Doctor of Philosophy (PhD), Ohio University, 2016, Biological Sciences (Arts and Sciences)

Since its inception, paleoneurology has shown the value of studying brain evolution in extinct taxa, revealing the complex history of neurological change and associated cognitive and behavioral innovation. Brains almost never fossilize, and thus vertebrate paleoneurology relies on the fidelity between the brain and its surrounding endocranial cavity wall, which is reflected on an endocast for study. However, if the brain fails to fill the cavity in life, a resultant endocast may lack clear evidence of brain size and shape. Due to poor brain-filling in life, many non-avian dinosaur endocasts lack clear evidence of brain impressions. Previous quantitative studies of dinosaur brain size corrected for brain-filling discrepancies by reducing endocast volumes by some percentage. However, corrections were often subjective. Additionally, past whole-brain studies masked underlying regional changes that (1) contributed to overall relative brain size change and (2) provided functional information. A new approach, Gross Anatomical Brain Region Approximation (GABRA), permits study of archosaur brain and brain-region size and shape, even when endocasts lack details of the brain itself. GABRA uses anatomical landmarks on virtual endocasts as criteria for delimiting underlying brain regions. GABRA criteria are validated osteological correlates of endocranial soft tissues (e.g., cranial nerves, blood vessels) that provide consistent topological information for brain regions. Following GABRA assessment of the endocast, brain regions are modeled within it, providing volumetric estimates, which, when summed, offer a whole-brain estimate. Such data from several dinosaurs here permit analyses using modern comparative methods of relative brain-size evolution (e.g., encephalization quotient). Additionally, analyses of GABRA data show a mix of concerted and mosaic patterns of brain evolution, wherein the pituitary and olfactory bulbs emerge as evolving independently from the rest of the bra (open full item for complete abstract)

Doctor of Philosophy, Case Western Reserve University, 2024, Biomedical Engineering

Intracortical microelectrodes (IMEs) are a type of brain-computer interface that allows for the recording of neural signals to communicate between the brain and computers. IMEs can be used to restore motor function in people with spinal cord injury, treatment of neurological disorders, and are a strong basic science tool for understanding the brain. Unfortunately, implanted IMEs consistently see a steady decline in recording ability over time, leading to failure of the device. Damage to the blood-brain barrier (BBB) from IME implantation is a key contributor to device failure. After BBB breach, neurotoxic molecules invade the brain and cause a downstream cascade of neuroinflammation and oxidative stress that further damages the BBB, brain tissue, and the IME itself. Attempts to minimize BBB damage to improve neuroinflammation and IME longevity have shown limited success. Given the lack of solutions to the chronic stability of neural recordings, further investigation into understanding and minimizing the effects of BBB damage is warranted. In my dissertation, I investigate multiple strategies to mitigate and expand our understanding of how BBB damage can impact IME performance. Thermal damage to underlying vasculature because of cranial drilling has been shown to impact BBB permeability. To combat this, I developed a standardized surgical approach to limit surgeon variability and reduce thermal damage on the BBB. Next, I utilized the antioxidant dimethyl fumarate to promote BBB healing and reduce oxidative stress, resulting in acute improvements to IME function without long-term stability. Lastly, I investigated what unknown molecules enter the brain through the permeable BBB and contribute to neuroinflammation. I was the first to discover that gut-derived bacteria invade the site of implantation through the damaged BBB, which can be modulated with antibiotics to alter neuroinflammation and IME performance. New therapeutics can be developed utilizing this connecti (open full item for complete abstract)

Doctor of Philosophy, The Ohio State University, 2022, Mechanical Engineering

Motor vehicle crashes are a leading cause of bleeding head injury, especially in the elderly population. Acute subdural hematomas (ASDH) are particularly lethal. The increased frequency of ASDH with age has been attributed to the rupture of bridging veins, necessitating a better understanding of the relationship between rotational kinematics and bridging vein failure. As bridging veins run from the surface of the cortex through the meninges and into the dural sinuses, any relative motion between the brain and the skull may result in the shearing of the bridging veins, resulting in ASDH. The increased atrophy in the elderly population compared to their younger counterparts results in an initial strain on the bridging veins, suggesting one of the reasons why the elderly population is more susceptible to ASDH from bridging vein failure. Previous studies have quantified whole brain motion under a variety of dynamic loading conditions. Further, finite element (FE) models of the brain have been utilized to supplement the investigation of the brain's susceptibility to injury; however, the experimental brain data currently used to validate these models are lacking surface-level validation data. The objective of this dissertation is to provide experimental brain displacement data at the surface of the brain to contribute to further validation of FE models and aid in the investigation of the relationship between head kinematics and brain displacement that could result in an ASDH in the elderly. Surface-level brain displacements were quantified in this dissertation work using high-frequency, Brightness-mode (B-mode) ultrasound due to its advantages of noninvasiveness and high resolution. However, the use of ultrasound to quantify displacement while the probe is rotating under high rates has not yet been validated. As an initial objective of this dissertation work, the ultrasound was validated under the same conditions that it was utilized for quantifying brain displace (open full item for complete abstract)

Doctor of Philosophy, University of Akron, 2020, Biomedical Engineering

Chiari malformation type I (CMI) is a neurological disorder that is typically diagnosed by a descent of the cerebellar tonsils greater than 5 mm below the foramen magnum. Even though the descent of the cerebellar tonsils has been used as radiological evidence of CMI, recent studies have shown that the degree of tonsillar descent is limited in identifying subjects with symptomatic CMI. Moreover, studies have shown that the cerebellar tonsillar position is poorly related to symptom severity. The main goal of this research was to identify brain or skull-based parameters that may be specific to CMI subjects. The second and third chapters of this research investigated two and three-dimensional brain morphometrics in subjects with CMI and healthy controls, respectively. Brain and skull-based structures evaluated include—the clivus, posterior cranial fossa, anterior and posterior cerebrospinal fluid spaces. Clivus bone volume was shown to be reduced by 31% on average in CMI subjects when compared to healthy controls. Additionally, the clivus length was found to be 3.7 mm shorter in CMI subjects compared to healthy controls. These findings revealed that morphometric properties of the clivus discriminate between subjects with CMI and healthy controls, and thus, serve as an additional distinctive criterion unique to CMI pathophysiology. The third and fourth chapters of this research focused on the deformation of the brain. Cardiac-induced brain tissue displacement and principal strain were quantified using an MRI methodology called displacement encoding with stimulated echoes (DENSE). Prior to quantifying brain tissue deformation, the accuracy of DENSE MRI was determined using a tissue motion phantom with displacements representative of those observed for in-vivo brain tissue. Displacement and strain were identified in eight different brain regions—the brainstem, cerebellum, cingulate gyrus, corpus callosum, frontal lobe, occipital lobe, parietal lobe, and the sella tur (open full item for complete abstract)

Doctor of Philosophy (PhD), Wright State University, 2019, Computer Engineering

Human brain analysis and understanding pose several challenges due to the great complexity of the structural organization and the functional connectivity that characterizes the human brain. The ability of the brain to adapt in dynamic changes over time such as normal aging, neurodegenerative diseases or congenital brain malformations renders the brain's exploration a particularly demanding and difficult task. In recent years, advances in brain imaging modalities and lately the multimodal fusion, combined with improvements in related technologies have greatly assisted the development of brain maps by providing insights regarding the overall brain structure and functionality. Even though the existence of sensory and motor maps for the human brain is known to some degree, the formation process is still subject to research. Electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) are the two mostly used non-invasive brain imaging modalities that can track the changes in brain activity. Due to their complementary nature, high temporal resolution from EEG and high spatial resolution from fMRI, the fusion of simultaneous acquired EEG and fMRI recordings aims to provide complementary information about the brain functionality. In an effort to extend the current research in the field of brain understanding, a novel Brain Mapping Model (BMM) based on EEG and fMRI is proposed within this Ph.D. dissertation. The proposed BMM is based on the synergy of state-of-the-art computational techniques to associate the brain regional activities provided by the EEG-fMRI fusion. In more details, first, a novel formal model for the EEG signals' representation is proposed. The proposed formal model enables the analysis and extraction of structural EEG features. The proposed method is based on the Syntactic Aggregate approXimation (SAX) algorithm, that in this work is improved by the Local-Global (LG) graph technique, to compose a Context Free-Grammar (CFG). Moreover (open full item for complete abstract)

Master of Science, The Ohio State University, 2016, Public Health

Spatial patterns of gene expression in brain tissue have been observed in both human and more thoroughly in mouse. Because of the increased complexity and data availability, these spatial gene expression patterns in human have not been biologically explained in the same way that they have in murine models. In mice they can be explained by the spatial distribution of cell types. Using this insight, we address the human biology behind these spatial transcription changes by informing the human model with a-priori mouse transcriptional profiles. We apply clustered single cell RNA sequencing (scRNA-Seq) derived expression profiles across transcriptomics platforms to show: i) ordinary least squares regression can accurately predict the cell types within a tissue sample (validated through biomarkers and training/test data), ii) the distribution of cell types in the human brain vary between different locations in the brain, and iii) the distribution of human and mouse neural densities correlate between human and mouse. We developed a methodology to deconvolute cell types within heterogeneous tissue samples that can be applied to disparate data and achieve meaningful results. We then map these results to the large Allen Brain microarray database to evaluate changes in tissue between brain location.

Bachelor of Arts, Wittenberg University, 2010, Music

The aim of this study was to detect, using electroencephalography, whether or not individuals respond differently to modalities within Western tonal music. Specifically I investigated whether or not hemispheric dominance had any effect on the participants' responses to specific musical selections, and if men and women respond differently. Electroencephalography records neurons firing throughout the brain and picks up this electrical activity on the scalp. In this experiment two electrodes were placed behind the subject's ears, two on the subject's forehead, one on the scalp, and a ground electrode on the forearm. The results indicated that there was no effect of music on a particular hemisphere or brainwaves, although right-brained females and left-brained males showed the greatest response to all types of music.

Doctor of Philosophy, The Ohio State University, 2007, Psychology

The dimensions of post-concussive symptoms (PCS) associated with pediatric mild traumatic head injuries (mild TBI) were examined in a prospective, longitudinal study of 186 8- to 15-year-old children with MHI and a comparison group of 99 children with orthopedic injuries (OI). Parents and children completed a 50-item questionnaire within 2 weeks of injury and again at 3 months post injury, rating the frequency of PCS on a 4-point scale. Common factor analysis with target rotation was used to rotate the ratings to four hypothesized dimensions, representing cognitive, somatic, emotional, and behavioral symptoms. The rotated factor matrix for baseline parent ratings was consistent with the target matrix. The rotated matrix for baseline child ratings was consistent with the target matrix for cognitive and somatic symptoms but not for emotional and behavioral symptoms. The rotated matrices for ratings obtained 3 months post injury were largely consistent with the target matrix derived from analyses of baseline ratings, except that parent ratings of behavioral symptoms did not cluster as before. Additional exploratory analyses comparing younger children to older children revealed similar results to the total group for both child-rated and parent-rated symptoms. Injury group exploratory analyses suggested that child- and parent-rated symptom dimensions may be different for the OI group than the mild TBI group. Parent and child ratings of PCS yield consistent factors reflecting cognitive and somatic symptom dimensions, but dimensions of emotional and behavioral symptoms are less robust across time and raters.

Master of Science, The Ohio State University, 2025, Psychology

Introduction: Brain-age difference has been suggested as a biomarker of healthy aging and a method of capturing brain state (see also, relative brain age (RBA), brain-predicted age difference (brainPAD), brain age gap estimate (brainAGE), etc.). Associations have been found between brain-age differences and lifestyle variables (e.g., body mass index (BMI) and smoking status), and between measures of brain-age difference and cognition in cognitively impaired populations. However, few studies have identified relationships between brain-age differences and age-related outcomes, such as cognition, in healthy adults. Methods used to calculate brain-age differences have proliferated; many studies suggest brain-age difference methods that vary in prediction model, input features, and training population. It therefore remains unclear whether brain-age differences have utility in healthy adults and whether this utility varies with the method of brain-age difference calculation. Methods: In the current study, three brain-age difference methods (Elastic Net regression, 3D Convolutional Neural Network, and Random Forest regression), each using measures of structural brain state based on T1-MPRAGE images, were compared. The Elastic Net regression and 3D Convolutional Neural Network models have been trained in independent studies on separate datasets using gray matter density (Elastic Net; n = 1,359, mean age (SD) = 40.04 (17.78) years) and voxel-wise and surface-based volume (3D Convolutional Neural Network; n = 5,851, mean age (SD) = 56.74 (16.88) years) and used to assess cognition. Random Forest regression, on the other hand, was trained for the current study on structural morphometry, including volume, thickness, and surface area, from the Human Connectome Project-Aging sample (n = 660, mean age (SD) = 59.04 (14.63) years). Each of these trained models were used to compute brain-age differences from a single, independent sample of healthy adults aged 36-87 years old (n = (open full item for complete abstract)

Doctor of Philosophy, Case Western Reserve University, 0, Biomedical Engineering

Brain-computer interfaces (BCIs) bridge the gap between dysfunctional central nervous system circuitry and prosthetic devices for individuals with somatic function loss. Intracortical microelectrodes (IMEs) record action potentials and transmit signals through BCI systems to enable external device functionality for neurorehabilitation. Although neural interfaces address the clinical need for restoring neurological function, IMEs face significant biological challenges. The initial rupturing of the blood-brain barrier (BBB) and chronic neuroinflammatory response can lead to IME failure. One strategy to mitigate biological response involves using anti-inflammatory drugs like dexamethasone (DEX), which suppress pro-inflammatory genes. However, systemically administered pharmaceuticals lack targeting functionality, limiting their therapeutic potential. This dissertation explores improving IME longevity by mitigating neuroinflammation and resealing the BBB through the use of a drug-loaded bio-inspired nanoparticle. Our approach employs synthetic platelet-inspired nanoparticles (SPINs) designed to leverage platelet physiology for vascular wound healing. Using IHC, we evaluated SPINs' ability to target IME sites, reduce BBB permeability, and decrease the presence of activated glial cells. Within the next chapter, we conducted the first omics analysis of SPINs as a drug delivery vehicle for DEX to target chronic inflammation at IME sites. This analysis revealed that encapsulating DEX alters its biodistribution, providing insights not observed with IHC. Multiple doses of DEX-loaded SPINs (SPIN-DEX) demonstrated potential to extend IME longevity by modulating gene expression to reduce neuroinflammation and promote BBB healing. Nanoparticle-based therapies enable adaptable dosing that can be informed by transcriptomic data, offering a promising solution for enhancing IME performance. By addressing chronic inflammation and BBB repair, SPIN-DEX provides a comprehensive approach t (open full item for complete abstract)

Doctor of Philosophy, The Ohio State University, 2024, Neuroscience Graduate Studies Program

Patients with breast cancer experience debilitating behavioral side effects and exhibit elevated concentrations of circulating inflammatory mediators, even prior to treatment. Inflammation is a proposed mechanism underlying the etiology of cognitive and mood disturbances and thus may be contributing to tumor-induced behavioral side effects. Preclinical rodent models likewise display impairments in learning/memory and anxiety- and depressive-like behaviors. In addition to tumor-induced elevations of circulating inflammatory mediators, tumor-bearing rodent models display neuroinflammation in brain regions important in regulating behavior. However, the cellular and molecular mechanisms by which tumor-induced behavioral side effects occur remain unknown. Estrogen is not only implicated in the etiology of breast cancer, but also in regulating inflammation and behavior; therefore, estrogen signaling may mediate the relationships between tumor-induced neuroinflammation and behavioral side effects. Here, I examine the extent to which 1. estrogen modulates tumor-induced neuroinflammatory and behavioral outcomes and 2. different cells in the brain (i.e., microglia and endothelial cells) contribute to the observed tumor-induced neuroinflammatory phenotype using orthotopic and syngeneic mammary tumors in female mice. In Chapter 2, I demonstrate that ovarian status modulates tumor-induced endocrine and neuroinflammatory outcomes. Most notably, I show that a mammary tumor in ovary-intact mice reduces circulating estradiol and alters estrogen-related signaling in the brain. Further, tumors in ovariectomized mice increase circulating estradiol and modestly exacerbate tumor-induced peripheral and central inflammation. Next, in Chapter 3 I demonstrate that brain-specific estradiol supplementation attenuates tumor-induced fatigue in group-housed mice, but not singly housed mice; the attenuation of tumor-induced fatigue in group-housed mice is not mediated by neuroinflammatory mediato (open full item for complete abstract)

Doctor of Philosophy, Case Western Reserve University, 2023, Biomedical Engineering

Functional electrical stimulation (FES) of arm and hand muscles combined with decoded motor intentions from intracortical recordings can restore reaching ability to individuals with spinal cord injury. This research aims to improve FES generated arm movements by incorporating real-time modulation of limb stiffness in addition to limb kinematics. During normal arm movements people actively adjust the amount of cocontraction, or the degree to which opposing muscles are simultaneously active. Increasing cocontraction stiffens our limbs making them more resistant to external perturbations while decreasing cocontraction minimizes energy use and facilitates rapid movement. Optimizing the degree of cocontraction is particularly important for FES because excess cocontraction can lead to muscle fatigue and faster battery drain. Conversely, too little cocontraction can lead to poorly controlled movements that are prone to perturbations from the environment. First, we incorporated automated stiffness modulation into FES systems using a virtual arm model. After running many simulations, we found the optimal control method to automatically modulate limb stiffness based on the intended limb velocity command. Next, we built upon that method by addressing two key practical issues: 1) balancing stimulation across multiple redundant muscles, and 2) optimizing stimulation of biarticular muscles. With these advances, we demonstrate how to generate an upper limb FES control algorithm that is clinically practical to implement and allows one to control limb stiffness in addition to kinematics. Finally, with the goal of finding a neurally encoded volitional stiffness signal, we trained macaques with intracortical microelectrodes to perform an EMG controlled cursor task in which independent activation of antagonist muscles controlled one dimension and a separate dimension of movement was controlled by the cocontraction of the same muscles. Results revealed some neural signal (open full item for complete abstract)

Doctor of Philosophy, The Ohio State University, 0, Speech and Hearing Science

Due in part to its complex nature, there is still much to uncover in the investigation of the neural processes that contribute to synchronization between speakers and listeners during communication in the context of social cognition, specifically between native and nonnative English speakers and listeners. This study used a novel method of hyperscan analysis and aimed to explore the effects of listening effort (LE) on brain-to-brain synchrony during communication, which is affected by various factors such as the listening environment, speech quality, hearing abilities, and linguistic complexity. The study analyzed brain-to-brain synchronization (B-bsync) patterns between speakers and listeners in situations where there is poor speech quality (accented English) or linguistic complexity (bilingual speakers) and its relationship to the corresponding number of hesitations/filler words in story recall of the listener. The study used a mixed-methods approach to investigate the impact of LE on brain-to-brain synchronization during communication in less-than-ideal conditions. The study found that there was significant synchronization between speakers and listeners in the native English to native English condition, with peak synchronization occurring at 0.5 and 1 second time shift, followed by a second peak at 5 seconds. In the native English speaker to nonnative English listener condition, significant speaker-to-listener coupling was observed at a time shift of 6 seconds, with listeners lagging the speaker. The synchronized brain regions were similar to those observed in the native speaker to native listener condition, but with two differences: there was no synchronization in the frontal eye fields, and there was synchronization in the left inferior frontal gyrus (LIFG), which is involved in syntactic processing. Results also showed that non-native accented speech required more cognitive resources for processing in bilinguals than in monolinguals, as evidenced by increased (open full item for complete abstract)

DNP, Otterbein University, 0, Nursing

Organ donation is a gift of life for both donors and recipients that can come from living donors, donors after cardiac death, or brain-dead donors (BDDs). Treating the donors with optimal care throughout the entire donation process is crucial due to organ supply shortages. Organs from BDDs are a large contributor to the number of organs donated each year and require critical care from the time of admission, declaration of brain death, and throughout the organ procurement surgery. Although each BDD requires meticulous care for successful retrieval and donation, there is a lack of evidence-based practice (EBP) guidelines for anesthesia for BDDs during organ procurement surgery. This project encompasses the development, implementation, and evaluation plan of EBP anesthesia guidelines for BDDs. The problem was identified through an introduction to and background information regarding the organ donation process, from the declaration of brain death to organ procurement surgery, organ rejection, financial impact, and the significance of the problem to anesthesia. Next, a clinical person, intervention, comparison, outcomes, and time (PICOT) question was introduced which drove the objectives of the project and facilitated a thorough literature review. With the results from the literature search and recommendations from the Lifeline of Ohio Organ Procurement Agency (LOOP), guidelines for anesthesia for BDDs were created. The Johns Hopkins Nursing Evidence-Based Practice (JHNEBP) Model was used to guide the development of and plan to implement the EBP anesthesia guidelines. Monitoring of outcomes will be completed by the QI department. Barriers, limitations, guideline improvement strategies, project timeline, and project budget are discussed, followed by a dissemination of the findings.

Doctor of Philosophy, The Ohio State University, 2023, Biomedical Sciences

Gene therapy refers to the use of genetic material to treat disease through gene addition, gene correction/alteration, or gene knockdown. The goal of the technique is to address the root causes of disease rather than symptoms alone. Gene therapy holds promise for treating a wide range of diseases, including many genetic disorders and certain types of cancer. Gene therapy was first conceptualized in the 1970s and 1980s following advances in our knowledge of genetic material. The first clinical trials were rightly met with skepticism due to lack of concern for patient safety and regulatory bodies. Ultimately, the first attempts came too soon and resulted in various adverse events and widely publicized patient deaths. The field slowed in the 1990s and early 2000s as we began to understand the basic science of gene therapy vectors and expand a so-called “toolkit” of vectors to increase safety and efficacy. Subsequent clinical trials proved more promising and resulted in the approval of the first gene therapies. Currently, gene therapy remains a clinical reality, though more work is needed to expand the number of therapeutics and indications. Adeno-associated viral (AAV) vectors are one tool within the gene therapy toolkit. AAVs are thought to be relatively safe for gene transfer due to their largely non-integrative nature and tendency to trigger mild immunogenic responses. Certain challenges remain in the field to maximize the utility of AAVs as vectors, including the need for cell-specific targeting, appropriate levels of the therapeutic construct, and the ability to evade immunogenic responses. The development of recombinant AAVs (rAAVs) through engineering of the transgene cassette and viral capsid can address many of these concerns, as both can dictate cellular transduction, transgene expression levels, and immune responses. Other areas of optimization include the use of different administration routes and dosing schedules. The combination of all the above will be (open full item for complete abstract)

PhD, University of Cincinnati, 2022, Engineering and Applied Science: Electrical Engineering

Accurate functional mapping with intracranial electrodes is essential for preserving cognitive function during resective neurosurgery. However, conventional mapping techniques still frequently result in postoperative cognitive deficits. This research presents novel signal and neuroimage processing methods for 3D localization of electrodes and functional mapping of a visual naming task using stereotactic EEG recordings. These methods were found to outperform state-of-the-art general purpose time series classifiers and conventional clinical techniques. Insights gained from this work were then extended to propose a data-driven spatiotemporal cognitive model of visual naming.

Doctor of Philosophy, Case Western Reserve University, 0, Molecular Medicine

Novel therapeutic regimens which spur the endogenous immune system to kill cancer cells, such as stereotactic radiosurgery (SRS) and immune checkpoint inhibition (ICI), are heterogeneously effective. Understanding causal factors of response is vital to guide risk assessment and treatment decisions. In this thesis, I evaluate the ability of three methods to prognosticate survival for brain metastases patients following SRS and ICI treatment. These include the clinically utilized response assessment in neuro-oncology for brain metastases (RANO-BM) protocol, as well as investigational computational methods such as radiomic feature analysis and convolutional neural network (CNN) image analysis. I find that easing the 10mm RANO-BM diameter threshold for measurable disease allows new lesions to be discovered as proof of progression in ICI-treated metastases. Further, I find that the trajectory of RANO-BM diameter can be more instructive for risk prediction than the ratio-change and that neither volume nor number of metastases, nor RANO-BM diameter can significantly predict survival until a year after treatment. Reproducing common radiomic methodology flaws observed in the published literature, I demonstrate that inconsistent partitioning, or the improper division of radiomic feature data into Training, Validation, Test, and External test sets, can provide a 1.4x performance boost to reported accuracy (AUROC) for predictive models. Additionally, I highlight how spurious correlations with biological variables can overstate the importance of radiomic features. Leveraging the conclusions from my radiomic reproduction study, I assess the ability of radiomic features and convolutional neural networks (CNNs) to predict overall survival in the largest ICI-treated brain metastases cohort assembled to date, comprising 175 patients from three institutions in two countries. I find that neither radiomic features nor any architecture of the survival AI model MetsSurv is capable of p (open full item for complete abstract)

Master of Arts in Speech Pathology and Audiology, Cleveland State University, 2022, College of Sciences and Health Professions

The purpose of this study was to identify whether public and private colleges or universities across the United States have procedures to assist student veterans who are facing academic challenges secondary to traumatic brain injury (TBI) or acquired brain injury (ABI). This study aimed to identify whether personnel in college and university veterans services offices, offices of disability services, academic success offices, tutoring centers, or other offices that support student veterans academically are aware of the role of speech-language pathologists in providing treatment to manage the effects of TBI/ABI on academic performance, along with the locations for speech-language pathology services to which their office refers student veterans, and whether their college or university has an on-campus speech-language pathology clinic. Further, this study identified whether such awareness differs based on public or private college or university status, college or university enrollment size, the type of office whose personnel responds to this survey, the employment status of the personnel who respond to this survey, and the region of the United States where the college or university is located. Results indicated that, as a whole, most public and private college or university personnel do not have awareness of the role of speech-language pathologists, do not have procedures for referrals, and are unaware of whether or not there is an existing university speech and hearing clinic. If referrals are made, most are to Veteran Affairs (VA) hospitals or facilities. The implications of these results suggest there is a need to boost awareness among campus personnel of the role of speech-language pathologists in treatment to manage the effects of TBI/ABI on academic performance, and to develop campus-wide procedures to refer veterans to on-campus speech and hearing clinics in order to promote accessibility and decrease the complexity of the referral process.

Doctor of Philosophy (PhD), Ohio University, 2022, Biological Sciences (Arts and Sciences)

The mammalian vasculature caters to tissue specific gaseous exchange and metabolic needs. The brain accounts for the largest consumption of oxygen and glucose, for which a structurally organized and functional cerebrovasculature is essential. Brain arteriovenous malformations (BAVM) are characterized by abnormally enlarged blood vessels, which direct blood through arteriovenous (AV) shunts, bypassing the normal artery-capillary-vein network. High-pressure, low-resistance AV shunts disrupt healthy blood flow and can result in cerebrovascular hemorrhage. BAVM is the leading cause of intracerebral hemorrhage in children, and accounts for 50% of stroke incidences in children and young adults. Clinically, BAVM treatments are invasive and not applicable to all cases; thus, there is critical need to understand BAVM mechanisms and develop targeted therapeutics. Using a mouse model of BAVM, that is deficient in Notch effector Rbpj from endothelial cells, from birth – we show that isolated Rbpj-deficient (RbpjiΔEC) brain endothelial cells (BECs) elicit altered whole-genome transcriptomic profile, early at Postanal day (P)7 when expansion of AV diameters – the most prominent BAVM phenotype is not observed, suggesting contribution of Rbpj regulated effector molecules in triggering onset of BAVM pathogenesis. Cellular studies over the course of characterized developmental time-periods at P7, P10, and P14 revealed that AV expansion in RbpjiΔEC mice do not originate from hyperplastic or hypertrophic mechanisms; but RbpjiΔEC BECs acquired atypical morphology and increased BEC density along AV shunts, as compared to controls, in postnatal mice. RbpjiΔEC mice also showed reduced regression of BECs over AV connections when studied through empty basement membrane collagen sleeve (EBMS) dynamics, suggesting lack of remodeling and accumulation of BECs over capillary like vessels in vivo. Using isolated postnatal mouse BECs, we found altered small GTPase activity in (open full item for complete abstract)

Master of Science in Biomedical Sciences (MSBS), University of Toledo, 2022, Biomedical Sciences (Bioinformatics and Proteomics/Genomics)

Temporal Lobe Epilepsy (TLE) is one of the most common neurological disorders and is characterized by recurrent and spontaneous seizures. Although TLE genetic and electrophysiological markers such as gamma oscillations are well characterized, alterations in the interactions between neurons predisposing a cortical region to seizures are not fully understood. To study these non-linear interactions, we incorporated RNA expression changes into a microcircuit computer model of the hippocampus, an area strongly implicated in TLE. Cellular deconvolution of bulk RNAseq data with single-cell transcriptomic data from the hippocampi of pilocarpine-induced temporal lobe epilepsy mice revealed three distinct cell clusters characterized as pyramidal (PYR) cells, oriens-lacunosum moleculare (OLM) interneurons, and parvalbumin-positive (PV) interneurons. We used the differential expression (log fold change) of genes coding for the Alpha-Amino-3-Hydroxy-5-Methyl-4-Isoxazole Propionic Acid (AMPA), N-methyl-D-aspartate (NMDA), and Gamma-aminobutyric acid type A (GABAA) receptor subunits in the control and epileptic conditions for each cell cluster to guide scaling of receptor density iv in the model. The model was composed of 800 PYR, 200 PV and 200 OLM neurons. PYR cells of the model activate PV, OLM, and other pyramidal cells via NMDA and AMPA receptors; in return, the PV and OLM interneurons inhibit PYR cells by acting on their GABAA receptors. Guided by the RNA expression data, we ran simulations where we increased the density of PYR AMPAR, OLM NMDAR, PV AMPAR, and PV GABAAR scaling. PYR GABAAR subunits were both upregulated and downregulated and thus, both changes were implemented when running simulations. Our simulations showed two dynamical changes with the RNA sequence changes. The first is the expected increased seizure susceptibility, reflected as increased gamma power. That pattern took place with pyramidal AMPAR/GABAAR upscaling. The second pattern was a surprising reduc (open full item for complete abstract)