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- Language: English
- Creators: Ira A. Fulton Schools of Engineering
Description
The purpose of this thesis creative project was to create an educational video to present research findings on the increasingly important issue of human biospecimen preanalytic variables. When a human biospecimen, such as blood, urine, or tissue, is removed from the body, it is subjected to a plethora of variables that are not recorded or regulated in a vast majority of cases. Frequently, these samples arrive at the research or pathology lab with an unknown history, then undergo analysis for translational research purposes, or to guide clinical management decisions. Thus, compromised specimen quality caused by preanalytic variables has substantial, and potentially devastating, downstream effects. To identify the preanalytic variables with the greatest impact on blood and tissue specimen quality, 45 articles were gathered using PubMed and Google Scholar databases and cited. Based on the articles, the top five variables with the most detrimental effects were identified for both blood and tissue samples. Multiple sets of parameters ensuring specimen fitness were compared for each of the five variables for each specimen type. Then, specific parameters guaranteeing the fitness of the greatest number of analytes were verified. To present the research findings in greater detail, a paper was written that focused on identifying the top variables and key parameters to ensure analyte fitness. To present the overall issue in an easy-to-digest format, a storyboard and script were created as a guideline for a final video project. Ultimately, two alternate versions of the video were created to pertain to the audience of choice (one version for patients, one version for professionals). It is the hope that these videos will be used as educational tools to continue efforts to standardize and enforce human biospecimen preanalytic variable parameters. This is a necessary step to improve the accuracy of our biomedical research data and the healthcare of patients worldwide.
ContributorsAzcarate, Heather (Author) / Compton, Carolyn (Thesis director) / LaBaer, Joshua (Committee member) / Borges, Chad (Committee member) / Barrett, The Honors College (Contributor) / Department of Psychology (Contributor)
Created2018-12
Learning Sparse Representations for Fruit-Fly Gene Expression Pattern Image Annotation and Retrieval
Description
Background
Fruit fly embryogenesis is one of the best understood animal development systems, and the spatiotemporal gene expression dynamics in this process are captured by digital images. Analysis of these high-throughput images will provide novel insights into the functions, interactions, and networks of animal genes governing development. To facilitate comparative analysis, web-based interfaces have been developed to conduct image retrieval based on body part keywords and images. Currently, the keyword annotation of spatiotemporal gene expression patterns is conducted manually. However, this manual practice does not scale with the continuously expanding collection of images. In addition, existing image retrieval systems based on the expression patterns may be made more accurate using keywords.
Results
In this article, we adapt advanced data mining and computer vision techniques to address the key challenges in annotating and retrieving fruit fly gene expression pattern images. To boost the performance of image annotation and retrieval, we propose representations integrating spatial information and sparse features, overcoming the limitations of prior schemes.
Conclusions
We perform systematic experimental studies to evaluate the proposed schemes in comparison with current methods. Experimental results indicate that the integration of spatial information and sparse features lead to consistent performance improvement in image annotation, while for the task of retrieval, sparse features alone yields better results.
Fruit fly embryogenesis is one of the best understood animal development systems, and the spatiotemporal gene expression dynamics in this process are captured by digital images. Analysis of these high-throughput images will provide novel insights into the functions, interactions, and networks of animal genes governing development. To facilitate comparative analysis, web-based interfaces have been developed to conduct image retrieval based on body part keywords and images. Currently, the keyword annotation of spatiotemporal gene expression patterns is conducted manually. However, this manual practice does not scale with the continuously expanding collection of images. In addition, existing image retrieval systems based on the expression patterns may be made more accurate using keywords.
Results
In this article, we adapt advanced data mining and computer vision techniques to address the key challenges in annotating and retrieving fruit fly gene expression pattern images. To boost the performance of image annotation and retrieval, we propose representations integrating spatial information and sparse features, overcoming the limitations of prior schemes.
Conclusions
We perform systematic experimental studies to evaluate the proposed schemes in comparison with current methods. Experimental results indicate that the integration of spatial information and sparse features lead to consistent performance improvement in image annotation, while for the task of retrieval, sparse features alone yields better results.
ContributorsYuan, Lei (Author) / Woodard, Alexander (Author) / Ji, Shuiwang (Author) / Jiang, Yuan (Author) / Zhou, Zhi-Hua (Author) / Kumar, Sudhir (Author) / Ye, Jieping (Author) / Biodesign Institute (Contributor) / Center for Evolution and Medicine (Contributor) / Ira A. Fulton Schools of Engineering (Contributor) / College of Liberal Arts and Sciences (Contributor) / School of Life Sciences (Contributor)
Created2012-05-23
Description
In the development of personalized medicine and many other clinical studies, biospecimen integrity serves as the prerequisite for not only the accurate derivation of patient- and disease-specific molecular data from biological specimens but the meaningful downstream validation of biomarkers. However, a large number of preanalytical variables may influence the quality of biospecimens in an undesired way and ultimately render the samples unsuitable for molecular analysis. The limited ability to directly reduce discrepancies caused by preanalytical variables gives rise to the need for development and retrospective application of appropriate tests for assessment of biospecimen integrity. Nevertheless, the most standard approaches to assessing biospecimen integrity involve nontrivial procedures. Thus, the need for quality control tools or tests that are readily applicable and can produce results in a straightforward way becomes critical. As one of the major ex vivo biomolecular degradation mechanisms, oxidation that occurs when blood plasma and serum samples are exposed to thawed states during storage and processing is hard to forestall and detect. In an attempt to easily detect and monitor the degree of oxidation, the technique of Fluorescence Resonance Energy Transfer (FRET) was examined to determine whether this concept could be employed to monitor exposure of samples to thawed conditions when controlled by spontaneous oxidative disulfide bonding. The intended mode of usage was envisioned as a fluorescence liquid being stored in a separate compartment but within the same test tube as archived plasma and serum samples. This would allow the assessment of sample integrity by direct visualization of fluorescence under a hand-held black light. The fluorescent dynamic range as well as kinetic control of the reaction were studied. While the addition of Cu(II) proved to facilitate excellent dynamic range with regard to fluorescence quenching, the kinetics of the reaction were too rapid for practical use. Further investigation revealed that the fluorescence quenching mechanism might have actually occurred via Intramolecular Charge Transfer (ICT) rather than FRET mediated by oxidative disulfide bond formation. Introduction of Cu(II) via copper metal slowed fluorescence quenching to the point of practical utility; facilitating demonstration that storing at room temperature, refrigerating or freezing the samples delayed fluorescence quenching to different extents. To establish better kinetic control, future works will focus on establishing controlled, thoroughly understood kinetic release of Cu(II) from copper metal.
ContributorsZhang, Zihan (Author) / Borges, Chad (Thesis director) / Emady, Heather (Committee member) / Williams, Peter (Committee member) / Chemical Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2018-12
Description
Since its discovery in 1524, many people have characterized the vermiform appendix. Charles Darwin considered the human appendix to be a vestige and a useless structure. Others at the time opposed this hypothesis. However, Darwin's hypothesis became prevalent one until recently when there became a renewed interest in the appendix because of advancements in microscopes, knowledge of the immune system, and phylogenetics. In this review, I will argue that the vermiform appendix, although still not completely understood, has important functions. First, I will give the anatomy of the appendix. I will discuss the comparative anatomy between different animals and also primates. I will address the effects of appendicitis and appendectomy. I will give background on vestigial structures and will discuss if the appendix is a vestige. Following, I will review the evolution of the appendix. Finally, I will argue that the function of the appendix is as an immune organ, including discussion of gut-associated lymphoid tissue (GALT), development of lymphoid follicles in GALT and their comparison within different organs, Immunoglobulin A (IgA) function in the gut, biofilms as evidence that the appendix is a safe-house for beneficial bacteria, re-inoculation of the bowel, and protection against recurring infection. I will conclude with future studies that should be conducted to further our understanding of the vermiform appendix.
ContributorsPrestwich, Shelby Elizabeth (Author) / Cartwright, Reed (Thesis director) / Lynch, John (Committee member) / Furstenau, Tara (Committee member) / School of Geographical Sciences and Urban Planning (Contributor) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2018-05
Description
Biomarkers are the cornerstone of modern-day medicine. They are defined as any biological substance in or outside the body that gives insight to the body's condition. Doctors and researchers can measure specific biomarkers to diagnose and treat patients, such as the concentration of hemoglobin Alc and its connection to diabetes. There are a variety of methods, or assays, to detect biomarkers, but the most common assay is enzyme-linked immunosorbent assay (ELISA). A new-generation assay termed mass spectrometric immunoassay (MSIA) can measure proteoforms, the different chemical variations of proteins, and their relative abundance. ELISA on the other hand measures the overall concentration of protein in the sample. Measuring each of the proteoforms of a protein is important because only one or two variations could be biologically significant and/or cause diseases. However, running MSIA is expensive. For this reason, an alternative plate-based MSIA technique was tested for its ability to detect the proteoforms of a protein called apolipoprotein C-III (ApoC-III). This technique combines the protein capturing procedure of ELISA to isolate the protein with detection in a mass spectrometer. A larger amount of ApoC-III present in the body indicates a considerable risk for coronary heart disease. The precision of the assay is determined on the coefficient of variation (CV). A CV value is the ratio of standard deviation in relation to the mean, represented as a percentage. The smaller the percentage, the less variation the assay has, and therefore the more ability it has to detect subtle changes in the biomarker. An accepted CV would be less than 10% for single-day tests (intra-day) and less than 15% for multi-day tests (inter-day). The plate-based MSIA was started by first coating a 96-well round bottom plate with 2.5 micrograms of ApoC-III antibody. Next, a series of steps were conducted: a buffer wash, then the sample incubation, followed by another buffer wash and two consecutive water washes. After the final wash, the wells were filled with a MALDI matrix, then spotted onto a gold plate to dry. The dry gold target was then placed into a MALDI-TOF mass spectrometer to produce mass spectra for each spot. The mass spectra were calibrated and the area underneath each of the four peaks representing the ApoC-III proteoforms was exported as an Excel file. The intra-day CV values were found by dividing the standard deviation by the average relative abundance of each peak. After repeating the same procedure for three more days, the inter-day CVs were found using the same method. After completing the experiment, the CV values were all within the acceptable guidelines. Therefore, the plate-based MSIA is a viable alternative for finding proteoforms than the more expensive MSIA tips. To further validate this, additional tests will need to be conducted with different proteins and number of samples to determine assay flexibility.
ContributorsTieu, Luc (Author) / Borges, Chad (Thesis director) / Nedelkov, Dobrin (Committee member) / Harrington Bioengineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2017-12
Description
Brown adipose tissue (BAT) is thought to be important in combating obesity as it can expend energy in the form of heat, e.g. thermogenesis. The goal of this study was to study the effect of injected norepinephrine (NE) on the activation of BAT in rats that were fed a high fat diet (HFD). A dose of 0.25 mg/kg NE was used to elicit a temperature response that was measured using transponders inserted subcutaneously over the BAT and lower back and intraperitoneally to measure the core temperature. The results found that the thermic effect of the BAT increased after the transition from low fat diet to a high fat diet (LFD) yet, after prolonged exposure to the HFD, the effects resembled levels found with the LFD. This suggests that while a HFD may stimulate the effect of BAT, long term exposure may have adverse effects on BAT activity. This may be due to internal factors that will need to be examined further.
ContributorsSion, Paul William (Author) / Herman, Richard (Thesis director) / Borges, Chad (Committee member) / School of Molecular Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2017-05
Description
With the rising data output and falling costs of Next Generation Sequencing technologies, research into data compression is crucial to maintaining storage efficiency and costs. High throughput sequencers such as the HiSeqX Ten can produce up to 1.8 terabases of data per run, and such large storage demands are even more important to consider for institutions that rely on their own servers rather than large data centers (cloud storage)1. Compression algorithms aim to reduce the amount of space taken up by large genomic datasets by encoding the most frequently occurring symbols with the shortest bit codewords and by changing the order of the data to make it easier to encode. Depending on the probability distribution of the symbols in the dataset or the structure of the data, choosing the wrong algorithm could result in a compressed file larger than the original or a poorly compressed file that results in a waste of time and space2. To test efficiency among compression algorithms for each file type, 37 open-source compression algorithms were used to compress six types of genomic datasets (FASTA, VCF, BCF, GFF, GTF, and SAM) and evaluated on compression speed, decompression speed, compression ratio, and file size using the benchmark test lzbench. Compressors that outpreformed the popular bioinformatics compressor Gzip (zlib -6) were evaluated against one another by ratio and speed for each file type and across the geometric means of all file types. Compressors that exhibited fast compression and decompression speeds were also evaluated by transmission time through variable speed internet pipes in scenarios where the file was compressed only once or compressed multiple times.
ContributorsHowell, Abigail (Author) / Cartwright, Reed (Thesis director) / Wilson Sayres, Melissa (Committee member) / Taylor, Jay (Committee member) / Barrett, The Honors College (Contributor)
Created2017-05
Description
Almost every form of cancer deregulates the expression and activity of anabolic glycosyltransferase (GT) enzymes, which incorporate particular monosaccharides in a donor acceptor as well as linkage- and anomer-specific manner to assemble complex and diverse glycans that significantly affect numerous cellular events, including tumorigenesis and metastasis. Because glycosylation is not template-driven, GT deregulation yields heterogeneous arrays of aberrant intact glycan products, some in undetectable quantities in clinical bio-fluids (e.g., blood plasma). Numerous glycan features (e.g., 6 sialylation, β-1,6-branching, and core fucosylation) stem from approximately 25 glycan “nodes:” unique linkage specific monosaccharides at particular glycan branch points that collectively confer distinguishing features upon glycan products. For each node, changes in normalized abundance (Figure 1) may serve as nearly 1:1 surrogate measure of activity for culpable GTs and may correlate with particular stages of carcinogenesis. Complementary to traditional top down glycomics, the novel bottom-up technique applied herein condenses each glycan node and feature into a single analytical signal, quantified by two GC-MS instruments: GCT (time-of-flight analyzer) and GCMSD (transmission quadrupole analyzers). Bottom-up analysis of stage 3 and 4 breast cancer cases revealed better overall precision for GCMSD yet comparable clinical performance of both GC MS instruments and identified two downregulated glycan nodes as excellent breast cancer biomarker candidates: t-Gal and 4,6-GlcNAc (ROC AUC ≈ 0.80, p < 0.05). Resulting from the activity of multiple GTs, t-Gal had the highest ROC AUC (0.88) and lowest ROC p‑value (0.001) among all analyzed nodes. Representing core-fucosylation, glycan node 4,6-GlcNAc is a nearly 1:1 molecular surrogate for the activity of α-(1,6)-fucosyltransferase—a potential target for cancer therapy. To validate these results, future projects can analyze larger sample sets, find correlations between breast cancer stage and changes in t-Gal and 4,6-GlcNAc levels, gauge the specificity of these nodes for breast cancer and their potential role in other cancer types, and develop clinical tests for reliable breast cancer diagnosis and treatment monitoring based on t-Gal and 4,6-GlcNAc.
ContributorsZaare, Sahba (Author) / Borges, Chad (Thesis director) / LaBaer, Joshua (Committee member) / School of Molecular Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
Many bacteria actively import environmental DNA and incorporate it into their genomes. This behavior, referred to as transformation, has been described in many species from diverse taxonomic backgrounds. Transformation is expected to carry some selective advantages similar to those postulated for meiotic sex in eukaryotes. However, the accumulation of loss-of-function alleles at transformation loci and an increased mutational load from recombining with DNA from dead cells create additional costs to transformation. These costs have been shown to outweigh many of the benefits of recombination under a variety of likely parameters. We investigate an additional proposed benefit of sexual recombination, the Red Queen hypothesis, as it relates to bacterial transformation. Here we describe a computational model showing that host-pathogen coevolution may provide a large selective benefit to transformation and allow transforming cells to invade an environment dominated by otherwise equal non-transformers. Furthermore, we observe that host-pathogen dynamics cause the selection pressure on transformation to vary extensively in time, explaining the tight regulation and wide variety of rates observed in naturally competent bacteria. Host-pathogen dynamics may explain the evolution and maintenance of natural competence despite its associated costs.
ContributorsPalmer, Nathan David (Author) / Cartwright, Reed (Thesis director) / Wang, Xuan (Committee member) / Sievert, Chris (Committee member) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
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