Masters Theses
Keywords and Phrases
Aging; Drosophila; Sleep
Abstract
"Sleep is essential for maintaining a healthy body and mind and is associated with aging and aging related diseases. There are individual differences in fly as well as human sleep behavior and lifespan. Between and within individuals, sleep varies in characteristics including consolidation, rhythmicity, continuity, duration, and more. Various evidence in the literature suggests there are many molecular pathways involved with aging and they may be different for individuals. Our research is interested in a possible restorative mechanism of sleep and the ramifications of that mechanism to aging. We have developed two predictive models of aging using the fruit fly Drosophila. These models allow us predict if a fly will be ‘long-lived’ or ‘short-lived’ based on their first 30 days of sleep data. We hypothesize that sleep characteristics are related to age. Our hypothesis is that poor sleep qualities lead to a shorter lifespan, and conversely good sleep characteristics lead to a longer lifespan. This work describes research done verifying the biological validity of these models. Specifically, we find that the models are able to separate out unique subsets of flies in different aging groups, including one group affected by a disruption in proteostasis"--Abstract, p. iii
Advisor(s)
Thimgan, Matthew S.
Committee Member(s)
Olbricht, Gayla R.
Hou, Chen
Department(s)
Biological Sciences
Degree Name
M.S. in Applied and Environmental Biology
Publisher
Missouri University of Science and Technology
Publication Date
Fall 2021
Pagination
viii, 47 pages
Note about bibliography
Includes bibliographical references (pages 39-46)
Rights
© 2021 Lauren Ashley Francis, All Rights Reserved
Document Type
Thesis - Open Access
File Type
text
Language
English
Thesis Number
T 12216
Recommended Citation
Francis, Lauren, "THE VALIDATION OF PREDICTED BIOLOGICAL AGE OF DROSOPHILA MELANOGASTER FROM COMBINED STATISTICAL MODELING" (2021). Masters Theses. 8127.
https://scholarsmine.mst.edu/masters_theses/8127