Overview

My PhD research, advised by Dr. Veronica Ciocanel, focuses on multi-scale modeling of microtubule polarity regulation mechanisms that support healthy neuronal function and regeneration following injury. I work with a variety of models including agent-based models, Markov Chains models, and partial differential equations to describe known intracellular dynamics and investigate mechanisms hypothesized to support neuronal regeneration. Beyond my dissertation, I have pursued additional research including interdisciplinary collaborations with clinicians and internships in Quantitative Systems Pharmacology at Pfizer and Simulations Plus, where I applied physiologically based models to drug development questions. 

Papers

3. Nucleation feedback can drive establishment and maintenance of biased microtubule polarity in neurites,
     Hannah G. Scanlon , Gibarni Mahata, Anna C. Nelson, Scott A. McKinely, Melissa M. Rolls, Maria-Veronica Ciocanel
    Mathematical Biosciences (2025). 389.

The microtubule cytoskeleton is comprised of dynamic, polarized filaments that facilitate transport within the cell. Polarized microtubule arrays are key to facilitating cargo transport in long cells such as neurons. Microtubules also undergo dynamic instability, where the plus and minus ends of the filaments switch between growth and shrinking phases, leading to frequent microtubule turnover. Although microtubules often completely disassemble and new filaments nucleate, microtubule arrays have been observed to both maintain their biased orientation throughout the cell lifetime and to rearrange their polarity as an adaptive response to injury. Motivated by cytoskeleton organization in neurites, we propose a spatially-explicit stochastic model of microtubule arrays and investigate how nucleation of new filaments could generate biased polarity in a simple linear domain. Using a continuous-time Markov chain model of microtubule growth dynamics, we model and parameterize two experimentally-validated nucleation mechanisms: nucleation feedback, where the direction of filament growth depends on existing microtubule content, and a checkpoint mechanism, where microtubules that nucleate in a direction opposite to the majority experience frequent catastrophe. When incorporating these validated mechanisms into the spatial model, we find that nucleation feedback is sufficient to establish biased polarity in neurites of different lengths, and that the emergence and maintenance of biased polarity is relatively stable in spite of stochastic fluctuations. This work provides a framework to study the relationship between microtubule nucleation and polarity, and could extend to give insights into mechanisms that drive the formation of polarized filament arrays in other biological settings.

2. Epidemic Conditions with Temporary Link Deactivation on a Network SIR Disease Model,
    Hannah Scanlon and  John Gemmer
     Spora: A Journal of Biomathematics (2021). 7: 72–85.

The spread of an infectious disease depends on intrinsic properties of the disease as well as the connectivity and actions of the population. This study investigates the dynamics of an SIR type model which accounts for human tendency to avoid infection while also maintaining preexisting, interpersonal relationships. Specifically, we use a network model in which individuals probabilistically deactivate connections to infected individuals and later reconnect to the same individuals upon recovery. To analyze this network model, a mean field approximation consisting of a system of fourteen ordinary differential equations for the number of nodes and edges is developed. This system of equations is closed using a moment closure approximation for the number of triple links. By analyzing the differential equations, it is shown that, in addition to force of infection and recovery rate, the probability of deactivating edges and the average node degree of the underlying network determine if an epidemic occurs.