AI 中文总结
该研究针对体外细胞活力实验有噪声的问题，提出结合最小统计分析与确定性近似的数学框架，通过参数化细胞活力模型量化喹啉酸对三种细胞的抗增殖作用，准确描述抑制情况并给出IC50值表达式，为分析相关数据提供实用方法。
AI 中文摘要
本文提出了一个强大的数学框架，用于从有噪声的体外细胞活力实验中量化抗增殖作用。通过参数化细胞活力模型，利用结晶紫测定法测量喹啉酸对B16-F10小鼠黑色素瘤、RAW264.7巨噬细胞和HaCaT角质形成细胞生长抑制的实验数据来演示该方法。实验数据具有很大变异性且违反经典推断统计的独立性假设。所提出的框架将最小统计分析（包括无模型置信区间和合并重复内变异性）与基于最小二乘法拟合实验均值和留一重复交叉验证的确定性近似相结合。三种细胞类型由共同机制框架描述，但各需不同参数化来捕捉其对喹啉酸的特征反应。所得一参数和两参数模型准确描述了剂量和时间依赖性抑制，预测误差接近固有实验变异性。模型还给出了时间依赖性IC50值的显式表达式，能够可靠预测达到特定生长抑制水平所需的抑制剂浓度。该框架为分析有噪声的临床前细胞活力数据提供了实用且强大的方法，可轻松扩展到其他抗增殖剂和实验系统。
英文摘要
This paper presents a robust mathematical framework for quantifying antiproliferative effects from noisy in vitro cell viability experiments. The methodology is demonstrated using crystal violet assay measurements of quinolinic acid-induced growth inhibition in B16-F10 murine melanoma, RAW264.7 macrophage, and HaCaT keratinocyte cells through parametric cell viability models. Experimental data exhibited substantial variability and violated the independence assumptions underlying classical inferential statistics. To address these challenges, the proposed framework combines minimal statistical analysis, comprising model-free confidence intervals and pooled within-replicate variability, with deterministic approximation based on least-squares fitting to experimental means and leave-one-replicate-out cross-validation. While all three cell types were described by a common mechanistic framework, each required a distinct parameterisation to capture its characteristic response to quinolinic acid. The resulting one- and two-parameter models accurately described dose- and time-dependent inhibition, with predictive errors close to the intrinsic experimental variability. The models also yielded explicit expressions for time-dependent IC50 values, enabling reliable prediction of inhibitor concentrations required to achieve specified levels of growth inhibition. The proposed framework provides a practical and robust approach for analysing noisy preclinical cell viability data and can be readily extended to other antiproliferative agents and experimental systems.
