Creation of highly aligned electrospun poly-L-lactic acid fibers for nerve regeneration applications

Han Bing Wang, Michael E. Mullins, Jared M. Cregg, Andres Hurtado, Martin Oudega, Matthew T. Trombley, Ryan J. Gilbert

Research output: Contribution to journalArticle

202 Citations (Scopus)

Abstract

Aligned, electrospun polymer fibers have shown considerable promise in directing regenerating axons in vitro and in vivo. However, in several studies, final electrospinning parameters are presented for producing aligned fiber scaffolds, and alignment where minimal fiber crossing occurs is not achieved. Highly aligned species are necessary for neural tissue engineering applications to ensure that axonal extension occurs through a regenerating environment efficiently. Axonal outgrowth on fibers that deviate from the natural axis of growth may delay axonal extension from one end of a scaffold to the other. Therefore, producing aligned fiber scaffolds with little fiber crossing is essential. In this study, the contributions of four electrospinning parameters (collection disk rotation speed, needle size, needle tip shape and syringe pump flow rate) were investigated thoroughly with the goal of finding parameters to obtain highly aligned electrospun fibers made from poly-L-lactic acid (PLLA). Using an 8 wt% PLLA solution in chloroform, a collection disk rotation speed of 1000 revolutions per minute (rpm), a 22 gauge, sharp-tip needle and a syringe pump rate of 2 ml h-1 produced highly aligned fiber (1.2-1.6 νm in diameter) scaffolds verified using a fast Fourier transform and a fiber alignment quantification technique. Additionally, the application of an insulating sheath around the needle tip improved the rate of fiber deposition (electrospinning efficiency). Optimized scaffolds were then evaluated in vitro using embryonic stage nine (E9) chick dorsal root ganglia (DRGs) and rat Schwann cells (SCs). To demonstrate the importance of creating highly aligned scaffolds to direct neurite outgrowth, scaffolds were created that contained crossing fibers. Neurites on these scaffolds were directed down the axis of the aligned fibers, but neurites also grew along the crossed fibers. At times, these crossed fibers even stopped further axonal extension. Highly aligned PLLA fibers generated under optimized electrospinning conditions guided neurite and SC growth along the aligned fibers. Schwann cells demonstrated the bipolar phenotype seen along the fibers. Using a novel technique to determine fiber density, an increase in fiber density correlated to an increase in the number of neurites, but average neurite length was not statistically different between the two different fiber densities. Together, this work presents methods by which to produce highly aligned fiber scaffolds efficiently and techniques for assessing neurite outgrowth on different fiber scaffolds, while suggesting that crossing fibers may be detrimental in fostering efficient, directed axonal outgrowth.

Original languageEnglish (US)
Article number016001
JournalJournal of Neural Engineering
Volume6
Issue number1
DOIs
StatePublished - 2009
Externally publishedYes

Fingerprint

Nerve Regeneration
Neurites
Lactic acid
Needles
Schwann Cells
Fibers
Syringes
Scaffolds
Foster Home Care
Spinal Ganglia
Fourier Analysis
Tissue Engineering
Growth
Chloroform
Electrospinning
Axons
Polymers
poly(lactic acid)
Phenotype
Cells

ASJC Scopus subject areas

  • Biomedical Engineering
  • Cellular and Molecular Neuroscience

Cite this

Creation of highly aligned electrospun poly-L-lactic acid fibers for nerve regeneration applications. / Wang, Han Bing; Mullins, Michael E.; Cregg, Jared M.; Hurtado, Andres; Oudega, Martin; Trombley, Matthew T.; Gilbert, Ryan J.

In: Journal of Neural Engineering, Vol. 6, No. 1, 016001, 2009.

Research output: Contribution to journalArticle

Wang, Han Bing ; Mullins, Michael E. ; Cregg, Jared M. ; Hurtado, Andres ; Oudega, Martin ; Trombley, Matthew T. ; Gilbert, Ryan J. / Creation of highly aligned electrospun poly-L-lactic acid fibers for nerve regeneration applications. In: Journal of Neural Engineering. 2009 ; Vol. 6, No. 1.
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