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Transport Rankings of Non-Steroidal Antiinflammatory Drugs across Blood-Brain Barrier In Vitro Models

机译:非甾体类抗炎药跨血脑屏障体外模型的运输排名

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摘要

The aim of this work was to conduct a comprehensive study about the transport properties of NSAIDs across the blood-brain barrier (BBB) in vitro. Transport studies with celecoxib, diclofenac, ibuprofen, meloxicam, piroxicam and tenoxicam were accomplished across Transwell models based on cell line PBMEC/C1-2, ECV304 or primary rat brain endothelial cells. Single as well as group substance studies were carried out. In group studies substance group compositions, transport medium and serum content were varied, transport inhibitors verapamil and probenecid were added. Resulted permeability coefficients were compared and normalized to internal standards diazepam and carboxyfluorescein. Transport rankings of NSAIDs across each model were obtained. Single substance studies showed similar rankings as corresponding group studies across PBMEC/C1-2 or ECV304 cell layers. Serum content, glioma conditioned medium and inhibitors probenecid and verapamil influenced resulted permeability significantly. Basic differences of transport properties of the investigated NSAIDs were similar comparing all three in vitro BBB models. Different substance combinations in the group studies and addition of probenecid and verapamil suggested that transporter proteins are involved in the transport of every tested NSAID. Results especially underlined the importance of same experimental conditions (transport medium, serum content, species origin, cell line) for proper data comparison.
机译:这项工作的目的是对NSAIDs在体外跨血脑屏障(BBB)的转运特性进行全面研究。在基于细胞系PBMEC / C1-2,ECV304或原代大鼠脑内皮细胞的Transwell模型中完成了塞来昔布,双氯芬酸,布洛芬,美洛昔康,吡罗昔康和替诺昔康的转运研究。进行了单一和小组物质研究。在组研究中,物质组的组成,转运介质和血清含量各不相同,加入了转运抑制剂维拉帕米和丙磺舒。比较所得的渗透系数并将其标准化为内标地西epa和羧基荧光素。获得了每个模型中NSAID的转运排名。在PBMEC / C1-2或ECV304细胞层上,单一物质研究显示出与相应的小组研究相似的排名。血清含量,神经胶质瘤条件培养基以及丙磺舒和维拉帕米抑制剂均会显着影响最终通透性。比较所有三种体外BBB模型,所研究的NSAID转运特性的基本差异相似。小组研究中不同的物质组合以及丙磺舒和维拉帕米的添加表明转运蛋白与每种受试NSAID的转运有关。结果尤其强调了相同实验条件(运输培养基,血清含量,物种起源,细胞系)对于正确数据比较的重要性。

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