Melanoidin-like carbohydrate-containing macromolecules from Shanxi aged vinegar exert immunoenhancing effects on macrophage RAW264.7 cells.

Bioactive macromolecule mining is important for the functional chemome analysis of traditional Chinese vinegar. In this study, we isolated and characterized carbohydrate-containing macromolecules from Shanxi aged vinegar (CCMSAV) and evaluated their immunomodulatory activity. The isolation process involved ethanol precipitation, deproteinization, decolorization, and DEAE-650 M column chromatography, resulting in the acquisition of four sub-fractions. All sub-fractions exhibited a molecular weight range of 6.92 to 16.71 kDa and were composed of 10 types of monosaccharides. Comparative analysis of these sub-fractions with two melanoidins exhibited similarities in elemental composition, spectral signature, and pyrolytic characteristics. Immunological assays confirmed the significantly enhanced cell viability, phagocytic activity, and secretion of nitric oxide, tumor necrosis factor (TNF)-α and interleukin (IL)-6 in RAW264.7 cells by all four sub-fractions. Further investigation of the immunomodulatory mechanism revealed that SAV-RP70-X, the most potent purified sub-fraction, enhanced aerobic glycolysis in macrophages and activated Toll-like receptor 2 (TLR2), TLR4, mannose receptor (MR), scavenger receptor (SR), and the dendritic cell-associated C-type lectin-1 receptor (Dectin-1). Furthermore, the activation of macrophages was associated with the MyD88/PI3K/Akt/NF-κB signaling pathway. Methylation analysis revealed that 1,4-Xylp was the most abundant glycosidic linkage in SAV-RP70-X.

Physicochemical properties, structure, and ameliorative effects of insoluble dietary fiber from tea on slow transit constipation.

Tea residue is a by-product of tea processing and contains âˆ¼ 60 % insoluble dietary fiber. We investigated the physicochemical properties and structure of the insoluble dietary fiber of tea (T-IDF), and its defecation function was evaluated. The physical and chemical indexes of the T-IDF, including its water holding, oil holding, swelling, cation exchange, and cholesterol exchange capacities, were measured, while its structure was analyzed by a range of analytical techniques. Furthermore, the related indexes of the animal defecation function were determined, and the in vitro detection of fermented short chain fatty acid was conducted. We found that T-IDF exhibits excellent physical and chemical properties. Moreover, the consumption of T-IDF significantly promoted defecation in slow transit intestinal dyskinesia mice and enhanced the production of short chain fatty acids. Overall, we demonstrated a good correlation between the physicochemical properties and the structure/function of T-IDF.

Near-infrared spectroscopy and machine learning-based technique to predict quality-related parameters in instant tea.

The traditional method for analyzing the content of instant tea has disadvantages such as complicated operation and being time-consuming. In this study, a method for the rapid determination of instant tea components by near-infrared (NIR) spectroscopy was established and optimized. The NIR spectra of 118 instant tea samples were used to evaluate the modeling and prediction performance of a combination of binary particle swarm optimization (BPSO) with support vector regression (SVR), BPSO with partial least squares (PLS), and SVR and PLS without BPSO. Under optimal conditions, Rp for moisture, caffeine, tea polyphenols, and tea polysaccharides were 0.9678, 0.9757, 0.7569, and 0.8185, respectively. The values of SEP were less than 0.9302, and absolute values of Bias were less than 0.3667. These findings indicate that machine learning can be used to optimize the detection model of instant tea components based on NIR methods to improve prediction accuracy.