Confidence intervals for concentration and brightness from fluorescence fluctuation measurements.
Confidence intervals for concentration and brightness from fluorescence fluctuation measurements.
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荧光波动测量的浓度和亮度的置信区间。
DOI：
10.1016/j.bpj.2012.07.045
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发表时间：
2012
影响因子：
3.4
通讯作者：
Genin,GuyM
中科院分区：
文献类型：
--
作者：
Pryse,KennethM;Rong,Xi;Whisler,JordanA;McConnaughey,WilliamB;Jiang,Yan-Fei;Melnykov,ArtemV;Elson,ElliotL;Genin,GuyM
光子计数直方图（PCH）分析的理论描述了由于通过聚焦的激光束扩散的荧光团群体的荧光波动幅度的分布，并提供了一个严格的框架，通过该框架可以确定荧光团的亮度和浓度。然而，在实践中，只能识别少数组分的亮度和浓度。通过将理论模型非线性最小二乘拟合到从荧光强度波动的记录导出的实验PCH来确定荧光度和浓度。由于模型的固有曲率、所研究系统的特定参数值以及数据中的相对噪声，最优参数集邻域中的χ 2超曲面可以具有不同程度的曲率。由于这种不同的曲率，从最小二乘分析估计的参数具有不同程度的不确定性与他们有关。有几种方法来分配置信区间的参数，但这些方法有不同的效力PCH数据。在这里，我们评估了几种方法来估计PCH数据的置信区间，包括渐近标准误差，似然联合置信区域，似然置信区间，斜校正和加速引导（BCa），和蒙特卡洛残差恢复方法。为了简单起见，我们用一个模型二维膜系统来研究这些，但这些原理也适用于三维溶液中的荧光团扩散。使用模拟荧光波动数据，我们发现BCa方法特别适合于估计PCH分析中的置信区间，而其他几种方法则不太适合。使用BCa方法和额外的模拟波动数据，我们发现，置信区间可以显着减少一个特定的非高斯光束轮廓。
The theory of photon count histogram (PCH) analysis describes the distribution of fluorescence fluctuation amplitudes due to populations of fluorophores diffusing through a focused laser beam and provides a rigorous framework through which the brightnesses and concentrations of the fluorophores can be determined. In practice, however, the brightnesses and concentrations of only a few components can be identified. Brightnesses and concentrations are determined by a nonlinear least-squares fit of a theoretical model to the experimental PCH derived from a record of fluorescence intensity fluctuations. Theχ2hypersurface in the neighborhood of the optimum parameter set can have varying degrees of curvature, due to the intrinsic curvature of the model, the specific parameter values of the system under study, and the relative noise in the data. Because of this varying curvature, parameters estimated from the least-squares analysis have varying degrees of uncertainty associated with them. There are several methods for assigning confidence intervals to the parameters, but these methods have different efficacies for PCH data. Here, we evaluate several approaches to confidence interval estimation for PCH data, including asymptotic standard error, likelihood joint-confidence region, likelihood confidence intervals, skew-corrected and accelerated bootstrap (BCa), and Monte Carlo residual resampling methods. We study these with a model two-dimensional membrane system for simplicity, but the principles are applicable as well to fluorophores diffusing in three-dimensional solution. Using simulated fluorescence fluctuation data, we find the BCa method to be particularly well-suited for estimating confidence intervals in PCH analysis, and several other methods to be less so. Using the BCa method and additional simulated fluctuation data, we find that confidence intervals can be reduced dramatically for a specific non-Gaussian beam profile.
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早年失忆症的情景记忆、语义记忆和程序记忆
影响因子：
2.6
作者：
A. Ostergaard
通讯作者：
A. Ostergaard
影响因子：
2.4
作者：
T. O. Nelson;Colin M. Macleod
通讯作者：
Colin M. Macleod
影响因子：
--
作者：
COBLENTZ, JM;MATTIS, S;KATZMAN, R
通讯作者：
KATZMAN, R
DOI：
10.1037//0278-7393.10.1.164
发表时间：
1984
期刊：
Journal of experimental psychology. Learning, memory, and cognition
影响因子：
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作者：
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通讯作者：
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DOI：
--
发表时间：
1986
期刊：
The Quarterly journal of experimental psychology. A, Human experimental psychology
影响因子：
--
作者：
A. Shimamura
通讯作者：
A. Shimamura