Leandro Forciniti 1 , C. E. Schmidt 1,2 *, M. H. Zaman 2,3 *

1. Computation model provides insight into the distinct responses of neurons to chemical and topographical cues Leandro Forciniti1, C. E. Schmidt1,2*, M. H. Zaman2,3* 1Department of Chemical Engineering, The University of Texas at Austin, Austin, TX 78727 2Department of Biomedical Engineering, The University of Texas at Austin, Austin, TX 78727 3Institute of Theoretical Chemistry, The University of Texas at Austin, Austin, TX 78727 *To whom correspondence should be addressed (mhzaman@mail.utexas.edu, schmidt@che.utexas.edu) October 2, 2008

2. Motivation • Why do we care about neuronal behavior and axonal regeneration in response to cues? • Peripheral Nervous System Injury • 12,000 patients and 10 billion dollars • Neuronal response to cues key in understanding how to engineer scaffolds for nervous system repair • Central Nervous System Diseases • Developmental Diseases • Parkinson’s and Alzheimer’s Disease

3. Shows distinct behavior depending on external cues Hippocampal neurons polarize in culture Dotti CG, Sullivan CA, Banker GA: The Establishment of Polarity by Hippocampal Neurons in Culture. The Journal of Neuroscience 1988, 8:1454-1468.

4. Topography-1 μm NGF-FITC* Topography- 2 μm *Unpublished Data From Dr. Natalia Gomez External topographical and chemical cues cause different levels of neuronal polarization

5. General approach Polarization is favored on topography versus immobilized NGF Describes previous experiments seen by Gomez et. al.* and predicts new behavior Probabilistic Model Better Understanding New Experiment Test Predicted Behavior *Gomez N, Lu Y, Chen S, Schmidt CE: Biomaterials 2007, 28:271-284.

6. ri,j 15 μm How are the (x,y) coordinates for this step determined? 3 μm Spherical horse approximation

7. Each step moves independently

8. Computational Model Algorithm Initial Conditions Enter Run Algorithm Output No Check end Condition? r1 > (r2 + 15 μm) Chemical or Topographical? Yes

9. Computational Results: As a function of characteristic lengths (l*)

10. l* = 110 μm l* = 17.5 μm Computational results: As a function of minimum step size

11. Micro-fabrication of Substrate

12. NGF Immobilization

13. 2 μm NGF (0.11 ng/mm2) PAA Control Raw Experimental Data • Polarization Probability • 58 % Topography • 42 % NGF

14. Nmin = 1μm Nmin = 1.5 μm Comparison of Results For both l* = 110 μm

15. Conclusion • The computation model is able to capture first order effects of neuronal response to chemical (NGF) versus topographical cues • Tight correlation between the model and experiments shows that cue spacing is the major parameter that needs to be considered for axon polarization • Model predicts that for topographical features a peak in polarization probability will occur at the characteristic length scale of a neurite

16. Acknowledgements • Dr. Schmidt • Dr. Zaman • Dr. Schmidt’s Lab • Dr. Zaman’s Lab • Dr. Natalia Gomez • CNM at University of Texas Austin • Funding Resources: • NIH R21