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  <title><![CDATA[PhD Proposal by Kim Le]]></title>
  <body><![CDATA[<p><strong>Kim Le</strong></p>

<p><strong>BME Ph.D. Proposal Presentation</strong></p>

<p>&nbsp;</p>

<p><strong>Date:&nbsp;</strong>12/12/19</p>

<p><strong>Time:&nbsp;</strong>2PM</p>

<p><strong>Location:&nbsp;</strong>EBB 5029</p>

<p><strong>Committee Members:</strong></p>

<p>&nbsp;- Hang Lu, PhD (Advisor)</p>

<p>&nbsp;- Gordon Berman, PhD</p>

<p>&nbsp;- Shuichi Takayama, PhD</p>

<p>&nbsp;- Patrick McGrath, PhD</p>

<p>&nbsp;- Annalise Paaby, PhD</p>

<p>&nbsp;</p>

<p><strong>Title:&nbsp;</strong>Toolsets for investigating&nbsp;environmental effects and stochasticity on behavioral decline and gene expression during aging in&nbsp;<em>Caenorhabditis elegans</em></p>

<p>&nbsp;</p>

<p><strong>Abstract:</strong></p>

<p>Genetics, environment, and stochasticity influence health and longevity. However, it is difficult to study how environmental cues and stochasticity modulate the aging process in a robust, high-throughput way. Even in the simple model organism&nbsp;<em>Caenorhabditis elegans</em>, existing methods are labor-intensive, lack individual-level resolution, or lack precise spatiotemporal environmental control. In this thesis I will develop a robust, microfluidic-based culture system for&nbsp;<em>C. elegans</em>&nbsp;and examine how environmental effects and stochasticity influence healthspan and lifespan. In Aim 1, I will engineer a robust pipeline for the long-term culture and longitudinal behavioral monitoring of&nbsp;<em>C. elegans&nbsp;</em>in aging studies. In Aim 2, I will characterize the impact of environmental perturbations on behavioral decline during aging, examining dynamic thermal cycling and different forms dietary restriction (chronic restriction and intermittent fasting). In Aim 3, I will examine differences in transcriptional regulation that arise in aging within isogenic populations under highly controlled environmental conditions. The completion of this thesis should provide 1) a new toolset to robustly explore how genetic, environmental, or stochastic effects influence longevity and healthspan, 2) insight into how environmental perturbations influence behavioral decline, and 3) insight into how aging and environmental perturbations influence gene expression and variability within a population.</p>
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