Matching Items (140)
Description
Microorganisms can produce metabolites in the gut including short chain fatty acids, vitamins, and amino acids. Certain metabolites produced in the gut can affect the brain through changes in neurotransmitter concentrations. Serotonin, a neurotransmitter, is associated with mood, appetite, and sleep. Up to 90% of serotonin synthesis is located in the gut, by human enterochromaffin cells. Bacteria known to biosynthesize tryptophan, precursor to serotonin, include Escherichia coli, Enterococcus and Streptococcus. Tryptophan is synthesized by bacteria with the enzyme tryptophan synthase and requires Vitamin B6 (Pyridoxal). We hypothesize that gut isolates from surgical weight loss patients can enhance tryptophan production, which relies on vitamin B6 availability. Our goal was to isolate bacteria in order to test for tryptophan production and to determine how Vitamin B6 concentrations could affect tryptophan production. We isolated gut bacteria was from successful surgical weight loss patient with selective pressures for Enterobacter isolates and Enterococcus isolates. We tested the isolates were tested to determine if they could biosynthesize tryptophan in-vitro. Bacterial cultures were enriched with yeast and enriched with serine and indole, substrates necessary for tryptophan biosynthesis. We analyzed the supernatant samples for tryptophan production using GC-FID. Bacterial isolates most closely related to E. coli and Klebsiella based on 16S rRNA gene sequences, produced tryptophan in vitro. While under serine & indole media conditions, R1, the isolate most similar to Klebsiella produced more tryptophan than R14, the isolate most similar to E. coli. We tested the R1 isolate with a gradient of vitamin B6 concentrations from 0.02 µg/mL to 0.2 µg/mL to determine its effect on tryptophan production. When less than 0.05 µg/mL of Vitamin B6 was added, tryptophan production at 6 hours was higher than tryptophan production with Vitamin B6 concentrations at 0.05 µg/mL and above. The production and consumption of tryptophan by Klebsiella under 0 µg/mL and 0.02 µg/mL concentrations of Vitamin B6 occurred at a faster rate when compared to concentrations 0.05 µg/mL or higher of Vitamin B6.
ContributorsYee, Emily L. (Author) / Krajmalnik-Brown, Rosa (Thesis director) / Ilhan, Zehra (Committee member) / W. P. Carey School of Business (Contributor) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2016-05
Description
Video object segmentation (VOS) is an important task in computer vision with a lot of applications, e.g., video editing, object tracking, and object based encoding. Different from image object segmentation, video object segmentation must consider both spatial and temporal coherence for the object. Despite extensive previous work, the problem is still challenging. Usually, foreground object in the video draws more attention from humans, i.e. it is salient. In this thesis we tackle the problem from the aspect of saliency, where saliency means a certain subset of visual information selected by a visual system (human or machine). We present a novel unsupervised method for video object segmentation that considers both low level vision cues and high level motion cues. In our model, video object segmentation can be formulated as a unified energy minimization problem and solved in polynomial time by employing the min-cut algorithm. Specifically, our energy function comprises the unary term and pair-wise interaction energy term respectively, where unary term measures region saliency and interaction term smooths the mutual effects between object saliency and motion saliency. Object saliency is computed in spatial domain from each discrete frame using multi-scale context features, e.g., color histogram, gradient, and graph based manifold ranking. Meanwhile, motion saliency is calculated in temporal domain by extracting phase information of the video. In the experimental section of this thesis, our proposed method has been evaluated on several benchmark datasets. In MSRA 1000 dataset the result demonstrates that our spatial object saliency detection is superior to the state-of-art methods. Moreover, our temporal motion saliency detector can achieve better performance than existing motion detection approaches in UCF sports action analysis dataset and Weizmann dataset respectively. Finally, we show the attractive empirical result and quantitative evaluation of our approach on two benchmark video object segmentation datasets.
ContributorsWang, Yilin (Author) / Li, Baoxin (Thesis advisor) / Wang, Yalin (Committee member) / Cleveau, David (Committee member) / Arizona State University (Publisher)
Created2013
Description
Learning from high dimensional biomedical data attracts lots of attention recently. High dimensional biomedical data often suffer from the curse of dimensionality and have imbalanced class distributions. Both of these features of biomedical data, high dimensionality and imbalanced class distributions, are challenging for traditional machine learning methods and may affect the model performance. In this thesis, I focus on developing learning methods for the high-dimensional imbalanced biomedical data. In the first part, a sparse canonical correlation analysis (CCA) method is presented. The penalty terms is used to control the sparsity of the projection matrices of CCA. The sparse CCA method is then applied to find patterns among biomedical data sets and labels, or to find patterns among different data sources. In the second part, I discuss several learning problems for imbalanced biomedical data. Note that traditional learning systems are often biased when the biomedical data are imbalanced. Therefore, traditional evaluations such as accuracy may be inappropriate for such cases. I then discuss several alternative evaluation criteria to evaluate the learning performance. For imbalanced binary classification problems, I use the undersampling based classifiers ensemble (UEM) strategy to obtain accurate models for both classes of samples. A small sphere and large margin (SSLM) approach is also presented to detect rare abnormal samples from a large number of subjects. In addition, I apply multiple feature selection and clustering methods to deal with high-dimensional data and data with highly correlated features. Experiments on high-dimensional imbalanced biomedical data are presented which illustrate the effectiveness and efficiency of my methods.
ContributorsYang, Tao (Author) / Ye, Jieping (Thesis advisor) / Wang, Yalin (Committee member) / Davulcu, Hasan (Committee member) / Arizona State University (Publisher)
Created2013
Description
This dissertation constructs a new computational processing framework to robustly and precisely quantify retinotopic maps based on their angle distortion properties. More generally, this framework solves the problem of how to robustly and precisely quantify (angle) distortions of noisy or incomplete (boundary enclosed) 2-dimensional surface to surface mappings. This framework builds upon the Beltrami Coefficient (BC) description of quasiconformal mappings that directly quantifies local mapping (circles to ellipses) distortions between diffeomorphisms of boundary enclosed plane domains homeomorphic to the unit disk. A new map called the Beltrami Coefficient Map (BCM) was constructed to describe distortions in retinotopic maps. The BCM can be used to fully reconstruct the original target surface (retinal visual field) of retinotopic maps. This dissertation also compared retinotopic maps in the visual processing cascade, which is a series of connected retinotopic maps responsible for visual data processing of physical images captured by the eyes. By comparing the BCM results from a large Human Connectome project (HCP) retinotopic dataset (N=181), a new computational quasiconformal mapping description of the transformed retinal image as it passes through the cascade is proposed, which is not present in any current literature. The description applied on HCP data provided direct visible and quantifiable geometric properties of the cascade in a way that has not been observed before. Because retinotopic maps are generated from in vivo noisy functional magnetic resonance imaging (fMRI), quantifying them comes with a certain degree of uncertainty. To quantify the uncertainties in the quantification results, it is necessary to generate statistical models of retinotopic maps from their BCMs and raw fMRI signals. Considering that estimating retinotopic maps from real noisy fMRI time series data using the population receptive field (pRF) model is a time consuming process, a convolutional neural network (CNN) was constructed and trained to predict pRF model parameters from real noisy fMRI data
ContributorsTa, Duyan Nguyen (Author) / Wang, Yalin (Thesis advisor) / Lu, Zhong-Lin (Committee member) / Hansford, Dianne (Committee member) / Liu, Huan (Committee member) / Li, Baoxin (Committee member) / Arizona State University (Publisher)
Created2022
Description
Under current climate conditions northern peatlands mostly act as C sinks; however, changes in climate and environmental conditions, can change the soil carbon decomposition cascade, thus altering the sink status. Here I studied one of the most abundant northern peatland types, poor fen, situated along a climate gradient from tundra (Daring Lake, Canada) to boreal forest (Lutose, Canada) to temperate broadleaf and mixed forest (Bog Lake, MN and Chicago Bog, NY) biomes to assess patterns of microbial abundance across the climate gradient. Principal component regression analysis of the microbial community and environmental variables determined that mean annual temperature (MAT) (r2=0.85), mean annual precipitation (MAP) (r2=0.88), and soil temperature (r2=0.77), were the top significant drivers of microbial community composition (p < 0.001). Niche breadth analysis revealed the relative abundance of Intrasporangiaceae, Methanobacteriaceae and Candidatus Methanoflorentaceae fam. nov. to increase when MAT and MAP decrease. The same analysis showed Spirochaetaceae, Methanosaetaceae and Methanoregulaceae to increase in relative abundance when MAP, soil temperature and MAT increased, respectively. These findings indicated that climate variables were the strongest predictors of microbial community composition and that certain taxa, especially methanogenic families demonstrate distinct patterns across the climate gradient. To evaluate microbial production of methanogenic substrates, I carried out High Resolution-DNA-Stable Isotope Probing (HR-DNA-SIP) to evaluate the active portion of the community’s intermediary ecosystem metabolic processes. HR-DNA-SIP revealed several challenges in efficiency of labelling and statistical identification of responders, however families like Veillonellaceae, Magnetospirillaceae, Acidobacteriaceae 1, were found ubiquitously active in glucose amended incubations. Differences in metabolic byproducts from glucose amendments show distinct patterns in acetate and propionate accumulation across sites. Families like Spirochaetaceae and Sphingomonadaceae were only found to be active in select sites of propionate amended incubations. By-product analysis from propionate incubations indicate that the northernmost sites were acetate-accumulating communities.
These results indicate that microbial communities found in poor fen northern peatlands are strongly influenced by climate variables predicted to change under current climate scenarios. I have identified patterns of relative abundance and activity of select microbial taxa, indicating the potential for climate variables to influence the metabolic pathway in which carbon moves through peatland systems.
ContributorsSarno, Analissa Flores (Author) / Cadillo-Quiroz, Hinsby (Thesis advisor) / Garcia-Pichel, Ferran (Committee member) / Krajmalnik-Brown, Rosa (Committee member) / Childers, Daniel (Committee member) / Arizona State University (Publisher)
Created2022
Description
Widespread use of halogenated organic compounds for commercial and industrial purposes makes halogenated organic pollutants (HOPs) a global challenge for environmental quality. Current wastewater treatment plants (WWTPs) are successful at reducing chemical oxygen demand (COD), but the removal of HOPs often is poor. Since HOPs are xenobiotics, the biodegradation of HOPs is usually limited in the WWTPs. The current methods for HOPs treatments (e.g., chemical, photochemical, electrochemical, and biological methods) do have their limitations for practical applications. Therefore, a combination of catalytic and biological treatment methods may overcome the challenges of HOPs removal.This dissertation investigated a novel catalytic and biological synergistic platform to treat HOPs. 4-chlorophenol (4-CP) and halogenated herbicides were used as model pollutants for the HOPs removal tests. The biological part of experiments documented successful co-oxidation of HOPs and analog non-halogenated organic pollutants (OPs) (as the primary substrates) in the continuous operation of O2-based membrane biofilm reactor (O2-MBfR). In the first stage of the synergistic platform, HOPs were reductively dehalogenated to less toxic and more biodegradable OPs during continuous operation of a H2-based membrane catalytic-film reactor (H2-MCfR). The synergistic platform experiments demonstrated that OPs generated in the H2-MCfR were used as the primary substrates to support the co-oxidation of HOPs in the subsequent O2-MBfR. Once at least 90% conversation of HOPs to OPs was achieved in the H2-MCfR, the products (OPs to HOPs mole ratio >9) in the effluent could be completely mineralized through co-oxidation in O2-MBfR. By using H2 gas as the primary substrate, instead adding the analog OP, the synergistic platform greatly reduced chemical costs and carbon-dioxide emissions during HOPs co-oxidation.
ContributorsLuo, Yihao (Author) / Rittmann, Bruce (Thesis advisor) / Krajmalnik-Brown, Rosa (Committee member) / Torres, Cesar (Committee member) / Arizona State University (Publisher)
Created2022
Description
Retinotopic map, the map between visual inputs on the retina and neuronal activation in brain visual areas, is one of the central topics in visual neuroscience. For human observers, the map is typically obtained by analyzing functional magnetic resonance imaging (fMRI) signals of cortical responses to slowly moving visual stimuli on the retina. Biological evidences show the retinotopic mapping is topology-preserving/topological (i.e. keep the neighboring relationship after human brain process) within each visual region.
Unfortunately, due to limited spatial resolution and the signal-noise ratio of fMRI, state of art retinotopic map is not topological.
The topic was to model the topology-preserving condition mathematically, fix non-topological retinotopic map with numerical methods, and improve the quality of retinotopic maps.
The impose of topological condition, benefits several applications.
With the topological retinotopic maps, one may have a better insight on human retinotopic maps, including better cortical magnification factor quantification, more precise description of retinotopic maps, and potentially better exam ways of in Ophthalmology clinic.
ContributorsTu, Yanshuai (Author) / Wang, Yalin (Thesis advisor) / Lu, Zhong-Lin (Committee member) / Crook, Sharon (Committee member) / Yang, Yezhou (Committee member) / Zhang, Yu (Committee member) / Arizona State University (Publisher)
Created2022
Description
Electroactive bacteria connect biology to electricity, acting as livingelectrochemical catalysts. In nature, these bacteria can respire insoluble compounds like
iron oxides, and in the laboratory, they are able to respire an electrode and produce an
electrical current. This document investigates two of these electroactive bacteria:
Geobacter sulfurreducens and Thermincola ferriacetica. G. sulfurreducens is a Gramnegative iron-reducing soil bacterium, and T. ferriacetica is a thermophilic, Grampositive bacterium that can reduce iron minerals and several other electron acceptors.
Respiring insoluble electron acceptors like metal oxides presents challenges to a
bacterium. The organism must extend its electron transport chain from the inner
membrane outside the cell and across a significant distance to the surface of the electron
acceptor. G. sulfurreducens is one of the most-studied electroactive bacteria, and despite
this there are many gaps in knowledge about its mechanisms for transporting electrons
extracellularly. Research in this area is complicated by the presence of multiple pathways
that may be concurrently expressed. I used cyclic voltammetry to determine which
pathways are present in electroactive biofilms of G. sulfurreducens grown under different
conditions and correlated this information with gene expression data from the same
conditions. This correlation presented several genes that may be components of specific
pathways not just at the inner membrane but along the entire respiratory pathway, and I
propose an updated model of the pathways in this organism. I also characterized the
composition of G. sulfurreducens and found that it has high iron and lipid content
independent of growth condition, and the high iron content is explained by the large
abundance of multiheme cytochrome expression that I observed. I used multiple
microscopy techniques to examine extracellular respiration in G. sulfurreducens, and in
the process discovered a novel organelle: the intracytoplasmic membrane. I show 3D
reconstructions of the organelle in G. sulfurreducens and discuss its implications for the
cell’s metabolism. Finally, I discuss gene expression in T. ferriacetica in RNA samples
collected from an anode-respiring culture and highlight the most abundantly expressed
genes related to anode-respiring metabolism.
ContributorsHowley, Ethan Thomas (Author) / Torres, César I (Thesis advisor) / Krajmalnik-Brown, Rosa (Thesis advisor) / Nannenga, Brent (Committee member) / Arizona State University (Publisher)
Created2022
Description
The microorganisms that colonize the gastrointestinal tract have been recognized over the last several decades to have a significant bearing on the health trajectories of the hosts that harbor them. The collection of these gut microbes display links with acute and chronic disease, garnering substantial interest in leveraging the microbiome for improved health states. How these microbes assemble as a complex community and interact with each other, and the host depends on a multitude of factors. In adulthood, diet is one of the main moderators, having a significant influence on community composition and the functional output captured in the metabolites produced and/or modified by the gut microbiome. Thus, the assembly of microbes in the gut are tightly intertwined with health. In this dissertation, I examine the impact of diet and feeding behaviors on the gut microbiome and what features may be grounding or responsive under such pressures. Specifically, I first explore the avian gut microbiome as a barometer of nutritional and environmental influence on host health. Birds have continually displayed robust physiology under dietary pressures, placing them in an important, though underutilized, position within the translational science framework. Second, I describe the association of food insecurity on gut microbiome and metabolome profiles in a diverse college-based sample. Food insecurity provides its own set of unique pressures, such as unintentional calorie restriction, and inconsistent dietary intake and access to healthy food options. Third, I examine the effect of a one vs. two-consecutive days of intermittent fasting on the gut microbiome, the plasma metabolome, and associated clinical outcomes in overweight and obese adults. Growing in scientific and lay popularity, dietary fasting has been noted to induce changes in the diversity of gut microflora and gut motility, though different fasting lengths have not been assessed in the context of the human microbiome. Overall, this collection of work underscores that the community of microbes in the gut are individualized, resilient, and baseline composition and functioning are germane to how an individual may react to a particular dietary intervention.
ContributorsMohr, Alex (Author) / Sweazea, Karen L. (Thesis advisor) / Johnston, Carol S. (Committee member) / Sears, Dorothy D. (Committee member) / Whisner, Corrie M. (Committee member) / Krajmalnik-Brown, Rosa (Committee member) / Arizona State University (Publisher)
Created2022
Description
Trichloroethene (TCE) and hexavalent chromium (Cr (VI)) are ubiquitous subsurface contaminants affecting the water quality and threatening human health. Microorganisms capable of TCE and Cr (VI) reductions can be explored for bioremediation at contaminated sites. The goal of my dissertation research was to address challenges that decrease the efficiency of bioremediation in the subsurface. Specifically, I investigated strategies to (i) promote improve microbial reductive dechlorination extent through the addition of Fe0 and (ii) Cr (VI) bio-reduction through enrichment of specialized microbial consortia. Fe0 can enhance microbial TCE reduction by inducing anoxic conditions and generating H2 (electron donor). I first evaluated the effect of Fe0 on microbial reduction of TCE (with ClO4– as co-contaminant) using semi-batch soil microcosms. Results showed that high concentration of Fe0 expected during in situ remediation inhibited microbial TCE and ClO4– reduction when added together with Dehalococcoides mccartyi-containing cultures. A low concentration of aged Fe0 enhanced microbial TCE dechlorination to ethene and supported complete microbial ClO4– reduction. I then evaluated a decoupled Fe0 and biostimulation/bioaugmentation treatment approach using soil packed columns with continuous flow of groundwater. I demonstrated that microbial TCE reductive dechlorination to ethene can be benefitted by Fe0 abiotic reactions, when biostimulation and bioaugmentation are performed downstream of Fe0 addition. Furthermore, I showed that ethene production can be sustained in the presence of aerobic groundwater (after Fe0 exhaustion) by the addition of organic substrates. I hypothesized that some lessons learned from TCE Bioremediation can be applied also for other pollutants that can benefit from anaerobic reductions, like Cr (VI). Bioremediation of Cr (VI) has historically relied on biostimulation of native microbial communities, partially due to the lack of knowledge of the benefits of adding enriched consortia of specialized microorganisms (bioaugmentation). To determine the merits of a specialized consortium on bio-reduction of Cr (VI), I first enriched a culture on lactate and Cr (VI). The culture had high abundance of putative Morganella species and showed rapid and sustained Cr (VI) bio-reduction compared to a subculture grown with lactate only (without Morganella). Overall, this dissertation work documents possible strategies for synergistic abiotic and biotic chlorinated ethenes reduction, and highlights that specialized consortia may benefit Cr (VI) bio-reduction.
ContributorsMohana Rangan, Srivatsan (Author) / Krajmalnik-Brown, Rosa (Thesis advisor) / Delgado, Anca G (Thesis advisor) / Torres, César I (Committee member) / van Paassen, Leon (Committee member) / Arizona State University (Publisher)
Created2022