title: Experimental and computational models of neurite extension at a choice point in response to controlled diffusive gradients.
abstract: OBJECTIVE
  Axons are guided toward desired targets through a series of choice points that they navigate by sensing cues in the cellular environment. A better understanding of how microenvironmental factors influence neurite growth during development can inform strategies to address nerve injury. Therefore, there is a need for biomimetic models to systematically investigate the influence of guidance cues at such choice points.
  
  
  METHODS
  We ran an adapted in silico biased turning axon growth model under the influence of nerve growth factor (NGF) and compared the results to corresponding in vitro experiments. We examined if growth simulations were predictive of neurite population behavior at a choice point. We used a biphasic micropatterned hydrogel system consisting of an outer cell restrictive mold that enclosed a bifurcated cell permissive region and placed a well near a bifurcating end to allow proteins to diffuse and form a gradient. Experimental diffusion profiles in these constructs were used to validate a diffusion computational model that utilized experimentally measured diffusion coefficients in hydrogels. The computational diffusion model was then used to establish defined soluble gradients within the permissive region of the hydrogels and maintain the profiles in physiological ranges for an extended period of time. Computational diffusion profiles informed the neurite growth model, which was compared with neurite growth experiments in the bifurcating hydrogel constructs.
  
  
  RESULTS
  Results indicated that when applied to the constrained choice point geometry, the biased turning model predicted experimental behavior closely. Results for both simulated and in vitro neurite growth studies showed a significant chemoattractive response toward the bifurcated end containing an NGF gradient compared to the control, though some neurites were found in the end with no NGF gradient.
  
  
  CONCLUSIONS
  The integrated model of neurite growth we describe will allow comparison of experimental studies against growth cone guidance computational models applied to axon pathfinding at choice points.
authors.affiliation: Department of Biomedical Engineering, Tulane University, Lindy Boggs Building Suite 500, New Orleans, LA 70118, USA.
authors.forename: G C
authors.initials: GC
authors.lastname: Catig
authors.forename: S
authors.initials: S
authors.lastname: Figueroa
authors.forename: M J
authors.initials: MJ
authors.lastname: Moore
mesh_terms: D000818:Animals; D040761:Biomimetic Materials / Q000737:chemistry*; D049108:Cell Enlargement; D002478:Cells, Cultured; D002630:Chemotactic Factors / Q000737:chemistry / Q000378:metabolism*; D003198:Computer Simulation; D004058:Diffusion; D008954:Models, Biological; D008956:Models, Chemical; D009414:Nerve Growth Factors / Q000378:metabolism*; D016501:Neurites / Q000737:chemistry / Q000502:physiology* / Q000648:ultrastructure*; D055495:Neurogenesis / Q000502:physiology; D051381:Rats; D020318:Rats, Long-Evans
chemical_list: D002630:Chemotactic Factors; D009414:Nerve Growth Factors