Liquid chromatography (LC) based techniques in combination with mass spectrometry (MS) detection have had a large impact on the development of new pharmaceuticals in the past decades.
A chemical characterization of the major components, namely, triacylglycerols (TAGs), polyphenols, and tocopherols in a Sacha inchi oil derived from cold pressing of the seed, is hereby reported. To tackle such a task, high-performance liquid chromatography in combination with photodiode array (PDA), fluorescence (RF), and mass spectrometry (MS) detection was employed. The latter was interfaced with atmospheric pressure chemical ionization and with electrospray ionization for the analysis of TAGs and polyphenols, respectively, whereas RF detection was tested for the determination of tocopherol content. Furthermore, fatty acid methyl esters (FAMEs) were evaluated by gas chromatography-flame ionization detector. A 93% amount of total fatty acids was represented by unsaturated FAMEs with the greatest percentage represented by linoleic (L) and linolenic (Ln) accounting for approximately 50 and 36%, respectively. The main TAGs (>10%) were represented by LLnL, LnLnLn, and LnLLn; the latter was present in the oil sample at the highest percentage (22.2%). Among tocopherols, γ-tocopherol was detected to be the most abundant component (over 50%). The polyphenolic composition was also investigated, and a total of 15 compounds were positively identified, through the complementary analytical information coming from PDA and MS data. To the best of our knowledge, this is the first report providing a thorough chemical characterization of a Plukenetia volubilis L. oil.
Tuberculosis (TB) is the deadliest infectious disease, and yet accurate diagnostics for the disease are unavailable for many subpopulations. In this study, we investigate the possibility of using human breath for the diagnosis of active TB among TB suspect patients, considering also several risk factors for TB for smokers and those with human immunodeficiency virus (HIV). The analysis of exhaled breath, as an alternative to sputum-dependent tests, has the potential to provide a simple, fast, non-invasive, and readily available diagnostic service that could positively change TB detection. A total of 50 individuals from a clinic in South Africa were included in this pilot study. Human breath has been investigated in the setting of active TB using the thermal desorption-comprehensive two-dimensional gas chromatography-time of flight mass spectrometry methodology and chemometric techniques. From the entire spectrum of volatile metabolites in breath, three machine learning algorithms (support vector machines, partial least squares discriminant analysis, and random forest) to select discriminatory volatile molecules that could potentially be useful for active TB diagnosis were employed. Random forest showed the best overall performance, with sensitivities of 0.82 and 1.00 and specificities of 0.92 and 0.60 in the training and test data respectively. Unsupervised analysis of the compounds implicated by these algorithms suggests that they provide important information to cluster active TB from other patients. These results suggest that developing a non-invasive diagnostic for active TB using patient breath is a potentially rich avenue of research, including among patients with HIV comorbidities.
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