Literature DB >> 17713648

Dendritic thickness: a morphometric parameter to classify mouse retinal ganglion cells.

L D Loopuijt1, M da Silva Filho, B Hirt, R Vonthein, J Kremers.   

Abstract

To study the dendritic morphology of retinal ganglion cells in wild-type mice we intracellularly injected these cells with Lucifer yellow in an in vitro preparation of the retina. Subsequently, quantified values of dendritic thickness, number of branching points and level of stratification of 73 Lucifer yellow-filled ganglion cells were analyzed by statistical methods, resulting in a classification into 9 groups. The variables dendritic thickness, number of branching points per cell and level of stratification were independent of each other. Number of branching points and level of stratification were independent of eccentricity, whereas dendritic thickness was positively dependent (r = 0.37) on it. The frequency distribution of dendritic thickness tended to be multimodal, indicating the presence of at least two cell populations composed of neurons with dendritic diameters either smaller or larger than 1.8 microm ("thin" or "thick" dendrites, respectively). Three cells (4.5%) were bistratified, having thick dendrites, and the others (95.5%) were monostratified. Using k-means cluster analysis, monostratified cells with either thin or thick dendrites were further subdivided according to level of stratification and number of branching points: cells with thin dendrites were divided into 2 groups with outer stratification (0-40%) and 2 groups with inner (50-100%) stratification, whereas cells with thick dendrites were divided into one group with outer and 3 groups with inner stratification. We postulate, that one group of cells with thin dendrites resembles cat beta-cells, whereas one group of cells with thick dendrites includes cells that resemble cat alpha-cells.

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Year:  2007        PMID: 17713648     DOI: 10.1590/s0100-879x2006005000161

Source DB:  PubMed          Journal:  Braz J Med Biol Res        ISSN: 0100-879X            Impact factor:   2.590


  2 in total

1.  Optimization of Traced Neuron Skeleton Using Lasso-Based Model.

Authors:  Shiwei Li; Tingwei Quan; Cheng Xu; Qing Huang; Hongtao Kang; Yijun Chen; Anan Li; Ling Fu; Qingming Luo; Hui Gong; Shaoqun Zeng
Journal:  Front Neuroanat       Date:  2019-02-21       Impact factor: 3.856

2.  Identifying Weak Signals in Inhomogeneous Neuronal Images for Large-Scale Tracing of Sparsely Distributed Neurites.

Authors:  Shiwei Li; Tingwei Quan; Hang Zhou; FangFang Yin; Anan Li; Ling Fu; Qingming Luo; Hui Gong; Shaoqun Zeng
Journal:  Neuroinformatics       Date:  2019-10
  2 in total

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