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Physical Sciences and Mathematics Commons

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Medicine and Health Sciences

William & Mary

Undergraduate Honors Theses

Publication Year

Articles 1 - 5 of 5

Full-Text Articles in Physical Sciences and Mathematics

Mathematical Modeling And Examination Into Existing And Emerging Parkinson’S Disease Treatments: Levodopa And Ketamine, Gabrielle Riddlemoser May 2024

Mathematical Modeling And Examination Into Existing And Emerging Parkinson’S Disease Treatments: Levodopa And Ketamine, Gabrielle Riddlemoser

Undergraduate Honors Theses

Parkinson’s disease (PD) is the second most common neurodegenerative disease across the world, affecting over 6 million people worldwide. This disorder is characterized by the progressive loss of dopaminergic neurons within the substantia nigra pars compacta (SNpc) due to the aggregation of α-synuclein within the brain. Patients with PD develop motor symptoms such as tremors, bradykinesia, and postural instability, as well as a host of non-motor symptoms such as behavioral changes, sleep difficulties, and fatigue. The reduction of dopamine within the brain is the primary cause of these symptoms. The main form of treatment for PD is levodopa, a precursor …


Process Modeling The Neuroprotective Effects Of A Plant-Based Diet On Parkinson's Disease, Julia Mitchell May 2024

Process Modeling The Neuroprotective Effects Of A Plant-Based Diet On Parkinson's Disease, Julia Mitchell

Undergraduate Honors Theses

Parkinson's disease (PD) is a progressive neurodegenerative disorder characterized by motor symptoms such as tremors, bradykinesia, rigidity, and postural instability. Recent research suggests an avenue for potential neuroprotection through dietary intervention, specifically the adoption of a plant-based diet. A plant-based diet predominantly comprises foods derived from plants, emphasizing fruits, vegetables, grains, legumes, and nuts while minimizing or excluding animal products. This thesis aims to explore the biochemical pathways implicated in PD progression and the potential impact of dietary choices on these pathways. The investigation focuses on several key pathways: alpha-synuclein aggregation, the blood-brain barrier crossing of levodopa, oxidative stress, ferroptosis, …


The Pandemic From Above: Estimating Covid-19 Cases Using Deep Learning And Satellite Imagery, John Hennin Apr 2022

The Pandemic From Above: Estimating Covid-19 Cases Using Deep Learning And Satellite Imagery, John Hennin

Undergraduate Honors Theses

Monitoring the spread of an outbreak of disease (such as COVID-19) is an important component of any coordinated pandemic response. Across the globe, our ability to conduct such monitoring - especially at early stages of the COVID- 19 pandemic - was highly limited due to a lack of public reporting mechanisms. Today, the process of case data collection remains expensive and, in some regions, is subject to political considerations. Researchers have turned to some techniques leveraging Google Trends and Twitter data to overcome limitations in public data sources. Here, we provide another approach which leverages satellite information to provide estimates …


Machine Learning In Healthcare: Improving The Diagnosis Of Pulmonary Embolism In Covid-19 Patients, Soheb Osmani Apr 2022

Machine Learning In Healthcare: Improving The Diagnosis Of Pulmonary Embolism In Covid-19 Patients, Soheb Osmani

Undergraduate Honors Theses

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has created new challenges for clinicians diagnosing pulmonary embolism (PE). Clinicians currently rely on D-Dimer levels in conjunction with clinical prediction scores to rule out and diagnose PE. However, patients with COVID-19 (the disease caused by SARS-CoV-2) often present with elevated D-Dimer levels. D-Dimer levels in COVID-19 patients have been found to be positively correlated with the severity of disease. Symptoms of COVID-19 also often align with symptoms of PE. Therefore, it becomes more difficult for clinicians to identify which COVID-19 positive patients should undergo further testing for PE. This study evaluates …


Developing Iron Complexes For Electrocatalytic Hydrogen Generation, Benjamin Travis Dec 2021

Developing Iron Complexes For Electrocatalytic Hydrogen Generation, Benjamin Travis

Undergraduate Honors Theses

Artificial photosynthesis systems convert solar energy into chemical fuels such as hydrogen gas. Photocatalytic hydrogen generation systems have previously been developed, but reliance on expensive metal catalysts limits the viability of these systems. In order for artificial photosynthesis to be used as a large-scale clean energy solution, it is crucial to discover more active and cost-efficient catalysts.

To this end, several novel iron polypyridyl complexes were synthesized using relatively inexpensive reactants. Electrochemical testing revealed that these complexes are active electrocatalysts for the reduction of protons to generate hydrogen gas. Furthermore, a naphthalene-terminated iron polypyridyl complex was found to be an …