Matching Items (2)
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- All Subjects: Uncertainty Quantification
- Creators: Crook, Sharon
Description
Optogenetics presents the ability to control membrane dynamics through the usage of transfected proteins (opsins) and light stimulation. However, as the field continues to grow, the original biological and stimulation tools used have become dated or limited in their uses. The usage of Organic Light Emitting Diodes (OLEDs) in optical stimulation offers greater resolution, finer control of pixel arrays, and the increased functionality of a flexible display at the cost of lower irradiance power density. This study was done to simulate methods using genetic and optical tools towards decreasing the threshold irradiance needed to initiate an action potential in a ChR2 expressing neuron. Simulations show that pulsatile stimulation can decrease threshold irradiances by increasing the overall duration of stimulus while keeping individual pulse durations below 5 ms. Furthermore, the redistribution of Channelrhodopsin-2 (ChR2) to the apical dendrites and a change in wavelength to 625 nm both result in lower threshold irradiances. However, the model used has many discrepancies and has room for improvement in areas such as the light distribution model and ChR2 dynamics. The simulations run with this model however still present valuable insight and knowledge towards the usage of new stimulation methods and revisions on existing protocols.
ContributorsKyeh, James (Author) / Muthuswamy, Jitendran (Thesis director) / Crook, Sharon (Committee member) / Harrington Bioengineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
The representation of a patient’s characteristics as the parameters of a model is a key component in many studies of personalized medicine, where the underlying mathematical models are used to describe, explain, and forecast the course of treatment. In this context, clinical observations form the bridge between the mathematical frameworks and applications. However, the formulation and theoretical studies of the models and the clinical studies are often not completely compatible, which is one of the main obstacles in the application of mathematical models in practice. The goal of my study is to extend a mathematical framework to model prostate cancer based mainly on the concept of cell-quota within an evolutionary framework and to study the relevant aspects for the model to gain useful insights in practice. Specifically, the first aim is to construct a mathematical model that can explain and predict the observed clinical data under various treatment combinations. The second aim is to find a fundamental model structure that can capture the dynamics of cancer progression within a realistic set of data. Finally, relevant clinical aspects such as how the patient's parameters change over the course of treatment and how to incorporate treatment optimization within a framework of uncertainty quantification, will be examined to construct a useful framework in practice.
ContributorsPhan, Tin (Author) / Kuang, Yang (Thesis advisor) / Kostelich, Eric J (Committee member) / Crook, Sharon (Committee member) / Maley, Carlo (Committee member) / Bryce, Alan (Committee member) / Arizona State University (Publisher)
Created2021