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首页> 外文期刊>BMC Bioinformatics >IPLaminator: an ImageJ plugin for automated binning and quantification of retinal lamination
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IPLaminator: an ImageJ plugin for automated binning and quantification of retinal lamination

机译:IPLaminator:一个ImageJ插件,用于自动合并和量化视网膜层压

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摘要

Information in the brain is often segregated into spatially organized layers that reflect the function of the embedded circuits. This is perhaps best exemplified in the layering, or lamination, of the retinal inner plexiform layer (IPL). The neurites of the retinal ganglion, amacrine and bipolar cell subtypes that form synapses in the IPL are precisely organized in highly refined strata within the IPL. Studies focused on developmental organization and cell morphology often use this layered stratification to characterize cells and identify the function of genes in development of the retina. A current limitation to such analysis is the lack of standardized tools to quantitatively analyze this complex structure. Most previous work on neuron stratification in the IPL is qualitative and descriptive. In this study we report the development of an intuitive platform to rapidly and reproducibly assay IPL lamination. The novel ImageJ based software plugin we developed: IPLaminator, rapidly analyzes neurite stratification patterns in the retina and other neural tissues. A range of user options allows researchers to bin IPL stratification based on fixed points, such as the neurites of cholinergic amacrine cells, or to define a number of bins into which the IPL will be divided. Options to analyze tissues such as cortex were also added. Statistical analysis of the output then allows a quantitative value to be assigned to differences in laminar patterning observed in different models, genotypes or across developmental time. IPLaminator is an easy to use software application that will greatly speed and standardize quantification of neuron organization.
机译:大脑中的信息通常被隔离成空间结构的层,这些层反映了嵌入式电路的功能。视网膜内丛状层(IPL)的分层或层压可能是最好的例证。视网膜神经节,无长突蛋白和双极细胞亚型的神经突在IPL中形成突触,这些神经突精确地组织在IPL内高度精化的层次中。专注于发育组织和细胞形态的研究通常使用这种分层分层来表征细胞并鉴定基因在视网膜发育中的功能。这种分析的当前局限性是缺乏用于定量分析这种复杂结构的标准化工具。 IPL中有关神经元分层的大多数先前工作是定性和描述性的。在本研究中,我们报告了一种直观平台的开发,该平台可快速,可重复地检测IPL层压。我们开发的新型基于ImageJ的软件插件:IPLaminator,可快速分析视网膜和其他神经组织中的神经突分层模式。一系列用户选项允许研究人员根据固定点(例如胆碱能无长突细胞的神经突)对IPL分层进行分类,或定义将IPL分为多个分类。还添加了用于分析组织(例如皮质)的选项。然后,通过对输出进行统计分析,可以将定量值分配给在不同模型,基因型或整个发育时间内观察到的层流模式差异。 IPLaminator是易于使用的软件应用程序,它将极大地加快和标准化神经元组织的量化。

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