This study creates and analyzes a model of the Hypothalamus-Pituitary-Adrenal axis to better understand cortisol rhythmicity perpetuated by circadian inputs, system dynamics and feedback inherent within the system. Differential equations are created to model human physiology with cortisol and precursor hormone outputs fit to physiologic data. The model is created with an input of circadian cues from the hypothalamus which are designed to create a more realistic stimulation of the cortisol cascade over predecessors. The study also incorporates additional signaling pathways unique to this model. The project explores the properties of the model under mathematical analysis; then, the simulation of known medical pathologies is used to analyze the model's predictive ability. It is found that incorporating the additional signaling pathway of Arginine Vasopressin increases the model's predictive capability in certain pathological conditions over predecessor models. Additionally, the origination of ultradian rhythm is explored through simulation and two possible explanations are found. First, pulsatile release of Adrenocorticotropic Hormone combined with negative feedback into the system from glucocorticoid receptors elicits the observed ultradian oscillations in humans. Additionally, simulations of increased hypothalamic monitoring and control of cortisol concentrations create a natural oscillation within the desired period. Results from numerical perturbation simulations and dynamic sensitivity analysis are employed to offer justification for known pathological conditions developing from circadian dysregulation. / Master of Science / This study aims to better understand the body's natural cortisol rhythm by creating a mathematical model of the Hypothalamus-Pituitary-Adrenal axis. The model uses differential equations to simulate human physiology and includes circadian cues from the suprachiasmatic nucleus to create a more accurate representation of how cortisol is released in the body. The study also incorporates additional signaling pathways and interactions unique to this model. By analyzing the model and simulating known medical conditions, it was found found that incorporating these additional signaling pathways improved the model's predictive ability in certain situations. Then, numerical simulations were used to investigate how circadian dysregulation can lead to pathological conditions.The study also explored the origin of ultradian rhythm, or short-term fluctuations in cortisol levels, and found two possible explanations. One explanation is the pulsatile release of Adrenocorticotropic Hormone combined with negative feedback from glucocorticoid receptors. Another explanation is increased hypothalamic control of cortisol concentrations. Overall, this study provides insights into the complex dynamics of the Hypothalamus-Pituitary-Adrenal axis and the origination of pathology in the system.
| Identifer | oai:union.ndltd.org:VTETD/oai:vtechworks.lib.vt.edu:10919/114768 |
| Date | 24 April 2023 |
| Creators | Caruso, Peter |
| Contributors | Mathematics, Abaid, Nicole, Childs, Lauren Maressa, Saucedo, Omar |
| Publisher | Virginia Tech |
| Source Sets | Virginia Tech Theses and Dissertation |
| Language | English |
| Detected Language | English |
| Type | Thesis |
| Format | ETD, application/pdf |
| Rights | In Copyright, http://rightsstatements.org/vocab/InC/1.0/ |
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