کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
5862080 | 1133772 | 2014 | 14 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Skin sensitization risk assessment model using artificial neural network analysis of data from multiple in vitro assays
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کلمات کلیدی
موضوعات مرتبط
علوم زیستی و بیوفناوری
علوم محیط زیست
بهداشت، سم شناسی و جهش زایی
پیش نمایش صفحه اول مقاله
چکیده انگلیسی
We previously reported that LLNA thresholds could be well predicted by using an artificial neural network (ANN) model, designated iSENS ver.1 (integrating in vitro sensitization tests version 1), to analyze data obtained from two in vitro tests: the human Cell Line Activation Test (h-CLAT) and the SH test. Here, we present a more advanced ANN model, iSENS ver.2, which additionally utilizes the results of antioxidant response element (ARE) assay and the octanol-water partition coefficient (Log P, reflecting lipid solubility and skin absorption). We found a good correlation between predicted LLNA thresholds calculated by iSENS ver.2 and reported values. The predictive performance of iSENS ver.2 was superior to that of iSENS ver.1. We conclude that ANN analysis of data from multiple in vitro assays is a useful approach for risk assessment of chemicals for skin sensitization.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Toxicology in Vitro - Volume 28, Issue 4, June 2014, Pages 626-639
Journal: Toxicology in Vitro - Volume 28, Issue 4, June 2014, Pages 626-639
نویسندگان
Kyoko Tsujita-Inoue, Morihiko Hirota, Takao Ashikaga, Tomomi Atobe, Hirokazu Kouzuki, Setsuya Aiba,