Product Details of 930-36-9On November 30, 2022 ,《Machine learning-assisted non-target analysis of a highly complex mixture of possible toxic unsymmetrical dimethylhydrazine transformation products with chromatography-mass spectrometry》 appeared in Chemosphere. The author of the article were Sholokhova, Anastasia Yu.; Grinevich, Oksana I.; Matyushin, Dmitriy D.; Buryak, Aleksey K.. The article conveys some information:
Unsym. dimethylhydrazine (UDMH) is a toxic and environmentally hostile compound that was massively introduced to the environment during previous decades due to its use in the space and rocket industry. The compound forms multiple transformation products, and many of them are as dangerous as UDMH or even more dangerous. The danger includes, but is not limited to, acute toxicity, chronic health hazards, carcinogenicity, and environmental damage. UDMH transformation products are poorly investigated. In this work, the mixture formed by long storage of the waste that contained UDMH was studied. Even a preliminary screening of such a mixture is a complex task. It consists of dozens of compounds, and most of them are missing in chem. and spectral databases. The complete preparative separation of such a mixture is very laborious. We applied several methods of gas chromatog.-mass spectrometry and liquid chromatog.-mass spectrometry, and several machine learning and chemoinformatics methods to make a preliminary but informative screening of the mixture Machine learning allowed predicting retention indexes and mass spectra of candidate structures. The combination of various ion sources and a comparison of the observed with the predicted spectra and retention was used to propose confident structures for 24 compounds It was demonstrated that neither high-resolution mass spectrometry nor mass spectral library matching is enough to elucidate the structures of unknown UDMH transformation products. At the same time, the use of machine learning and a combination of methods significantly improves the identification power. Finally, machine learning was applied to estimate the acute toxicity of the discovered compounds It was shown that many of them are comparable to or even more toxic than UDMH itself. Such an extremely wide and still underestimated variety of easily formed derivatives of UDMH can lead to a significant underestimation of the potential hazard of this compound The experimental part of the paper was very detailed, including the reaction process of 1-Methylpyrazole(cas: 930-36-9Product Details of 930-36-9)
1-Methylpyrazole(cas: 930-36-9) belongs to pyrazoles. Pyrazoles and their related multiring analogs are common elements of a wide variety of bioactive compounds. These ring structures are rare in nature. A consequence of this is that they have previously been thought to be poor moieties to include in potential new drugs. Product Details of 930-36-9
Referemce:
Pyrazole – Wikipedia,
Pyrazoles – an overview | ScienceDirect Topics