RESUMEN
This study analysed the pharmacological mechanism of Gastrodiae Rhizoma, Lycii Fructus, and Ziziphi Spinosae Semen in sedation and tranquillising mind using network pharmacology methods. The findings of this study aimed to serve as a reference for the development of novel drugs and the clinical expansion and application of traditional Chinese medicine formulas. The chemical constituents and therapeutic targets of Gastrodiae Rhizoma, Lycii Fructus, and Ziziphi Spinosae Semen were acquired from TCMSP, HERB, and ETCM databases. Active components were identified using ADME criteria, while the primary targets associated with sedation and mental tranquillity were obtained from GENECARDS, OMIM, and DRUGBANK databases. A protein-protein interaction (PPI) network analysis was conducted using the STRING platform to investigate potential functional protein modules by the network. The METASCAPE platform was employed for the study of the "component-target" and its associated biological processes and pathways. Subsequently, the "component-target" network was constructed using Cytoscape 3.9.1 software. Finally, the validation of molecular docking was conducted through AUTODOCK. The findings revealed that Quercetin, Atropine, Dauricine, (S)-Coclaurine, and other active ingredients were identified as the core constituents of Gastrodiae Rhizoma, Lycii Fructus, and Ziziphi Spinosae Semen. Additionally, PTGS2, PTGS1, MAOB, GABRA1, SLC6A2, ADRB2, CHRM1, HTR2A, and other targets were identified as the core targets. The results of the molecular docking analysis demonstrated that Quercetin, Atropine, Dauricine, and (S)-Coclaurine exhibited binding solid affinity towards PTGS2 and PTGS1. The predominant biological pathways associated with sedation and tranquilisation primarily involved Neuroactive ligand-receptor interaction and activation of receptors involved in chemical carcinogenesis. This study provided initial findings on the multi-component, multi-target, and multi-pathway mechanism underlying the sedative and tranquillising effects of Gastrodiae Rhizoma, Lycii Fructus, and Ziziphi Spinosae Semen. These findings had the potential to serve as a foundation for the future development and utilisation of Gastrodiae Rhizoma, Lycii Fructus, and Ziziphi Spinosae Semen.
RESUMEN
The roots and rhizomes of Glycyrrhiza uralensis Fisch. represent the oldest and most frequently used herbal medicines in Eastern and Western countries. However, the quality of cultivated G. uralensis has not been adequate to meet the market demand, thereby exerting increased pressure on wild G. uralensis populations. Nitrogen, vital for plant growth, potentially influences the bioactive constituents of plants. Yet, more information is needed regarding the effect of different forms of nitrogen on G. uralensis. G. uralensis seedlings were exposed to a modified Hoagland nutrient solution (HNS), varying concentrations of nitrate (KNO3), or ammonium (NH4)2SO4. We subsequently obtained the roots of G. uralensis for physiology, transcriptomics, and metabolomics analyses. Our results indicated that medium-level ammonium nitrogen was more effective in promoting G. uralensis growth compared to nitrate nitrogen. However, low-level nitrate nitrogen distinctly accelerated the accumulation of flavonoid ingredients. Illumina sequencing of cDNA libraries prepared from four groups-treated independently with low/medium NH4 + or NO3 - identified 364, 96, 103, and 64 differentially expressed genes (DEGs) in each group. Our investigation revealed a general molecular and physiological metabolism stimulation under exclusive NH4 + or NO3 - conditions. This included nitrogen absorption and assimilation, glycolysis, Tricarboxylic acid (TCA) cycle, flavonoid, and triterpenoid metabolism. By creating and combining putative biosynthesis networks of nitrogen metabolism, flavonoids, and triterpenoids with related structural DEGs, we observed a positive correlation between the expression trend of DEGs and flavonoid accumulation. Notably, treatments with low-level NH4 + or medium-level NO3 - positively improved primary metabolism, including amino acids, TCA cycle, and glycolysis metabolism. Meanwhile, low-level NH4 + and NO3 - treatment positively regulated secondary metabolism, especially the biosynthesis of flavonoids in G. uralensis. Our study lays the foundation for a comprehensive analysis of molecular responses to varied nitrogen forms in G. uralensis, which should help understand the relationships between responsive genes and subsequent metabolic reactions. Furthermore, our results provide new insights into the fundamental mechanisms underlying the treatment of G. uralensis and other Glycyrrhiza plants with different nitrogen forms.
RESUMEN
Brain functional network has been widely applied to investigate brain function changes among different conditions and proved to be a small-world-like network. But seldom researches explore the effects of mental fatigue on the small-world brain functional network organization. In the present study, 20 healthy individuals were included to do a consecutive mental arithmetic task to induce mental fatigue, and scalp electroencephalogram (EEG) signals were recorded before and after the task. Correlations between all pairs of EEG channels were determined by mutual information (MI). The resulting adjacency matrices were converted into brain functional networks by applying a threshold, and then, the clustering coefficient (C), characteristic path length (L), and corresponding small-world feature were calculated. Through performing analysis of variance (ANOVA) on the mean MI for every EEG rhythm, only the data of α1 rhythm during the task state were emerged for the further explorations of mental fatigue. For a wide range of thresholds, C increased and L and small-world feature decreased with the deepening mental fatigue. The pattern of the small-world characteristic still existed when computed with a constant degree. Our present findings indicated that more functional connectivities were activated at the mental fatigue stage for efficient information transmission and processing, and mental fatigue can be characterized by a reduced small-world network characteristic. Our results provide a new perspective to understand the neural mechanisms of mental fatigue based on complex network theories.