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Description
Single cell analysis has become increasingly important in understanding disease onset, progression, treatment and prognosis, especially when applied to cancer where cellular responses are highly heterogeneous. Through the advent of single cell computerized tomography (Cell-CT), researchers and clinicians now have the ability to obtain high resolution three-dimensional (3D) reconstructions of

Single cell analysis has become increasingly important in understanding disease onset, progression, treatment and prognosis, especially when applied to cancer where cellular responses are highly heterogeneous. Through the advent of single cell computerized tomography (Cell-CT), researchers and clinicians now have the ability to obtain high resolution three-dimensional (3D) reconstructions of single cells. Yet to date, no live-cell compatible version of the technology exists. In this thesis, a microfluidic chip with the ability to rotate live single cells in hydrodynamic microvortices about an axis parallel to the optical focal plane has been demonstrated. The chip utilizes a novel 3D microchamber design arranged beneath a main channel creating flow detachment into the chamber, producing recirculating flow conditions. Single cells are flowed through the main channel, held in the center of the microvortex by an optical trap, and rotated by the forces induced by the recirculating fluid flow. Computational fluid dynamics (CFD) was employed to optimize the geometry of the microchamber. Two methods for the fabrication of the 3D microchamber were devised: anisotropic etching of silicon and backside diffuser photolithography (BDPL). First, the optimization of the silicon etching conditions was demonstrated through design of experiment (DOE). In addition, a non-conventional method of soft-lithography was demonstrated which incorporates the use of two positive molds, one of the main channel and the other of the microchambers, compressed together during replication to produce a single ultra-thin (<200 µm) negative used for device assembly. Second, methods for using thick negative photoresists such as SU-8 with BDPL have been developed which include a new simple and effective method for promoting the adhesion of SU-8 to glass. An assembly method that bonds two individual ultra-thin (<100 µm) replications of the channel and the microfeatures has also been demonstrated. Finally, a pressure driven pumping system with nanoliter per minute flow rate regulation, sub-second response times, and < 3% flow variability has been designed and characterized. The fabrication and assembly of this device is inexpensive and utilizes simple variants of conventional microfluidic fabrication techniques, making it easily accessible to the single cell analysis community.
ContributorsMyers, Jakrey R (Author) / Meldrum, Deirdre (Thesis advisor) / Johnson, Roger (Committee member) / Frakes, David (Committee member) / Arizona State University (Publisher)
Created2012
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Description
Traditional Reinforcement Learning (RL) assumes to learn policies with respect to reward available from the environment but sometimes learning in a complex domain requires wisdom which comes from a wide range of experience. In behavior based robotics, it is observed that a complex behavior can be described by a combination

Traditional Reinforcement Learning (RL) assumes to learn policies with respect to reward available from the environment but sometimes learning in a complex domain requires wisdom which comes from a wide range of experience. In behavior based robotics, it is observed that a complex behavior can be described by a combination of simpler behaviors. It is tempting to apply similar idea such that simpler behaviors can be combined in a meaningful way to tailor the complex combination. Such an approach would enable faster learning and modular design of behaviors. Complex behaviors can be combined with other behaviors to create even more advanced behaviors resulting in a rich set of possibilities. Similar to RL, combined behavior can keep evolving by interacting with the environment. The requirement of this method is to specify a reasonable set of simple behaviors. In this research, I present an algorithm that aims at combining behavior such that the resulting behavior has characteristics of each individual behavior. This approach has been inspired by behavior based robotics, such as the subsumption architecture and motor schema-based design. The combination algorithm outputs n weights to combine behaviors linearly. The weights are state dependent and change dynamically at every step in an episode. This idea is tested on discrete and continuous environments like OpenAI’s “Lunar Lander” and “Biped Walker”. Results are compared with related domains like Multi-objective RL, Hierarchical RL, Transfer learning, and basic RL. It is observed that the combination of behaviors is a novel way of learning which helps the agent achieve required characteristics. A combination is learned for a given state and so the agent is able to learn faster in an efficient manner compared to other similar approaches. Agent beautifully demonstrates characteristics of multiple behaviors which helps the agent to learn and adapt to the environment. Future directions are also suggested as possible extensions to this research.
ContributorsVora, Kevin Jatin (Author) / Zhang, Yu (Thesis advisor) / Yang, Yezhou (Committee member) / Praharaj, Sarbeswar (Committee member) / Arizona State University (Publisher)
Created2021
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Description
Cellular heterogeneity is a key factor in various cellular processes as well as in disease development, especially associated with immune response and cancer progression. Cell-to-cell variability is considered to be one of the major obstacles in early detection and successful treatment of cancer. Most present technologies are based on

Cellular heterogeneity is a key factor in various cellular processes as well as in disease development, especially associated with immune response and cancer progression. Cell-to-cell variability is considered to be one of the major obstacles in early detection and successful treatment of cancer. Most present technologies are based on bulk cell analysis, which results in averaging out the results acquired from a group of cells and hence missing important information about individual cells and their behavior. Understanding the cellular behavior at the single-cell level can help in obtaining a complete profile of the cell and to get a more in-depth knowledge of cellular processes. For example, measuring transmembrane fluxes oxygen can provide a direct readout of the cell metabolism.

The goal of this thesis is to design, optimize and implement a device that can measure the oxygen consumption rate (OCR) of live single cells. A microfluidic device has been designed with the ability to rapidly seal and unseal microchambers containing individual cells and an extracellular optical oxygen sensor for measuring the OCR of live single cells. The device consists of two parts, one with the sensor in microwells (top half) and the other with channels and cells trapped in Pachinko-type micro-traps (bottom half). When the two parts of the device are placed together the wells enclose each cell. Oil is flown in through the channels of the device to produce isolated and sealed microchamber around each cell. Different fluids can be flowed in and out of the device, alternating with oil, to rapidly switch between sealed and unsealed microenvironment around each cell. A fluorescent ratiometric dual pH and oxygen sensor is placed in each well. The thesis focuses on measuring changes in the oxygen consumption rate of each cell within a well. Live and dead cells are identified using a fluorescent live/dead cell assay. Finally, the technology is designed to be scalable for high-throughput applications by controlling the flow rate of the system and increasing the cell array density.
ContributorsRodrigues, Meryl (Author) / Meldrum, Deirdre (Thesis advisor) / Kelbauskas, Laimonas (Committee member) / LaBelle, Jeffrey (Committee member) / Arizona State University (Publisher)
Created2014