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Disturbances in the protein interactome often play a large role in cancer progression. Investigation of protein-protein interactions (PPI) can increase our understanding of cancer pathways and will disclose unknown targets involved in cancer disease biology. Although numerous methods are available to study protein interactions, most platforms suffer from drawbacks including high false positive rates, low throughput, and lack of quantification. Moreover, most methods are not compatible for use in a clinical setting. To address these limitations, we have developed a multiplexed, in-solution protein microarray (MISPA) platform with broad applications in proteomics. MISPA can be used to quantitatively profile PPIs and as a robust technology for early detection of cancers. This method utilizes unique DNA barcoding of individual proteins coupled with next generation sequencing to quantitatively assess interactions via barcode enrichment. We have tested the feasibility of this technology in the detection of patient immune responses to oropharyngeal carcinomas and in the discovery of novel PPIs in the B-cell receptor (BCR) pathway. To achieve this goal, 96 human papillomavirus (HPV) antigen genes were cloned into pJFT7-cHalo (99% success) and pJFT7-n3xFlag-Halo (100% success) expression vectors. These libraries were expressed via a cell-free in vitro transcription-translation system with 93% and 96% success, respectively. A small-scale study of patient serum interactions with barcoded HPV16 antigens was performed and a HPV proteome-wide study will follow using additional patient samples. In addition, 15 query proteins were cloned into pJFT7_nGST expression vectors, expressed, and purified with 93% success to probe a library of 100 BCR pathway proteins and detect novel PPIs.
ContributorsRinaldi, Capria Lakshmi (Author) / LaBaer, Joshua (Thesis director) / Mangone, Marco (Committee member) / Borges, Chad (Committee member) / School of Molecular Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
Description
Microfluidic platforms have been exploited extensively as a tool for the separation of particles by electric field manipulation. Microfluidic devices can facilitate the manipulation of particles by dielectrophoresis. Separation of particles by size and type has been demonstrated by insulator-based dielectrophoresis in a microfluidic device. Thus, manipulating particles by size has been widely studied throughout the years. It has been shown that size-heterogeneity in organelles has been linked to multiple diseases from abnormal organelle size. Here, a mixture of two sizes of polystyrene beads (0.28 and 0.87 μm) was separated by a ratchet migration mechanism under a continuous flow (20 nL/min). Furthermore, to achieve high-throughput separation, different ratchet devices were designed to achieve high-volume separation. Recently, enormous efforts have been made to manipulate small size DNA and proteins. Here, a microfluidic device comprising of multiple valves acting as insulating constrictions when a potential is applied is presented. The tunability of the electric field gradient is evaluated by a COMSOL model, indicating that high electric field gradients can be reached by deflecting the valve at a certain distance. Experimentally, the tunability of the dynamic constriction was demonstrated by conducting a pressure study to estimate the gap distance between the valve and the substrate at different applied pressures. Finally, as a proof of principle, 0.87 μm polystyrene beads were manipulated by dielectrophoresis. These microfluidic platforms will aid in the understanding of size-heterogeneity of organelles for biomolecular assessment and achieve separation of nanometer-size DNA and proteins by dielectrophoresis.
ContributorsOrtiz, Ricardo (Author) / Ros, Alexandra (Thesis advisor) / Hayes, Mark (Committee member) / Borges, Chad (Committee member) / Arizona State University (Publisher)
Created2021
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 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
Description
In cold chain tracking systems, accuracy and flexibility across different temperatures ranges plays an integral role in monitoring biospecimen integrity. However, while two common cold chain tracking systems are currently available (electronic and physics/chemical), there is not an affordable cold chain tracking mechanism that can be applied to a variety of temperatures while maintaining accuracy for individual vials. Hence, our lab implemented our understanding of biochemical reaction kinetics to develop a new cold chain tracking mechanism using the permanganate/oxalic acid reaction. The permanganate/oxalic acid reaction is characterized by the reduction of permanganate (MnVII) to Mn(II) with Mn(II)-autocatalyzed oxidation of oxalate to CO2, resulting in a pink to colorless visual indicator change when the reaction system is not in the solid state (i.e., frozen or vitrified). Throughout our research, we demonstrate, (i) Improved reaction consistency and accuracy along with extended run times with the implementation of a nitric acid-based labware washing protocol, (ii) Simulated reaction kinetics for the maximum length reaction and 60-minute reaction based on previously developed MATLAB scripts (iii) Experimental reaction kinetics to verify the simulated MATLAB maximum and 60-minute reactions times (iv) Long-term stability of the permanganate/oxalic acid reaction with water or eutectic solutions of sodium perchlorate and magnesium perchlorate at -80°C (v) Reaction kinetics with eutectic solvents, sodium perchlorate and magnesium perchlorate, at 25°C, 4°C, and -8°C (vi) Accelerated reaction kinetics after the addition of varying concentrations of manganese perchlorate (vii) Reaction kinetics of higher concentration reaction systems (5x and 10x; for darker colors), at 25°C (viii) Long-term stability of the 10x higher concentration reaction at -80°C.
ContributorsLjungberg, Emil (Author) / Borges, Chad (Thesis director) / Levitus, Marcia (Committee member) / Williams, Peter (Committee member) / Barrett, The Honors College (Contributor) / School of Molecular Sciences (Contributor) / Department of Psychology (Contributor)
Created2022-12
Description
Interdigitated back contact (IBC) solar cells have achieved the highest single junction silicon wafer-based solar cell power conversion efficiencies reported to date. This thesis is about the fabrication of a high-efficiency silicon heterojunction IBC solar cell for potential use as the bottom cell for a 3-terminal lattice-matched dilute-nitride Ga (In)NP(As)/Si monolithic tandem solar cell. An effective fabrication process has been developed and the process challenges related to open circuit voltage (Voc), series resistance (Rs), and fill factor (FF) are experimentally analyzed. While wet etching, the sample lost the initial passivation, and by changing the etchant solution and passivation process, the voltage at maximum power recovered to an initial value of over 710 mV before metallization. The factors reducing the series resistance loss in IBC cells were also studied. One of these factors was the Indium Tin Oxide (ITO) sputtering parameters, which impact the conductivity of the ITO layer and transport across the a-Si:H/ITO interface. For the standard recipe, the chamber pressure was 3.5 mTorr with no oxygen partial pressure, and the thickness of the ITO layer in contact with the a-Si:H layers, was optimized to 150 nm. The patterning method for the metal contacts and final annealing also change the contact resistance of the base and emitter stack layers. The final annealing step is necessary to recover the sputtering damage; however, the higher the annealing time the higher the final IBC series resistance. The best efficiency achieved was 19.3% (Jsc = 37 mA/cm2, Voc = 691 mV, FF = 71.7%) on 200 µm thick 1-15 Ω-cm n-type CZ C-Si with a designated area of 4 cm2.
ContributorsMoeini Rizi, Mansoure (Author) / Goodnick, Stephen (Thesis advisor) / Honsberg, Christina (Committee member) / Goryll, Michael (Committee member) / Smith, David (Committee member) / Bowden, Stuart (Committee member) / Arizona State University (Publisher)
Created2022
Description
The future will be replete with Artificial Intelligence (AI) based agents closely collaborating with humans. Although it is challenging to construct such systems for real-world conditions, the Intelligent Tutoring System (ITS) community has proposed several techniques to work closely with students. However, there is a need to extend these systems outside the controlled environment of the classroom. More recently, Human-Aware Planning (HAP) community has developed generalized AI techniques for collaborating with humans and providing personalized support or guidance to the collaborators. In this thesis, the take learning from the ITS community is extend to construct such human-aware systems for real-world domains and evaluate them with real stakeholders. First, the applicability of HAP to ITS is demonstrated, by modeling the behavior in a classroom and a state-of-the-art tutoring system called Dragoon. Then these techniques are extended to provide decision support to a human teammate and evaluate the effectiveness of the framework through ablation studies to support students in constructing their plan of study (\ipos). The results show that these techniques are helpful and can support users in their tasks. In the third section of the thesis, an ITS scenario of asking questions (or problems) in active environments is modeled by constructing questions to elicit a human teammate's model of understanding. The framework is evaluated through a user study, where the results show that the queries can be used for eliciting the human teammate's mental model.
ContributorsGrover, Sachin (Author) / Kambhampati, Subbarao (Thesis advisor) / Smith, David (Committee member) / Srivastava, Sidhharth (Committee member) / VanLehn, Kurt (Committee member) / Arizona State University (Publisher)
Created2022
Description
Plasma and serum are the most commonly used liquid biospecimens in biomarker research. These samples may be subjected to several pre-analytical variables (PAVs) during collection, processing and storage. Exposure to thawed conditions (temperatures above -30 °C) is a PAV that is hard to control, and track and could provide misleading information, that fail to accurately reveal the in vivo biological reality, when unaccounted for. Hence, assays that can empirically check the integrity of plasma and serum samples are crucial. As a solution to this issue, an assay titled ΔS-Cys-Albumin was developed and validated. The reference range of ΔS-Cys-Albumin in cardio vascular patients was determined and the change in ΔS-Cys-Albumin values in different samples over time course incubations at room temperature, 4 °C and -20 °C were evaluated. In blind challenges, this assay proved to be successful in identifying improperly stored samples individually and as groups. Then, the correlation between the instability of several clinically important proteins in plasma from healthy and cancer patients at room temperature, 4 °C and -20 °C was assessed. Results showed a linear inverse relationship between the percentage of proteins destabilized and ΔS-Cys-Albumin regardless of the specific time or temperature of exposure, proving ΔS-Cys-Albumin as an effective surrogate marker to track the stability of clinically relevant analytes in plasma. The stability of oxidized LDL in serum at different temperatures was assessed in serum samples and it stayed stable at all temperatures evaluated. The ΔS-Cys-Albumin requires the use of an LC-ESI-MS instrument which limits its availability to most clinical research laboratories. To overcome this hurdle, an absorbance-based assay that can be measured using a plate reader was developed as an alternative to the ΔS-Cys-Albumin assay. Assay development and analytical validation procedures are reported herein. After that, the range of absorbance in plasma and serum from control and cancer patients were determined and the change in absorbance over a time course incubation at room temperature, 4 °C and -20 °C was assessed. The results showed that the absorbance assay would act as a good alternative to the ΔS-Cys-Albumin assay.
ContributorsJehanathan, Nilojan (Author) / Borges, Chad (Thesis advisor) / Guo, Jia (Committee member) / Van Horn, Wade (Committee member) / Arizona State University (Publisher)
Created2022
Description
Written corrective feedback (WCF) has received considerable attention in secondlanguage (L2) writing research. The conducive role of WCF in developing L2 writing and
second language acquisition has been corroborated by a number of theoretical frameworks,
and the findings of empirical studies, meta-analyses, and research syntheses. WCF research
has predominantly addressed its effectiveness in improving learners’ syntactic, lexical, and
orthographic knowledge. This dissertation project extends the scope of this line of research
to formulaic aspects of language and investigates the relative effectiveness of WCF
targeting formulaic vs. non-formulaic constructions in L2 writing. The text-analytic
descriptive aspect of this research design aimed at investigating the extent of L2 learners’
non-target-like use of formulaic vs. non-formulaic forms in L2 writing and writing
teachers’ WCF treatment of non-target (non)formulaic language use. A total of 480 first
drafts of essays written by 33 advanced adult English-as-a-foreign language (EFL) learners
during one semester and 480 drafts of essays corrected through WCF by three EFL teachers
constituted the corpus in this study. Advancing the field of learner corpus research, the
findings demonstrated that whereas learners’ non-target formulaic forms outnumbered that
of non-formulaic ones in their writing assignments, all three teachers provided WCF more
often for erroneous use of non-formulaic forms. The quasi-experimental aspect of the
research design attempts to add new empirical evidence on the L2 learning potential of
accessing and processing WCF provided for formulaic vs. non-formulaic constructions in
L2 writing. To this end, a total of 66 EFL learners in a Test of English as a Foreign
Language preparation course participated in a pretest-posttest design, with 5 experimental groups (those who were provided with direct, indirect, direct plus metalinguistic, and
indirect plus metalinguistic WCF) and a control group (those who were not provided with
WCF). Maintaining a division between formulaic vs. non-formulaic forms, the findings
provide empirical evidence on the interactions between types of WCF, types of linguistic
targets, and the effectiveness of WCF in terms of enhancing L2 learners’ accuracy and
acquisition in their revised writing and new writings in the short and long term.
ContributorsGholami, Leila (Author) / Smith, David (Thesis advisor) / Matsuda, Paul K (Committee member) / James, Mark A (Committee member) / Arizona State University (Publisher)
Created2022
Description
Trace evidence is an essential component of forensic investigations. Anthropogenicmaterials such as fibers and glass have been well studied for use in forensic trace evidence, but the potential use of retroreflective beads found in soils for forensic investigations is largely unexplored. Retroreflective glass beads are tiny spheres mixed into pavement markings to create reflective surfaces to reduce lane departure accidents. Retroreflective glass beads are a potentially new source of trace evidence for forensic investigations.
Analysis of the spatial distribution and chemical compositions of retroreflective glass beads recovered from 17 soil samples were analyzed and compared to see if there are striking variations that can distinguish samples by source. Soil samples taken near marked roads showed significantly higher concentrations of glass beads, averaging from 0.18 bead/g of soil sample to 587 beads/g of soil, while soil samples taken near unmarked roads had average range of concentration of 0 bead/g of soil to 0.21 bead/g of soil. Retroreflective glass beads come from pavement markings, thus soil samples near marked roads are expected to have higher concentrations of glass beads. Analysis of spatial distribution of glass beads showed that as sample collection moved further from the road, concentration of glass beads decreased.
ICP-MS results of elemental concentrations for each sample showed discriminative differences between samples, for most of the elements. An analysis of variance for elemental concentrations was conducted, and results showed statistically significant differences, beyond random chance alone for half of the elements analyzed. For forensic comparisons, a significant difference in even just one element is enough to conclude that the samples came from different sources. The elemental concentrations of glass beads collected from the same location, but of varying differences, was also analyzed. ANOVA results show significant differences for only one or two elements. A pair-wise t-test was conducted to determine which elements are most discriminative among all the samples. Rubidium was found to be the most discriminative, showing significant difference for 67% of the pairs. Beryllium, potassium, and manganese were also highly discriminative, showing significant difference for at least 50% of all the pairs.
ContributorsGomez, Janelle Kate Pacifico (Author) / Montero, Shirly (Thesis advisor) / Herckes, Pierre (Thesis advisor) / Borges, Chad (Committee member) / Gordon, Gwyneth (Committee member) / Arizona State University (Publisher)
Created2023
Description
Type 1 diabetes (T1D) is the result of an autoimmune attack against the insulin-producing β-cells of the pancreas causing hyperglycemia and requiring the individual to rely on life-long exogenous insulin. With the age of onset typically occurring in childhood, there is increased physical and emotional stress to the child as well as caregivers to maintain appropriate glucose levels. The majority of T1D patients have antibodies to one or more antigens: insulin, IA-2, GAD65, and ZnT8. Although antibodies are detectable years before symptoms occur, the initiating factors and mechanisms of progression towards β-cell destruction are still not known. The search for new autoantibodies to elucidate the autoimmune process in diabetes has been slow, with proteome level screenings on native proteins only finding a few minor antigens. Post-translational modifications (PTM)—chemical changes that occur to the protein after translation is complete—are an unexplored way a self-protein could become immunogenic. This dissertation presents the first large sale screening of autoantibodies in T1D to nitrated proteins. The Contra Capture Protein Array (CCPA) allowed for fresh expression of hundreds of proteins that were captured on a secondary slide by tag-specific ligand and subsequent modification with peroxynitrite. The IgG and IgM humoral response of 48 newly diagnosed T1D subjects and 48 age-matched controls were screened against 1632 proteins highly or specifically expressed in pancreatic cells. Top targets at 95% specificity were confirmed with the same serum samples using rapid antigenic protein in situ display enzyme-linked immunosorbent assay (RAPID ELISA) a modified sandwich ELISA employing the same cell-free expression as the CCPA. For validation, 8 IgG and 5 IgM targets were evaluated with an independent serum sample set of 94 T1D subjects and 94 controls. The two best candidates at 90% specificity were estrogen receptor 1 (ESR1) and phosphatidylinositol 4-kinase type 2 beta (PI4K2B) which had sensitivities of 22% (p=.014) and 25% (p=.045), respectively. Receiver operating characteristic (ROC) analyses found an area under curve (AUC) of 0.6 for ESR1 and 0.58 for PI4K2B. These studies demonstrate the ability and value for high-throughput autoantibody screening to modified antigens and the frequency of Type 1 diabetes.
ContributorsHesterman, Jennifer (Author) / LaBaer, Joshua (Thesis advisor) / Borges, Chad (Committee member) / Sweazea, Karen (Committee member) / Mangone, Marco (Committee member) / Arizona State University (Publisher)
Created2022