Sivakumar, Sruthi
(2023)
Information Theory to Understand the Molecular (Dis)order that Accompanies Skeletal Muscle Aging.
Doctoral Dissertation, University of Pittsburgh.
(Unpublished)
This is the latest version of this item.
![[img]](https://d-scholarship.pitt.edu/style/images/fileicons/application_pdf.png) |
PDF (Sruthi PhD Dissertation)
Primary Text
Restricted to University of Pittsburgh users only until 19 January 2025.
Download (4MB)
| Request a Copy
|
Abstract
Life represents a perpetual contest between two opposing forces, namely, constructive biological forces and destructive physical forces. Biology creates order from chaos; physics creates chaos from order. Through biomolecular interactions, cells perform orchestrated functions such as creating life-sustaining energy, executing specialized tasks, and propagating population succession through self-replication. Yet, these functions are not without consequences and, over time, biomolecules within the cells dissipate energy, make mistakes, and accumulate waste. Aging—characterized by a progressive loss of physiological integrity that leads to impaired function and increased vulnerability to death—arguably begins at that turning point when destructive physical forces start to dominate over constructive biological forces. This time-dependent accumulation of molecular mistakes leads to ever-increasing chaos (Lipsitz & Goldberger, 1992). A chaotic system is characterized by unpredictable behavior that is highly sensitive to initial conditions but can be explained by deterministic laws. As biomolecules within a given cell communicate with each other to perform complex tasks, ‘wear and tear’ of the system results in increased noise and, thus, an impaired information flow—or entropy.
In 1948, Claude Shannon mathematically described communication of information over a noisy channel (Shannon, 1948). In this now seminal work, Shannon described entropy as a measure of ‘information’ or uncertainty encoded in a message. The greater the uncertainty, the greater the amount of stored information, or entropy. Since Shannon set the stage for the formation of the novel field of Information Theory, its principles have extended into numerous applications, including language, engineering, and medicine. A decade later, prominent bio-gerontologist, Bernard Strehler, suggested that information theory can help understand whether age-related deterioration is due to ‘the disorganization of stored collection of directions (information)’ or ‘the disruption of information transmitting or decoding machinery’ (Blokh & Stambler, 2017).
In this dissertation, we present a series of studies that test the central hypothesis that aging is a result of disordered information at the transcriptomic level, and disruption of the message propagation machinery in individual aging cells. Understanding if and how an aging system preserves certain biological functions may ultimately help researchers develop anti-aging therapeutics that preserve effective biomolecular communication over time.
Share
| Citation/Export: |
|
| Social Networking: |
|
Details
| Item Type: |
University of Pittsburgh ETD
|
| Status: |
Unpublished |
| Creators/Authors: |
|
| ETD Committee: |
|
| Date: |
19 January 2023 |
| Date Type: |
Publication |
| Defense Date: |
12 August 2022 |
| Approval Date: |
19 January 2023 |
| Submission Date: |
9 November 2022 |
| Access Restriction: |
2 year -- Restrict access to University of Pittsburgh for a period of 2 years. |
| Number of Pages: |
156 |
| Institution: |
University of Pittsburgh |
| Schools and Programs: |
Swanson School of Engineering > Bioengineering |
| Degree: |
PhD - Doctor of Philosophy |
| Thesis Type: |
Doctoral Dissertation |
| Refereed: |
Yes |
| Uncontrolled Keywords: |
Aging, Skeletal muscle, information theory |
| Date Deposited: |
19 Jan 2023 19:26 |
| Last Modified: |
19 Jan 2023 19:26 |
| URI: |
http://d-scholarship.pitt.edu/id/eprint/43847 |
Available Versions of this Item
-
Information Theory to Understand the Molecular (Dis)order that Accompanies Skeletal Muscle Aging. (deposited 19 Jan 2023 19:26)
[Currently Displayed]
Metrics
Monthly Views for the past 3 years
Plum Analytics
Actions (login required)
 |
View Item |
![[feed]](/images/feed-icon-32x32.png){kind=icon}