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Threshold-Free Population Analysis Identifies Larger DRG Neurons to Respond Stronger to NGF Stimulation

机译:无阈值人群分析可确定更大的DRG神经元对NGF刺激的反应更强

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摘要

Sensory neurons in dorsal root ganglia (DRG) are highly heterogeneous in terms of cell size, protein expression, and signaling activity. To analyze their heterogeneity, threshold-based methods are commonly used, which often yield highly variable results due to the subjectivity of the individual investigator. In this work, we introduce a threshold-free analysis approach for sparse and highly heterogeneous datasets obtained from cultures of sensory neurons. This approach is based on population estimates and completely free of investigator-set parameters. With a quantitative automated microscope we measured the signaling state of single DRG neurons by immunofluorescently labeling phosphorylated, i.e., activated Erk1/2. The population density of sensory neurons with and without pain-sensitizing nerve growth factor (NGF) treatment was estimated using a kernel density estimator (KDE). By subtraction of both densities and integration of the positive part, a robust estimate for the size of the responsive subpopulations was obtained. To assure sufficiently large datasets, we determined the number of cells required for reliable estimates using a bootstrapping approach. The proposed methods were employed to analyze response kinetics and response amplitude of DRG neurons after NGF stimulation. We thereby determined the portion of NGF responsive cells on a true population basis. The analysis of the dose dependent NGF response unraveled a biphasic behavior, while the study of its time dependence showed a rapid response, which approached a steady state after less than five minutes. Analyzing two parameter correlations, we found that not only the number of responsive small-sized neurons exceeds the number of responsive large-sized neurons—which is commonly reported and could be explained by the excess of small-sized cells—but also the probability that small-sized cells respond to NGF is higher. In contrast, medium-sized and large-sized neurons showed a larger response amplitude in their mean Erk1/2 activity.
机译:背根神经节(DRG)中的感觉神经元在细胞大小,蛋白质表达和信号传导活性方面高度异质。为了分析它们的异质性,通常使用基于阈值的方法,由于各个研究者的主观性,这些方法通常会产生高度可变的结果。在这项工作中,我们为从感觉神经元文化获得的稀疏和高度异构的数据集引入了无阈值分析方法。这种方法基于人口估计,并且完全没有研究人员设定的参数。用定量自动化显微镜,我们通过免疫荧光标记磷酸化的,即激活的Erk1 / 2,来测量单个DRG神经元的信号状态。使用核密度估计器(KDE)估计接受和不接受痛敏神经生长因子(NGF)治疗的感觉神经元的种群密度。通过减去密度和阳性部分的积分,可以获得对响应亚群大小的可靠估计。为了确保足够大的数据集,我们使用自举方法确定了可靠估计所需的像元数。提出的方法用于分析神经生长因子刺激后DRG神经元的响应动力学和响应幅度。因此,我们以真实种群为基础确定了NGF反应性细胞的比例。对剂量依赖性NGF反应的分析揭示了一种双相行为,而对时间依赖性的研究则显示了快速反应,在不到五分钟的时间里就达到了稳态。通过分析两个参数的相关性,我们发现不仅响应性小神经元的数量超过了响应性大神经元的数量(通常被报道,而且可以用小细胞的过多来解释),而且还发现小细胞对NGF的反应较高。相反,中型和大型神经元的平均Erk1 / 2活性显示出较大的响应幅度。

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