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In this work, the feasibility of negative-ion atmospheric pressure chemical ionisation (APCI) and atmospheric pressure photoionisation (APPI) for ultra-high-performance liquid chromatography tandem mass spectrometry (UHPLC-MS/MS) determination of fluorotelomer alcohols (FTOHs), fluorinated octanesulfonamides (FOSAs) and fluorinated octanesulfonamido-ethanols (FOSEs) was evaluated. The study of the effect of mobile phase composition on the atmospheric pressure ionisation of these compounds indicated that methanol/water mixtures provided the best responses in APCI, while acetonitrile/water with a post-column addition of toluene as dopant was the most appropriated mixture in APPI. Under the optimal working conditions, most of the target compounds produced the ion [M-H] as base peak, although in-source collision-induced dissociation fragment ions in APCI and APPI and superoxide adduct ions [M+O] in APPI were also present. These ions proved to be more useful as precursor ions for MS/MS determination than the adduct ions generated in electrospray. Although the UHPLC-APCI-MS/MS method allowed the determination of these semi-volatile compounds at low concentration levels, the analysis by UHPLC-APPI-MS/MS provided the lowest limits of detection and it was applied to the analysis of water samples in combination with solid-phase extraction. Quality parameters demonstrated the good performance of the proposed method, providing low method limits of detection (0.3-6 ng L), good precision (RSD % < 5%) and an accurate quantification (relative error % < 14%). Among the river water samples analysed by the developed method, 4:2 FTOH and N-EtFOSA were determined at 30 and 780 ng L, respectively.

Because of the central role of fatty acids in biological systems, their accurate quantification is still important. However, the impact of the complex matrix of biologically and clinically relevant samples such as plasma, serum, or cells makes the analysis still challenging, especially, when free non-esterified fatty acids have to be quantified. Here we developed and characterized a novel GC–MS method using pentafluorobenzyl bromide as a derivatization agent and compared different ionization techniques such as atmospheric pressure chemical ionization (APCI), atmospheric pressure chemical photoionization (APPI), and negative ion chemical ionization (NICI). The GC-APCI-MS showed the lowest limits of detection from 30 to 300 nM for a broad range of fatty acids and a similar response for various fatty acids from a chain length of 10 to 20 carbon atoms. This allows the number of internal standards necessary for accurate quantification to be reduced. Moreover, the use of pentafluorobenzyl bromide allows the direct derivatization of free fatty acids making them accessible for GC–MS analysis without labor-intense sample pretreatment.

Cannabis is an ancient plant that has been used for therapeutic and recreational purposes. Nowadays, industrial hemp, a variety with low concentration of the psychoactive cannabinoid Δ9-tetrahydrocannabinol (THC) and high concentration of non-psychoactive cannabinoids, is getting more and more interest in the food, pharmaceutical, and cosmetic industry. However, cannabis not only contains cannabinoids as bioactive components but also other metabolites like terpenes and phenolic compounds, and the content of these interesting secondary metabolites greatly differs with the genetic variety of the plant. Due to the huge complexity of composition of the cannabis matrix, in this work, a comprehensive two-dimensional liquid chromatography (LC × LC) method has been developed as a very power separation technique coupling a pentafluorophenyl (PFP) and a C18 in the first and second dimensions. Two industrial hemp strains (cookie and gelato) were analyzed to determine the difference in their content of cannabinoids and phenolic compounds. To do this, a new demodulation process was applied for the first time to transform 2D raw data into 1D data which allowed carrying out the chemometric analysis needed to determine the statistical differences between the hemp strains. The cookie strain presented a total of 41 cannabinoid markers, while the gelato strain presented more representative phenolic compounds, in total 24 phenolic compounds were detected as potential markers of this sample. These differences in the chemical composition could determine the industrial destiny of the different hemp strains. Graphical abstract

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