Matching Items (292)
Description
Students across the United States lack the necessary skills to be successful college students in Science, Technology and Math (STEM) majors and as a result post-secondary institutions are developing summer bridge programs to aid in their transition. As they develop these programs, effective theory and approach are critical to developing successful programs. Though there are a multitude of theories on successful student development, a focus on self-efficacy is critical. Summer Bridge programs across the country as well as the Bio Bridge summer program at Arizona State University were studied alone and through the lens of Cognitive Self-Efficacy Theory as mentioned in Albert Bandura's "Perceived Self-Efficacy in Cognitive Development and Functioning." Cognitive Self-Efficacy Theory provides a framework for self-efficacy development in academic settings. An analysis of fifteen bridge programs found that a large majority focused on developing academic capabilities and often overlooked development of community and social efficacy. An even larger number failed to focus on personal psychology in managing self-debilitating thought patterns based on published goals. Further, Arizona State University's Bio Bridge program could not be considered successful at developing cognitive self-efficacy or increasing retention as data was inconclusive. However, Bio Bridge was tremendously successful at developing social efficacy and community among participants and faculty. Further research and better evaluative techniques need to be developed to understand the program's effectiveness in cognitive self-efficacy development and retention.
ContributorsTummala, Sailesh Vardhan (Author) / Orchinik, Miles (Thesis director) / Brownell, Sara (Committee member) / Shortlidge, Erin (Committee member) / Barrett, The Honors College (Contributor) / School of Life Sciences (Contributor)
Created2015-05
Description
Cancer remains one of the leading killers throughout the world. Death and disability due to lung cancer in particular accounts for one of the largest global economic burdens a disease presents. The burden on third-world countries is especially large due to the unusually large financial stress that comes from late tumor detection and expensive treatment options. Early detection using inexpensive techniques may relieve much of the burden throughout the world, not just in more developed countries. I examined the immune responses of lung cancer patients using immunosignatures – patterns of reactivity between host serum antibodies and random peptides. Immunosignatures reveal disease-specific patterns that are very reproducible. Immunosignaturing is a chip-based method that has the ability to display the antibody diversity from individual sera sample with low cost. Immunosignaturing is a medical diagnostic test that has many applications in current medical research and in diagnosis. From a previous clinical study, patients diagnosed for lung cancer were tested for their immunosignature vs. healthy non-cancer volunteers. The pattern of reactivity against the random peptides (the ‘immunosignature’) revealed common signals in cancer patients, absent from healthy controls. My study involved the search for common amino acid motifs in the cancer-specific peptides. My search through the hundreds of ‘hits’ revealed certain motifs that were repeated more times than expected by random chance. The amino acids that were the most conserved in each set include tryptophan, aspartic acid, glutamic acid, proline, alanine, serine, and lysine. The most overall conserved amino acid observed between each set was D - aspartic acid. The motifs were short (no more than 5-6 amino acids in a row), but the total number of motifs I identified was large enough to assure significance. I utilized Excel to organize the large peptide sequence libraries, then CLUSTALW to cluster similar-sequence peptides, then GLAM2 to find common themes in groups of peptides. In so doing, I found sequences that were also present in translated cancer expression libraries (RNA) that matched my motifs, suggesting that immunosignatures can find cancer-specific antigens that can be both diagnostic and potentially therapeutic.
ContributorsShiehzadegan, Shima (Author) / Johnston, Stephen (Thesis director) / Stafford, Phillip (Committee member) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2015-12
Description
Collaborative learning has been found to enhance student learning experiences through interaction with peers and instructors in a way that typically does not occur in a traditional lecture course. However, more than half of all collaborative learning structures have failed to last very long after their initial introductions which makes understanding the factors of collaboration that make it successful very important. The purpose of this study was to evaluate collaborative learning in a blended learning course to gauge student perceptions and the factors of collaboration and student demographics that impact that perception. This was done by surveying a sample of students in BIO 282 about their experiences in the BIO 281 course they took previously which was a new introductory Biology course with a blended learning structure. It was found that students agree that collaboration is beneficial as it provides an opportunity to gain additional insight from peers and improve students' understanding of course content. Also, differences in student gender and first generation status have less of an effect on student perceptions of collaboration than differences in academic achievement (grade) bracket.
ContributorsVu, Bethany Thao-Vy (Author) / Stout, Valerie (Thesis director) / Brownell, Sara (Committee member) / Wright, Christian (Committee member) / Barrett, The Honors College (Contributor) / School of Life Sciences (Contributor)
Created2014-05
Description
The influenza virus, also known as "the flu", is an infectious disease that has constantly affected the health of humanity. There is currently no known cure for Influenza. The Center for Innovations in Medicine at the Biodesign Institute located on campus at Arizona State University has been developing synbodies as a possible Influenza therapeutic. Specifically, at CIM, we have attempted to design these initial synbodies to target the entire Influenza virus and preliminary data leads us to believe that these synbodies target Nucleoprotein (NP). Given that the synbody targets NP, the penetration of cells via synbody should also occur. Then by Western Blot analysis we evaluated for the diminution of NP level in treated cells versus untreated cells. The focus of my honors thesis is to explore how synthetic antibodies can potentially inhibit replication of the Influenza (H1N1) A/Puerto Rico/8/34 strain so that a therapeutic can be developed. A high affinity synbody for Influenza can be utilized to test for inhibition of Influenza as shown by preliminary data. The 5-5-3819 synthetic antibody's internalization in live cells was visualized with Madin-Darby Kidney Cells under a Confocal Microscope. Then by Western Blot analysis we evaluated for the diminution of NP level in treated cells versus untreated cells. Expression of NP over 8 hours time was analyzed via Western Blot Analysis, which showed NP accumulation was retarded in synbody treated cells. The data obtained from my honors thesis and preliminary data provided suggest that the synthetic antibody penetrates live cells and targets NP. The results of my thesis presents valuable information that can be utilized by other researchers so that future experiments can be performed, eventually leading to the creation of a more effective therapeutic for influenza.
ContributorsHayden, Joel James (Author) / Diehnelt, Chris (Thesis director) / Johnston, Stephen (Committee member) / Legutki, Bart (Committee member) / Barrett, The Honors College (Contributor) / Department of Psychology (Contributor) / Department of Chemistry and Biochemistry (Contributor)
Created2014-05
Description
Identifying disease biomarkers may aid in the early detection of breast cancer and improve patient outcomes. Recent evidence suggests that tumors are immunogenic and therefore patients may launch an autoantibody response to tumor associated antigens. Single-chain variable fragments of autoantibodies derived from regional lymph node B cells of breast cancer patients were used to discover these tumor associated biomarkers on protein microarrays. Six candidate biomarkers were discovered from 22 heavy chain-only variable region antibody fragments screened. Validation tests are necessary to confirm the tumorgenicity of these antigens. However, the use of single-chain variable autoantibody fragments presents a novel platform for diagnostics and cancer therapeutics.
ContributorsSharman, M. Camila (Author) / Magee, Dewey (Mitch) (Thesis director) / Wallstrom, Garrick (Committee member) / Petritis, Brianne (Committee member) / Barrett, The Honors College (Contributor) / College of Liberal Arts and Sciences (Contributor) / Virginia G. Piper Center for Personalized Diagnostics (Contributor) / Biodesign Institute (Contributor)
Created2012-12
Description
We, a team of students and faculty in the life sciences at Arizona State University (ASU), currently teach an Introduction to Biology course in a Level 5, or maximum-security unit with the support of the Arizona Department of Corrections and the Prison Education Program at ASU. This course aims to enhance current programs at the unit by offering inmates an opportunity to practice literacy and math skills, while also providing exposure to a new academic field (science, and specifically biology). Numerous studies, including a 2005 study from the Arizona Department of Corrections (ADC), have found that vocational programs, including prison education programs, reduce recidivism rates (ADC 2005, Esperian 2010, Jancic 1988, Steurer et al. 2001, Ubic 2002) and may provide additional benefits such as engagement with a world outside the justice system (Duguid 1992), the opportunity for inmates to revise personal patterns of rejecting education that they may regret, and the ability of inmate parents to deliberately set a good example for their children (Hall and Killacky 2008). Teaching in a maximum security prison unit poses special challenges, which include a prohibition on most outside materials (except paper), severe restrictions on student-teacher and student-student interactions, and the inability to perform any lab exercises except limited computer simulations. Lack of literature discussing theoretical and practical aspects of teaching science in such environment has prompted us to conduct an ongoing study to generate notes and recommendations from this class through the use of surveys, academic evaluation of students' work and ongoing feedback from both teachers and students to inform teaching practices in future science classes in high-security prison units.
ContributorsLarson, Anika Jade (Author) / Mor, Tsafrir (Thesis director) / Brownell, Sara (Committee member) / Lockard, Joe (Committee member) / Barrett, The Honors College (Contributor) / School of Politics and Global Studies (Contributor) / School of Life Sciences (Contributor)
Created2015-05
Description
Recent studies suggest a role for the microbiota in autism spectrum disorders (ASD), potentially arising from their role in modulating the immune system and gastrointestinal (GI) function or from gut–brain interactions dependent or independent from the immune system. GI problems such as chronic constipation and/or diarrhea are common in children with ASD, and significantly worsen their behavior and their quality of life. Here we first summarize previously published data supporting that GI dysfunction is common in individuals with ASD and the role of the microbiota in ASD. Second, by comparing with other publically available microbiome datasets, we provide some evidence that the shifted microbiota can be a result of westernization and that this shift could also be framing an altered immune system. Third, we explore the possibility that gut–brain interactions could also be a direct result of microbially produced metabolites.
ContributorsKrajmalnik-Brown, Rosa (Author) / Lozupone, Catherine (Author) / Kang, Dae Wook (Author) / Adams, James (Author) / Biodesign Institute (Contributor)
Created2015-03-12
Description
Background
Drosophila melanogaster has been established as a model organism for investigating the developmental gene interactions. The spatio-temporal gene expression patterns of Drosophila melanogaster can be visualized by in situ hybridization and documented as digital images. Automated and efficient tools for analyzing these expression images will provide biological insights into the gene functions, interactions, and networks. To facilitate pattern recognition and comparison, many web-based resources have been created to conduct comparative analysis based on the body part keywords and the associated images. With the fast accumulation of images from high-throughput techniques, manual inspection of images will impose a serious impediment on the pace of biological discovery. It is thus imperative to design an automated system for efficient image annotation and comparison.
Results
We present a computational framework to perform anatomical keywords annotation for Drosophila gene expression images. The spatial sparse coding approach is used to represent local patches of images in comparison with the well-known bag-of-words (BoW) method. Three pooling functions including max pooling, average pooling and Sqrt (square root of mean squared statistics) pooling are employed to transform the sparse codes to image features. Based on the constructed features, we develop both an image-level scheme and a group-level scheme to tackle the key challenges in annotating Drosophila gene expression pattern images automatically. To deal with the imbalanced data distribution inherent in image annotation tasks, the undersampling method is applied together with majority vote. Results on Drosophila embryonic expression pattern images verify the efficacy of our approach.
Conclusion
In our experiment, the three pooling functions perform comparably well in feature dimension reduction. The undersampling with majority vote is shown to be effective in tackling the problem of imbalanced data. Moreover, combining sparse coding and image-level scheme leads to consistent performance improvement in keywords annotation.
Drosophila melanogaster has been established as a model organism for investigating the developmental gene interactions. The spatio-temporal gene expression patterns of Drosophila melanogaster can be visualized by in situ hybridization and documented as digital images. Automated and efficient tools for analyzing these expression images will provide biological insights into the gene functions, interactions, and networks. To facilitate pattern recognition and comparison, many web-based resources have been created to conduct comparative analysis based on the body part keywords and the associated images. With the fast accumulation of images from high-throughput techniques, manual inspection of images will impose a serious impediment on the pace of biological discovery. It is thus imperative to design an automated system for efficient image annotation and comparison.
Results
We present a computational framework to perform anatomical keywords annotation for Drosophila gene expression images. The spatial sparse coding approach is used to represent local patches of images in comparison with the well-known bag-of-words (BoW) method. Three pooling functions including max pooling, average pooling and Sqrt (square root of mean squared statistics) pooling are employed to transform the sparse codes to image features. Based on the constructed features, we develop both an image-level scheme and a group-level scheme to tackle the key challenges in annotating Drosophila gene expression pattern images automatically. To deal with the imbalanced data distribution inherent in image annotation tasks, the undersampling method is applied together with majority vote. Results on Drosophila embryonic expression pattern images verify the efficacy of our approach.
Conclusion
In our experiment, the three pooling functions perform comparably well in feature dimension reduction. The undersampling with majority vote is shown to be effective in tackling the problem of imbalanced data. Moreover, combining sparse coding and image-level scheme leads to consistent performance improvement in keywords annotation.
ContributorsSun, Qian (Author) / Muckatira, Sherin (Author) / Yuan, Lei (Author) / Ji, Shuiwang (Author) / Newfeld, Stuart (Author) / Kumar, Sudhir (Author) / Ye, Jieping (Author) / Biodesign Institute (Contributor) / Center for Evolution and Medicine (Contributor) / College of Liberal Arts and Sciences (Contributor) / School of Life Sciences (Contributor) / Ira A. Fulton Schools of Engineering (Contributor)
Created2013-12-03
Description
Background
“Stoichioproteomics” relates the elemental composition of proteins and proteomes to variation in the physiological and ecological environment. To help harness and explore the wealth of hypotheses made possible under this framework, we introduce GRASP (http://www.graspdb.net), a public bioinformatic knowledgebase containing information on the frequencies of 20 amino acids and atomic composition of their side chains. GRASP integrates comparative protein composition data with annotation data from multiple public databases. Currently, GRASP includes information on proteins of 12 sequenced Drosophila (fruit fly) proteomes, which will be expanded to include increasingly diverse organisms over time. In this paper we illustrate the potential of GRASP for testing stoichioproteomic hypotheses by conducting an exploratory investigation into the composition of 12 Drosophila proteomes, testing the prediction that protein atomic content is associated with species ecology and with protein expression levels.
Results
Elements varied predictably along multivariate axes. Species were broadly similar, with the D. willistoni proteome a clear outlier. As expected, individual protein atomic content within proteomes was influenced by protein function and amino acid biochemistry. Evolution in elemental composition across the phylogeny followed less predictable patterns, but was associated with broad ecological variation in diet. Using expression data available for D. melanogaster, we found evidence consistent with selection for efficient usage of elements within the proteome: as expected, nitrogen content was reduced in highly expressed proteins in most tissues, most strongly in the gut, where nutrients are assimilated, and least strongly in the germline.
Conclusions
The patterns identified here using GRASP provide a foundation on which to base future research into the evolution of atomic composition in Drosophila and other taxa.
“Stoichioproteomics” relates the elemental composition of proteins and proteomes to variation in the physiological and ecological environment. To help harness and explore the wealth of hypotheses made possible under this framework, we introduce GRASP (http://www.graspdb.net), a public bioinformatic knowledgebase containing information on the frequencies of 20 amino acids and atomic composition of their side chains. GRASP integrates comparative protein composition data with annotation data from multiple public databases. Currently, GRASP includes information on proteins of 12 sequenced Drosophila (fruit fly) proteomes, which will be expanded to include increasingly diverse organisms over time. In this paper we illustrate the potential of GRASP for testing stoichioproteomic hypotheses by conducting an exploratory investigation into the composition of 12 Drosophila proteomes, testing the prediction that protein atomic content is associated with species ecology and with protein expression levels.
Results
Elements varied predictably along multivariate axes. Species were broadly similar, with the D. willistoni proteome a clear outlier. As expected, individual protein atomic content within proteomes was influenced by protein function and amino acid biochemistry. Evolution in elemental composition across the phylogeny followed less predictable patterns, but was associated with broad ecological variation in diet. Using expression data available for D. melanogaster, we found evidence consistent with selection for efficient usage of elements within the proteome: as expected, nitrogen content was reduced in highly expressed proteins in most tissues, most strongly in the gut, where nutrients are assimilated, and least strongly in the germline.
Conclusions
The patterns identified here using GRASP provide a foundation on which to base future research into the evolution of atomic composition in Drosophila and other taxa.
ContributorsGilbert, James D. J. (Author) / Acquisti, Claudia (Author) / Martinson, Holly M. (Author) / Elser, James (Author) / Kumar, Sudhir (Author) / Fagan, William F. (Author) / Biodesign Institute (Contributor) / Center for Evolution and Medicine (Contributor) / College of Liberal Arts and Sciences (Contributor) / School of Life Sciences (Contributor)
Created2013-09-04
Description
Background
Improvements in sequencing technology now allow easy acquisition of large datasets; however, analyzing these data for phylogenetics can be challenging. We have developed a novel method to rapidly obtain homologous genomic data for phylogenetics directly from next-generation sequencing reads without the use of a reference genome. This software, called SISRS, avoids the time consuming steps of de novo whole genome assembly, multiple genome alignment, and annotation.
Results
For simulations SISRS is able to identify large numbers of loci containing variable sites with phylogenetic signal. For genomic data from apes, SISRS identified thousands of variable sites, from which we produced an accurate phylogeny. Finally, we used SISRS to identify phylogenetic markers that we used to estimate the phylogeny of placental mammals. We recovered eight phylogenies that resolved the basal relationships among mammals using datasets with different levels of missing data. The three alternate resolutions of the basal relationships are consistent with the major hypotheses for the relationships among mammals, all of which have been supported previously by different molecular datasets.
Conclusions
SISRS has the potential to transform phylogenetic research. This method eliminates the need for expensive marker development in many studies by using whole genome shotgun sequence data directly. SISRS is open source and freely available at https://github.com/rachelss/SISRS/releases.
Improvements in sequencing technology now allow easy acquisition of large datasets; however, analyzing these data for phylogenetics can be challenging. We have developed a novel method to rapidly obtain homologous genomic data for phylogenetics directly from next-generation sequencing reads without the use of a reference genome. This software, called SISRS, avoids the time consuming steps of de novo whole genome assembly, multiple genome alignment, and annotation.
Results
For simulations SISRS is able to identify large numbers of loci containing variable sites with phylogenetic signal. For genomic data from apes, SISRS identified thousands of variable sites, from which we produced an accurate phylogeny. Finally, we used SISRS to identify phylogenetic markers that we used to estimate the phylogeny of placental mammals. We recovered eight phylogenies that resolved the basal relationships among mammals using datasets with different levels of missing data. The three alternate resolutions of the basal relationships are consistent with the major hypotheses for the relationships among mammals, all of which have been supported previously by different molecular datasets.
Conclusions
SISRS has the potential to transform phylogenetic research. This method eliminates the need for expensive marker development in many studies by using whole genome shotgun sequence data directly. SISRS is open source and freely available at https://github.com/rachelss/SISRS/releases.
ContributorsSchwartz, Rachel (Author) / Harkins, Kelly (Author) / Stone, Anne (Author) / Cartwright, Reed (Author) / Biodesign Institute (Contributor) / Center for Evolution and Medicine (Contributor) / College of Liberal Arts and Sciences (Contributor) / School of Human Evolution and Social Change (Contributor) / School of Life Sciences (Contributor)
Created2015-06-11