Assessment of the skin sensitization potential of fragrance ingredients using the U-SENS™ assay

敏化 生物信息学 皮肤致敏 化学 局部淋巴结试验 毒理 医学 生物化学 生物 免疫学 基因
作者
Isabelle Lee,Mihwa Na,Devin O’Brien,R. Parakhia,Nathalie Alépée,Walter M.A. Westerink,Irene Eurlings,A.M. Api
出处
期刊:Toxicology in Vitro [Elsevier BV]
卷期号:79: 105298-105298 被引量:1
标识
DOI:10.1016/j.tiv.2021.105298
摘要

The U-SENS™ assay was developed to address the third key event of the skin sensitization adverse outcome pathway (AOP) and is described in OECD test guideline 442E, Annex II. A dataset of 68 fragrance ingredients comprised of 7 non-sensitizers and 61 sensitizers was tested in the U-SENS™ assay. The potential for fragrance ingredients to activate dendritic cells, measured by U-SENS™, was compared to the sensitization potential determined by weight of evidence (WoE) from historical data. Of the non-sensitizers, 4 induced CD86 cell surface marker ≥1.5-fold while 3 did not. Of the sensitizers, 50 were predicted to be positive in U-SENS™, while the remaining 11 were negative. Positive and negative predictive values (PPV and NPV) of U-SENS™ were 93% and 21%, respectively. No specific chemical property evaluated could account for misclassified ingredients. Assessment of parent and metabolite protein binding alerts in silico suggests that parent chemical metabolism may play a role in CD86 activation in U-SENS™. Combining the U-SENS™ assay in a "2 out of 3" defined approach with the direct peptide reactivity assay (DPRA) and KeratinoSens™ predicted sensitization hazard with PPV and NPV of 97% and 24%, respectively. Combining complementary in silico and in vitro methods to the U-SENS™ assay should be integrated to define the hazard classification of fragrance ingredients, since a single NAM cannot replace animal-based methods.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
1秒前
1秒前
迅速忆雪应助li采纳,获得10
2秒前
LJR发布了新的文献求助10
2秒前
LLL发布了新的文献求助10
3秒前
3秒前
Fafa给egcb的求助进行了留言
5秒前
LeonPan完成签到,获得积分10
5秒前
5秒前
WYNN094完成签到,获得积分10
5秒前
5秒前
今后应助Haixia采纳,获得30
8秒前
hrpppp完成签到,获得积分10
8秒前
心灵美映之完成签到 ,获得积分10
9秒前
CodeCraft应助hrpppp采纳,获得10
11秒前
1234完成签到,获得积分20
11秒前
科目三应助幸福的鞋垫采纳,获得10
12秒前
秋秋发布了新的文献求助10
13秒前
思源应助FF采纳,获得10
14秒前
14秒前
科研通AI6.3应助麦满分采纳,获得10
16秒前
俞安珊完成签到,获得积分10
17秒前
LJR完成签到,获得积分10
18秒前
RT驳回了prigogin应助
21秒前
竹叶青发布了新的文献求助10
22秒前
22秒前
22336应助pinxin采纳,获得20
22秒前
lewellyn完成签到,获得积分10
23秒前
23秒前
23秒前
英姑应助彭仲康采纳,获得10
23秒前
爆米花应助彭仲康采纳,获得10
24秒前
24秒前
25秒前
25秒前
25秒前
英姑应助科研通管家采纳,获得10
25秒前
woshi123应助科研通管家采纳,获得10
25秒前
852应助科研通管家采纳,获得10
25秒前
英俊的铭应助科研通管家采纳,获得10
26秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
Discerning Saints: Moralization of Intrinsic Motivation and Selective Prosociality at Work 500
Handbuch Trainingswissenschaft – Trainingslehre 500
Additive Manufacturing Design and Applications (ASM Handbook, Volume 24A) 500
Variations: A More Diverse Picture of Contemporary Art 400
Induction Heating and Heat Treatment (ASM Handbook, Volume 4C) 300
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7590513
求助须知:如何正确求助?哪些是违规求助? 9167905
关于积分的说明 19623414
捐赠科研通 7169567
什么是DOI,文献DOI怎么找? 3267336
关于科研通互助平台的介绍 2432192
邀请新用户注册赠送积分活动 2259540