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Integration of MUTZ-Langerhans cells into a 3D full-thickness skin equivalent and influences of serum reduction and undefined medium supplements on differentiation.
Toxicol In Vitro
January 2025
Henkel AG & Co. KGaA, Düsseldorf, Germany. Electronic address:
The MUTZ-3 cell line is a surrogate for Langerhans cells (LCs) employed in New Approach Methodologies for assessing the skin sensitizing potential of chemicals. However, MUTZ-3 cells must first be differentiated to achieve the LC-typical phenotype. As all protocols use high fetal calf serum (FCS) concentrations, we aimed at reducing, or even replacing FCS, while maintaining MUTZ-LC characteristics.
View Article and Find Full Text PDFQuantum-Mechanics Calculations Elucidate Skin-Sensitizing Pharmaceutical Compounds.
Chem Res Toxicol
August 2024
SafeBridge Regulatory & Life Sciences Group, 330 Seventh Ave #2001, New York, New York 10001, United States.
Skin sensitization is a critical end point in occupational toxicology that necessitates the use of fast, accurate, and affordable models to aid in establishing handling guidance for worker protection. While many in silico models have been developed, the scarcity of reliable data for active pharmaceutical ingredients (APIs) and their intermediates (together regarded as pharmaceutical compounds) brings into question the reliability of these tools, which are largely constructed using publicly available nonspecialty chemicals. Here, we present the quantum-mechanical (QM) Computer-Aided Discovery and REdesign (CADRE) model, which was developed with the bioactive and structurally complex chemical space in mind by relying on the fundamentals of chemical interactions in key events (versus structural attributes of training-set data).
View Article and Find Full Text PDFHealth risks from exposure to chemicals in clothing - Non-regulated halogenated aromatic compounds.
Chemosphere
September 2024
Department of Materials and Environmental Chemistry, Stockholm University, SE-106 91, Stockholm, Sweden. Electronic address:
The objective of the present study was to investigate some commonly detected halogenated textile pollutants for their bioavailability and hazardous properties. Release into artificial sweat and skin absorption in vitro were examined as well as mutagenic effects by Ames test, and skin-sensitizing properties from a peptide reactivity assay combined with a cell test. All investigated compounds were shown to migrate from the textile into sweat and be absorbed by the skin, although to a different extent.
View Article and Find Full Text PDFViCEKb: Vitiligo-linked Chemical Exposome Knowledgebase.
Sci Total Environ
February 2024
The Institute of Mathematical Sciences (IMSc), Chennai, India; Homi Bhabha National Institute (HBNI), Mumbai, India. Electronic address:
Vitiligo is a complex disease wherein the environmental factors, in conjunction with the underlying genetic predispositions, trigger the autoimmune destruction of melanocytes, ultimately leading to depigmented patches on the skin. While genetic factors have been extensively studied, the knowledge on environmental triggers remains sparse and less understood. To address this knowledge gap, we present the first comprehensive knowledgebase of vitiligo-triggering chemicals namely, Vitiligo-linked Chemical Exposome Knowledgebase (ViCEKb).
View Article and Find Full Text PDFPrediction-Inspired Intelligent Training for the Development of Classification Read-across Structure-Activity Relationship (c-RASAR) Models for Organic Skin Sensitizers: Assessment of Classification Error Rate from Novel Similarity Coefficients.
Chem Res Toxicol
September 2023
Drug Theoretics and Cheminformatics Laboratory, Department of Pharmaceutical Technology, Jadavpur University, Kolkata 700 032, India.
The advancements in the field of cheminformatics have led to a reduction in animal testing to estimate the activity, property, and toxicity of query chemicals. Read-across structure-activity relationship (RASAR) is an emerging concept that utilizes various similarity functions derived from chemical information to develop highly predictive models. Unlike quantitative structure-activity relationship (QSAR) models, RASAR descriptors of a query compound are computed from its close congeners instead of the compound itself, thus targeting predictions in the model training phase.
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