期刊
JOURNAL OF NEUROSCIENCE
卷 25, 期 18, 页码 4565-4576出版社
SOC NEUROSCIENCE
DOI: 10.1523/JNEUROSCI.0588-05.2005
关键词
retina; development; growth; patterning; modeling; computational
The vertebrate retina is composed of cellular arrays that are nonrandom across two-dimensional space. The determinants of these nonrandom two-dimensional cellular patterns in the inner nuclear layer of the retina were investigated using empirical and computational modeling techniques. In normal and experimental models of goldfish retinal growth, the patterns of tyrosine hydroxylase- and serotonin-positive cells indicated that neither cell death nor lateral migration of differentiated cells were dominant mechanisms of cellular pattern formation. A computational model of cellular pattern formation that used a signaling mechanism arising from differentiated cells that inhibited homotypic cell-fate decisions generated accurate simulations of the empirically observed patterns in normal retina. This model also predicted the principal atypical cellular pattern characteristic, a transient cell-type-specific hyperplasia, which was empirically observed in the growing retina subsequent to selective ablation of differentiated retinal cells, either tyrosine hydroxylase positive or serotonin positive. The results support the hypothesis that inhibitory spatiotemporal regulation of homotypic cell-fate decisions is a dominant mechanistic determinant of nonrandom cellular patterns in the vertebrate retina.
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