METHODS: Liquid-liquid partition chromatography was used to separate methanolic extract to get hexane, ethyl acetate, butanol and residual aqueous fractions. The total antioxidant activity was determined by 2,2-diphenyl-1-picrylhydrazy (DPPH) radical scavenging and ferric reducing antioxidant power assay (FRAP). The antidiabetic activity of methanol extract and its consequent fractions were examined by α-glucosidase inhibitory bioassay. The chemical profiling was carried out by gas chromatography coupled with quadrupole time-of-flight mass spectrometry (GC Q-TOF MS).
RESULTS: The total yield for methanol extraction was (12.63 ± 0.98) % (w/w) and highest fractionated value found for residual aqueous (52.25 ± 1.01) % (w/w) as compared to the other fractions. Significant DPPH free radical scavenging activity was found for methanolic extract (63.07 ± 0.11) % and (79.98 ± 0.31) % for ethyl acetate fraction among all the fractions evaluated. Methanol extract was the most prominent in case of FRAP (141.89 ± 0.87 μg AAE/g) whereas most effective reducing power observed in ethyl acetate fraction (133.6 ± 0.2987 μg AAE/g). The results also indicated a substantial α-glucosidase inhibitory activity for butanol fraction (72.16 ± 1.0) % and ethyl acetate fraction (70.76 ± 0.49) %. The statistical analysis revealed that total phenolic and total flavonoid content of the samples had the significant (p
METHODS: Four different solvent extracts of OS, namely aqueous, ethanolic, 50% aqueous ethanolic and methanolic, at a dose of 500 mg/kg body weight (bw) were orally administered for 14 days to diabetic rats induced via intraperitoneal injection of 60 mg/kg bw STZ. NMR metabolomics approach using pattern recognition combined with multivariate statistical analysis was applied in the rat urine to study the resulted metabolic perturbations.
RESULTS: OS aqueous extract (OSAE) caused a reversal of DM comparable to that of 10 mg/kg bw glibenclamide. A total of 15 urinary metabolites, which levels changed significantly upon treatment were identified as the biomarkers of OSAE in diabetes. A systematic metabolic pathways analysis identified that OSAE contributed to the antidiabetic activity mainly through regulating the tricarboxylic acid cycle, glycolysis/gluconeogenesis, lipid and amino acid metabolism.
CONCLUSIONS: The results of this study validated the ethnopharmacological use of OS in diabetes and unveiled the biochemical and metabolic mechanisms involved.
PURPOSE: This study provides new insights on the changes of endogenous metabolites caused by I. aquatica ethanolic extract and improves the understanding on the therapeutic efficacy and mechanism of I. aquatica ethanolic extract.
METHODS: By using a combination of 1H nuclear magnetic resonance (NMR) with multivariate analysis (MVDA), the changes of metabolites due to I. aquatica ethanolic extract administration in obese diabetic-induced Sprague Dawley rats (OB+STZ+IA) were identified.
RESULTS: The results suggested 19 potential biomarkers with variable importance projections (VIP) above 0.5, which include creatine/creatinine, glucose, creatinine, citrate, carnitine, 2-oxoglutarate, succinate, hippurate, leucine, 1-methylnicotinamice (MNA), taurine, 3-hydroxybutyrate (3-HB), tryptophan, lysine, trigonelline, allantoin, formiate, acetoacetate (AcAc) and dimethylamine. From the changes in the metabolites, the affected pathways and aspects of metabolism were identified.
CONCLUSION: I. aquatica ethanolic extract increases metabolite levels such as creatinine/creatine, carnitine, MNA, trigonelline, leucine, lysine, 3-HB and decreases metabolite levels, including glucose and tricarboxylic acid (TCA) intermediates. This implies capabilities of I. aquatica ethanolic extract promoting glycolysis, gut microbiota and nicotinate/nicotinamide metabolism, improving the glomerular filtration rate (GFR) and reducing the β-oxidation rate. However, the administration of I. aquatica ethanolic extract has several drawbacks, such as unimproved changes in amino acid metabolism, especially in reducing branched chain amino acid (BCAA) synthesis pathways and lipid metabolism.
RESULTS: Comparison of the PLS and RF showed that RF exhibited poorer generalization and hence poorer predictive performance. Both the regression coefficient of PLS and the variable importance of RF revealed that quercetin and kaempferol derivatives, caffeic acid and vitexin-2-O-rhamnoside were significant towards the tested bioactivities. Furthermore, principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA) results showed that sonication and absolute ethanol are the preferable extraction method and ethanol ratio, respectively, to produce N. oleracea extracts with high phenolic levels and therefore high DPPH scavenging and α-glucosidase inhibitory activities.
CONCLUSION: Both PLS and RF are useful regression models in metabolomics studies. This work provides insight into the performance of different multivariate data analysis tools and the effects of different extraction conditions on the extraction of desired phenolics from plants. © 2017 Society of Chemical Industry.