标题： 大量细胞特异性动作电位模型，用于复制兔心室肌细胞电压的荧光记录 显示英文标题

标题： A large population of cell-specific action potential models replicating fluorescence recordings of voltage in rabbit ventricular myocytes

摘要： 最近的高通量实验揭示了在相同条件下，解耦的健康心肌细胞之间存在显著的电生理多样性。为了量化细胞间的变异性，从大量细胞的荧光电压测量中估计了一个广泛认可的心室肌动作电位数学模型中部分参数的值。统计推断得到了近1200个细胞特异的模型变体，这些模型在群体水平上能够再现实验测得的生物标志物范围和分布，并且与早期研究不同，它们在单个细胞的基础上也匹配实验测得的生物标志物值。这个模型群体可以被视为健康兔心室肌细胞表型的一个随机样本。给出了估计参数的单变量和双变量联合边缘分布，并揭示了几种常用电生理生物标志物的参数依赖性。参数值之间相关性较弱，而诸如动作电位持续时间等汇总指标并不强烈依赖于心肌细胞的任何单一电生理特征。我们的结果证明了在大规模下准确且高效拟合整个动作电位波形的可行性。关键词：细胞兴奋性，兔心室肌细胞，荧光电压测量，动作电位波形，微分方程中的参数估计，噪声时间序列 显示英文摘要

摘要： Recent high-throughput experiments unveil substantial electrophysiological diversity among uncoupled healthy myocytes under identical conditions. To quantify inter-cell variability, the values of a subset of the parameters in a well-regarded mathematical model of the action potential of rabbit ventricular myocytes are estimated from fluorescence voltage measurements of a large number of cells. Statistical inference yields a population of nearly 1200 cell-specific model variants that, on a population-level replicate experimentally measured biomarker ranges and distributions, and in contrast to earlier studies, also match experimental biomarker values on a cell-by-cell basis. This model population may be regarded as a random sample from the phenotype of healthy rabbit ventricular myocytes. Uni-variate and bi-variate joint marginal distributions of the estimated parameters are presented, and the parameter dependencies of several commonly utilised electrophysiological biomarkers are revealed. Parameter values are weakly correlated, while summary metrics such as the action potential duration are not strongly dependent on any single electrophysiological characteristic of the myocyte. Our results demonstrate the feasibility of accurately and efficiently fitting entire action potential waveforms at scale. Keywords: cellular excitability, rabbit ventricular myocytes, fluorescence voltage measurements, action potential waveform, parameter estimation in differential equations, noisy time series