Background

Recent anthropomorphic disturbances are occurring at an increasing rate leading to organisms facing a variety of challenges. This change is testing the information processing capacity (IPC) of all animals. Brain function is widely accepted to be influenced by a variety of factors, including relative size, number of neurons and neuronal densities. Therefore, in order to understand what drives an animals IPC, a methodological approach to analyze these factors must be established.

New method

Here we created a protocol that allowed for high-throughput, non-biased quantification of neuronal density and size across six regions of the brain. We used the Isotropic Fractionator method in combination with flow cytometry to identify neuronal and non-neuronal cells in the brains of adult rats.

Comparison with existing methods

The results obtained were comparable to those identified using stereological counting methods.

Results

By employing this new method, the number of nuclei in a specific brain region can be compared between replicate animals within an experiment. By calibrating the forward scatter channel of the flow cytometer with size standard beads, neuronal and non-neuronal nuclear sizes can be estimated simultaneously with nuclei enumeration. These techniques for nuclear counting and size estimation are technically and biologically reproducible.

Conclusion

Use of flow cytometry provides a methodological approach that allows for consistency in research, so that information on brain morphology, and subsequent function, will become comparable across taxa.

中文翻译：

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使用流式细胞仪定量测定神经元大小和密度

背景

最近的拟人化干扰正在以越来越高的速度发生，导致生物面临各种挑战。这一变化正在测试所有动物的信息处理能力（IPC）。人们普遍认为脑功能受多种因素影响，包括相对大小，神经元数量和神经元密度。因此，为了了解驱动动物IPC的原因，必须建立一种分析这些因素的方法。

新方法

在这里，我们创建了一个协议，该协议可以对大脑六个区域的神经元密度和大小进行高通量，无偏量化。我们将各向同性分馏器方法与流式细胞仪结合使用，以鉴定成年大鼠大脑中的神经元和非神经元细胞。

与现有方法的比较

获得的结果与使用立体计数法确定的结果相当。

结果

通过采用这种新方法，可以比较实验中复制动物之间特定大脑区域中核的数量。通过用大小标准珠校准流式细胞仪的前向散射通道，可以在核计数的同时估算神经元和非神经元核的大小。这些用于核计数和大小估计的技术在技术和生物学上都是可复制的。

结论

流式细胞仪的使用提供了一种方法学方法，该方法可确保研究的一致性，以便有关脑形态学和后续功能的信息在整个分类单元中变得可比。