Directly Mapping the Spatial Distribution of Organic Compounds on Mineral Rock Surfaces by DESI and LAESI Mass Spectrometry Imaging.

Here, we present a new application of desorption electrospray ionization (DESI) and laser ablation electrospray ionization (LAESI) mass spectrometry imaging to assess the spatial location of organic compounds, both polar and nonpolar, directly from rock surfaces. Three carbonaceous rocks collected from an aquatic environment and a berea sandstone subjected to a small-scale oil recovery experiment were analyzed by DESI and LAESI. No rock pretreatment was required before DESI and LAESI analyses. DESI detected and spatially mapped several fatty acids and a disaccharide on the surfaces of carbonaceous rocks, and various nitrogenated and oxygenated compounds on the surfaces of berea sandstone. In contrast, LAESI using a 3.4 µm infrared laser beam was able to detect and map hydrocarbons on the surfaces of all rock samples. Both techniques can be combined to analyze polar and nonpolar compounds. DESI can be used first to detect polar compounds, as it does not destroy the rock surface, and LAESI can then be used to analyze nonpolar analytes, as it destroys a layer of the sample surface. Both techniques have the potential to be used in several scientific areas involving rocks and minerals, such as in the analysis of industry-derived contaminants in aquatic sediments or in small-scale rock-fluid interaction experiments.

Directly transferring pepper constituents to triangular papers for pungency determination by paper spray ionization mass spectrometry.

A method named imprint paper spray ionization mass spectrometry (imprint-PSI-MS) has been developed and employed for the determination of pungency of peppers. A pepper fruit was cut into a triangular shape, deposited onto a triangular paper, and compressed by a homemade press tool aiming to imprint and transfer the pepper constituents onto the paper surface. Subsequently, the triangular paper was submitted to conventional PSI-MS analysis. Twelve peppers were analyzed, ranging from highly pungent to lowly pungent taste. Pepper pungency values from the Scoville scale (in Scoville heat units, SHU) were compared with the ion intensities of the capsaicin and dihydrocapsaicin compounds obtained from the imprint-PSI-MS analysis, and a correlation coefficient of 0.97 was achieved. In addition, the ion intensities of a sugar compound were monitored in all peppers, and the results were compared with the Scoville scale. Low sugar ion intensities were detected in pungent peppers, while high ion intensities were achieved in low-pungent peppers, suggesting that the pepper pungency may be determined by inversely relating pungency to sugar contents. This work demonstrates the utility of the imprint-PSI-MS method to perform rapid qualitative analyses of peppers and estimate the pungency by monitoring the pepper metabolites. Graphical abstract.

Multivariate classification techniques and mass spectrometry as a tool in the screening of patients with fibromyalgia.

Fibromyalgia is a rheumatological disorder that causes chronic pain and other symptomatic conditions such as depression and anxiety. Despite its relevance, the disease still presents a complex diagnosis where the doctor needs to have a correct clinical interpretation of the symptoms. In this context, it is valid to study tools that assist in the screening of this disease, using chemical work techniques such as mass spectroscopy. In this study, an analytical method is proposed to detect individuals with fibromyalgia (n = 20, 10 control samples and 10 samples with fibromyalgia) from blood plasma samples analyzed by mass spectrometry with paper spray ionization and subsequent multivariate classification of the spectral data (unsupervised and supervised), in addition to the treatment of selected variables with possible associations with metabolomics. Exploratory analysis with principal component analysis (PCA) and supervised analysis with successive projections algorithm with linear discriminant analysis (SPA-LDA) showed satisfactory results with 100% accuracy for sample prediction in both groups. This demonstrates that this combination of techniques can be used as a simple, reliable and fast tool in the development of clinical diagnosis of Fibromyalgia.