Hostname: page-component-77c89778f8-fv566 Total loading time: 0 Render date: 2024-07-20T23:06:15.943Z Has data issue: false hasContentIssue false
  • English
  • Français

Quantification of Axonal Outgrowth on a Surface with Asymmetric Topography

Published online by Cambridge University Press:  28 February 2014

Elise Spedden  and
Cristian Staii
Elise Spedden
Affiliation:
Tufts University Department of Physics and Astronomy, 4 Colby St, Medford, MA 02155
Cristian Staii
Affiliation:
Tufts University Department of Physics and Astronomy, 4 Colby St, Medford, MA 02155
Get access

Abstract

Topographical features are known to influence the axonal outgrowth of neurons. Understanding what kinds of topographical features are most effective at growth cone guidance and how outgrowth responds to these structures is of great importance to the study of nerve regeneration. To this end we analyze axonal outgrowth on tilted nanorod substrates which have been shown to impart directional bias to neuron growth. We utilize the Atomic Force Microscope to characterize the surface features present on these substrates and how such features are influencing the axonal outgrowth. Additionally, using a model which considers the neuronal growth cone as an object influenced by an effective potential we determine an effective force imparted on the growth cone by the surface topography.

Keywords

biologicalnanostructuremicrostructure
Type
Articles
Information
MRS Online Proceedings Library (OPL) , Volume 1621: Symposium H/C/D/J – Advances in Structures, Properties and Applications of Biological and Bioinspired Materials , 2014 , pp. 243 - 248
Copyright
Copyright © Materials Research Society 2014 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

Wen, Z. and Zheng, J. Q., Current opinion in neurobiology 16(1), 52–58 (2006).CrossRefGoogle Scholar
Huber, A. B., Kolodkin, A. L., Ginty, D. D. and Cloutier, J. F., Annual review of neuroscience 26, 509–563 (2003).CrossRefGoogle Scholar
Clark, P., Britland, S. and Connolly, P., Journal of cell science 105 ( Pt 1), 203–212 (1993).Google Scholar
Kennedy, T. E., Serafini, T., de la Torre, J. R. and Tessier-Lavigne, M., Cell 78(3), 425–435 (1994).CrossRefGoogle Scholar
Rajnicek, A., Britland, S. and McCaig, C., Journal of cell science 110 ( Pt 23), 2905–2913 (1997).Google Scholar
Rajnicek, A. and McCaig, C., Journal of cell science 110 ( Pt 23), 2915–2924 (1997).Google Scholar
Fozdar, D. Y., Lee, J. Y., Schmidt, C. E. and Chen, S., Int J Nanomedicine 6, 45–57 (2011).Google Scholar
Fan, Y. W., Cui, F. Z., Hou, S. P., Xu, Q. Y., Chen, L. N. and Lee, I. S., Journal of neuroscience methods 120(1), 17–23 (2002).CrossRefGoogle Scholar
Johansson, F., Carlberg, P., Danielsen, N., Montelius, L. and Kanje, M., Biomaterials 27(8), 1251–1258 (2006).CrossRefGoogle Scholar
Smeal, R. M. and Tresco, P. A., Experimental neurology 213(2), 281–292 (2008).CrossRefGoogle Scholar
Beighley, R., Spedden, E., Sekeroglu, K., Atherton, T., Demirel, M. C. and Staii, C., Applied physics letters 101(14), 143701 (2012).CrossRefGoogle Scholar
Patel, N. and Poo, M. M., The Journal of neuroscience : the official journal of the Society for Neuroscience 2(4), 483–496 (1982).CrossRefGoogle Scholar
Rizzo, D. J., White, J. D., Spedden, E., Wiens, M. R., Kaplan, D. L., Atherton, T. J. and Staii, C., Physical Review E 88(4), 042707 (2013).CrossRefGoogle Scholar
Riveline, D., Zamir, E., Balaban, N. Q., Schwarz, U. S., Ishizaki, T., Narumiya, S., Kam, Z., Geiger, B. and Bershadsky, A. D., The Journal of cell biology 153(6), 1175–1186 (2001).CrossRefGoogle Scholar
Frey, M. T., Tsai, I. Y., Russell, T. P., Hanks, S. K. and Wang, Y. L., Biophysical journal 90(10), 3774–3782 (2006).CrossRefGoogle Scholar