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Interfacing Proteins with Conducting Polymers for the Fabrication of Biohybrid and Biomolecular-based Electronics
No full textThe overarching theme of the work presented herein is the combination of proteins with conducting polymers for the investigation of biohybrid and biomolecular-based electronics. While this topic is broad and encompasses many potential avenues of application, this doctoral research focuses on the interfacial properties and applications of proteins and conducting polymers through the themes of green renewable energy and biosensing. In exploring novel approaches for solar energy conversion, Photosystem I (PSI), an intrinsically photoactive multi-subunit protein that is found in higher order photosynthetic organisms, is highlighted. PSI is a promising candidate for renewable biohybrid energy applications due to its abundance in nature and its high quantum yield. To utilize PSI’s light-responsive properties and to overcome its innate electrically insulating nature, the protein can be paired with a biologically compatible conducting polymer that carries charge at appropriate energy levels, allowing excited PSI electrons to travel within a composite network upon light excitation.
This dissertation offers insight into the combination of PSI with two intrinsically conducting polymers (ICPs). First, PSI is mixed with the ICP poly(3,4-ethylenedioxythiophene):polystyrene sulfonate (PEDOT:PSS) to deposit well-mixed thin films via spin coating from aqueous solution, enabling uniform, reproducible, and rapid film formation in which the composition and thickness of composite films can be readily tuned up to a few hundred nanometers. The combination of the protein and ICP yields increased photocurrents and turnover numbers when compared to single-component films of the protein or ICP alone to reveal a synergistic combination of film components. Second, we chemically oxidize a methoxy aniline (para-anisidine) to synthesize poly(p-anisidine) (PPA) and interface this polymer with PSI for the fabrication of PSI-PPA composite films by drop casting. Combining PPA with PSI yields composite films that exhibit photocurrent densities on the order of several μA/cm2 when tested with appropriate mediators in a 3-electrode setup. The composite films also display increased photocurrent output when compared to single-component films of the protein or PPA alone to reveal a synergistic combination of the film components. Tuning film thickness and PSI loading within the PSI-PPA films yields optimal photocurrents for the described system.
For biosensing applications in bacteria or virus detection, we functionalize gold surfaces with antibodies via photo- and electrochemical approaches by combining the polymer polyaniline (PAni) with Staphylococcal Protein A Fluorescein antibody mimic, in the presence of a light-active benzophenone derivative. Effective mechanisms of detecting bacteria or viruses, i.e., SARS-CoV-2, have shown inadequate aptness to identify a virus rapidly and accurately, especially in early stages of infection, and at low pathogen concentrations. In this work, we fabricate photoactive films that could selectively bind an antibody protein to the surface. The functionalized surfaces are shown to be transferrable to micron-scale substrates for potential applications in microcantilever-based biosensing. The protein, Staphylococcal Protein A Fluorescein is tagged with a green fluorescent protein (GFTag) and is used as an antibody mimic to test the light reactivity and efficiency of poly(aniline-4-aminobenzophenone) films in selective protein binding. Cyclic voltammetry confirms the synthesis of conductive poly(aniline- 4-aminobenzophenone) films with improved binding to the GFTag protein under UV-light exposure
Ascorbate Depletion Disrupts Brain Function and Behavior After Mild Traumatic Brain Injury in Mice
No full textTraumatic brain injuries (TBIs) possess a complex pathophysiology that often results in chronic neurological and behavioral impairments. A critical component in the progression of TBI-related cellular damage and associated functional deficits is oxidative stress, as evidenced in both human and rodent studies. Vitamin C (Ascorbate, ASC) is a necessary antioxidant in the brain and protects against oxidative stress. Dietary deficiency of ASC is of concern for humans who do not get adequate nutrition. Depleted levels of ASC have been associated with altered neuroinflammatory response, changes in neurotransmitter metabolism and increased oxidative stress, which may each contribute to the pathophysiology and cognitive change following mild TBI. Neuroinflammation is a major characteristic of pathology in TBI. Microglia, the brain’s resident myeloid cells, shift between activation states under neuroinflammatory conditions, both responding to, but also driving damage in the brain. Uptake of ASC throughout the central nervous system is facilitated by the sodium-dependent vitamin C transporter 2 (SVCT2). SVCT2 transports the reduced form of ASC into neurons and microglia, however the contribution of altered SVCT2 expression to the neuroinflammatory response in microglia is not well understood.
We investigated the impact of depleted brain ASC on behavioral outcomes in mild TBI and explores the potential involvement of glutamate-related mechanisms. Our results indicate that a single mTBI event disrupted prepulse inhibition outcomes acutely in a sexually dimorphic manner, with resolution occurring at different time courses for male and female mice. We also demonstrate that SVCT2 expression modifies microglial response, as shown through changes in cell morphology and mRNA expression, following a mild TBI in mice with decreased or increased expression of SVCT2. Results were supported by in vitro studies in an immortalized microglial cell line and in primary microglial cultures derived from SVCT2-heterozygous and transgenic animals.
Together these studies demonstrate the importance of SVCT2 and ASC in modulating the microglial response to mTBI and suggests a potential role for both in response to mitigate oxidative driven neuroinflammatory challenges and associated behavioral changes
Functional Transfer of miRNA Promotes Cancer Cell Growth and Enhances Invasiveness
No full textmicroRNAs display increased expression in cells and extracellular vesicles and nanoparticles (EVPs) from cancer cells. miR-100 and miR-125b were previously identified as having increased expression in colorectal cancer cells. Utilizing a combination of bioinformatics and analysis of gene expression patterns in both wild type and miR-100/miR-125b colorectal cancer cell lines, 96 different potential miR-100 and miR-125b targets were identified and 13 were verified as targets by reporter assays. Among those targets, I found that one of the most statistically downregulated proteins in these assays was Cingulin (CGN), a protein that links the cytoskeleton to tight junctions. I found that increased expression of miR-100 and miR-125b causes cell-autonomous downregulation of CGN and that transfer of miR-100 and miR-125b by extracellular vesicles can inhibit CGN expression in recipient cells in a non-cell-autonomous manner. Consistent with a role for tight junctions in invasion and metastasis of colorectal cancer cells, I found that downregulation of CGN by miR-100 and miR-125b increased 3D growth and invasiveness in both colorectal and glioblastoma cancer cell lines
A Mixed-Method Study of the Implementation of a Two-Question Screening Protocol Assessing Homelessness and Housing Insecurity in an Urban Emergency Department
No full textAbstract
Background
Hospital screenings for social determinants of health are becoming more prevalent. Although Senate Bill 1152 mandated a homelessness screen within California hospitals and the Veterans Health Administration has a housing screen in outpatient clinics, neither the Veterans Health Administration nor California hospitals have evaluated the screening question wording. The current study examines the process of implementing a screen for homelessness and housing insecurity in an urban Emergency Department (ED) with a Level 1 trauma center. Patients who screened positive were referred to social workers for assistance. We describe resulting changes in procedures and evaluate alternative screening questions.
Methods
This paper consists of two studies. For Study 1, from November 2022 to March 2023, we conducted qualitative interviews with 26 registration, social worker (SW), and physician ED staff, with iterative modifications to procedures created in response through February 2024. We also conducted a focus group of people with lived experience to gather their perspective on the screening questions. Because Study 1 uncovered concerns with question wording, we tested the predictive efficacy of different questions in quantitative Study 2 in Fall 2023.
Results
For Study 1, registration staff reported that the two-question screening integrated into their workflow well, but was complex. SWs reported that they engaged with more patients, felt more comfortable navigating resources, and could follow up with patients during subsequent ED visits. Physicians reported care adaptations for patients they believed homeless; however, they did not use the screening information. For Study 2, altered wording led to fewer patients screening positive and fewer true positives as evaluated by SWs but a higher positive predictive value.
Conclusion
The modified screening process was acceptable within registration and SW workflows and did not directly impact physician workflow. Our screening process lays the groundwork for improving care for patients facing homelessness and housing insecurity
The Study of Lens AQP0-Protein and -Lipid Interactions using Advanced Mass Spectrometry Methods
No full textThe ocular lens is an avascular tissue that generates an internal microcirculation system that delivers nutrients, regulates lens homeostasis, and is fundamental for lens transparency and lens function. Lens membrane aquaporins are water permeable channel proteins that participate in the generation and regulation of the lens microcirculation system (MCS). The most abundant aquaporin in the lens is aquaporin-0 (AQP0) which, in addition to being a water channel, functions as a cell-adhesion molecule. Given the important role of AQP0 in lens transparency and cataract development, understanding how proteins regulate AQP0 structure and function is critical to understanding its role in the MCS. Furthermore, the lipid composition surrounding integral membrane proteins has been shown to affect membrane protein structure, function, and stability, yet prior to this work, interactions with native lens lipids had not been elucidated for AQP0. This dissertation focused on characterizing full-length AQP0-protein and AQP0-lipid interactions using crosslinking-mass spectrometry (XL-MS), hydrogen-deuterium exchange mass spectrometry (HDX-MS) and native mass spectrometry (nMS). Through XL-MS, specific regions of interaction were elucidated for several AQP0 interacting partners including phakinin, α-crystallin, connexin-46, and connexin-50 and, two new interacting partners, vimentin and connexin-46, were identified. Through nMS, a variety of endogenous lens lipids, i.e., phosphatidylcholines (PCs) and sphingomyelins (SMs) were found to differentially bind AQP0 in a regionally dependent manner (lens cortex vs nucleus) suggesting that the native lipid environment surrounding AQP0 regulates its function differentially throughout the lens. Since both proteins and lipids regulate AQP0, the specific lens proteins and lipids found in this work to interact with AQP0 can inform us on how these interactions impact AQP0 structure and function in the context of the MCS. My dissertation research advances the lens field by demonstrating how and where proteins and lipids interact with AQP0 in the lens and provides a framework for the development of therapeutics and/or practices that could help delay or prevent the onset of cataracts. Furthermore, the mass spectrometry techniques, methods, and sample preparation workflows established in my studies of AQP0 could be of particular use to membrane protein structural biologists
Rotationally Driven Activity of Red Giant Stars in the UV
No full textThe magnetic activity of stars is known to be produced by stellar dynamos, which are driven by rotation and convection of the stellar atmosphere. However, before a star evolves into a giant, rotation is greatly diminished due to wind angular momentum loss. Additionally, once a star begins ascent of the red giant branch, its envelope begins to swell, and conservation of angular momentum forces rotation to slow further. As a consequence of this evolutionary spin down, giant stars are generally observed to be inactive because they lack the necessary rotation to stimulate strong dynamo action. Given the expectation that giants spin slowly, most stellar activity research has favored observations of dwarf stars. A considerable number of giants have been discovered to have appreciable rotation rates and magnetic fields, but how their stellar activity relates to dwarf stars remains uncertain. In this dissertation, we sample giants observed by the Sloan Digital Sky Survey APOGEE and investigate their stellar activity through empirically derived relationships between near-UV (NUV) excess and projected rotational velocity (vsini). Our relations are initially fit to 133 red giant stars, where we demonstrate NUV excess is strongly correlated to vsini. Furthermore, these relations are found to share trends with M dwarf rotation-activity relations, including saturation/supersaturation. This suggests similar dynamo origins for giants and cool dwarf stars. After expanding our sample to 7,286 giants, we fit a linear correction function ζ([M/H]) to account for metallicity dependence due to line-blanketing. Analysis using ζ([M/H]) corrected NUV excess reveals rotationally active giants typically have large radial velocity variations, which supports tidal synchronization as the dominant channel for rotationally active giants. We also find convincing evidence that giants dimmer/redder than the red giant branch, i.e. sub-subgiants, are especially active synchronized giant binaries. Our rotation-activity relations serve as a general approach for advancing activity research for post-main-sequence stars. Our results add new insight into giant activity by demonstrating fundamental similarity to cool dwarfs and differences between single and binary giants
Development of a High-Contrast Heads-Up Display for Intraoperative Ophthalmic Surgical Guidance
No full textMicroscope-integrated intraoperative optical coherence tomography (iOCT) enables depth-resolved imaging of ocular structures and tissue-instrument interactions during ophthalmic surgery. Real-time visualization of iOCT data for surgeon feedback has been demonstrated with external monitors in the surgical suite and with heads-up displays (HUDs) optically coupled into the surgical microscope oculars. When iOCT is displayed on external monitors, stereoscopic surgical views are either completely lost or require the use of polarization glasses with limited viewing angles, which hinders surgical workflow. Current intraocular HUDs couple LED/OLED displays with a beamsplitter cube that inherently limits surgical field visualization because display contrast is limited by low panel brightness and display and surgical field brightness trade-offs. Therefore, overlays are generally constrained to dark or unused regions of the surgical field-of-view (FOV), which limits displays of important qualitative information onto the FOV. Here, we demonstrate a digital micromirror device (DMD) based HUD that overcomes the contrast limitations of existing intraocular HUDs. We demonstrate live OCT overlays in benchtop experiments of ophthalmic surgical maneuvers with a preliminary DMD-HUD design using stock optics. We also present a custom optical design for a DMD-HUD that overcomes the limitations of our preliminary design to enable clinical translation. Further development of this technology will enhance real-time iOCT visualization to improve surgical ergonomics and provide augmented reality guidance during ophthalmic surgery
Black Feminist Empiricism: An Exploration of a Black Woman’s Science Engagement
No full textIn this dissertation, I develop Black feminist empiricism as a conceptual framework grounded in Black feminist epistemologies to recognize Black womxn’s contributions to science and science learning. I build on work in critical human geography to conceptualize rational spatial domination, a mechanism that positions Black womxns’ knowledge production in science as impossible. Black feminist empiricism is fundamentally political, as it is tied to the oppositional knowledge production that Black womxn produce as an oppressed group within the context of White supremacy. I draw on the three dimensions of this conceptual framework to examine the final project of a former student in a university Science Modeling course, a Black woman creating an embodied model using Black womxns expressive cultures to understand plant growth in new ways. The findings demonstrate a rich sensemaking practice tied to an intellectual genealogy that is currently not recognized as an empiricist tradition, highlighting the necessity of this theorization towards a more equitable forms of science learning for Black womxn
Modeling Individual Differences in High-Level Visual Cognition Using DNNs
No full textDeep neural networks (DNN) can be a useful tool in the wider computational modeling toolkit to provide mechanistic explanations of individual differences in high-level visual cognition. DNNs are well-suited to model sources of individual differences caused by representational variability. DNNs can generate representations from images that are informed by their experience and neural architecture, which can be used with cognitive models to simulate responses and response times given the images. This allows us to create end-to-end image-computable models of high-level visual cognition tasks that can directly act on the images that human participants would see. However, there remain foundational questions to be answered. In the first project, we asked which measure of representational variability was the best and leveraged the best measure to quantify the variability caused by model differences in model randomization, dataset distribution, and architecture. In the second project, we asked what factors should be manipulated to generate reliable representational variability across models by analyzing a large collection of pretrained DNNs and tested our findings by training our own set of models. In the final project, using DNNs in conjunction with a cognitive model, we tested whether we could replicate a classic pattern of results in categorization and then cause individual differences in performance based on manipulating DNN training. We have evidence towards how representational variability should be measured, what factors should be manipulated in DNNs to cause representational variability, and how to leverage representational variability to cause individual differences in cognitive models of high-level visual cognition tasks. Taken together, we completed the groundwork towards leveraging differences in DNNs to model individual differences in high-level visual cognition, opening the way for new model pursuits to understand the mechanisms underlying individual differences
Deep Clustering for FMRI Data Representation
No full textThis study investigates the use of autoencoder-based dimensionality reduction and deep clustering techniques to analyze functional connectivity (FC) matrices derived from resting-state fMRI data. Avalanche analysis was applied to extract key time points for FC computation, followed by encoding the high-dimensional FC matrices into 16-dimensional latent representations using MLP and CNN autoencoders (AEs) and variational autoencoders (VAEs). Among these models, the MLP AE outperformed others in reconstruction fidelity and variance differentiation in latent variables, enabling effective K-means clustering of distinct brain states. In contrast, VAEs showed lower reconstruction accuracy and limited clustering performance. These results demonstrate the potential of autoencoder-based methods in FC analysis for identifying functional brain states. Future work will explore dynamic FC and hyperparameter optimization for VAEs to enhance clustering outcomes