Comparative Study of the Components and Anti-Fatigue Effect of Schisandra chinensis Polysaccharides from China and Russia

Schisandra chinensis Bail. polysaccharides from China (CSP) and Russia (RSP) were separated by DEAE-52 cellulose column chromatography. The content of neutral polysaccharide was determined by the phenol concentrated sulfuric acid method, the content of acid polysaccharide by the hydroxybiphenyl method, and the monosaccharide composition and molecular weight arrangement of CSP and RSP by 1-phenyl-3-methyl-5-pyrazolone (PMP) pre-column derivatization HPLC. The effects of CSP and RSP on the exercise endurance of mice were compared by the forelimb grip strength test, rota-rod test and weight-bearing swimming. The results showed that one neutral polysaccharide and three acidic polysaccharides could be eluted from a DEAE-52 cellulose column from CSP and RSP, respectively. The content of acidic and neutral polysaccharides in RSP was higher than that in CSP, and the anti-fatigue effect of RSP was more significant than that of CSP.

Multidimensional exploration of essential oils generated via eight oregano cultivars: Compositions, chemodiversities, and antibacterial capacities

Numerous species of Origanum (Lamiaceae) have been widely used as spices to extend the shelf life of foods. Essential oils extracted from this genus have attracted much attention owing to their potential applications as bactericides. Here, we evaluated the chemical compositions of eight oregano essential oils (OEOs) using gas chromatography-mass spectrometry and assessed their antibacterial activities. The chemical compositions of OEOs were affected by the cultivar factor, and seven common compounds, including carvacrol, were identified among eight OEOs. Partial least squares discriminant analysis enabled the distinction of three groups among these OEOs, as characterized by the proportions of carvacrol, thymol, and sesquiterpenes. OEOs effectively inhibited Escherichia coli and Staphylococcus aureus with varying antibacterial activities. Spearman correlation network highlighted core antibacterial contributors in the chemical profiles of OEOs. Our results revealed that the bacteriostatic effects of OEOs could be explained by core compounds and their synergistic effects.

Employing fingerprinting of medicinal plants by means of LC-MS and machine learning for species identification task

A dataset of liquid chromatography-mass spectrometry measurements of medicinal plant extracts from 74 species was generated and used for training and validating plant species identification algorithms. Various strategies for data handling and feature space extraction were tested. Constrained Tucker decomposition, large-scale (more than 1500 variables) discrete Bayesian Networks and autoencoder based dimensionality reduction coupled with continuous Bayes classifier and logistic regression were optimized to achieve the best accuracy. Even with elimination of all retention time values accuracies of up to 96% and 92% were achieved on validation set for plant species and plant organ identification respectively. Benefits and drawbacks of used algortihms were discussed. Preliminary test showed that developed approaches exhibit tolerance to changes in data created by using different extraction methods and/or equipment. Dataset with more than 2200 chromatograms was published in an open repository.