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Use of the Multiple Myeloma Immunosignature for the Synthesis of Synbody Therapeutic Treatment

Description

Currently, treatment for multiple myeloma (MM), a hematological cancer, is limited to post-symptomatic chemotherapy combined with other pharmaceuticals and steroids. Even so, the immuno-depressing cancer can continue to proliferate, leading to a median survival period of two to five years. B cells in the bone marrow are responsible for generating…

Currently, treatment for multiple myeloma (MM), a hematological cancer, is limited to post-symptomatic chemotherapy combined with other pharmaceuticals and steroids. Even so, the immuno-depressing cancer can continue to proliferate, leading to a median survival period of two to five years. B cells in the bone marrow are responsible for generating antigen-specific antibodies, but in MM the B cells express mutated, non-specific monoclonal antibodies. Therefore, it is hypothesized that antibody-based assay and therapy may be feasible for detecting and treating the disease. In this project, 330k peptide microarrays were used to ascertain the binding affinity of sera antibodies for MM patients with random sequence peptides; these results were then contrasted with normal donor assays to determine the "immunosignatures" for MM. From this data, high-binding peptides with target-specificity (high fluorescent intensity for one patient, low in all other patients and normal donors) were selected for two MM patients. These peptides were narrowed down to two lists of five (10 total peptides) to analyze in a synthetic antibody study. The rationale behind this originates from the idea that antibodies present specific binding sites on either of their branches, thus relating high binding peptides from the arrays to potential binding targets of the monoclonal antibodies. Furthermore, these peptides may be synthesized on a synthetic antibody scaffold with the potential to induce targeted delivery of radioactive or chemotherapeutic molecular tags to only myelomic B cells. If successful, this would provide a novel alternative to current treatments that is less invasive, has fewer side effects, more specifically targets the cause of MM, and reliably diagnoses the cancer in the presymptomatic stage.

ContributorsBerry, Jameson (Co-author) / Buelt, Allison (Co-author) / Johnston, Stephen (Thesis director) / Diehnelt, Chris (Committee member) / School of Molecular Sciences (Contributor) / School of International Letters and Cultures (Contributor) / Division of Teacher Preparation (Contributor) / Barrett, The Honors College (Contributor)

Created2016-05

Probabilistic Modeling and Regression Analysis of Experimental Data for Structural Systems

Description

The Experimental Data Processing (EDP) software is a C++ GUI-based application to streamline the process of creating a model for structural systems based on experimental data. EDP is designed to process raw data, filter the data for noise and outliers, create a fitted model to describe that data, complete a…

The Experimental Data Processing (EDP) software is a C++ GUI-based application to streamline the process of creating a model for structural systems based on experimental data. EDP is designed to process raw data, filter the data for noise and outliers, create a fitted model to describe that data, complete a probabilistic analysis to describe the variation between replicates of the experimental process, and analyze reliability of a structural system based on that model. In order to help design the EDP software to perform the full analysis, the probabilistic and regression modeling aspects of this analysis have been explored. The focus has been on creating and analyzing probabilistic models for the data, adding multivariate and nonparametric fits to raw data, and developing computational techniques that allow for these methods to be properly implemented within EDP. For creating a probabilistic model of replicate data, the normal, lognormal, gamma, Weibull, and generalized exponential distributions have been explored. Goodness-of-fit tests, including the chi-squared, Anderson-Darling, and Kolmogorov-Smirnoff tests, have been used in order to analyze the effectiveness of any of these probabilistic models in describing the variation of parameters between replicates of an experimental test. An example using Young's modulus data for a Kevlar-49 Swath stress-strain test was used in order to demonstrate how this analysis is performed within EDP. In order to implement the distributions, numerical solutions for the gamma, beta, and hypergeometric functions were implemented, along with an arbitrary precision library to store numbers that exceed the maximum size of double-precision floating point digits. To create a multivariate fit, the multilinear solution was created as the simplest solution to the multivariate regression problem. This solution was then extended to solve nonlinear problems that can be linearized into multiple separable terms. These problems were solved analytically with the closed-form solution for the multilinear regression, and then by using a QR decomposition to solve numerically while avoiding numerical instabilities associated with matrix inversion. For nonparametric regression, or smoothing, the loess method was developed as a robust technique for filtering noise while maintaining the general structure of the data points. The loess solution was created by addressing concerns associated with simpler smoothing methods, including the running mean, running line, and kernel smoothing techniques, and combining the ability of each of these methods to resolve those issues. The loess smoothing method involves weighting each point in a partition of the data set, and then adding either a line or a polynomial fit within that partition. Both linear and quadratic methods were applied to a carbon fiber compression test, showing that the quadratic model was more accurate but the linear model had a shape that was more effective for analyzing the experimental data. Finally, the EDP program itself was explored to consider its current functionalities for processing data, as described by shear tests on carbon fiber data, and the future functionalities to be developed. The probabilistic and raw data processing capabilities were demonstrated within EDP, and the multivariate and loess analysis was demonstrated using R. As the functionality and relevant considerations for these methods have been developed, the immediate goal is to finish implementing and integrating these additional features into a version of EDP that performs a full streamlined structural analysis on experimental data.

ContributorsMarkov, Elan Richard (Author) / Rajan, Subramaniam (Thesis director) / Khaled, Bilal (Committee member) / Chemical Engineering Program (Contributor) / School of Mathematical and Statistical Sciences (Contributor) / Ira A. Fulton School of Engineering (Contributor) / Barrett, The Honors College (Contributor)

Created2016-05

Microbiota Transfer Therapy Alters Gut Ecosystem and Improves Gastrointestinal and Autism Symptoms: An Open-Label Study

Description

Background: Autism spectrum disorders (ASD) are complex neurobiological disorders that impair social interactions and communication and lead to restricted, repetitive, and stereotyped patterns of behavior, interests, and activities. The causes of these disorders remain poorly understood, but gut microbiota, the 1013 bacteria in the human intestines, have been implicated because children…

Background: Autism spectrum disorders (ASD) are complex neurobiological disorders that impair social interactions and communication and lead to restricted, repetitive, and stereotyped patterns of behavior, interests, and activities. The causes of these disorders remain poorly understood, but gut microbiota, the 1013 bacteria in the human intestines, have been implicated because children with ASD often suffer gastrointestinal (GI) problems that correlate with ASD severity. Several previous studies have reported abnormal gut bacteria in children with ASD. The gut microbiome-ASD connection has been tested in a mouse model of ASD, where the microbiome was mechanistically linked to abnormal metabolites and behavior. Similarly, a study of children with ASD found that oral non-absorbable antibiotic treatment improved GI and ASD symptoms, albeit temporarily. Here, a small open-label clinical trial evaluated the impact of Microbiota Transfer Therapy (MTT) on gut microbiota composition and GI and ASD symptoms of 18 ASD-diagnosed children.

Results: MTT involved a 2-week antibiotic treatment, a bowel cleanse, and then an extended fecal microbiota transplant (FMT) using a high initial dose followed by daily and lower maintenance doses for 7–8 weeks. The Gastrointestinal Symptom Rating Scale revealed an approximately 80% reduction of GI symptoms at the end of treatment, including significant improvements in symptoms of constipation, diarrhea, indigestion, and abdominal pain. Improvements persisted 8 weeks after treatment. Similarly, clinical assessments showed that behavioral ASD symptoms improved significantly and remained improved 8 weeks after treatment ended. Bacterial and phage deep sequencing analyses revealed successful partial engraftment of donor microbiota and beneficial changes in the gut environment. Specifically, overall bacterial diversity and the abundance of Bifidobacterium, Prevotella, and Desulfovibrio among other taxa increased following MTT, and these changes persisted after treatment stopped (followed for 8 weeks).

Conclusions: This exploratory, extended-duration treatment protocol thus appears to be a promising approach to alter the gut microbiome and virome and improve GI and behavioral symptoms of ASD. Improvements in GI symptoms, ASD symptoms, and the microbiome all persisted for at least 8 weeks after treatment ended, suggesting a long-term impact.

ContributorsKang, Dae Wook (Author) / Adams, James (Author) / Gregory, Ann C. (Author) / Borody, Thomas (Author) / Chittick, Lauren (Author) / Fasano, Alessio (Author) / Khoruts, Alexander (Author) / Geis, Elizabeth (Author) / Maldonado Ortiz, Juan (Author) / McDonough-Means, Sharon (Author) / Pollard, Elena (Author) / Roux, Simon (Author) / Sadowsky, Michael J. (Author) / Schwarzberg Lipson, Karen (Author) / Sullivan, Matthew B. (Author) / Caporaso, J. Gregory (Author) / Krajmalnik-Brown, Rosa (Author) / Biodesign Institute (Contributor)

Created2017-01-23

Reduced Incidence of Prevotella and Other Fermenters in Intestinal Microflora of Autistic Children

Description

High proportions of autistic children suffer from gastrointestinal (GI) disorders, implying a link between autism and abnormalities in gut microbial functions. Increasing evidence from recent high-throughput sequencing analyses indicates that disturbances in composition and diversity of gut microbiome are associated with various disease conditions. However, microbiome-level studies on autism are…

High proportions of autistic children suffer from gastrointestinal (GI) disorders, implying a link between autism and abnormalities in gut microbial functions. Increasing evidence from recent high-throughput sequencing analyses indicates that disturbances in composition and diversity of gut microbiome are associated with various disease conditions. However, microbiome-level studies on autism are limited and mostly focused on pathogenic bacteria. Therefore, here we aimed to define systemic changes in gut microbiome associated with autism and autism-related GI problems. We recruited 20 neurotypical and 20 autistic children accompanied by a survey of both autistic severity and GI symptoms. By pyrosequencing the V2/V3 regions in bacterial 16S rDNA from fecal DNA samples, we compared gut microbiomes of GI symptom-free neurotypical children with those of autistic children mostly presenting GI symptoms. Unexpectedly, the presence of autistic symptoms, rather than the severity of GI symptoms, was associated with less diverse gut microbiomes. Further, rigorous statistical tests with multiple testing corrections showed significantly lower abundances of the genera Prevotella, Coprococcus, and unclassified Veillonellaceae in autistic samples. These are intriguingly versatile carbohydrate-degrading and/or fermenting bacteria, suggesting a potential influence of unusual diet patterns observed in autistic children. However, multivariate analyses showed that autism-related changes in both overall diversity and individual genus abundances were correlated with the presence of autistic symptoms but not with their diet patterns. Taken together, autism and accompanying GI symptoms were characterized by distinct and less diverse gut microbial compositions with lower levels of Prevotella, Coprococcus, and unclassified Veillonellaceae.

ContributorsKang, Dae Wook (Author) / Park, Jin (Author) / Ilhan, Zehra (Author) / Wallstrom, Garrick (Author) / LaBaer, Joshua (Author) / Adams, James (Author) / Krajmalnik-Brown, Rosa (Author) / Biodesign Institute (Contributor)

Created2013-06-03

The Simian Barrier Dilemma: Improving Gene Vaccines for the Future

Description

Since its inception in the early 1990s, the concept of gene vaccines, particularly DNA vaccines, has enticed researchers across the board due to its simple design, flexible modification, and overall inexpensive cost of manufacturing. However, the past three decades have proven to be less fruitful than anticipated as scientists have…

Since its inception in the early 1990s, the concept of gene vaccines, particularly DNA vaccines, has enticed researchers across the board due to its simple design, flexible modification, and overall inexpensive cost of manufacturing. However, the past three decades have proven to be less fruitful than anticipated as scientists have yet to tackle the issue of inducing a strong enough response in humans and non-human primates to protect against foreign pathogens, an issue that has since been coined as the “simian barrier.” This appears to be a human/primate barrier as protective vaccines have been produced for other mammals. Despite millions of dollars in research along with some of the world’s brightest minds chipping in to resolve this, there has yet to be any truly viable solution to overcoming this barrier. With current research illustrating effective applications of RNA vaccines in humans, these studies may be uncovering the solution to the largely unsolved simian barrier dilemma. If vaccines using RNA, the transcribed version of DNA, are effective in humans, the problem may be inefficient transcription of the DNA. This may be attributable to a DNA promoter that has insufficient activity in primates. Additionally, with DNA vaccines being even cheaper and easier to manufacture than RNA vaccines, along with having no required cold chain for distribution, this concept remains more promising than RNA vaccines that are further along in clinical trials.

ContributorsWillis, Joshua Aaron (Author) / Johnston, Stephen (Thesis director) / Sykes, Kathryn (Committee member) / Shen, Luhui (Committee member) / Dean, W.P. Carey School of Business (Contributor) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)

Created2020-12

Developing a Framework for the in-situ Analysis of Artists’ Prints and Paintings via Hyperspectral Imaging

Description

Hyperspectral imaging is a novel technology which allows for the collection of reflectance spectra of a sample in-situ and at a distance. A rapidly developing technology, hyperspectral imaging has been of particular interest in the field of art characterization, authentication, and conservation as it avoids the pitfalls of traditional characterization…

Hyperspectral imaging is a novel technology which allows for the collection of reflectance spectra of a sample in-situ and at a distance. A rapidly developing technology, hyperspectral imaging has been of particular interest in the field of art characterization, authentication, and conservation as it avoids the pitfalls of traditional characterization techniques and allows for the rapid and wide collection of data never before possible. It is hypothesized that by combining the power of hyperspectral imaging with machine learning, a new framework for the in-situ and automated characterization and authentication of artworks can be developed. This project, using the CMYK set of inks, began the preliminary development of such a framework. It was found that hyperspectral imaging and machine learning as a combination show significant potential as an avenue for art authentication, though further progress and research is needed to match the reliability of status quo techniques.

ContributorsChowdhury, Tanzil Aziz (Author) / Newman, Nathan (Thesis director) / Tongay, Sefaattin (Committee member) / School of Politics and Global Studies (Contributor) / Materials Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)

Created2020-05

Controllable Doping of Transition Metal Dichalcogenides by Chemical Vapor Transport

Description

Transition metal dichalcogenides (TMDs) are a family of layered crystals with the chemical formula MX2 (M = W, Nb, Mo, Ta and X = S, Se, Te). These TMDs exhibit many fascinating optical and electronic properties making them strong candidates for high-end electronics, optoelectronic application, and spintronics. The layered structure…

Transition metal dichalcogenides (TMDs) are a family of layered crystals with the chemical formula MX2 (M = W, Nb, Mo, Ta and X = S, Se, Te). These TMDs exhibit many fascinating optical and electronic properties making them strong candidates for high-end electronics, optoelectronic application, and spintronics. The layered structure of TMDs allows the crystal to be mechanically exfoliated to a monolayer limit, where bulk-scale properties no longer apply and quantum effects arise, including an indirect-to-direct bandgap transition. Controllably tuning the electronic properties of TMDs like WSe2 is therefore a highly attractive prospect achieved by substitutionally doping the metal atoms to enable n- and p-type doping at various concentrations, which can ultimately lead to more effective electronic devices due to increased charge carriers, faster transmission times and possibly new electronic and optical properties to be probed. WSe2 is expected to exhibit the largest spin splitting size and spin-orbit coupling, which leads to exciting potential applications in spintronics over its similar TMD counterparts, which can be controlled through electrical doping. Unfortunately, the well-established doping technique of ion implantation is unable to preserve the crystal quality leading to a major roadblock for the electronics applications of tungsten diselenide. Synthesizing WSe2 via chemical vapor transport (CVT) and flux method have been previously established, but controllable p-type (niobium) doping WSe2 in low concentrations ranges (<1 at %) by CVT methods requires further experimentation and study. This work studies the chemical vapor transport synthesis of doped-TMD W1-xNbxSe2 through characterization techniques of X-ray Diffraction, Scanning Electron Microscopy, Energy Dispersive X-ray Spectroscopy, and X-ray Photoelectron Spectroscopy techniques. In this work, it is observed that excess selenium transport does not enhance the controllability of niobium doping in WSe2, and that tellurium tetrachloride (TeCl4) transport has several barriers in successfully incorporating niobium into WSe2.

ContributorsRuddick, Hayley (Author) / Tongay, Sefaattin (Thesis director) / Jiao, Yang (Committee member) / Barrett, The Honors College (Contributor) / Materials Science and Engineering Program (Contributor)

Created2024-05

Evaluating The Effects of Fumonisin B1 on the Human Gut Microbiome with in vitro Bioreactors

Description

Fumonisins are fungal metabolites found in corn and cereals. Fumonisins pose health risks, including suspected carcinogenicity, yet their mechanism of toxicity remains unclear. While modifications in the human gut microbiome can impact host health, the effects of fumonisins on the microbiome are not well understood. Thus, our study aimed to…

Fumonisins are fungal metabolites found in corn and cereals. Fumonisins pose health risks, including suspected carcinogenicity, yet their mechanism of toxicity remains unclear. While modifications in the human gut microbiome can impact host health, the effects of fumonisins on the microbiome are not well understood. Thus, our study aimed to assess a possible dose-response relationship between fumonisin B1 (FB1) and the gut microbiome. We utilized in vitro anaerobic bioreactors with media simulating most of the nutrients in the human large intestine, inoculated them with fecal samples from 19 healthy adults and treated them with FB1 at concentrations of 0, 10, 100, and 1000 ppb. Analyses of bioreactor headspace revealed declining methane production over time, possibly influenced by the addition of dimethyl sulfoxide (DMSO). Significant differences in acetic acid production were observed in 10 ppb reactor (Day 2) and 100 ppb reactor (Day 8) when compared to 0 ppb control. Microbiome analysis showed minimal shifts in microbial relative abundances during FB1 treatment, except for Desulfovibrio desulfuricans C at Day 8 when compared between 0 ppb and 10 ppb as well as 10 ppb and 1000 ppb at Day 16. Alpha diversity analyses indicated significant differences in observed features within bioreactors of different treatments, with some variation in Faith’s Phylogenetic Diversity between the 0 ppb and 10 ppb bioreactors. Beta diversity analyses, however, revealed no significant differences between bioreactors. Overall, our findings suggest no clear dose-response relationship between FB1 treatment and gut microbiome composition/functions. The presence of DMSO may have obscured potential effects. This research will help contribute to our understanding of mycotoxicity influence on the human gut microbiome.

ContributorsSanchez Carreon, Aurely (Author) / Krajmalnik-Brown, Rosa (Thesis director) / Cheng, Qiwen (Committee member) / Barrett, The Honors College (Contributor) / School of Molecular Sciences (Contributor)

Created2024-05