Pressurized hot water extraction and chemometric fingerprinting of flavonoids from Bidens pilosa by UPLC-tandem mass spectrometry

Development of the Pipette-Tip Micro-Solid-Phase Extraction for Extraction of Rutin From Moringa oleifera Lam. Using Activated Hollow Carbon Nanospheres as Sorbents

Herein, a micro-solid-phase extraction (μSPE) method was developed using a pipette tip for rutin extraction, employing activated hollow carbon nanospheres (HCNSs) as the sorbent. Characterization of the activated carbon nanospheres through TGA, FTIR, and SEM analysis confirmed the success of the activation process. The study demonstrated the efficacy of PT-μSPE in rutin extraction under pH 2 conditions with a standard concentration of 2 mg·L-1. The optimal mass of HCNSs was found to be 2 mg, and a loading volume of 500 μL resulted in the maximum recovery of rutin. Propan-2-ol was the best elution solvent with 15 aspirating/dispensing cycles. The correlation of determination (R 2) for the calibration curve was found to be 0.9991, and the LOD and LOQ values were 0.604 and 1.830 mg·L-1, respectively. The applicability of the method was demonstrated by extracting rutin from a complex Moringa oleifera leaf extract with the relative standard deviation (RSD) of 3.26%, thereby validating this method as feasible for the extraction of useful bioactive compounds from complex plant samples.

Application of a generative adversarial network for multi-featured fermentation data synthesis and artificial neural network (ANN) modeling of bitter gourd-grape beverage production

Artificial neural networks (ANNs) have in recent times found increasing application in predictive modelling of various food processing operations including fermentation, as they have the ability to learn nonlinear complex relationships in high dimensional datasets, which might otherwise be outside the scope of conventional regression models. Nonetheless, a major limiting factor of ANNs is that they require quite a large amount of training data for better performance. Obtaining such an amount of data from biological processes is usually difficult for many reasons. To resolve this problem, methods are proposed to inflate existing data by artificially synthesizing additional valid data samples. In this paper, we present a generative adversarial network (GAN) able to synthesize an infinite amount of realistic multi-dimensional regression data from limited experimental data (n = 20). Rigorous testing showed that the synthesized data (n = 200) significantly conserved the variances and distribution patterns of the real data. Further, the synthetic data was used to generalize a deep neural network. The model trained on the artificial data showed a lower loss (2.029 ± 0.124) and converged to a solution faster than its counterpart trained on real data (2.1614 ± 0.117).

Prospective Role of Indigenous Leafy Vegetables as Functional Food Ingredients

Indigenous leafy vegetables (ILVs) play a pivotal role in sustaining the lives of many people of low socio-economic status who reside in rural areas of most developing countries. Such ILVs contribute to food security since they withstand harsher weather and soil conditions than their commercial counterparts and supply important nutrients such as dietary fibre, vitamins and minerals. Furthermore, ILVs contain bioactive components such as phenolic compounds, flavonoids, dietary fibre, carotene content and vitamin C that confer health benefits on consumers. Several studies have demonstrated that regular and adequate consumption of vegetables reduces risks of chronic conditions such as diabetes, cancer, metabolic disorders such as obesity in children and adults, as well as cardiovascular disease. However, consumption of ILVs is very low globally as they are associated with unbalanced and poor diets, with being food for the poor and with possibly containing toxic heavy metals. Therefore, this paper reviews the role of ILVs as food security crops, the biodiversity of ILVs, the effects of processing on the bioactivity of ILVs, consumer acceptability of food derived from ILVs, potential toxicity of some ILVs and the potential role ILVs play in the future of eating.

Molecular Spectroscopic (FTIR and UV-Vis) and Hyphenated Chromatographic (UHPLC-qTOF-MS) Analysis and In Vitro Bioactivities of the Momordica balsamina Leaf Extract

Momordica balsamina (M. balsamina) is a medicinal herb comprising health-promoting secondary metabolites. This study was aimed to profile bioactive compounds in the methanolic extract of M. balsamina leaves using molecular spectroscopic (UV-Vis and FTIR) and hyphenated chromatographic (UHPLC-qTOF-MS) techniques and evaluate the biological (in vitro anti-inflammatory and cytotoxicity) activities of the extract. The preliminary phytochemical screening tests revealed the presence of cardiac glycosides, flavonoids, saponins, tannins, and terpenoids. The UV-Vis profile revealed various absorption bands ranging from 200 to 750 nm, indicating the presence of flavonoids, phenolic compounds, tannins, terpenoids, carotenoids, chlorophyll, and alkaloids. FTIR spectra confirmed the presence of alkaloids, flavonoids, terpenes, anthraquinones, and phenolic compounds. A high-resolution and accurate mass spectrometer (LC-QTOF-MS model LC-MS-9030 instrument) was used, and the results confirmed the presence of flavonoid aglycones, such as quercetin, isorhamnetin, and kaempferol, as well as pseudolaroside A and dicaffeoylquinic and feruloyl isocitric acids. To the best of our knowledge, this is the first report of pseudolaroside A dimer and feruloyl isocitric acid in M. balsamina leaves. In vitro cytotoxicity assay showed that the extract was nontoxic against human colorectal adenocarcinoma (HT29 and Caco2), Vero, and RAW 264.7 cells. However, the extract showed anti-inflammatory activity on RAW 264.7 cells. The study confirmed that M. balsamina leaves contain nontoxic secondary metabolites that may play a pivotal role in human health as anti-inflammatory agents.

Proportional coexistence of okanin chalcone glycoside and okanin flavanone glycoside in Bidens pilosa leaves and theoretical investigation on the antioxidant properties of their aglycones

Bidens pilosa plant has been shown to produce okanin flavanone glycoside and its chalcone derivative. In most other plants, due to chalcone isomerase enzyme, the flavanone tends to exist in higher proportions than their chalcone precursors. Herein we have utilized liquid chromatography-mass spectrometry approach and shown that within the leaves of Bidens pilosa plant the two okanin glycosides exist in unusual equal proportional distribution, which indicates that Bidens pilosa plant is an alternative rich source of these highly sought-after antioxidant molecules. The aglycone okanin chalcone (ONC) and okanin flavanone (ONF) have experimentally been shown to exhibit antioxidant activity. However, experimental findings have not conclusively determined which of the two compounds is a more potent antiradical than the other. Herein, the density functional theory (DFT) method is utilized to establish, from structural and thermodynamic energetic considerations, the preferred antioxidant molecule between the two aglycone okanins. A theoretical study on the antioxidant properties of ONC and ONF has been performed by considering their radical scavenging and metal cation (Mⁿ⁺, where M = Cu(II) or Fe (III)) chelation ability. The study has been performed using B3LYP/6-31 + G(d,p) method. In the case of the metal chelation mechanism, the LANL2DZ pseudo-potential was selected to describe the selected Mⁿ⁺ cations. The results of the study suggest that ONC is a better radical scavenger than ONF because of the extended electron delocalization on its neutral radical, which is due to the presence of conjugation within the ONC neutral radical after hydrogen atom abstraction. In the metal chelation mechanism, it is noted that the binding energies depend on the media, the nature of the ligand and the cation and the cation coordination site on the ligand. The charge and the spin density on Mⁿ⁺ decrease on coordination to the ligand. The ability of the ligands to reduce Mⁿ⁺ cations, coupled with the strong Mⁿ⁺ binding properties, has significant implication on the antioxidant ability of both okanins. However, since ONC⋅⋅⋅M⁺ⁿ interaction results in higher binding energy than ONF⋅⋅⋅M⁺ⁿ interaction, the implication is that ONC is a preferred free metal ion chelator than ONF.

Parallel validation of a green-solvent extraction method and quantitative estimation of multi-mycotoxins in staple cereals using LC-MS/MS

In this study, 15 different mycotoxins were estimated in three staple cereals from selected agro-ecological regions in Nigeria using a 'novel' green extraction method, pressurized hot water extraction (PHWE) in comparison to a conventional solvent extraction method. Discrimination of the results of PHWE and solvent extraction using principal component analysis (PCA) and orthogonal projection to latent structures discriminate analysis (OPLS-DA) did not yield any differential clustering patterns. All maize samples (n = 16), 32% (n = 38) of sorghum and 35% (n = 37) of millet samples were positive for at least one of the 15 tested mycotoxins. Contamination levels for the cereals were higher in the warm humid rain forest region and gradually decreased towards the hot and arid region in the north of the country. The results demonstrate the applicability of PHWE as a possible alternative extraction method to conventional methods of extraction, which are solvent based.