细胞计中的可复制性:信号分析及其与不确定性量化的联系
Paul N Patrone1, Matthew DiSalvo1, Anthony J Kearsley1
1National Institute of Standards and Technology, Gaithersburg, MD, United States of America.
PloS one
|December 22, 2023
概括
用于流细胞计的新信号分析技术通过将生物变异与仪器噪声分开来提高数据准确性. 这允许更可靠的细胞测量和双重解卷,减少细胞计数据的不确定性.
科学领域:
- 定量生物学 定量生物学
- 生物物理测量方法
- 分析化学 分析化学
背景情况:
- 传统的细胞计量很难将生物变异性与仪器器件区分开来,这导致了细胞性质量化的不确定性.
- 由于难以评估测量不确定性,现有方法在双重解卷等任务中面临挑战.
- 流量条件和颗粒大小等仪器因素使细胞计中精确的信号解释变得复杂.
研究的目的:
- 开发用于细胞计学的先进信号分析技术,以应对不确定性量化和数据解释方面的挑战.
- 提高在细胞计量测量中区分生物变异与技术变异的能力.
- 为了实现准确的双重解卷和每事件不确定性估计.
主要方法:
- 利用利用尺度转换的信号分析技术来建模和纠正由操作条件引起的信号变形.
- 应用受约束优化以"逆转"信号形状变形,其余值量化可重现性.
- 在微流体细胞计平台上演示了这种方法.
主要成果:
- 成功地将生物标志物表达的变化与流量条件和粒子大小效应分开.
- 与激光查询区域相关的量化可重现性.
- 在信号形状上达到不到2.5%的剩余不确定性,在集成面积中达到不到1%,考虑到仪器和测量和变化.
结论:
- 开发的信号分析方法有效地解释了细胞计量中的仪器诱导的变化.
- 这种方法可以准确地估计每事件的不确定性,并提高细胞计量数据的可靠性.
- 这些技术有助于从多个单元中精确地提取单元并提高整体细胞计量数据的质量.
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