Matching Items (100)
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Animals must learn to ignore stimuli that are irrelevant to survival, a process referred to as latent inhibition. The Amtyr1 gene has been shown through quantitative trait loci mapping to be linked to strong latent inhibition in honey bees. Here we implicate this G-protein coupled receptor for the biogenic amine

Animals must learn to ignore stimuli that are irrelevant to survival, a process referred to as latent inhibition. The Amtyr1 gene has been shown through quantitative trait loci mapping to be linked to strong latent inhibition in honey bees. Here we implicate this G-protein coupled receptor for the biogenic amine tyramine as an important factor underlying this form of learning in honey bees. We show that dsRNA targeted to disrupt the tyramine receptors, specifically affects latent inhibition but not excitatory associative conditioning. Our results therefore identify a distinct reinforcement pathway for latent inhibition in insects.
ContributorsPetersen, Mary Margaret (Author) / Smith, Brian (Thesis director) / Wang, Ying (Committee member) / Sinakevitch, Irina (Committee member) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2016-12
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The free-base tetra-tolyl-porphyrin and the corresponding cobalt and iron porphyrin complexes were synthesized and characterized to show that this class of compound can be promising, tunable catalysts for carbon dioxide reduction. During cyclic voltammetry experiments, the iron porphyrin showed an on-set of ‘catalytic current’ at an earlier potential than the

The free-base tetra-tolyl-porphyrin and the corresponding cobalt and iron porphyrin complexes were synthesized and characterized to show that this class of compound can be promising, tunable catalysts for carbon dioxide reduction. During cyclic voltammetry experiments, the iron porphyrin showed an on-set of ‘catalytic current’ at an earlier potential than the cobalt porphyrin’s in organic solutions gassed with carbon dioxide. The cobalt porphyrin yielded larger catalytic currents, but at the same potential as the electrode. This difference, along with the significant changes in the porphyrin’s electronic, optical and redox properties, showed that its capabilities for carbon dioxide reduction can be controlled by metal ions, allotting it unique opportunities for applications in solar fuels catalysis and photochemical reactions.
ContributorsSkibo, Edward Kim (Author) / Moore, Gary (Thesis director) / Woodbury, Neal (Committee member) / School of Molecular Sciences (Contributor) / School of Sustainability (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
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In Apis mellifera, gustatory responsiveness to sucrose is a good indicator of learning ability \u2014 in that individuals with high sucrose responsiveness will typically form faster, longer-lasting associations with conditioned stimulus than individuals with a low sucrose responsiveness. The purpose of this study was to determine whether experience with olfactory

In Apis mellifera, gustatory responsiveness to sucrose is a good indicator of learning ability \u2014 in that individuals with high sucrose responsiveness will typically form faster, longer-lasting associations with conditioned stimulus than individuals with a low sucrose responsiveness. The purpose of this study was to determine whether experience with olfactory conditioning had lasting effects on gustatory responsiveness. Groups were placed in an environment that would facilitate association of an odor to a sucrose reward, tested for retention, then tested for gustatory responsiveness. Control groups underwent the same testing schedule, but were not exposed to odor in the first environment. There was no significant difference in gustatory responsiveness between the two groups. Mann-Whitney tests were used to analyze the results, and though the mean GRS score was lower among the treatment group there was no significant trend, possibly due to small sample sizes.
ContributorsSeemann, J. H. (Author) / Amdam, Gro (Thesis director) / Smith, Brian (Committee member) / Barrett, The Honors College (Contributor)
Created2016-05
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ABSTRACT Peptide microarrays may prove to be a powerful tool for proteomics research and clinical diagnosis applications. Fodor et al. and Maurer et al. have shown proof-of-concept methods of light- and electrochemically-directed peptide microarray fabrication on glass and semiconductor microchips respectively. In this work, peptide microarray fabrication based on the

ABSTRACT Peptide microarrays may prove to be a powerful tool for proteomics research and clinical diagnosis applications. Fodor et al. and Maurer et al. have shown proof-of-concept methods of light- and electrochemically-directed peptide microarray fabrication on glass and semiconductor microchips respectively. In this work, peptide microarray fabrication based on the abovementioned techniques were optimized. In addition, MALDI mass spectrometry based peptide synthesis characterization on semiconductor microchips was developed and novel applications of a CombiMatrix (CBMX) platform for electrochemically controlled synthesis were explored. We have investigated performance of 2-(2-nitrophenyl)propoxycarbonyl (NPPOC) derivatives as photo-labile protecting group. Specifically, influence of substituents on 4 and 5 positions of phenyl ring of NPPOC group on the rate of photolysis and the yield of the amine was investigated. The results indicated that substituents capable of forming a π-network with the nitro group enhanced the rate of photolysis and yield. Once such properly substituted NPPOC groups were used, the rate of photolysis/yield depended on the nature of protected amino group indicating that a different chemical step during the photo-cleavage process became the rate limiting step. We also focused on electrochemically-directed parallel synthesis of high-density peptide microarrays using the CBMX technology referred to above which uses electrochemically generated acids to perform patterned chemistry. Several issues related to peptide synthesis on the CBMX platform were studied and optimized, with emphasis placed on the reactions of electro-generated acids during the deprotection step of peptide synthesis. We have developed a MALDI mass spectrometry based method to determine the chemical composition of microarray synthesis, directly on the feature. This method utilizes non-diffusional chemical cleavage from the surface, thereby making the chemical characterization of high-density microarray features simple, accurate, and amenable to high-throughput. CBMX Corp. has developed a microarray reader which is based on electro-chemical detection of redox chemical species. Several parameters of the instrument were studied and optimized and novel redox applications of peptide microarrays on CBMX platform were also investigated using the instrument. These include (i) a search of metal binding catalytic peptides to reduce overpotential associated with water oxidation reaction and (ii) an immobilization of peptide microarrays using electro-polymerized polypyrrole.
ContributorsKumar, Pallav (Author) / Woodbury, Neal (Thesis advisor) / Allen, James (Committee member) / Johnston, Stephen (Committee member) / Arizona State University (Publisher)
Created2013
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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

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
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Description
Computational models have long been used to describe and predict the outcome of complex immunological processes. The dissertation work described here centers on the construction of multiscale computational immunology models that derives biological insights at the population, systems, and atomistic levels. First, SARS-CoV-2 mortality is investigated through the lens of

Computational models have long been used to describe and predict the outcome of complex immunological processes. The dissertation work described here centers on the construction of multiscale computational immunology models that derives biological insights at the population, systems, and atomistic levels. First, SARS-CoV-2 mortality is investigated through the lens of the predicted robustness of CD8+ T cell responses in 23 different populations. The robustness of CD8+ T cell responses in a given population was modeled by predicting the efficiency of endemic MHC-I protein variants to present peptides derived from SARS-CoV-2 proteins to circulating T cells. To accomplish this task, an algorithm, called EnsembleMHC, was developed to predict viral peptides with a high probability of being recognized by CD T cells. It was discovered that there was significant variation in the efficiency of different MHC-I protein variants to present SARS-CoV-2 derived peptides, and countries enriched with variants with high presentation efficiency had significantly lower mortality rates. Second, a biophysics-based MHC-I peptide prediction algorithm was developed. The MHC-I protein is the most polymorphic protein in the human genome with polymorphisms in the peptide binding causing striking changes in the amino acid compositions, or binding motifs, of peptide species capable of stable binding. A deep learning model, coined HLA-Inception, was trained to predict peptide binding using only biophysical properties, namely electrostatic potential. HLA-Inception was shown to be extremely accurate and efficient at predicting peptide binding motifs and was used to determine the peptide binding motifs of 5,821 MHC-I protein variants. Finally, the impact of stalk glycosylations on NL63 protein dynamics was investigated. Previous data has shown that coronavirus crown glycans play an important role in immune evasion and receptor binding, however, little is known about the role of the stalk glycans. Through the integration of computational biology, experimental data, and physics-based simulations, the stalk glycans were shown to heavily influence the bending angle of spike protein, with a particular emphasis on the glycan at position 1242. Further investigation revealed that removal of the N1242 glycan significantly reduced infectivity, highlighting a new potential therapeutic target. Overall, these investigations and associated innovations in integrative modeling.
ContributorsWilson, Eric Andrew (Author) / Anderson, Karen (Thesis advisor) / Singharoy, Abhishek (Thesis advisor) / Woodbury, Neal (Committee member) / Sulc, Petr (Committee member) / Arizona State University (Publisher)
Created2022
Description

Understanding learning in fruit flies (D. melanogaster) can lead to many important discoveries about learning in humans due to the large overlap of shared DNA and the appearance of the same diseases in both species. Fruit flies have already been test subjects for many influential research experiments, some of which

Understanding learning in fruit flies (D. melanogaster) can lead to many important discoveries about learning in humans due to the large overlap of shared DNA and the appearance of the same diseases in both species. Fruit flies have already been test subjects for many influential research experiments, some of which earned Nobel Prizes. This study seeks to investigate inhibitory conditioning in a way that differs from the traditional forward pairing inhibitory conditioning. Specifically, this experiment aims to establish inhibitory learning in fruit flies using backward association. The results show that when fruit flies are trained using backward conditioning as opposed to forward conditioning, there is a pattern of preference that differs substantially from the results showing an aversion to the associated odor in forward conditioning. When comparing the data using Two-Factor ANOVA of forward versus backward conditioning, it clearly indicates that the results are significant. Simply by altering the temporal placement of an unconditioned stimulus and a conditioned stimulus, the fruit flies learn significantly differently, switching from an aversion to the paired odor to a preference. Based on these results, fruit flies can be considered capable of inhibitory learning via backward pairing. Further research will consider whether responses become stronger after more repetitions of the training, and summation and retardation tests can be done in order to confirm that the response is, in fact, due to inhibitory conditioning and not just habituation.

ContributorsLawrence, Heidi (Author) / Smith, Brian (Thesis director) / de Belle, John (Committee member) / Barrett, The Honors College (Contributor) / School of Molecular Sciences (Contributor)
Created2023-05
Description

In the face of widespread pollinator decline, research has increasingly focused on ways that pesticides could be harming bees. Fungicides are pesticides that are used in greater volumes than insecticides, yet significantly fewer studies have investigated the effects of these agrochemicals. The fungicide Pristine® is commonly used on bee-pollinated crops

In the face of widespread pollinator decline, research has increasingly focused on ways that pesticides could be harming bees. Fungicides are pesticides that are used in greater volumes than insecticides, yet significantly fewer studies have investigated the effects of these agrochemicals. The fungicide Pristine® is commonly used on bee-pollinated crops and has been shown to be detrimental to physiological processes that are key to honey bee foraging, such as digestion and learning. This study seeks to investigate how Pristine® exposure affects the amount of water, nectar, and pollen that honey bees collect. Colonies were fed either plain pollen patties or pollen patties containing 23 ppm Pristine®. Exposure to fungicide had no significant effect on corbicular pollen mass, the crop volumes of nectar or water foragers, or the proportions of foragers collecting different substances. There was a significantly higher sugar concentration in the crop of Pristine®-exposed nectar foragers (43.6%, 95% CI [38.8, 48.4]) compared to control nectar foragers (36.3%, 95% CI [31.9, 40.6]). The higher sugar concentration in the nectar of Pristine®-treated bees could indicate that the agrochemical decreases sucrose responsiveness or nutritional status in bees. Alternatively, fungicide exposure may increase the amount of sugar that bees need to make it back to the hive. Based on these results, it would appear that fungicides like Pristine® do not strongly affect the amounts of substances that honey bees collect, but it is still highly plausible that treated bees forage more slowly or with lower return rates.

ContributorsChester, Elise (Author) / Harrison, Jon (Thesis director) / DesJardins, Nicole (Committee member) / Smith, Brian (Committee member) / Barrett, The Honors College (Contributor) / School of Life Sciences (Contributor)
Created2023-05
Description

One of the identified health risk areas for human spaceflight is infectious disease, particularly involving environmental microorganisms already found on the International Space Station (ISS). In particular, bacteria belonging to the Burkholderia cepacia complex (Bcc) which can cause human disease in those who are immunocompromised, have been identified in the

One of the identified health risk areas for human spaceflight is infectious disease, particularly involving environmental microorganisms already found on the International Space Station (ISS). In particular, bacteria belonging to the Burkholderia cepacia complex (Bcc) which can cause human disease in those who are immunocompromised, have been identified in the ISS water supply. This present study characterized the effect of spaceflight analog culture conditions on Bcc to certain physiological stresses (acid and thermal as well as intracellular survival in U927 human macrophage cells). The NASA-designed Rotating Wall Vessel (RWV) bioreactor was used as the spaceflight analogue culture system in these studies to grow Bcc bacterial cells under Low Shear Modeled Microgravity (LSMMG) conditions. Results show that LSMMG culture increased the resistance of Bcc to both acid and thermal stressors, but did not alter phagocytic uptake in 2-D monolayers of human monocytes.

ContributorsVu, Christian-Alexander (Author) / Nickerson, Cheryl (Thesis director) / Barrila, Jennifer (Committee member) / Ott, Mark (Committee member) / Barrett, The Honors College (Contributor) / Harrington Bioengineering Program (Contributor)
Created2023-05
Description
Active sensing is a sensory phenomenon in which organisms use self-generated energy to examine their surroundings. This experiment strives to better understand active sensing in honeybees, predicting that active sensing may display itself primarily through antennae movement and that preventing antennae movement may result in differences in electroantennogram dose-response curves

Active sensing is a sensory phenomenon in which organisms use self-generated energy to examine their surroundings. This experiment strives to better understand active sensing in honeybees, predicting that active sensing may display itself primarily through antennae movement and that preventing antennae movement may result in differences in electroantennogram dose-response curves and associative learning plasticity. This will be done by examining changes in amplitude in electroantennogram response in both fixed-antenna and free-antenna bees over the course of a differential training protocol that establishes learned behavior discrimination.
ContributorsLei, Harry (Author) / Smith, Brian (Thesis director) / Albin-Brooks, Christopher (Committee member) / Barrett, The Honors College (Contributor)
Created2023-05