Search Results (4)

Burnout syndrome, which significantly impacts both individual and societal quality of life, is primarily characterized by three key criteria: depersonalization, emotional exhaustion, and low personal accomplishment, all linked to work-related stress. Purpose: Comparative evaluation of urine metabolite patterns that may discriminate the burnout levels and the effects of night shifts on healthcare professionals. The Maslach Burnout Inventory survey was administered to 64 physicians and nurses working day and night shifts, with scores for each criterion recorded. Methods: Urine samples were collected, and metabolomic patterns were analyzed using UHPLC-QTOF-ESI+-MS technology. This analysis employed both untargeted and semi-targeted metabolomics, coupled with multivariate and ANOVA statistics, utilizing the online Metaboanalyst 6.0 platform. Partial Least Squares Discriminant Analysis (PLSDA) was performed, along with VIP values, Random Forest graphs, and heatmaps based on 79 identified metabolites. These were further complemented by biomarker analysis (AUC ranking) and pathway analysis of metabolic networks. Results: The findings highlighted the biochemical effects of night shifts and their correlation with burnout scores from each dimension. Conclusions: This study demonstrated the involvement of three major metabolic pathways in diagnosing burnout: lipid metabolism, particularly related to steroid hormones (cortisol, cortisone, and androsterone metabolites); energetic metabolism, involving long-chain acylated carnitines as transporters of free fatty acids, which play a role in burnout control; and a third pathway affecting catecholamine metabolism (neurotransmitters derived from tyrosine, such as dopamine, adrenaline, and noradrenaline), as well as tryptophan metabolism (serotonin and melatonin metabolites) and amino acid metabolism (including aspartate, arginine, and valine). Full article

Allergic rhinitis affects millions globally, causing significant discomfort and reducing the quality of life. This study investigates the metabolic alterations in murine mast cells (MC/9) under allergic rhinitis conditions induced by lipopolysaccharide (LPS) stimulation, employing UHPLC-QTOF-MS-based untargeted and targeted metabolomics. The analysis identified 44 significantly regulated metabolites, including histamine, leukotrienes, prostaglandins, thromboxanes, and ceramides. Key metabolic pathways such as arachidonic acid, histidine, and sphingolipid metabolisms were notably modulated. The study further examined the therapeutic effects of triprolidine and zileuton, demonstrating their capacity to reverse LPS-induced metabolic shifts. Triprolidine primarily modulated histidine and sphingolipid metabolism, while zileuton targeted arachidonic acid and sphingolipid metabolism. These findings underscore the utility of metabolomics analysis in elucidating the complex biochemical pathways involved in allergic rhinitis and highlight the potential of metabolomics for evaluating therapeutic interventions. This study enhances our understanding of mast cell metabolism in allergic responses and provides a robust model for assessing the efficacy of anti-allergic agents, paving the way for more effective treatments. Full article

Currently, there is a renewed interest towards the development of plant-based pharmacophores. In this work, 16 extracts prepared from the leaves, twigs, roots and fruits of a hydro-halophyte, Rhizophora mucronata Lam. (Family: Rhizophoraceae), were studied for possible antioxidant activity and the phenolic profiles established. Thereafter, enzymatic inhibitory activities (α-amylase, α-glucosidase, tyrosinase, acetyl- (AChE), butyrylcholinesterase (BChE), lipase, and elastase) were assessed. The total phenolic, flavonoid, phenolic acid, tannin, flavanol and triterpenoid content were estimated using standard assays. An untargeted metabolomics-based approach, based on ultra-high-pressure liquid chromatography coupled to quadrupole-time-of-flight mass spectrometry (UHPLC-QTOF-MS) followed by multivariate statistics, was then used to comprehensively profile and describe the phenolics present. UHPLC-QTOF-MS allowed for putatively annotating 104 phenolic acids, 103 flavonols, 94 flavones, 71 anthocyanins, 66 tyrosols, 29 lignans, 15 alkylphenols and 10 stilbenes in the extracts. Nine strains (Escherichia coli, Pseudomonas aeruginosa, Klebsiella pneumoniae, Methicillin-resistant Staphylococcus aureus (MRSA), Salmonella enteritidis, Sarcina lutea, Proteus mirabilis, Bacillus cereus and Candida albicans) were then used to investigate the antimicrobial properties. The methanolic twig extract exhibited significant reducing potential towards Cu (II)/Cu (I) and Fe (III)/Fe (II) (1336.88 ± 15.70 and 710.18 ± 21.04 mg TE/g, respectively) and was the most potent DPPH radical scavenger (807.07 ± 6.83 mg TE/g). Additionally, the methanolic twig extract showed significant inhibition against most targeted enzymes. Anti-microbial results showed that all extracts were active against MRSA. Multivariate analysis demonstrated that the phenolic profile of ethyl acetate extracts and leaves were the two most discriminative parameters in terms of solvents and organs, respectively. The present findings indicated that R. mucronata may be further explored for the management/prevention of oxidative stress, neurodegenerative complications and hyperpigmentation. Full article

The flower buds of three Panax species (PGF: flower bud of P. ginseng; PQF: flower bud of P. quinquefolius; PNF: flower bud of P. notoginseng), widely consumed as healthcare products, are easily confused particularly in the extracts or traditional Chinese medicine (TCM) formulae. We are aimed to develop an untargeted metabolomics approach, by ultra-high performance liquid chromatography/ion mobility-quadrupole time-of-flight mass spectrometry (UHPLC/IM-QTOF-MS) to unveil the chemical markers diagnostic for the differentiation of PGF, PQF, and PNF. Key parameters affecting chromatographic separation and MS detection were optimized in sequence. Forty-two batches of flower bud samples were analyzed in negative high-definition MS^E (HDMS^E; enabling three-dimensional separations). Efficient metabolomics data processing was performed by Progenesis QI (Waters, Milford, MA, USA), while pattern-recognition chemometrics was applied for species classification and potential markers discovery. Reference compounds comparison, analysis of both HDMS^E and targeted MS/MS data, and retrieval of an in-house ginsenoside library, were simultaneously utilized for the identification of discovered potential markers. Satisfactory conditions for metabolite profiling were achieved on a BEH Shield RP18 column and Vion™ IMS-QTOF instrument (Waters; by setting the capillary voltage of 1.0 kV and the cone of voltage 20 V) within 37 min. A total of 32 components were identified as the potential markers, of which Rb3, Ra1, isomer of m-Rc/m-Rb2/m-Rb3, isomer of Ra1/Ra2, Rb1, and isomer of Ra3, were the most important for differentiating among PGF, PQF, and PNF. Conclusively, UHPLC/IM-QTOF-MS-based metabolomics is a powerful tool for the authentication of TCM at the metabolome level. Full article