Matching Items (337)
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Description

Myxoma virus (MYXV) is Leporipoxvirus that possesses a specific rabbit‐restricted host tropism but exhibits a much broader cellular host range in cultured cells. MYXV is able to efficiently block all aspects of the type I interferon (IFN)‐induced antiviral state in rabbit cells, partially in human cells and very poorly in

Myxoma virus (MYXV) is Leporipoxvirus that possesses a specific rabbit‐restricted host tropism but exhibits a much broader cellular host range in cultured cells. MYXV is able to efficiently block all aspects of the type I interferon (IFN)‐induced antiviral state in rabbit cells, partially in human cells and very poorly in mouse cells. The mechanism(s) of this species‐specific inhibition of type I IFN‐induced antiviral state is not well understood. Here we demonstrate that MYXV encoded protein M029, a truncated relative of the vaccinia virus (VACV) E3 double‐stranded RNA (dsRNA) binding protein that inhibits protein kinase R (PKR), can also antagonize the type I IFN‐induced antiviral state in a highly species‐specific manner. In cells pre‐treated with type I IFN prior to infection, MYXV exploits M029 to overcome the induced antiviral state completely in rabbit cells, partially in human cells, but not at all in mouse cells. However, in cells pre‐infected with MYXV, IFN‐induced signaling is fully inhibited even in the absence of M029 in cells from all three species, suggesting that other MYXV protein(s) apart from M029 block IFN signaling in a speciesindependent manner. We also show that the antiviral state induced in rabbit, human or mouse cells by type I IFN can inhibit M029‐knockout MYXV even when PKR is genetically knocked‐out, suggesting that M029 targets other host proteins for this antiviral state inhibition. Thus, the MYXV dsRNA binding protein M029 not only antagonizes PKR from multiple species but also blocks the type I IFN antiviral state independently of PKR in a highly species‐specific fashion.

Created2017-02-02
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Description
Breast cancer is the leading cause of cancer-related deaths of women in the united states. Traditionally, Breast cancer is predominantly treated by a combination of surgery, chemotherapy, and radiation therapy. However, due to the significant negative side effects associated with these traditional treatments, there has been substantial efforts to develo

Breast cancer is the leading cause of cancer-related deaths of women in the united states. Traditionally, Breast cancer is predominantly treated by a combination of surgery, chemotherapy, and radiation therapy. However, due to the significant negative side effects associated with these traditional treatments, there has been substantial efforts to develop alternative therapies to treat cancer. One such alternative therapy is a peptide-based therapeutic cancer vaccine. Therapeutic cancer vaccines enhance an individual's immune response to a specific tumor. They are capable of doing this through artificial activation of tumor specific CTLs (Cytotoxic T Lymphocytes). However, in order to artificially activate tumor specific CTLs, a patient must be treated with immunogenic epitopes derived from their specific cancer type. We have identified that the tumor associated antigen, TPD52, is an ideal target for a therapeutic cancer vaccine. This designation was due to the overexpression of TPD52 in a variety of different cancer types. In order to start the development of a therapeutic cancer vaccine for TPD52-related cancers, we have devised a two-step strategy. First, we plan to create a list of potential TPD52 epitopes by using epitope binding and processing prediction tools. Second, we plan to attempt to experimentally identify MHC class I TPD52 epitopes in vitro. We identified 942 potential 9 and 10 amino acid epitopes for the HLAs A1, A2, A3, A11, A24, B07, B27, B35, B44. These epitopes were predicted by using a combination of 3 binding prediction tools and 2 processing prediction tools. From these 942 potential epitopes, we selected the top 50 epitopes ranked by a combination of binding and processing scores. Due to the promiscuity of some predicted epitopes for multiple HLAs, we ordered 38 synthetic epitopes from the list of the top 50 epitope. We also performed a frequency analysis of the TPD52 protein sequence and identified 3 high volume regions of high epitope production. After the epitope predictions were completed, we proceeded to attempt to experimentally detected presented TPD52 epitopes. First, we successful transduced parental K562 cells with TPD52. After transduction, we started the optimization process for the immunoprecipitation protocol. The optimization of the immunoprecipitation protocol proved to be more difficult than originally believed and was the main reason that we were unable to progress past the transduction of the parental cells. However, we believe that we have identified the issues and will be able to complete the experiment in the coming months.
ContributorsWilson, Eric Andrew (Author) / Anderson, Karen (Thesis director) / Borges, Chad (Committee member) / School of Molecular Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
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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
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Description

Background: The relationship between relative metabolic disturbances and developmental disorders is an emerging research focus. This study compares the nutritional and metabolic status of children with autism with that of neurotypical children and investigates the possible association of autism severity with biomarkers.

Method:Participants were children ages 5-16 years in Arizona with Autistic

Background: The relationship between relative metabolic disturbances and developmental disorders is an emerging research focus. This study compares the nutritional and metabolic status of children with autism with that of neurotypical children and investigates the possible association of autism severity with biomarkers.

Method:Participants were children ages 5-16 years in Arizona with Autistic Spectrum Disorder (n = 55) compared with non-sibling, neurotypical controls (n = 44) of similar age, gender and geographical distribution. Neither group had taken any vitamin/mineral supplements in the two months prior to sample collection. Autism severity was assessed using the Pervasive Development Disorder Behavior Inventory (PDD-BI), Autism Treatment Evaluation Checklist (ATEC), and Severity of Autism Scale (SAS). Study measurements included: vitamins, biomarkers of vitamin status, minerals, plasma amino acids, plasma glutathione, and biomarkers of oxidative stress, methylation, sulfation and energy production.

Results: Biomarkers of children with autism compared to those of controls using a t-test or Wilcoxon test found the following statistically significant differences (p < 0.001): Low levels of biotin, plasma glutathione, RBC SAM, plasma uridine, plasma ATP, RBC NADH, RBC NADPH, plasma sulfate (free and total), and plasma tryptophan; also high levels of oxidative stress markers and plasma glutamate. Levels of biomarkers for the neurotypical controls were in good agreement with accessed published reference ranges. In the Autism group, mean levels of vitamins, minerals, and most amino acids commonly measured in clinical care were within published reference ranges. A stepwise, multiple linear regression analysis demonstrated significant associations between several groups of biomarkers with all three autism severity scales, including vitamins (adjusted R[superscript 2] of 0.25-0.57), minerals (adj. R[superscript 2] of 0.22-0.38), and plasma amino acids (adj. R[superscript 2] of 0.22-0.39).

Conclusion: The autism group had many statistically significant differences in their nutritional and metabolic status, including biomarkers indicative of vitamin insufficiency, increased oxidative stress, reduced capacity for energy transport, sulfation and detoxification. Several of the biomarker groups were significantly associated with variations in the severity of autism. These nutritional and metabolic differences are generally in agreement with other published results and are likely amenable to nutritional supplementation. Research investigating treatment and its relationship to the co-morbidities and etiology of autism is warranted.

ContributorsAdams, James (Author) / Audhya, Tapan (Author) / McDonough-Means, Sharon (Author) / Rubin, Robert A. (Author) / Quig, David (Author) / Geis, Elizabeth (Author) / Gehn, Eva (Author) / Loresto, Melissa (Author) / Mitchell, Jessica (Author) / Atwood, Sharon (Author) / Barnhouse, Suzanne (Author) / Lee, Wondra (Author) / Ira A. Fulton Schools of Engineering (Contributor)
Created2011-06-08
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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
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Description

Background: Vitamin/mineral supplements are among the most commonly used treatments for autism, but the research on their use for treating autism has been limited.

Method: This study is a randomized, double-blind, placebo-controlled three month vitamin/mineral treatment study. The study involved 141 children and adults with autism, and pre and post symptoms of autism

Background: Vitamin/mineral supplements are among the most commonly used treatments for autism, but the research on their use for treating autism has been limited.

Method: This study is a randomized, double-blind, placebo-controlled three month vitamin/mineral treatment study. The study involved 141 children and adults with autism, and pre and post symptoms of autism were assessed. None of the participants had taken a vitamin/mineral supplement in the two months prior to the start of the study. For a subset of the participants (53 children ages 5-16) pre and post measurements of nutritional and metabolic status were also conducted.

Results: The vitamin/mineral supplement was generally well-tolerated, and individually titrated to optimum benefit. Levels of many vitamins, minerals, and biomarkers improved/increased showing good compliance and absorption. Statistically significant improvements in metabolic status were many including: total sulfate (+17%, p = 0.001), S-adenosylmethionine (SAM; +6%, p = 0.003), reduced glutathione (+17%, p = 0.0008), ratio of oxidized glutathione to reduced glutathione (GSSG:GSH; -27%, p = 0.002), nitrotyrosine (-29%, p = 0.004), ATP (+25%, p = 0.000001), NADH (+28%, p = 0.0002), and NADPH (+30%, p = 0.001). Most of these metabolic biomarkers improved to normal or near-normal levels. The supplement group had significantly greater improvements than the placebo group on the Parental Global Impressions-Revised (PGI-R, Average Change, p = 0.008), and on the subscores for Hyperactivity (p = 0.003), Tantrumming (p = 0.009), Overall (p = 0.02), and Receptive Language (p = 0.03). For the other three assessment tools the difference between treatment group and placebo group was not statistically significant. Regression analysis revealed that the degree of improvement on the Average Change of the PGI-R was strongly associated with several biomarkers (adj. R[superscript 2] = 0.61, p < 0.0005) with the initial levels of biotin and vitamin K being the most significant (p < 0.05); both biotin and vitamin K are made by beneficial intestinal flora.

Conclusions: Oral vitamin/mineral supplementation is beneficial in improving the nutritional and metabolic status of children with autism, including improvements in methylation, glutathione, oxidative stress, sulfation, ATP, NADH, and NADPH. The supplement group had significantly greater improvements than did the placebo group on the PGI-R Average Change. This suggests that a vitamin/mineral supplement is a reasonable adjunct therapy to consider for most children and adults with autism.

ContributorsAdams, James (Author) / Audhya, Tapan (Author) / McDonough-Means, Sharon (Author) / Rubin, Robert A. (Author) / Quig, David (Author) / Geis, Elizabeth (Author) / Gehn, Eva (Author) / Loresto, Melissa (Author) / Mitchell, Jessica (Author) / Atwood, Sharon (Author) / Barnhouse, Suzanne (Author) / Lee, Wondra (Author) / Autism/Asperger's Research Program (Contributor)
Created2011-12-12
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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