Matching Items (6)
- Genre: Academic theses
- Creators: Arizona State University
- Creators: McIntyre, Sean
- Member of: ASU Electronic Theses and Dissertations
This work demonstrated a novel microfluidic device based on direct current (DC) insulator based dielectrophoresis (iDEP) for trapping individual mammalian cells in a microfluidic device. The novel device is also applicable for selective trapping of weakly metastatic mammalian breast cancer cells (MCF-7) from mixtures with mammalian Peripheral Blood Mononuclear Cells (PBMC) and highly metastatic mammalian breast cancer cells, MDA-MB-231. The advantage of this approach is the ease of integration of iDEP structures in microfliudic channels using soft lithography, the use of DC electric fields, the addressability of the single cell traps for downstream analysis and the straightforward multiplexing for single cell trapping. These microfluidic devices are targeted for capturing of single cells based on their DEP behavior. The numerical simulations point out the trapping regions in which single cell DEP trapping occurs. This work also demonstrates the cell conductivity values of different cell types, calculated using the single-shell model. Low conductivity buffers are used for trapping experiments. These low conductivity buffers help reduce the Joule heating. Viability of the cells in the buffer system was studied in detail with a population size of approximately 100 cells for each study. The work also demonstrates the development of the parallelized single cell trap device with optimized traps. This device is also capable of being coupled detection of target protein using MALDI-MS.
Efficient separation techniques for organelles and bacteria in the micron- and sub-micron range are required for various analytical challenges. Mitochondria have a wide size range resulting from the sub-populations, some of which may be associated with diseases or aging. However, traditional methods can often not resolve within-species size variations. Strategies to separate mitochondrial sub-populations by size are thus needed to study the importance of this organelle in cellular functions. Additionally, challenges also exist in distinguishing the sub-populations of bio-species which differ in the surface charge while possessing similar size, such as Salmonella typhimurium (Salmonella). The surface charge of Salmonella wild-type is altered upon environmental stimulations, influencing the bacterial survival and virulence within the host tissue. Therefore, it is important to explore methods to identify the sub-populations of Salmonella.
This work exploits insulator-based dielectrophoresis (iDEP) for the manipulation of mitochondria and Salmonella. The iDEP migration and trapping of mitochondria were investigated under both DC and low-frequency AC conditions, establishing that mitochondria exhibit negative DEP. Also, the first realization of size-based iDEP sorting experiments of mitochondria were demonstrated. As for Salmonella, the preliminary study revealed positive DEP behavior. Distinct trapping potential thresholds were found for the sub-populations with different surface charges.
Further, DEP was integrated with a non-intuitive migration mechanism termed absolute negative mobility (ANM), inducing a deterministic trapping component which allows the directed transport of µm- and sub-µm sized (bio)particles in microfluidic devices with a nonlinear post array under the periodic action of electrokinetic and dielectrophoretic forces. Regimes were revealed both numerically and experimentally in which larger particles migrate against the average applied force, whereas smaller particles show normal response. Moreover, this deterministic ANM (dANM) was characterized with polystyrene beads demonstrating improved migration speed at least two orders of magnitude higher compared to previous ANM systems with similar sized colloids. In addition, dANM was induced for mitochondria with an AC-overlaid waveform representing the first demonstration of ANM migration with biological species. Thus, it is envisioned that the efficient size selectivity of this novel migration mechanism can be employed in nanotechnology, organelle sub-population studies or fractionating protein nanocrystals.
The large-scale anthropogenic emission of carbon dioxide into the atmosphere leads to many unintended consequences, from rising sea levels to ocean acidification. While a clean energy infrastructure is growing, mid-term strategies that are compatible with the current infrastructure should be developed. Carbon capture and storage in fossil-fuel power plants is one way to avoid our current gigaton-scale emission of carbon dioxide into the atmosphere. However, for this to be possible, separation techniques are necessary to remove the nitrogen from air before combustion or from the flue gas after combustion. Metal-organic frameworks (MOFs) are a relatively new class of porous material that show great promise for adsorptive separation processes. Here, potential mechanisms of O2/N2 separation and CO2/N2 separation are explored.
First, a logical categorization of potential adsorptive separation mechanisms in MOFs is outlined by comparing existing data with previously studied materials. Size-selective adsorptive separation is investigated for both gas systems using molecular simulations. A correlation between size-selective equilibrium adsorptive separation capabilities and pore diameter is established in materials with complex pore distributions. A method of generating mobile extra-framework cations which drastically increase adsorptive selectivity toward nitrogen over oxygen via electrostatic interactions is explored through experiments and simulations. Finally, deposition of redox-active ferrocene molecules into systematically generated defects is shown to be an effective method of increasing selectivity towards oxygen.
A new challenge on the horizon is to utilize the large amounts of protein found in the atmosphere to identify different organisms from which the protein originated. Included here is work investigating the presence of identifiable patterns of different proteins collected from the air and biological samples for the purposes of remote identification. Protein patterns were generated using high performance liquid chromatography (HPLC). Patterns created could identify high-traffic and low-traffic indoor spaces. Samples were collected from the air using air pumps to draw air through a filter paper trapping particulates, including large amounts of shed protein matter. In complimentary research aerosolized biological samples were collected from various ecosystems throughout Ecuador to explore the relationship between environmental setting and aerosolized protein concentrations. In order to further enhance protein separation and produce more detailed patterns for the identification of individual organisms of interest; a novel separation device was constructed and characterized. The separation device incorporates a longitudinal gradient as well as insulating dielectrophoretic features within a single channel. This design allows for the production of stronger local field gradients along a global gradient allowing particles to enter, initially transported through the channel by electrophoresis and electroosmosis, and to be isolated according to their characteristic physical properties, including charge, polarizability, deformability, surface charge mobility, dielectric features, and local capacitance. Thus, different types of particles are simultaneously separated at different points along the channel distance given small variations of properties. The device has shown the ability to separate analytes over a large dynamic range of size, from 20 nm to 1 μm, roughly the size of proteins to the size of cells. In the study of different sized sulfate capped polystyrene particles were shown to be selectively captured as well as concentrating particles from 103 to 106 times. Qualitative capture and manipulation of β-amyloid fibrils were also shown. The results demonstrate the selective focusing ability of the technique; and it may form the foundation for a versatile tool for separating complex mixtures. Combined this work shows promise for future identification of individual organisms from aerosolized protein as well as for applications in biomedical research.
Rapid and reliable separation and analysis of proteins require powerful analytical methods. The analysis of proteins becomes especially challenging when only small sample volumes are available, concomitantly with low concentrations of proteins. Time critical situations pose additional challenges. Due to these challenges, conventional macro-scale separation techniques reach their limitations. While microfluidic devices require only pL-nL sample volumes, they offer several advantages such as speed, efficiency, and high throughput. This work elucidates the capability to manipulate proteins in a rapid and reliable manner with a novel migration technique, namely dielectrophoresis (DEP). Since protein analysis can often be achieved through a combination of orthogonal techniques, adding DEP as a gradient technique to the portfolio of protein manipulation methods can extend and improve combinatorial approaches. To this aim, microfluidic devices tailored with integrated insulating obstacles were fabricated to create inhomogeneous electric fields evoking insulator-based DEP (iDEP). A main focus of this work was the development of pre-concentration devices where topological micropost arrays are fabricated using standard photo- and soft lithographic techniques. With these devices, positive DEP-driven streaming of proteins was demonstrated for the first time using immunoglobulin G (IgG) and bovine serum albumin. Experimentally observed iDEP concentrations of both proteins were in excellent agreement with positive DEP concentration profiles obtained by numerical simulations. Moreover, the micropost iDEP devices were improved by introducing nano-constrictions with focused ion beam milling with which numerical simulations suggested enhancement of the DEP effect, leading to a 12-fold increase in concentration of IgG. Additionally, concentration of β-galactosidase was observed, which seems to occur due to an interplay of negative DEP, electroosmosis, electrokinesis, diffusion, and ion concentration polarization. A detailed study was performed to investigate factors influencing protein DEP under DC conditions, including electroosmosis, electrophoresis, and Joule heating. Specifically, temperature rise within the iDEP device due to Joule heating was measured experimentally with spatial and temporal resolution by employing the thermosensitive dye Rhodamine B. Unlike DNA and cells, protein DEP behavior is not well understood to date. Therefore, this detailed study of protein DEP provides novel information to eventually optimize this protein migration method for pre-concentration, separation, and fractionation.
Optimal design theory provides a general framework for the construction of experimental designs for categorical responses. For a binary response, where the possible result is one of two outcomes, the logistic regression model is widely used to relate a set of experimental factors with the probability of a positive (or negative) outcome. This research investigates and proposes alternative designs to alleviate the problem of separation in small-sample D-optimal designs for the logistic regression model. Separation causes the non-existence of maximum likelihood parameter estimates and presents a serious problem for model fitting purposes.
First, it is shown that exact, multi-factor D-optimal designs for the logistic regression model can be susceptible to separation. Several logistic regression models are specified, and exact D-optimal designs of fixed sizes are constructed for each model. Sets of simulated response data are generated to estimate the probability of separation in each design. This study proves through simulation that small-sample D-optimal designs are prone to separation and that separation risk is dependent on the specified model. Additionally, it is demonstrated that exact designs of equal size constructed for the same models may have significantly different chances of encountering separation.
The second portion of this research establishes an effective strategy for augmentation, where additional design runs are judiciously added to eliminate separation that has occurred in an initial design. A simulation study is used to demonstrate that augmenting runs in regions of maximum prediction variance (MPV), where the predicted probability of either response category is 50%, most reliably eliminates separation. However, it is also shown that MPV augmentation tends to yield augmented designs with lower D-efficiencies.
The final portion of this research proposes a novel compound optimality criterion, DMP, that is used to construct locally optimal and robust compromise designs. A two-phase coordinate exchange algorithm is implemented to construct exact locally DMP-optimal designs. To address design dependence issues, a maximin strategy is proposed for designating a robust DMP-optimal design. A case study demonstrates that the maximin DMP-optimal design maintains comparable D-efficiencies to a corresponding Bayesian D-optimal design while offering significantly improved separation performance.