用于扩散给药类器官阵列中表观异质性的仅转运零模型
A transport-only null model for apparent heterogeneity in diffusively dosed organoid arrays
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中文总结 AI 辅助
本研究开发了用于扩散给药肝癌类器官阵列的仅转运零模型，经多类验证显示其可作为评估实测类器官异质性的几何特异性基准。
中文摘要 AI 辅助
即使类器官本质上完全相同，空间转运也会产生表观生物学异质性。我们开发了一种用于扩散给药肝癌类器官阵列的转运-表型零模型，该模型将本体扩散与清除过程，和部分可及的吸附、可逆表面滞留、有效内化以及细胞内状态动力学耦合起来。匹配渐近法将穿孔域问题简化为格林函数系统，而更新预解式则描述了解吸、再吸附和滞留时间效应。在2000个具有局部给药的随机十类器官阵列中，预测的仅转运成熟度变异系数中位数为0.623；单因素设计可将该中位数在0.27至0.86之间变动。在匹配阵列平均暴露量后，分布式给药可将基线变异程度降低约五倍。分析还表明，在保守反射腔室中，解吸会改变摄取时机与分配，但不改变最终总摄取量；要降低总摄取量则需要存在竞争性损失通道。不过，均值相等的滞留规律仍可产生不同的瞬时表型。空间缩减结果已通过完整偏微分方程的有限元解验证，时间重构则通过数值拉普拉斯逆变换验证。最后，大批次定理表明，增加批次大小可对独立过程变异求平均，但无法对共享的线或批次效应求平均。该框架提供了一种特定几何结构的零基准，可用于评估实测类器官异质性。
英文摘要
Spatial transport can create apparent biological heterogeneity even when organoids are intrinsically identical. We develop a transport-to-phenotype null model for diffusively dosed liver-cancer organoid arrays. The model couples bulk diffusion and clearance to partially accessible adsorption, reversible surface residence, productive internalization, and intracellular state dynamics. Matched asymptotics reduce the perforated-domain problem to a Green-function system, while renewal resolvents describe desorption, re-adsorption, and residence-time effects. Across $2000$ random ten-organoid arrays with localized dosing, the predicted transport-only maturation coefficient of variation has median $0.623$; one-factor design changes move this median between $0.27$ and $0.86$. After matching array-mean exposure, distributed dosing reduces the baseline spread approximately fivefold. The analysis also shows that, in a conservative reflecting chamber, desorption changes uptake timing and allocation but not total eventual uptake; reductions in total uptake require a competing loss channel. Residence laws with equal means can nevertheless produce different transient phenotypes. The spatial reduction is verified against finite-element solutions of the full PDE, and the time reconstruction against numerical Laplace inversion. Finally, a large-batch theorem shows that increasing batch size averages independent process variation but not shared line or batch effects. The framework provides a geometry-specific null against which measured organoid heterogeneity can be assessed.
