Chaotic neural network algorithm with competitive learning integrated with partial Least Square models for the prediction of the toxicity of fragrances in sanitizers and disinfectants.

This study addresses the need for accurate structural data regarding the toxicity of fragrances in sanitizers and disinfectants. We compare the predictive and descriptive (model stability) potential of multiple linear regression (MLR) and partial least squares (PLS) models optimized through variable selection (VS). A novel hybrid chaotic neural network algorithm with competitive learning (CCLNNA)-PLS modeling strategy can offer specific optimization with satisfactory results, even for a limited dataset. While also exploring the preliminary comparative analysis, the goal is to introduce an adapted novel CCLNNA optimization strategy for VS, inspired by neural networks, along with exploring the influence of the percentage of significant descriptors in the optimization function to enhance the final model's capabilities. We analyzed an available dataset of 24 molecules, incorporating ADMET and PaDEL descriptors as predictor variables, to explore the relationship between the response/target variable (pLC50) and the meticulously optimized set of descriptors. The suitability of the selected PLS models (cross- and external-validated accuracy combined with percentage of significant descriptors at a level equal to or >80 %) underscores the importance of expanding the dataset to amplify the validation protocols, thus enhancing future model reliability and environmental impact.

Allergen content of popular chemical hair relaxers: A product analysis.

BACKGROUND: Chemical hair relaxers are widely utilized by black women, yet little research exists on the allergens present in these products. OBJECTIVE: This study aims to investigate allergen prevalence in the most popular chemical hair relaxers. METHODS: We analysed 41 products from five major retailers, identifying allergens through ingredient lists and comparing them to the 2020 American Contact Dermatitis Group Core allergen series. RESULTS: The most common contact allergens in chemical relaxers include propylene glycol, cetyl steryl alcohol, fragrance, D/L-a-tocopherol, tea tree oil and cocamidopropyl betaine. CONCLUSION: Understanding allergen exposure in products used by individuals with textured hair is needed for managing contact dermatitis in diverse populations. This analysis underscores the presence of potential allergens in hair relaxers, emphasizing the importance of dermatologists' awareness and patient scrutiny of ingredient lists.

Update to RIFM fragrance ingredient safety assessment, 4-hexen-1-ol, 5-methyl-2-(1-methylethenyl)-, CAS registry number 58461-27-1.

4-Hexen-1-ol, 5-methyl-2-(1-methylethenyl)- was evaluated for genotoxicity, repeated dose toxicity, reproductive toxicity, local respiratory toxicity, photoirritation/photoallergenicity, skin sensitization, and environmental safety. Data show that 4-hexen-1-ol, 5-methyl-2-(1-methylethenyl)- is not genotoxic. The repeated dose, reproductive, and local respiratory toxicity endpoints were evaluated using the Threshold of Toxicological Concern (TTC) for a Cramer Class I material, and the exposure to 4-hexen-1-ol, 5-methyl-2-(1-methylethenyl)- is below the TTC (0.03 mg/kg/day, 0.03 mg/kg/day, and 1.4 mg/day, respectively). Data from read-across analog 3-methylbut-3-en-1-ol (CAS # 763-32-6) show that there are no safety concerns for 4-hexen-1-ol, 5-methyl-2-(1-methylethenyl)- for skin sensitization under the current declared levels of use. The photoirritation/photoallergenicity endpoints were evaluated based on ultraviolet/visible (UV/Vis) spectra; 4-hexen-1-ol, 5-methyl-2-(1-methylethenyl)- is not expected to be photoirritating/photoallergenic. The environmental endpoints were evaluated; 4-hexen-1-ol, 5-methyl-2-(1-methylethenyl)- was found not to be Persistent, Bioaccumulative, and Toxic (PBT) as per the International Fragrance Association (IFRA) Environmental Standards, and its risk quotients, based on its current volume of use (VoU) in Europe and North America (i.e., Predicted Environmental Concentration/Predicted No Effect Concentration [PEC/PNEC]), are <1.