Study on the mechanism of Gastrodiae Rhizoma, Lycii Fructus, and Ziziphi Spinosae Semen in sedation and tranquillising mind.

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.

Sensitivity analysis and estimation using a hierarchical Bayesian method for the parameters of the FvCB biochemical photosynthetic model.

Photosynthesis is a major process included in land surface models. Accurately estimating the parameters of the photosynthetic sub-models can greatly improve the ability of these models to accurately simulate the carbon cycle of terrestrial ecosystems. Here, we used a hierarchical Bayesian approach to fit the Farquhar-von Caemmerer-Berry model, which is based on the biochemistry of photosynthesis using 236 curves for the relationship between net CO2 assimilation and changes in the intercellular CO2 concentration. An advantage of the hierarchical Bayesian algorithm is that parameters can be estimated at multiple levels (plant, species, plant functional type, and population level) simultaneously. The parameters of the hierarchical strategy were based on the results of a sensitivity analysis. The Michaelis-Menten constant (Kc25), enthalpies of activation (EJ and EV), and two optical parameters (θ and α) demonstrated considerable variation at different levels, which suggests that this variation cannot be ignored. The maximum electron transport rate (Jmax25), maximum rate of Rubisco activity (Vcmax25), and dark respiration in the light (Rd25) were higher for broad-leaved plants than for needle-leaved plants. Comparison of the model's simulated outputs with observed data showed strong and significant positive correlations, particularly when the model was parameterized at the plant level. In summary, our study is the first effort to combine sensitivity analysis and hierarchical Bayesian parameter estimation. The resulting realistic parameter distributions for the four levels provide a reference for current and future land surface models. Furthermore, the observed variation in the parameters will require attention when using photosynthetic parameters in future models.

Integrated transcriptomic and metabolomic analysis reveals the regulation mechanism of early bolting and flowering in two cultivars of Angelica sinensis.

The root of Angelica sinensis is utilized in Traditional Chinese medicine to enhance blood replenishment and facilitate blood circulation. The early bolting and flowering (EBF) of A. sinensis, however, compromises the quality of the roots and restricts the yield of medicinal substances. The study was conducted to compare the transcriptomic and metabolomic profiles between EBF plants and normal plants of two cultivars of A. sinensis, followed by validation of the transcriptome results using qRT-PCR. There were 3677 DEGs in EBF plants compared to normal plants of cultivar 2 (Mingui No.2), and cultivar 4 (Mingui No.4) was 3354. The main differential metabolites in the EBF and normal plants were phenolic acids, flavonoids, lignans, and coumarins. The analysis of 5 EBF-related pathways revealed 28 genes exhibiting differential expression and 5 metabolites showing differential accumulation. The expression of the Lhcb5, Lhcb2, Lhcb6, Lhcb1, Lhca4, ATPG1, EGLC, CELB, AMY, glgA, CYCD3, SnRK2, PYL, AHK2, AUX1, BSK, FabI/K, ACACA and FabV decreased and the expression of the PsbR, PsbA, LHY, FT, CO, malQ, HK, GPI and DELLA increased in EBF plants. In addition, the Abscisic acid, d-Glucose-6P, α-d-Glucose-1P, NADP+, and ADP were more significantly enriched in EBF plants. The findings offer novel perspectives on the EBF mechanisms in A. sinensis and other medicinal plants of the Apiaceae family.

Identification of three cultivated varieties of Scutellaria baicalensis using the complete chloroplast genome as a super-barcode.

Scutellaria baicalensis has been one of the most commonly used traditional Chinese medicinal plants in China for more than 2000 years. The three new varieties cultivated could not be distinguished by morphology before flowering. It will hinder the promotion of later varieties. Chloroplast DNA has been widely used in species identification. Moreover, previous studies have shown that complete chloroplast genome sequences have been suggested as super barcodes for identifying plants. Therefore, we sequenced and annotated the complete chloroplast genomes of three cultivated varieties. The chloroplast genomes of SBW, SBR, and SBP were 151,702 bp, 151,799 bp, and 151,876 bp, which contained 85 protein-coding genes, 36 tRNA genes, and 8 rRNA genes. The analysis of the repeat sequences, codon usage, and comparison of chloroplast genomes shared a high degree of conservation. However, the sliding window results show significant differences among the three cultivated varieties in matK-rps16 and petA-psbJ. And we found that the matK-rps16 sequence can be used as a barcode for the identification of three varieties. In addition, the complete chloroplast genome contains more variations and can be used as a super-barcode to identify these three cultivated varieties. Based on the protein-coding genes, the phylogenetic tree demonstrated that SBP was more closely related to SBW, in the three cultivated varieties. Interestingly, we found that S. baicalensis and S. rehderiana are closely related, which provides new ideas for the development of S. baicalensis. The divergence time analysis showed that the three cultivated varieties diverged at about 0.10 Mya. Overall, this study showed that the complete chloroplast genome could be used as a super-barcode to identify three cultivated varieties of S. baicalensis and provide biological information, and it also contributes to bioprospecting.

Transcriptomics and metabolomics reveal the primary and secondary metabolism changes in Glycyrrhiza uralensis with different forms of nitrogen utilization.

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.