The New Jersey Institute of Technology's
Electronic Theses & Dissertations Project

Title:	A microfluidic culture for two populations of dorsal root ganglia for differential staining
Author:	Sidhu, Ishnoor
View Online:	njit-etd2011-083 (xii, 51 pages ~ 2.7 MB pdf)
Department:	Department of Biomedical Engineering
Degree:	Master of Science
Program:	Biomedical Engineering
Document Type:	Thesis
Advisory Committee:	Perez-Castillejos, Raquel (Committee chair) Pfister, Bryan J. (Committee member) Cho, Cheul H. (Committee member)
Date:	2011-05
Keywords:	Dorsal root ganglia Differential staining
Availability:	Unrestricted
Abstract:	The goal of this study was to design and fabricate a microfluidic system that can be used to visibly distinguish the two populations of dorsal root ganglia (DRGs) by differential staining. Polydimethylsiloxane (PDMS) is the most widely used silicon-based organic polymer, and is particularly known for its wide spread use in microfluidics. Various methods have been employed to pump fluids in these channels for applications ranging from patterning of cells and biomolecules to control of local environment factors such as temperature, which requires external pumping or other applied forces. We demonstrated a pump-free device that exploits the surface energy stored in a liquid droplet to pump liquid in the channels. The fluid was pumped by using two droplets of unequal sizes connected via fluid filled channel. The flow was generated from smaller droplet to larger droplet. This passive pumping technique was used to simultaneously stain the two cultured DRGs in connected channels. The in vitro system can be further exploited to study the guided growth in axons. This study provides a cost effective method to detect the influence of the presence of pioneer neuron on the growth patterns of the new generation of neurons. It eliminates the need of using transgenic cells to study the guided growth in axons, thereby giving some insight for the repair of spinal cord injuries and the understanding of the early growth model.