半抗原前致敏剂鉴定及效价分类的三培养体系。

TECHNOLOGY Pub Date : 2018-06-01 Epub Date: 2018-06-29 DOI:10.1142/S233954781850005X
Serom Lee, Talia Greenstein, Lingting Shi, Tim Maguire, Rene Schloss, Martin Yarmush
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引用次数: 6

摘要

过敏性接触性皮炎(ACD)是一种影响15-20%普通人群的炎症性疾病,需要准确的化学品风险评估筛查方法。然而,大多数方法很难预测前半抗原和前半抗原致敏剂,这需要在诱导致敏之前进行非生物或代谢转化。我们开发了一个由mutz -3衍生的朗格汉斯细胞、HaCaT角质形成细胞和原代真皮成纤维细胞组成的三培养系统,以模拟皮肤致敏的细胞和代谢环境。一组非致敏剂和致敏剂进行了测试,并对分泌组进行了评估。使用支持向量机(SVM)识别最具预测性的敏化特征,并使用分类树识别统计阈值来预测敏化剂效力。SVM使用排名前3位的生物标志物(IL-8、MIP-1β和GM-CSF)计算出91%的三培养预测准确率,并提高了前半抗原和前半抗原的检测。这种体外实验与计算机数据分析相结合,提供了一种有前途的方法,并为增强ACD敏化剂筛选提供了多度量分析的可能性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Tri-culture system for pro-hapten sensitizer identification and potency classification.

Tri-culture system for pro-hapten sensitizer identification and potency classification.

Allergic contact dermatitis (ACD) is an inflammatory disease that impacts 15-20% of the general population and accurate screening methods for chemical risk assessment are needed. However, most approaches poorly predict pre- and pro-hapten sensitizers, which require abiotic or metabolic conversion prior to inducing sensitization. We developed a tri-culture system comprised of MUTZ-3-derived Langerhans cells, HaCaT keratinocytes, and primary dermal fibroblasts to mimic the cellular and metabolic environments of skin sensitization. A panel of non-sensitizers and sensitizers was tested and the secretome was evaluated. A support vector machine (SVM) was used to identify the most predictive sensitization signature and classification trees identified statistical thresholds to predict sensitizer potency. The SVM computed 91% tri-culture prediction accuracy using the top 3 ranking biomarkers (IL-8, MIP-1β, and GM-CSF) and improved the detection of pre- and pro-haptens. This in vitro assay combined with in silico data analysis presents a promising approach and offers the possibility of multi-metric analysis for enhanced ACD sensitizer screening.

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来源期刊
TECHNOLOGY
TECHNOLOGY ENGINEERING, MULTIDISCIPLINARY-
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