BACKGROUND Cell-based assays comprising primary sensory neurons cultured in vitro are an emerging tool for the screening and identification of potential analgesic compounds and chronic pain treatments. High-content screening (HCS) platforms for drug screening are characterized by a measure of assay quality indicator, such as the Z'-factor, which considers the signal dynamic range and data variation using control compounds only. Although widely accepted as a quality metric in high throughput screening (HTS), standard Z'-factor are not well-suited to indicate the quality of complex cell-based assays. NEW METHOD The present study describes a method to assess assay quality in the context of extracellular recordings from dorsal root ganglion (DRG) sensory neurons cultured on multi-well microelectrode arrays. Data transformations are applied to electrophysiological parameters, such as electrode and well spike rates, for valid normality assumptions and suitability for use as a sample signal. Importantly, using transformed well-wide metrics, a robust version of the Z'-factor was applied, based on the median and median absolute deviation, to indicate assay quality and assess hit identification of putative pharmacological compounds. RESULTS Application of appropriately scaled data and robust statistics ensured insensitivity to data variation and approximation of normal distribution. The use median and median absolute deviation of log transformed well spike rates in computing the Z'-factor revealed a value of 0.61, which is accepted as an "excellent assay." Known antagonists of nociceptor-specific voltage-gated sodium ion channels were identified as true hits in the present assay format under both spontaneous and thermally stimulated conditions. COMPARISON WITH EXISTING METHODS The present approach demonstrated a large signal dynamic range and reduced sensitivity to data variation compared to standard Z'-factor used widely in HTS. CONCLUSION Overall, the present study provides a statistical basis for the implementation of a HCS platform utilizing adult DRG neurons on microelectrode arrays.

中文翻译：

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在使用成人背根神经节神经元的基于微电极阵列的筛选中，稳健的 Z' 因子对测定质量评估的适应。

背景技术包括体外培养的初级感觉神经元的基于细胞的测定是用于筛选和鉴定潜在镇痛化合物和慢性疼痛治疗的新兴工具。用于药物筛选的高内涵筛选 (HCS) 平台的特点是测定质量指标，例如 Z' 因子，它仅考虑使用对照化合物的信号动态范围和数据变化。虽然被广泛接受为高通量筛选 (HTS) 中的质量指标，但标准 Z' 因子并不适合指示基于复杂细胞的检测的质量。新方法 本研究描述了一种在多孔微电极阵列上培养的背根神经节 (DRG) 感觉神经元的细胞外记录情况下评估测定质量的方法。数据转换应用于电生理参数，例如电极和孔尖率，以实现有效的正态假设和用作样本信号的适用性。重要的是，使用转换后的全范围指标，基于中位数和中位数绝对偏差应用了稳健版本的 Z' 因子，以指示测定质量并评估推定药理化合物的命中鉴定。结果 应用适当缩放的数据和稳健的统计数据确保了对数据变化和正态分布近似的不敏感。在计算 Z' 因子时使用对数转换井尖峰率的中值和中值绝对偏差显示值为 0.61，这被认为是“优秀的测定”。已知的伤害感受器特异性电压门控钠离子通道拮抗剂在自发和热刺激条件下在本测定形式中被确定为真正的命中。与现有方法的比较与 HTS 中广泛使用的标准 Z' 因子相比，本方法展示了大的信号动态范围和对数据变化的敏感性降低。结论 总体而言，本研究为利用微电极阵列上的成人 DRG 神经元实施 HCS 平台提供了统计基础。