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Neuroendocrine regulation of social dominance and reproductive success in a highly social cichlid fish
No full textSexual reproduction requires animals to be in the right state at the right time to successfully reproduce. How does an animal regulate its readiness to mate and how does it respond to the social interaction that is mating before ultimately producing viable offspring. Using the highly social African cichlid fish, Astatotilapia burtoni, my dissertation research employed neurobiological and transcriptomic approaches to investigate the function and evolution of neuroendocrine gene networks in the regulation of reproduction. A. burtoni males exhibit remarkable social status-dependent plasticity whose neuromolecular underpinnings have been well characterized. Specifically, my research asked how animals get ready to reproduce, reproductive state, investigated the act of reproduction, reproduction synchronization, and analyzed the consequences of reproduction, reproductive success. Taken together, my dissertation research traces how an individual prepares, participates, and succeeds at reproduction, thereby providing a powerful framework for the study of social behavior and its neuromolecular underpinnings in non-traditional model systems.Ecology, Evolution and Behavio
Application of mathematical optimization to the resilience and reliability of the electric grid
No full textAs the electric grid is fundamental to modern society, it is imperative to maintain the functioning of the electric grid in the face of both high-impact, low-probability events and low-impact, high-probability events. Namely, the electric grid must receive the support needed for it to exhibit resilience as well as reliability. It is then considered that mathematical optimization is the branch of applied mathematics concerned with finding the best solution to a problem. Consequently, while mathematical optimization is not the focus of this dissertation, it does contain decidedly novel research contributions to the application of mathematical optimization for the resilience and reliability of the electric grid. The contributions include not only optimization models developed but also other concepts devised in the process of developing the models. One electric-grid resilience issue that this dissertation tackles with optimization is the application of mobile energy storage (MES) to assist with black-start (BS) restoration of a transmission system. MES-assisted BS restoration is assessed from the perspectives of pre-placement before a blackout and multi-period operations over a time horizon following a blackout. In the former case, the concept of a discretized expected value realization is devised to address the inadequacy of the expected value problem when presented with an integer-valued random parameter vector. Another electric-grid resilience issue this dissertation optimally approaches is the enhancement of the flood resilience of a transmission system. Resilience of the transmission system to a particular, imminent flood event is enhanced with mobile-substation (MS) resources, and resilience to multiple potential flood events over a multi-year horizon is enhanced with substation hardening. In the former case, an intricate optimization model considering MS resources arises, so a parallel heuristic is devised to efficiently solve instances of the model. Lastly, an electric-grid reliability issue that this dissertation confronts with optimization is the installation of fault indicators (FIs) to facilitate impedance-based fault location within a radial distribution system. The optimization model for placing FIs leverages the concept of an expanse, which is devised to account for continuous ranges of fault locations.Electrical and Computer Engineerin
An investigation of inorganic nanomaterial synthesis via extracellular electron transfer by Shewanella oneidensis
No full textInorganic materials play a role in an ever-growing part of our everyday lives. These materials have multiple applications in several industries but find expanded use as nanomaterials. Changes in surface area, porosity, and structural organization convey distinct properties in particles that present advantages to their macro-sized counterparts. These materials are typically synthesized using physical and chemical methods, but recent advances in in genomic tools, synthetic regulations, and non-natural biomolecules as well as mild reaction conditions and enhanced stability are advantages of biological synthesis. Despite these advances, there are limitations to tunability and our understanding of these systems. To address this, we utilize the extracellular electron transfer (EET) mechanism in Shewanella oneidensis as a platform for biosynthesis of inorganic nanomaterials. This work seeks to explore the diversity of inorganic nanomaterials that can be synthesized, modulated, or controlled using EET. The first part of this work explores the functionality of linking EET with metal reduction to evaluate the breadth and properties of materials that can be formed via biological redox reactions. This work specifically looks to expand knowledge of the types of nanomaterial formation achievable with S. oneidensis as the source of synthesis. It also aims to understand the functional properties associated with those materials. In chapter 2, we show the application of this system toward the formation of palladium nanoparticles. In chapter 3, we demonstrate ability of this system for the reduction of ruthenium. The second part of this work investigates EET mechanics and evaluates for key components and system changes associated with different electron accepters. This objective expands on the first, specifically probing the relationship between the abiotic/biotic interface to elucidate specific metabolic impacts when utilizing EET pathways with varying electron acceptors. In this case, we seek to explore how the phenotypic factors associated with material formation are impacted by changes in culture workflow and genotypic changes enabled by microbial engineering. To achieve this, we used a variety of knockouts, gene expression systems using genetic logic, and modified proteins with binding peptides. This work provides foundational knowledge for the advancement of biological synthesis of inorganic materials using biological electron transfer.Chemical Engineerin
Computational modeling of protein fluorosequencing
Get PDFSingle molecule protein sequencing is a field of new technologies for proteomics with great potential. I developed a machine learning-based interpretive framework called whatprot to analyze data produced by the single molecule protein sequencing technique we call fluorosequencing. whatprot accurately fits and classifies fluorosequencing data using specially customized implementations of k-Nearest Neighbors (kNN) and hidden Markov models (HMM). In particular, the transition matrices of the hidden Markov models are factored to dramatically improve runtime and enable direct parameter estimation with a modified Baum-Welch implementation that we have been unable to find in existing literature. I also compared this parameter estimation method with a method developed by Kent VanderVelden using DIRECT followed by Powell’s method as a sanity check on our implementation. Lastly, I began to explore peptide and protein inference from fluorosequencing data, guiding a master’s degree student, Sophia Zhou, in using expectation maximization (EM) for this purpose.Computational Science, Engineering, and Mathematic
Studies on the cellular localization and spore morphology of Hip1r phosphomutants in Dictyostelium discoideum
Get PDFClathrin mediated endocytosis is a multistep process that facilitates the transport of material across membranes in eukaryotic cells. Cargo molecules internalize in clathrin coated vesicles on the plasma membrane and are transported into the intracellular space. Clathrin and several accessory and adaptor proteins participate in this process. Epsin and Hip1r are two adaptor proteins that provide a structural link between the plasma membrane and the clathrin pits. Using Dictyostelium discoideum as our model organism, previous studies in our lab showed that epsin is required for the phosphorylation and proper localization of Hip1r. Furthermore, cells lacking epsin or Hip1r share defects in spore morphology and the dynamic assembly of clathrin and actin on the plasma membrane. Because cells lacking epsin contain only non-phosphorylated Hip1r, we hypothesized that Hip1r phosphorylation could be related to the phenotypic defects. Having identified three sites of phosphorylation in the Hip1r sequence, we tested both the cellular localization and function of Hip1r phosphomutants expressed in cells lacking Hip1r. A special focus of this project was on residue S417. We found that Hip1r null cells expressing a phosphosilent version of Hip1r (Hip1r [superscript S417A]) were indistinguishable from non-transformed wild type cells in the cellular localization of the protein and spore morphology. Hip1r null cells expressing a phosphomimetic version of Hip1r (Hip1r [superscript S417D]) showed wild type spore morphology, but had a different distribution on the plasma membrane than wild type. A helix breaking mutant (Hip1r [superscript S417G]) rendered the protein non-functional, with round spore morphology and cellular distribution closer to the Hip1rS417D. Expression of the same mutants in epsin null cells had similar effects in localization but failed to rescue the defective spore morphology of epsin null cells. These results show that phosphorylation is not important for spore morphology but it may act as a spatiotemporal switch; non-phosphorylated Hip1r may become phosphorylated to promote dissociation from the clathrin pits. The function of Hip1r is dependent on the integrity of the helix. Finally, epsin has an additional role in the process than mediating Hip1r phosphorylation.Microbiolog
Microwave impedance microscopy for the characterization of dielectrics, ferroelectrics, and amorphous semiconductors
Get PDFThe invention of field-effect transistors in the last century has led to substantial technological advances, which greatly changed our daily life over the past few decades. As we enter the era of artificial intelligence, the quest of ever-increasing computing power has set high demands for new materials, new architectures, and new characterization tools. The traditional way of characterizing device performance is electrical transport, such as the measurements of current-voltage relation or capacitance-voltage relation. However, this type of method may suffer from contact issues, making it difficult to obtain the intrinsic properties. In this dissertation, I will use three examples to show how we implement microwave impedance microscopy (MIM) to extract material information that is less likely accessible by conventional techniques. The first example is to evaluate the dielectric constant of ultrathin dielectric flakes. By combining MIM scanning and COMSOL simulation, we successfully extracted the permittivity values of several high-κ oxides and low-κ polymers. The thinnest flake we measured is about 2 nm. The second one is to image the coexistence of polar and non-polar BiFeO₃ phases. The contrast in MIM-Im and MIM-Re channels can be attributed to the difference in permittivity and AC conductivity between the two phases, respectively. The extracted permittivity values match well with results from other independent experiments. The AC conductivity is almost unchanged for a broad range of frequencies, confirming that it is electronic in nature. The last one is to study the charge transport of amorphous InGaZnO (a-IGZO) thin film transistors. We studied the equilibrium and transient states of the devices by applying constant and pulsed gate bias, respectively. Through the analysis of MIM images and transient signals, we visualized the potential landscape, identified two transport mechanisms, and extracted the characteristic length and time scales. All results provide new insights into the properties of these advanced materials, which are important for their future applications in nanoscale transistors, memories, and displays. The ideology can be generalized to the characterization of other newly discovered materials and devices as well.Physic
InSb-based dilute-bismide alloys for long-wave infrared sensing
Get PDFDilute-bismide alloys have received significant attention over the past few decades due to the rather dramatic bandgap reductions caused by the incorporation of small concentrations of bismuth into traditional III-V alloys. This presents unique opportunities in strain and bandgap engineering for optoelectronic devices; in fact, bismuth-induced bandgap reductions can be leveraged to access technologically significant wavelength ranges for sources and emitters with III-V-Bi materials. In particular, dilute-bismide alloys have the potential to enable access to the long-wave infrared (LWIR), a spectral region with numerous applications in gas sensing, astronomical imaging, and thermography. Currently, LWIR devices continue to be dominated by the material system mercury cadmium telluride (Hg[subscript 1-x]Cd[subscript x]Te). As this material system not only suffers from numerous growth and fabrication challenges but is also comprised of highly toxic constituent elements, there is strong motivation for developing a direct transition, lattice-matched III-V alloy with tunable bandgap energies across the LWIR. Since InSb possesses the narrowest bandgap energy of any traditonal III-V binary alloy, InSb-based dilute-bismide alloys can be expected to span the entire LWIR with minimal bismuth incorporation. As compared to wider bandgap host matrices, InSb and III-Bi materials boast relatively similar properties including bond strengths, electronegativities, and optimal growth temperatures. In turn, this may enable significant bismuth incorporation into InSb without the extreme material and optical degradation often seen in other dilute-bismide alloys. Despite these advantages, InSb[subscript 1-x]Bi[subscript x] and antimony-rich InAs[subscript y]Sb[subscript 1-x-y]Bi[subscript x] remain relatively underexplored and many fundamental material properties have yet to be experimentally investigated for these InSb-based dilute-bismide alloys. This work seeks to optimize the growth window for InAs[subscript y]Sb[subscript 1-x-y]Bi[subscript x] and gain a deeper understanding of the alloy's structural and optical properties to evaluate the material system's potential for high-performance optoelectronic devices. In particular, this work demonstrates, for the first time, InSb[subscript 1-x]Bi[subscript x] with unity-sticking bismuth incorporation as a route to photoluminescence at extended wavelengths beyond that of InSb. Building on this, the additional incorporation of small amounts of arsenic is shown to restore lattice-matching to InSb substrates, which is of paramount importance for photodetectors. To wholly evaluate the potential of this material system for optoelectronic devices, prototype photodetectors are designed, fabricated, and characterized showcasing extension in cutoff wavelength beyond that of InSb photodetectors.Electrical and Computer Engineerin
Emission and dispersion models to assess impacts of unconventional oil and gas development on air quality and community exposures
Get PDFThe rapid expansion of unconventional oil and gas development (UOGD) in the United States has resulted in detrimental impacts on climate, air quality and human health. To comprehensively assess the impacts of UOGD on air quality and community exposures, better characterization of emissions from UOGD is needed. However, the complexity and heterogeneity of UOGD operations make the characterization of emissions difficult and limited. UOGD operations emit various pollutants, including several criteria air pollutants and hazardous air pollutants, with sources and characteristics varying significantly between and within sites. Transport and transformation of these pollutants further complicates source attribution and exposure assessment. To accurately estimate impacts of UOGD emissions and attribute ambient concentrations of pollutants to sources, fine scale spatial and temporal characterization of these emissions is required. This dissertation describes the development of spatially and temporally resolved emissions of Nitrogen oxides (NOx) from a highly localized and transient UOGD source, hydraulic fracturing. These fine scale emissions are coupled with a chemical transport model to assess their impacts on regional air quality. Accurate spatial and temporal allocation of NOx emissions from hydraulic fracturing leads to increased predicted ozone formation in Eagle Ford Shale of Texas, a NOx-limited region. Frameworks to simplify atmospheric dispersion models for use in exposure assessment and measurement reconciliation are also developed. In Eagle Ford Shale, modeling dispersion from oil and gas sources within a 50-100 km radius of a receptor site is necessary to fully explain concentrations at that site. A space-weighted source aggregation method within this radius can reduce the number of sources by an order of magnitude, while maintaining accuracy in exposure predictions. Finally, a nested modeling domain for dispersion modeling is proposed, which aims to capture local effects and regional trends. These frameworks will contribute to a community model predicting exposures from UOGD.Chemical Engineerin
On neural mechanisms for relaying sensory inputs
Get PDFSensory systems must maintain sensitivity and selectivity across a broad range of environments and behavioral contexts to compute meaningful representations of the world. The relay of sensory information from peripheral receptors to central brain areas is a dynamic process, as the neural code shifts with both environmental and internal states. While these adaptations allow organisms to navigate the range of contexts which they encounter, dynamic sensory relay also raises the question of how cortical areas construct reliable sensory representations across conditions.
The clearest example of the dual challenges of maintaining sensitivity and selectivity in sensory systems comes from luminance adaptation in the visual system. To maintain sensitivity across the massive range of luminance intensities encountered between midnight and midday, the retina transitions between rod and cone-mediated phototransduction. This adaptation is known to shift the selectivity of retinal ganglion cells, which relay the output of the retina to central brain areas. In the first part of this dissertation, I show how thalamic and cortical populations encode features of the visual world across luminance conditions. I present data from large populations of simultaneously recorded neurons in the mouse to show that visual cortex generates a representation that is invariant to the absolute intensity of peripheral signals. I show how a physiologically constrained model of the visual pathway provides a mechanism by which visual cortex generates a luminance-invariant code despite changing receptive fields and interneuronal correlations at the periphery.
In addition to exploring sensory relay across environmental conditions, in the second part of this dissertation I explore how sensory relay is disrupted in disease. Typical thalamocortical relay is characterized by two distinct firing modes- burst and tonic. These two firing modes are hypothesized to function in tandem to relay distinct sensory information to cortex. Using population recordings in mouse thalamus, I quantify the distribution of firing modes and synchrony across neurons. I also show how firing mode is modulated by behavioral state. Finally, I show that in Fragile X mutant mice, the typical distribution of thalamic firing modes is disrupted, which may contribute to the abnormal cognitive phenotype of individuals with FX.Psycholog
Intricate interaction of dietary saturated fat intake and plasma triglycerides on memory performance in middle-aged adults
Get PDFAlzheimer's disease and related dementias are projected to triple by 2050. Addressing modifiable health and lifestyle factors is crucial for prevention and reducing the associated public health burden. This study investigates the interaction between triglyceride levels and dietary intake and quality on memory performance in middle-aged adults at heightened risk for metabolic health issues. Community-dwelling adults aged 40-65 participated in this cross-sectional study. Participants were excluded if they had a history of neurological or psychiatric disease, or were smokers. Dietary intake was self-reported via a 3-day food record. Serum triglyceride levels were measured. Neuropsychological testing assessed memory performance. Cross-sectional regression analyses examined the interactions between dietary intake and quality with triglyceride levels on memory performance in 146 middle aged adults with heightened cardiometabolic risk. The analysis revealed a significant interaction between triglyceride levels and the ratio of dietary saturated fat to total caloric intake on memory performance (β = -0.087, p = 0.022). Participants with elevated triglyceride levels and a higher ratio of saturated fat in their diet performed worse on memory tests. Conversely, those with elevated triglycerides but a lower ratio of saturated fat in their diet exhibited better memory performances. Higher adherence to USDA dietary guidelines, indicated by higher Healthy Eating Index 2020 scores, was associated with better memory performance (β = 0.018, p < 0.002), regardless of triglyceride levels. Thus, diet quality, measured by adherence to dietary guidelines, is broadly beneficial for cognitive health. Although, the combination of elevated triglyceride levels with a high ratio of dietary saturated fat intake is significantly associated with poorer memory performance in midlife adults. Precision nutrition strategies to reduce the ratio of saturated fat to total caloric intake guided towards midlife adults with elevated triglyceride levels may mitigate memory-related cognitive decline and improve brain health.Psycholog