BACKGROUND In neurodegenerative diseases such as Alzheimer's and Parkinson's, excessive irons as well as lactoferrin (Lf), but not transferrin (Tf), have been found in and around the affected regions of the brain. These evidences suggest that lactoferrin plays a critical role during neurodegenerative diseases, although Lf-mediated iron transport across blood-brain barrier (BBB) is negligible compared to that of transferrin in normal condition. However, the kinetics of lactoferrins and lactoferrin-mediated iron transport are still unknown. METHOD To determine the kinetic rate constants of lactoferrin-mediated iron transport through BBB, a mass-action based ordinary differential equation model has been presented. A Bayesian framework is developed to estimate the kinetic rate parameters from posterior probability density functions. The iron transport across BBB is studied by considering both Lf- and Tf-mediated pathways for both normal and pathologic conditions. RESULTS Using the point estimates of kinetic parameters, our model can effectively reproduce the experimental data of iron transport through BBB endothelial cells. The robustness of the model and parameter estimation process are further verified by perturbation of kinetic parameters. Our results show that surge in high-affinity receptor density increases lactoferrin as well as iron in the brain. CONCLUSIONS Due to the lack of a feedback loop such as iron regulatory proteins (IRPs) for lactoferrin, iron can transport to the brain continuously, which might increase brain iron to pathological levels and can contribute to neurodegeneration. GENERAL SIGNIFICANCE This study provides an improved understanding of presence of lactoferrin and iron in the brain during neurodegenerative diseases.

中文翻译：

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贝叶斯推断参数在乳铁蛋白介导的跨血脑屏障的铁运输中的估计。

背景技术在诸如阿尔茨海默氏症和帕金森氏症的神经退行性疾病中，在大脑的受影响区域及其周围发现了过多的铁以及乳铁蛋白（Lf），但未发现转铁蛋白（Tf）。这些证据表明，乳铁蛋白在神经退行性疾病中起关键作用，尽管与正常情况下转铁蛋白相比，Lf介导的跨血脑屏障（BBB）的铁转运可以忽略不计。然而，乳铁蛋白和乳铁蛋白介导的铁转运的动力学仍是未知的。方法为了确定乳铁蛋白介导的铁通过BBB的动力学速率常数，提出了一种基于质量作用的常微分方程模型。贝叶斯框架被开发来从后验概率密度函数估计动力学速率参数。通过同时考虑正常情况和病理情况的Lf和Tf介导的途径研究了跨BBB的铁转运。结果使用动力学参数的点估计，我们的模型可以有效地再现铁通过BBB内皮细胞运输的实验数据。通过动力学参数的扰动进一步验证了模型和参数估计过程的鲁棒性。我们的结果表明，高亲和力受体密度的增加会增加乳铁蛋白以及大脑中的铁。结论由于缺乏反馈环，如乳铁蛋白的铁调节蛋白（IRP），铁可以连续转运到大脑，这可能使脑铁增加到病理水平，并可能导致神经退行性变。