AxonQuant: A Microfluidic Chamber Culture-Coupled Algorithm That Allows High-Throughput Quantification of Axonal Damage.

AxonQuant: A Microfluidic Chamber Culture-Coupled Algorithm That Allows High-Throughput Quantification of Axonal Damage.
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AxonQuant:一种微流控室培养耦合算法,可对轴突损伤进行高通量定量

DOI:
10.1159/000358092
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发表时间:
2014
期刊:
Neuro-Signals
影响因子:
--
通讯作者:
Wu JY
Wu JY
中科院分区:
其他
文献类型:
--
作者:
Li Y;Yang M;Huang Z;Chen X;Maloney MT;Zhu L;Liu J;Yang Y;Du S;Jiang X;Wu JY

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已发表的成像和定量分析神经元轴突形态变化的方法有严重的局限性,因为它们的样本量小,耗时和非客观的性质。在这里,我们提出了一种改进的微流控室设计,适用于神经元轴突的快速和高通量成像。提出了适用于轴突成像数据自动处理的AxonQuant算法。这种微流控腔耦合算法允许计算“轴突连续性指数”,以独立于神经元或轴突密度的方式定量测量轴突健康状态。这种方法允许轴突形态的定量分析在自动和无偏的方式。我们的方法将促进涉及轴突损伤的神经退行性疾病的基因或治疗化合物的大规模高通量筛选。当与利用不同基因标记的成像技术相结合时,该方法将为轴突变性的机制基础提供新的见解。我们的微流控室培养耦合轴突定量算法将广泛应用于轴突生物学和神经退行性疾病的研究。©2014 S. Karger AG,巴塞尔
Published methods for imaging and quantitatively analyzing morphological changes in neuronal axons have serious limitations because of their small sample sizes, and their time-consuming and nonobjective nature. Here we present an improved microfluidic chamber design suitable for fast and high-throughput imaging of neuronal axons. We developed the AxonQuant algorithm, which is suitable for automatic processing of axonal imaging data. This microfluidic chamber-coupled algorithm allows calculation of an ‘axonal continuity index' that quantitatively measures axonal health status in a manner independent of neuronal or axonal density. This method allows quantitative analysis of axonal morphology in an automatic and nonbiased manner. Our method will facilitate large-scale high-throughput screening for genes or therapeutic compounds for neurodegenerative diseases involving axonal damage. When combined with imaging technologies utilizing different gene markers, this method will provide new insights into the mechanistic basis for axon degeneration. Our microfluidic chamber culture-coupled AxonQuant algorithm will be widely useful for studying axonal biology and neurodegenerative disorders. © 2014 S. Karger AG, Basel
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