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Oral Health as a Predictor of Memory Accuracy in Healthy Older Adults
No full textIn the past, most Alzheimer's disease research has focused on the amyloid hypothesis, but recent studies have found that chronic inflammation caused by periodontal disease and negative changes in the gut microbiome could potentially contribute to the onset of the disease. However, previous studies investigating the relationship between oral health and cognition have all used varying methods to measure oral health, which has led to conflicting findings in the literature. In this study, we developed a comprehensive oral health survey and validated the scales using exploratory factor analysis. We also tested the association between oral health and cognition by analyzing the performance of 190 healthy older adults on the 15 Words Test, which is an episodic memory task. Our results suggest that there is no relationship between oral health and deficits in episodic memory. This work contributes to an existing debate in this field and could impact the direction of future research on the etiology of Alzheimer’s disease.UndergraduateNeuroscienc
Catalysts and Barriers to the Adoption of New Innovation Methods
No full textConference Paper presented as research in progress at XXXVI ISPIM Innovation Conference, held in Bergen, Norway on 15 June to 18 June 2025.Academics have developed a wide range of tools and methods to support innovation and the product development process. Unfortunately, few of these methods and tools have been widely adopted in industry. The current work seeks to identify what catalyzes and blocks the adoption of R&D innovation tools and methods in large organizations. Semi-structured exploratory interviews were conducted at several U.S.-based Fortune 500 companies. Interviewees include executives, managers, and individual contributors. Future work includes interviews with at least two more organizations with at least eight to ten individuals per organization. Initial interviews were transcribed, and open coding sought themes (commonly called categories) containing the catalysts and barriers. Initial findings indicate six themes that catalyze adoption: Confidence in the Method, Characteristics of the Method, Characteristics of the Practitioner, Practitioner Benefits, Leadership, and Organization. Barriers identified include Organization, Characteristics of the Method, Characteristics of the Practitioner, and Practitioner Drawbacks.National Science Foundation Grant No.223055
Scatter Protocol: An Incentivized and Trustless Protocol for Decentralized Federated Learning
No full textFederated Learning is a form of privacy-preserving machine learning where multiple entities train local models which are then aggregated into a global model. Current forms of federated learning rely on a centralized server to orchestrate the process, leading to issues such as requiring trust in the orchestrator, the necessity of a middleman, and a single point of failure. Blockchains provide a way to record information on a transparent, distributed ledger accessible and verifiable by any entity. We leverage these properties of blockchains to produce a decentralized, federated learning marketplace-style protocol for training models collaboratively. Our core contributions are as follows: first, we introduce novel staking, incentivization, and penalization mechanisms to deter malicious nodes and encourage benign behavior. Second, we introduce a dual-faceted lottery-based validation layer to ensure the authenticity of the models trained. Third, we test different components of our system to verify sufficient incentivization, penalization, and resistance to malicious attacks.UndergraduateComputer Scienc
Computational Investigation of Mixture Adsorption in Metal-Organic Frameworks
No full textTraditional separations necessitate high energy usage and thus have great costs and significant environmental impact associated with their operation. Adsorption systems have garnered much attention in recent years as replacement technologies for many of these conventional separations processes. As separations inherently involve mixtures, understanding adsorption from real mixtures, a complex process, is crucial for widespread industrial implementation. A significant amount of complexity arises from the wide variety of adsorbents from which to choose. One class of adsorbent is that of metal-organic frameworks (MOFs), porous materials comprised of inorganic nodes connected via organic ligands to yield structures with large surface areas and a significant degree of tunability. These materials have been heavily investigated for their potential to address separations problems with significant specificity due to their tunable nature. As measuring experimental mixture adsorption directly has yet to be widely implemented due to its relative difficulty compared to single-component adsorption experiments, many have turned to mixture adsorption prediction methods such as molecular simulations.
GCMC (Grand Canonical Monte Carlo) predictions of mixture adsorption in MOFs have been compared to those from IAST (Ideal Adsorbed Solution Theory), a popular method for predicting mixture adsorption, with experimental mixture adsorption measurements in three MOFs providing the basis against which to test these predictions. The merits and drawbacks of both prediction methods in the studied systems are considered both quantitatively and qualitatively. GCMC simulations are then leveraged to investigate adsorption systems which are either difficult or impossible to study with experimental adsorption measurements. Firstly, the significance of MOF characteristics to the relative impacts of electrostatic interactions during adsorption are studied with carbon dioxide and light hydrocarbons as adsorbate species. Secondly, the validity of the Henry adsorption isotherm model is assessed for minor representative impurities within post-carbon capture streams. Through these studies, the thesis work presented aims to aid the understanding of molecular simulations’ usefulness in the field of mixture adsorption.Ph.D.Chemical and Biomolecular Engineerin
Peripheral nerve transection results in the permanent deletion of propriosensory synapses through a Ccl2 mechanism
No full textSynaptic plasticity has been a topic of great interest, especially given the poor prognosis of motor neuron injuries that result in functional losses. Much research has investigated the effects of peripheral nerve injuries (PNIs) on the degradation of synaptic structures as well as the physiological deficits that result from the injuries (Alvarez et al., 2011; Bullinger et al., 2011). Unfortunately, not much is known about the mechanisms of how synaptic plasticity occurs following PNI and how that may contribute to motor deficits observed in injured models. This paper attempts to explore Ccl2, a ligand implicated in the recruitment of Ccr2 immune cells, as a possible intermediate involved in the removal VGluT1, a glutamate transporter used to assess Ia afferent synaptic health, following a nerve transection cut-repair procedure (Rotterman et al., 2019; Alvarez et al., 2011). The paper also attempts to determine if blocking the Ccl2-Ccr2 mechanism results in restoration of Ia synaptic contacts. 4 groups of 4-6 mice were used in the experiment: a control with no genetic alteration, Ccl2^(flx/flx) group as a genetic control, 〖MN〗^ΔCcl2 experimental group with Ccl2 specifically KO in motoneurons, and 〖MG〗^ΔCcl2 experimental group with Ccl2 specifically KO in microglia. Ccl2-mCherryflox mice used in the experiment allowed for visualization of the presence or absence of Ccl2 via the fluorescent reporter protein mCherry. The fluorescent retrograde enhancer Fast Blue was administered to label motoneurons including their dendritic branches, and immunohistochemistry was performed to label VGluT1. Confocal z-stack images were then used to generate 3D reconstructions utilized in the determination of VGluT1 density following nerve cut and repair. A one-way ANOVA and post-hoc Bonferroni determined significant decreases (p<0.05) in VGluT1 density on the dendrites and somas of Ccl2^(flx/flx) (32.5% and 48.7% respectively) and 〖MN〗^ΔCcl2 (26.7% and 42.0% respectively) compared to control, but 〖MG〗^ΔCcl2 groups only demonstrated a significant decrease in VGluT1 density (37.2%) on the soma. These results are compounded with the analysis that 75.3% ± 3% (±SD) of VGluT1 synapses are located on dendrites. As a result, it was concluded that selective KO of VGluT1 on microglia in the 〖MG〗^ΔCcl2 group recued VGluT1. Although Ccl2 was identified as one possible agent in the degradation pathway of VGluT1 and thus implicated in the synaptic plasticity changes following nerve cut, it remains unclear what agents are involved in the actual removal of the synaptic structures. Future studies can further explore, which specific agents are recruited by Ccl2 signaling as well as functional differences that result despite structural recovery.UndergraduateNeuroscienc
Preliminary Analysis of Northwest Corridor Revenue from General Purpose and Managed Lanes by Household Income Group
No full textThis master’s thesis research presents Georgia Department of Transportation (GDOT) expenses to construct reversible managed lanes along the Northwest Corridor (NWC), takes a first-cut at estimating costs to operate the system and the time savings benefits of the system, and allocates benefits and costs across user groups by household income, using demographic results from a 2022 study. This research consisted of calculating corridor improvement costs and revenue streams that agencies face during the construction of managed lanes, beginning with construction costs (without maintenance). Gas taxes and toll expenditures were also estimated from traffic volumes and fuel consumption modeling. The Amount of gas tax spent for each household income group was then distributed among all vehicles ages to generate how much each income group is spending on gas tax alone each year, using SRTA studies. Annual corridor toll revenues were also estimated using public data. These costs were then allocated to income groups using data from a previous demographic study of corridor users. Payback periods were also analyzed to see how long it would take to completely pay off the corridors, assuming no major increase in vehicle activity, tolls, or average vehicle fuel economy.M.S.Civil Engineering/City and Regional Plannin
Deciphering spatial signaling networks using image-based multiplexed approaches
No full textNon-small cell lung cancer (NSCLC), accounting for 80% to 85% of lung cancer cases includes a subgroup of patients with EGFR mutations who can benefit from EGFR tyrosine kinase inhibitors (TKIs). However, patients can still develop acquired drug resistance due to the activation and crosstalk among signaling pathways. Protein-protein interactions (PPI) significantly regulate signaling pathways and cell phenotyping. Visualizing the dynamics of proteins sheds light on the crosstalk of spatially resolved signaling networks. Current approaches have been limited to bulk-level molecular assays or non-spatial measurements. To overcome these limitations, we first presented an approach called rapid multiplexed immunofluorescence (RapMIF) to explore the signaling proteins involved in the WNT/β-catenin and AKT/mTOR pathways. RapMIF automated iterative staining, bleaching, and imaging, and achieved measuring up to 25-plex spatial protein maps across 33 multiplexed pixel-lever clusters, revealing intricate signaling states, translocation patterns, and subcellular signaling clusters within single cells. Furthermore, we developed a new multiplex image-based assay to detect the PPIs at the subcellular level, termed Intelligent Sequential Proximity Ligation Assay (iseqPLA). iseqPLA enables multiplexed profiling of 47-plex proteins including 22 pairs of proteins involved in the AKT/mTOR, MEK/ERK, and YAP/TEAD pathways NSCLC EGFR mutant cell cultures. The capability of performing iseqPLA on tissues was further validated. The multiplexed single-cell data reconstructs the subcellular distributions of signaling proteins and PPIs under drug perturbations and uncovers the dynamic changes in signaling networks. Integrating RapMIF and iseqPLA data could help predict cell status, providing invaluable insights into the intricate subcellular organization of PPIs toward precision therapy design and signaling discovery.Ph.D.Biomedical Engineerin
Study of toilet seat configuration correlation with transfer stability
No full textThis study investigates the impact of two toilet seat modes, general and preferred, on transfer stability for individuals with mobility disabilities. The main objective is to determine if the preferred mode, tailored to individual needs and preferences, provides better stability compared to the general mode. The research involved simulated toilet transfer trials with participants who can ambulate but have a mobility disability. The Center of Pressure (COP) on the toilet seat was calculated using the force results from four load cell sensors, and an ellipse was generated to bound the movement of the user's COP. Statistical analysis and machine learning techniques were employed to analyze and compare the ellipse areas in the general and preferred mode trials. Descriptive statistics indicated a trend of higher ellipse areas in the preferred mode trials, but the Mann-Whitney U test and Cliff's delta results revealed no statistically significant difference between the ellipse areas for the two modes. This study provides valuable insights into the factors affecting stability during toilet seat usage and transfers, and highlights the potential of machine learning algorithms for enhancing stability and safety for users, especially older adults and individuals with disabilities.UndergraduateComputer Scienc
Longitudinal Trajectories of Early Coordinated Communication in Toddlers with Autism: Predicting Language Outcomes at Age Three
No full textEarly coordinated communication behaviors—such as gestures, gaze, and vocalizations—are known predictors of language development in children with Autism Spectrum Disorder (ASD), yet few studies have examined how these behaviors unfold longitudinally across early development greater than two timepoints and how their trajectories predict later language skills. This study examined whether longitudinal growth trajectories in early coordinated communication, measured through linear, quadratic, and cubic components of Communication Complexity Scale (CCS) scores, and gesture frequency at the first visit predicted language outcomes at age three in toddlers with ASD. Using data from 20 children across at least four time points, I modeled communication growth and assessed language acquisition via the Mullen Scales of Early Learning. Results partially supported the hypotheses. The overall shape of communication trajectories—linear, quadratic, or cubic—was not significantly related to language outcomes. However, the slope of the linear growth component, representing the overall magnitude and direction of communication change, significantly predicted increases in receptive language scores. This relationship held even for children whose communication growth was best characterized by non-linear (quadratic or cubic) patterns, emphasizing that the overall developmental trend, rather than the specific trajectory shape, matters most for language outcomes. Gesture frequency at intake did not predict language outcomes, nor did it moderate the association between linear slope and language acquisition. In exploratory analyses, initial CCS scores significantly predicted both receptive and expressive language levels at age three, highlighting the predictive utility of early coordinated communication measured at a single time point.
These findings highlight the importance of modeling developmental processes in context rather than isolation. Static, single-timepoint measures may obscure important patterns of growth that unfold over time. Despite limitations including small sample size and measurement ceilings, this study underscores the need for dynamic, longitudinal approaches in understanding early communication and informing individualized interventions in ASD.M.S.Psycholog