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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
Sleep diaries and actigraphy are two common methods used to assess sleep subjectively and objectively, respectively. Compared to the gold standard of sleep assessment, polysomnography, sleep diaries and actigraphic methods are more cost-effective and simpler to use. This study aimed to compare the sleep parameters derived from actigraphy and sleep diaries (total sleep time, sleep onset latency, number of awakenings, wake after sleep onset, percentage of time awake, and sleep efficiency). Based on results from previous similar studies, it was hypothesized that the sleep diaries would overestimate the total sleep time parameter and underestimate wake parameters. Twenty healthy young adults without sleep problems volunteered to participate. The participants wore an Actiwatch 2 on their wrist and filled out a sleep diary every morning for the duration of six days. A high intraclass correlation coefficient value between subjective and objective sleep was found for the parameter total sleep time, even though total sleep time was found to be slightly overestimated by the sleep diaries. Sleep onset latency, wake after sleep onset, number of awakenings, percentage of time awake, and sleep efficiency were underestimated by the sleep diaries and did not have high correlation values. Based off of the ICC results, there does not seem to be a strong correlation between the Actiwatch 2 and the sleep diaries, but looking at the Bland Altman plots, there seems to be agreement between the methods.
ContributorsRameshkumar, Aarthi (Author) / Buman, Matthew (Thesis director) / Petrov, Megan (Committee member) / Diaz-Piedra, Carolina (Committee member) / School of Molecular Sciences (Contributor) / Barrett, The Honors College (Contributor) / School of Nutrition and Health Promotion (Contributor)
Created2016-12
Description
Recent research has confirmed and revealed many physical and mental benefits of yoga. The practice of yoga has spread throughout the western world, where it is widely used for the purpose of exercise and fitness. Due to its rise in popularity, there is a need for research regarding the energy expenditure required for different types of yoga. The majority of the literature cites yoga as being an effective exercise for light intensity activity, but there are not as many studies attempting to determine if there are postures and sequences that can meet the requirements for moderate physical activity. In addition, there is a need to validate mobile devices with which to measure energy expenditure (EE) that are compatible with the dynamic movements that occur during yoga. The purpose of this study was to measure energy expenditure of twenty-two yoga practitioners of varying experience during a 30-minute Vinyasa flow yoga practice and from this data collection determine: if an ashtanga-based vinyasa yoga class meets the criteria for moderate intensity physical activity, the reliability between the Actigraph and Oxycon Mobile and the validity of an Actigraph GT3X device worn on the hip in estimating energy expenditure for ashtanga-based vinyasa flow yoga. The Actigraph GT3X and the Oxycon mobile were used to measure energy expenditure. Mean values for energy expenditure recorded by the Oxycon and Actigraph were 3.19 ± 0.42 METs and 1.16 ± 0.23 METs respectively, exhibiting a significant difference in data collection. There was no correlation between the values recorded by the two devices, indicating that the Actigraph was not consistent with the Oxycon Mobile (previously validated for measurement of EE). Results of this study indicate that this Vinyasa flow yoga sequence does satisfy the criteria for moderate intensity physical activity as defined by ACSM with an average EE of 3.19 ± 0.42 METs, and that the Actigraph GT3X is not an accurate device for measurement of EE for yoga.
ContributorsHand, Lindsay Gabrielle (Author) / Huberty, Jennifer (Thesis director) / Buman, Matthew (Committee member) / School of Nutrition and Health Promotion (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
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
Aberrant glycosylation has been shown to be linked to specific cancers, and using this idea, it was proposed that the levels of glycans in the blood could predict stage I adenocarcinoma. To track this glycosylation, glycan were broken down into glycan nodes via methylation analysis. This analysis utilized information from N-, O-, and lipid linked glycans detected from gas chromatography-mass spectrometry. The resulting glycan node-ratios represent the initial quantitative data that were used in this experiment.
For this experiment, two Sets of 50 µl blood plasma samples were provided by NYU Medical School. These samples were then analyzed by Dr. Borges’s lab so that they contained normalized biomarker levels from patients with stage 1 adenocarcinoma and control patients with matched age, smoking status, and gender were examined. An ROC curve was constructed under individual and paired conditions and AUC calculated in Wolfram Mathematica 10.2. Methods such as increasing size of training set, using hard vs. soft margins, and processing biomarkers together and individually were used in order to increase the AUC. Using a soft margin for this particular data set was proved to be most useful compared to the initial set hard margin, raising the AUC from 0.6013 to 0.6585. In regards to which biomarkers yielded the better value, 6-Glc/6-Man and 3,6-Gal glycan node ratios had the best with 0.7687 AUC and a sensitivity of .7684 and specificity of .6051. While this is not enough accuracy to become a primary diagnostic tool for diagnosing stage I adenocarcinoma, the methods examined in the paper should be evaluated further. . By comparison, the current clinical standard blood test for prostate cancer that has an AUC of only 0.67.
For this experiment, two Sets of 50 µl blood plasma samples were provided by NYU Medical School. These samples were then analyzed by Dr. Borges’s lab so that they contained normalized biomarker levels from patients with stage 1 adenocarcinoma and control patients with matched age, smoking status, and gender were examined. An ROC curve was constructed under individual and paired conditions and AUC calculated in Wolfram Mathematica 10.2. Methods such as increasing size of training set, using hard vs. soft margins, and processing biomarkers together and individually were used in order to increase the AUC. Using a soft margin for this particular data set was proved to be most useful compared to the initial set hard margin, raising the AUC from 0.6013 to 0.6585. In regards to which biomarkers yielded the better value, 6-Glc/6-Man and 3,6-Gal glycan node ratios had the best with 0.7687 AUC and a sensitivity of .7684 and specificity of .6051. While this is not enough accuracy to become a primary diagnostic tool for diagnosing stage I adenocarcinoma, the methods examined in the paper should be evaluated further. . By comparison, the current clinical standard blood test for prostate cancer that has an AUC of only 0.67.
ContributorsDe Jesus, Celine Spicer (Author) / Taylor, Thomas (Thesis director) / Borges, Chad (Committee member) / School of Mathematical and Statistical Sciences (Contributor) / School of Molecular Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
Disturbances in the protein interactome often play a large role in cancer progression. Investigation of protein-protein interactions (PPI) can increase our understanding of cancer pathways and will disclose unknown targets involved in cancer disease biology. Although numerous methods are available to study protein interactions, most platforms suffer from drawbacks including high false positive rates, low throughput, and lack of quantification. Moreover, most methods are not compatible for use in a clinical setting. To address these limitations, we have developed a multiplexed, in-solution protein microarray (MISPA) platform with broad applications in proteomics. MISPA can be used to quantitatively profile PPIs and as a robust technology for early detection of cancers. This method utilizes unique DNA barcoding of individual proteins coupled with next generation sequencing to quantitatively assess interactions via barcode enrichment. We have tested the feasibility of this technology in the detection of patient immune responses to oropharyngeal carcinomas and in the discovery of novel PPIs in the B-cell receptor (BCR) pathway. To achieve this goal, 96 human papillomavirus (HPV) antigen genes were cloned into pJFT7-cHalo (99% success) and pJFT7-n3xFlag-Halo (100% success) expression vectors. These libraries were expressed via a cell-free in vitro transcription-translation system with 93% and 96% success, respectively. A small-scale study of patient serum interactions with barcoded HPV16 antigens was performed and a HPV proteome-wide study will follow using additional patient samples. In addition, 15 query proteins were cloned into pJFT7_nGST expression vectors, expressed, and purified with 93% success to probe a library of 100 BCR pathway proteins and detect novel PPIs.
ContributorsRinaldi, Capria Lakshmi (Author) / LaBaer, Joshua (Thesis director) / Mangone, Marco (Committee member) / Borges, Chad (Committee member) / School of Molecular Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
Description
Microfluidic platforms have been exploited extensively as a tool for the separation of particles by electric field manipulation. Microfluidic devices can facilitate the manipulation of particles by dielectrophoresis. Separation of particles by size and type has been demonstrated by insulator-based dielectrophoresis in a microfluidic device. Thus, manipulating particles by size has been widely studied throughout the years. It has been shown that size-heterogeneity in organelles has been linked to multiple diseases from abnormal organelle size. Here, a mixture of two sizes of polystyrene beads (0.28 and 0.87 μm) was separated by a ratchet migration mechanism under a continuous flow (20 nL/min). Furthermore, to achieve high-throughput separation, different ratchet devices were designed to achieve high-volume separation. Recently, enormous efforts have been made to manipulate small size DNA and proteins. Here, a microfluidic device comprising of multiple valves acting as insulating constrictions when a potential is applied is presented. The tunability of the electric field gradient is evaluated by a COMSOL model, indicating that high electric field gradients can be reached by deflecting the valve at a certain distance. Experimentally, the tunability of the dynamic constriction was demonstrated by conducting a pressure study to estimate the gap distance between the valve and the substrate at different applied pressures. Finally, as a proof of principle, 0.87 μm polystyrene beads were manipulated by dielectrophoresis. These microfluidic platforms will aid in the understanding of size-heterogeneity of organelles for biomolecular assessment and achieve separation of nanometer-size DNA and proteins by dielectrophoresis.
ContributorsOrtiz, Ricardo (Author) / Ros, Alexandra (Thesis advisor) / Hayes, Mark (Committee member) / Borges, Chad (Committee member) / Arizona State University (Publisher)
Created2021
Description
Meditation app usage is associated with decreases in stress, anxiety, and depression symptoms. Many meditation app subscribers, however, quickly abandon or reduce their app usage. This dissertation presents three manuscripts which 1) determined the behavioral, demographic, and socioeconomic factors associated with the abandonment of a meditation app, Calm, during the COVID-19 pandemic, 2) determined which participant characteristics predicted meditation app usage in the first eight weeks after subscribing, and 3) determined if changes in stress, anxiety, and depressive symptoms from baseline to Week 8 predicted meditation app usage from Weeks 8-16. In Manuscript 1, a survey was distributed to Calm subscribers in March 2020 that assessed meditation app behavior and meditation habit strength, and demographic information. Cox proportional hazards regression models were estimated to assess time to app abandonment. In Manuscript 2, new Calm subscribers completed a baseline survey on participants’ demographic and baseline mental health information and app usage data were collected over 8 weeks. In Manuscript 3, new Calm subscribers completed a baseline and Week 8 survey on demographic and mental health information. App usage data were collected over 16 weeks. Regression models were used to assess app usage for Manuscripts 2 and 3. Findings from Manuscript 1 suggest meditating after an existing routine decreased risk of app abandonment for pre-pandemic subscribers and for pandemic subscribers. Additionally, meditating “whenever I can” decreased risk of abandonment among pandemic subscribers. No behavioral factors were significant predictors of app abandonment among the long-term subscribers. Findings from Manuscript 2 suggest men had more days of meditation than women. Mental health diagnosis increased average daily meditation minutes. Intrinsic motivation for meditation increased the likelihood of completing any meditation session, more days with meditation sessions, and more average daily meditation minutes. Findings from Manuscript 3 suggest improvements in stress increased average daily meditation minutes. Improvements in depressive symptoms decreased daily meditation minutes. Evidence from this three-manuscript dissertation suggests meditation cue, time of day, motivation, symptom changes, and demographic and socioeconomic variables may be used to predict meditation app usage.
ContributorsSullivan, Mariah (Author) / Stecher, Chad (Thesis advisor) / Huberty, Jennifer (Committee member) / Buman, Matthew (Committee member) / Larkey, Linda (Committee member) / Chung, Yunro (Committee member) / Arizona State University (Publisher)
Created2022
Description
Traditional Reinforcement Learning (RL) assumes to learn policies with respect to reward available from the environment but sometimes learning in a complex domain requires wisdom which comes from a wide range of experience. In behavior based robotics, it is observed that a complex behavior can be described by a combination of simpler behaviors. It is tempting to apply similar idea such that simpler behaviors can be combined in a meaningful way to tailor the complex combination. Such an approach would enable faster learning and modular design of behaviors. Complex behaviors can be combined with other behaviors to create even more advanced behaviors resulting in a rich set of possibilities. Similar to RL, combined behavior can keep evolving by interacting with the environment. The requirement of this method is to specify a reasonable set of simple behaviors. In this research, I present an algorithm that aims at combining behavior such that the resulting behavior has characteristics of each individual behavior. This approach has been inspired by behavior based robotics, such as the subsumption architecture and motor schema-based design. The combination algorithm outputs n weights to combine behaviors linearly. The weights are state dependent and change dynamically at every step in an episode. This idea is tested on discrete and continuous environments like OpenAI’s “Lunar Lander” and “Biped Walker”. Results are compared with related domains like Multi-objective RL, Hierarchical RL, Transfer learning, and basic RL. It is observed that the combination of behaviors is a novel way of learning which helps the agent achieve required characteristics. A combination is learned for a given state and so the agent is able to learn faster in an efficient manner compared to other similar approaches. Agent beautifully demonstrates characteristics of multiple behaviors which helps the agent to learn and adapt to the environment. Future directions are also suggested as possible extensions to this research.
ContributorsVora, Kevin Jatin (Author) / Zhang, Yu (Thesis advisor) / Yang, Yezhou (Committee member) / Praharaj, Sarbeswar (Committee member) / Arizona State University (Publisher)
Created2021
Description
In cold chain tracking systems, accuracy and flexibility across different temperatures ranges plays an integral role in monitoring biospecimen integrity. However, while two common cold chain tracking systems are currently available (electronic and physics/chemical), there is not an affordable cold chain tracking mechanism that can be applied to a variety of temperatures while maintaining accuracy for individual vials. Hence, our lab implemented our understanding of biochemical reaction kinetics to develop a new cold chain tracking mechanism using the permanganate/oxalic acid reaction. The permanganate/oxalic acid reaction is characterized by the reduction of permanganate (MnVII) to Mn(II) with Mn(II)-autocatalyzed oxidation of oxalate to CO2, resulting in a pink to colorless visual indicator change when the reaction system is not in the solid state (i.e., frozen or vitrified). Throughout our research, we demonstrate, (i) Improved reaction consistency and accuracy along with extended run times with the implementation of a nitric acid-based labware washing protocol, (ii) Simulated reaction kinetics for the maximum length reaction and 60-minute reaction based on previously developed MATLAB scripts (iii) Experimental reaction kinetics to verify the simulated MATLAB maximum and 60-minute reactions times (iv) Long-term stability of the permanganate/oxalic acid reaction with water or eutectic solutions of sodium perchlorate and magnesium perchlorate at -80°C (v) Reaction kinetics with eutectic solvents, sodium perchlorate and magnesium perchlorate, at 25°C, 4°C, and -8°C (vi) Accelerated reaction kinetics after the addition of varying concentrations of manganese perchlorate (vii) Reaction kinetics of higher concentration reaction systems (5x and 10x; for darker colors), at 25°C (viii) Long-term stability of the 10x higher concentration reaction at -80°C.
ContributorsLjungberg, Emil (Author) / Borges, Chad (Thesis director) / Levitus, Marcia (Committee member) / Williams, Peter (Committee member) / Barrett, The Honors College (Contributor) / School of Molecular Sciences (Contributor) / Department of Psychology (Contributor)
Created2022-12