Valerian essential oil for treating insomnia via the serotonergic synapse pathway.

Valerian volatile oil can be used in the treatment of insomnia; however, the active components and mechanisms of action are currently unclear. Therefore, we used transcriptome sequencing and weight coefficient network pharmacology to predict the effective components and mechanism of action of valerian volatile oil in an insomnia model induced by intraperitoneal injection of para-Chlorophenylalanine (PCPA) in SD rats. Valerian essential oil was given orally for treatment and the contents of 5-hydroxytryptamine receptor 1 A (5-HT1AR), γ-aminobutyric acid (GABA), cyclic adenosine monophosphate (cAMP), and protein kinase A (PKA) in the hippocampus of rats in each group were detected by enzyme-linked immunosorbent assay (ELISA), western blot, Polymerase Chain Reaction (PCR), and immunohistochemistry. The results showed that after treatment with valerian essential oil, insomnia rats showed significantly prolonged sleep duration and alleviated insomnia-induced tension and anxiety. Regarding the mechanism of action, we believe that caryophyllene in valerian essential oil upregulates the 5-HT1AR receptor to improve the activity or affinity of the central transmitter 5-HT, increase the release of 5-HT, couple 5-HT with a G protein coupled receptor, convert adenosine triphosphate (ATP) into cAMP (catalyzed by ADCY5), and then directly regulate the downstream pathway. Following pathway activation, we propose that the core gene protein kinase PKA activates the serotonergic synapse signal pathway to increase the expression of 5-HT and GABA, thus improving insomnia symptoms and alleviating anxiety. This study provides a theoretical basis for the application of valerian volatile oil in health food.

[Investigation of Paeonia sinjiangensis resources using remote sensing and expert knowledge].

OBJECTIVE: To study the effectiveness and feasibility of remote sensing technology in the rare species of wild plant resources. METHOD: The mechanism and characteristics of Paeonia sinjiangensis were analyzed to find the possibility of extracting from TM imagery. An expert system has been used with Landsat Thematic Mapper data to derive P. sinjiangensis. Then logical decision rules were used with the various datasets to assign values. RESULT: The land for P. sinjiangensis possible growth were mapped and accuracy tested was approving. CONCLUSION: The results suggest that the remote sensing expert interpretation system using satellite imagery and ancillary data will be feasible for research of rare wild medicinal plants distribution.