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Title:Using resonant MEMS pedestal sensors and filtering techniques to determine the growth curve of MDA-MB-231, metastatic breast cancer cells
Author(s):Keller, Katrina
Advisor(s):Bashir, Rashid
Department / Program:Bioengineering
Degree Granting Institution:University of Illinois at Urbana-Champaign
Subject(s):Microelectromechanical systems (MEMS)
Abstract:Studying cells at the individual level is incredibly important for understanding underlying mechanisms for growth, cell cycle control, cell mass, cell adhesion to surfaces, and ultimately the nature of cancer cells. A resonant pedestal sensor was used to study single, adherent cells non-invasively. This measurement tool was preferred over other methods because the mass uniformity of its surface is independent of the location of the cell. Images were taken at each time point to aid in the data processing. This resonant pedestal sensor was fabricated in a cleanroom facility and used to measure the mass of an individual MDA-MB-231 (metastatic breast cancer) cell. The noisy mass measurements were subjected to two different processing methods: Savitzky-Golay and Moving Average. Our main goal in performing these two techniques was to determine the most appropriate processing method for our data. We found the Savitzky-Golay method to be more favorable than the moving average to interpret the MDA-MB-231 cell growth curves. Once outlier exclusion was performed on the data, a positive linear relationship was visible and we were able to calculate the percent change of this cell type: 1% of cell mass is increased per hour.
Issue Date:2014-01-16
Rights Information:Copyright 2013 Katrina Keller
Date Available in IDEALS:2014-01-16
Date Deposited:2013-12

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