Matching Items (179)
Description
Aberrant glycosylation has been shown to be linked to specific cancers, and using this idea, it was proposed that the levels of glycans in the blood could predict stage I adenocarcinoma. To track this glycosylation, glycan were broken down into glycan nodes via methylation analysis. This analysis utilized information from N-, O-, and lipid linked glycans detected from gas chromatography-mass spectrometry. The resulting glycan node-ratios represent the initial quantitative data that were used in this experiment.
For this experiment, two Sets of 50 µl blood plasma samples were provided by NYU Medical School. These samples were then analyzed by Dr. Borges’s lab so that they contained normalized biomarker levels from patients with stage 1 adenocarcinoma and control patients with matched age, smoking status, and gender were examined. An ROC curve was constructed under individual and paired conditions and AUC calculated in Wolfram Mathematica 10.2. Methods such as increasing size of training set, using hard vs. soft margins, and processing biomarkers together and individually were used in order to increase the AUC. Using a soft margin for this particular data set was proved to be most useful compared to the initial set hard margin, raising the AUC from 0.6013 to 0.6585. In regards to which biomarkers yielded the better value, 6-Glc/6-Man and 3,6-Gal glycan node ratios had the best with 0.7687 AUC and a sensitivity of .7684 and specificity of .6051. While this is not enough accuracy to become a primary diagnostic tool for diagnosing stage I adenocarcinoma, the methods examined in the paper should be evaluated further. . By comparison, the current clinical standard blood test for prostate cancer that has an AUC of only 0.67.
For this experiment, two Sets of 50 µl blood plasma samples were provided by NYU Medical School. These samples were then analyzed by Dr. Borges’s lab so that they contained normalized biomarker levels from patients with stage 1 adenocarcinoma and control patients with matched age, smoking status, and gender were examined. An ROC curve was constructed under individual and paired conditions and AUC calculated in Wolfram Mathematica 10.2. Methods such as increasing size of training set, using hard vs. soft margins, and processing biomarkers together and individually were used in order to increase the AUC. Using a soft margin for this particular data set was proved to be most useful compared to the initial set hard margin, raising the AUC from 0.6013 to 0.6585. In regards to which biomarkers yielded the better value, 6-Glc/6-Man and 3,6-Gal glycan node ratios had the best with 0.7687 AUC and a sensitivity of .7684 and specificity of .6051. While this is not enough accuracy to become a primary diagnostic tool for diagnosing stage I adenocarcinoma, the methods examined in the paper should be evaluated further. . By comparison, the current clinical standard blood test for prostate cancer that has an AUC of only 0.67.
ContributorsDe Jesus, Celine Spicer (Author) / Taylor, Thomas (Thesis director) / Borges, Chad (Committee member) / School of Mathematical and Statistical Sciences (Contributor) / School of Molecular Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
Course-Based Undergraduate Research Experiences, or CUREs have become an increasingly popular way to integrate research opportunities into the undergraduate biology curriculum. Unlike traditional cookbook labs which provide students with a set experimental design and known outcome, CUREs offer students the opportunity to participate in novel and interesting research that is of interest to the greater biology community. While CUREs have been championed as a way to provide more students with the opportunity to experience, it is unclear whether students benefit differently from participating in different CURE with different structural elements. In this study we focused in on one proposed element of a CURE, collaboration, to determine whether student's perception of this concept change over the course of a CURE and whether it differs among students enrolled in different CUREs. We analyzed pre and post open-ended surveys asking the question "Why might collaboration be important in science?" in two CUREs with different structures of collaboration. We also compared CURE student responses to the responses of senior honors thesis students who had been conducting authentic research. Five themes emerged in response to students' conceptions of collaboration. Comparing two CURE courses, we found that students' conceptions of collaboration were varied within each individual CURE, as well as what students were leaving with compared to the other CURE course. Looking at how student responses compared between 5 different themes, including "Different Perspectives", "Validate/Verify Results", "Compare Results", "Requires Different Expertise", and "Compare results", students appeared to be thinking about collaboration in distinct different ways by lack of continuity in the amount of students discussing each of these among the classes. In addition, we found that student responses in each of the CURE courses were not significantly different for any of the themes except "Different Expertise" compared to the graduating seniors. However, due to the small (n) that the graduating seniors group had, 22, compared to each of the CURE classes composing of 155 and 98 students, this comparison must be taken in a preliminary manner. Overall, students thought differently about collaboration between different CUREs. Still, a gap filling what it means to "collaborate", and whether the structures of CUREs are effective to portray collaboration are still necessary to fully elaborate on this paper's findings.
ContributorsWassef, Cyril Alexander (Author) / Brownell, Sara (Thesis director) / Stout, Valerie (Committee member) / Cooper, Katelyn (Committee member) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
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
ABSTRACT Peptide microarrays may prove to be a powerful tool for proteomics research and clinical diagnosis applications. Fodor et al. and Maurer et al. have shown proof-of-concept methods of light- and electrochemically-directed peptide microarray fabrication on glass and semiconductor microchips respectively. In this work, peptide microarray fabrication based on the abovementioned techniques were optimized. In addition, MALDI mass spectrometry based peptide synthesis characterization on semiconductor microchips was developed and novel applications of a CombiMatrix (CBMX) platform for electrochemically controlled synthesis were explored. We have investigated performance of 2-(2-nitrophenyl)propoxycarbonyl (NPPOC) derivatives as photo-labile protecting group. Specifically, influence of substituents on 4 and 5 positions of phenyl ring of NPPOC group on the rate of photolysis and the yield of the amine was investigated. The results indicated that substituents capable of forming a π-network with the nitro group enhanced the rate of photolysis and yield. Once such properly substituted NPPOC groups were used, the rate of photolysis/yield depended on the nature of protected amino group indicating that a different chemical step during the photo-cleavage process became the rate limiting step. We also focused on electrochemically-directed parallel synthesis of high-density peptide microarrays using the CBMX technology referred to above which uses electrochemically generated acids to perform patterned chemistry. Several issues related to peptide synthesis on the CBMX platform were studied and optimized, with emphasis placed on the reactions of electro-generated acids during the deprotection step of peptide synthesis. We have developed a MALDI mass spectrometry based method to determine the chemical composition of microarray synthesis, directly on the feature. This method utilizes non-diffusional chemical cleavage from the surface, thereby making the chemical characterization of high-density microarray features simple, accurate, and amenable to high-throughput. CBMX Corp. has developed a microarray reader which is based on electro-chemical detection of redox chemical species. Several parameters of the instrument were studied and optimized and novel redox applications of peptide microarrays on CBMX platform were also investigated using the instrument. These include (i) a search of metal binding catalytic peptides to reduce overpotential associated with water oxidation reaction and (ii) an immobilization of peptide microarrays using electro-polymerized polypyrrole.
ContributorsKumar, Pallav (Author) / Woodbury, Neal (Thesis advisor) / Allen, James (Committee member) / Johnston, Stephen (Committee member) / Arizona State University (Publisher)
Created2013
Description
In the Rare-earth-Tri-telluride family, (RTe3s) [R=La, Ce, Nd, Sm, Gd, Tb, Dy, Er, Ho, Tm] the emergence of Charge Density Waves, (CDW) has been under investigation for a long time due to broadly tunable properties by either chemical substitution or pressure application. These quasi 2D Layered materials RTe3s undergo Fermi Surface Nesting leading to CDW instability. CDWs are electronic instabilities found in low-dimensional materials with highly anisotropic electronic structures. Since the CDW is predominantly driven by Fermi-surface (FS) nesting, it is especially sensitive to pressure-induced changes in the electronic structure. The FS of RTe3s is a function of p-orbitals of Tellurium atoms, which are arranged in two adjacent planes in the crystal structure. Although the FS and electronic structure possess a nearly four-fold symmetry, RTe3s form an incommensurate CDW.This dissertation is structured as follows: Chapter 1 includes basic ideas of Quantum materials, followed by an introduction to CDW and RTe3s. In Chapter 2, there are fundamentals of crystal growth by Chemical Vapor Transport, including various precursors, transport agent, temperature gradient, and rate of the reaction. After the growth, the crystals were confirmed for lattice vibrations by Raman, for composition by Energy Dispersive Spectroscopy; crystal structure and orientation were confirmed by X-ray Diffraction; magnetic ordering was established by Vibrating sample measurement. Detailed CDW study was done on various RTe3s by Raman spectroscopy. The basic mechanism and instrumentations used in these characterizations are explained in Chapter 3. Chapter 4 includes experimental data for crystal growth and results of these characterizations for Parent RTe3s. Chapter 5 includes fundamental insights on Cationic alloying of RTe3s, along with one alloy system’s crystal growth and characterization. This work tries to explain the behavior of CDW by a Temperature-dependent Raman study of RTe3s established the CDW transition temperature accompanied by Phonon softening; Angle-resolved Raman data confirming the nearly four-fold symmetry; thickness-dependent Raman spectroscopy resulting in the conclusion that as thickness decreases CDW transition temperature increases. Also, CDW transition is analyzed as a function of alloying.
ContributorsAttarde, Yashika (Author) / Tongay, Sefaattin (Thesis advisor) / Botana, Antia (Committee member) / Alford, Terry (Committee member) / Arizona State University (Publisher)
Created2021
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
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
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
Computational models have long been used to describe and predict the outcome of complex immunological processes. The dissertation work described here centers on the construction of multiscale computational immunology models that derives biological insights at the population, systems, and atomistic levels. First, SARS-CoV-2 mortality is investigated through the lens of the predicted robustness of CD8+ T cell responses in 23 different populations. The robustness of CD8+ T cell responses in a given population was modeled by predicting the efficiency of endemic MHC-I protein variants to present peptides derived from SARS-CoV-2 proteins to circulating T cells. To accomplish this task, an algorithm, called EnsembleMHC, was developed to predict viral peptides with a high probability of being recognized by CD T cells. It was discovered that there was significant variation in the efficiency of different MHC-I protein variants to present SARS-CoV-2 derived peptides, and countries enriched with variants with high presentation efficiency had significantly lower mortality rates. Second, a biophysics-based MHC-I peptide prediction algorithm was developed. The MHC-I protein is the most polymorphic protein in the human genome with polymorphisms in the peptide binding causing striking changes in the amino acid compositions, or binding motifs, of peptide species capable of stable binding. A deep learning model, coined HLA-Inception, was trained to predict peptide binding using only biophysical properties, namely electrostatic potential. HLA-Inception was shown to be extremely accurate and efficient at predicting peptide binding motifs and was used to determine the peptide binding motifs of 5,821 MHC-I protein variants. Finally, the impact of stalk glycosylations on NL63 protein dynamics was investigated. Previous data has shown that coronavirus crown glycans play an important role in immune evasion and receptor binding, however, little is known about the role of the stalk glycans. Through the integration of computational biology, experimental data, and physics-based simulations, the stalk glycans were shown to heavily influence the bending angle of spike protein, with a particular emphasis on the glycan at position 1242. Further investigation revealed that removal of the N1242 glycan significantly reduced infectivity, highlighting a new potential therapeutic target. Overall, these investigations and associated innovations in integrative modeling.
ContributorsWilson, Eric Andrew (Author) / Anderson, Karen (Thesis advisor) / Singharoy, Abhishek (Thesis advisor) / Woodbury, Neal (Committee member) / Sulc, Petr (Committee member) / Arizona State University (Publisher)
Created2022
Description
In the last few decades, extensive research efforts have been focused on scaling down silicon-based complementary metal-oxide semiconductor (CMOS) technology to enable the continuation of Moore’s law. State-of-art CMOS includes fully depleted silicon-on-insulator (FDSOI) field-effect-transistors (FETs) with ultra-thin silicon channels (6 nm), as well as other three-dimensional (3D) device architectures like Fin-FETs, nanosheet FETs, etc. Significant research efforts have characterized these technologies towards various applications, and at different conditions including a wide range of temperatures from room temperature (300 K) down to cryogenic temperatures. Theoretical efforts have studied ultrascaled devices using Landauer theory to further understand their transport properties and predict their performance in the quasi-ballistic regime.Further scaling of CMOS devices requires the introduction of new semiconducting channel materials, as now established by the research community. Here, two-dimensional (2D) semiconductors have emerged as a promising candidate to replace silicon for next-generation ultrascaled CMOS devices. These emerging 2D semiconductors also have applications beyond CMOS, for example in novel memory, neuromorphic, and spintronic devices. Graphene is a promising candidate for spintronic devices due to its outstanding spin transport properties as evidenced by numerous studies in non-local lateral spin valve (LSV) geometries. The essential components of graphene-based LSV, such as graphene FETs, metal-graphene contacts, and tunneling barriers, were individually investigated as part of this doctoral dissertation.
In this work, several contributions were made to these CMOS and beyond CMOS technologies. This includes comprehensive characterization and modeling of FDSOI nanoscale FETs from room temperature down to cryogenic temperatures. Using Landauer theory for nanoscale transistors, FDSOI devices were analyzed and modeled under quasi-ballistic operation. This was extended towards a virtual-source modeling approach that accounts for temperature-dependent quasi-ballistic transport and back-gate biasing effects. Additionally, graphene devices with ultrathin high-k gate dielectrics were investigated towards FETs, non-volatile memory, and spintronic devices. New contributions were made relating to charge trapping effects and their impact on graphene device electrostatics (Dirac voltage shifts) and transport properties (impact on mobility and conductivity). This work also studied contact resistance and tunneling effects using transfer length method (TLM) graphene FET structures and magnetic tunneling junction (MTJ) towards graphene-based LSV.
ContributorsZhou, Guantong (Author) / Sanchez Esqueda, Ivan (Thesis advisor) / Vasileska, Dragica (Committee member) / Tongay, Sefaattin (Committee member) / Thornton, Trevor (Committee member) / Arizona State University (Publisher)
Created2023