Due to the COVID-19 outbreak, in-person mental health services became, in many cases, prohibited, increasing the need for telehealth. The present study will investigate clinicians’ perceptions of the effectiveness of delivering cognitive-behavioral therapy (CBT) via telehealth. Telehealth, in this context, refers to remotely delivering psychotherapy via a variety of platforms such as on-line services, video, and/or phone calls. Previous studies found that delivering CBT via telehealth can be as effective as in-person delivery. However, there are barriers to implementing psychotherapy remotely, including lack of training support, organizational and clinician buy-in, and cost. Thus, we aimed to investigate whether clinicians found delivering CBT via telehealth effective, whether it had an impact on engagement and therapeutic relationships, and how well elements of CBT training were provided during telehealth delivery. Data came from a project leveraging a Washington State CBT+ Initiative. Clinicians and supervisors from agencies in WA state participated and got training in CBT for youth depression, anxiety, trauma, and behavioral problems. Clinicians completed pre-and post-training surveys with questions pertaining to how telehealth preparation time compared to in-person sessions, clinicians’ opinions on continued telehealth implementation, clinicians’ ability to deliver effective services via telehealth, and client and caregiver engagement levels over telehealth. We plan to run descriptive analyses to summarize clinicians’ perceptions of telehealth. Preliminary analyses suggest that most clinicians found telehealth to be beneficial and an effective way to deliver CBT to youth. Further, our analyses reveal that clinicians, on average, found engaging younger children in treatment as the most significant barrier associated with telehealth. Harnessing telehealth for the provision of CBTs may be a viable solution that addresses some barriers to access. If telehealth is found effective by clinicians, it could serve as a long-term option for delivering CBTs. Therefore, it is important to understand clinicians’ perspectives.

  My research focuses on ‘tauopathy’—the pathological effects of misfolding of the tau protein—using the fruit fly, Drosophila melanogaster, as a model system. In particular, I am interested in how the expression of tau affects locomotive function. Tau is a protein found in both humans and flies that is associated with stabilizing neuronal microtubules. However, under certain physiological conditions, human tau proteins form neurotoxic aggregates in the brain. This neuronal damage leads to dementia, a hallmark of Alzheimer’s Disease (AD). Aging comes with a multitude of age-related functional deficits, including decline in locomotor function. Some individuals with AD pathology are never diagnosed, however, because the cognitive impairment they experience is not sufficient for a clinical diagnosis of dementia, the most common symptom of AD. Consequently, it is imperative we understand AD as more than dementia. I study the climbing abilities of transgenic tau and control flies through negative geotaxis assays. Negative geotaxis refers to the tendency of flies to move vertically upward when startled. For my project, I am measuring the climbing performance of the flies to see the effects of tau on locomotor function as flies age. I hypothesize that the neurotoxic tau aggregates that form will interfere with neural activity involved in the flies’ motor function, resulting in decreased climbing performance. This research holds an abundance of biomedical implications and a capacity to better the lives of many. By using motor function to flag at-risk individuals early in their lives, they have the opportunity to participate in preclinical AD clinical trials that may prevent them from developing AD pathology later on. It is important that we, as a scientific community, strive to better understand the effects of aging and tauopathies, as it is through this understanding we can provide elderly individuals with care that transforms their quality of life.

Aging is the most prevalent risk factor behind many common diseases such as cancer, cardiovascular disease, and various neurodegenerative diseases. The changes that take place with age are complex and affect most of the human body; age-related changes in gait, in particular, have been found to be associated with the onset of disease. While it is generally understood that there is an effect of aging on walking speed in humans, the mechanisms underlying age-related locomotor impairment have not yet been fully characterized. The focus of my research is using Drosophila melanogaster as a model to investigate such mechanisms. My hypothesis is that D. melanogaster exhibit similar age-related changes in gait as those seen in humans, which includes a decrease in walking velocity and duration, and a significant change in limb coordination over their lifespan. I followed cohorts of D. melanogaster over their lifespans and recorded videos of their walking in an arena. I then used these videos to study factors such as walking velocity and duration by analyzing the trajectories of each fly. In addition, I investigated more in-depth limb coordination of individual flies by analyzing the movement of each individual leg. Previous studies using D. melanogaster have found a significant decrease in climbing behavior with age, but have not looked at gait on a finer scale. Therefore, upon completion of this study, I expect to see a decrease in limb coordination and population walking velocity as the flies age. With the findings from this study, I hope to establish a foundation for how gait changes with age in D. melanogaster and to further use gait analysis to help predict the onset of disease and to distinguish between diseased and healthy flies.

Alzheimer’s Disease (AD) is a neurological disease that causes memory loss and neurodegeneration, and is one of the leading causes of death within the United States. Alzheimer’s is linked to the presence of neurofibrillary tangles within the brain, generated by hyperphosphorylation and aggregation of a protein called tau. However, the specific impact that tau has on biochemical pathways in neurons is largely unknown. My project attempts to fill this gap. I compared samples of wild type fruit flies, Drosophila melanogaster, with a strain which expresses the human tau gene in neurons. Despite the difference in human and fly brains, determining the affected biochemical pathway in flies could suggest similar effects in humans. I am using metabolomics, which quantifies the levels of approximately one hundred metabolites, to try to identify the biochemical pathways that are affected by expression of tau in the neurons. Head and body samples of these two fly strains were frozen at 12 days of age and assayed for a targeted set of metabolites. I analyzed these metabolome data using statistical methods in Python to search for potential differences between wild type and tau flies. Any metabolites found to be different will then be analyzed to see if they tend to represent similar biochemical pathways, allowing us to speculate about the effect of tau on those pathways, both in flies and humans. Future work aims to analyze fly brains and individual neurons, thus mapping the affected metabolic pathways more precisely. Importantly, metabolic pathways are often identical between organisms, allowing us to speculate on the effect tau has on similar pathways within humans, thus this work will inform our understanding of the mechanism of AD in humans.

As scientists collect ever larger volumes of data, methods to deal with these data have evolved as well. One of the fields that has thus emerged is the field of network science. Network science has many applications in biological fields as it allows scientists to connect variables of any type in a quantitative way. This versatility makes network science ideal for studies on comorbidity, or the consistent cooccurrence of various diseases in individuals. By analyzing comorbidities, we gain greater insight into interactions between diseases and systems of the body. This helps us understand how potential risk factors such as age, sex, and genotype affect various disease risks as well as the risk of comorbidity. We applied these methods to data on age of diagnosis for over 300 diseases collected from more than 28,000 owner reported surveys through the Dog Aging Project. We constructed comorbidity networks from these data and analyzed these networks using quantitative network statistics which allowed us to compare nodes both in and between networks. We first constructed undirected networks with the nodes representing various diseases to establish and identify pairs of diseases with significantly higher rates of cooccurrence than expected by chance. Using this network, we assigned directions to edges based on temporal data on the relative ages of diagnoses, which allowed us to identify which diseases are precursors to others. We observed how these networks changed through stratifications based on age, sex, and size to identify disease progression through age. In doing so, we hope that we can identify how age affects comorbidity in dogs, which can help researchers identify and develop therapies for lengthening dog lifespans. This knowledge will also provide insight into the mechanisms behind certain disease connections that were previously unknown.

Cystic fibrosis (CF) is a genetic disorder characterized by chronic lung infections involving various organisms, including the gram-positive pathogen Staphylococcus aureus. Antibiotics, such as trimethoprim-sulfamethoxazole (SMX), play key roles in treating CF infections; these drugs inhibit bacterial growth by disrupting important bacterial metabolic processes. SMX specifically inhibits folate metabolism, causing DNA damage that results in bacterial cell death. However, S. aureus is able to persist in CF pulmonary infections despite treatment with antibiotics, and evidence suggests that S. aureus does so through adaptive mutations. Our goal is to identify the adaptive mutations of S. aureus during SMX exposure in vitro, to understand how this pathogen persists and to prevent the emergence of resistance. We grew S. aureus in the presence of super-inhibitory SMX concentrations for 24 hours in Luria Bertani broth. We sampled the culture at specific timepoints and measured viable bacterial counts on chocolate agar; we evaluated all resulting colonies for SMX susceptibility and associated genetic changes. Surprisingly, we identified mutants that survived SMX treatment carrying diverse adaptive changes not associated with folate metabolism or DNA repair, suggesting previously-unknown lethal effects of SMX against S. aureus. These mutants carried mutations predicted to decrease production of reactive oxygen species (ROS) - toxic compounds produced by all cells during aerobic respiration and in response to stress. Our results indicate ROS may play a role in SMX-mediated S. aureus cell death, suggesting that treatments that augment the effects of ROS could improve antibiotic efficacy. We are now exploring the involvement of ROS in S. aureus killing by SMX using engineered S. aureus strains with knockout and overproducing mutations in ROS detoxification genes. This study will help us better understand SMX’s mechanism of action and S. aureus’ response to this drug, in order to improve the treatment of diverse infections caused by this pathogen.

Arrhythmogenic cardiomyopathy (AC) is a devastating inheritable heart disease characterized by lethal heart rhythms and abnormal contractile function that can lead to sudden cardiac death or congestive heart failure. More than 70% of AC cases are due to mutations in desmosomal proteins, which are essential for maintaining structural integrity and intercellular junctions in the heart. Frameshift mutations in desmoplakin (DSP), a desmosomal protein, are a common cause of AC, therefore my project aims to use human induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs) to model AC due to premature truncating DSP variants and to determine if the mechanism results from haploinsufficiency of DSP protein. From two unrelated patients with AC carrying different pathogenic DSP variants, p.Leu463Serfs*22 and DSP p.Arg941*, we generated patient-specific iPSC-CMs from each patient. With these cells, we created engineered heart tissues (EHTs) and found preliminary data that suggests DSP L463Sfs*22 EHTs generate less active twitch force compared to wild type, indicating that this human iPSC model can recapitulate the salient clinical phenotype. Protein analysis of these cells revealed that patients with premature truncating mutations in desmoplakin have lower desmoplakin levels when compared to wild type cells (DSP L463Sfs*22 iPSC-CMs have 38% less DSP protein levels compared to wild type iPSC-CMs). There was no evidence of the predicted truncated protein to suggest a dominant negative mechanism. Furthermore, we found a significant reduction in DSP transcript in the DSP L463Sfs*22 iPSC-CMs that was partially rescued by knocking down UPF1, a key regulator of the nonsense-mediated decay (NMD) pathway, suggesting a NMD-mediated clearance of DSP transcripts that results in haploinsufficiency. Should we also find that increasing desmoplakin protein rescues the phenotypes observed in patients, there is potential to find a novel treatment option for patients with desmoplakin-associated cardiomyopathy.

Metallic foams have long been sought after for their conductive and structural properties, but have not become widespread due to the extraordinarily difficult processes typically used to produce such materials. Utilizing conventional Fused Filament Fabrication (FFF), also known as Fused Deposition Modeling (FDM), 3D printing equipment and the viscous properties exhibited by the molten filament extruded during printing, we have established that these properties can produce fully customizable metallic foams. The material properties of these foams are configurable to produce varying degrees of density, scale, and geometry via the manipulation of standard printing variables such as print height, print speed, and extrusion speed. Preliminary results with polymeric FFF filaments have successfully produced foams demonstrating significant compressive strength in every direction despite being an open celled geometry with an extremely high surface area to volume ratio. Conversely, polymer foams printed with flexible materials allow us to tailor material properties for energy absorption over structural integrity. This work will establish the minimum and maximum limits of the fabrication process as well as the material properties of metallic foams. To date, our experiments have demonstrated this technique of manufacturing metallic foams is reliable, controllable and scalable with great potential to change the availability and usage of metallic foams, and could significantly impact fields such as structural engineering, automotive, and aerospace where these types of metallic foams are highly sought after.

Despite widespread implementation of solar energy, there are still issues with efficiency in varying conditions. For example, photovoltaic (PV) arrays function optimally at a specific temperature and have decreasing efficiencies at higher temperatures. Other factors that also impact the power production of a PV array include the amount of direct sunlight, the distribution of incident light, and the intensity of incident light. As solar energy installations continue to increase worldwide, proper modeling of PV arrays is critical for potential asset owners and power system operators. Effective simulations of a PV array’s power production require models that effectively consider the uncertain external factors that vary by geographical region and climate. In this research project, a realistic PV cell model is developed in the programming language Python. This model explores the sensitivity of a PV cell’s power production to different external variables, including ambient temperature, solar irradiance, and other weather conditions. Additionally, this PV cell model is extensible, allowing power production from PV modules and arrays to easily be considered. This model can be seamlessly integrated with other energy asset models, including those for energy storage and flexible demand resources, allowing for complex scenarios to be simulated. To display this functionality, a cost-minimizing consumer with a behind-the-meter PV array and battery is simulated.

Alzheimer’s disease, the most common human neurodegenerative disorder, is characterized by hyperphosphorylation of the protein tau, leading to the protein’s aggregation and the formation of neurofibrillary tangles. The subsequent neurodegenerative consequences of these tangles may influence the biological response and sensitivity to neurological stressors, such as a traumatic brain injury (TBI). A TBI usually results from a strong blow to the head that leads to damaged brain cells and neurodegeneration. In the Promislow Lab, we are currently examining how neuronal tau affects the mortality response to a TBI-like trauma in the fruit fly, Drosophila melanogaster. Using the UAS-GAL4 gene expression system, we are able to induce the expression of the tau gene in fly neurons from eclosion. From both an experimental fly genotype (tau expression) and a control fly genotype (no tau expression), we are currently sampling flies at various time points during their lifespan and administering a TBI-like trauma on the flies using a high-impact trauma device. To quantify the impact of tau on the flies’ response to the TBI-like trauma, we are recording the percentage of flies dead 24 hours later (24 hour mortality index). We hypothesized that inflicting a TBI-like trauma would lead to a significantly increased 24-hour mortality index in the experimental genotype compared to the control genotype due to increased sensitivity in the former. Thus far, we have observed significantly increased mortality in response to a TBI-like trauma in the control genotype compared to the experimental genotype. The decreased mortality in the experimental genotype suggests a novel positive role of tau in the response to a TBI, which holds significant implications for targeting clinical TBI treatments and therapies. Further analysis and follow-up experiments will provide useful insight into understanding the mechanisms of tau’s role and the pathways of both Alzheimer’s and TBIs.