The integration of plant metabolomics to support preharvest fruit development studies can provide important insights into the biochemical mechanisms involved and lately support producers on harvesting management. A metabolomic-based strategy for fingerprinting of volatile terpenoids and norisoprenoids from Sambucus nigra L. berries from three cultivars, through ripening, was established. From 42 monoterpenic, 20 sesquiterpenic, and 14 norisoprenoid compounds, 48 compounds are reported for the first time as S. nigra berries components. Chemometric tools revealed that ripening was the factor that influenced more the volatile fraction profile and physicochemical parameters (pH, TS, and TSS), followed by cultivar. For the unripe stages, a higher overall content of the studied metabolites was observed, which gradually decreased over the ripening stages, being consistent for the three cultivars. These trends were mainly ruled by limonene, p-cymene, aromadendrene, β-caryophyllene, and dihydroedulan, which might therefore be used by producers as an additional simple decision making tool in conjunction with physicochemical parameters.
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http://dx.doi.org/10.1021/acs.jafc.6b00984 | DOI Listing |
Metabolites
February 2024
Laboratory of Food Development for Special Health Purpose and Education (DAFEE), Nutrition Institute Josué de Castro (INJC), Federal University of Rio de Janeiro, Rio de Janeiro 21941-902, Rio de Janeiro, Brazil.
A competitive volleyball game is a highly metabolic and physically demanding event for professional players. This study aimed to investigate whether a single game at the end of a preseason promotes changes in the biochemical markers of physical exercise responses and the metabolomic profile of professional volleyball players. This cross-sectional study included 13 male Brazilian professional volleyball players.
View Article and Find Full Text PDFJ Pharm Biomed Anal
May 2024
School of Pharmacy, Shenyang Pharmaceutical University, Benxi, Liaoning 117004, P.R. China. Electronic address:
Gushudan (GSD) was a traditional Chinese prescription with the remarkable effect of kidney-tonifying and bone-strengthening. However, the potential prevention mechanisms of the GSD on kidney-yang-deficiency-syndrome (KYDS) and its regulation on gut microbe metabolism still need to be further systematically investigated. This study established untargeted urinary metabolomics based on RP/HILIC-UHPLC-Q-Orbitrap HRMS and combined with multivariate statistical analysis to discover differential metabolites and key metabolic pathways.
View Article and Find Full Text PDFCancers (Basel)
December 2023
Oncologic Pathology Group, Biomedical Research Institute of Lleida (IRBLleida), University of Lleida, Av. Rovira Roure 80, 25198 Lleida, Spain.
Transl Pediatr
December 2022
Hongqiao International Institute of Medicine, Tongren Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Background: Phototherapy is a recommended method for the treatment of neonatal hyperbilirubinemia. However, biomarkers for predicting the more effective duration of phototherapy prior to treatment are lacking. Therefore, we aimed to determine novel predictors for the timing of phototherapy from the perspective of metabolomics.
View Article and Find Full Text PDFJ Agric Food Chem
May 2022
Methods and Application of Food Composition Laboratory, Beltsville Human Nutrition Research Center, Agricultural Research Services, United States Department of Agriculture, Beltsville, Maryland 20705-2350, United States.
A metabolomic ratio rule-based classification method was developed and programmed for automated metabolite profiling and differentiation of four major cinnamon species using ultra-high-performance liquid chromatography-high-resolution mass spectrometry (UHPLC-HRMS). The computational program identifies key cinnamon metabolites, including proanthocyanidins, cinnamaldehyde, and coumarin, from test samples through LC-MS data processing and assigns cinnamon species by critical metabolite ratios using a stepwise classification strategy. Further, 100% classification accuracy was achieved on the training sample set through critical ratio optimization, and over 95% accuracy was achieved on the validation sample set.
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