Date Approved

9-2-2021

Embargo Period

9-7-2021

Document Type

Dissertation

Degree Name

Ph.D. Doctor of Philosophy

Department

Biomedical Engineering

College

Henry M. Rowan College of Engineering

Advisor

Mary M. Staehle, Ph.D.

Committee Member 1

Vince Beachley, Ph.D.

Committee Member 2

Alison Krufka, Ph.D.

Committee Member 3

Joseph Stanzione, III, Ph.D.

Committee Member 4

Umashanger Thayasivam, Ph.D.

Committee Member 5

Sebastián Vega, Ph.D.

Keywords

Bisphenol A, Developmental, High-throughput, Neurotoxicity, Planaria, Toxicology

Subject(s)

Neurotoxic agents--Testing

Disciplines

Biomedical Engineering and Bioengineering

Abstract

The increase in commercially used chemicals that are inadequately evaluated for safety and risk to development has created a reticent threat to human health. Addressing these deficiencies is compounded by limited methodologies to determine the etiology of exposure-related developmental neurotoxicity (DNT). Current means of assessing DNT are largely retrospective and limited by the expensive, time-consuming, and labor-intensive use of laboratory animal models, thereby motivating a global research effort to produce alternative chemical screening assays. In this work, we have developed a novel high- throughput platform that serves as a new tool to evaluate the effects of exogenous chemical exposure on developmental processes in the non-vertebrate animal model, Schmidtea mediterranea (Smed). We demonstrate that light avoidance in Smed is a robust behavior that can be assayed throughout head regeneration and is temporally correlated to the anatomical development of central nervous system structure. Thus, reacquisition of this behavior serves as a surrogate measure of neurodevelopment that can be utilized to characterize exposure-related effects in DNT. Our high-throughput screening platform enables a more sensitive classification of these responses and assesses both endpoint and temporal effects of chemical exposure in DNT, which paves the way for more exhaustive and predictive chemical assessment to minimize the impact on human health.

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