Literature DB >> 9240399

Diffusion in axon guidance.

G J Goodhill1.   

Abstract

Axon guidance by target-derived diffusible factors plays an important role in the development of the nervous system. This paper considers the constraints imposed on this process by the mathematics of diffusion. A point source continuously producing a factor into an infinite three-dimensional volume is considered as a model for both the in vivo and in vitro situation. Basic constraints for effective guidance are assumed to be that the concentration falls between certain maximum and minimum limits, and that the percentage change in concentration across the width of the growth cone exceeds a certain minimum value. The evolution of the shape of the gradient over time is analysed. Using biologically reasonable parameter values, it is shown that the maximum range over which growth cone guidance by a diffusible factor is possible for large times (several days) after the start of the production of the factor is 500-1000 microm. This maximum distance is independent of the diffusion constant of the diffusing molecule, applies to both chemoattractants and chemorepellents, and agrees with experimental data. At earlier times, however, the constraints may be satisfied for distances up to several millimetres. The time it takes for this maximum guidance distance to fall to the asymptotic value depends on the diffusion constant. This time is a few hours for a small molecule but as much as a few days for a large molecule. The model therefore predicts that guidance over distances larger than 1000 microm is possible if the start of production of the factor is carefully matched to the time when guidance is required.

Mesh:

Year:  1997        PMID: 9240399     DOI: 10.1111/j.1460-9568.1997.tb01496.x

Source DB:  PubMed          Journal:  Eur J Neurosci        ISSN: 0953-816X            Impact factor:   3.386


  31 in total

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3.  Spatial distributions of guidance molecules regulate chemorepulsion and chemoattraction of growth cones.

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Journal:  J Neurosci       Date:  2000-02-01       Impact factor: 6.167

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5.  Designing in vivo concentration gradients with discrete controlled release: a computational model.

Authors:  Edgar Y Walker; Dennis L Barbour
Journal:  J Neural Eng       Date:  2010-07-19       Impact factor: 5.379

6.  Semi-automatic quantification of neurite fasciculation in high-density neurite images by the neurite directional distribution analysis (NDDA).

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7.  Bayesian model predicts the response of axons to molecular gradients.

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Journal:  Proc Natl Acad Sci U S A       Date:  2009-06-18       Impact factor: 11.205

8.  Spatially patterned gene expression for guided neurite extension.

Authors:  Tiffany Houchin-Ray; Alyssa Huang; Erin R West; Marina Zelivyanskaya; Lonnie D Shea
Journal:  J Neurosci Res       Date:  2009-03       Impact factor: 4.164

9.  Mechanistic insights from a quantitative analysis of pollen tube guidance.

Authors:  Shannon F Stewman; Matthew Jones-Rhoades; Prabhakar Bhimalapuram; Martin Tchernookov; Daphne Preuss; Aaron R Dinner
Journal:  BMC Plant Biol       Date:  2010-02-22       Impact factor: 4.215

10.  Manipulation of signaling thresholds in "engineered stem cell niches" identifies design criteria for pluripotent stem cell screens.

Authors:  Raheem Peerani; Kento Onishi; Alborz Mahdavi; Eugenia Kumacheva; Peter W Zandstra
Journal:  PLoS One       Date:  2009-07-30       Impact factor: 3.240

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