AIMC Topic: Gas Chromatography-Mass Spectrometry
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Machine learning-assisted non-target analysis of a highly complex mixture of possible toxic unsymmetrical dimethylhydrazine transformation products with chromatography-mass spectrometry.
Chemosphere
Jul 18, 2022
Unsymmetrical 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 transformatio...
Fully automatic resolution of untargeted GC-MS data with deep learning assistance.
Talanta
Mar 26, 2022
DeepResolution (Deep learning-assisted multivariate curve Resolution) has been proposed to solve the co-eluting problem for GC-MS data. However, DeepResolution models must be retrained when encountering unknown components, which is undoubtedly time-c...
Pyrolytic characteristics of fine materials from municipal solid waste using TG-FTIR, Py-GC/MS, and deep learning approach: Kinetics, thermodynamics, and gaseous products distribution.
Chemosphere
Jan 5, 2022
Fine materials (FM) from municipal solid waste (MSW) classification require disposal, and pyrolysis is a feasible method for the treatments. Hence, the behavior, kinetics, and products of FM pyrolysis were investigated in this study. A deep learning ...
Quantitative analysis of fragrance allergens in various matrixes of cosmetics by liquid-liquid extraction and GC-MS.
Journal of food and drug analysis
Dec 15, 2021
Fragrances are the most common chemicals in cosmetics to which people expose every day. However, the unwanted allergic reactions such as contact dermatitis caused by direct contact with fragrances may happen. In Directive 2003/15/EC of the EU, cosmet...
Application of Artificial Neural Network Based on Traditional Detection and GC-MS in Prediction of Free Radicals in Thermal Oxidation of Vegetable Oil.
Molecules (Basel, Switzerland)
Nov 6, 2021
In this study, electron paramagnetic resonance (EPR) and gas chromatography-mass spectrometry (GC-MS) techniques were applied to reveal the variation of lipid free radicals and oxidized volatile products of four oils in the thermal process. The EPR r...
Machine learning approaches to predict gestational age in normal and complicated pregnancies via urinary metabolomics analysis.
Scientific reports
Sep 7, 2021
The elucidation of dynamic metabolomic changes during gestation is particularly important for the development of methods to evaluate pregnancy status or achieve earlier detection of pregnancy-related complications. Some studies have constructed model...
Assessment of Volatile Aromatic Compounds in Smoke Tainted Cabernet Sauvignon Wines Using a Low-Cost E-Nose and Machine Learning Modelling.
Molecules (Basel, Switzerland)
Aug 23, 2021
Wine aroma is an important quality trait in wine, influenced by its volatile compounds. Many factors can affect the composition and levels (concentration) of volatile aromatic compounds, including the water status of grapevines, canopy management, an...
Nasopharyngeal metabolomics and machine learning approach for the diagnosis of influenza.
EBioMedicine
Aug 19, 2021
BACKGROUND: Respiratory virus infections are significant causes of morbidity and mortality, and may induce host metabolite alterations by infecting respiratory epithelial cells. We investigated the use of liquid chromatography quadrupole time-of-flig...
Deep-Learning-Assisted multivariate curve resolution.
Journal of chromatography. A
Nov 13, 2020
Gas chromatography-mass spectrometry (GC-MS) is one of the major platforms for analyzing volatile compounds in complex samples. However, automatic and accurate extraction of qualitative and quantitative information is still challenging when analyzing...
Presence of emerging organic contaminants and solvents in schools using passive sampling.
The Science of the total environment
Oct 13, 2020
In this study, we report on the applicability of passive sampling with Carbopack X adsorbent tubes followed by thermal desorption gas-chromatography-mass spectrometry (TD-GC-MS) to monitor the concentrations of emerging organic contaminants (EOCs) an...
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