isoen_US
dc.subjectHeLa cellsen
dc.subjectp53en
dc.subjectRICSen
dc.titleRaster Image Correlation Spectroscopy [RICS] Analysis of HeLa cellsen
dc.typeBooken
dc.typeThesisen
thesis.degree.departmentElectrical and Computer Engineeringen
thesis.degree.disciplineElectrical Engineeringen
thesis.degree.grantorTexas A&M Universityen
thesis.degree.nameMaster of Scienceen
thesis.degree.levelMastersen
dc.contributor.committeeMemberSu, Chin
dc.contributor.committeeMemberCheng, Xing
dc.contributor.committeeMemberChang, Kuang-An
dc.type.genreElectronic Thesisen
dc.type.materialtexten


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record