Skin irritation and sensitization potential of oxidative hair dye substances evaluated with in vitro, in chemico and in silico test methods

Park, Hanseul; Hwang, Jee Hyun; Han, Ji Seok; Lee, Byoung‐Seok; Kim, Yong Bum; Joo, Kyung Mi; Choi, Min-Seok; Cho, Sun A.; Kim, Bae Hwan; Lim, Kyung Min

doi:10.1016/j.fct.2018.09.017

Cited by 11 publications

(2 citation statements)

References 29 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The obtained metal consists of Co 0 with a cubic structure as revealed by XRD analysis presented in Fig. 5-A Para-aminoaniline is an aromatic diamine used in many application including the synthesis of Kevlar [59] and dyes matrices [60], [61], while aminophenols are biologically active and are used in the pharmaceutical industry [62].…”

Section: A Aerogels Characterizationmentioning

confidence: 99%

Comprehensive preparation and catalytic activities of Co/TEMPO-cellulose nanocomposites: A promising green catalyst

Idrissi

Belachemi

Merle³

et al. 2022

Carbohydrate Polymers

View full text Add to dashboard Cite

Section: A Aerogels Characterizationmentioning

confidence: 99%

Comprehensive preparation and catalytic activities of Co/TEMPO-cellulose nanocomposites: A promising green catalyst

Idrissi

Belachemi

Merle³

et al. 2022

Carbohydrate Polymers

View full text Add to dashboard Cite

“…Skin sensitizers are chemicals capable of inducing skin hypersensitivity [ 1 ], a condition that can progress to allergic contact dermatitis [ 2 ]. Consequently, the identification and regulation of skin sensitizers are imperative in compliance with chemicals and cosmetics regulations [ 3 ].…”

Section: Introductionmentioning

confidence: 99%

Integration of the Natural Language Processing of Structural Information Simplified Molecular-Input Line-Entry System Can Improve the In Vitro Prediction of Human Skin Sensitizers

Kwon,

Kim,

Lim

et al. 2024

Toxics

Self Cite

View full text Add to dashboard Cite

Natural language processing (NLP) technology has recently used to predict substance properties based on their Simplified Molecular-Input Line-Entry System (SMILES). We aimed to develop a model predicting human skin sensitizers by integrating text features derived from SMILES with in vitro test outcomes. The dataset on SMILES, physicochemical properties, in vitro tests (DPRA, KeratinoSensTM, h-CLAT, and SENS-IS assays), and human potency categories for 122 substances sourced from the Cosmetics Europe database. The ChemBERTa model was employed to analyze the SMILES of substances. The last hidden layer embedding of ChemBERTa was tested with other features. Given the modest dataset size, we trained five XGBoost models using subsets of the training data, and subsequently employed bagging to create the final model. Notably, the features computed from SMILES played a pivotal role in the model for distinguishing sensitizers and non-sensitizers. The final model demonstrated a classification accuracy of 80% and an AUC-ROC of 0.82, effectively discriminating sensitizers from non-sensitizers. Furthermore, the model exhibited an accuracy of 82% and an AUC-ROC of 0.82 in classifying strong and weak sensitizers. In summary, we demonstrated that the integration of NLP of SMILES with in vitro test results can enhance the prediction of health hazard associated with chemicals.

show abstract

Review and Analysis of Biological Tests on Nanomaterials to be Applied in Biological Areas

Cuéllar-Gaona

Ibarra-Alonso

Reyna-Martínez

et al. 2023

Green-Based Nanocomposite Materials and Applications

View full text Add to dashboard Cite

Skin irritation and sensitization potential of oxidative hair dye substances evaluated with in vitro, in chemico and in silico test methods

Cited by 11 publications

References 29 publications

Comprehensive preparation and catalytic activities of Co/TEMPO-cellulose nanocomposites: A promising green catalyst

Comprehensive preparation and catalytic activities of Co/TEMPO-cellulose nanocomposites: A promising green catalyst

Integration of the Natural Language Processing of Structural Information Simplified Molecular-Input Line-Entry System Can Improve the In Vitro Prediction of Human Skin Sensitizers

Review and Analysis of Biological Tests on Nanomaterials to be Applied in Biological Areas

Contact Info

Product

Resources

About