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首页> 外文期刊>The European Journal of Neuroscience >Fine structure analysis of perineuronal nets in the ketamine model of schizophrenia
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Fine structure analysis of perineuronal nets in the ketamine model of schizophrenia

机译：精神分裂症氯胺酮模型中肺炎群体的细结构分析

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Perineuronal nets (PNNs) represent a highly condensed specialized form of brain extracellular matrix (ECM) enwrapping mostly parvalbumin-positive interneurons in the brain in a mesh-like fashion. PNNs not only regulate the onset and completion of the critical period during postnatal brain development, control cell excitability, and synaptic transmission but are also implicated in several brain disorders including schizophrenia. Holes in the perineuronal nets, harboring the synaptic contacts, along with hole-surrounding ECM barrier can be viewed as PNN compartmentalization units that might determine the properties of synapses and heterosynaptic communication. In this study, we developed a novel open-source script for Fiji (ImageJ) to semi-automatically quantify structural alterations of PNNs such as the number of PNN units, area, mean intensity of PNN marker expression in 2D and 3D, shape parameters of PNN units in the ketamine-treated Sprague-Dawley rat model of schizophrenia using high-resolution confocal microscopic images. We discovered that the mean intensity of ECM within PNN units is inversely correlated with the area and the perimeter of the PNN holes. The intensity, size, and shape of PNN units proved to be three major principal factors to describe their variability. Ketamine-treated rats had more numerous but smaller and less circular PNN units than control rats. These parameters allowed to correctly classify individual PNNs as derived from control or ketamine-treated groups with = 85% reliability. Thus, the proposed multidimensional analysis of PNN units provided a robust and comprehensive morphometric fingerprinting of fine ECM structure abnormalities in the experimental model of schizophrenia.
机译：神经周围网（Perineuronal nets，PNN）是一种高度浓缩的大脑细胞外基质（extracellular matrix，ECM），主要以网状方式包裹大脑中的小白蛋白阳性中间神经元。PNN不仅调节出生后大脑发育关键期的开始和完成、控制细胞兴奋性和突触传递，还与包括精神分裂症在内的几种大脑疾病有关。神经周围网中的孔，包括突触接触，以及ECM屏障周围的孔，可以被视为PNN区隔单元，可能决定突触和异突触通讯的性质。在本研究中，我们为斐济开发了一个新的开源脚本（ImageJ），使用高分辨率共焦显微图像半自动量化PNN的结构改变，例如，在氯胺酮治疗的Sprague-Dawley精神分裂症大鼠模型中，2D和3D中PNN标记物表达的数量、面积、平均强度、PNN单位的形状参数。我们发现PNN单元内ECM的平均强度与PNN孔的面积和周长成反比。PNN单元的强度、大小和形状被证明是描述其可变性的三个主要因素。与对照组大鼠相比，氯胺酮治疗组大鼠的PNN环数量更多，但更小，更少。这些参数允许正确地将单个PNN分类为来自对照组或氯胺酮治疗组的PNN，可靠性=85%。因此，提出的PNN单位的多维分析为精神分裂症实验模型中精细ECM结构异常提供了一个稳健而全面的形态计量指纹图谱。

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