On September 21, 2020, Zarini, Daniele; Sangion, Alessandro; Ferri, Emanuele; Caruso, Enrico; Zucchi, Sara; Orro, Alessandro; Papa, Ester published an article.Related Products of 34413-35-9 The title of the article was Are In Silico Approaches Applicable As a First Step for the Prediction of e-Liquid Toxicity in e-Cigarettes?. And the article contained the following:
Recent studies have raised concerns about e-cigarette liquid inhalation toxicity by reporting the presence of chems. with European Union CLP toxicity classification. In this scenario, the regulatory context is still developing and is not yet up to date with vaping current reality. Due to the paucity of toxicol. studies, robust data regarding which components in tent. In this study we applied computational methods for studied chems. as a useful tool for predicting the acute toxicity of chems. contained in e-liquids The purpose of t the potential health concerns associated with e-liquid ingredients, (b) to prioritize e-liquid ingredients by calculating the e-tox index, and (c) to estimate acute toxicity of e-liquid mixtures QSAR models were generated using QSARINS software to fill the acute toxicity data gap of 264 e-liquid ingredients. As a second step, the potential acute toxicity of e-liquids mixtures was evaluated. Our preliminary data suggest that a computational approa serve as a roadmap to enable regulatory bodies to better regulate e-liquid composition and to contribute to consumer health protection. The experimental process involved the reaction of 5,6,7,8-Tetrahydroquinoxaline(cas: 34413-35-9).Related Products of 34413-35-9
The Article related to toxicity electronic cigarette liquid qsar model, Toxicology: Methods (Including Analysis) and other aspects.Related Products of 34413-35-9
Referemce:
Quinoxaline – Wikipedia,
Quinoxaline | C8H6N2 | ChemSpider